United States Information July 1983
Environmental Protection Clearinghouse
Agency (PM 211A)
Washington DC 20460
Office of Administrations
Office of Management Information & Support Services
FPA ENVIRONMENTAL
DATA BASE AND
MODEL DIRECTORY
Volume 2 of 2
Part 2 of 2 (Page's 811 through 1625)
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Accession Mo. 6408000201 (cont)
R.I.
(ROR) Responsible Organization: Office of Research and
Development.Office of Environaental Processes and Effects Rese
811
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Accession Ho. 6408000202
(DQ) Date of Questionaire: 12-02-82
(HAH) Name of Data Base of Model: Coastal Environmental Assessment
Studies
(ACR) Ac Tonya of Data Base or Model: CEAS
(MED) Media/Subject of Data Base or Model: Sediment ;Surface
vater-estuarlne/marine ;Tissue Mercenaria mercenaria, Mytllus
Pseudopleuronectes aaericanus
(ABS) Abstract/Overview of Data Base or Model: This data base contains
tissue residue analyses for several species including Mytilus
edulis, Mercenaria aercenarla and Pseudopleuronectes americanus
from both indigenous and transplanted populations exposed to
varying degrees of pollution in coastal and estuarine areas of the
United States. Saaple frequency varies. Pollutants measured
include metals, synthetic organ!cs, and petroleum hydrocarbons*
Biological effects are also addressed through histopathological
examination plus a number of physiological parameters, prin-
cipally Scope for Growth.
(CTC) CORTACTS: Subject aatter Donald K. PheIPS, Environmental
Scientist ; Computer-related Robert Payne, ADP Coordinator
(401) ; EPA Office Robert Barles, Exploratory Research
(DTP) Type of data collection or monitoring: Coabination/Other data
collection - aabient and non-point source, sludge and dredge
spoil dumping
(STA) Data Base status: Operational/ongoing
(HPP) Hon-pollutant paraaeters included in the data base: Biological
data ^Collection method ^Concentration measures ;Exposure data ;
Location j Physical data ;Salinity ^Sampling data ^Temperature /
Shell measurements ^Organism Heights ;Sex
(DS) Time period covered by data base: 01-01-70 TO 04-30-81
(TRM) Termination of data collection: Hot anticipated
(PRO) Frequency of data collection or sampling: weekly ^monthly ;as
needed
(HOB) Number of observations in data base: 1200(Bstimated)
(RED Estimated annual increase of observations in data base: 200
(IMF) Data base includes: Ran data/observations
(ITS) Total number of stations or sources covered in data base: 15
(MCS) Ho. stations or sources currently originating/contributing data:
5
(HOP) Huaber of facilities covered In data base (source monitoring): 0
(6EO) Geographic coverage of data base: Rational selected areas
(LOC) Data elements Identifying location of station or source include:
State ;City ^Coordinates - latitude/longitude
(FAC) Data elements identifying facility include: H/A
(CDE) Pollutant Identification data are: Ohcoded
(LIN) Limitation/variation in data of Hhich user should be ay are: The
CEAS is a research data base and entries are subject to revision.
(DPR) Data collect./anal, procedures conform to QRD guidelines: Samplin
g plan documented jCollection method documented ;Analysis method
document QA procedures documented
(AML) Lab analysis based on EPA-approved or accepted methods? TES
(ADO) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates are not available.
812
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Accession No. 6408000202 (cont)
(EOT) Editting: No known edit procedures exist.
(CBY) Data collected by: EPA lab-ERL, Narragansett, R.I.
(ABY) Data analyzed by: EPA lab-ERL, Narragansett, R.I.
Other federal agency-NOAA/NMFS, Milford
CIDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Anticipatory/research
(AUT) Authorization for data collection: Bo statutory requirement:
Data collection requirement is for research purposes*
(OMB) Data col lee ted/sub* it ted using OMB-approved EPA reporting foras:
QQ
(REP) Form of available reports and outputs of data base: Publications
- Phelps, O.K. and tf.B. Gallouay. 1979. The Use of Introduced
Species (Mytilus edulis) as a Biological Indicator of Trace
Metal Contamination in an Estuary. In: Advances in Marine
Environmental Research. OSEPA 600/9-79-035:26-37. Hlddows, J.L.,
O.K. Phelps and V.B. Galloway. 1981. Measure- ment of
Physiological Condition of Mussels Along a Pollution Gradient
in Narragansett Bay. Marine Environmental Research. 4:181-194.
Phelps, O.K. and M.B. Galloway. 1980. A Report on the Coastal
Environmental Assessment Station (CEAS) Program. Rapp. P.-v.
Reun. Cons. Int. Explor. Mer., 179:76-81. Phelps, O.K., M.B.
Galloway, P.P. Thurberg, E. Gould, M.A. Dauson. 1981. Comparison
of Several Physiological Monitoring Techniques as Applied to Blue
Mussel Mytilus edulis. Along a Gradient of Pollutant Stress in
Marragansett Bay, Rhode Island. In: Biological Monitoring of
Marine Pollutants. F.J. fernberg, A. Calabrese, P.P. Thurberg,
V.B. ?ernberg, eds., Academic Press, 335-355. Myers, Allen C. 1979.
Summer and Winter Burrows of a Mantis Shrimp, Squilla empusa, in
Harragansett Bay, Rhode Island (OSA). Estuarine and Coastal
Marine Science, fol. 8, 87-98. Phelps, D.K. and A.C. Myers.
1977. Ecological considerations in site assessment for
dredging and spoiling activities. In: Proceedings of the second
U.S./Japan meeting on management of bottom sediments containing
toxic substances, October, 1976. EPA Ecological Research
Series, EPA 600-3-77-083. Phelps, O.K., Telek, G., and R.L.
Lapan, Jr. 1975. Assessment of heavy metal distribution within
the food web. In: Marine Pollution and Marine Haste Disposal,
pp. 341-348. Ed. by E.A. Pearson and E.D. Frangipane. Pergamon
Press, Oxford and Rew York. Bayne, B.L., Moore, M.H., Hiddows,
J., Livingstone, D.R. and Salkeld, P.M. 1979. Measurement of
the responses of individuals to environmental stress and pollution.
Phil. Trans. R. Soc. Ser. B. 286, 563-81.
Unpublished reports - unknown at this time
(ROS) Number of regular users of data base: 1
(OSR) Current regular users of data base: EPA laboratories
(CMF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Magnetic disc ;0rigioal form (hardcopy,
readings) ...... .«.
(DAC) Type of data access: Manually jEPA software: DATUM jEPA
hardware DEC 11/70
813
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Accession No. 6408000202 (coot)
(CHG) Direct charge for non-EPA use: Ho
(OPDT) Frequency of data base master file up-date: Other as necessary
(CMP) Completion of fora:
Halter Gallouay
OFC: EPA/ERL-Karragansett
AD: South Ferry Road, Narragansett, R.I. 02882
PH: (401) 789-1071
(OF) Date of form completion: 09-21-81
(WHAT) Number of substances represented in data base: 28
(NCAS) Number of CAS registry numbers in data base: 25
(MAT) Substances represented in data base:
PCB-1254 (Arochlorl254) dibenzota,h:ianthracene<53-70-3>
<11097-69-l> dissolved oxygen
aluninua<7429-90-5> fluoranthene<206-44-0>
aMonia<7664-41-7> hydrocarbons
anthracene<120-12-7> iron<7439-89-6>
benzo(a)anthracene<56-55-3> lead<7439-92-l>
benzo(g,h,l)perylene<191-24-2> n-alkanes (clO-c30)
be nzo(k)fluoranthene<207-08-9> nickel<7440-02-0>
ben2oCalpyrene<50-32-8> phenanthrene<85-01-8>
cadmlum<7440-43-9> polychlorlnated blphenyls (PCBs)
chlordane<57-74-9> <1336-36-3>
chro«iu»<7440-47-3> pyrene<129-00-0>
chrysene<218-01-9> silver<7440-22-4>
copper<7440-50-8> vanadiuX7440-62-2>
ddt<50-29-3> zinc<7440-66-6>
(CAS) CAS registry numbers of substances Included in data base: 11097-6
9-1; 7429-90-5; 7664-41-7; 120-12-7; 56-55-3; 191-24-2; 207-08-9;
50-32-8; 7440-43-9; 57-74-9; 7440-47-3; 218-01-9; 7440-50-8;
50-29-3; 53-70-3; 206-44-0; 7439-89-6; 7439-92-1; 7440-02-0;
85-01-8; 1336-36-3; 129-00-0; 7440-22-4; 7440-62-2; 7440-66-6
(CNN) Contact name(s): Galloway,H. ; Payne,R.
(COR) contact organization: Robert Barles, Exploratory Research
(ROR) Responsible Organization: Office of Research and
Development.Offlee of Environmental Processes and Effects Rese
814
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Accession Mo. 6409000106
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Environmental (Nicrobial
Populations)
(ACR) Acronyn of Data Base or Model: lone
(MED) Media/Subject of Data Base or Model: Surface uater estuarine
(ABS) Abstract/Overview of Data Base or Model: Samples of inshore
surface films were collected using a membrane adsorption
technique. These samples were analyzed for bacterial
populations which Here typically 10-100 times greater than those
in underlying Haters of 10 centimeters.
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Accession Ho. 6409000106 (cont)
Proceedings of International Biodegradation Symposium, 1976
(MUS) Number of regular users of data base: Ho longer used
CCIF) Confidentiality of data and Halts on access: Ho Halts on
access to data
(OLC) Primary physical location of data: published
(DST) Fora of data storage: none
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
fCMP) Completion of form:
Al fiourquln
OFC: EPA/(ORD)/(OEPER)/(ERL-GB)
AD: Sabine Island Gulf Breeze/ FL
PR: (904)932-5311
(DP) Date of fora completion: 12-14-82
(CUM) contact name(s): BOUTguIn,A.
(COR) Contact organization: Environmental Research Lab-Gulf Breeze
(ROR) Responsible Organization: Office of Research and
Development.Offlee of Environmental Processes and Effects Rese
816
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Accession Mo. 6409000107
CDQ) Date of Questionaire: 12-02-82
(NAM) Have of Data Base of Model: River Pollution by
Anticholinesterase Agents
Site
description ; Test/analysis Method
(OS) Ti«e period covered by data base: 07-01-72 TO 10-30-72
(TRM) Termination of data collection: Occurred 10/30/72
(FRQ) Frequency of data collection or saMpling: one tine only
(NOB) NuMber of observations in data base: 2.(Actual)
(NEI) Estimated annual increase of observations in data base: 0.
(INF) Data base includes: SuMMary aggregate observations
(NTS) Total nuMber of stations or sources covered in data base: 5.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) NuMber of facilities covered in data base (source Monitoring): 1
(GEO) Geographic coverage of data base: Geographic region Missouri and
Kansas Rivers
(LOC) Data elements identifying location of station or source include:
State jCity
(FAC) Data elements identifying facility include: Plant location
(CDE) Pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Four
pesticides Measured in effluent at Kansas City, MO. 5 stations
Monitored for fish poisoning on Kansas and Missouri Rivers in
1972 (July and October).
(DPR) Data collect./anal, procedures conform to ORO guidelines:
g plan documented ^Collection Method documented ^Analysis Method
document QA procedures documented
(AMD Lab analysis based on EPA-approved or accepted Methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base.
817
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Accession No. 6409000107 (cont)
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: EPA lab Environnental Research Lab-Gulf
Breeze
(ABY) Data analyzed by: EPA lab Environmental Research Lab-Gulf Breeze
(IDL) Laboratory identification: TES
(PR1) Primary purpose of data collection: Compliance or enforcement
(A0T) Authorization for data collection: Statutory authorization is P
L 92-500 as amended (Clean Hater Act-CWA) Statutory authorization
is P L 92-516 as amended (Federal Insecticide, Fungicide and
Rodentlcide Act-FlFRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Publications
Coppage, D.L. and T.E*. Braldech "River Pollution by
Antlcholinesterase Agents." Hater Research (1976) vol. 10, pp.
19-24.
(HOS) Humber of regular users of data base: 1 office
(OSR) Current regular users of data base: EPA laboratories
(CNF) Confidentiality of data and limits on access: No Halts on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other single
study-only one time data collection
(CMP) Completion of form:
David L. Coppage
OFC: EPA/(OPTS)/(OPP)/(HED)
AD: 401 M St S.tf. Washington, DC 20460
PH: (703) 557-0576
(DF) Date of fora completion: 12-14-82
(NMAT) Number of substances represented in data base: 4
(NCAS) Number of CAS registry numbers In data base: 4
(MAT) Substances represented in data base:
disulfoton<298-04-4> guthion<86-50-0>
fensulfothion<115-90-2> propoxur
(CAS) CAS registry numbers of substances included in data base:
41 115-90-2; 86-50-0; 114-26-1
(CNM) Contact name(s): Coppage,D. ....._.*. or
(COR) Contact organization: Environmental Research Lab-Gulf Breeze, FL
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects Rese
818
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Accession No. 6502000104
(DQ) Date of Questionaire: 12-02-82
(RAM) Name of Data Base of Model: Epidemiology studies (including
"CHESS")
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Air ;0ther health status
questionnaires regarding physiologic measures
(ABS) Abstract/Overview of Data Base or Model: The data base includes
questionnaire responses from population surveys of health
status, such as: acute respiratory disease incidence, chronic
respiratory disease prevalence, and asthma attack frequency?
physiologic monitoring, such as ventilatory function; personal
information on demographic, socio-economic characteristics; and
aabient air quality data.
(CTC) CONTACTS: Subject matter WillIan Nelson (919)541-2330 ;
Computer-related Gerald
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Discontinued
(GRP) Groups of substances represented in Data Base: 7 criteria NAAQS
(NPP) Non-pollutant parameters included in the data base: Concentration
measures ;Exposure data ;Health effects ^Population demographics ;
Temperature
(DS) Time period covered by data base: 09-01-70 TO 06-30-79
(TRM) Termination of data collection: Occurred 06/30/79
(FRQ) Frequency of data collection or sampling: Other Variable from
less than hourly to as needed (but not ongoing)
(NOB) Number of observations in data base: 4000000-(Estimated)
(NEI) Estimated annual Increase of observations in data base: 0.
(INF) Data base includes: Raw data/observations ^Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 40
((approximately).)
(RCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: County/smaller location
approximately 40 separate cities or neighborhoods.
(LOO Data elements identifying location of station or source include:
State jCounty >City ;Town/township ;Street address ^Coordinates OTM
> Project Identifier
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Saroad parameter
(LIH) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal. procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented ;Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base. Edit variable by individual study.
(CBY) Data collected by: EPA lab Health Effects Research Lab-Research
Triangle Park >Contractor several c
(ABY) Data analyzed by: EPA lab Health Effects Research Lab-Research
Triangle Park
819
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Accession lo. 6502000104 (cent)
Contractor lab several contractor labs
sulfur dioxlde<7446-09-5>
ozone<10028-15-6> total suspended participates
(CAS) CAS registry nuabers of substances included in data base: 10102-4
4-0; 10028-15-6; 7446-09-5
(CHM) Contact naae(s): Nelson,*. ; II eh Is, G. ; Cortesi,R.
(ROR) Responsible Organization: Office of Research and
Development.Offlee of Health Research.Health Effects Search La
820
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Accession No. 6502000105
(DQ) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: Clinical Laboratory for Evaluation
and Analysis of Noxious Substances/Clinical Research
CACR) Acronya of Data Base or Model: CLEANS/CLEVER
(MED) Media/Subject of Data Base or Model: Air ;Blood ^Tissue nasal
washings ;Other physiological perfornance
(ABS) Abstract/overview of Data Base or Model: The data base includes
test subject physical and medical status/ environmental exposure
measurement and control data, environmental facility operational
status, physiologic function measurements/ results of
biochemical and immunological blood analyses, instrument
calibration data, and quality assurance audit results.
(CTC) CONTACTS: Subject matter Walter L. Crider (919) 541-2872;
Computer-related Walter
(DTP) Type of data collection or monitoring: Combination/Other
exposure atmospheres
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 7 criteria NAAQS
;3 HID CAA
(NPP) Non-pollutant parameters included in the data bases Biological
data ;chemical data ^collection method ;Concentration measures ;
Exposure data ;Flou rates ;Health effects ;Physical data ;Sampling
date ; Temperature ;Yolume/mass measures ;physiologic performance
(DS) Time period covered by data base: 03-01-77 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: less than hourly 2
minute intervals
(NOB) Number of observations in data base: 70000000.(Estimated)
(NEI) Estimated annual increase of observations in data base: 30000000.
(INF) Data base includes: Ran data/observations ;Summary aggregate
observations ;measurement data
(NTS) Total number of stations or sources covered in data base: 2.
(NCS) No. stations or sources currently originating/contributing data:
2.
(NOF) Number of facilities covered in data base (source monitoring): 1.
(LOC) Data elements identifying location of station or source include:
N/A
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORO guidelines: ORD
Guidelines
(AND Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base.
(EDT) Edittlng: Edit procedures used and documented.
(CBY) Data collected by: EPA lab Health Effects Research Laboratory -
RTF ;Contractor lab Rockwell
(ABY) Data analyzed by: EPA lab Health Effects Research Laboratory -
RTF
Contractor lab Rockwell
821
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Accession Mo. 6502000105 (cont)
(IDL) Laboratory Identification: NO
(AOT) Authorization for data collection: Statutory authorization is P
L 86-206 as amended (Clean Air Act - CAA)
(OMB) Data collected/submitted using OMB-approved EPA reporting foras:
QQ
(REP) Fora of available reports and outputs of data base: Publications
Effects of Air Pollutants on Huaan Cardlopulaonary Function
Machine-readable raw data
On-line computer
(NDS) Nuaber of regular users of data base: 1 office
(OSR) Current regular users of data base: EPA laboratories
(CNF) Confidentiality of data and liaits on access: Limits on access
Hithin EPA and outside agency for soae data
(DLC) Priaary physical location of data: Contractor
(OST) Fora of data storage: Magnetic tape
(DAC) Type of data access: EPA software set of individual prograas
with no systea naae j EPA hardware DEC PDP-11/40
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base aaster file up-date: Meekly
(CMP) Coapletion of fora:
Robert E. Lee
OFC: EPA/(ORD)/(OHR)/(HERL-RTP)
AD: Research Triangle Park, MC 27711
PH: (919) 541-2283
(DP) Date of fora completion: 01-25-83
(RMAT) Muaber of substances represented in data base: 6
(RCAS) Huaber of CAS registry nuabers in data base: 4
(MAT) Substances represented in data base:
acid alst ozone<10028-15-6>
carbon aonoxlde<630-08-0> sulfur dioxide<7446-09-5>
nitrogen dioxide<10102-44-0> total suspended particulates
(CAS) CAS registry nuabers of substances included in data base: 630-08-
0} 10102-44-0; 10028-15-6; 7446-09-5
(CMM) Contact naae(s): Crider,H.L. ; Crider,U.L. ;
Cortesi,R.
(ROR) Responsible Organization: Office of Research and
Developaent.Office of Health Research.Health Effects Search La
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Accession No. 6502000106
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Mortality Data Base
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Other No Specific
Media-death records from National Center for Health Statistics
(ABS) Abstract/Overview of Data Base or Model: The data base includes
all U.S. cancer deaths for the years 1950-1961 and all deaths for
the years 1962-1978.
(CTC) CONTACTS: Subject matter Wilson B. Riggan (919) 541-2674?
Computer-related John V
(DTP) Type of data collection or monitoring: Combination/Other cancer
related death records
(STA) Data Base status: Discontinued
(NPP) Non-pollutant parameters included in the data base: Political
subdivisions ^Population demographics ;Health Effects: Death
records
(DS) Time period covered by data base: 01-01-50 TO 12-31-78
(TRM) Termination of data collection: Occurred 12/31/78
(FRQ) Frequency of data collection or sampling: Other annual death
records
(NOB) Number of observations in data base: 35000000.(Estimated)
(NEI) Estimated annual increase of observations in data base: (N/A.)
(INF) Data base includes: Summary aggregate observations
(NTS) Total number of stations or sources covered in data base: 0.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
State ;County
(FAC) Data elements identifying facility include: N/A
(CDC) Pollutant identification data are: Other coding scheme
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: QA
procedures documented
(AUD) Lab Audit: Data not based on lab analysis.
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Other federal agency U.S. National Center for
Health Statistics
(ABY) Data analyzed by: Other federal agency U.S. National Center for
Health Statistics
(PR1) Primary purpose of data collection: Special study
(AUT) Authorization for data collection: No statutory requirement:
Data collection requirement Is used to support Health Effects
Research Laboratory research.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Publications
several publications
Machine-readable raw data
(NUS) Number of regular users of data base: 2 offices
(USR) Current regular users of data base: EPA laboratories
823
-------
Accession Ho. 6502000106 (cont)
university
(CIV) Confidentiality of data and limits on access: No Halts on
access to data
(DLC) Primary physical location of data: NCC/UHIVAC
(DST) Form of data storage: Magnetic tape
(DAC) Type of data access: EPA software Mortality Studies Support
MIDS:6502200106 ;individual computer tap
(CHG) Direct charge for non-EPA use: Bo
(UPDT) Frequency of data base master file up-date: Other data base no
longer being updated
(CMP) Completion of fora:
William Kelson
OFC: EPA/(ORD)/(OHR)/(HERL-RTP)
AD: Research Triangle Park MC 27711
PH: (919) 541-2330
(DF) Date of fora completion: 01-25-83
(CNM) Contact name(s): Riggan,U.B. / Van Bruggen,J.
(RQR) Responsible Organization: Office of Research and
Development.Offlee of Health Research.Health Effects Search La
824
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Accession Mo. 6502000108
(DQ) Date of Questionaire: 12-02-82
(HAN) Kane of Data Base of Model: Population at Risk
(ACR) Acronym of Data Base or Model: POPATRISK
(MED) Media/Subject of Data Base or Model: Air ;Other climatology
;Other death records census population records } Ho specific
•edia
(ABS) Abstract/Overview of Data Base or Model: County level national
data base containing air quality, death rate, climatology,
socio-economic/ demographic, and Migration information. Air
quality includes 1974 Beans, • ax in a, and minima for 5 criteria
pollutants: total suspended particulates (TSP), sulfur dioxide
(S0<2», nitrogen dioxide (N0<2», carbon monoxide (CO), and
ozone. Death records include 1969-71 age adjusted death rates
for 50 International Classification of Diseases-Adapted
categories by race and sex.
(CTC) CONTACTS: Subject natter William Nelson (919) 541-2330 ;
Computer-related Jerome
(DTP) Type of data collection or nonitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(GRP) Croups of substances represented in Data Base: 7 criteria NAAQS
(NPP) Non-pollutant parameters included in the data base: Concentration
neasures ^Elevation ;Health effects ;Political subdivisions ;
Population denographics ^Population density ^Precipitation ;Site
description ; Tenperature jin-out county migration ;family incone
;alcohol sales
(DS) Tine period covered by data base: 01-01-69 TO 12-30-74
(TRM) Termination of data collection: Occurred 12/30/74
(FRQ) Frequency of data collection or sampling: Other includes SAROAD
(Storage and Retrieval of Air Quality Data) 1974 air quality data
base.
(NOB) Sunber of observations in data base: 10000000.(Estimated)
(NEI) Estimated annual increase of observations in data base: 0.
(INF) Data base includes: Ray data/observations ^Summary aggregate
observations ^Reference data/citations
(NTS) Total number of stations or sources covered in data base: 6000.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NQF) Nunber of facilities covered in data base (source monitoring): 60
00.
(GEO) Geographic coverage of data base: National
(LOC) Data elenents identifying location of station or source include:
State ;County
(FAC) Data elenents identifying facility include: N/A
(CDE) Pollutant identification data are: Saroad parameter
(LIM) Limitation/variation in data of which user should be aware: None
(ANL) Lab analysis based on EPA-approved or accepted nethods? YES
(PRE) Precision: Precision and accuracy estinates are not available
(EOT) Fditting: Edit procedures used but undocumented.
(CBY) Data collected by: Contractor Systen Sciences, Inc. ;Other
federal agency U.S. Census Bureau, Natio Health Statistics,
National Oceanographic and Atmospheric Administration ; EPA
headquarters Office of Air Quality Planning and Standards.
825
-------
Accession to* 6502000108 (cent)
(ABY) Data analyzed by: EPA headquarters Office of Air Quality
Planning and Standards
CIDL) Laboratory identification: 10
(PR1) Primary purpose of data collection: Anticipatory/research
(AUT) Authorization for data collection: Ho statutory requirement:
Data collection requirement is to support air quality health
effects research.
COMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data bases Publications
Population at Risk to various Air Pollution Exposures: Data
Base -POPATRISK* (EPA 600/1-78-051) also in National Technical
Information Service
Machine-readable ran data
CMOS) Number of regular users of data base: 5 offices
(OSR) Current regular users of data base: EPA headquarter offices
Office of Research and Development
EPA laboratories
Other federal agencies
(CNF) Confidentiality of data and limits on access: Ho limits on
access to data
(DLC) Primary physical location of data: HCC/ONIYAC
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: Commercial software System 2000 ;EPA
hardware UNIVAC 1100
CCHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other data base no
longer updated
(CMP) Completion of form:
Hilliam Nelson
OFC: EPA/(ORD)/(OHR)/(H£RL-RTP)/(BD)
AD: Research Triangle Park/ RC 27711
PH: 919-541-2330
(DF) Date of form completion: 01-25-83
(HMAT) Number of substances represented in data bases 5
(HCAS) Number of CAS registry numbers in data base: 4
(MAT) Substances represented in data base:
carbon monoxide<630-08-0> sulfur dioxlde<7446-09-5>
nitrogen dioxlde<10102-44-0> total suspended particulates
ozone<10028-15-6>
(CAS) CAS registry numbers of substances Included in data base: 630-08-
0; 10102-44-0; 10028-15-6; 7446-09-5
(CHM) Contact name(s)s Helson/H. ; Getding,J.
(COR) Contact organization: Health Effects Research Lab-Research
Triangle Park
(ROR) Responsible Organization: Office of Research and
Development.Office of Health Research.Health Effects Search La
826
-------
Accession No. 6502000109
(DQ) Date of Questionaire: 12-02-82
(RAH) Dane of Data Base of Model: Genetic Toxicology Information
System
(ACR) Acronym of Data Base or Model: GTDMIS
(MED) Media/Subject of Data Base or Model: Air ;Mobile source
emissions ;0ther complex chemical bioassays ; Other Hot related to
specific media: pure chemicals also tested
(ABS) Abstract/Overview of Data Base or Model: This data base is
designed to store data from genetic toxicology bioassays of
pollutants including complex mixtures and pure chenicals. The
data will include results fro» Genetic Toxicology Divisions
(GTD) research and GTD contractor bioassays. In addition,
results of biological tests reported in the literature will be
included on some chemicals. Pollutant parameters have not, as
yet, been defined for inclusion in the data base.
(CTC) COHTACTS: Subject matter Barry Houard (919) 541-4689 ;
Computer-related Carol
(DTP) Type of data collection or monitoring: Combination/Other
laboratory observations
(STA) Data Base status: Funded for development
(DPO) Projected operational date of Data Base: 01-00-82
(NPP) Bon-pollutant parameters included in the data base: Biological
data
(DS) Time period covered by data base: 01-00-80
(TRM) Termination of data collection: Mot anticipated
(FRQ) Frequency of data collection or sampling: as needed
(MOB) Number of observations in data base: M/A.(Estimated)
(MEI) Estimated annual increase of observations in data base: 300.
(INF) Data base includes: Raw data/observations *Summary aggregate
observations ^Reference data/citations
(NTS) Total number of stations or sources covered in data base: (N/A.)
(MCS) Mo. stations or sources currently originating/contributing data:
(MOF) Number of facilities covered in data base (source monitoring): (N
(LOC) *Data elements identifying location of station or source include:
N/A
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: CAS registry number
(LIM) Limitation/variation in data of which user should be auare: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: Analysi
s method documented ;QA procedures documented
(AML) Lab analysis based on EPA-approved or accepted methods? MO
(AUD) Lab Audit: Data not based on lab analysis.
(PRE) Precision: Precision and accuracy estimates are not available
(EOT) Editting: Edit procedures used and documented.
(CBT) Data collected by: EPA lab Health Effects Research Lab-Research
Triangle Park ^Contractor lab vario
(ABY) Data analyzed by: EPA lab Health Effects Research Lab-Research
Triangle Park
Contractor lab various labs under contract to EPA
(IDL) Laboratory Identification: YES
827
-------
Accession Ho. 6502000109 (cont)
(PR1) Priaary purpose of data collection: refining and- developing
bioassays
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data base: Printouts on
request
(HOS) Number of regular users of data base: 1 office
(OSR) Current regular users *f data base: EPA laboratories
(CRT) Confidentiality of data and Halts on access: Limits on access
within EPA and outside agency for soae data
(DLC) Priaary physical location of data: HCC/UMIYAC
(DST) Fora of data storage: Magnetic disc
(DAC) Type of data access: EPA software Genetic Toxicology Inforaation
Systea MIOS:6502800904 ; EPA hardware UHIVAC 1100
(CHG) Direct charge for non-EPA use: no outside use/access permitted
(UPDT) Frequency of data base master file up-date: Quarterly
(CMP) Completion of fora:
Carol Evans
OFC: EPA/(ORD)/(OHR)/(RERL-RTP)/(BD)
AD: Research Triangle Park, HC 27711
PH: (919) 541-2567
(DP) Date of fora completion: 01-25-83
(CMM) Contact naae(s): Howard,8. ; Evans,C.
(COR) Contact organization: Genetic Toxicology Division
(RQR) Responsible Organization: Office of Research and
Development*Offlee of Health Research.Health Effects Search La
828
-------
Accession No. 6502000110
(DQ) Date of Questionaire: 12-02-82
(RAM) Rame of Data Base of Model: HUMan Morbidity Costs of Air
Pollution in St. Louis
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Over view of Data Base or Model: Consists of records for
approximately 10,000 individuals residing in the urbanized area of
the St. Louis Standard Metropolitan Statistical Area (SMSA) who
vere administered background and follow-up questionnaires during
overlapping 8 week periods between June 1978 and July 1979.
Principal background parameters concern demographics/ income/
health insurance/ occupation/ residence/ diet/ exercise/ smoking/
and baseline health status. Principal follow-up parameters
concern medical problems/ disability, health services utilization/
and exposure to ambient pollutants and meteorological
conditions.
(CTC) CORTACTS: Subject matter Michael D. Koontz (301) 424-9133
; Computer-related Michael D. Koontz (301 424-9133 ; EPA
Office Alan P. Carlin (202) 382-5754
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Funded for development
(DPO) Projected operational date of Data Base: 12-00-80
(GRP) croups of substances represented In Data Base: 7 criteria HAAQS
(IPP) Ron-pollutant parameters included in the data base: Cost/economic
data ?Exposure data jHealth effects jLocation j Population
demographics ;Temperature ;Bind velocity ;income ; health
Insurance ;occupation ;residence ;diet ;exercise ;sacking ;
baseline health status
(DS) Time period covered by data base: 06-01-78 TO 07-30-79
(TRM) Termination of data collection: Occurred 07/30/79
(FRQ) Frequency of data collection or sampling: one time only
(HOB) Number of observations in data base: 10000.(Estimated)
(iEI) Estimated annual increase of observations in data base: (R/A.)
(INF) Data base includes: Raw data/observations }Summary aggregate
observations
(RTS) Total number of stations or sources covered in data base: 25.
(RCS) Ro. stations or sources currently originating/contributing data:
(HOF) Number of facilities covered in data base (source monitoring): (R
(GEO) "Geographic coverage of data base: Geographic region St. Louis
Standard Metropolitan Statistical area
(CDE) Pollutant identification data are? Uncoded
(LIM) Limitation/variation in data of which user should be aware: Indiv
idual exposures assigned from closest local monitoring data to
their hourly locations for major activities (e.g. residence/
work, school) during an 8 week period; health effects over the
same period are reported by one respondent for each household
on a biweekly basis.
(DPR) Data collect./anal. procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented ;Analysis method
document QA procedures documented
829
-------
Accession Ho. 6502000110 (cont)
(ANL) Lab analysis based on EPA-approved or accepted Methods? YES
(ADD) Lab Audit: Data not based on lab analysis.
CPRE) Precision: Precision and accuracy estimates exist but are not
included in data base.
(EOT) Edittlng: Edit procedures used and documented.
(CBT) Data collected by: Local agency St. Louis City/County and
Southwest Illinois Monitoring stations. Contractor Geomet
Technologies, Inc.
(ABY) Data analyzed by: Mo analysis has been done to date
(IDL) Laboratory identification: 10
(PR1) Primary purpose of data collection: Anticipatory/research
(PR2) Secondary purpose of data collection: Special study
(AOT) Authorization for data collection: Ho statutory requirement:
Data collection requirement is intended to provide estimates of
economic benefits (fro* reduced morbidity) associated with air
pollution control strategies.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0158
(REP) For* of available reports and outputs of data base: Machine-reada
ble raw data
(HOS) number of regular users of data base: 0
(USR) Current regular users of data base: EPA headguarter offices
Office of Strategies Assessment and Special Studies/Office of
Research and Development.
(CMF) Confidentiality of data and limits on access: Limits on outside
access for some data
(DLC) primary physical location of data: Contractor
(DST) Form of data storage: Magnetic tape
(DAC) Type of data access: Commercial software any software accepting
IBM EBCDIC character coding
(CHG) Direct charge for non-EPA uses no outside use/access permitted
as yet
(OPDT) Frequency of data base master file up-date: Other one time
study only
(RDBEPA) Related EPA data bases used in conjunction with this data base
SAROAD (Storage and Retrieval of Aerometric Data) data used in
constructing data base.
(CMP) Completion of form:
Michael D. Koontz
OFC: Geomet Technologies, Inc.
AD: 15 Firstfield Road Galthersburg, NO 20760
PH: 301-424-9133
(DF) Date of form completion: 01-25-83
(NMAT) Number of substances represented in data base: 5
(RCAS) Mumber of CAS registry numbers in data base: 4
(MAT) Substances represented in data base:
carbon mono*ide<630-08-0> sulfur dloxlde<7446-09-5>
nitrogen dioxide<10102-44-0> total suspended partlculates
ozone<10028-15-6>
(CAS) CAS registry numbers of substances included in data base: 630-08-
0; 10102-44-0; 10028-15-6; 7446-09-5
(CHM) Contact name(s): Koontz,M.D. ; Koontz,M.D. ;
830
-------
Accession No. 6502000110 (cont)
Carlin,A.P. !
(ROR) Responsible Organization: Office of Research and
Development.Office of Health Research.Health Effects Search La
831
-------
Accession Ho. 6502000111
5 HESHAPS J7 criteria MAAQS ;3 HID CAA * 18
radioactive ;noise j!29 307 CMA >41 CMA potential criteria ; 21
drinking Mater standards ;9 potential drinking water >29 drinking
water monitoring ; 299 hazardous substances ;48 cancelled
pesticides ;9 monitoring pesticides > 54 TSCA assessment ;RCRA
hazardous Hastes ;16 Pre-RPAR
(HPP) Hon-pollutant parameters included in the data base: Chemical
data jTest/analysis method *«.„,, •»« a*
(DS) Time period covered by data base: 01-01-30 TO 11-30-81
(TRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: as needed
(HOB) Humber of observations In data base: (more than
32000)(Estimated) .,„•«..*
(HEI) Estimated annual increase of observations in data base: (unknown)
(IHF) Data base includes: Ran data/observations ;Reference
(UTS) Total number of stations or sources covered in data base: 1000
(HCS) Ho. stations or sources currently originating/contributing data:
(HOF) number of facilities covered in data base (source monitoring): (H
(CEO) Geographic coverage of data base: International ...
(LOC) Data elements identifying location of station or source include:
project identifier
(PAC) Data elements identifying facility include: H/A
(CDE) Pollutant Identification data are: CAS registry number
(LIM) Limitation/variation in data of which user should be anare. This
library is accessible through the Management information and
Data systems Division (MiDSD). Only a fraction of this data
originates in the Health Effects Research Lab-Research Triangle
Park (HERL-RTP)-none is stored as a data base there. Data
originating in HERL-RTP is contributed to the Chemical Information
System (CIS) in Washington.
832
-------
Accession Mo. 6502000111 (cent)
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: No knoun edit procedures exist.
(CBY) Data collected by: EPA lab Health Effects Research Lab-Research
Triangle Park /various universities
(ABY) Data analyzed by: EPA lab Health Effects Research Lab-Research
Triangle Park
various universities and research laboratories
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Anticipatory/research
(AUT) Authorization for data collection: Statutory authorization Is P
L 92-516 as amended (Federal Insecticide, Fungicide and Rodenticide
Act-FIFRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data base: On-line
conputer
(HUS) Number of regular users of data base: 1000 or more
(OSR) Current regular users of data base: EPA laboratories
Other federal agencies
States
(CNF) Confidentiality of data and Halts on access: Ho Units on
access to data
(DLC) Primary physical location of data: Contractor
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: Commercial software Telenet
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Other
unknown-updates done by users
(RSS) Related EPA automated systems which use data base: Chemical
Information System CCIS)
(CMP) Completion of form:
Nancy K. Milson
OFC: EPA/(ORD)/(OHR)/(HERL-RTP)
AD: Research Triangle Park MC 27711
PH: (919) 629-2358
(OF) Date of form completion: 01-25-83
(NMAT) Number of substances represented in data base: 769
(NCAS) Number of CAS registry numbers in data base: 995
(MAT) Substances represented in data base:
1,1,2,2,-tetrachloroethane
-0,0-diethyl phosphoricacid,0-p- <79-34-5>
nitrophenyl ester<311-45-5> l,l,2-trichloroethane<79-00-5>
0,0-diethyl-0-(2-pyrazinyl) l,l,2-trichloroethene<79-01-6>
phoshorothloO,0-diethyl-s-(2- 1,1-dichloroethane<75-3 4-3>
ethylthlo)ethyl)ester of l,l-dichloroethylene<75-35-4>
phosphorodlthioicacld l,l-dimethylhydrazine<57-14-7>
0,0-diethyl-s-Bethyl ester of phos l/12-trichloroethene<79-01r6>
1,1,1,2-tetrachloroethane l,2,3,4,10,10-hexachloro-l,4,4a,5,
<630-20-6> 8* 8a-h«xahydro-l*4:5*8
Iflf1-trichloroethane<71-55-6> endo-dimetha
833
-------
Accession lo. 6502000111
(cont)
l*2*4*-trichlorobenzene 1,2,4,5-
tetrachlorobenzene<95-94-3>
l*2-dibro«o-3-chloropropane (dbcp)
<96-12-8>
l,2-dibro»oethajie<106-93-4>
If 2-dlchlorobenzene< 95-50-1>
1, 2-dichloroethane<107-06-2>
1* 2-dichloropropane<78-87-5>
l,2-di«thylhydrazine<1615-80-l>
If 2-di«ethylhydrazine<540-73-8>
l,2-diphenylhydrazine<122-66-7>
l*2~propanediol<57-55-6>
if 2-tr ans-dlchloroethylene
<156-60-5>
1*3,4 trlchlorobenzene<120-82-l>
If 3-dichlorobenzene<541-73-l>
1* 3-dichloroprop«ne<542-75-6>
1^3-dlchloropropylene<542-75-6>
1^3-Pentadiene<504-60-9>
1^3-propane sultone<1120-7l-4>
If 4-dlchloro-2-butene<110-57-6>
If 4-dlchlorobenzene<106-46-7>
If4-dioxane<123-91-l>
1, 4-naphthoquinone<130-15-4>
1- C o-chlorophenyl) thiourea
<5344-82-l>
l-(p-chloroben2oyl)-5-»ethoxy-2-
•ethylindole-3-acetlc acid
l-chloro-2, 3»epoxypropane
<106-89-8>
1-naphthyl-2-thlour«a<86-88-4>
1-naph thyl »ine< 134-32-7>
2^2-dichloropropionlc acid
<75-99-0>
tr achlor ophenol<58-90-2>
aiiines
esters
2,4,5-t salts
2f 4,5-tp acid esters
2^4^5-trichlorophenol<95-95-4>
2,4^5-trichlorophenoxyacetic acid
2^4^5-trichlorophenoxypropionic
acid (TP)<93-72-l>
2,4^6-trichlorophenol<88-06-2>
2^4^7^8-tetrachlorodibenzo-p-
dioxin (tcdd)
2^4-d acid<94-75-7>
2^4-d esters
2,4-dichloroph«nol<120-83-2>
2^4-dichlorophenoxyacetic acid (2*
4-dX94-75-7>
2,4-diaethylphenol<105-67-9>
2^4-dinitrophenol<51-28-5>
2^4-dinitrotoluene<121-14-2>
2, 4-dithiobiur et<541-53-7>
2,6-dichlorophenol<87-65-0>
2,6-dinitrotoluene<606-20-2>
2-acetylaainof lourene
2-butanone peroxide<1338-23-4>
2-chloroethyl vinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-cyclohexy 1- 4, 6-dlnitr ophenol
<131-89-5>
2-fluoroacetamide (1081)<640-19-7>
2-Bethyl-2-(raethylthio)propionalde
hyde-o-{roethylcarbonyl)oxiae
<80-62
-6>
2-«ethylaziridine<75-55-8>
2-Bethyllactonitrile<75-86-5>
2-naphthylaraine<91-59-8>
2-nitrophenol<88-75-5>
2-nltropropane<79-46-9>
2-picoline<109-06-8>
2-propyn-l-01<107-19-7>
2-sec butyl-4, 6-dlnitrophenol
<88-85-7>
3^3'-dichlorobenzidine<91-94-l>
3,3 '-dine thoxybenzidine<119-90-4>
3^3 '-dimethyl-l(methylthlo)-2-
butanone-0-((methylanino)
carbonyDoxime
3^3 •-dira€thylb€nzidine<119-93-7>
3/4-benzofluoranthene<205-99-2>
3r 4-dihydroxy- alpha-die thy Ian Ino)-
methyl benzyl alcohol
3-chloropropionitrile<542-76-7>
3-»ethylcholanthrene<56-49-5>
39196-18-4>
4^4'-dde(p,p'-ddx)<72-55-9>
4,4'-ddt<50-29-3>
4/4»-»ethylene-bis-(2-chloroanilin
4^6-dinitro-o-cresol<534-52-l>
4-A«inopyrldlne<504-24-5>
4-bro«ophenyl phenyl ether
<101-55-3>
4-chloro-o-toluidine hydrochloride
<3165-93-3>
4-chlorophenyi phenyl ether
<7005-72-3>
834
-------
Accession No. 6502000111
(cont)
4-nitrophenol<100-02-7>
5-(aninonethyl)-3-isoxazolol
<2763-96-4>
5-nitro-o-toluidine<99-55-8>
6-a«ino-l,lar2,8,8a,Bb-hexahydro-
B-thydroxymethyl) 8-methoxy-5-
•ethyl-caraba
7,12-dinethylbenz(a)ant 7-
oxabicycol(2. 2.1) heptane-2,3-
dicarboxylicacid<145-73-3>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acetaldehyde<75-07-0>
acetic acid<64-19-7>
acetic anhydride<108-24-7>
acetone cyanohydrin<75-86-5>
acetone<67-64-l>
acetonitrlle<75-05-8>
acetophenone<98-86-2>
acetyl bromlde<506-96-7>
acetyl chloride<75-36-5>
acid *ist
acrolein<107-02-8>
acrylaaide<79-06-l>
acrylic acid<79-10-7>
acrylonitrile<107-13-l>
adipic acid<124-04-9>
alachlor<15972-60-8>
aldrin<309-00-2>
allyl alcohol<107-18-6>
allyl chloride<107-05-l>
alpha,alpha-dimethylbenzylhydro-
peroxide<80-15-9>
alpha,alpha-dimethylphenethylasine
<122-09-8>
alpha-chlorotoluene<100-44-7>
aluiinun phosphide<20859-73-8>
aluainun sulfate<10043-01-3>
alu»inu«<7429-90-5>
a*ltraz (baa«)<33089-61-l>
a«itrole<61-82-5>
a««onia<7664-41-7>
aaaonliui acetate<631-61-8>
onlun benzoate<1863-63-4>
bicarbonate<1066-33-7>
bichronate<7789-09-5>
aaaoniua bifluoride<1341-49-7>
auoniun bisulfite<10192-30-0>
aiMoniue carbaiate
aaaoniuB carbonate<506-87-6>
aaaoniun chloride<12125-02-9>
chromate<7788-98-9>
annoniun citrate<7632-50-0>
amaonlun f luoborate<13826-83-0>
amaonium f luo ride< 121 25-01- 8>
aaaonium hydroxide< 13 36-21- 6>
aowoniuM oxalate<1113-38-8>
aamoniuB picrate<131-74-8>
annoniun sllicofluoride
<16919-19-0>
annoniun sulf anate<7773-06-0>
annoniun sulf ide<12135-76-l>
annoniun sulf ite<10l96-04-0>
annoniun tartrate<3164-29-2>
annoniun thiocyanate<1762-95-4>
annoniun thiosulfate<7783-18-8>
anyl acetate<628-63-7>
aniline<62-53-3>
anthracene<120-12-7>
antlnony pentachioride<7647-18-9>
antinony potassiun tar tr ate
antinony tribroraide<7789-61-9>
antinony trlchloride<10025-91-9>
antinony trif luoride<7783-56-4>
antinony trioxide<1309-64-4>
antimony<7440-36-0>
araalte<140-57-8>
arsenic acid<1327-52-2>
arsenic disulf ide<1303-32-8>
arsenic pentoxide<1303-28-2>
arsenic trichloride<7784-34-l>
arsenic trioxlde<1327-53-3>
arsenic trisulf ide<1303-33-9>
arsenic<7440-38-2>
asbestos<1332-21-4>
atrazine<1912-24-9>
auraaine<2465-27-2>
azaserine<115-02-6>
banvel-d<1918-00-9>
barlun cyanide<542-62-l>
bariuo<7440-39-3>
benefin<1861-40-l>
benomyl<17804-35-2>
benz ( c) acridine<225-51-4>
benzac
benzal chloride<98-87-3>
benzene<71-43-2>
benzenesulfonyl chloride<98-09-9>
benzene thiol<108-98-5>
benzidine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(9,h,i)perylene<191-24-2>
835
-------
Accession Ho. 6502000111
(cont)
benzo(k)fluoranthene<207-08-9>
benzole acid<65-85-0>
benzonitrile<100-47-0>
benzotrichloride<98-07-7>
benzoyl chloride<98-88-4>
benzyl chloride<100-44-7>
beryllium chlorlde<7787-47-5>
berylliuv -dust
berylliuB fluorlde<7787-49-7>
berylliuB nitrate<13597-99-4>
berylliuB<7440-41-7>
bhc
bhc-alpha<319-84-6>
bhc-be ta<3 19-8 5-7>
bhc-delta<319-86-8>
biphenyl<92-52-4>
bis (2-chloroethoxy)Bethane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloroMthyl)ether<542-68-l>
bisauth co«pounds< 7440-6 9-9>
boron co«pounds<7440-42-8>
bro«ine<7726-95-6>
bro«oacetone<598-31-2>
broBobenzene<108-86-l>
broBOchlorobenzene<28906-38-9>
bro»odichloro«ethane<75-27-4>
bro»o«ethane<74-83-9>
brucine<357-57-3>
bu t ach lor< 231 84-66 -9>
butyl acetate<123-86-4>
butyl benzyl phthalate<85-68-7>
butyla«lne<109-73-9>
butyric ac Id <1 07-92- 6>
cacodylic acid and salts<75-60-5>
cadBiua acetate<543-90-8>
cadBlua bro«ide<7789-42-6>
cadaiuB chloride
cadBlu«<7440-43-9>
calciUB arsenate<7778-44-l>
calciuB arsenite<52740-16-6>
calciu* carbide<75-20-7>
calciuB chroBate
calciuB cyanide<592-01-8>
calcium dodecylbenzenesulfonate
<26264-06-2>
calciuB hydroxide<1305-62-0>
calclUB hypochlorite<7778-54-3>
oxide<1305-78-8>
captan<133-06-2>
carbaryl<63-25-2>
carbofuran<1563-66-2>
carbon disulfide<75-15-0>
carbon Bonoxlde<630-08-0>
carbon tetrachlorlde<56-23-5>
carbony1 fluoride<353-50-4>
chloral<75-87-6>
chloraBbucll<305-03-3>
chlor anil<118-75-2>
chlordane<57-74-9>
chlorinated naphthalenes
chlorlne<7782-50-5>
chloroac«taldehyde<107-20-0>
chlorobenzene<108-90-7>
chlorobenzilate<510-15-6>
chlorodibroBoaethane<124-48-l>
chloroethane<75-00-3>
chloroethene<75-01-4>
chloroethyl vinyl ether<110-75-8>
chlorofluorocarbons
chlorofor«<67-66-3>
chloro»ethane<74-87-3>
chloroaethyl Methyl ether
<107-30-2>
chloroprene<126-99-8>
chlorosulfonlc acid<7790-94-5>
chlorpyrlfos<2921-88-2>
chroaic acetate<1066-30-4>
chroBic acid<7738-94-5>
chroBic sulfate<10101-53-8>
chroBiuB<7440-47-3>
chroaous chlorlde<10049-05-5>
chrysene<218-01-9>
cls-l,2-dlchloroethylene<156-59-2>
coal tar<8007-45-2>
cobalt<7440-48-4>
cobaltous bro«ide<7789-43-7>
cobaltous for«ate<544-18-3>
cobaltous sulfaaate
copper cyanlde<544-92-3>
copper<7440-50-8>
couBaphos<56-72-4>
creosote<8021-39-4>
cresol<1319-77-3>
cresylic acid<1319-77-3>
crotonaldehyde<4170-30-3>
cuB«ne<98-82-8>
cupric acetate<142-71-2>
cuprlc ac«toars«nite<12002-03-8>
cupric chlorlde<7447-39-4>
836
-------
Accession Ho. 6502000111
(cont)
cupric nitrate<3251-23-8>
cupric oxalate<814-91-5>
cupric sulfate airaoniated
<10380-29-7>
cupric sulfate<7758-98-7>
cupric tartrate<815-82-7>
cyanazine<21725-46-2>
cyanide<57-12-5>
cyanogen bro«ide<506-68-3>
cyanogen chloride<506-77-4>
cy a noge n< 460 -19- 5>
cyclohexan«KllO-82-7>
cyclohexanon«Kl08-94-l>
cyclophosphaaide<50-18-0>
dauno«ycin<20830-81-3>
ddd(tde)
ddt
deneton<8065-48-3>
di-isopropylfluorophosphate
<55-91-4>
di-n-butyl phthalate<84-74-2>
dl-n-octyl phthalate<117-84-0>
dl-n-propylnitrosanine<621-64-7>
dialkyl ethers
dialkyl phosphates
diallate<2303-16-4>
diazinon<333-41-5>
dibenzo( a, h)anthracene<53-70-3>
dibenzofuran<132-64-9>
dibenzol(a,i)pyrene
dibroMOchlor oaethane<124-48-l>
dibro«oaethane<74-95-3>
dibutyl phthalate<84-74-2>
dicanba<1918-00-9>
dichlobenl1<1194-6 5-6>
dichlone<117-80-6>
dichlorobenzene<25321-22-6>
dichlorobroMonethane<75-27-4>
dlchlorodifluoro«ethane<75-71-8>
dichloroiodo«ethane<594-04-7>
dichloro»ethane<75-09-2>
dichlorophenylarsine<696-28-6>
dlchloropropane<26638-19-7>
dichloropropene-dichloropropane
•Ixture
dlchloropropene<26952-23-8>
dichlorvos (ddvp)<62-73-7>
dleldrin<60-57-l>
diepoxybutane<1464-53-5>
diethyl phthalate<84-66-2>
diethyla»in€<109-89-7>
diethylarsine
dlethylstilbestrol<56-53-l>
dihydrosafrole<94-58-6>
diaethoate<60-51-5>
diaethyl phthalate<131-ll-3>
dlaethyl sulfate<77-78-l>
di«ethylamine<124-40-3>
diaethylcarbaaoyl chloride
<79-44-7>
dime thy lnitrosamine<62-75-9>
dlnitrobenzene<25154-54-5>
dlnitrophenol
dinltrotoluene<25321-14-6>
dioxane<123-91-l>
dioxin<828-00-2>
dlphenyl ether
diphenylhydrazine<38622-18-3>
dipropylaaine<142-84-7>
diquat<2764-72-9>
disulfoton<298-04-4>
dluron<330-54-l>
dodecylbenzenesulfonic acid
<27176-87-0>
ebdc's (ethylenebisdithlocarbaaate
s)
edta<60-00-4>
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endosulfan
endrin aldehyde<7421-93-4>
endrin<72-20-8>
epichlorohydrin<106-89-8>
epn (ethyl-p-nitrophenyl thionoben
zenephosonate)<2104-64-5>
erbon<136-25-4>
ethioiK563-12-2>
ethyl acetate<141-78-6>
ethyl acrylate<140-88-5>
ethyl chloride<75-00-3>
ethyl ether<60-29-7>
ethyl nethacrylate<97-63-2>
ethyl «ethanesulfonate<62-50-0>
ethyl parathion<56-38-2>
ethylbenzene<100-41-4>
ethylcyanlde<107-12-0>
ethylene bisdithiocarbaaate
ethylene dibroaide (edb)<106-93-4>
ethylene dichloride<107-06-2>
ethylene oxide<75-21-8>
ethylene thiourea<96-45-7>
ethylenedlaaine<107*15-3>
ethylenelalne<151-56-4>
837
-------
Accession Ho. 6502000111
(cont)
ferric araoniui citrate<1185-57-5>
ferric amoniu* oxalate
<14221-47-7>
ferric chloride<7705-08-0>
ferric cyanide
ferric fluoride<7783-50-8>
ferric nitrate<10421-48-4>
ferric sulfate<10028-22-5>
ferrous aMonlra sulfate
<10045-89-3>
ferrous chloride<7758-94-3>
ferrous suifate<7720-78-7>
fluoranthene<206-44-0>
fluorene<86-73-7>
fluorides
fluorine<7782-41-4>
fluoroacetic acid, sodlua salt
fluorotrichloro«ethane<75-69-4>
for»aldehyde<50-00-0>
foralc aci
fuaarlc acld<110-17-8>
furan<110-00-9>
furfural<98-01-l>
glycidylaldehyde
gross alpha
guthion<86-50-0>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlorobutadiene<87-68-3>
he xach loro cy cl ohexane< 58-89-9>
hexach lorocyclopentadlene<77-47-4>
hexachloroethane<67-72-l>
hexachlorophene<70-30-4>
hexachloropropene<1888-7l-7>
hexaethyl tetraphosphate<757-58-4>
hydrazine<302-01-2>
hydrocarbons
hydrochloric acid<7647-01-0>
hydrocyanic acid<74-90-8>
hydrofluoric acld<7§64-39-3>
hydrogen cyanide<74-90-8>
hydrogen sulflde<7783-06-4>
hydroxydiaethyl arsine oxide
<75-60-5>
indeno (l,2r3-cd)pyrene<193-39-5>
lodooe thanc<74-88-4>
iron and co«pounds<7439-89-6>
iron dextran<9004-66-4>
isobutyl alcohol<78-83-l>
isocyanic acid, Methyl ester
<624-83-9>
isophorone<78-59-l>
lsoprene<78-79-5>
isopropanolaalne dodecylbenzene
sulfonate<54590-52-2>
lsosafrole<120-58-l>
kelthane
kepone<143-50-0>
1asiocarpine<303-34-4>
lead ac«tate<301-04-2>
lead arsenate<3687-31-8>
lead chlorlde<7758-95-4>
lead fluoride<7783-46-2>
lead fluoroborate<13814-96-S>
lead lodide<10101-63-0>
lead nltrate<10099-74-8>
lead phosphate<7446-27-7>
lead st«arate<1072-35-l>
lead subacetate<1335-32-6>
lead sulfate<7446-14-2>
lead sul£ide<1314-87-0>
lead thlocyanate<592-87-0>
lead<7439-92-l>
llndan«<58-89-9>
llthiui and co«pounds<7439-93-2>
lithluB chro«ate
«-cresol<108-39-4>
•-xy1ene<10 8-3 6-3>
•alathion<121-75-5>
•aleic acid<110-16-7>
•aleic anhydrlde
•aleic hydrazide<123-33-l>
•alononitrile<109-77-3>
•anganese<7439-96-5>
•anaade beta
•ate
•«lphalan<148-82-3>
•ercaptodlB«thur<2032-65-7>
•ercurlc cyanlde<592-04-l>
•ercuric nitrate<10045-94-0>
•ercuric sulfate<7783-35-9>
•ercuric thiocyanate<592-85-8>
•ercurous nitrat«<10415-75-5>
•ercury ful»inate<628-86-4>
•ercury<7439-97-6>
•ethanearsonates
•ethanethiol<74-93-l>
•ethanol<67-56-l>
•ethapyrllene<91-80-5>
•«tho«yl<167$2-77-5>
•ethoxychlor<72-43-5>
•ethyacrylonltrll«<126-98-7>
•ethyl chlorocarbonate<79-22-l>
838
-------
Accession Ho. 6502000111
(cont)
•ethyl chlorofora<71-55-6>
methyl ethyl ketone (mek)<78-93-3>
methyl ethyl ketone peroxide
<1338-23-4>
methyl hydrazine<60-34-4>
methyl iodide<74-88-4>
methyl Isobutyl ketone<108-10-l>
methyl mercaptan<74-93-l>
methyl methacrylate<80-62-6>
methyl parathion<298-00-0>
methylthiouracil<56-04-2>
mevi nphos<77 86-3 4-7>
mexacarbate< 315-18-4>
microbiology coliform bacteria
mirex<2385-85-5>
molybdenun and compounds
<7439-98-7>
Bonoethyla*ine<75-04-7>
monoeethy1anine< 74-89-5>
monuron<150-68-5>
n, n-bis(2-chloroethyl)-2-naphthyla
mine<494-03-l>
n-alkanes clO-c30
n-butyl alcohol<71-36-3>
n-butyl phthalate<84-74-2>
n-aethyl-n*-nitro-n-nitrosoguanidi
ne<70-25-7>
n-nitroso-n-ethylurea<759-73-9>
n-ni troso-n-ae thy lurea<684-93-5>
n-nitroso-n-*ethylurethane
<615-53-2>
n-nltrosodi-n-butylamlne<924-16-3>
n-nitrosodi-n-propylam ine
<621-64-7>
n-nitrosodiethanola«ine<1116-54-7>
n-nltrosodlethyla«ine<55-18-5>
n-nitrosodimethylamine<62-75-9>
n-ni trosodiphenylamine<86-30-6>
n-nitrosomethylvinylamine
n-nitrosopiperidine<100-75-4>
n-nltrosopyrrolidine<930-55-2>
n-phenylthiourea<103-85-5>
n-propylanine<107-10-8>
naled<300-76-5>
naphthalene<91-20-3>
naphthenic acid<1338-24-5>
nickel amonium sulfate<7785-20-8>
nickel carbonyl<12612-55-4>
nickel chloride<7718-54-9>
nickel cyanide<557-19-7>
nickel hydroxide<12054-48-7>
nickel nitrate<13138-45-9>
nickel sulfate<7786-81-4>
nickel<7440-02-0>
nicotine and salts<54-ll-5>
nitralin<4726-14-l>
nitrate<14797-55-8>
nitrates/nitrites
nitric acid<7697-37-2>
nitric oxide<10102-43-9>
nitriloacetates
nitrobenzene<98-95-3>
nitrogen dioxide<10102-44-0>
nitrogen peroxide<10102-44-0>
nitrogen tetroxide<10544-72-6>
nitroglycerine<55-63-0>
nitrophenol<25154-55-6>
nltrosoaethylurea<684-93-5>
nitrosoaorpholine<59-89-2>
nltrotoluene
nonaphthalene
o-cresol<95-48-7>
o-methoxyphenol<90-05-l>
o-toluidine hydrochloride
<636-21-5>
o-xylene<95-47-6>
octaaethylpyrophosphoraaide (OMPA)
<152-16-9>
oil and grease
oleyl alcohol condensed with 2
aoles ethylene oxide
osmiua tetroxide<20816-12-0>
ozone<10028-15-6>
p-chloro-a-cresol<59-50-7>
p-chloroaniline<106-47-8>
p-cresol<106-44-5>
p-dichlorobenzene<106-46-7>
p-diaethyla»inoazobenzene<60-ll-7>
p-nltroanillne<100-01-6>
p-xylen
paraforaaldehyde<30525-89-4>
paraldehyde<123-63-7>
paraquat<4685-14-7>
parathion<56-38-2>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
639
-------
Accession No. 6502000111
(cont)
pcb-1254 (arochlor 1254}
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorobenzene<608-93-5>
pentachloroethane<76-01-7>
pentachloronitrobenzene (PCIB)
<82-68-8>
pentachlorophenol<87-86-5>
perchloroethyl«ne<127-18-4>
perthane<72-56-0>
phenac«tin<62-44-2>
phenanthrene<85-01-8>
phenarsazine chloride<578-94-9>
phenol<108-95-2>
phenyl diehloroarsine<696-28-6>
ph«nylacetic acid<103-82-2>
phenylmercury acetate<62-38-4>
phorate 298-0202
phorate<298-02-2>
phosgene<75-44-5>
phosophorothioic acid,o,o-
dimethyl ester,o-ester yith nf
n-dimethylbenzene
phosphine<7803-51-2>
phosphoric acid<7664-38-2>
phosphorus and compounds
phosphorus o*ychloride<10025-87-3>
phosphorus pentasulfide<1314-80-3>
phosphorus sulfide<1314-80-3>
phosphorus trichloride<7719-12-2>
phosphorus<7723-14-0>
photon emitters
phthallc acid<88-99-3>
phthallc anhydrlde<85-44-9>
piperonyl butoxide<51-03-6>
polybroainated blphonyls (PBBs)
polychlorinated bipnenyls CPCBs)
potasslua arsenate<7784-41-0>
potassiu* arsenite<10124-50-2>
potassluM bichro«ate<7778-50-9>
potasslui chro»ate<7789-00-6>
potassiua cyanlde<151-50-8>
potassiu* hydroxide<1310-58-3>
potassiUM per«anganate<7722-64-7>
potassiUM silver cyanide<506-61-6>
prona«ide<23950-58-5>
pr opachlor
propanlKl 09-98-8>
propar glte<2312-35-8>
proplonic acid<79-09-4>
propionic anhydride<123-62-6>
propionltrile<107-12-0>
proplyene oxide<75-56-9>
propoxur<114-26-l>
propylene oxide<75-56-9>
pyrene<129-00-0>
pyrethrin<121-29-9>
pyridine
qulnoline<91-22-5>
quinones
radiua 226<13982-63-3>
radiun 228<15262-20-1>
radon<10043-92-2>
reserpine<50-55-5>
resorcinol<108-46-3>
ronneK 299-84-3>
rotenone<83-79-4>
s/s^s-tributyl phosphorotrithloate
<78-48-8>
saccharin<81-07-2>
8afrole<94-59-7>
secondary aaines
selenious acid<7783-00-8>
seleniua oxide<12640-89-0>
seleniu* sulfide<7446-34-6>
seleniu«<7782-49-2>
selenourea<630-10-4>
silver cyanlde<506-64-9>
silver nitrate<7761-88-8>
sll»er<7440-22-4>
silvex<93-72-l>
sUazlne<122-34-9>
sodlue and co«pounds<7440-23-5>
sodlui arsenate<7631-89-2>
sodiiM arsenite<7784-46-5>
sodium azide<26628-22-8>
sodium bichro«ate<10588-01-9>
sodiua blfluoride<1333-83-l>
sodiu* bisulfite<7631-90-5>
sodium chro«ate<7775-ll-3>
sodium cyanide<143-33-9>
sodium dodecylbenzenesulfonate
<25155-30-0>
sodium fluoride<7681-49-4>
sodium fluoroacetate (1080)
<62-74-8>
sodium hydrosulfide<16721-80-5>
sodium hydroxide<1310-73-2>
sodium hypochlorite<7681-52-9>
sodium methylate<124-41-4>
sodium nitrite<7632-00-0>
840
-------
Accession No. 6502000111
(cont)
sodiua phosphate, dibasic
<7558-79-4>
sodiua phosphate, tribasic
<7601-54-9>
sodiUB selenite<10102-18-8>
sodiUB<7440-23-5>
streptozotocin
strobane<8001-50-l>
strontium chroaate<7789-06-2>
strontium sulfide<13l4-96-l>
strychine<57-24-9>
strychnine<57-24-9>
styrene<100-42-5>
sulfates
sulfides
sulfonaaide
sulfur dioxide<7446-09-5>
sulfur Bonochloride<10025-67-9>
sulfuric acid<7664-93-9>
tde<72-54-8>
terpenes
tetrachloroethene<127-18-4>
tetrachloroethylene<127-!8-4>
tetrachloroaethane<56-23-5>
tetraethyl dithiopyrophosphate
<3689-24-5>
tetraethyl lead<78-00-2>
tetraethyl pyrophosphate<107-49-3>
tetrahydofuran<109-99-9>
tetranltro«ethane< 509-14-8>
thallic oxide<1314-32-5>
thalliua acetate<563-68-8>
thalliua carbonate<29809-42-5>
thai HUB chloride<7791-12-0>
thallium nitrate<10102-45-l>
thalliua selenite
thalliua sulfate<7446-18-6>
thallium<7440-28-0>
thioaceta«ide<62-55-5>
thiophanate •ethyl<23564-05-8>
thiosenicarbazide<79-19-6>
thiourea<62-56-6>
thiura»<137-26-8>
toluene diisocyanate<26471-62-5>
toluene<108-88-3>
toluen«dia«ine<25376-45-8>
total reduced sulphur
total suspended particulates
toxaphene<8001 -35-2>
triallate<2303-17-5>
tribro«omethane<75-25-2>
tr ichl or f on< 52*6 8-6>
trichloroethane<25323-89-l>
trichloroethene<79-01-6>
trichloroethylene<79-01-6>
trichlorofluoro«ethane<75-69-4>
trichloro«ethanethiol<75-70-7>
trichiorophenol (TCP)<25167-82-2>
triethanolaaine dodecylbenzenesulf
onate<27323-41-7>
triethylaaine<121-44-8>
trifluraline (tref lan)<1582-09-8>
tri«ethyla«lne<75-50-3>
trinitrobenzene<99-35-4>
tris(2,3-dibroBopropyl)phosphate
<126-72-7>
trypan blue<72-57-l>
trysben<50-31-7>
turbidity
uracil •ustard<66-75-l>
uraniu«<7 440- 61-1 >
uranyl acetate<541-09-3>
uranyl nitrate<10102-06-4>
urethane<51-79-6>
vanadic acid, amoniua salt
vanadiun pentoxidc<13l4-62-l>
vanadiun<7440-62-2>
vanadyl sulfate<27774-13-6>
vinyl acetate<108-05-4>
¥inyl chloride<75-01-4>
vinylldene chloridc<75-35-4>
xylene<1330-20-7>
xylenol<1300-71-6>
zinc acetate<557-34-6>
zinc aiaoniua chloride
zinc borate<1332-07-6>
zinc br OB ide< 7699-45- 8>
zinc carbonate<3486-35-9>
zinc chloride<7646-85-7>
zinc cyanide
zinc fluoride<7783-49-5>
zinc forBate<557-41-5>
zinc hydrosulf ite<7779-86-4>
zinc nitrate<7779-88-6>
zinc phenol sulfonate<127-82-2>
zinc phosphide<1314-84-7>
zinc silicofluoride<16871-71-9>
zinc sulfate<7733-02-0>
zinc<7440-66-6>
zirconiua nitrate<13746-89-9>
zirconiuB potassiua fluoride
<16923-95-8>
zirconiuB sulfate<14644-61-2>
841
-------
Accession Ho. 6502000111 (cont)
zirconIUH tetrachlorlde
<10026-ll-6>
(CAS) CAS registry lumbers of substances included in data base: 311-45-
5; 630-20-6; 71-55-6; 79-34-5; 79-00-5; 79-01-6; 75-34-3;
75-35-4; 57-14-7; 79-01-6; 95-94-3; 96-12-8; 106-93-4; 95-50-1;
107-06-2; 78-87-5; 1615-80-1; 540-73-8; 122-66-7; 57*55-6;
156-60-5; 120-82-1; 541-73-1; 542-75-6; 542-75-6; 504-60-9;
1120-71-4; 110-57-6; 106-46-7; 123-91-1; 130-15-4; 5344-82-1;
106-89-8; 86-88-4; 134-32-7; 75-99-0; 58-90-2; 95-95-4; 93-76-5;
93-72-1; 88-06-2; 94-75-7; 120-83-2; 94-75-7; 105-67-9;
51-28-5; 121-14-2; 541-53-7; 87-65-0; 606-20-2; 1338-23-4;
110-75-8; 91-58-7; 95-57-8; 131-89-5; 640-19-7; 80-62-6;
75-55-8; 75-86-5; 91-59-8; 88-75-5; 79-46-9; 109-06-8;
107-19-7; 88-85-7; 91-94-1; 119-90-4; 119-93-7; 205-99-2;
542-76-7; 56-49-5; 72-55-9; 50-29-3; 101-14-4; 534-52-1;
504-24-5; 101-55-3; 3165-93-3; 7005-72-3; 100-02-7; 2763-96-4;
99-55-8; 145-73-3; 83-32-9; 208-96-8; 75-07-0; 64-19-7; 108-24-7;
75-86-5; 67-64-1; 75-05-8; 98-86-2; 506-96-7; 75-36-5;
107-02-8; 79-06-1; 79-10-7; 107-13-1; 124-04-9; 15972-60-8;
309-00-2; 107-18-6; 107-05-1; 80-15-9; 122-09-8; 100-44-7;
20859-73-8; 10043-01*3; 7429-90-5; 33089-61-1; 61-82-5; 7664-41-7;
631-61-8; 1863-63-4; 1066-33-7; 7789-09-5; 1341-49-7; 10192-30-0;
1111-78-0; 506-87-6; 12125-02-9; 7788-98-9; 7632-50-0; 13826-83-0;
12125-01-8; 1336-21-6; 1113-38-8; 131-74-8; 16919-19-0; 7773-06-0;
12135-76-1; 10196-04-0; 3164-29-2; 1762-95-4; 7783-18-8; 628-63-7;
62-53-3; 120-12-7; 7647-18-9; 11071-15-1; 7789-61-9; 10025-91-9;
7783-56-4; 1309-64-4; 7440-36-0; 140-57*8; 1327-52-2; 1303-32-8;
1303-28-2; 7784-34-1* 1327-53-3; 1303-33-9; 7440-38-2; 1332-21-4;
1912-24-9; 2465-27-2; 115-02-6; 1918-00-9; 542-62-1; 7440-39-3;
1861-40-1; 17804-35-2; 225-51-4; 98-87-3; 71-43-2; 98-09-9;
108-98-5; 92-87-5; 56-55-3; 50-32-8; 191-24-2; 207-08-9;
65-85-0; 100-47-0; 98-07-7; 98-88-4; 100-44-7; 7787-47-5;
7787-49-7; 13597-99-4; 7440-41-7; 58-89-9; 319-84-6; 319-85-7;
319-86-8; 92-52-4; 111-91-1; 111-44-4; 39638-32-9; 117-81-7;
542-88-1; 7440-69-9; 7440-42-8; 7726-95-6; 598-31-2;
108-86-1; 28906-38-9; 75-27-4; 74-83-9; 357-57-3; 23184-66-9;
123-86-4; 85-68-7; 109-73-9; 107-92-6; 75-60-5; 543-90-8;
7789-42-6; 7440-43-9; 7778-44-1; 52740-16-6; 75-20-7;
13765-19-0; 592-01-8; 26264-06-2; 1305-62-0; 7778-54-3; 1305-78-8;
133-06-2; 63-25-2; 1563-66-2; 75-15-0; 630-08-0; 56-23-5; 353-50-4;
75-87-6; 305-03-3; 118-75-2; 57-74-9; 7782-50-5; 107-20-0;
108-90-7; 510-15-6; 124-48-1; 75-00-3; 75-01-4; liO-75-8;
67*66-3; 74-87*3; 107*30-2; 126-99-8; 7790-94-5; 2921-88-2;
1066-30-4; 7738-94-5; 10101-53-8; 7440-47-3; 10049-05-5;
218-01-9; 156-59-2; 8007-45-2; 7440-48-4; 7789-43-7; 544-18-3;
544-92-3; 7440-50-8; 56-72-4; 8021-39-4; 1319-77-3; 1319-77-3;
4170-30-3; 98-82-8; 142-71-2; 12002-03-8; 7447-39-4; 3251*23-8;
814-91-5; 10380-29-7; 7758-98-7; 815-82-7; 21725-46-2; 57-12-5;
506-68-3; 506-77-4; 460-19-5; 110-82-71 108-94-1; 50-18-0;
20830-81-3; 8065-48-3; 55-91-4; 84-74-2; 117-84-0; 621-64-7;
2303-16-4; 333-41-5; 53-70-3; 132-64-9; 189^55-9; 124-48-1;
74-95-3; 84-74-2; 1918-00-9; 1194-65-6; 117-80-6; 25321*22-6;
842
-------
Accession Mo. 6502000111 (cont)
75-27-4; 75-71-8; 594-04-7; 75-09-2; 696-28-6; 26638-19-7;
26952-23-8; 62-73-7; 60-57-1; 1464-53-5; 84-66-2; 109-89-7;
56-53-1; 94-58-6; 60-51-5; 131-11-3; 77-78-1; 124-40-3;
79-44-7; 62-75-9; 25154-54-5; 25321-14-6; 123-91-1; 828-00-2;
38622-18-3; 142-84-7; 2764-72-9; 298-04-4; 330-54-1; 27176-87-0;
60-00-4; 1031-07-8; 959-98-8; 33213-65-9; 115-29-7; 7421-93-4;
72-20-8; 106-89-8; 2104-64-5; 136-25-4; 563-12-2; 141-78-6;
140-88-5; 75-00-3; 60-29-7; 97-63-2; 62-50-0; 56-38-2;
100-41-4; 107-12-0; 106-93-4; 107-06-2; 75-21-8; 96-45-7;
107-15-3; 151-56-4; 1185-57-5; 14221-47-7; 7705-08-0;
7783-50-8; 10421-48-4; 10028-22-5; 10045-89-3; 7758-94-3;
7720-78-7; 206-44-0; 86-73-7; 7782-41-4; 75-69-4; 50-00-0;
64-18-6; 110-17-8; 110-00-9; 98-01-1; 86-50-0; 1024-57-3; 76-44-8;
118-74-1; 87-68-3; 58-89-9; 77-47-4; 67*72-1; 70-30-4; 1888-71-7;
757-58-4; 302-01^2; 7647-01-0; 74-90-8; 7664-39-3; 74-90-8;
7783-06-4; 75-60-5; 193-39-5; 74-88-4; 7439-89-6; 9004-66-4;
78-83-1; 624-83-9; 78-59-1; 78-79-5; 54590-52-2; 120-58-1;
115-32-2; 143-50-0; 303-34-4; 301-04-2; 3687-31-8; 7758-95-4;
7783-46-2; 13814-96-5; 10101-63-0; 10099-74-8; 7446-27-7;
1072-35-1; 1335-32-6; 7446-14-2; 1314-87-0; 592-87-0; 7439-92-1;
58-89-9; 7439-93-2; 14307-35-8; 108-39-4; 108-38-3; 121-75-5;
110-16-7; 108-31-6; 123-33-1; 109-77-3; 7439-96-5; 148-82-3;
2032-65-7; 592-04-1; 10045-94-0; 7783-35-9; 592-85-8;
10415-75-5; 628-86-4; 7439-97*6; 74-93-1; 67-56-1; 91-80-5;
16752-77-5; 72-43-5; 126-98-7; 79-22-1; 71-55-6; 78-93-3;
1338-23-4; 60-34-4; 74-88-4; 108-10-1; 74-93-1; 80-62-6;
298-00-0; 56-04-2; 7786-34-7; 315-18-4; 2385-85-5; 7439-98-7;
75-04-7; 74-89-5; 150-68-5; 494-03-1; 71-36-3; 84-74-2;
70-25-7; 759-73-9; 684-93-5; 615-53-2; 924-16-3; 621-64-7;
1116-54-7; 55-18-5; 62-75-9; 86-30-6; 100-75-4; 930-55-2;
103-85-5; 107-10-8; 300-76-5; 91-20-3; 1338-24-5; 7785-20-8;
12612-55-4; 7718-54-9; 557-19-7; 12054-48-7; 13138-45-9;
7786-81-4; 7440-02-0; 54-11-5; 4726-14-1; 14797-55-8; 7697-37-2;
10102-43-9; 98-95-3; 10102-44-0; 10102-44-0; 10544-72-6; 55-63-0;
25154-55-6; 684-93-5; 59-89-2; 95-48-7; 90-05-1; 636-21-5; 95-47-6;
152-16-9; 20816-12-0; 10028-15-6; 59-50-7; 106-47-8; 106-44-5;
106-46-7; 60-11-7; 100-01-6; 106-42-3; 30525-89-4; 123-63-7;
4685-14-7; 56-38-2; 12674-11-2; 11104-28-2; 11141-16-5; 53469-21-9;
12672-29-6; 11097-69-1; 11096-82-5; 608-93-5; 76-01-7; 82-68-8;
87.86-5; 127-18-4; 72-56-0; 62-44-2; 85-01-8; 578-94-9; 108-95-2;
696-28-6; 103-S2-2; 62-38-4; 298-02-2; 75-44-5; 7803-51-2;
7664-38-2; 7723-14-0; 10025-87-3; 1314-80-3; 1314-80-3;
7719-12-2; 7723-14-0; 88-99-3; 85-44-9; 51-03-6; 7784-41-0;
10124-50-2; 7778-50-9; 7789^00-6; 151-50-8; 1310-58-3;
7722-64-7; 506-61-6; 23950-58-5; 1918-16-7; 109-98-8;
2312-35-8; 79-09-4; 123-62-6; 107-12-0; 75-56-9; 114-26-1;
75-56-9; 129-00-0; 121-29-9; 110-86-1; 91-22-5; 13982-63-3;
15262-20-1; 10043-92-2; 50-55-5; 108-46-3; 299-84-3; 83-79-4;
78-48-8; 81-07-2; 94-59-7; 7783-00-8; 12640-89-0; 7446-34-6;
7782-49-2; 630-10-4; 506-64-9; 7761-88-8; 7440-22-4; 93-72-1;
122-34-9; 7440-23-5; 7631-89-2; 7784-46-5; 26628-22-8; 10588-01-9;
1333-83-1; 7631-90-5; 7775-11-3; 143-33-9; 25155-30-0; 7681-49-4;
843
-------
Accession Ho. 6502000111 Ccont)
62-74-8; 16721-80-5; 1310-73-2; 7681-52-9; 124-41-4; 7632-00-0;
7558-79-4; 7601-54-9; 10102-18-8; 7440-23-5; 8001-50-1; 7789-06-2;
1314-96-1; 57-24-9; 57-24-9; 100-42-5; 7446-09-5; 10025-67*9;
7664-93-9; 72-54-8; 127-18-4; 127-18-4; 56-23-5; 3689-24-5;
78-00-2; 107-49-3; 109-99-9; 509-14-8; 1314-32-5; 563-68-8;
29809-42-5; 7791-12-0; 10102-45-1; 7446-18-6; 7440-28-0; 62-55-5;
23564-05-8; 79-19-6; 62-56-6; 137-26-8; 26471-62-5; 108-88-3;
25376-45-8; 8001-35-2; 2303-17-5; 75-25-2; 52-68-6; 25323-89-1;
79-01-6; 79-01-6; 75-69-4; 75-70-7; 25167-82-2; 27323-41-7;
121-44-8; 1582-09-8; 75-50-3; 99-35-4; 126-72-7; 72-57-1;
50-31-7; 66-75-1; 7440-61-1; 541-09-3; 10102-06-4; 51-79-6;
11115-67-6; 1314-62-1; 7440-62-2; 27774-13-6; 108-05-4;
75-01-4; 75-35-4; 1330-20-7; 1300-71-6; 557-34-6; 1332-07-6;
7699-45-8; 3486-35-9; 7646-85-7; 7783-49-5; 557-41-5;
7779-86-4; 7779-88-6; 127-82-2; 1314-84-7; 16871-71-9;
7733-02-0; 7440-66-6; 13746-89-9; 16923-95-8; 14644-61-2;
10026-11-6
(CRN) Contact naae(s): Heller,S. ; Heller,S. ; Heller,S.
(ROR) Responsible Organization: Office of Research and
Development.Offlee of Health Research.Health Effects Search La
844
-------
Accession No. 6503000108
(DQ) Date of Questionaire: 12-02-82
CHAN) Have of Data Base of Model: Health Effects Research
Laboratory-Cincinnati, OH Aggregate
(ACR) Acronym of Data Base or Model: HERL-CIN
(MED) Media/Subject of Data Base or Model: Drinking Hater ^Effluents
industrial, publicly owned treatment uorks j Enissions uater
reclamation plant ;Solid waste }Surface water lakes, reservoirs,
coastal, influent Tissue humans, animals yother Mortality rates,
cancer rates
(ABS) Abstract/Overview of Data Base or Model: HERL Cincinnati's
project files cover BOre than 300 research projects. Over
one-third of these include environmental measurement data.
Individual project data is reported in published reports and
sometimes incorporated in automated data bases maintained by
other laboratories. This summary covers the environmental
measurement data only.
(CTC) CONTACTS: Subject matter varies by project;
Computer-related varies by project
(DTP) Type of data collection or monitoring: Point source data
collection uater supplies and mammals (primarily)
(STA) Data Base status: Discontinued
(NPP) Non-pollutant parameters included in the data base: Biological
data ;Chemical data ^Collection method ;Concentration measures ;
Exposure data ;Geographic subdivision ;Health effects ;Location ;
Physical data ^Political subdivisions population demographics ;
population density ^Sampling date ;Test/analysis method
;epidemiological
(DS) Time period covered by data base: 07-01-71 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Other varies by
individual project from very short term observa- tions to those
requiring several years*
(NOB) Number of observations in data base: 50000 or more.(Estimated)
(NEI) Estimated annual increase of observations in data base: (unknown.
(INF) Data base includes: Raw data/observations ;Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 3000
(or more.)
(NCS) No. stations or sources currently originating/contributing data:
103 (or more.)
(NOF) Number of facilities covered in data base (source monitoring): 18
4 (or more.)
(GEO) Geographic coverage of data base: Geographic region varies by
project
(LOC) Data elements identifying location of station or source include:
varies by project
(FAC) Data elements identifying facility Include: varies by project
(CDE) Pollutant identification data are: Other coding scheme
Oneoded
(LIM) Limitation/variation in data of which user should be aware: Data
base includes more than 150 studies each with difference
parameters, area, period, and protocols. Quality assurance aspects
845
-------
Accession Ro. 6503000108 (cent)
of data*
(AMD Lab analysis based on EPA-approved or accepted Methods? YES
(AOD) Lab Audit: Lab audit Is satisfactory for varies by project.
(PRE) Precision: Precision and accuracy estimates partially exist for
varies by project Edit varies by project.
CCBY) Data collected by: EPA lab Health Effects Research
Lab-Cincinnati, OH (31%) ^Contractor lab various Contractor various
(24%) ;various grantees (25%) and cooperative agreements (20%)
(ABT) Tata analyzed by: EPA lab Health Effects Research
Lab-Cincinnati, OH (31%)
Contractor lab various
Contractor various (24%)
grantees (25%) and cooperative agreements (20%)
(IOL) Laboratory identification: YES
(PR2) Secondary purpose of data collection: Trend assessment
(AUT) Authorization for data collection: No statutory requirement:
Data collection requirement is usually not—varies by project
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Published in
open scientific literature as project summaries and reports and
various unpublished reports.
(NOS) Number of regular users of data base: 100 or more
(OSR) Current regular users of data base: EPA headquarter offices
office of Toxic Substances, Office of Hater and Haste Management
EPA laboratories
Other federal agencies
universities
(CMF) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for some data
(DLC) Primary physical location of data: principal investigator
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Other varies by
project
(RDBEPA) Related EPA data bases used in conjunction yith this data base
Uaterdrop D6404000110
(CMP) Completion of form:
James B. Lucas
OFC: Health Effects Research Laboratory
AD: U.S. EPA, 26 H. St. Clair St., Cincinnati, OH 45268
PR: (513) 684-7359
(DF) Date of form completion: 02-07-83
(MMAT) lumber of substances represented in data base: 58
(MCAS) lumber of CAS registry numbers in data base: 19
(MAT) Substances represented in data base:
alkalinity asbestos<1332-21-4>
aerosols bacteria
alumlnum<7429-90-5> calcium
arsenic<7440-38-2> carbon
artificial sweetners carbon monoxide<630-08-0>
846
-------
Accession Ho. 6503000108 (cont)
carcinogens sludge
coal strontium<7440-24-6>
coliforms sulfur
conductivity teratogens
diseases tin
drinking water contaminants trace metals
endotoxin viruses
giardia uasteuater
hardness barium<7440-39-3>
heavy metals benzene<71-43-2>
hepatitis cadmium<7440-43-9>
inorganics chlorine<7782-50-5>
magnesium chloroform<67-66-3>
methane copper<7440-50-8>
microorganisms fluorides
mutagens formaldehyde<50-00-0>
organics iron<7439-89-6>
parasites lead<7439-92-l>
pesticides nitrogen<7727-37-9>
polyphosphates pH
rddionuclides potassium<7440-09-7>
radium sodium<7440-23-5>
reclaimed vater styrene<100-42-5>
silicon zinc<7440-66-6>
(CAS) CAS registry numbers of substances Included in data base: 7429-90
-5; 7440-38-2; 1332-21-4; 630-08-0; 7440-24-6; 7440-39-3;
71-43-2; 7440-43-9; 7782-50-5; 67-66-3; 7440-50-8; 50-00-0;
7439-89-6; 7439-92-1; 7727-37-9; 7440-09-7; 7440-23-5;
100-42-5; 7440-66-6
(CNN) Contact name(s): project/I.; project,M.
(COR) Contact organization: Health Effects Research Lab-Cincinnati, OH
(ROR) Responsible Organization: Office of Research and
Development.Office of Health Research.Toxicology & Nicrobiolog
847
-------
Accession Mo. 6606000506
(DQ> Date of Questionaire: 12-02-82
(NAM) Mane of Data Base of Model: PRESTO
(ACR) Acronym of Data Base or Model: PRESTO
(NED) Media/Subject of Data Base or Model: Ground water ; runoff-
water from waste burial
(IBS) Abstract/Overview of Data Base or Model: Low level Hater
Transport & Health Effect Model
(CTC) CONTACTS: Subject matter j. Broadway FTS-534-761S ;
Computer-related J. Broadway FTS-534-7615 ; EPA Office J.
Broad way FTS-534-7615
(DTP) Type of data collection or monitoring: Non-point source
(STA) Data Base status: Funded for Development: projected operational
date of data base 83-03.
(6RP) Groups of substances represented in Data Base: 18 radioactive
(MPP) Non-pollutant parameters included in the data base: Health
effects } temperature
(OS) Time period covered by data base: 01-75 TO 01-80
(PRQ) Frequency of data collection or sampling: Ongoing:as needed
(•OB) Number of observations in data base: SOOCEstimated to Date)
(RED Estimated annual Increase of observations in data base: 100
(INF) Data base includes: reference data or citations
(NTS) Total number of stations or sources covered in data base: 10
(NCS) Ho. stations or sources currently originating/contributing data:
3
(HOP) Number of facilities covered in data base (source monitoring): 10
(GEQ) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source Include:
State ; city
(FAC) Data elements identifying facility include: plant or facility
name ; plant location
(COS) Pollutant identification data are: coded, other coding scheme
(LIN) Limitation/variation in data of which user should be aware: throu
ghout OSA
(DPR) Data collect./anal, procedures conform to ORD guidelines: YES
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: N/A: data not based on laboratory analysis
(PRE) Precision: None available
(EOT) Edittlng: No known edits
(CBY) Data collected by: Contractor Lab, OBML
(ABY) Data analyzed by: Contractor Lab, ORNL
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: development of regulations
or standards
(PR2) Secondary purpose of data collection: None
(AGT) Authorization for data collection: NO
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
NO
(REP) Form of available reports and outputs of data base: Publications,
Inpress
(NOS) Number of regular users of data base: in development
(OSR) Current regular users of data base: EPA Headquarters Offices,
Office of Radiation Programs
848
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Accession Mo. 6606000506 (cont)
(CNF) Confidentiality of data and Units on access: Hone
fDLC) Primary physical location of data: Contractor
(DST) Fora of data storage: Magnetic tape
(DAC) Type of data access: Manually only
(CHG) Direct charge for non-EPA use? MO
(UPDT) Frequency of data base aaster file up-date: When revisions are
available
(RSS) Related EPA automated systems which use data base: None
(RDBEPA) Related EPA data bases used in conjunction with this data base
Mone
(RDB) Non-EPA data bases used in conjunction uith this data base: lone
(CMP) Completion of fora: f J. Broaduayf OFC: EERF, Montgoaery, ALff
PH: (205) 272-3402f
(OF) Date of fora completion: 01-13-83
(RMAT) Nuaber of substances represented in data base: 18
(MCAS) Nuaber of CAS registry nuabers in data base: 0016
(MAT) Substances represented in data base:
Bariua 140 <14798-08-4> Uraniua 238 <7440-61-1>
Carbon 14 <14762-75-5> Plutoniua 238
Cesiua 137 <10045-97-3> Plutoniua 239 <15117-48-3>
Iodine 129 <15046-84-l> Potassiua <7440-09-7>
Iodine 131 <10043-66-0> Radiokrypton
Krypton 85 <13983-27-2> Radioxenon
Tritium <10028-17-8> Radiun 226 <13982-63-3>
Oraniua 234 <13966-29-5> Strontiua 89 <14158-27-l>
Uranium 235 <15117~96-1> Strontiua 90 <10098-97-2>
(CAS) CAS registry nuabers of substances included in data base: 14798-0
8-4; 14762-75-5; 10045-97-3; 15046-84-1; 10043-66-0;
13983-27-2; 10028-17-8; 13966-29-5; 15117-96-1; 7440-61-1;
13981-16-3; 15117-48-3; 7440-09-7; 13982-63-3; 14158-27-1;
10098-97-2
(CNN) Contact naae(s): Broadway, J. ; Broadway,J. ; Broad way/J.
(COR) Contact organization: J. Broadway
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Radiation Prograas.Eastern Environaental
849
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Accession No. 6606000507
(OQ) Date of Questionaire: 12-02-82
(MAN) Hame of Data Base of Model: Environmental Radiation Ambient
Monitoring System
(ACR) Acronym of Data Base or Model: CAA
(MED) Media/Subject of Data Base or Model: Air ; atmospheric
deposition ; drinking nater ; ground water > surface water (river
water) ; Other- milk
(ABS) Abstract/Overview of Data Base or Model: Ambient levels of
radiation in air, milk, water. Common fission products and
actinides included.
(CTC) CONTACTS: Subject Batter J. Broadway FTS-534-7615 ;
Computer-related J. Broadway FTS-534-7615 j EPA Office Charles
R. Porter Director* Eastern environmental Research Facility
534-7615
(DTP) Type of data collection or monitoring: Ambient
(STA) Data Base status: Presently Operational/Ongoing
(GRP) Groups of substances represented in Data Base: 18 radioactive
(NPP) Non-pollutant parameters included in the data base: Location ;
Types of Radiochemical Analysis used.
(DS) Time period covered by data base: 07-73 TO 01-83
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Ongoing:monthly }
ongoing:quarterly ; ongoing:annually
(NOB) Number of observations in data base: 20,000(Actual to Date)
(NEI) Estimated annual increase of observations in data base: 2,000
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 200
(NCS) No. stations or sources currently originating/contributing data:
200
(HOF) Number of facilities covered in data base (source monitoring): 20
0
(GEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
(FAC) Data elements identifying facility include: coded, other coding
scheme , . ,,.
(LIM) Limitation/variation in data of which user should be aware: All
over USA
(DPR) Data collect./anal, procedures conform to ORD guidelines: YES
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: YES
(PRE) Precision: YES, for all measurements
(EOT) Editting: YES, documented edits
(CBY) Data collected by: State agency, all States
(ABY) Data analyzed by: EPA Lab SERF, EPA, Montgomery
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection:
6606000507 40
(AUT) Authorization for data collection: YES, citation- Clean Air Act
ammended 1977.
(OMB) Data colleeted/submitted using OMB-approved EPA reporting forms.
NO
850
-------
Accession Ho* 6606000507 (cont)
(REP) For* of available reports and outputs of data base: Unpublished
reports Environmental Data Reports ; on-line computer terminal
(IDS) number of regular users of data bases 300
(OSR) Current regular users of data base: SPA Headquarters Offices,
Office of Radiation Programs
(CNF) Confidentiality of data and limits on access: Hone
(DLC) Primary physical location of data: EPA Lab
(DST) Form of data storage: Magnetic tape
(DAC) Type of data access: EPA Software System CAA, Hardware POP-1745
(CHG) Direct charge for non-EPA use: NO
(UPDT) Frequency of data base master file up-date: Monthly
(RSS) Related EPA automated systems which use data base: Hone
(ROBEPA) Related EPA data bases used in conjunction with this data base
Hone
(ROB) Non-EPA data bases used in conjunction with this data base: None
(CMP) Completion of form: f J. Broadway! OFC: EBRF/ Montgomery, AL
36193f AD: P.O. Box 3009, Montgomery, AL 361931 PR: (205)
272-34021
(OF) Date of form completion: 01-13-83
(NMAT) Number of substances represented in data base: 18
(NCAS) Number of CAS registry numbers in data base: 0016
(MAT) Substances represented in data base:
Barium 140 <14798-08-4> Uranium 238 <7440-61-1>
Carbon 14 <14762-75-5> Plutonium 238 <13981-16-3>
Cesium 137 <10045-97-3> Plutonium 239 <15117-48-3>
Iodine 129 <15046-84-l> Potassium <7440-09-7>
Iodine 131 <10043-66-0> Radlokrypton
Krypton 85 <13983-27-2> Radioxenon
Tritium <10028-17-8> Radium 226 <13982-63-3>
Uranium 234 <13966-29-5> Strontium 89 <14158-27-l>
Uranium 235 <15117-96-l> Strontium 90 <10098-97-2>
(CAS) CAS registry numbers of substances included in data base: 14798-0
8-4> 14762-75-5; 10045-97-31 15046-84-1; 10043-66-0;
13983-27-2; 10028-17-8; 13966-29-5; 15117-96-1; 7440-61-1;
13981-16-3; 15117-48-3; 7440-09-7; 13982-63-3; 14158-27-1;
10098-97-2
(CNM) Contact name(s): Broadway,J. ; Broadway,J. ; Porter,C.R.
(COR) Contact organization: Eastern Environmental Radiation Facility
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Radiation Programs.Eastern Environmental
851
-------
Accession No. 7103000901
(DQ) Date of Quest!onaire: 12-02*82
(•Ml) Name of Data Base of Model: Chemical Substances Infornation
Hetvork
(ACR) Acronym of Data Base or Model: CSIM
(MED) Media/Subject of Data Base or Model: Other CSIN to allow access
to many kinds of existing resources carrying data and
information on all the Media.
(ABS) Abstract/Overview of Data Base or Model: CSIH provides a
coordinated approach to the identification, location, accessing,
processing, and analysis of data and inforaation on chemical
substances and how they impact humans and other compartments of
the environment. The Hetwork alloys and encourages user
interaction with data and information resources which are
geographically scattered and available in systems which are
independent and autonomous for its computers and software selected.
Most of the complex interfacing steps previously required to make
use of such computerized information resources have been made
transparent to the user.
(CTC) C01TACTS: Subject matter Sidney Siegel (202)382-22561
Computer-related Dr. Sidney Siegel (202)382-2256 ; EPA Office
Office of CSIH Administration (202)382-2256
(DTP) Type of data collection or monitoring: Combination/Other CSIH
offers access to many data bases carrying data & information from
various sources.
(STA) Data Base status: Operational Prototype form.
(DPO) Projected operational date of Data Base: 11-01-81
(GRP) Groups of substances represented in Data Base: 43 air priority
chemicals >5 HESHAPS >7 criteria NAAQS ;3 HID CAA > 18
radioactive ;noise ;129 307 CHA ;11 conventional water ;41 CHA
potential criteria } 21 drinking water standards ;9 potential
drinking water ;29 drinking water monitoring ; 299 hazardous
substances ;48 cancelled pesticides ;9 monitoring pesticides ;
54 TSCA assessment ;RCRA hazardous wastes ;16 Pre-fiPAR ;15 metals
CHPP) Hon-pollutant parameters included in the data base: Biological
data ;Chemical data Collection method ;Compliance data ;
Concentration measures ;Cost/economic data /Discharge points J
Disposal /Elevation /Exposure data /Flow rates /Funding data ;
Geographic subdivision ;Bealth effects ;Industry /Inspection data /
Location /Manufacturer ;Physical data ;Political subdivisions ;
Population demographics population density /Precipitation
/Production levels / Salinity ;Sampling date /Site description
/Temperature /Test/analysis method / Treatment devices /Use
/?olume/mass measures /Hind direction ; Hind velocity /Presence
of data elements varies by resource (data base)
(DS) Time period covered by data base: 01-01-70 TO 01-30-83
CTRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: Other frequency of
collection, sampling, updating dependent on rate established by
each Information resource accessible through the network*
(HOB) Number of observations in data base: 25 million(Estimated)
(HEI) Estimated annual increase of observations in data base: 2.5-5.0
(million)
852
-------
Accession Mo. 7103000901 (cont)
(IMF) Data base includes: Ran data/observations ^Summary aggregate
observations ;Reference data/citations varies by resource/data
base
(NTS) Total number of stations or sources covered in data base: 8-10
(resources)
(HCS) Ho. stations or sources currently originating/contributing data:
7
(HOP) Number of facilities covered in data base (source monitoring): (»
/A)
(GEO) Geographic coverage of data base: International ;national
(LOG) Data elements identifying location of station or source include:
State ^County ;Congressional district ;SMSA jCity ;Town/township ;
Street address ^Coordinates ;Project identifier ;varies by
resource/data base
(FAC) Data elements identifying facility include: Plant facility name
jPlant location ;Parent corp name ;Parent corp location ; Street
address ;SIC code ;Dun Bradstreet ;SCC ;HPDES ^Program identifier ?
varies by resource/data base
(COE) Pollutant identification data are: CAS registry number
(LlM) Limitation/variation in data of which user should be auare: The
prototype, operational '81, includes NLM (Medlars Cheallne, etc.)
CIS CAS-ON-LINE, SDC(ORBIT), MACS, Conditional with DIALOGUE,
BRS, ETIS/HAZARDLINE, TONS, & PROPHET. 5-7 additional resources
will be added in calendar *83. For each resource accessable
through the network usually a statement made when its system is
first accessed will speak to differences in periods of
sampling, numbers of observations, experimental protocols, quality
assurance procedures followed & levels of documentation, etc.
(DpR) Data collect./anal, procedures conform to ORD guidelines: QRD
Guidelines ;sampling plan documented ^Collection method documented
; Analysis method documented jQA procedures documented (Above
varies by resource/data base.) •
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AOD) Lab Audit: Lab audit is satisfactory but varies by data base.
(PRE) Precision: Precision and accuracy estimates partially exist for
some resources/data bases Edit for some resources, not for
others. •
(CBY) Data collected by: Self reporting ;Local agency ;State agency
^Regional office ; EPA lab ^Contractor lab Contractor >Other
federal agency 7EPA headquarters ; collector varies by
resource/data base
(ABY) Data analyzed by: Self reporting
Local agency
State agency
Regional office
EPA lab
Contractor lab
Contractor
Other federal agency
EPA headquarters
analyzer varies by resource/data base
(IDL) Laboratory identification: YES
853
-------
Accession Mo. 7103000901 (coat)
(AOT) Authorization foe data collection: Statutory authorization is P
L 94-469, Sections 10 & 25. Each resource has its own
authorization.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data base: Publications
overview documents, technical user documents, CSIH Directory
Unpublished reports
Printouts on request
Microfila
Machine-readable ran data
On-line coaputer
Outputs available vary by resource/data base.
(HUS) Ruaber of regular users of data base: 10-50 offices
(OSR) Current regular users of data base: EPA headquarter offices
Office of Pesticides and Toxic Substances Office of Toxic
Integration
EPA regional offices
EPA laboratories
Other federal agencies
States
industry, acadeaia, and other nations.
(CMF) Confidentiality of data and 11*its on access: Limits on access
within EPA and outside agency for some data
-------
Accession Mo. 7103000901
(cont)
(MCAS) Nuaber of CAS registry nuabers
(NAT) Substances represented in data
"0, 0-diethyl phosphoricacid,0-p-
nltrophenyl ester<311-45-5>
0,0-diethyl-O-(2-pyrazinyl>
phoshorothioO,0-diethyl-s-(2-
ethylthio)ethyl)ester of
phosphorodithioicacid
0,0-diethyl-s-»ethyl ester of phos
If If\f2-tetrachloroethane
<630-20-6>
l,l,l-trichloroethane<71-55-6>
1,1,2,2,-tetrachloroethane
<79-34-5>
l,l,2-trlchloro«thane<79-00-5>
I/l-dichloro«thane<75-34-3>
l,l-dichloro«thylene<75-35-4>
l,l-di«ethylhydrazine<57-l4-7>
I/12-trichloroethene<79-01-6>
l,2,3,4,10,10-hexachloro-l,4,4a,5,
8,8a-hexahydro-l, 4:5, 8-endo,
endo-dinetha
l/2/4/-trichlorobenzene<120-82-l>
1/2,4/5-tetrachlorobenzene
<95-94-3>
l/2-dibro«o-3-chloropropane (dbcp)
<96-12-8>
lf 2-dibroraoe thane<106-93-4>
If2-dichlorobenzene<95-50-l>
It2-dichloroethane<107-06-2>
U2-dichloropropane<78-87-5>
if2-diethyIhydrazine<1615-80-l>
1,2-di»ethylhydrazine<540-73-8>
1^2-diphenylhydrazlne<122-66-7>
1^2-propanediol<57-55-6>
1,2-trans-dichloroethylene
<156-60-5>
1,3,4 trichlorobenzene<120-82-l>
l,3-dichlorobenzene<541-73-1>
If3-dichloropropene< 542-75-6>
I/3-pentadiene<504-60-9>
1,3-propane sultone<1120-71-4>
1, 4-dichloro-2-bu t ene< 110-57-6>
If4-dlchlorobenzene<106-46-7>
If4-dioxane<123-91-1>
If4-naphthoquinone<130-15-4>
l-(o-chlorophenyl)thiourea
<5344-82-l>
l-(p-chlorobenzoyl)-5-«ethoxy-2-
•ethylindole-3-acetic acid
in data base: 724
base:
l-chloro-2,3-epoxypropane
<106-89-8>
l-naphthyl-2-thiourea<86-88-4>
l-naphthyla«ine<134-32-7>
2/2-dlchloropropionic acid
<75-99-0>
2,3/4,6-tetrachlorophenol<58-90-2>
2/4,5-t anines
2,4,5-t esters
2,4,5-t salts
2,4,5-tp acid esters
2,4,5-trichlorophenol<95-95-4>
2,4,5-trichlorophenoxyacetic acid
(T)<93-76-5>
2,4,5-trlchlorophenoxypropionic
acid (TPX93-72-l>
2/4,6-trlchlorophenol<88-06-2>
2,4/7/8-tetrachlorodibenzo-p-
dloxin (tcdd)
2,4-d acid<94-75-7>
2,4-d esters
2/4-dlchlorophenol<120-83-2>
2f4-dlchlorophenoxyacetic acid (2,
4-d)<94-75-7>
2/4-diicthylphenol<105-67-9>
2f4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2f4-dithiobiuret<541-53-7>
2/6-dichlorophenol<87-65-0>
2,6-dinitrotoluene<606-20-2>
2-acetyla«lnoflourene
2-butanone peroxide<1338-23-4>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-cyclohexyl-4x6-dinitrophenol
<131-89-5>
2-fluoroacetaraide (l081)<640-19-7>
2-»ethyl-2-(«ethylthlo)propionalde
hyde-o-(aethylcarbonyl)oxiae
<80-62
-6>
2-«ethylaziridine<75-55-8>
2-«ethyllactonitrile<75-86-5>
2-naphthyla«lne<91-59-8>
2-nltrophenol<88-75-5>
2-nitropropane<79-46-9>
2-plcoline<109-06-8>
2-propyn-l-01<107-19-7>
855
-------
Accession No. 7103000901
(cont)
2- sec butyl- 4, 6-dinitrophenol
<88-85-7>
3, 3 '-dicti! orobenzidlne<91-94-l>
3, 3 '-d Uethoxybenzidine
3,3*-diBethyl-l-2-
butanone-0- (dethyl anlno)
carbonyDoxiae
3,3--diBethylbenzidine<119-93-7>
3,4-benzofluoranthene<205-99-2>
3, 4-dlhydroxy-alpha-(«ethylaaino)-
•ethyl benzyl alcohol
3-chloropropipnitrile<542-76-7>
3-Bethylcholanthrene<56~49-5>
39196-18-4>
4,4'-ddd(p,p'tde)
4,4*-dde(p,p'-ddx)<72-55-9>
4,4*-ddt<50-29-3>
4, 4'-aethylene-bis-( 2-chloroanilin
4,6-dinltro-o-cresol<534-52-l>
4-Aminopyr idine<50 4- 2 4-5 >
4-broaophenyl phenyl ether
<101-55-3>
4-chloro-o-toluidine hydrochloride
<3165-93-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
5-(a«inoBethyl)-3-isoxazolol
<27 63-96- 4>
5-nitro-o-toluidine<99-55-8>
8- ( hy droxy aethy 1) 8- «e thoxy-5-
•ethyl-cacaba
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acctaldehyde<7 5-07-0 >
acetic acid<64-19-7>
acetic anhydride<108-24-7>
acetone cyanohydrin<75-86-5>
acetone<67-64-l>
acetonitrile<75-05-8>
ac«tophenone<98-86-2>
acetyl bro«ide<506-96-7>
acetyl chloride<75-36-5>
acid Bist
acidity
acrolein<107-02-8>
acrylaBide<7 9-06-1 >
acrylic acid<79-10-7>
acrylonitrile<107-13-l>
adiplc aci
alachlor<15972-60-8>
aldrin<309-00-2>
alkalinity
allyl alcohol<107-18-6>
allyl chloride<107-05-l>
alpha, alpha-diaethylbenzy Ihydro-
peroxide<80-15-9>
alpha, alpha-diaethylphenethylamlne
<122-09-8>
alpha-chlorotoluene<100-44-7>
aluainuB phosphide<20859*73-8>
aluBinua sulfate< 10043-01 -3>
aluainUB<7429-90-5>
aaitraz (baa»)<33089-61-l>
aBitrole<61-82-5>
awonia<7664-4l-7>
aBBoniua acetate<631-61-8>
aBBoniuB benzoate<1863-63-4>
aBBoniua bicarbonate
aBBoniuB bichro«ate<7789-09-5>
aBBoniuB bif luoridc<1341-49-7>
amoniuB bisulfite<10192-30-0>
aBBoniuB carbaBate
aBBoniuB carbonate<506-87-6>
aBBoniuB chloride<12125-02-9>
amoniuB chroiate<7788-98-9>
aaaoniuB citrate<7632-50-0>
f luoborate<13826-83-0>
fluoride< 12125-01- 8>
aBBoniuB hydroxide<1336-21-6>
aBBoniuB oxalate<1113-38-8>
aBMonluB picrate<131-74-8>
aBBoniuB sillcofluorlde
<16919-19-0>
aaaonluB sulfaBate<7773-06-0>
aaaoniua sulf ide< 12 135-76-1 >
aBBoniuB tartrate<3164-29-2>
aBBoniuB thlocyanate< 1762-9 5-4>
aaaoniUB thiosulf ate<7783-18-8>
a«yl acetate<628-63-7>
anlllne<62-53-3>
anthracene<120-12-7>
antiaony pentachlorlde<7647-18-9>
antiaony potassiua tartrate
antimony tribroBide<7789-61-9>
antiBony trlchloride<10025-91-9>
antiBony trif luoride<7783-56-4>
antiaony trioxide<1309-64-4>
antiaony<7440-36-0>
araBite<140-57-8>
arsenic acid<1327-52-2>
856
-------
Accession No. 7103000901
(cont)
arsenic dlsulf ide<1303-32-8>
arsenic pent oxide< 1303-28- 2>
arsenic trichloride< 77 84-3 4-l>
arsenic trioxide<1327-53-3>
arsenic trisulfide<1303-33-9>
arsenic<7440-38-2>
asbestos<1332-21-4>
atrazine
auramine<2465-27-2>
azaserine<115-02-6>
banvel-d
bariuB 140<14798-08-4>
bariua cyanide<542-62-l>
bariua<7440-39-3>
b«nefin<1861-40-l>
benoayl<17804-35-2>
benz(c)acridine<225-51-4>
benzac
benzal chl or ide< 98-87- 3>
benzene<71-43-2>
benzenesulfonyl chloride<98-09-9>
benzenethiol<108-98-5>
benzi dine<92-87-5>
benzo( a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h,i)perylene<191-24-2>
benzo
benzoic acid<65-85-0>
benzonitrile<100-47-0>
benzotrichloride<98-07-7>
benzoyl chloride<98-88-4>
benzyl chloride<100-44-7>
beryllium chloride<7787-47-5>
berylliuM dust
beryllium fluoride<7787-49-7>
beryllium nitrate<13597-99-4>
berylliuB<7440-41-7>
bhc (lindane)-ga»aia<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
biphenyl<92- 52-4>
bis(2-chloroethoxy)«ethane
bis(2-ehloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloro«ethyl)ether<542-88-l>
bisvuth co»pounds<7440-69-9>
boron co«pounds<7440-42-8>
bromine<7726-95-6>
bro»oacetone<598-31-2>
bromobenzene<108-86-l>
bromochlorobenzene<28906-38-9>
broBOdichloroBethane<75-27-4>
broBoaethane<74-83-9>
brucine<357-57-3>
butachlor<23184-66-9>
butyl acetate<123-86-4>
butyl benzyl phthalate<85-68-7>
butyla«ine<109-73-9>
butyric acid<107-92-6>
cacodylic acid and salts<75-60-5>
cadaiuB acetate<543-90-8>
cadaiuB bromide<7789-42-6>
cadaiua chloride
cadmiu«<7440-43-9>
calciUB arsenate<7778-44-l>
calciua arsenite<52740-16*6>
calciuB carbide<75*20-7>
calciua chroaate<13765-19-0>
calciua cyanide<592-01-8>
calciu* dodecylbenzenesulfonate
<26264-06-2>
calciua hydroxide<1305-62-0>
calciua hypochlorite<7778-54-3>
calciua oxide<1305-78-8>
captan<133-06-2>
c arbaryl<63-25-2>
carbofuran<1563-66-2>
carbon 14<14762-75-5>
carbon disulfide<75-15-0>
carbon monoxide<630-08-0>
carbon tetrachloride<56-23-5>
carbonyl fluoride<353-50-4>
cesiua 137<10045-97-3>
chloral<75-87-6>
chloraabucil<305-03-3>
chloranil<118-75-2>
chlor dane< 57-7 4-9>
chlorinated naphthalenes
chlorlne<7782-50-5>
chloroacetaldehyde<107-20-0>
chlorobenzene<108-90-7>
chlorobenzilate<510-15-6>
chlorodibroBoaethane<124-48-l>
chloroethane<75-00-3>
chloroethene<75-01-4>
chloroethyl vinyl ether<110-75-8>
chlorofluorocarbons
chlorofora<67-66-3>
chloroaethane<74-87-3>
857
-------
Accession Mo. 7103000901
(cent)
chloroaethyl »ethyl ether
<107-30-2>
chloroprene<126-99-8>
chlorosulfonic acid<7790-94-5>
chlorpyrifos<2921-88-2>
chronic acetate<1066-30-4>
chroaic acid<7738-94-5>
cbroaic sulfate<10101-53-8>
chro*iun<7 440-47-3>
chreaous chloride<10049-05-5>
chrysene<218-Ol-9>
cls-l,2-dlchloroethylene<156-59-2>
coal tar<8007-45-2>
cobalt<7440-48-4>
cobaltous bro«lde<7789-43-7>
cobaltous foraate<544-18-3>
cobaltous 8ulfa«ate<14017-41-5>
copper cyanld«<544-92-3>
copp«r<7440-50-8>
cov>aphos< 56-72- 4>
creosote<8021-39*4>
cr«aol<1319-77-3>
cresylic acl
crotonaldehyde<4170-30-3>
ciuene<98-82-8>
cupric acetate<142-71-2>
cupric acetoarsenite<12002-03-8>
cupric chlorld«<7447-39-4>
cupric nitrate<3251-23-8>
cupric oxalate<814-91-5>
cupric sulfate auionlated
<10380-29-7>
cupric sulfate<7758-98-7>
cupric tartrate<815-82-7>
cyanazln«<21725-46-2>
cyanlde<57-12-5>
cyanogen bro«ide<506-68-3>
cyanogen chlor ide< 506-77-4>
cyanoyeiK460-l9-5>
cycloh«xane<110-82-7>
cyclohexanone<108-94-l>
cyclopnospha«ide<50-18-0>
dauno»ycin<20830-81-3>
dddCtde)
ddt
d«»eton<8065-48-3>
dl-isopropylfluorophosphate
<55-91-4>
di-n-butyl phthalate<84-74-2>
dl-n-octyl phthalate<117*84-0>
dl-n-propylnitrosaaine<621-64-7>
dialkyl ethers
dialkyl phosphates
dlallate<2303-16-4>
diazinon<333-41-5>
dib«nzo(a,h)anthracene<53-70-3>
dibcnzofuran<132-64-9>
dlbenzol(a,i)pyrene<189-55-9>
dlbro«ocbloromethane<124-48-l>
dibro«o«ethane<74-95-3>
dibutyl phthalate<84-74-2>
dicaaba<1918-00-9>
dichlobeniKl 194-6 5-6 >
dichlone<117-80-6>
dlchlorobenzene<25321-22-6>
dichlorobro»o«ethane<75-27-4>
dlchlorodlfluoro««than«<75-71-8>
dlchlorolodo««thane<594-04-7>
dlchloro««thane<75-09-2>
dlchlorophenylarslne<696-28-6>
dichloropropane<26638-19-7>
dlchloropropene-dlchloropropane
•ixture
dichloroprop«ne< 26952-23-8>
dlchlorvos (ddvp><62-73-7>
dl«ldrln<60-57-l>
dlepoxybutaoe<1464-53-5>
diethyl phthalate<84-66-2>
di«thyla«lne<109-89-7>
dlethylstilbestrol<56-53-l>
d ihydrosafrole<94-58-6>
di«ethoate<60-51-5>
diaethyl phthalate<131-11-3>
dUethyl sulfate<77-78-l>
dl«ethyla«ine<124-40-3>
diaethylcarbaaoyl chloride
<79-44-7>
dU€thylnitrosa«ln«<62-75-9>
dlnitrobenzene<25154-54-5>
dlnltrophenol
dinitrotoluene<25321-14-6>
dloxane<123-91-l>
dioxln<828-00-2>
diphenyl ether<101-84-8>
dlpbenylhydrazlne<38622-18-3>
dlpropyla«lne<142-84-7>
diquat<2764-72-9>
dissolved oxygen
dissolved solids
dIsulfoton<29 8-04-4>
diuron<330-54-l>
dodecylbenzenesulfonic acid
<27176-87-0>
858
-------
Accession Mo. 7103000901
(cont)
ebdc's (ethylenebisdithiocarbaaate
s)
edta<60-00-4>
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endosulfan<115-29-7>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
eplchlorohydrin<106-89-8>
ethion<563-12-2>
ethyl acrylate<140-88-5>
ethyl chloride<75-00-3>
ethyl ether<60-29-7>
ethyl »ethacrylate<97-63-2>
ethyl •ethanesulfonate<62-50-0>
ethyl parathion<56-38-2>
ethylbenzene<100-41-4>
ethylcyanide
ethylene bisdithiocarbavate
ethylene dibroaide Cedb)<106-93-4>
ethylene dichloride<107-06-2>
ethylene oxide<75-21-8>
ethylene thiourea<96-45-7>
ethylenedia«ine<107-15-3>
ethylenei«ine<151-56-4>
fecal colifora
ferric amoniua citrate<1185-57-5>
ferric amoniua oxalate
<14221-47-7>
ferric chloride<7705-08-0>
ferric cyanide
ferric fluoride<7783-50-8>
ferric nitrate<10421-48-4>
ferric sulfate<10028-22-5>
ferrous aaaoniua sulfate
<10045-89-3>
ferrous chloride<7758-94-3>
ferrous sulfate<7720-78-7>
fluoranthene<206-44-0>
fluorene<86-73-7>
fluorides
fluorine<7782-41-4>
fluoroacetic acid/ sodiui salt
fluorotrichloro«ethane<75-69-4>
for«aldehyde<50-00-0>
for»ic acid<64-18-6>
fuaaric acid<110-17-8>
furan<110-00^9>
furfural<98-01-l>
glycidylaldehyde
gross alpha
guthion<86-50-0>
heptachior epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlcrobutadiene<87-68-3>
hex achlorocyclohexane<58-89-9>
hexachlorocyclopentadiene<77*47-4>
hexachloroethane<67-72-l>
hexachlorophene<70-30-4>
hexachloropropene<1888-71-7>
hexaethyl tetraphosphate<757-58-4>
hydrazlne<302-01-2>
hydrocarbons
hydrochloric acid<7647-01-0>
hydrocyanic acid<74-90-8>
hydrofluoric acid<7664-39-3>
hydrogen cyanide<74-90-8>
hydrogen sulfide<7783-06-4>
hydroxydiaethyl arsine oxide
<75-60-5>
indeno (1^ 2,3-cd)pyrene<193-39-5>
iodine 129<15046-84-l>
iodine 13K100 43-66-0 >
iodoaethane<74-88-4>
iron dextran<9004-66-4>
iron<7439-89-6>
isobutyl alcohol<78-83-l>
isocyanic acid, aethyl ester
<624-83-9>
isophorone<78-59-l>
isoprene<78-79-5>
isopropanolaaine dodecylbenzene
sulfonate<54590-S2-2>
isosafrol«<120-58-l>
kelthane<115-32-2>
kepone<143-50-0>
krypton 85<13983-27-2>
1asiocarpine<303-34-4>
lead acetate<301-04-2>
lead arsenate<3687-31-8>
lead chloride<7758-95-4>
lead fluoride<7783-46-2>
lead fluoroborate<13814-96-5>
lead iodide<10101-63-0>
lead nitrate<10099-74-8>
lead phosphate<7446-27-7>
lead stearate<1072-35-l>
lead subacetate<1335-32-6>
lead sulfat
lead sulfide<1314-87-0>
lead thiocyanate<592-87-0>
lead<7439-92-l>
859
-------
Accession Mo. 7103000901
(cont)
lindane<58-89-9>
lithiUB and co»pounds<7439-93-2>
lithiu. chro»ate<14307-35-8>
«-ctesol<108-39-4>
m-xylene<108-38-3>
•alathion<121-75-5>
•aleic acid<110-16-7>
•aleic anhydride<108-31-6>
•aleic hydrazide<123-33-l>
•alononltrile<109-77-3>
»anganese<7439-96-5>
ma nit ad e beta
•ate
•elphalan<148-82-3>
•ercaptodlaethur<2032~65-7>
•ercurie cyanide<592-04-l>
•ercuric nitrate<10045-94-0>
•ercurie sulfate<7783-35-9>
•ercuric thiocyanate<592-85-8>
•ercurous nitrate<10415-75-5>
•ercury ful«inat
•ercury<7439-97-6>
•ethanearsooates
•ethanethlol<74-93-l>
•cthanol<67-56-l>
•«thapyrilcne<91-80-5>
•etiHwyl<16752-77-5>
•ethoxychlor<72-43-5>
•ethyacrylonitril«<126-98-7>
•ethyl chlorocarbonate<79-22-l>
•ethyl chlorofor«<71-55-6>
•ethyl ethyl Ice tone (•ek)<78-93-3>
•ethyl ethyl ketone peroxide
<1338-23-4>
•ethyl hydrazine<60-34-4>
•ethyl iodide<74-88-4>
•ethyl isobutyl ketone<108-10-l>
•ethyl •ercaptan<74-93-l>
•ethyl «ethacrylate<80-62-6>
•ethyl parathion<298-00-0>
•ethylthlouracil<56-04~2>
•evinphos<7786-34-7>
•exacarbate<315-18-4>
•icrobiology colifora bacteria
•irex<2385-85-5>
•olybdenuB and coapounds
<7439-98-7>
•onoethyla»ine<75-04-7>
•onoaethylaaine<74-89-5>
•onuron<150-68-5>
n,n-bis(2-chloroethyl)-2-naphthyla
•ine<494-03-l>
o-alkanes clO-c30
n-butyl alcohol<71-36-3>
n-butyl phthalate<84-74-2>
n-«ethyl-n*-nitro-n-nitrosoguanidi
ne<70-25-7>
n-nitroso-n-ethylurea<759-73-9>
n-nitroso-n-»ethylurea<684-93-5>
n-nitroso-n-«ethylurethane
<615-53-2>
n-nitrosodi-n-butyla«ine<924-16-3>
n-nitrosodi-n-propyla«ine
<621-64-7>
n-nitrosodiethanola«ine<1116-54-7>
n-nitrosodiethyla»ine<55-18-5>
n-nitrosodi«ethyla*ine<62-75-9>
n-nltrosodiphenyla»ine<86-30-6>
n-nitrosoBethylvinylaaine
n-nitrosopiperidine<100-75-4>
n-nitrosopyrrolldine<930-55-2>
n-pheny1thlourea
n-propyla»Ine<107-10-8>
naled<300-76-5>
naphthenic acid<1338-24-5>
nickel a»«oniu« sulfate<7785-20-8>
nickel carbonyl<12612-55-4>
nickel chloride<7718-54-9>
nickel hydroxide<12054-48-7>
nickel nitrate<13138-45-9>
nickel sulfate<7786-81-4>
nlckel<7440-02-0>
nicotine and salts<54-ll-5>
nltralin<4726-14-l>
nitrate<14797-55-8>
nitrates/nitrites
nitric acid<7697-37-2>
nitric oxide<10102-43-9>
nitriloacetates
nitrobenzene<98-95-3>
nitrogen dioxide<10102-44-0>
nitrogen peroxide<10102-44-0>
nitrogen tetroxide<10544-72-6>
ni trogen<7727-37-9>
nitroglycerine<55-63-0>
nitrophenol<25154-55-6>
nltroso«ethylurea<684-93-5>
nitroso«orpholine<59-89-2>
nitrotoluene
nonaphthalene
o-cresol<95-48-7>
o-«ethoxyphenol<90-05-l>
o-toluldine hydrochloride
<636-21-5>
860
-------
Accession Ho. 7103000901
(cent)
o-xy lene<9 5- 47-6>
octane thy Ipyrophosphoraaide (QMPJl)
<152-16-9>
oil and grease
oleyl alcohol condensed with 2
moles ethyl ene oxide
osalua tetroxide<20816-12-0>
oxygen denand
ozore<1002 8-15-6 >
p-chloro-a-cresol< 59-50-7>
p-chloroaniline<106-47-8>
p-cresol<106-44-5>
p-dichlorobenzene<106-46-7>
p-di«ethylaainoazobenzene<60-ll-7>
P-nitroaniline<100-01-6>
P-xylene
PH
paraforaaldehyde<30525-89-4>
paraldehyde< 123-63-7>
paraquat<4685-14-7>
para thiorK 56-38- 2>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorobenzene<608-93-5>
pentachloroethane<76-01-7>
pentachloronitrobenzene (PCNB)
<82-68-8>
pentachlorophenol<87-86-5>
perchloroethylene<127-18-4>
per thane <7 2- 56-0 >
phenacetin<62-44-2>
phenanthrene<85-01-8>
phenarsazine chloride<578-94-9>
phenol<108-95-2>
phenyl dichloroarsine<696-28-6>
phenyl acetic acid<103-82-2>
phenylnercury acetate<62-38-4>
phorate 298-0202
phosgene<75-44-5>
phosophorothioic acid/o/o>
diaethyl ester,o-ester with n,
n-dine thyIbenzene
phosphine<7803-51-2>
phosphoric acid<7664-38-2>
phosphorus and compounds
<7723-14-0>
phosphorus oxychloride<10025-87-3>
phosphorus pentasulfide<1314-80-3>
phosphorus sulfide<13l4-80-3>
phosphorus trichloride<7719-12-2>
photon emitters
phthalic acid<88-99-3>
phthalic anhydride<85-44-9>
plperonyl butoxide<51-03-6>
plutoniua 238<13981-16-3>
Plutonium 239<15117-48-3>
polybroinated biphenyls (PBBs)
polychlorinated biphenyls (PCBs)
potassiu* arsenate<7784-41-0>
potassiua ars«nite<10124-50-2>
potassium bichro«ate<7778-50-9>
potassiuji chro«ate<7789-00-6>
potassiUR cyanide<151-50-8>
potassiua hydroxide<1310-58-3>
potassiua peraanganate<7722-64-7>
potassiua silver cyanide<506-61-6>
potassiua<7440-09-7>
pronaaide<23950-58-5>
propachlor<1918-16-7>
propanil<109-98-8>
proparqite<2312-35-8>
propionlc acid<79-09-4>
propionic anhydride<123-62-6>
propionitrile<107-12-6>
proplyene oxide<75-56-9>
propoxur<114-26-l>
pyrene<129-00-0>
pyrethrin<121-29-9>
pyridine<110-86-l>
quinoline< 91-22-5>
quinones
radiokrypton
radioxenon
radiua 226<13982-63-3>
radium 228<15262-20-1>
radon<10043-92-2>
reserpine<50-55-5>
resorcinol<108-46-3>
ronnel<299-84-3>
rotenone<83-79-4>
saccharin<81-07-2>
861
-------
Accession No. 7103000901
(cont)
safrole<94-59-7>
secondary nines
selenious acid<7783-00-8>
seleniua oxide<12640-89-0>
selenium sulfide<7446-34-6>
seleniuB<7782-49-2>
selenourea<630-10-4>
silver cyanide<506-64-9>
silver nitrate<7761-88-8>
silver<7440-22-4>
sil»ex<93-72-l>
siBazine<122-34-9>
soditui and co»pounds<7440-23-5>
sodium arsenate<7631-89-2>
sodiuB arsenite<7784-46-5>
sodiuB azide<26628-22-8>
sodiua bichro»ate<10588-01-9>
sodiin bifluoride<1333-83-l>
sodiuB bisulfite<7631-90-5>
sodiuB chroBate<7775-ll-3>
sodim cyanlde<143-33-9>
sodiua dodecylbenzenesulfonate
<25155-30-0>
sodiin fluoroacetate (1080)
<62-74-8>
sodiua hydrosulfide
sodiua hydroxide<1310-73-2>
sodiiw hypochlorite<7681-52-9>
sodiin methylate<124-41-4>
sodium nitrite<7632-00-0>
sodlua phosphate^ dibasic
<7558-79-4>
sodiui phosphate^ tribaslc
<7601-54-9>
sodlua selenite<10102-18-8>
sodiu«<7440-23-5>
streptozotocin<18883-66-4>
strobane<8001-50-l>
strontiua 89<14158-27-l>
strontiua 90<10098-97-2>
strontiuB sulfide<1314-96-l>
strychine< 57-24-9>
styrene<100-42-5>
sulfates
suIfides
sulfonaaide
sulfur dioxide<7446-09-5>
sulfur •onochloride<10025-67-9>
sulfurlc acid<7664-93-9>
suspended solids
tde<72-54-8>
terpenes
tetrachloroethylene<127-l8-4>
tetrachloroaethane<56-23-5>
tetraethyl dithiopyrophosphate
<3689-24-5>
tetraethyl lead<78-00-2>
tetraethyl pyrophosphate<107-49-3>
tetrahydofuran<109-99-9>
tetranittOBethane<509-14-8>
thallic oxide<1314-32-5>
thalliua acetate<563-68-8>
thaiHUB carbonate<29809-42-b>
thailiu« chloride<7791-12-0>
thalllua nitrate<10102-45-l>
thalliua selenlte
thalliuB suifate<7446-18-6>
thalliuB<7440-28-0>
thioacetaBide<62-55-5>
thiophanate Bethyl<23564-05-8>
thiose«icarbazide<79-19-6>
thiourea<62-56-6>
thiuraB<137-26-8>
titaniuB<7440-32-6>
toluene diisocyanate<26471-62-5>
tolucne<108-88-3>
toluenediaBine<25376-45-8>
total reduced sulphur
total suspended particulates
toxaphene< 8001-35-2>
triallate<2303-17-5>
tribrOBOBethane<75-25-2>
tributyl phosphorotrithioate
<78-48-8>
trichlorfon<52-68-6>
trichloroethane<25323-89-l>
trichloroethylene<79-01-6>
trichlorofluoro«ethane<75-69-4>
trichloroBethanethiol<75-70-7>
trichlorophenol (TCP)<25167-82-2>
triethanolanine dodecylbenzenesulf
onate<27323-41-7>
triethylaBine<121-44-8>
trifluraline (treflan)<1582-09-8>
triBethylaBine<75-50-3>
trinitrobenzene<99-35-4>
tris(If3-dibroBopropyl)phosphate
<126-72-7>
tritiu»<10028-17-8>
trypan blue<72-57*l>
trysb«n<50-31-7>
turbidity
uracil BUStard<66-75-l>
uraniua 234<13966-29-5>
862
-------
Accession Ho. 7103000901 (cent)
uranium 235<15117-96-l> zinc borate<1332-07-6>
uranium 238<7440-61-1> ziac brOBide<7699-45-8>
uraniun<7440-61-l> zinc carbonate<3486-35-9>
uranyl acetate<541-09-3> zinc chloride<7646-85-7>
uranyl nitrate<10102-06-4> zinc cyanide
urethane<51-79-6> zinc fluoride<7783-49-5>
vanadie acid, aanoniun salt zinc for«ate<557-41-5>
<11115-67-6> zinc hydrosulfite<7779-86-4>
vanadium pentoxide<1314-62-l> zinc nitrate<7779-88-6>
vanadiu»<7440-62-2> zinc phenol sulfonate<127-82-2>
vanadyl sulfate<27774-13-6> zinc phosphide<1314-84-7>
vinyl acetate<108-05-4> zinc silicofluoride<16871-71-9>
vinyl chloride<75-01-4> zinc sulfate<7733-02-0>
vinylidene chloride<75-35-4> zinc<7440-66-6>
xylene<1330-20-7> zirconiui nitrate<13746-89-9>
xylenol<1300-71-6> zirconiu* sulfate<14644-61-2>
zinc acetate<557-34-6> zirconiua tetrachloride
zinc aBBoniuB chloride <10026-ll-6>
(CAS) CAS registry numbers of substances included in data bases 311-45-
5; 630-20-6; 71-55-6; 79-34-5; 79-00-5; 75-34-3; 75-35-4;
57-14-7; 79-01-6; 120-82-1; 95-94-3; 96-12-8; 106-93-4;
95-50-1; 107-06-2; 78-87-5; 1615-80-1; 540-73-8; 122-66-7;
57-55-6; 156-60-5; 120-82-1; 541-73-1; 542-75-6; 504-60-9;
1120-71-4; 110-57-6; 106-46-7; 123-91-1; 130-15-4; 5344-82-1;
106-89-8; 86-88-4; 134-32-7; 75-99-0; 58-90-2; 95-95-4; 93-76-5;
93-72-1; 88-06-2; 94-75-7; 120-83-2; 94-75-7; 105-67-9; 51-28-5;
121-14-2; 541-53-7; 87-65-0; 606-20-2; 1338-23-4; 110-75-8;
91-58-7; 95-57-8; 131-89-5; 640-19-7; 80-62-6; 75-55-8;
75-86-5; 91-59-8; 88-75-5; 79-46-9; 109-06-8; 107-19-7;
88-85-7; 91-94-1; 119-90-4; 119-93-7; 205-99-2; 542-76-7;
56-49-5; 72-55-9; 50-29-3; 101-14-4; 534-52-1; 504-24-5;
101-55-3; 3165-93-3; 7005-72-3; 100-02-7; 2763-96-4; 99-55-8;
83-32-9; 208-96-8; 75-07-0; 64-19-7; 108-24-7; 75-86-5; 67-64-1;
75-05-8; 98-86-2; 506-96-7; 75-36-5; 107-02-8; 79-06-1;
79-10-7; 107-13-1; 124-04-9; 15972-60-8; 309-00-2; 107-18-6;
107-05-1; 80-15-9; 122-09-8; 100-44-7; 20859-73-8; 10043-01-3;
7429-90-5; 33089-61-1; 61-82-5; 7664-41-7; 631-61-8; 1863-63-4;
1066-33-7; 7789-09-5; 1341-49-7; 10192-30-0; 1111-78-0; 506-87-6;
12125-02-9; 7788-98-9; 7632-50-0; 13826-83-0; 12125-01-8?
1336-21-6; 1113-38-8; 131-74-8; 16919-19-0; 7773-06-0;
12135-76-1; 3164-29-2; 1762-95-4; 7783-18-8; 628-63-7; 62-53-3;
120-12-7; 7647-18-9; 11071-15-1; 7789-61-9; 10025-91-9;
7783-56-4; 1309-64-4; 7440-36-0; 140-57-8; 1327-52-2; 1303-32-8;
1303-28-2; 7784-34-1; 1327-53-3; 1303-33-9; 7440-38-2;
1332-21-4; 1912-24-9; 2465-27-2; 115-02-6; 1918-00-9;
14798-08-4; 542-62-1; 7440-39-3; 1861-40-1; 17804-35-2;
225-51-4; 98-87-3; 71-43-2; 98-09-9; 108-98-5; 92-87-5; 56-55-3;
50-32-8; 191-24-2; 207-08-9; 65-85-0; 100-47-0; 98-07-7; 98-88-4;
100-44-7; 7787-47-5; 7787-49-7; 13597-99-4; 7440-41-7; 58-89-9;
319-84-6; 319-85-7; 319-86-8; 92-52-4; 111-91-1; 111-44-4;
39638-32-9; 117-81-7; 542-88-1; 7440-69-9; 7440-42-8; 7726-95-6;
598-31-2; 108-86-1; 28906-38-9; 75-27-4; 74-83-9; 357-57-3;
863
-------
Accession Ho. 7103000901 (cent)
23184-66-9; 123-86-4; 85-68-7; 109-73-9; 107-92-6; 75-60-5;
543-90-8; 7789-42-6; 7440-43-9; 7778-44-1; 52740-16-6;
75-20-7; 13765-19-0; 592-01-8; 26264-06-2; 1305-62-0;
7778-54-3; 1305-78-8; 133-06-2; 63-25-2; 1563-66-2;
14762-75-5; 75-15-0; 630-08-0; 56-23-5; 353-50-4; 10045-97-3;
75-87-6; 305-03-3; 118-75-2; 57-74-9; 7782-50-5; 107-20-0;
108-90-7; 510-15-6; 124-48-1; 75-00-3; 75-01-4; 110-75-8;
67-66-3; 74-87-3; 107-30-2; 126-99-8; 7790-94-5; 2921-88-2;
1066-30-4; 7738-94-5; 10101-53-8; 7440-47-3; 10049-05-5; 218-01-9;
156-59-2; 8007-45-2; 7440-48-4; 7789-43-7; 544-18-3; 14017-41-5;
544-92-3; 7440-50-8; 56-72-4; 8021-39-4; 1319-77-3; 1319-77-3;
4170-30-3; 98-82-8; 142-71-2; 12002-03-8; 7447-39-4; 3251-23-8;
814-91-5; 10380-29-7; 7758-98-7; 815-82-7; 21725-46-2; 57-12-5;
506-68-3; 506-77-4; 460-19-5; 110-82-7; 108-94-1; 50-18-0;
20830-81-3; 8065-48-3; 55-91-4; 84-74-2; 117-84-0; 621-64-7;
2303-16-4; 333-41-5; 53-70-3; 132-64-9; 189-55-9; 124-48-1;
74-95-3; 84-74-2; 1918-00-9; 1194-65-6; 117-80-6; 25321-22-6;
75-27-4; 75-71-8; 594-04-7; 75-09-2; 696-28-6; 26638-19-7;
26952-23-8; 62-73-7; 60-57-1; 1464-53-5; 84-66-2; 109-89-7;
56-53-1; 94-58-6; 60-51-5; 131-11-3; 77-78-1; 124-40-3;
79-44*7; 62-75-9; 25154-54*5; 25321-14-6; 123-91-1; 828-00-2;
101-64-8; 36622-18-3; 142-84-7; 2764-72-9; 298-04-4;
330-54-1; 27176-87-0; 60-00-4; 1031-07-8; 959-98-8; 33213-65-9;
115-29-7; 7421-93-4; 72-20-8; 106-89-8; 563-12-2; 140-88-5;
75-00-3; 60-29-7; 97-63-2; 62-50-0; 56-38-2; 100-41-4;
107-12-0; 106-93-4; 107-06-2; 75-21-8; 96-45-7; 107-15-3;
151-56-4; 1185-57-5; 14221-47-7; 7705-08-0; 7783-50-8; 10421-48-4;
10028-22-5; 10045-89-3; 7758-94-3; 7720-78-7; 206-44-0; 86-73-7;
7782-41-4; 75-69-4; 50-00-0; 64-18-6; 110-17-8; 110-00-9; 98-01-1;
86-50-0; 1024-57-3; 76-44-8; 118-74-1; 87-68-3; 58-89-9; 77-47-4;
67-72-1; 70-30-4; 1888-71-7; 757-58-4; 302-01-2; 7647-01-0;
74-90-8; 7664-39-3; 74-90-8; 7783-06-4; 75-60-5; 193-39-5;
15046-84-1; 10043-66-0; 74-88-4; 9004-66-4; 7439-89-6; 78-83-1;
624-83-9; 78-59-1; 78-79-5; 54590-52-2; 120-58-1; 115-32-2;
143-50-0; 13983-27-2; 303-34-4; 301-04-2; 3687-31-8;
7756-95-4; 7783-46-2; 13814-96-5; 10101-63-0; 10099-74-8;
7446-27-7; 1072-35-1; 1335-32-6; 7446-14-2; 1314-87-0;
592-87-0; 7439-92-1; 58-89-9; 7439-93-2; 14307-35-8; 108-39-4;
108-38-3; 121-75-5; 110-16-7; 108-31-6; 123-33-1; 109-77-3;
7439-96-5; 148-82-3; 2032-65-7; 592-04-1; 10045-94-0; 7783-35-9;
592-85-8; 10415-75-5; 628-86-4; 7439-97-6; 74-93-1; 67-56-1;
91-80-5; 16752-77-5; 72-43-5; 126-98-7; 79-22-1; 71-55-6;
78-93-3; 1338-23-4; 60-34-4; 74-88-4; 108-10-1; 74-93-1;
80-62-6; 298-00-0; 56-04-2; 7786-34-7; 315-18-4; 2385-85-5;
7439-98-7; 75-04-7; 74-89-5; 150-68-5; 494-03-1; 71-36-3; 84-74-2;
70-25-7; 759-73-9; 684-93-5; 615-53-2; 924-16-3; 621-64-7;
1116-54-7; 55-18-5; 62-75-9; 86-30-6; 100-75-4; 930-55-2;
103-85-5; 107-10-8; 300-76-5; 1338-24-5; 7785-20-8; 12612-55-4;
7718-54-9; 12054-48-7; 13138-45-9; 7786-81-4; 7440-02-0;
54-11-5; 4726-14-1; 14797-55-8; 7697-37-2; 10102-43-9; 98-95-3;
10102-44-0; 10102-44-0; 10544-72-6; 7727-37-9; 55-63-0;
25154-55-6; 684-93-5; 59-89-2; 95-48-7; 90-05-1; 636-21-5;
864
-------
Accession Mo. 7103000901 (cont)
95-47-6; 152-16-9; 20816-12-0; 10028-15-6; 59-50-7; 106-47-8;
106-44-5; 106-46-7; 60-11-7; 100-01-6; 106-42-3; 30525-89-4;
123-63-7; 4685-14-7; 56-38-2; 12674-11-2; 11104-28-2;
11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5;
608-93-5; 76-01-7; 82-68-8; 87-86-5; 127-18-4; 72-56-0;
62-44-2; 85-01-8; 578-94-9; 108-95-2; 696-28-6; 103-82-2;
62-38-4; 75-44-5; 7803-51-2; 7664-38-2; 7723-14-0;
10025-87-3; 1314-80-3; 1314-80-3; 7719-12-2; 88-99-3; 85-44-9;
51-03-6; 13981-16-3; 15117-48-3; 7784-41-0; 10124-50-2?
7778-50-9; 7789-00-6; 151-50-8; 1310-58-3; 7722-64-7; 506-61-6;
7440-09-7; 23950-58-5; 1918-16-7; 109-98-8; 2312-35-8;
79-09-4; 123-62-6; 107-12-0; 75-56-9; 114-26-1; 129-00-0; 121-29-9;
110-86-1; 91-22-5; 13982-63-3; 15262-20-1; 10043-92-2; 50-55-5;
108-46-3; 299-84-3; 83-79-4; 81-07-2; 94-59-7; 7783-00-8;
12640-89-0; 7446-34-6; 7782-49-2; 630-10-4; 506-64-9;
7761-88-8; 7440-22-4; 93-72-1; 122-34-9; 7440-23-5;
7631-89-2; 7784-46-5; 26628-22-8; 10588-01-9; 1333-83-1;
7631-90-5; 7775-11-3; 143-33-9; 25155-30-0; 62-74-8; 16721-80-5;
1310-73-2; 7681-52-9; 124-41-4; 7632-00-0; 7558-79-4;
7601-54-9; 10102-18-8; 7440-23-5; 18883-66-4; 8001-50-1;
14158-27-1; 10098-97-2; 1314-96-1; 57-24-9; 100-42-5; 7446-09-5;
10025-67-9; 7664-93-9; 72-54-8; 127-18-4; 56-23-5; 3689-24-5;
78-00-2; 107-49-3; 109-99-9; 509-14-8; 1314-32-5; 563-68-8;
29809-42-5; 7791-12-0; 10102-45-1; 7446-18-6; 7440-28-0; 62-55-5;
23564-05-8; 79-19-6; 62-56-6; 137-26-8; 7440-32-6; 26471-62-5;
108-88-3; 25376-45-8; 8001-35-2; 2303-17-5; 75-25-2; 78-48-8;
52-68-6; 25323-89-1; 79-01-6; 75-69-4; 75-70-7; 25167-82-2;
27323-41-7; 121-44-8; 1582-09-8; 75-50-3; 99-35-4; 126-72-7;
10028-17-8; 72-57-1; 50-31-7; 66-75-1; 13966-29-5; 15117-96-1;
7440-61-1; 7440-61-1; 541-09-3; 10102-06-4; 51-79-6; 11115-67-6;
1314-62-1; 7440-62-2; 27774-13-6; 108-05-4; 75-01-4; 75-35-4;
1330-20-7; 1300-71-6; 557-34-6; 1332-07-6; 7699-45-8; 3486-35-9;
7646-85-7; 7783-49-5; 557-41-5; 7779-86-4; 7779-88-6; 127-82-2;
1314-84-7; 16871-71-9; 7733-02-0; 7440-66-6; 13746-89-9;
14644-61-2; 10026-11-6
(CNH) Contact name(s): Siegel,S. ; Siegel,S.
(COR) Contact organization: Office of CSIH Administration
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Intergration.
865
-------
Accession lo. 7202000005
-------
Accession No. 7202000005 (cont)
(ANL) Lab analysis based on EPA-approved or accepted methods? NO
(PRE) Precision: Precision and accuracy estimates are not available.
Edit Programs for validity of bibliographic information only; no
edits for accuracy.
(CBY) Data collected by: Self reporting pesticide producers and
Manufacturers ;EPA headquarters Office of
(ABY) Data analyzed by: Self reporting primary data analysis
EPA headquarters Office of Pesticide Programs
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Development of regulations
or standards
(PR2) Secondary purpose of data collection: Risk assessment
(AUT) Authorization for data collection: statutory authorization is P
L 92-516 as amended, section 3(c)<2)(c) (FIFRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data base: Printouts on
request
Microfilm
(NUS) number of regular users of data base: 350 people (OPP revleu
Scientists and contract revieuers)
(USR) Current regular users of data base: EPA headquarter offices
Office of Pesticide Programs
(CNF) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for some data
(DLC) Primary physical location of data: Headquarters office
(DST) Fora of data storage: Magnetic disc ;Microfich/fila
(DAC) Type of data access: Commercial software NYLBOR ;EPA hardware
IBM 370/168 HIDS:7200000905
(CHG) Direct charge for non-EPA use: no outside use/access permitted
(OPDT) Frequency of data base master file up-date: Weekly
(CMP) Completion of fora:
if 111 Ian C. Grosse
OFC: EPA/(OPTS)/(OPP)/(PSD)
AD: 401 M St., S.tf. Washington, DC 20460
PH: (703) 557-7143
(OF) Date of fora coupletion: 12-22-82
(NMAT) Number of substances represented in data base: 73
(NCAS) Number of CAS registry numbers in data base: 20
(MAT) Substances represented in data base:
2-ethyl,1,3-hexanediol benefin<1861-40-l>
4-Aninopyridine<504-24-5> bifenox
CDEC boric acid and salts
EPTC bromacil and salts
OBPA butralin
acephate butyl acetate<123-86-4>
alachlor<15972-60-8> butylate
aluminum phosphide<20859-73-8> carboxin (vitavax)
ammonium sulfamate<7773-06-0> chlorbromuron
aspon chloroneb
atrazine<1912-24-9> chloropicrin
bandane chloroxuron
867
-------
Accession Ho. 7202000005 (cent)
coUBaphos<56-72-4> aethoayl<16752-77-5>
cyanazine<21725-46-2> aethoprene
cyclohexiaide aetobroauron
cyprazlne aetolachlor
daainozide (alar) aonuron<150-68-5>
ddd(tde) naphthalene<91-20-3>
deet naphthaleneacetic acid
dial if or neburon
dlcaaba<1918-00-9> norea
dichlone<117-80-6> phosalone
dicrotophos (bidrin) potassiua azide
dluron<330-54-l> potassim cyanate
endosulfan<115-29-7> redox potential (oxidation
•thlolate reduction potential)
ethoxyquin slduron
fluOMeturon sl«azine<122-34-9>
fUMarin and Ha salt sodiua azide<26628-22-8>
hypochlorites tebuthiuron
isocyanurates teaephos
isopropalln terbacil
kelthane<115-32-2> terbutol
llnuron terrazole
•cpa and salts trlchlorobezychlore
•ethaaidophos (aonitor) warfarin and Ha salt
aethidathion zinc phosphide<1314-84-7>
(CAS) CAS registry nuabers of substances included in data base: 504-24-
5; 15972-60-8; 20859-73-8; 7773-06-0; 1912-24-9; 1861-40-1;
123-86-4; 56-72-4; 21725-46-2; 1918-00-9; 117-80-6; 330-54-1;
115-29-7; 115-32-2; 16752-77-5; 150-68-5; 91-20-3; 122-34-9;
26628-22-8; 1314-84-7
(CBM) Contact nawe(s): Grosse,V.C. ; Fry^B.C. ; €rosse,H.C.
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Pesticide Programs.Program Suppor
868
-------
Accession No. 7202000009
Industry ;Manufacturer
(DS) Time period covered by data base: 01-01-50 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: weekly
(NOB) Number of observations in data base: 40000.(Estimated)
(NED Estimated annual increase of observations in data base: 200.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: (N/A.)
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
company number
(FAC) Data elements identifying facility Include: Parent corp name
;Parent corp location ;Program identifier
(CDE) Pollutant identification data are: Other coding scheme
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal. procedures conform to ORD guidelines: Collect
ion method documented ;QA procedures documented
(ADD) Lab Audit: Data not based on lab analysis.
(PRE) Precision: Precision and accuracy estimates are not available
(EDT) Editting: Edit procedures used and documented.
(CBY) Data collected by: EPA headquarters Office of Pesticide
Programs, Registration Division
(ABY) Data analyzed by: EPA headquarters Office of Pesticide Programs
(IDL) Laboratory identification: NO
(AUT) Authorization for data collection: Statutory authorization is P
L 92-516 (The Federal insecticide. Fungicide, and Rodenticide Act
as amended)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0068 J158-R-0066
869
-------
Accession Mo. 7202000009 (cont)
(REP) Fora of available reports and outputs of data base: Printouts on
request
Microfilm
Machine-readable raw data
(NUS) Number of regular users of data bases 300
(OSR) Current regular users of data base: EPA headquarter offices
EPA regional offices
Other federal agencies
States
private industry
(CNF) Confidentiality of data and !!•its on access: Limits on access
within EPA and outside agency for sone data
(DLC) Primary physical location of data: HCC/IBM
(DST) Fora of data storage: Magnetic disc
(DAC) Type of data access: EPA software PPIS Cobol & Easytrlve
MIDS:7200000909 >EPA hardware IBM 370/168
(CHG) Direct charge for non-EPA use: no outside use/access permitted
of confidential formulas.
(OPDT) Frequency of data base vaster file up-date: Meekly
(RDBEPA) Related EPA data bases used in conjunction with this data base
Establishment Registration Support System (ERSS) in Office of
Enforcement
(CMP) Completion of fora:
Elgin G« Fry
OFC: EPA/(OPTS)/(OPP)/(PSD)/(SSB)
AD: TS-757, 401 M St., S.H., Washington, DC 20460
PH: (202)426-8862
(OF) Date of fora completion: 12-22-82
(HMAT) lumber of substances represented in data base: 77
(•CAS) Number of CAS registry numbers in data base: 70
(MAT) Substances represented in data base:
l,2-dibromo-3-chloropropane coal tar<8007-45-2>
(dbcp)<96-12-8> creosote<8021-39-4>
2,4,5-trichlorophenol<95-95-4> ddd(tde)
1f 4,5-trichlorophenoxyacetlc acid ddt
(T)<93-76-5> diallate<2303-16-4>
2-fluoroacetamide (1081)<640-19-T> dleldriiK60-57-l>
acrylonitrile<107-13-l> dimethoate<60-51-5>
aldrin<309-00-2> ebdc's (ethyleneblsdlthiocarbamate
amltraz (baam)<33089-61-l> s)
araiite<140-57-8> endrin<72-20-8>
arsenic acid<1327-52-2> epn (ethyl-p-nitrophenyl thlonoben
arsenic pentoxida<1303-28~2> zenephosonate)<2104-64-5>
arsenic trioxide ethylene dibromide (edb)<106-93-4>
arsenic<7440-38-2> ethylene oxide<75-21-8>
benomyl<17804-35-2> heptachlor<76-44-8>
benzac kepone<143-50-0>
cad»iu«<7440-43-9> lindane<58-89-9>
chloranil<118-75-2> maleic hydrazide<123-33-l>
chlordane<57-74-9> mirex<2385-85-5>
chlorobenzilate<510-15-6> monuron<150-68-5>
chloroform<67-66-3>
870
-------
Accession Ho. 7202000009
(cent)
octanethylpyrophosphoramide (OMPA)
<152-16-9>
pentachloronitrobenzene (PCNB)
<82-68-8>
pentachlorophenol<87-86-5>
phenarsazine chloride<578-94-9>
pronaaide<23950-58-5>
safrole<94-59-7>
silwex<93-72-l>
sodium fluoroacetate (1080)
<62-74-8>
strobane<8001-50-l>
strychnine<57-24-9>
thlophanate aethyl<23564-05-8>
toxaphene<8001-35-2>
trifluralin
trysben<50-31-7>
2,4-d acid<94-75-7>
ca captan<133-06-2>
carbaryl<63-25-2>
carbofuran<1563-66-2>
carbon tetrachloride<56-23-5>
chlorpyrifos<2921-88-2>
dialkyl phosphates
dicanba<1918-00-9>
dichlorvos (ddvp)<62-73-7>
erbon<136-25-4>
ethyl parathion<56-38-2>
•alathion<121-75-5>
aethanearsonates
•ethyl parathion<298-00-0>
paraquatX 4685-14-7>
perthane<72-56-0>
piperonyl butoxide<51-03-c»
polychlorinated biphenyls (PCBs)
propoxur<114-26-l>
ronnel<299-84-3>
rotenone<83-79-4>
s,s^s-tributyl phosphorotrithioat
<78-48-8>
triallate<2303-17-5>
tributyl phosphorotrithioate
<78-48-8>
trichlor fon<52-68-6>
(CAS) CAS registry numbers of substances included in data base: 96-12-8
; 95-95-4; 93-76-5; 640-19-7; 107-13-1; 309-00-2; 33089-61-1;
140-57-8; 1327-52-2; 1303-28-2; 1327-53-3; 7440-38-2;
17804-35-2; 7440-43-9; 118-75-2; 57-74-9; 510-15-6; 67-66-3;
8007-45-2; 8021-39-4; 2303-16-4; 60-57-1; 60-51-5; 72-20-8;
2104-64-5; 106-93-4; 75-21-8; 76-44-8; 143-50-0; 58-89-9;
123-33-1; 2385-85-5; 150-68-5; 152-16-9; 82-68-8; 87-86-5;
578-94-9; 23950-58-5; 94-59-7; 93-72-1; 62-74-8; 8001-50-1;
57-24-9; 23564-05-8; 8001-35-2; 1582-09-8; 50-31-7; 94-75-7;
133-06-2; 63-25-2; 1563-66-2; 56-23-5; 2921-88-2; 1918-00-9;
62-73-7; 136-25-4; 56-38-2; 121-75-5; 298-00-0; 4685-14-7;
72-56-0; 51-03-6; 114-26-1; 299-84-3; 83-79-4; 78-48-8;
2303-17-5; 78-48-8; 52-68-6
(Cf|M) Contact naae(s): Fry,E.G. ; Fry/E.G.
(COR) Contact organization: Prograa Support Div. GPP,OPTS
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Pesticide Prograas.Program Suppor
871
-------
Accession No. 7205000001
(DQ) Date of Questionaire: 12-02-82
(HAN) Name of Data Base of Model: National Human Milk Monitoring
Prograa
(ACR) Acronym of Data Base or Model: IHMP
(MED) Media/Subject of Data Base or Model: Other human milk
(ABS) Abstract/Over view of Data Base or Model: Data base contains
values of chlorinated. hydrocarbon insecticides and
polychlorinated biphenyl residues found in human milk saaples
provided by approximately 3,000 volunteers randomly selected
from the entire continental O.S.
(CTC) COHTACTS: Subject matter Jerry Blonde11 (703)557*0267;
Coaputer-related Jerry Blonde11 (703)557-0267; EPA Office of
Pesticide Programs, Health Effects Branch
(DTP) Type of data collection or monitoring: Point source data
collection human volunteers
(STA) Data Base status: Operational/ongoing
(CRP) Groups of substances represented in Data Base: 129 307 CHA ;48
cancelled pesticides ;9 monitoring pesticides
(NPP) Non-pollutant parameters included in the data base: Collection
method ;Health effects ;Location ;Physical data ^Population
demograph Volume/mass measures
(DS) Time period covered by data base: 01-01-75 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: one time only
(NOB) Number of observations in data base: 30000.(Estimated)
(NEI) Estimated annual increase of observations in data base: 100.
(INF) Data base includes: Rau data/observations
(NTS) Total number of stations or sources covered in data base: 500.
(NCS) No. stations or sources currently originating/contributing data:
500.
(NOF) Number of facilities covered in data base (source monitoring): 50
0.
(6EO) Geographic coverage of data base: National
(LOG) Data elements identifying location of station or source include:
State ^Project identifier ;Hospltal Identification
(FAC) Data elements identifying facility include: Program Identifier
;Hospital Identification
(CDE) Pollutant identification data are: Other coding scheme
(LIN) Limitation/variation in data of which user should be aware: Sampl
e is representative for each of 48 states. Major periods covered
are 1975-76 (1436 observations) and 1978-79 (1800 observations).
Annual increase of 100 is ongoing in the absence of major new data
collection in 1981-82. The data base is accessed through the
Health Effects Branch, Hazard Evaluation Division, Office of
Pesticides and Toxic Substances, as veil as through Colorado
State University.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Saaplin
g plan documented jCollection method documented ;Analysis method
document QA procedures documented
(AWL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory*
(PRB) Precision: Precision and accuracy estimates exist for all
872
-------
Accession No. 7205000001 (cent)
measurements
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Contractor lab Colorado State University and
various labs under cooperative agr
(ABY) Data analyzed by: Contractor lab Colorado State University and
various labs under cooperative agreements
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Development of regulations
or standards
(PR2) Secondary purpose of data collection: Risk assessment
(AUT) Authorization for data collection: Statutory authorization is P
L 92-516 as amended. Section 20 (Federal Insecticide, Fungicide,
and Rodenticide Act-FIFRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Forn of available reports and outputs of data base: Publications
National Study to Determine Levels of Chlorinated Hydrocarbon
Insecticides in Human Milk 1975-76, vol. I 4 II.
ray data available on request
(NUS) Number of regular users of data base: 50-100
(USR) Current regular users of data base: EPA headquarter offices
Office of Pesticides & Toxic Substances, Office of Research and
Development, Special Pesticide Review Division
EPA regional offices
EPA laboratories
Other federal agencies
States
World Health Organization, United nations
Food and Agriculture Organization, United Nations
(CNF) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for some data
(DLC) Primary physical location of data: Contractor
(DST) Form of data storage: Magnetic tape
(DAC) Type of data access: Software system at Colorado State
University
(CHG) Direct charge for non-EPA use: yes
(UPDT) Frequency of data base master file up-date: Annually
(CMP) Completion of form:
Jerry Blonde11
OFC: EPA/(OPTS)/(OPP)/(HED)
AD: 1921 Jefferson-Davis Highway, Arlington, VA 22202 PR:
(703)557-0267
(OF) Date of form completion: 01-27-83
(NMAT) Number of substances represented in data base: 20
(NCAS) Number of CAS registry numbers in data base: 15
(MAT) Substances represented in data base:
4,4*-ddd(p,p'tde) bhc-beta<319-85-7>
4,4'-dde(p,p'-ddx)<72-55-9> chlordane<57-74-9>
4,4'-ddt<50-29-3> ddd(tde)
aldrin<309-00-2> ddt
bhc (lindane)-gamma<58-89-9> dieldriiK60-57-l>
bhc-alpha<319-84-6> endrin<72-20-8>
873
-------
Accession Ho. 7205000001 (cont)
heptachlor epoxide<1024-57-3> pcb-1254 (arochlor 1254}
heptachlor<76-44-8> <11097-69-l>
hexachlorobenzene<118-74-1> pcb-1260 (arochlor 1260)
kepone<143-50-0> <11096-82-5>
lindane<58-89-9> polychlorlnated blphenyls (PCBs)
(CAS) CAS registry lumbers of substances included in data base: 72-55-9
; 50-29-3; 309-00-2; 58-89-9; 319-84-6; 319-85-7; 57-74-9;
60-57*1; 72-20-8; 1024-57-3; 76-44-8; 118-74-1; 143-50-0;
58-89-9; 11097-69-1; 11096-82-5
(CiM) Contact naae(s): Jerry Blonde 11 j Jerry 81ondell
(COR) Contact organization: of Pesticide Programs, Health Effects
Branch
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Offlee of Pesticide Programs*Hazard Evaluat
874
-------
Accession No, 7205000002
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: National Electronic Injury
Surveillance System
(ACR) Acronya of Data Base or Model: NEISS
(MED) Media/Subject of Data Base or Model: Other sample is hospital
emergency rooms which treat pesticide poisonings.
(ABS) Abstract/Overview of Data Base or Model: NEISS consists of a
listing of pesticide poisoning incidents giving information on
type of pesticide/ route of exposure, whether or not the case was
diagnosed as a poisoning by a physician, what symptoms, if any,
were present, the brand name of the pesticide, and the EPA
registration number of the product, if known.
(CTC) CONTACTS: Subject matter Jerome Blondell <703)557-57S5>
Computer-related Eileen
(DTP) Type of data collection or monitoring: Combination/Other
monitoring of injuries (pesticide poisonings) treated in hospital
emergency rooms.
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: All pesticides in
use are covered.
(NPP) Non-pollutant parameters included in the data base: Exposure
data ;Health effects jLocatlon population demographics ;
Sampling date /Treatment devices ;pesticide type ;route of exposure
; physician diagnosis of poisoning ;symptoms present lage & sex of
patient ; disposition of case ;body part affected ;EPA regulation
number
(DS) Time period covered by data base: 01-01-79 to Present
(TRM) Termination of data collection: Mot anticipated
(FRO) Frequency of data collection or sampling: Annual reports.
(NOB) Number of observations in data base: 17207(Estimated)
(NEI) Estimated annual increase of observations in data base: 18500.
(INF) Data base includes: Raw data/observations ;Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 74.
(NCS) Mo. stations or sources currently originating/contributing data:
52.
(NOF) Number of facilities covered In data base (source monitoring): 74
•
(CEO) Geographic coverage of data base: National
(LOG) Data elements identifying location of station or source include:
County ;State (available to Health Effects Branch only)
(PAG) Data elements identifying facility include: hospital
identification number assigned by Consumer Product Safety
Commission
(CDE) Pollutant identification data are; Other coding scheme
(LIM) Limitation/variation in data of which user should be aware: Pesti
cide data accessible by type only, i.e. Insecticide, rodenticlde,
etc.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ;Analysis method documented
(AML) Lab analysis based on EPA-approved or accepted methods? NO
(AUD) Lab Audit: Data not based on lab analysis.
875
-------
Accession Ho. 7205000002 (cont)
(PRE) Precisions Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: hospital personnel
(ABY) Data analyzed by: Other federal agency U.S. Consumer Product
Safety Commission (CPSC)
(IDL) Laboratory identification: 10
(PR2) Secondary purpose of data collection: Special study
CAOT) Authorization for data collection: Ho statutory requirement:
Data collection requirement is to support Agency research into
health effects of pesticides.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Report of First Year Data-Interagency Agreement with the
Consumer Product Safety Commission
(JIUS) lumber of regular users of data base: 5
(DSR) Current regular users of data base: EPA headquarter offices
Health Effects Branch, Office of Pesticide Programs
EPA laboratories Pesticide Incident Monitoring System (PINS) Data
Center, Miami FL.
(CNF) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for some data
(DLC) Primary physical location of data: Other federal agency
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: through the Health Effects Contact with the
Consumer Product Safety Commission
(CHG) Direct charge for non-EPA use: Report or abstract of data
available at no charge
(OPDT) Frequency of data base master file up-date: Semi-annually
Bother report annually
(ROB) lon-EPA data bases used in conjunction with this data base: repor
ts from Poison Control Centers
(CMP) Completion of form:
Mary Frankenberry
OFC: EPA/(OPTS)/(OPP)/(HED)/(HEB)
AD: 401 M St., S.tf., Hashing ton, DC 20460
PH: (202)426-2454
(OF) Date of form completion: 01-27-82
(MMAT) Huaber of substances represented in data base: 78
(RCAS) lumber of CAS registry numbers in data base: 69
(MAT) Substances represented in data base:
l,2-dibromo-3-chloropropane arsenic acid<1327-52-2>
(dbcp)<96-12-8> arsenic pentoxide<1303-28-2>
2,4,5-trichlorophenol<95-95-4> arsenic trioxide<1327-53-3>
2,4,5-trlchlorophenoxyacetic acid arsenic<7440-38-2>
(T)<93-76-5> benomyl<17804-35-2>
2-fluoroacetamide (1081)<640-19-7> benzac
acrylonitrlle<107-13-1> c admium<7440-43-9>
aldrin<309-00-2> chloranil<118-75-2>
amltraz (baam)<33089-61-1> chlordane<57-74-9>
aramite<140-57-8> chlorobenzilate<510-15-6>
876
-------
Accession Ho. 7205000002
(cont)
chlorofora<67-66-3>
coal tar<8007-45-2>
creosote<8021-39-4>
ddd(tde)
ddt
diallate<2303-16-4>
dieldrin<60-57-l>
di«ethoate<60-51-5>
ebdc's (ethylenebisdithiocarbaaate
s)
endrin<72-20-8>
epn (ethyl-p-nitrophenyl thlonoben
zenephosonate)<2104-64-5>
ethylene dibroaide (edb)<106-93-4>
ethylene oxide<75-21-8>
heptachlor<76-44-8>
kepone<143-50-0>
lindane<58-89-9>
•aleic hydrazide<123-33-l>
•irex<2385-85-5>
•onurotK 150-68-5>
octa»ethyIpyrophosphoraside (OMPA)
<152-16-9>
pentachloronitrobenz«ne (PCNB)
<82-68-8>
pentachlorophenol<87-86-5>
phenarsazine chloride<578-94-9>
prona«ide<23950-58-5>
safrole<94-59-7>
silvex<93-72-l>
sodli^i fluoroacetate (1080)
<62-74-8>
strobane<8001-50-1>
thiophanate methyl<23564-05-8>
toxaphene<8001-35-2>
trifluraline (treflan)<1582-09-8>
trysben<50-31-7>
2^4-d acid<94-75-7>
az cacodyllc acid and salts
<75-60-5>
captan<133-06-2>
carbaryl<63-25-2>
carbofuran<1563-66-2>
carbon t«trachloride<56-23-5>
chlorpyrifos<2921-88-2>
dlalkyl phosphates
dicaaba<1918-00-9>
dichlorvos (ddvp)<62-73-7>
erbon<136-25-4>
ethyl parathion<56-38-2>
•alathion<121-75-5>
•ethanearsonates
•ethyl parathion<298-00-0>
paraquat<4685-14-7>
P erthane<7 2-56-0>
piperonyl butoxide<51-03-6>
polychlorlnated biphenyls CPCBs)
propoxur<114-26-l>
ronnel<299-84-3>
rotenone<83-79-4>
s,sxs-tributyl phosphorotrithioat
<78-48-8>
triallate<2303-17-5>
tributyl phosphorotrithioate
<78-48-8>
trichlorfon<52-68-6>
strychnine<57-24-9>
{CAS) CAS registry nu«l>ers of substances Included in data base: 96-12-8
; 95-95-4; 93-76-5; 640-19-7; 107-13-1; 309-00-2; 33089-61-1;
140-57-8; 1327-52-2; 1303-28-2; 1327-53-3; 7440-38-2;
17804-35-2; 7440-43-9; 118-75-2; 57-74-9; 510-15-6; 67-66-3;
8007-45-2; 6021-39-4; 2303-16-4; 60-57-1; 60-51-5; 72-20-8;
2104-64-5; 106-93-4; 75-21-8; 76-44-8; 143-50-0; 58-89-9;
123-33-1; 2385-85-5; 150-68-5; 152-16-9; 82-68-8; 87-86-5;
578-94-9; 23950-58-5; 94-59-7; 93-72-1; 62-74-8; 8001-50-1;
57-24-9; 23564-05-8; 8001-35-2; 1582-09-8; 50-31-7; 94-75-7;
75-60-5; 133-06-2; 63-25-2; 1563-66-2; 56-23-5; 2921-88-2;
1918-00-9; 62-73-7; 136-25-4; 56-38-2; 121-75-5; 298-00-0;
4685-14-7; 72-56-0; 51-03-6; 114-26-1; 299-84-3; 83-79-4;
78-48-8; 2303-17-5; 78-48-8; 52-68-6
(CHM) contact naae(s): Blondell/J. ; Kessler,E«; Blondell,J.
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Offlee of pesticide Prograss.Hazard Evaluat
877
-------
Accession Bo. 7205000003
(DQ) Date of Questionaire: 12-02-82
(MAM) name of Data Base of Model: Pesticide Incident Monitoring System
(ACR) Acronym of Data Base or Model: PINS
(MED) Media/Subject of Data Base or Model: Air ;Blood ;Drinking Hater
;Ground water ;Runoff agricultural j Sediment >Soil ;Tissue
human, animal, fish
CABS) Abstract/Overview of Data Base or Model: The Pesticide
Monitoring Systea (PIMS) enters, stores, coordinates and retrieves
pesticide incident data within the EPA. The system develops and
•aintains reporting sources, Monitors suspected incidents and
provides confirmatory analysis and data on circumstances of the
incident.
CCTC) COMTACTS: Subject matter James J. Boland (703)557-0576;
Computer-related Kelly Thomas (305)547-5823.? EPA Office Hazard
E-valuation Division, Office of Pesticide
(DTP) Type of data collection or monitoring: Combination/Other data
collection or monitoring is often determined by the nature of
the incident.
(STA) Data Base status: Partially Operational/Under revision
(GRP) Groups of substances represented in Data Base: 43 air priority
chemicals ;129 307 CMA ;41 CMA potential criteria } 21 drinking
water standards ;9 potential drinking water ;29 drinking water
monitoring ; 299 hazardous substances ;48 cancelled pesticides ;9
monitoring pesticides ; 54 TSCA assessment >16 Pre-RPAR
(MPP) Non-pollutant parameters included in the data base: Biological
data yChemical data ^Collection method Concentration measures ;
Disposal ^Exposure data ^Geographic subdivision ;Health effects ;
Industry ;Location }Manufacturer ;Physical data precipitation ;
Sampling date ;Site description ;Dse ;Uind direction ;fflnd velocity
; some application methods ;Rates
(DS) Time period covered by data base: 01-01-66 TO 09-30-81
(TRM) Termination of data collection: lot anticipated
(PRO) Frequency of data collection or sampling: Other varies as
incidents are reported-may be as frequently as daily.
(MOB) number of observations in data base: 53000.(Actual)
(IfEl) Estimated annual Increase of observations in data base: 4000.
(INF) Data base includes: Raw data/observations ^Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 100
(or more.)
(NCS) No. stations or sources currently originating/contributing data:
50 (major contributors.)
(MOP) Number of facilities covered in data base (source monitoring): (N
w "A f
(GEO) Geographic coverage of data base: National
(LOC) Data elements Identifying location of station or source include:
State ;County ;City ;Project identifier ;Agency or reporting source
(CDE) Pollutant Identification data are: Other coding scheme
(LIN) Limitation/variation in data of which user should be aware: Pesti
cides with most reported incidents are those with high agricultural
and home use rates. No incidents have been reported for some of
the pesticides. PlMs is a voluntary system—as such, numbers of
878
-------
Accession Ho. 7205000003 (cont)
reports vary as does the quality (e.g. confined as to pesticide
cause. )
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Data not based on lab analysis.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base Edit automated data processing system
edited periodically.
(CBY) Data collected by: Self reporting ;Local agency ;State agency 3*
collecting 90% of the reports. ; Regional office ? EPA lab
Contractor lab ^Contractor 8 universities are collecting the
reports. ; Other federal agency JEPA headquarters
(ABY) Data analyzed by: Local agency
State agency
Regional office
SPA lab
Contractor lab
Contractor cooperative agreement with the University of Miami,
School of Medicine-operates PIMS
Other federal agency
EPA headquarters
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Development of regulations
or standards
(PR2) Secondary purpose of data collection: Anticipatory/research
(AUT) Authorization for data collection: Statutory authorization is P
L 92-516 as amended, Section 3 (The Federal Insecticide,
Fungicide, and Rodent!cide Act-FIFRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0008
(REP) Form of available reports and outputs of data base: Publications
summary reports
Unpublished reports
Printouts on request
(NUS) Number of regular users of data base: 50
(OSR) Current regular users of data base: EPA headquarter offices
Office of Pesticide Programs, Office of General Counsel, Office of
Pesticides and Toxic Substances, Office of Enforcement
EPA regional offices
Other federal agencies
States
General Accounting Office
Public Interest Groups - various ones
(CNF) Confidentiality of data and limits on access: Limits on outside
access for all data
(DLC) Primary physical location of data: Contractor
(DST) Form of data storage: Magnetic disc ^Original form (hardcopy,
readings)
(DAC) Type of data access: University of Miami, IBM Series I
(CHG) Direct charge for non-EPA use: No
(UPDT) Frequency of data base master file up-date: Other daily
(CMP) Completion of form:
James J. Boland
879
-------
Accession Ho. 7205000003
(cont)
OFC: EPA/(OPTS)/(OPP)/(HED)/(TS-769-C)
AD: 1921 Jefferson Davis Buy., Arlington, Virginia 20002
PH: (703)557-0576
(DP) Date of fora completion: 01-14-83
(•NAT) limber of substances represented In data base: 201
(•CAS) MuBber of CAS registry numbers In data base: 172
(MAT) Substances represented In data base:
l,l,l-trichloroethane<7l-55-
6>
If 1, 2, 2, -tet rachloroet bane
<79-34-5>
lr2,4,-trichlorobenzen«<120-82-l>
1, 2-dlbroao~3-cbloropropane (dbcp)
<96-12-8>
1, 2-dlchlorobenzene<95-50-l>
l,2-dichloroethane<107-06-2>
If 3-dlchlorobenzen«< 541-73-l>
1, 4-dichlorobenzene<106-46-7>
2,2-dichloroproplonic acid
<75-99-0>
2,4,5-t nines
2, 4,5-t esters
2,4,5-t salts
2,4,5-tp acid esters
2f 4,5- trichlorophenol<95-95-4>
2,4,5-trichlorophenoxyacetic acid
(T)<93-76-5>
2,4,5-trichlorophenoxypropionic
acid (TP)<93-72-l>
2,4,6- trichl or ophenol<88-06-2>
2,4-d acid<94-75-7>
2,4-d esters
2f 4-dichlorophenoxyacetlc acid (2,
4-d)<94-75-7>
2f 4-dlnItrophenol<51-28-5>
2-fluoroacetaalde (1081)<640-19-7>
4,4*-ddd(p,p*tde)
4,4--ddt<50-29-3>
ac«naphth«ne<83-32-9>
acetic acld<64-19-7>
acroleln<107-02-8>
acrylonltrile< 107-13-
al achlor <1 5972-60-8>
aldrln<309-00-2>
allyl alcohol<107-18-6>
aaltraz (baa»)<33089-61-l>
a»»onla<7664-41-7>
aaaonlua chlorlde<12125-02-9>
aaaoniUB sulfa»ate<7773-06-0>
aaaoniui thlocyanate<1762-95-4>
thlosulfate<7783-18-8>
ara«ite<140-57-8>
arsenic acid<1327-52-2>
arsenic disulfide<1303-32-8>
arsenic pentoxlde<1303-28-2>
arsenic trioxld
arsenic<7440-38-2>
atrazin«<1912-24-9>
banvel-d<1918-00-9>
b«nefin<1861-40-l>
beno»yl<17804-35-2>
benzac '
benzene<71-43-2>
bhc (lindane)-ga»na<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bro«o«cthanc<74-83-9>
butachlor<23184-66-9>
cacodylic acid and salts<75-60-5>
cad«iu«<7440-43-9>
calciua arsenate<7778-44-l>
calciui arsenite<52740-16-6>
calciua hydroxlde<1305-62-0>
calcium hypochlorite<7778-54-3>
calcluB oxide<1305-78-8>
captan<133-06-2>
carbaryl<63-25-2>
carbo£uran<1563-66-2>
carbon disulfide<75-15-0>
carbon t«trachloride<56-23-5>
chloranil<118-75-2>
chlordane< 57-7 4-9>
chlorobenzilat«<510-15-6>
chlorofor«<67-66-3>
chloro»ethane<74-87-3>
chlorpyrlfos<2921-88-2>
chroiiu«<7440-47-3>
coal tar<8007-45-2>
copper<7440-50-8>
couBaphos<56-72-4>
cr«osote<8021-39-4>
cresol<1319-77-3>
cyanazln«<21725-46-2>
cyanlde<57-12-5>
ddd(tde)
880
-------
Accession Ho. 7205000003
(cont)
ddt
deneton<8065-48-3>
dlalkyl phosphates
dlallate<2303-16-4>
diazinon<333-41-5>
dIbutyl phthalate<34-74-2>
dica»ba<1918-00-9>
dichlobenll<1194-65-6>
dichlone<117-80-6>
dichlorobenzene<25321-22-6>
dichloronethane<75-09-2>
dichloropropane<2663 8-19-7>
dlchloropropene-dlchloropropane
mixture
dichloroprop ene< 26 952-23-8>
dichlorvos (ddvp)<62-73-7>
di«ldrin<60-57-l>
di»ethoate<60-51-5>
dlnitrophenol
dlqtiat<2764-72-9>
disulfoton<298-04-4>
diuron<330-54-l>
ebdc's (ethylenebisdlthiocarbaaate
sy
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endcsulfan-beta<33213-65-9>
endosulfan<115-29-7>
endrln<72-20-8>
epichlorohydrin<106-89-8>
epn (ethyl-p-nltrophenyl thlonoben
zenephosonate)<2104-64-5>
erbon<136-25-4>
ethion<563-12-2>
ethyl parathioiK56-38-2>
ethylene dibroiide (edb)<106-93-4>
ethylene dichloride<107-06-2>
ethylene oxide<75-21-8>
for»aldehyde<50-00-0>
guthion<86-50-0>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene
hydrogen cyanlde<74-90-8>
k€lthane
kepone<143-50-0>
lead arsenate<3687-31-8>
lindane<58-89-9>
m-cresol<108-39-4>
»alathion<121-75-5>
•alelc hydrazide
•ercaptodi«ethur<2032-65-7>
nethanearsonates
»ethoxychlor<72-43-5>
•ethyl chlorofor«<71-55-6>
•ethyl parathion<298-00-0>
•evinphos<7786-34-7>
•lrex<2385-'85-5>
•onuron<150-68-5>
naled<300-76-5>
naphthalene<91-20-3>
nitrophenol<25154-55-6>
o-cresol<95-48-7>
octanethyIpyrophosphoraalde (OMPA)
<152-16-9>
p-cresol<106-44-5>
p-dichlorobenzene<106-46-7>
pHenol<108-95-2>
paraquat<4685-14-7>
parathlon< 56-38-2>
pentachloronitrobenzene (PCHB)
<82-68-8>
pentachlorophenol<87-86-5>
perchloroethylene<127-l8-4>
perthane<72-56-0>
phenarsazine chlorlde<578-94-9>
phenol<108-95-2>
phorate 298-0202
phosgene<75-44-5>
phosphorus and compounds
<7723-14-0>
phosphorus<7723-14-0>
phthalic acld<88-99-3>
piperonyl butoxide<51-03-6>
polychlorlnated blphenyls (PCBs)
pronaalde<23950-58-5>
propachlor<1918-16-7>
propanil<709-98-8>
proparglte<2312-35-8>
proplyene oxide<75-56-9>
propoxur<114-26-l>
pyrethrln<121-29-9>
ronnel<299-84-3>
rotenone<83-79-4>
s,s,s-tributyl phosphorotrlthloate
<78-48-8>
safrole<94-59-7>
sllvex<93-72-l>
si*azine<122-34-9>
sodiun acsenate<7631-89-2>
sodiua arsenlte<7784-46-5>
sodium cyanide<143-33-9>
sodiun fluocoacetate (1080)
<62-74-8>
881
-------
Accession No. 7205000003 (cont)
sodiua hypochlorite<7681-52-9> tributyl pbosphorotrithioate
strobane<8001-50-l> <78-48-8>
strychine<57-24-9> trichlorfon<52-68-6>
strychnine<57-24-9> trichloroethane<25323-89-l>
td«<72-54-8> trichloroethylene<79-01-6>
tetrachloroethylene<127-18-4> trichlorophenol (TCP)<25167-82-2>
tetraethyl pyrophosphate<107-49-3> trifluraline (treflan)<1582-09-8>
thaiHUB sulfate<7446-18-6> trysben<50-31-7>
thalliu»<7440-28-0> xylene<1330-20-7>
thiophanate •etbyl<23564-05-8> zinc chloride<7646-85-7>
toxaphene<8001-35-2> zinc sulfate<7733-02-0>
triallate<2303-17-5>
-------
Accession No. 7206000901
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Pesticide Usage Data Base
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Other-Households
(ABS) Abstract/Overview of Data Base or Model: This data base contains
demographic inforaation on respondents and quantity data and
site data on pesticides used in home. General attitudinal
questions on pesticide use uere used for collection of data.
(CTC) CONTACTS: Subject matter L. DeLuise, Economist, Economic
Analysis ; Computer-relat
(DTP) Type of data collection or monitoring: Point source data
collection - households
(STA) Data Base status: Funded for development
(DPO) Projected operational date of Data Base: 03-01-83
(NPP) Ron-pollutant parameters included in the data base: Disposal
population demographics ;Sit« description ;Quantity data
(DS) Time period covered by data base: 01-01-82 TO 12-31-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Other-three times a
year
(NOB) Number of observations in data base: 1500Sampling plan documented Collection method
docume Analysis method documented ;QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? NO
(AOD) Lab Audit: Lab audit is not based on lab analysis
(PRE) Precision: Precision and accuracy estimates are not yet known.
(EOT) Editting: Edit procedures are unknown at this point. System is
under development.
(CBT) Data collected by: Contractor - to be named
(ABY) Data analyzed by: Contractor - to be named
(IDL) Laboratory Identification: NO
(PR2) Secondary purpose of data collection: Program evaluation
(AOT) Authorization for data collection: Statutory authorization is
P.L. 92-516 FIFRA a .
(OMB) Data collected/submitted using OMB-approved EPA reporting forms.
SF 83
(REP) Form of available reports and outputs of data base: Unknown at
this time. System under development.
883
-------
Accession Mo. 7206000901 (cont)
(OSR) Current regular users of data base: Unknown
(CNF) Confidentiality of data and lliits on access: Mo Halts on
access to data
(DLC) primary physical location of data: Unknown
COST) Fora of data storage: Magnetic disc ;Microfich/fila ^Original
fore (hardcopy, readings)
(DAC) Type of data access: EPA hardware - not yet developed
(CHG) Direct charge for non-EPA use: Mo
(UPDT) Frequency of data base aaster file up-dateX Other-Rone
(ROBEPA) Related EPA data bases used in conjunction with this data base
Unknown
(CMP) Completion of for*:
L. DeLuise
OFC: Benefit & Field Studies Oiv./Bconoaic Analysis Branch/
Office of Pesticide Programs
AD: 1921 Jefferson Davis Hwy., Crystal Mall |2, R>. 803,
Arlington, firginia
PH: (703) 557-7560
(OF) Date of fora completion: 01-27-83
(CNM) Contact naae(s): DeLuise,L.; DeLulse,L.
(COR) Contact organization: Economic Analysis Branch/Benefit fc Field
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Management Suppo
884
-------
Accession No. 7301400901
(DQ) Date of Questions!re: 12-02-82
(NAM) Name of Data Base of Model: Soil, Hater/ Estuarine Monitoring
System
(ACR) Acronym of Data Base or Model: SHENS
(MED) Media/Subject of Data Base or Model: Soil jTissue agricultural
crops
(ABS) Abstract/Overview of Data Base or Model: The soils section of
the SWEMS system contains residue data for agricultural and
urban soils/ raw agricultural crops, and agricultural chemical
application data for the sites sampled, these data »ay be
summarized in several Hays: by Material, by state, by county, by
crop, by urban area (for urban soils)*
(CIC) CONTACTS: Subject Matter Daniel T. Heggem (202)382-3584 ;
Computer-related Qlch Levy (202) 382-3895 ; EPA Office Frederick
V. Kutz (202) 382-3569
(DTP) Type of data collection or Monitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters included in the data base: Sampling
date ?Site description
(DS) TlMe period covered by data base: 05-01-68 TO 09-30-81
(TRM) Termination of data collection: Not anticipated-no samples
collected in 1981
(FRQ) Frequency of data collection or sampling: Other annually urban
soil only
(NOB) Number of observations in data base: 12500.(Estimated)
(NEI) Estimated annual increase of observations in data base: 500.
(INF) Data base includes: Rav data/observations ^Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 9000.
(NCS) No. stations or sources currently originating/contributing data:
3000. M v ,„
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
State jCounty ;SMSA >ProJect identifier
(CDE) Pollutant identification data are: Other coding scheme
(LIM) Limitation/variation in data of which user should be aware: Agric
ultural data collected only 1968-1973. 1973 (FY '74) data is a
six-year schedule, so 2 sets of data (different years) are
available for most SMSAs. Pesticide residue data has been
automated through 1978. 1979 data is being analyzed but not
automated. 1980 samples are currently being analyzed.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ;Collection Method documented ;Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(BDT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Contractor various ;0ther federal agency
885
-------
Accession Ho. 7301400901 (cont)
Department of Agriculture, U.S. Geological Survey JEPA
headquarters Exposure Evaluation Division, Office of Toxic
Substances
«ABY) Data analyzed by: EPA headquarters Toxicant Analysis Center,
Field Studies Branch, Exposure Evaluation Division
(IDL) Laboratory identification: MO
(PR2) Secondary purpose of data collection: Prograa evaluation
(AUT) Authorization for data collection: Statutory authorization is P
L 94-469, section 10 P L 92-516, as amended. Section 20(c)
(OMB) Data collected/submitted using OMB-approved EPA reporting foras:
agricultural data collected with OMB approved fora through 1975*
(REP) For* of available reports and. outputs of data base: Publications
Carey, A.E. and J.A. Gotten. 1976. PCB's in agricultural and
urban soil. Pages 195-198. In Proceedings of the national
Conference on PCBs. EPA 560/6-75-004.
Carey, A.E. 1974. Soil. In Guidelines on Sampling and
Statistical Methodologies for Aabient Pesticide
Monitoring.Fed.Hortcing Group on Pest Mgt., Hash.D.C., Oct.1074.
Chap. Ill, III.1-III.7.
Printouts on request
Machine-readable ran data
Carey,A.E«, et al. 1973. Organochlorine pesticide residues in
soils and crops of the corn belt region, U.S.-1970. Pestle* Monit.
J. 6:369-376.
Carey,A.E., et al. 1977. Pesticide application and cropping data
fro* 37 states, 1971-Hational Soils Monitoring Prograa. Pestle.
Monit. J. 12:137-148.
Carey,A.E. and J.A. Gowen. 1979. Pesticide application and cropping
data fro* 37 states in 1972-Rational Soils Monitoring Prograa.
Pestic. Monit. J. 12:198-208.
Crockett, A. B., et al. 1974. Pesticide residue levels in soils
and crops, FY 70-Hational Soils Monitoring Prograa (II). Pestle.
Monit. J. 8:69-97.
Vlersaa, G. B., et al. 1972. Pesticide Residue Levels in Soils, FY
1969-Wational soils Monitoring Prograa. Pestic. Nonit. J.
6:194-228.
Carey, A. E. et al. 1976. Pesticide residues in urban soils
fro* 14 U.S. cities, 1970. Pestic. Monit. J. 10:54-70.
Mlersaa, G. B. et al. 1972. Pesticide residues in soil froa
eight cities-1969. Pestic. Monit. J. 6:126-129.
Carey, A. E. et al. 1978. Pesticide residue levels in soils and
crops in 1971-Rational Soils Monitoring Prograa (III) Pestic.
Monit. J. 12:117-136.
Carey, A. E., et al. 1978. Pesticide residue levels in soils and
crops in 1972-Hational Soils Monitoring Prograa (If). Pestic.
Monit. J. 12:209-229.
Carey, A. E., et aI. 1980. Heavy Betal concentrations in soils
of five United States cities, 1972. Urban Soils Monitoring
Prograa. Pestic. Monit. J. 13:150-154.
Carey, A. E. 1979. Monitoring pesticides in agricultural and
urban soils in the United States. Pestic. Monit. J. 13:23-27.
Carey, A. E. 1979. Pesticide residue concentrations in soils of
886
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Accession No. 7301400901 (cont)
five U. s. cities. 1971. Urban Soils Monitoring Program.
Pestic. Monit. J. 13:17-22.
(NOS) Number of regular users of data base: 50
(USR) Current regular users of data base: EPA headquarter offices
Office of Pesticide Programs, Office of Toxic Substances, Office
of General Counsel.
EPA regional offices
EPA laboratories
Other federal agencies
States
(CNF) Confidentiality of data and Halts on access: No Units on
access to data
(DLC) Primary physical location of data: Headquarters office
(DST) Form of data storage: Magnetic tape
(DAC) Type of data access: EPA software Special program
HIDS:7501300900 ;EPA hardware IBM 370/168
(CHG) Direct charge for non-EPA use: no outside use/access permitted
(DPDT) Frequency of data base naster file up-date: Semi-annually
(CMP) Completion of form:
Ann E. Carey
OFC: EPA/
4,4"-dde(p,p*-ddx)<72-55-9> heptachlor<76-44-8>
aldrin<309-00-2> hexachlorobenzene<118-74-l>
arsenic<7440-38-2> lead<7439-92-l>
atrazine<1912-24-9> lindane<58-89-9>
bhc (lindane)-ga»ma<58-89-9> malathion<121-75-5>
cad»ium<7440-43-9> mercury<7439-97-6>
chlordane<57-74-9> methyl parathion<298-00-0>
ddd(tde) «irex<2385-85-5>
diazinon<333-41-5> parathion<56-38-2>
dieldrin<60-57-l> pcb-1242 (arochlor 1242)
endosulfan sulfate<1031-07-8> <53469-21-9>
endosulfan-alpha<959-98-8> pcb-1254 {arochlor 1254)
endosulfan-beta<33213-65-9> <11097-69-l>
endrin aldehyde<7421-93-4> pcb-1260 (arochlor 1260)
endrin<72-20-8> <11096-82-5>
epn (ethyl-p-nitrophenyl thionoben polychlorinated biphenyls (PCBs)
zenephosonate)<2104-64-5> propachlor<1918-16-7>
ethion<563-12-2> ronnel<299-84-3>
ethyl parathion tde<72-54-8>
<56-38- 6-50-OoiK86-50-0> trifluraline (treflan)<1582-09-8>
(CAS) CAS registry numbers of substances included in data base: 72-55-9
; 309-00-2; 7440-38-2? 1912-24-9; 58-89-9; 7440-43-9; 57-74-9;
333-41-5; 60-57-1; 1031-07*8; 959-98-8; 33213-65-9;
7421-93-4; 72-20-8; 2104-64-5; 563-12-2; 1024-57-3; 76-44-8;
887
-------
Accession lo. 7301400901
-------
Accession No. 7301400902
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Hunan Monitoring Data Base
(ACR) Acronya of Data Base or Model: HMDB
(MED) Media/Subject of Data Base or Model: Blood ;Tlssue human
biological media, urine and adipose tissue
(ABS) Abstract/overview of Data Base or Model: HMDB monitors on a
national scale, the incidences, prevalences, and levels of
selected pesticides and toxic substances in various human
biological media to assess trends over time; to evaluate the
effects of regulatory actions. Includes HANES II blood and urine
data (2/76 - 3/81). and annual tissue data. Data automated
through 12/79.
(CTC) CONTACTS: Subject natter Brion Cook (202)382-3581 ;
Computer-related Rich Levy (202)382-3895
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CUA ;41
CVA potential criteria ;21 drinking water standards ; 299
hazardous substances ;48 cancelled pesticides ;9 monitoring
pesticides
(NPP) Non-pollutant parameters included in the data base: Biological
data Collection method ^Exposure data ;Geographic subdivision /
Health effects ;Location ;Population demographics ^Sampling date ;
Test/analysis nethod }Volume/mass measures
(OS) Time period covered by data base: 07-01-68 TO 03-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: annually ;Other also
includes special projects
(NOB) Number of observations in data base: 16,000.(Estimated)
(NEI) Estimated annual increase of observations in data base: 1000.
(INF) Data base includes: Ran data/observations ;Summary aggregate
observations
(NTS) Total nunber of stations or sources covered in data base: 125.
(NCS) No. stations or sources currently originating/contributing data:
40.
(NOF) Number of facilities covered in data base (source monitoring): 12
5.
(GEQ) Geographic coverage of data base: National
(LOG) Data elements identifying location of station or source include:
State /SMSA ;Town/township
(FAC) Data elements identifying facility include: Plant facility nane
;Street address ;Program identifier ;census divisions
(CDE) Pollutant identification data are: Other coding scheme
(LIM) Limitation/variation in data of which user should be aware: Natio
nal survey design; data valid on Census Division, Census Region,
or National basis. No others (i.e. state) valid.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented jCollection method documented ;Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? NO
(ADD) Lab Audit: Lab audit Is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
889
-------
Accession Mo. 7301400902 (cont)
Included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Other federal agency National Center for
Health Statistics-HANES II ; contracted hospitals-Adipose data
(ABT) Data analyzed by: Contractor lab 2 labs-adipose; 4 labs RANES-II
EPA headquarters Exposure Evaluation Division
(IDL) Laboratory identification: YES
(PR2) Secondary purpose of data collection: baseline data and public
health evaluations
(AOT) Authorization for data collection: Statutory authorization is P
L 94-469, section 10 (The Toxic Substances Control Act - TSCA)
Statutory authorization is P L 92-516, as amended, section 20 (The
Federal Insecticide, Fungicide, and Rodenticide Act - FIFRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158R0140
(REP) Fora of available reports and outputs of data base: Publications
"Survey of Selected organochlorlne Pesticides in the General
Population of the 0. S.n; and others
Unpublished reports PCP residues in human tissue
Printouts on request
Microfilm, microfiche
Machine-readable raw data
On-line computer
(MOS) lumber of regular users of data base: 15
(OSR) Current regular users of data base: EPA headquarter offices
Office of Pesticide Programs, Office of Toxic Substances, Office
of the General Counsel
EPA regional offices
EPA laboratories
Other federal agencies
States
press
physicians
(CNF) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for some data
(DLC) Primary physical location of data: Contractor
(DST) Form of data storage: Magnetic tape
(DAC) Type of data access: EPA software custom written programs
MIDS:7501300900 ;EPA hardware IBM 370/168
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Quarterly
(RDBEPA) Related EPA data bases used in conjunction with this data base
Soil, Mater, Estuarine Monitoring System (SHEMS); Multimedia
Toxics Information System (formerly TOXET)
(CMP) Completion of form:
Brion Cook
OFC: EPA/(QPTS)/(OTS)/(EED)/(FSB)
AD: 401 M St., S.H. Mashington, D.C. 20460
PH: (202)382-3581
(DF) Date of form completion: 01-26-83
(•MAT) Number of substances represented in data base: 52
(•CAS) Number of CAS registry numbers In data base: 86
890
-------
Accession Mo. 7301400902
(cent)
(MAT) Substances represented in data base:
2,4,5-trlchlorophenol<95-95-
4>
2,4,5-trichlorophenoxyacetic acid
(T)<93-76-5>
2, 4, 5-tr ic hi or op he no xy prop ionic
acid
2,4-d acid<94-75-7>
2/4-dichlorophenoxyacetic acid (2*
4-d)<94-75-7>
2, 4-dinitrophenol<51-28-5>
4,4*-ddd(p,p'tde)
4,4*-dde(p,p*-ddx)<72-55-9>
4,4'-ddt<50-29-3>
4-nltrophenol<100-02-7>
aldrin<309-00-2>
bhc (lindane)-ga«»a<58-89-9>
bhc-alpha< 319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
captan<133-06-2>
carbofuran<1563-66-2>
chlordane<57-74-9>
chlorpyrifos<2921-88-2>
ddd(tde)
ddt
dialkyl phosphates
diazinon<333-41-5>
dibenzofuran<132-64-9>
dicanba<1918-00-9>
dieldrin<60-57-l>
dioxin<828-00-2>
endrin<72-20-8>
ethyl parathion<56-38-2>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachloroben2ene<118-74-l>
lindane<58-89-9>
•alathion<121-75-5>
•ethyl parathion<298-00-0>
»irex<2385-85-5>
naled<300-76-5>
naphthalene<91-20-3>
nitrophenoK 25154-5 5-6>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 Carochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260).
<11096-82-5>
pentachlorophenol<87-86-5>
phosphorus and compounds
<7723-14-0>
polychlorinated biphenyls (PCBs)
propoxur<114-26-l>
silvex<93-72-l>
eiiui JIIJN i A— c.v—of tde<72—54—8>
(CAS) CAS registry numbers of substances Included in data base: 95-95-4
; 93-76-5; 93-72-1; 94-75-7; 94-75-7; 51-28-5; 72-55-9;
50-29-3; 100-02-7; 309-00-2; 58-89-9; 319-84-6; 319:8*-7; _
319-86-8; 133-06-2; 1563-66-2; 57-74-9; 2921-88-2; 333-41-5;
132-64-9; 1918-00-9; 60-57*1; 828-00-2; 72-20-8; 56-38-2;
1024-57-3; 76-44-8; 118-74-1; 58-89-9; 121-75-5; 298-00-0;
2385-85-5; 300-76-5; 91-20-3; 25154-55-6; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 7723-14-0; 114-26-1; 93-72-1; 72-54-8
(CUM) Contact name(s): Cook,B. ; Levy,R. .,»««.
(COR) Contact organization: Field Studies Branch, Exposure Evaluation
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Exposure Evaluat
891
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Accession No. 7301400903
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Pesticides in Ambient Air
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/overview of Data Base or Model: Pesticides in Ambient
Air is a raw data base containing about 3*000 observations. The
data can only be accessed Manually. Years of collection:
1970-1972* and 1975 - present. The quantity of data collected
each year of the 1970-1972 period is about ten times that of the
1975-1980 period.
(CTC) CONTACTS: Subject Matter Henry Yang (202)382-3578 ; EPA
Office Field Studies Branch* Exposure Evaluation Division
(DTP) Type of data collection or Monitoring: AMbient data collection
(STA) Data Base status: Operational/ongoing
(NPP) Hon-pollutant paraMeters included in the data base: Concentration
Measures ;Flow rates ;Location ;precipitatlon ; SaMpling date
;Terperature ;Uind direction ;Hlnd velocity
(OS) TiMe period covered by data base: 04-01-70 TO 09-30-81
(TRM) TerM!nation of data collection: Mot anticipated
(PRO) Frequency of data collection or sampling: other Monthly 90% of
the data
(NOB) Number of observations in data base: 3000.(Estimated)
(NEI) EstiMated annual increase of observations in data base: 100.
(INF) Data base includes: Ran data/observations
(NTS) Total number of stations or sources covered in data base: 80.
(NCS) NO. stations or sources currently originating/contributing data:
10.
(NOF) NuMber of facilities covered in data base (source Monitoring): (N
/A.)
(GEO) Geographic coverage of data base: Geographic region selected
locations in selected states
(LOC) Data elements identifying location of station or source include:
State ;County ;Clty ; Town/town ship ;Street address
(COB) Pollutant identification data ares encoded
(LIM) Limitation/variation in data of which user should be aware: Exten
sive annual sampling 1970-72. No data 1972-74. Fewer samples
fro* 1975 on. Currently data base covers California* Montana*
Illinois* Mississippi and Texas.
(DPR) Data collect./anal, procedures conform to GRD guidelines: Saaplin
g plan documented /Collection Method documented /Analysis Method
document
(ANL) Lab analysis based on EPA-approved or accepted Methods? YES
(PRE) Precision: Precision and accuracy estimates are not available
(EOT) Editting: No known edit procedures exist.
(CBY) Data collected by: EPA headquarters Field Studies Branch*
Exposure Evaluation Division.
(ABf) Data analyzed by: EPA lab Office of Pesticide Programs Beltway
Lab (Washington* D.C.) for other data.
Contractor lab Various* currently: Midwest Research Institute
(IDL) Laboratory identification: HO
(PR1) Primary purpose of data collection: Risk assessment
(PR2) Secondary purpose of data collection: Anticipatory/research
892
-------
Accession No. 7301400903 Ccont)
(AUT) Authorization for data collection: Statutory authorization is P
L 92-516 as amended by P L 94-140 and PL 95-396 section 20
(The Federal Insecticide, Fungicide, and Rodenticide Act-FIFRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Publications
Air Pollution froa Pesticides and Agricultural Processes (CRC
Press)
(•OS) Number of regular users of data base: 50
(USR) Current regular users of data base: EPA headquarter offices
Office of General Counsel Office of Pesticide Programs
States
(CNF) confidentiality of data and Halts on access: No Halts on
access to data
(DLC) Primary physical location of data: Headquarters office
(DST) Fora of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base naster file up-date: Annually
(RDBEPA) Related EPA data bases used in conjunction uith this data base
Pesticides in Soil; Pesticides in Hater; Pesticides in Humans?
Pesticides in Estuary Fishes and Animals.
(CMP) Completion of fora:
Henry Yang
OFC: EPA/(OPTS)/(OTS)/(EED)/(FSB)
AD: 401 M St., S.H. Washington, D.C. 20460
PH: (202)382-3578
(OF) Date of fora coapletlon: 01-26-83
(•MAT) Nuaber of substances represented in data base: 39
(•CAS) Nuaber of CAS registry numbers in data base: 33
(HAT) Substances represented in data base:
2,4,5-t esters endrin<72-20-8>
2,4-d esters ethion<563-12-2>
4,4*-ddd(p,p"tde) ethyl parathion<56-38-2>
4,4"-dde(p,P *-ddx)<72-55-9> guthion<86-50-0>
4,4'-ddt<50-29-3> heptachlor epoxide<1024-57-3>
aldrin<309-00-2> h«ptachlor<76-44-8>
bhc (lindane)-gamaa<58-89-9> hexachlorobenzene<118-74-l>
bhc-alpha<319-84-6> lindane<58-89-9>
bhc-beta<319-85-7> aalathion<121-75-5>
bhc-delta<319-86-8> aethoxychlor<72-43-5>
captan<133-06-2> aethyl parathion<298-00-0>
carbofuran<1563-66-2> parathion<56-38-2>
chlordane<57VM-9> phorate<298-02-2>
ddd(tde) polychlorinated biphenyls (PCBs)
ddt ronneK 299-84-3>
deaeton<8065-48-3> tde<72-54-8>
diazinon<333-41-5> toxaphene<8001-35-2>
dleldrin<60-57-l> trifluraline
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endosulfan<115-29-7>
893
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Accession No. 7301400903 (cont)
(CAS) CAS registry numbers of substances included in data base: 72-55-9
; 50-29-3* 309-00-2; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
133-06-2; 1563-66-2; 57-74-9; 8065-48-3; 333-41-5; 60-57-1;
959-98-8; 33213-65-9; 115-29-7; 72-20-8; 563-12-2; 56-38-2;
86-50-0; 1024-57-3; 76-44-8; 118-74-1; 58-89-9; 121-75-5;
72-43-5; 298-00-0; 56-38-2; 298-02-2; 299-84-3; 72-54-8;
8001-35-2; 1582-09-8
(CUM) Contact naae(s): Yang,H.
(COR) Contact organization: Field Studies Branch, Exposure Evaluation
Division
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Exposure Evaluat
894
-------
Accession No. 7301400904
(DO) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: National Estuarine Monitoring
Program
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Tissue fish and shellfish
(ABS) Abstract/Overviey of Data Base or Model: The National Estuarine
Monitoring Program tested for levels of pesticides and other
toxic substances in fish and shellfish. The data from this
program was never made into a data base and computerized.
(CTC) CONTACTS: Subject natter Dr. F. ». Kutz (202)755-8060 ;
EPA Office David Redford (202)382-3583
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Discontinued
(NPP) Non-pollutant parameters included In the data base: Biological
data Concentration measures ^Location ;Sampling date ; residue
levels: whole fish ;residue levels: shellfish ;residue levels: fish
livers ; Geographic subdivision bay
(DS) Time period covered by data base: 01-01-65 TO 12-30-78
(TRM) Termination of data collection: Occurred 12/30/78
(FRQ) Frequency of data collection or sampling: Other several separate
studies, at the approximate rate of at least one per year
(NOB) Number of observations in data base: 10000.(Estimated)
(NEI) Estimated annual increase of observations in data base: 0.
(INF) Data base includes: Raw data/observations ;Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: (over
)200.
(NCS) No. stations or sources currently originating/contributing data:
(NOF) Number of facilities covered in data base (source monitoring): (N
(CEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
State ;water body
(CDE) Pollutant identification data are: Hncoded
(LIM) Limitation/variation in data of which user should be aware: Proto
col and parameters may differ for separate studies.
(DPR) Data collect./anal, procedures conform to ORD guidelines: ORD
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates are not available
(EDT) Editting: No known edit procedures exist.
(CBY) Data collected by: EPA lab Toxicant Analysis Center;
Environmental Research Lab, Gulf Breeze
(ABf) Data analyzed by: EPA lab Toxicant Analysis Center;
Environmental Research Lab, Gulf Breeze
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Special study
(AOT) Authorization for data collection: Statutory authorization is P
L 92-516 as amended, Section 20 (The Federal Insecticide,
Fungicide and Rodenticide Act-FIFRA) *„,..-.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms.
895
-------
Accession Ho. 7301400904 (cont)
QQ
(REP) Fora of available reports and outputs of data base: Publications
"Pesticide and PCB Residues in Estuarine Finfish* Pesticide
Monitoring Journal
Journal articles
(NOS) lumber of regular users of data base: 15-20
(OSR) Current regular users of data base: EPA headquarter offices
Office of General Counsel/ Office of Pesticides and Toxic
Substances, Office of Toxic Substances
EPA regional offices
EPA laboratories
Other federal agencies
States _ , . . .
(C»F) Confidentiality of data and limits on access: lo Units on
access to data
(DLC) Primary physical location of data: Headquarters office
(DST) Fora of data storage: Original fora (hardcopy, readings)
(OAC) Type of data access: journals
(CHG) Direct charge for non-EPA use: Bo
(OPDT) Frequency of data base master file up-date: Other Data base no
longer being updated
(CMP) Completion of fora:
David Redford
OFC: EPA/(OPTS}/(OTS)/(EED)/(FSB)
AD: 401 M St., S.M. Washington, D.C. 20460
PH: (202)382-3583
(DP) Date of for» completion: 01-26-83
(NMAT) lumber of substances represented in data base: 23
(RCAS) Number of CAS registry numbers in data base: 18
(MAT) Substances represented in data base:
aldrin<309-00-2> endosulfan<115-29-7>
2, 4,5- trichlorophenoxy acetic acid ethion< 563-1 2-2>
(T)<93-76-5> heptachlor<76-44-8>
2,4-dichlorophenoxyacetic acid (2, lindane<5!;5?'?L^N
4-dK94-75-7> malathlon<121-75-5>
DEF mirex<2385-85-5>
azinphosmethyl Pjrat5i;««6;?8;?>
carbophenothiron phorate<29 8-0 2- 2>
chlordane<57-74-9> polychlorinated blphenyls (PCBs)
silvex<93-72-l>
demeton<8065-48-3>
dia2inon<333-41-5> trifluraline
(CAS)lecASl?egistry numbers of substances included in data base: 309-00-
2s 93-76-52 94-75-71 57-74-9> 8065-48-31 333-41-5; 60-57-1;
115-29-5; 563-12-2, 7i-44-8/ 58-89-9, 121-75-5, 2385-85-5,
56-38-2; 298-02-2, 93-72-1, 8001-35-2, 1582-09-8
(CKf) Contact name(s): Kutz,F.U. , R*2f2rdiS%^ ,, Trtvi^
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances. Off ice of Toxic Substances. Exposure Evaluat
896
-------
Accession No. 7301400905
(DQ) Date of Questionaire: 12-02-82
(MAM) Kane of Data Base of Model: National Surface Water Monitoring
Program
(ACR) Acronym of Data Base or Model: HSHMP
(MED) Media/Subject of Data Base or Model: Surface water streams
(ABS) Abstract/overvieu of Data Base or Model: Contains pesticide
residue and toxic substance Monitoring data on 40 chemicals at
approximately 150 nationwide collection stations*
(CTC) CONTACTS: Subject natter Daniel T. Heggem (202)382-3584;
Cosputer-related Rich Levy (202)382-3895 ; EPA Office
Frederick H. Katz (202)382-3569
(DTP) Type of data collection or Monitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters included in the data base: Collection
•ethod ^Concentration Measures ;Flow rates ;Geographic subdivision
; Location jPhysical data political subdivisions ;Sampling date ;
Site description ^Temperature ;Test/analysis method jUse
;volune/mass Measures
(DS) TiMe period covered by data base: 05-01-76 TO 09-30-81
(TRM) Termination of data collections Not anticipated
(FRQ) Frequency of data collection or sampling: quarterly
(NOB) Number of observations in data base: 90000.(Estimated)
(NED Estimated annual increase of observations in data base: 600-1000.
(INF) Data base includes: Ran data/observations
(NTS) Total number of stations or sources covered in data base: 150.
(NCS) No. stations or sources currently originating/contributing data:
150.
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:.
State ^Coordinates Latitude and longitude
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Other coding scheme
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal. procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented
(ANL) Lab analysis based on EPA-approved or accepted methods? NO
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Other federal agency U.S. Geological
Survey-National Stream Quality Accounting Network (NASQAN) Stations
(ABY) Data analyzed by: EPA lab Bay St. Louis, Ms., Office of
Pesticides and Toxic Substances
EPA headquarters Field Studies Branch, Office of Pesticides and
Toxic Substances
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Trend assessment
(AOT) Authorization for data collection: Statutory authorization is P
L 92-516 as amended. Section 20 (Federal Insecticide, Fungicide
897
-------
Accession No. 7301400905 (cont)
and Rodenticide Act-FIFRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting foras:
QQ
(REP) For* of available reports and outputs of data base: On-line
computer
(•OS) Umber of regular users of data base: 80-100
(OSR) Current regular users of data base: EPA headquarter offices
Office of Pesticides and Toxic Substances
Other federal agencies
States
(CUT) Confidentiality of data and liaits on access: No Halts on
access to data
(OLC) Primary physical location of data: EPA lab
(OST) For* of data storage: Magnetic tape
(DAC) Type of data access: EPA software Soil, Water, Estuarine
Monitoring System (SWEMS) MIDS:7501300900 ;EPA hardware IBM
370/168
(CMC) Direct charge for non-EPA use: no
(DPDT) Frequency of data base Master file up-date: Quarterly
(ROBEPA) Related EPA data bases used in conjunction with this data base
National Soils Monitoring Prograa
(CMP) Completion of for*:
Thoaas Dixon
OFC: EPA/(OPTS)/(EED)/(FSB)/(OTS)
AD: 401 M St, S.V. Washington, DC 20460
PR: (202) 755-8060
(DF) Date of fora completion: 01-26-83
(NMAT) Number of substances represented in data base: 43
(NCAS) Number of CAS registry numbers in data base: 35
(MAT) Substances represented in data base:
( 2, 3,6-trichlorophenyl)aceti endosulf an-alpha<959-98-8>
c acid (fenac) endosulfan-beta<33213-65-9>
2,4,5-trichlorophenol<95-95-4> endrin<72-20-8>
2,4,5-trichlorophenoxyacetlc acid enothion)
(T)<93-76-5> ethion<563-12-2>
2f 4-dichlorophenoxyacetlc acid (2, heptacblor epoxide<1024-57-3>
4-d)<94-75-7> heptachlor<76-44-8>
alachlor<15972-60-8> hexachlorobenzene<118-74-l>
aldrin<309-00-2> isodrin<465-73-6>
atrazine<1912-24-9> •alathion<121-75-5>
bhc (lindane)-gaMa<58-89-9> •ethoxychlor<72-43-5>
bhc-alpha<319-84-6> methyl parathion<298-00-0>
bhc-beta<319-85-7> parathion<56-38-2>
chlordane<57-74-9> pentachlorophenol<87-86-5>
chlorinated naphthalenes phorate<298-02-2>
ddt polybromlnated biphenyls (PBBs)
diazinon<333-41-5> propachlor<1918-16-7>
dicamb ronnel<299-84-3>
dieldrin<60-57-l> st(p-chlorophenylthio)aethyl3 0,0-
dimethyl tetrachloroterephthaiate diethyl phosphorordithioate
(DCPA) (carboph
endosulfan sulfate<1031-07-8> silvex<93-72-l>
898
-------
Accession No. 7301400905 (cont)
siiazine<122-34-9> tributyl phosphorotrithioite
toxaphene<8001-35-2> (nerpbos)
tributyl phosphorotrithioate trifluraline (treflan)
<78-48-8>
(CAS) CAS registry nuabers of substances included in data base: 95-95-4
; 93-76-5; 94-75-7; 15972-60-8; 309-00-2; 1912-24-9; 58-89-9;
319-84-6; 319-85-7; 57-74-9; 333-41-5; 1918-00-9; 60-57-1;
1031-07-8; 959-98-8; 33213-65-9; 72-20-8; 563-12-2; 1024-57-3;
76-44-8; 118-74-1; 465-73-6; 121-75-5; 72-43-5; 298-00-0;
56-38-2; 87-86-5; 298-02-2; 1918-16-7; 299-84-3; 93-72-1;
122-34-9; 8001-35-2; 78-48-8; 1582-09-8
(Cm) Contact nane(s): Heggen/D. ; Levy/R. ; Heggem/D.
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Exposure Evaluat
899
-------
Accession Mo. 7301400909
(DQ) Date of Questionaire: 12-02-82
(RAN) Name of Data Base of Model: Chemicals Identified in Hunan
Biological Media
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Other Hot applicable-data
obtained from published sources
(ABS) Abstract/Overview of Data Base or Model: Centralized collection
of human body burden data fro» world literature and other sources
is contained in this data base* Data is accessible by tissue,
chemical and other pertinent factors. Approximately 500
chemicals are in data base retro- spective to 1974* Reports are
published annually in tabular format and available on-line on
ReCON and DIALOG.
(CTC) CONTACTS: Subject matter Cindy Stroup OTS/EED/DDB (202)
382-3891 ; Computer-related Cindy Stroup QTS/EED/DDB
(202)382-3891 ; EPA Office Cindy Stroup OTS/EED/DDB
(202)382-3891
(DTP) Type of data collection or monitoring: Combination/Other data
collection -human body burden
(STA) Data Base status: Operational/ongoing
(GRp) croups of substances represented in Data Base: 129 307 CHA ;299
hazardous substances ;54 TSCA assessment /RCRA hazardous wastes IS
metals
(NPP) Poo-pollutant parameters Included in the data base: Chemical
data ^Collection method ;Coneentration measures ^Exposure data ;
Geographic subdivision ?Hea1th effects ;Other-toxicity
?Otlter-pathology ; Other-tissue ;Other-experimental design
jOther-metals ;0ther-pesticides
(OS) Time period covered by data base: 01-01-74 TO 10-31-81
(TRM) Termination of data collection: Mot anticipated
(FRQ) Frequency of data collection or sampling: daily
(NOB) Number of observations in data base: 5000(Actual)
(NED Fstimated annual increase of observations in data base: 1500
(INF) Data base includes: Raw data/observations ;Summary or aggregate
observations ^Reference data/citatio
(NTS) Total number of stations or sources covered in data base: (N/A)
(HCS) Ho. stations or sources currently originating/contributing data:
(N/A)
(HOP) Number of facilities covered In data base (source monitoring): (N
/A)
(GEO) Geographic coverage of data base: International
(LOC) Data elements identifying location of station or source include:
State ;County ;City ;Other-country
(FAC) Data elements identifying facility include: Not applicable
(CDE) Pollutant identification data are: CAS registry number
(LIN) Limitation/variation in data of which user should be aware: Data
has not been evaluated. User must exercise own professional
judgement.
(DPR) Data collect./anal, procedures confori to ORD guidelines: Conform
to ORD QA Guidelines-N/A
(AND tab analysis based on EPA-approved or accepted methods? Lab
analysis is not applicable.
900
-------
Accession Ho. 7301400909 (cont)
(ADD) Lab Audit: Lab audit is not applicable.
(PRE) Precision: Precision and accuracy estimates are not applicable.
(EOT) Edltting: Mo known edit procedures exist.
(CBY) Data collected by: Self reporting ;Local agency ;State agency
;Regional office ; Other federal agency /EPA headquarters
;0ther-published literature
(ABY) Data analyzed by: Self reporting
Local agency
State agency
Regional office
Other federal agency
EPA headquarters
Other-published literature
(ADT) Authorization for data collection: Statutory authorization is
TSCA Section 10 P.L. 94-469
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data base: Publications-
Chemicals Identified in Human Biological Media: A Data Base/ 1st
and 2nd Annual Reports. Third in progress.
Unpublished reports-Third Annual Report in progress.
On-line computer
(MOS) Nunber of regular users of data base: 10000
(OSR) Current regular users of data base: EPA headquarter offices-Air/
Hater, OTS/ OPP, Enforcement
SPA regional offices
Other federal agencies
States
international nailing list
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Contractor
(DST) Form of data storage: Magnetic disc ^Original form (hardcopy,
readings)
(DAC) Type of data access: Manually ;ReCON, DIALOG
(CHG) Direct charge for non-EPA use: No
(UPDT) Frequency of data base master file up-date: Weekly
(CMP) Completion of form:
Cindy Stroup
OFC: OTS/Exposure & Evaluation Div/Office of Toxic Substances/EPA
AD: 401 M. Street, S.M. Washington, D.C. 20460 (ET-305)
PH: (202) 382-3891
(OF) Date of form completion: 01-26-83
(•MAT) Number of substances represented in data base: 668
(•CAS) Number of CAS registry numbers in data base: 648
(NAT) Substances represented in data base:
0,0-diethyl-0-(2-pyrazinyl)
-azirino(2-3-:3,4)-pyrrolo(l,2-a) phosphorothioate<297-97-2>
indole-4,7-dione(ester) 0,0-dlethyl-s-(2-ethylthio)ethyl)
<50-07-7> ester of phosphorodithioic acid
0,0-diethyl phosphoric acid,0-p- 0,0-diethyl-s-methyl ester of
nitrophenyl ester<311-45-5> phosphorodithioic acid
901
-------
Accession Ho. 7301400909
(cont)
1, 1,1, 2-te tr achloroethane
<630-20-6>
lf l,l-trichloroethane<71-55-6>
1, If2f 2-te trachloroethane<79-34-5>
l,l,2-trichloroethane<79-00-5>
l,l,2-trichloroethene<79-01-6>
1, l-dichioroethane<75-34-3>
1, 1-dichloroethy lene<75-35-4>
l,l-di«ethylhydrazine<57-14-7>
1, 2, 3, 4, 1 0, 1 0-hexach loro-1, 4, 4 a, 5,
8,8a-hexahydro-l, 4: 5,8- en do,
endo-diaethan
1,2,4,-trichlorobeazene 1,2,4,5-
tetrachlorobenzene<95-94-3>
l,2-dibro«o-3-chloropropane (dbcp)
l,
1,
l,
l,
l,
1,
I,
I
1,
It
If
l,
If
l-
l-
1-
l-
2,
2-dlbro«oethane<106-93-4>
2-dichlorobenzene<95-50-l>
2-dichloroethane<107-06-2>
2-dichioropropane<78-87-5>
2-dichioropropylene<563-54-2>
2-diethylhydrazine<1615-80-l>
2-di«ethylhydrazine<540-73-8>
2-diphcnylhydrazine<122-66-7>
2-propanedlol< 57-55- 6>
2-trans-dichloroethylene
<156-60-5>
3-dichiorobenzene< 541-73-l>
3-dichloropropene<542-75-6>
3-pentadiene<504-60-9>
3-propane sultone<1120-71-4>
4-dichloro-2-butene< 110-57-6>
4-dichlorobenz«ne<106-46-7>
4-dioxane<123-91-l>
4-naphthoquinon«< 1 30-1 5-4>
(o-chloropheny 1) thiourea
<5344-82-l>
(p-chlorobenzoyl)-5-«ethoxy-2-
•ethyiindole-3-ac«tic acid
<53-86-l>
chlo ro- 2, 3- epoxy pr op ane
<106-8 l-naprtthyl-2-thiourea
<86-88-4>
naphthyla«ine<134-32-7>
2-dichloropropionic acid
<75-99-0>
2* 3^ 4, 6- te tr achlor ophenoK 58- 90- 2>
2,4,5-t ajiines
2,4,5-t esters
2,4,5-t salts
2,4,5-tp acid esters
2,4^5-trichlorophenol<95-95-4>
2,4,5-trlchlorophenoxyacetic acid
(T)<93-76-5>
2,4,5-trichlorophenoxypropionic
acid (TP)<93-72-l>
2,4,6-trichlorophenol<88-06-2>
2,4,7,8-tetrachlorodibenzo-p-
dioxin (tcdd)
2,4-d acid<94-75-7>
2,4-d esters
2,4-dichlorophenol<120-83-2>
2,4-dichlorophenoxyacetic acid (2,
4-d)<94-75-7>
2,4-di»ethylphenol<105-67-9>
2,4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2,4-dithiobiuret<541-53-7>
2,6-dichlorophenol<87-65-0>
2,6-dinitrotoluene<606-20-2>
2-acetyla«inoflourene<53-96-3>
2-butanone peroxide<1338-23-4>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene< 91-58-7>
2-chlorophenol<95-57-8>
2-cyclohexyl-4,6-dinitrophenol
<131-89-5>
2-fluoroaceta»ide (1081)<640-19-7>
2-»ethyl-2-(«ethylthio)propionalde
hyde
o-(Methylcarbaw>yl)oxlMe
<116-06-3>
2-«ethylaziridine<75-55-8>
2-«ethyllactonitrile<75-86-5>
2-naphthyla«ine<91-59-8>
2-nitrophenol<88-75-5>
2-nitropropane<79-46-9>
2-picoline<109-06-8>
2-propyn-l-ol<107-19-7>
2-sec butyl-4,6-dlnitrophenol
<88-»85r7>
3,3*-dichlorobenzidine<91-94-l>
3,3 *-di»e thoxybenz idine<119-90-4>
3,3*-di«ethyl-l(»ethylthio)-2-
butanone-0-((»ethyla«ino)
carbonyDoxiae
3,3 *-di«ethylbenzidine
<119-9 3,4-benzofluoranthene
<205-99-2>
3,4-dihydroxy-alpha-((«ethyla»ino)
•ethyl) benzyl alcohol<51-43-4>
3-chloropropionitrile<542-76-7>
3-«ethylcholanthrene<56-49-5>
39196-18-4>
902
-------
Accession No. 7301400909
(cont)
4/ 4 '-ddd(p/p 'tde )<72-54-8>
4,4'-dde(p/p*-ddx<72-55-9>
4/4'-ddt<50-29-3>
4/4'-nethylene-bis-(2-chloroanilin
4/6-dinitro-o-cresol<534-52-l>
4-A«inopyridine<504-24-5>
4-bromophenyl phenyl ether
<101-55-3>
4-chloro-o-toluidine hydrochlorlde
<3165-93-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
5- ( ami none thyl ) -3-isoxazolol
<2763-96-4>
5-nitro-o-toluidin«< 99-55- 8>
6- amino-1/ la/2/8/8 a/ 8b-hex ahydro-
8-hydroxyaethyl-8-methoxy-5-
nethylcarbaaat
Oc tame thylpyrophosphor aside (OMPA)
<152-16-9>
acenaphthene<83-32-9>
aceraphthylene<208-96-8>
acetaldehyde<75-07-0>
acetic acid<64-19-7>
acetic anhydride<108-24-7>
acetone cyanohydrin<75-86-5>
acetone<67-64-l>
acetonitrile<75-05-8>
ac«tophenone<98-86-2>
acetyl bro«ide<506-96-7>
acetyl chloride<75-36-5>
acrolein<107-02-8>
acrylamide<79-06-l>
acrylic acid<79-10-7>
acrylonitrile<107-13-l>
adipic acid<124-04-9>
aldrin<309-00-2>
allyl alcohol<107-18-6>
allyl chloride<107^05-l>
alpha/ alpha-diaethylbenzylhydro-
peroxide<80-15-9>
alpha/ alpha-dime thylphenethylanine
<122-09-8>
alpha-chlorotoluene<100-44-7>
aluninum phosphide<20 859-7 3-8>
alutinun sulfate<10043-01-3>
anitrole<61-82-5>
a»nonia<7664-41-7>
annoniuB acetate<631-61-8>
annonium benzoate<1863-63-4>
auoniun bicarbonate<1066-33-7>
annoniua bichroaate<7789-09-5>
amoniun bif iuoride<1341-49-7>
ammonium bisulf ite<10192-30-0>
amaoniua carbasate< 1111-7 8-0>
aanoniua carbonate<506-87-6>
anaonium chloride<12125-02-9>
aanoniuM chromate<7788-98-9>
auaoniuB citrate<7632-50-0>
anmoniUH f luoborate<13826-83-0>
aaaoniuB f luoride<12125-01-8>
amoniun hydroxide<1336-21-6>
annoniun oxalate<1113-38-8>
ammonium picrate<131-74-8>
amnoniua silicofluoride
<16919-19-0>
amaoniua sulf anate<7773-06-0>
anmonium sulf ide<12135-76-l>
aaaoniua sulf ite<10196-04-0>
anaonium tartrate<3164-29-2>
ammonium thiocyanate<1762-95-4>
aaaoniua thiosulf ate<7783-18-8>
aayl acetate<628-63-7>
aniline<62-53-3>
anthracene<120-12-7>
antimony pentachloride<7647-18-9>
antiaony potassium tart rate
antiaony tribroaide<7789-61-9>
antiaony trichloride<10025-91-9>
antimony trifluoride<7783-56-4>
antiaony<7440-36-0>
arsenic acid<1327-52-2>
arsenic disulf ide<1303-32-8>
arsenic pentoxide<1303-28-2>
arsenic trichloride<7784-34-l>
arsenic trioxide<1327-53-3>
arsenic trisulfide<1303-33-9>
arsenic<7440-38-2>
asbestos<1332-21-4>
auraaine<2465-27-2>
azaserine<115-02-6>
bariua cyanide<542-62-l>
bariua<7440-39-3>
benz(c)acridine<225-51-4>
benzal chloride<98-87-3>
benzene<71-43-2>
benzenesulfonyl chloride<98-09-9>
benzene thiol<108-98-5>
benzldine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
903
-------
Accession Ho. 7301400909
Ccont)
benzo(g,h,l)perylene<191-24-2>
benzo( k ) f 1 uo rant hene< 207-0 8-9>
benzole acid<65-85-0>
benzonitrile<100-47-0>
benzotrichloride<98-07-7>
benzoyl chloride<98-88-4>
benzyl chloride<100-44-7>
berylliua chloride<7787-47-5>
beryllium dust
beryllium f luoride<7787-49-7>
beryllium nitrate<13597-99-4>
beryllium<7440-41-7>
bhc (lindane)-gam«a<58-89-9>
bhc*alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)methane
bls(2-chloroethyl)ether
bis(2-chloroisopropyl)ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloro«ethyl)ether<542-88-l>
bro«oacetone<598-31-2>
bro»o»ethane<74-83-9>
brucine<357-57-3>
butyl acetate<123-86-4>
butyl benzyl phthalat«<85-68-7>
butyla«ine<109-73-9>
butyric aci(K107-92-6>
cad«lu« acetate<543-90-8>
bro«ide<7789-42-6>
chloride
cad«iu»<7440-43-9>
calclua arsenat«<7778-44-l>
calciun arsenlte<52740-16-6>
calclua carbide<75-20-7>
calciui chroma te< 137 6 5-1 9-0 >
calclua cyanlde<592-01-8>
calciua dodecylbenzenesulf onate
<26264-06-2>
calclua hydroxld«<1305-62-0>
calclua hypochlorite<7778-54-3>
calclua oxide<1305-78-8>
captan<133-06-2>
carbaryl<63-25-2>
carbofuran<1563-66-2>
carbon disulflde<75-15-0>
carbon tetrachlorlde<56-23-5>
carbonyl f iuoride<353-50-4>
chloral<75-87-6>
chlora»bucll<305-03-3>
chlordane<57-74-9>
chlorinated ethanes
chlorinated naphthalenes
chlorine<7782-50-5>
chloroacetaldehyde<107-20-0>
chlorobenzene<108-90-7>
chlorobenzilate<510-15-6>
chlorodlbro«o«ethane<124-48-l>
chlocoethane<75*00-3>
chloroethene<75-01-4>
chloroethyl vinyl ether<110-75-8>
chlorofluorocarbons
chlorofor«<67-66-3>
chloroiethane<74-87-3>
chloroaethyl aethyl ether
<107-30-2>
chlcrop rene
chlocosulfonlc acld<7790-94-5>
chlorpyrifos<2921-88-2>
chroalc acetate<1066-30-4>
chromic acld< 7738-94-5>
chromic sulfate<10101-53-8>
chromium<7440-47-3>
chromotis chloride<10049-05-5>
chrysene<218-01-9>
cobalt<7440-48-4>
cobaltous bromlde<7789-43-7>
cobaltous for«ate<544-18-3>
cobaltous sulfamate<140l7-41-5>
copper cyanlde<544-92-3>
copper<7440-50-8>
coumaphos<56-72-4>
cresol<1319-77-3>
cresylic acid<1319-77-3>
crotonaldehyde<4170-30-3>
c u» ene< 98- 8 2- 8>
cuprlc acetate<142-71-2>
cupric acetoarsenlte<12002-03-8>
cuprlc cblorlde<7447-39-4>
cuprlc nltrate<3251-23-8>
cuprlc oxalate<814-91-5>
cuprlc sulfata aaaonlated
<10380-29-7>
cuprlc sulfate<7758-98-7>
cuprlc tartrate<815-82-7>
cyanlde<57-12-5>
cyanogen bro»lde<506-68-3>
cyanogen chlorlde<506-77-4>
cyanogen<460-19-5>
cyclohexane<110-82-7>
cyclohexanone<108-94-l>
904
-------
Accession Mo. 7301400909
(cont)
cyclophospharaide<50-18-0>
daunomycin<20830-81-3>
ddd(tde)<72-54-8>
ddt<50-29-3>
di-isopropylfluorophosphate
<55-91-4>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
di-n-propylnitrosaaine<621-64-7>
diallate<2303-16-4>
diazinon<333-41-5>
dibenzo(ash)anthracene<53-70-3>
dibenzol(a,i)pyrene<189-55-9>
dibroBOchloronethane<124-48-l>
dibro»omethane<74-95-3>
dicamba<1918-00-9>
dichlobenil<1194-65-6>
dichlone<117-80-6>
dichlorobenzene<25321-22-6>
dichlorobroaoaethane<75-27-4>
dichlorodifluoroaethane<75-71-8>
dlchloro»ethanc<75-09-2>
dichlorophenylarsine<696-28-6>
dlchloroprop ane<7 8-87-5>
dichloropropene-dichloropropane
«ixture<8003-19-8>
dichloropropene<542-75-6>
dichlorvos<62-73-7>
dieldrin<60-57-l>
diepoxybutane
diethyl phthalate<84-66-2>
diethylamine
diethylarsine
diethylstllbestrol<56-53-l>
dihydrosafrole<94-58-6>
diraethoate<60-51-5>
diBcthyl phthalate<131-ll-3>
dimethyl sulfate<77-78-l>
dimethylaBine<124-40-3>
dimethyIcarbaraoyl chloride
<79-44-7>
diBethylnitrosaaine<62-75-9>
dinitrobenzene<25154-54-5>
dinitrophenol
dinitrotoluene<25321-14-6>
dioxin<828-00-2>
dipropylaBine<142-84-7>
diquat<2764-72-9>
disulfoton<298-04-4>
diuron<330-54-l>
dodecylbenzenesulfonic acid
<27176-87-0>
e
edta<60-00-4>
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endosulfan<115-29-7>
endrin aldehyde<742l-93-4>
endrin<72-20-8>
epichlorohydrin<106-89-8>
ethion<563-12-2>
ethyl acetate<141-78-6>
ethyl acrylate<140-88-5>
ethyl ether<60-29-7>
ethyl Bethacrylate<97-63-2>
ethyl aethanesulfonate<62-50-0>
ethylbenzene<100-41-4>
ethylcyanide<107-12-0>
ethylene bisdithiocarbanate
ethylene dibromide<106-93-4>
ethylene dichloride<107-06-2>
ethylene oxide<75-21-8>
ethylene thiourea<96-45-7>
ethylenedlaBine
ethyleneiBine<151>56-4>
ferric aamoniUB citrate<1135-57-5>
ferric aaaoniua oxalate
<14221-47-7>
ferric chloride<7705-08-0>
ferric cyanide
ferric fluoride<7783-50-8>
ferric nitrate<10421-48-4>
ferric sulfate<10028-22-5>
ferrous aaaonlua sulfate
<10045-89-3>
ferrous chloride<7758-94-3>
ferrous sulfate<7720-78-7>
fluoranthene<206-44-0>
fluorene<86-73-7>
fluorine<7782-41-4>
fluoroacetic acid, sodiua salt
<62-74-8>
fluorotrichloroaethane<75-69-4>
foraaldehyde<50-00-0>
formic acid<64-18-6>
fuaaric acid<110-17-8>
furan<110-00-9>
furfural<98-01-l>
glycidylaldehyde<765-34-4>
guthion<86-50-0>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
905
-------
Accession Mo. 7301400909
4cont)
hexach!orobutadiene<87-68-3>
hexachlorocyclohexane<58-89-9>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
he xachloro phene<7 0-30-4>
hexachloropropene<1888-71-7>
hexaethyl tetraphosphate<757-58-4>
hydrazine<302-01-2>
hydrochloric acld<7647-01-0>
hydrocyanic acid<74-90-8>
hydrofluoric acid<7664-39-3>
hydrogen cyanide<74-90-8>
hydrogen sulfide<7783-06-4>
hydroxydiaethyl arsine oxide
<75-60-5>
indeno (1*2,3-cd)pyrene<193-39-5>
iodo*ethane<74-88-4>
iron dextran<9004-66-4>
iron<7439-89-6>
isobutyl alcohol<78-83-l>
isocyanic acid* aethyl ester
<624-83-9>
isophorone<78-59-l>
isoprene<78-79-5>
isopropanolaaine dodecylbenzene
sulfonate<54590-52-2>
isosafrole<120-58-l>
kelthane<115-32-2>
kepone<143-50-0>
lasiocarpine<303-34-4>
lead acetate<301-04-2>
lead arsenate<3687-31-8>
lead chloride<7758-95-4>
lead fluorborate<13814-96-5>
lead fluorlde<7783-46-2>
lead iodlde<10101-63-0>
lead nitrate<10099-74-8>
lead phosphate<7446-27-7>
lead stearate<1072-35-l>
lead subacetate<1335-32-6>
lead sul£ate<7446-14-2>
lead sulfide<1314-87-0>
lead thlocyanate<592-87-0>
lead<7439-92-l>
lindane<58-89-9>
llthiua chro»ate<14307-35-8>
»-cresol<108-39-4>
»-xylene<108-38-3>
•alathion<121-75-5>
•alcic acld<110-16-7>
•alelc anhydride<108-31-6>
•aleic hydrazide<123-33-l>
•alononitrile<109-77-3>
•anganese and co»pounds<7439-96-5>
•elphalan<148-82-3>
•ercaptodinethur< 2032-65-7>
•ercurie cyanide<592-04-l>
•ercuric nitrate<10045-94-0>
•ercuric sulfate<7783-35-9>
•ercuric thiocyanate<592-85-8>
•ercurous nitrate<10415-75-5>
•ercury ful»inate<628-86-4>
•ercury<7439-97-6>
»ethanethiol<74-93-l>
•ethanol<67-56-l>
•ethapyrilene<91-80-5>
»etho«yl<16752-77-5>
•ethoxychlor<72-43-5>
»ethyacrylonitrile<126-98-7>
•ethyl chlorocarbonate<79-22-l>
•ethyl ethyl ketone («ek)<78-93-3>
•ethyl ethyl ketone peroxide
<1338-23-4>
•ethyl hydrazine<60-34-4>
•ethyl iodide<74-88-4>
•ethyl isobutyl ketone<108-10-l>
•ethyl »ercaptan<74-93-l>
•ethyl »ethacrylate<80-62-6>
•ethyl parathion<298-00-0>
•ethylthiouraciK 56-04-2>
•evinphos<7786-34-7>
•exacarbate<315-18-4>
•onoethyla«lne<75-04-7>
»onoHethylamine<74-89-5>
n/n-bis(2-chlotoethyl)-2-naphthyla
•ine<494-03-l>
n-butyl alcohol<71-36-3>
n-butyl phthalate<84-74-2
n-«ethyl-n*-nitro-n-
nitrosoguanidine<70-25-7>
n-nitroso-n-ethylurea<759-73-9>
n-nitroso-n-«ethylurea<684-93-5>
n-nitroso-n-«ethylurethane
<615-53-2>
n-nitroscdi-n-butyla«ine<924-16-3>
n-nitrosodi-n-propylaaine
<621-64-7>
n-nitrosodiethanola»ine<1116-54-7>
n-nltrosodiethyla«ine<55-18-5>
n-nitrosodi«ethyla«ine<62-75-9>
n-nitrosodiphenyla«ine<86-30-6>
n-nitrosomethylvinylamine
<4549-40-0>
n-nitrosopiperidine<100-75-4>
906
-------
Accession No. 7301400909
(cont)
n-nitrosopyrrolidine<930-55-2>
n-phenylthiourea<103-85-5>
n-propyla»ine<107-10-8>
naleoX300-76-5>
naphthalene< 9l-20-3>
naphthenic acid< 1338-2 4-5>
nickel amnoniua sulfate<7785-20-8>
nickel car bony l<12612-55-4>
nickel chloride<7718-54-9>
nickel cyanide<557-19-7>
nickel hydroxide<12054-48-7>
nickel nitrate<13138-45-9>
nickel sulfate<7786-81-4>
nickel<7440-02-0>
nicotine and salts<54-ll-5>
nitric acid<7697-37-2>
nitric oxide<10102-43-9>
ni trobenzene< 9 8- 95-3>
nitrogen dioxide<10102-44-0>
nitrogen peroxide<10102-44-0>
nitrogen tetroxide<10544-72-6>
nitroglycerine<55-63-0>
nitrophenol<25l54-55-6>
nitrotoluene
o-cresol<95-48-7>
o-toluidine hydrochloride
<636-21-5>
o-xy lene< 95- 47-6>
oil and grease
oleyl alcohol condensed with 2
•oles ethylene ox ide< 9004-98- 2>
onaphthalene<465-73-6>
osBiua tetroxide<20816-12-0>
p-chloro-«-cresol<59-50-7>
p-chloroaniline<106-47-8>
p-cresol<106-44-5>
p-dimethyla«inoazobenzen€<60-ll-7>
p-nitroaniline<100-01-6>
p-xylene<106-42-3>
parafor«aldehyde<30525-89-4>
paraldehyde<123-63-7>
par athion< 56-38- 2>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arocblor 1232)
pcb-1242 (arochlor 1242)
<53 469-21 -9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorobenzene<608-93-5>
pentachloroethane<76-01-7>
pentachloronitrobenzene (PCNB)
<82-68-8>
pentachlorophenol<87-86-5>
phenacetin<62-44-2>
phenanthrene<85-01-8>
phenol<108-95-2>
phenyl dichloroarsine<696-28-6>
phenylnercury acetate<62-38-4>
phorate<298-02-2>
phosgene<75-44-5>
phosphine<7803-51-2>
phosphoric acid<7664-38-2>
phosphorothioic acid,o,o-diaethyl
esterro-ester yith n/n-dimethyl
benzene s
phosphorus oxychloride
< phosphorus pentasulflde
<1314-80-3>
phosphorus sulfide<1314-80-3>
phosphorus trichloride<7719-12-2>
phosphorus<7723-14-0>
phthalic anhydride<85-44-9>
polybrominated biphenyls (PBBs)
polychlocinated biphenyls (PCBs)
<1336-36-3>
potassiUM arsenite<10124-50-2>
potassium bichro«ate<7778-50-9>
potassiuc chroaate<7789-00-6>
potassiUB cyanide<151-50-8>
potassiua hydroxide
potassiui pernanganate<7722-64-7>
potassiua silver cyanide<506-61-6>
potassiu«-arsenate<7784-41-0>
prona«ide<23950-58-5>
propargite<2312-35-8>
prop ionic acid<79-09-4>
propionic anhydride<123-62-6>
propionitrile<107-12-0>
propylene oxide<75-56-9>
pyrene<129-00-0>
pyrethrin<121-29-9>
pyridine<110-86-l>
quinoline<91-22-5>
quinones
reserpine<50-55-5>
resorcinol
907
-------
Accession Ho. 7301400909
(cent)
saccharitK 81-07-2>
safrole<94-59-7>
selenious acid<7783-00-8>
selenium oxide<12640-89-0>
selenium sulfide<7446-34-6>
selenium<7782-49-2>
selenourea<630-10-4>
silver cyanide<506-64-9>
silver nitrate<7761-88-8>
silver<7440-22*4>
sodium arsenate<7631-89-2>
sodium arsenlte<7784-46-5>
sodium azide<26628-22-8>
sodium bichromate<10588-01-9>
sodium blfluorlde<1333-83-l>
sodiUB bisuifite<7631-90-5>
sodita chromate<7775-ll-3>
sodium cyanide<143-33-9>
sodium dodecylbenzenesulfonate
<25155-30-0>
sodiua fluoride<768l-49-4>
sodiUB hydrosulfide<16721-80-5>
sodiui hydroxide<1310-73-2>
sodluB hypochlorite<7681-52-9>
sodiua »ethylate
sodlua nitrlte<7632-00-0>
sodliia phosphate^ dibasic
<7558-79-4>
sodluB phosphate^ trlbasic
<7601-54-9>
sodiua selenlte<10102-18-8>
sodiua<7440-23-5>
sir eptozotocin
strontium chroiate<7789-06-2>
strontium sul£ide<1314-96-l>
strychnln«<57-24-9>
«tyrene<100-42-5>
sulfur «onochloride<10025-67-9>
sulfurlc acid<7664-93-9>
tde<72-54-8>
tctrachloroethene<127-18-4>
tetrachloroethylene
tatrachloro««than€<56-23-5>
tetraethyl dithiopyrophosphate
<3689-24-5>
tatraethyl lead<78-00-2>
tetraethyl pyrophosphat«<107-49-3>
tetrahydofuran<109-99- 9>
tetranitromethane<509-14-8>
thailie oxide<1314-32-5>
thallium acetate<563-68-8>
thallium carbonate<29809-42-5>
thallium chloride<779l-12-0>
thallium nitrate<10l02-45-l>
thallium selenite<12039-52-0>
thallium sulf ate<7446-l 8-6>
thailium<7440-28-0>
thioacetamide<62-55-5>
thios«mlcarbazide<79-19-6>
thiourea<62-56-6>
thiura«<137-26-8>
titanium<7440-32-6>
toluene diisocyanate<26471-62-5>
toluene<108-88-3>
tolu«nedia«lne<25376-45-8>
toxaphene<8001-35-2>
tribromo«ethane<75-25-2>
trichlorfon<52-68-6>
trichloroethane<25323-89-l>
trichloroethene<79-01-6>
trichloroethylene<79-01-6>
trichlorofluoromethane<75-69>4>
trichloromethanethiol<75-70-7>
tcichlorophenol (TCP)<25167-82-2>
triethanolamine dodecylbenzenesulf
onate<27323-41-7>
triethylamine<121-44-8>
trimethylamine
<75-50-3> trinitrobenzene
<99-35-4>
tris(2,3-dibromop ropy 1) phosphate
<1 26-7 2-7 >
trypan blue<72-57-l>
ulfonamide<52-85-7>
uracil mustard<66-75-l>
uranyl acetate<541-09-3>
uranyl nitrate<10102-06-4>
urethane<51-79-6>
vanadic acid, ammonium salt
vanadium pentoxide<1314-62-l>
vanadium<7440-62-2>
vanadyl sulfate<27774-13-6>
vinyl ac«tate<108-05-4>
vinyl chloride<75-01-4>
vinylideoe chloride<75-35-4>
xylene<1330-20-7>
xylenol<1300-71-6>
zinc ace tate< 557-3 4-6 >
zinc ammonium chloride
zinc borate<1332-07-6>
zinc bromide<7699-45-8>
zinc carbonate<3486-35-9>
zinc ch lor ide< 7646- 85-7>
903
-------
Accession Ho. 7301400909 (cont)
zinc cyanide<557-21-l> zinc sul£ate<7733-02-0>
zinc fluoride<7783-49-5> zinc<7440-66-6>
zinc formate<557-41-5> zirconiui nitrate
zinc hydrosulfIte<7779-86-4> zirconiu* potassiua fluoride
zinc nitrate<7779-88-6> <16923-95-8>
zinc phenol sulfonate<127-82-2> zirconiua sulfate
zinc phosphide<1314-84-7> zirconiua tetrachloride
zinc silicofluoride <10026-ll-6>
(CAS) CAS registry numbers of substances included in data base: 50-07-7
; 311-45-5; 297-97-2; 630-20-6; 71-55-6; 79-34-5; 79-00-5;
79-01-6; 75-34-3; 75-35-4; 57-14-7; 95-94-3; 96-12-8; 106-93-4;
95-50-1; 107-06-2; 78-87-5; 563-54-2; 1615-80-1; 540-73-8;
122-66-7; 57-55-6; 156-60-5; 541-73-1; 542-75-6; 504-60-9;
1120-71-4; 110-57-6; 106-46-7; 123-91-1; 130-15-4; 5344-82-1;
53-86-1; 134-32-7; 75-99-0; 58-90-2; 95-95-4; 93-76-5; 93-72-1;
88-06-2; 94-75-7; 120-83-2; 94-75-7; 105-67-9; 51-28-5;
121-14-2; 541-53-7; 87-65-0; 606-20-2; 53-96-3; 1338-23-4;
110-75-8; 91-58-7; 95-57-8; 131-89-5; 640-19-7; 116-06-3;
75-55-8; 75-86-5; 91-59-8; 88-75-5; 79-46-9; 109-06*8;
107-19-7; 88-85-7; 91-94-1; 119-90-4; 51-43-4; 542-76-7;
56-49-5; 72-54-8; 72-55-9; 50-29-3; 101-14-4; 534-52-1;
504-24-5; 101-55-3; 3165-93-3; 7005-72-3; 100-02-7; 2763-96-4;
99-55-8; 152-16-9; 83-32-9; 208-96-8; 75-07-0; 64-19-7; 108-24-7;
75-86-5; 67-64-1; 75-05-8; 98-86-2; 506-96-7; 75-36-5;
107-02-8; 79-06-1; 79-10-7; 107-13-1; 124-04-9; 309-00-2;
107-18-6; 107-05-1; 80-15-9; 122-09-8; 100-44-7; 20859-73-8;
10043-01-3; 61-82-5; 7664-41-7; 631-61-8; 1863-63-4; 1066-33-7;
778S-09-5; 1341-49-7; 10192-30-0; 1111-78-0; 506-87-6; 12125-02-9;
7788-98-9; 7632-50-0; 13826-83-0; 12125-01-8; 1336-21-6; 1113-38-8;
131-74-8; 16919-19-0; 7773-06-0; 12135-76-1; 10196-04-0; 3164-29-2;
1762-95-4; 7783-18-8; 628-63-7; 62-53-3; 120-12-7; 7647-18-9;
11071-15-1; 7789-61-9; 10025-91-9; 7783-56-4; 7440-36-0; 1327-52-2;
1303-32-8; 1303-28-2; 7784-34-1; 1327-53-3; 1303-33-9; 7440-38-2;
1332-21-4; 2465-27-2; 115-02-6; 542-62-1; 7440-39-3; 225-51-4;
98-87-3; 71-43-2; 98-09-9; 108-98-5; 92-87-5; 56-55-3; 50-32-8;
191-24-2; 207-08-9; 65-85-0; 100-47-0; 98-07-7; 98-88-4; 100-44-7;
7787-47-5; 7787-49-7; 13597-99-4; 7440-41-7; 58-89-9; 319-84-6;
319-85-7; 319-86-8; 111-91-1; 111-44-4; 39638-32-9; 117-81-7;
542-88-1; 598-31-2; 74-83-9; 357-57-3; 123-86-4; 85-68-7; 109-73-9;
107-92-6; 543-90-8; 7789-42-6; 7440-43-9; 7778-44-1; 52740-16-6;
75-20-7; 13765-19-0; 592-01-8; 26264-06-2; 1305-62-0; 7778-54-3;
1305-78-8; 133-06-2; 63-25-2; 1563-66-2; 75-15-0; 56-23-5;
353-50-4; 75-87-6; 305-03-3; 57-74-9; 7782-50-5; 107-20-0;
108-90-7; 510-15-6; 124-48-1; 75-00-3; 75-01-4; 110-75-8;
67-66-3; 74-87-3; 107-30-2; 126-99-8; 7790-94-5; 2921-88-2;
1066-30-4; 7738-94-5; 10101-53-8; 7440-47-3; 10049-05-5;
218-01-9; 7440-48-4; 7789-43-7; 544-18-3; 14017-41-5;
544.92-3; 7440-50-8; 56-72-4; 1319-77-3; 1319-77-3;
4170-30-3; 98-82-8; 142-71-2; 12002-03-8; 7447-39-4; 3251-23-8;
814-91-5; 10380-29-7; 7758-98-7; 815-82-7; 57-12-5; 506-68-3;
506-77-4; 460-19-5; 110-82-7; 108-94-1; 50-18-0; 20830-81-3;
72-54-8; 50-29-3; 55-91-4; 84-74-2; 117-84-0; 621-64-7;
909
-------
Accession No. 7301400909 (cont)
2303-16-4; 333-41-5; 53-70-3; 189-55-9; 124-48-1; 74-95-3;
1918-00-9; 1194-65-6; 117-80-6; 25321-22-6; 75-27-4; 75-71-8;
75-09-2; 696-28-6; 78-87-5; 8003-19-8; 542-75-6; 62-73-7;
60-57-1; 1464-53-5; 84-66-2; 109-89-7; 56-53-1; 94-58-6;
60-51-5; 131-11-3; 77-78-1; 124-40-3; 79-44-7; 62-75-9;
25154-54-5; 25321-14-6; 828-00-2; 142-84-7; 2764-72-9; 298-04-4;
330-54-1; 27176-87-0; 60-00-4; 1031-07-8; 959-98-8; 33213-65-9;
115-29-7; 7421-93-4; 72-20-8; 106-89-8; 563-12-2; 141-78-6;
140-88-5; 60-29-7; 97-63-2; 62-50-0; 100-41-4; 107-12-0;
106-93-4; 107-06-2; 75-21-8; 96-45-7; 107-15-3; 151-56-4;
1185-57-5; 14221-47-7; 7705-08-0; 7783-50-8; 10421-48-4;
10028-22-5; 10045-89-3; 7758-94-3; 7720-78-7; 206-44-0;
86-73-7; 7782-41-4; 62-74-8; 75-69-4; 50-00-0; 64-18-6; 110-17-8;
110-00-9; 98-01-1; 765-34-4; 86-50-0; 1024-57-3; 76-44-8;
118-74-1; 87-68-3; 58-89-9; 77-47-4; 67-72-1; 70-30-4;
1888-71-7; 757-58-4; 302-01-2; 7647-01-0; 74-90-8; 7664-39-3;
74-90-8; 7783-06-4; 75-60-5; 193-39-5; 74-88-4; 9004-66-4;
7439-89-6; 78-83-1; 624-83-9; 78-59-1; 78-79-5; 54590-52-2;
120-58-1; 115-32-2; 143-50-0; 303-34-4; 301-04-2; 3687-31-8;
7758-95-4; 13814-96-5; 7783-46-2; 10101-63-0; 10099-74-8;
7446-27-7; 1072-35-1; 1335-32-6; 7446-14-2; 1314-87-0; 592-87-0;
7439-92-1; 58-89-9; 14307-35-8; 108-39-4; 108-38-3; 121-75-5;
110-16-7; 108-31-6; 123-33-1; 109-77-3; 7439-96-5; 148-82-3;
2032-65-7; 592-04-1; 10045-94-0; 7783-35-9; 592-85-8;
10415-75-5; 628-86-4; 7439-97-6; 74-93-1; 67-56-1; 91-80-5;
16752-77-5; 72-43-5; 126-98-7; 79-22-1; 78-93-3; 1338-23-4;
60-34-4; 74-88-4; 108-10-1; 74-93-1; 80-62-6; 298-00-0;
66-04-2; 7786-34-7; 315-18-4; 75-04-7; 74-89-5; 494-03-1;
71-36-3; 84-74-2; 759-73-9; 684-93-5; 615-53-2; 924-16-3;
621-64-7; 1116-54-7; 55-18-5; 62-75-9; 86-30-6; 4549-40-0;
100-75-4; 930-55-2; 103-85-5; 107-10-8; 300-76-5; 91-20-3;
1338-24-5; 7785-20-8; 12612-55-4; 7718-54-9; 557-19-7;
12054-48-7; 13138-45-9; 7786-81-4; 7440-02-0; 54-11-5; 7697-37-2;
10102-43-9; 98-95-3; 10102-44-0; 10102-44-0; 10544-72-6; 55-63-0;
25154-55-6; 95-48-7; 636-21-5; 95-47-6; 9004-98-2; 465-73-6;
20816-12-0; 59-50-7; 106-47-8; 106-44-5; 60-11-7; 100-01-6;
106-42-3; 30525-89-4; 123-63-7; 56-38-2; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 608-93-5; 76-01-7; 82-68-8; 87-86-5; 62-44-2;
85-01-8; 108-95-2; 696-28-6; 62-38-4; 298-02-2; 75-44-5;
7803-51-2; 7664-38-2; 1314-80-3; 7719-12-2; 7723-14-0; 85-44-9;
1336-36-3; 10124-50-2; 7778-50-9; 7789-00-6; 151-50-8;
1310-58-3; 7722-64-7; 506-61-6; 7784-41-0; 23950-58-5;
2312-35-8; 79-09-4; 123-62-6; 107-12-0; 75-56-9; 129-00-0;
121-29-9; 110-86-1; 91-22-5; 50-55-5; 108-46-3; 81-07-2;
94.59.7. 7783-00-8; 12640-89-0; 7446-34-6; 7782-49-2; 630-10-4;
506-64-9; 7761-88-8; 7440-22-4; 7631-89-2; 7784-46-5;
26628-22-8; 10588-01-9; 1333-83-1; 7631-90-5; 7775-11-3;
143-33-9; 25155-30-0; 7681-49-4; 16721-80-5; 1310-73-2;
7681-52-9; 124-41-4; 7632-00-0; 7558-79-4; 7601-54-9;
10102-18-8; 7440-23-5; 7789-06-2; 1314-96-1; 57-24-9; 100-42-5;
10025-67-9; 7664-93-9; 72-54-8; 127-18-4; 127-18-4; 56-23-5;
910
-------
Accession Mo. 7301400909 (cont)
3689-24-5; 78-00-2; 107-49-3; 109-99-9; 509-14-8; 1314-32-5;
563-68-8; 29809-42-5; 7791-12-0; 10102-45-1; 12039-52-0; 7446-18-6;
7440-28-0; 62-55-5; 79-19-6; 62-56-6; 137-26-8; 7440-32-6;
26471-62-5; 108-88-3; 25376-45-8; 8001-35-2; 75-25-2; 52-68-6;
25323-89-1; 79-01-6; 79-01-6; 75-69-4; 75-70-7; 25167-82-2;
27323-41-7; 121-44-8; 75-50-3; 99-35-4; 126-72-7; 72-57-1; 52-85-7;
66-75-1; 541-09-3; 10102-06-4; 51-79-6; 11115-67-6; 1314-62-1;
7440-62-2; 27774-13-6; 108-05-4; 75-01-4; 75-35-4; 1330-20-7;
1300-71-6; 557-34-6; 1332-07-6; 7699-45-8; 3486-35-9; 7646-85-7;
557-21-1; 7783-49-5; 557-41-5; 7779-86-4; 7779-88-6; 127-82-2;
1314-84-7; 16871-71-9; 7733-02-0; 7440-66-6; 13746-89-9;
16923-95-8; 14644-61-2; 10026-11-6
(CNN) Contact narae(s): OTS,C.S. ; OTS,C.S.
(COR) Contact organization: Cindy Stroup OTS/EED/DDB
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Exposure Evaluat
911
-------
Accession Ho. 7301700901
(DQ) Date of Questionaire: 12-02-82
(STATUS) Status of entry: Test Data Bank
(HAM) Have of Data Base of Model: Scientific Paraaeters in Health and
the Environment, Retrieval and Estivation
(ACR) Acronym of Data Base or Model: SPHERE
(MED) Media/Subject of Data Base or Model: Physical-Chemical
properties. Health Effects, Environmental Affects and Environmental
Fate.
(ABS) Abstract/Overview of Data Base or Model: This data bank is a
repository for scientific data generated by, submitted to, or
collected by or for the Office of Toxic Substances (OTS).
SPHERE is currently a test component of the HIH/EPA Chemical
Information System (CIS) which provides substructure search and
data analysis capabilities for OTS to use in conjunction with
their scientific data.
(CTC) COHTACTS: Paula Miles (202) 382-3775
(DTP) Type of data collection or monitoring: Data extracted from the
literature, EPA summary data, and Unpublished laboratory test
result data.
(STA) Cata Base status: Funded for development
(DPO) Projected operational date of Data Base: 08-01-83
(HPP) Non-pollutant parameters included in the data base: Physical-chem
ical properties, health effects, environmental effects and
environmental fate data.
(DS) Time period covered by data base: 01-01-70 to 01-01-81
(TRM) Termination of data collections Hot anticipated
(FRQ) Frequency of data collection or sampling: as needed ;Qther file
building/as funded
(ROB) Number of observations In data base: 25,000 records
(HEX) Estimated annual increase of observations in data base: 15,000
records
(IMF) Data base includes: evaluated data generated by expert groups
and unevaluated data from the literature or from laboratory tests.
(HTS) Total number of stations or sources covered in data base: Current
ly 6 data sources in test data set.
(HCS) MO. stations or sources currently originating/contributing data:
(•OF)" Number of facilities covered in data base (source monitoring): 0.
(6EO) Geographic coverage of data base: International
(LOC) Data elements identifying location of station or source include:
H/A
(FAC) Data elements identifying facility include: H/A
(COE) Pollutant identification data are: CAS registry number
(HM) Limitation/variation in data of which user should be aware: Conce
ntrations/levels of a chemical in a particular media are not
included in this data base. Toxicity, physical-chemical, and
environmental fate data are included. Future access through
the HIH/EPA Chemical Information System; test data base limited
to OTS use.
(DPRO Data collect./anal, procedures conform to ORD guidelines: Conform
s to ORD Quality Assurance Standards
(AIL) Lab analysis based on EPA-approved or accepted methods? MO
912
-------
Accession Ho. 7301700901 (cont)
(PRE) Precision: Quality Indicators included for some components of
the data bank* Considerable test condition data also presented
in the records.
(EOT) Editting: SPHERE CoMlttee (OTS interdlvisional Committee)
conforms to the ORD Quality Assurance Standards for editing.
Data are edited to assure that they are true to the original
source. Source data are not validated.
(CBY) Data collected by: Federal Agencies ;industry ,? published
literature
(ABY) Data analyzed by: Data in system are not generally analyzed;
user does his oun analysis using CIS analytical components such as
their mathematical modelling laboratory.
(IDL) Laboratory identification: M/A
(AOT) Authorization for data collection: Statutory authorization is P
L 94-469, Section 10 (Toxic Substances Control Act 15 2609)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Similar to
other NIH/EPA CIS outputs, e.g. printouts on reguest and On-line
computer access
(NUS) number of regular users of data base: Test data base has 20
users; 500 users expected by January 1984.
(DSR) Current regular users of data base: Office of Toxic Substances
EPA regional offices
By August 1983, Industry, Government, Academia
(CNF) Confidentiality of data and limits on access: No confidentiality
limits, public access after test mode - August 1983.
(DLC) Primary physical location of data: NIH/EPA Chemical Information
System DEC 2060 Computer in Washington, D.C.
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: Through NIH/EPA Chemical Information System
(CHG) Direct charge for non-EPA use: will conform to CIS rate
structure. Expected $65.00/connect hr.
(UPDT) Frequency of data base master file up-date: Quarterly.
(CMP) Completion of form:
Paula Miles
OFC: EPA/(OPTS)/(OTS )/(MSD)
AD: 401 M St. SV, Washington, DC
PH: (202) 382-3775
(OF) Date of form completion: 12-10-82
(NMAT) Number of substances represented in data base: 2,000 substances
(NCAS) Number of CAS registry numbers in data base: 1,900 CAS RN
(CKM) Contact name(s): Auer,C. ; Jover,T. ; Miles,P.
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Off Ice of Toxic Integration.
913
-------
Accession No. 7301700902
(DQ) Date of Questionaire: 12-02-82
(STATUS) Status of entry: Inactive
(MAN) Name of Data Base of Model: CHEMTRAX
(ACR) Acronym of Data Base or Model: CHEMTRAX
(MED) Media/Subject of Data Base or Model: Other status of chemical
assessment
(ABS) Abstract/Overview of Data Base or Model: Tracking of action and
decision status of chemical substances within the Office of
Toxic Substances, other EPA programs, and federal agencies
pertinent to the Office of Toxic Substances* planning. In addition
to the chemicals individually identified, CHEMTRAX covers the
following lists:
-CAG chemicals 144
-IRLG regulatory development 29
-MCI bioassay 552
-FIFRA 23
-AD pre-chips screening 419
-304 Hater Pollution Control Federation
-382 Active Ingredients in registered pesticides
-89 Fishbine List
-661 NTP testing chemicals
-947 OSHA carcinogens
-65 hazardous wastes
-42 CUT
-661 preliminary list
-50 highest production volume chemicals
-65 OTS mutegenicity tested chemicals
(CTC) CONTACTS: Subject matter Jim Bradshaw (202)755-2110;
Computer-related Frances Cor
(DTP) Type of data collection or monitoring: Combination/Other
administrative actions
(STA) Data Base status: Discontinued
(6RP) Groups of substances represented In Data Base: 129 307 CWA ;21
drinking water standards ;9 potential drinking water ; 29 drinking
water monitoring ;299 hazardous substances ;48 cancelled pesticides
; 54 TSCA assessment
(IPP) Bon-pollutant parameters included in the data base: action
decision status
(DS) Time period covered by data base: 02-01-78 TO 09-30-80
(TRM) Termination of data collection: Rot anticipated
(FRQ) Frequency of data collection or sampling: Other ad hoc
(•08) Rumber of observations in data base: 7500(Estimated)
(•El) Estimated annual Increase of observations in data base: 1500
(IMF) Data base includes: chemical decision status and Office of Toxic
Substances actions
(MTS) Total number of stations or sources covered in data base: 0
(ICS) io. stations or sources currently originating/contributing data:
0
(•OF) Number of facilities covered in data base (source monitoring): 0
(LOC) Data elements identifying location of station or source include:
(FAC) Data elements identifying facility include: N/A
914
-------
Accession No. 7301700902 (cont)
(CDE) Pollutant Identification data are: Other coding scheme
(LIM) Limitation/variation in data of which user should be aware: Coded
with CHEMTRAX identification numbers; actual data from contributors
predates initiation of CHEMTRAX; System is not interactive-
presently being rewritten.
(ANL) Lab analysis based on EPA-approved or accepted methods? MO
(AUD) Lab Audit: Data not based on lab analysis.
(PRE) Precision: precision and accuracy estimates are not available
(EOT) Fditting: No known edit procedures exist.
(CBY) Data collected by: Self reporting Office of Toxic Substances/
BPA Bother federal agency National In Safety and Health,
Occupational Safety and Health Administration, Food and Drug
Administration/ Interagency Testing Committee ;EPA headguarters
Office of Toxic Substances/ EP
(ABY) Data analyzed by: EPA headguarters Office of Toxic Substances/
EPA
UDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: program coordination
U0T) Authorization for data collection: Statutory authorization is P
L 94-469, Sections 9 & 10-support of assessment process (Toxic
Substances Control Act of 1976-TSCA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
reguest
(•OS) lumber of regular users of data base: 1 office
(OSR) Current regular users of data base: EPA headguarter offices
Office of Toxic Substances Search Center/ Management Support
Division . _. ..
(CiF) Confidentiality of data and limits on access: No limits on
access to data ^ , .
(OLC) Primary physical location of data: Other Federal Agency:
National Institutes of Health-will move to EPA
(DST) Form of data storage: Magnetic disc „«*.«*,»,».» «.„.
(DAC) Type of data access: EPA software CHEMTRAX MIDS:7500000902 ;EPA
hardware IBM 370
(CHG) Direct charge for n on-EPA use: no
(CMP) Completion of form:
Fran Corbin
OFC: EPA/(OPTS)/(OTS)/(MSO)
AD: 401 N St. S.W. Washington/ D.C. 20460
PH: (202)426-2447
(DF) Date of form completion: 12-10-82
(IMAT) Number of substances represented in data base. 10^2
(ICAS) Number of CAS registry numbers in data base: 1068
(NAT) Substances represented in data base:
l/l/l/2-tetracHloroethane<63 i,l,2-trichloro-l/2/2-trifluoroeth
0-20-6> ane<76-13—1>
1,I/l-trichloroethane<71-55-6> l,l,2-trichloroethane<79-00-5>
l'l/2/2/-tetrachloroethane i,l,2-trichloroethene<79-01-6>
' l,l-dichloroethane<75-34-3>
i,i-dichloroethylene<75-35-4>
915
-------
Accession Ho. 7301700902
(cont)
l,l-dichloropropane<78-99-9>
1,12-benzoperylene<191-24-2>
1* 2,3,4-tetrachlorobenzene
<634-66-2>
1,2,3,5-tetrachlorobenzene
<634-90-2>
l,2,3-trichlorobenzene<96-18-4>
l,2,4,-trichlorobenzene<120-82-l>
l,2-dibro»o-3-chloropropane (dbcp)
<96-12-8>
1,2-dibro»oethane<106-93-4>
1,2-dichlorobenzene<95-50-l>
l,2-dichloroethane<107-06-2>
1,2-dichloropropane<78-B7-5>
l,2-diphenylhydrazine<122-66-7>
1,2-trans-dichloroethylene
<156-60-5>
1,3,4 trichlorobenzene<120-82-l>
l,3,5-trichlorobenzene<108-70-3>
1,3-butylene glycol<107-88-0>
1,3-dichlorobenz«ne<541-73-l>
1,3-dichloroprop«n«<542-75-6>
1,3-dioxolane< 646-06-0>
1,4-dlchlorobenzen«<10 6-46-7>
1,5-cyclooctadiene
l-pent«ne<109-67-l>
11,12-benzofluoranthene<207-08-9>
2,2-dichloropropionlc acid
<75-99-0>
2^3,7,8-tetrachlorodibenzo-p-
dioxin
2,3-dinltrotoluene<602-01-7>
2,3-o-phenylenepyrene<193-39-5>
2, 4,5-t a*ines
2,4,5-t esters
2,4,5-t salts
2,4,5-tp acid esters
2, 4,5-trlchlorophenoK 95-95-4>
2,4,5-trlchlorophenoxyacetlc acid
Cf><93-76-5>
2,4,5-trichlorophenoxyprop ionic
acid (TP)<93-72-l>
2,4,6-trichlorophenol<88-06-2>
2,4-d acid<94-75-7>
2/4-d esters
2,4-dichlorophenol<120-83-2>
2,4-dichlorophenoxyacetic acid (2,
4-d)<94-75-7>
2,4-dl«ethylphenol<105-67*9>
2,4-dinltrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2,4-toluene diisocyanat«<584-84-»9>
2,5-dinitrotoluene<619-15-8>
2,6-dlnitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-diaethyl aainoethanol<108-01-0>
2-ethyl hexanol<104-76-7>
2-fluoroacetaaide {1081)<640-19-7>
2-hydroxy-benzoic acid<69-72-7>
2-hydroxy-prppanolc acid<50-21-5>
2-nitrophenol*<88-75-5>
2-nitroptopane<79-46-9>
3,3'-dichlorobenzidine<91-94-l>
3,4,5-trichlorogualacol
3,4-benzofluoranthene<205-99-2>
3,4-dinitrotoluene<610-39-9>
4,4'-dde
4,4'-ddt<50-29-3>
4,6-dinitro-o-cresol<534-52-l>
4-broaophenyl phenyl ether
<101-55-3>
4-chloro-3-«ethyl phenol<59-50-7>
4-chlorophenyl phenyl ether
<7005-72-3>
4-»ethyl-benzenesulfona«ide
<70-55-3>
4-nitrophenol<100-02-7>
5-ethyl-5-isopentyl-barbiturlc
acid<57-43-2>
5-ethyl-5-phenyl-barbituric acid
<50-06-6>
abietlc
abs<9003-56-9>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acetaldehyde<75-07-0>
acetaldol<107-89-l>
aceta«lde<60-35-5>
acetanilide<103-84-4>
acetic acid salts
acetic acld<64-19-7>
acetic anhydride<108-24-7>
acetone cyanohydrln<75-86-5>
acetone<67*64-l>
acetonitrile<75-05-8>
acetophenone<98-86-2>
acetyl bro«ide<506-96-7>
acetyl chloride<75-36-5>
acetylene<74-86-2>
acrolein<107-02-8>
acryla»id«<79-06-l>
acrylic acid<79-10-7>
916
-------
Accession No. 7301700902
(cont)
acrylic fiber
acrylic resins
acrylonitrile<107-13-l>
adipic acid<124-04-9>
adiponitrile
aerosols
alachlor<15972-60-8>
aldrin<309-00-2>
allyl alcohol<107-18-6>
allyl chloride<107-05-l>
alpha- terpineol
aluvinuB sulfate<10043-01-3>
ajiitraz (baam)<33089-61-l>
aBBcni a<76 64- 4 1-7>
aBBoniun acetate<631-61-8>
aBBoniuB benzoate<1863-63-4>
aBBoniuB bicarbonate<1066-33-7>
aBBoniuB bichroaate<7789-09-5>
aBBoniuB bif luoride<1341-49-7>
aBBoniun bisulf ite<10192-30-0>
aBBonlua carba»ate
aBBoniua carbonate<506-87-6>
aBBoniuB chlorid«<12125-02-9>
aamcniua chro«ate<7788-98-9>
aBBoniUB fluoborate<13826-83-0>
aBBoniuB f luoride<12125-01-8>
aaaoniuB hydroxide<1336-21-6>
aBnoniUB oxalate<1113-38-8>
aBBoniuB silicof luoride
<16919-19-0>
aBBoniuB sulf anate<7773-06-0>
aBBoniua sulfide<12135-76-l>
aMoniuB sulf ite<10196-04-0>
aBBoniuB tar trate<3164-29-2>
aBBoniua thiocyanate
aaaoniuB thiosulfate<7783-18-8>
aayl acetate<628-63-7>
aByla«ine<110-58-7>
aniline hydrochloride< 142-0 4-l>
aniline<62-53-3>
anisole<100-66-3>
anthracene
anthranilic acid<118-92-3>
anthraquinone<84-65-l>
antiaony pentachloride<7647-18-9>
antiaony potassiua tartrate
arsenic acid<1327-52-2>
arsenic disulf ide<1303-32-8>
arsenic pentoxide<1303-28-2>
arsenic trichloride<7784-34-l>
arsenic trioxide<1327-53-3>
arsenic trisulfide<1303-33-9>
arsenic <7440-38-2>
asbestos<1332-21-4>
aspirin<50-78-2>
a tr azlne< 1 912-24- 9>
banvel-d<1918-00-9>
barluB cyanide<542-62-l>
bariUB<7440-39-3>
benefin<1861-40-l>
benoByl<17804-35-2>
benzaldehyde<100-52-7>
benzaBide<55-21-0>
benzene acetic acid<103-82-2>
benz«ne<71-43-2>
benzenepropanoic acid<501-52-0>
benzenesulfonic acid<98-ll-3>
benzidine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g^h^i)perylene<191-24-2>
benzo (k) f luor anthene<207-08-9>
benzole acid<65-85-0>
benzoin
benzoni tr ile<100-47-0>
benzophenone
benzoyl chlorlde<98-88-4>
benzoyl peroxide<94-36-0>
benzyl alcohol<100-51-6>
benzyl chloride<100-44-7>
benzyl dichloride<98-87-3>
beryl HUB chloride<7787-47-5>
berylliuB f luoride<7787-49-7>
beryl HUB nitrate<13597-99-4>
berylliuB<7440-41-7>
bhc (lindane)-gaama<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)Bethane
antiaony tribro«ide<7789-61-9>
antiaony trichloride<10025-91-9>
antiaony trifluoride<7783-56-4>
antimony trioxide<1309-64-4>
an ti»ony< 7 440-36-0 >
bls(2-chloroethyl)ether
bls(2-chloroisopropyl)ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloronethyl)ether<542-88-l>
bisphenol a<80-05-7>
917
-------
Accession No. 7301700902
(cont)
boric acid and salts
bro»obenzene<108-86-l>
bro»odlchloro«ethane<75-27-4>
bro»ofor»<75-25-2>
bro«o»ethane<74-83-9>
bu tadi ene<10 6-99-0>
butralin<33629-47-9>
butyl acetate<123-86-4>
butyl benzyl phthaiate<85-68-7>
butyl phthalyl butyl glycolate
<85-70-l>
butyla»ine<109-73-9>
butyloctyl phthalate<84-78-6>
butyric acid<107-92-6>
cad*lu« acetate<543-90-8>
cad»lu» bro«ide<7789-42-6>
cadaiua chloride
cad*iu«<7440-43-9>
caffeine<58-08-2>
calclua arsenate<7778-44-l>
calciuM arscnite<52740-16-6>
calcium carbide<75-20-7>
calclua chro«ate<13765-19-0>
calclua cyanide<592-01-8>
calciua dodecylbenzenesulfonate
<26264-06-2>
calciun hydroxlde<1305-62-0>
calclua hypochlorlte<7778-54-3>
calciua oxide<1305-78-8>
calciUM stearate<1592-23-0>
caprolacta«<105-60-2>
captan<133-06-2>
carbaryl<63-25-2>
carbofuran<1563-66-2>
carbon dioxide<124-38-9>
carbon disulfide<75~15-0>
carbon tetrabro«ide<558-13-4>
carbon tetrachloride<56-23-5>
carbon tetrafluorid«<75-73-0>
carbon<7440-44-0>
castor oll<8001-79-4>
cellophane<9005-81-6>
cellulose acetate<9004-35-7>
cellulose nltrate<9004-70-0>
cblor dane<57-7 4-9>
chloride
chlorinated ethanes
chlorinated hydrocarbons
chlorinated naphthalenes
chlorine<778 2-50-5>
chloroacetlc acid<79-ll-8>
chloroacetophenone<1341-24-8>
chlorobenzene<108-90-7>
chlorobenzilate<5lO-15-6>
chlorodibro«o«ethane<124-48-l>
chlorodilluoroBethane<75-45-6>
chloroethane<75-00-3>
chlorofluoroc arbons
chlorofor»<67-66-3>
chloro»ethane<74-87-3>
chlorophenols
chloroprene<126-99-8>
chlorosulfonlc acid<7790-94-5>
chlorpyrifos<2921-88-2>
cholesterol<57-88-5>
chollne chlorid«<67-48-l>
chroBic acetate<1066-30-4>
chroalc «cid<7738-94-5>
chroalc sulfate<10101-53-8>
chro»lu» (hexaval«nt)<7440-47-3>
chro»iu»<7440-47-3>
chroaous chloride<10049-05-5>
chrysene<218-01-9>
cis-l,2-dichloroethylene<156-59-2>
cis-9xcls-12-octadecadienoic acid
<60-33-3>
coal tar<8007-45-2>
cobaltous bro»ide<7789-43-7>
cobaltous £or«ate<544-18-3>
cobaltous sulfa»ate<14017-4l-5>
coke oven e»lsslons<65996-81-8>
copper<7440-50-8>
cou»aphos<56-72-4>
creosote<802l-39-4>
cresol<1319-77-3>
crotonaldehyd«<4170-30-3>
crotonic acid<3724-65-0>
cuaene hydroperoxide<80-15-9>
cuprlc acetate<142-71-2>
cuprlc acetoarsenite<12002-03-8>
cuprlc chloride<7447-39-4>
cuprlc nltrate<3251-23-8>
cupric oxalate<814-91-5>
cupric sulfate a»»oniated
<10380-29-7>
cuprlc sulfate<7758-98-7>
cupric tartrate<815-82-7>
cyanazine<2!725-46-2>
cyanide<57-12-5>
cyanides
cyanoacetic acid<372-09-8>
cyanogen chloride<506-77-4>
cyanuric acid<108-80-5>
cyanurlc chloride<108-77-0>
918
-------
Accession No. 7301700902
(cont)
cyclohexane<110-82-7>
cyclohexanol<108-93-0>
cyclohexene<110-83-8>
cyclohexylaBine<108-91-8>
ddt
decanol<112-30-l>
dehydrobietic<1740-19-8>
di-isobutyl phthaiate<84-69-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
di-tridecyl phthalate<121-69-7>
diacetone alcohol<123-42-2>
diallate<2303-16-4>
diazinon<333-4l-5>
dibenzo(a,h)anthracene<53-70-3>
dibutyl phthalate<84-74-2>
dicanba<1918-00-9>
dichlobenil<1194-65-6>
dichlone<117-80-6>
dichlorobenzene<25321-22-6>
dichlorobro«oraethane<75-27-4>
dichlorodifluoromethane<75-71-8>
dichloroethyl ether
dichlorohydrin<26545-73-3>
dichloromethane<75-09-2>
dichloropropene-dichloropropane
mixture
dichloropropene<26952-23-8>
dichlorotetrafluoroethane
<1320-37-2>
dichlorvos (ddvp)<62-73-7>
dicyclohexyla«ine<101-83-7>
dicyclopentadine<77-73-6>
didecyl phthalate<84-77-5>
dieldrin<60-57-l>
diepoxybutane
diethy1 phthalate<84-66-2>
diethyl sulfate<64-67-5>
diethylaaine<109-89-7>
diethylene glycol monobutyl ether
acetate
diethylene glycol nonobutyl ether
<112-34-5>
diethylene glycol nonoethyl ether
acetate
diethylene glycol mononethyl
ether
diethylene glycol
diethylstilbestrol<56-53-l>
diisobutylene<25167-70-8>
dilsocotyl phthalate<27554-26-3>
diisodecyl phthalate<26761-40-0>
diisopropyl anine<108-18-9>
diketene<674-82-8>
di»ethoate<60-51-5>
diaethyl phthalate<131-ll-3>
dimethyl sulfide<75-18-3>
dimethyl sulfoxide<67-68-5>
diaethyl terephthalate<120-61-6>
dinethylanine<124-40-3>
dimethylcarbanoyl chloride
<79-44-7>
dinitrobenzene<25154-54-5>
dinitrotoluene<25321-14-6>
dioxin<828-00-2>
diphenylanine<122-39-4>
diphenylthiourea<102-08-9>
dlpropylene glycol<25265-71-8>
diquat<2764-72-9>
disulfoton<298-04-4>
diuron<330-54-l>
dodecyl »ercaptan<112-55-0>
dodecylbenzenesulfonic acid
<27176-87-0>
dodecylphenol<27193-86-8>
dosiun phenate<139-02-6>
ebdc's (ethylenebisdithiocarbaaate
s)
edta<60-00-4>
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endosulfan<115-29-7>
endrin aldehyde<7421-93-4>
endrin ketone<53494-70-5>
endrin<72-20-8>
epichiorohydrin<106-89-8>
epn (ethyl-p-nitrophenyl thionoben
zenephosonate)<2104-64-5>
epoxy resins<61788-97-4>
ethanol<64-17- ethanolaalnes
ethelene glycol monoethyl ether
acetate
ethion<563-12-2>
ethyl acetoacetate<141-97-9>
ethyl bronide<74-96-4>
ethyl chloride<75-00-3>
ethyl chloroacetate<105-39-5>
ethyl «ercaptan<75-08-l>
ethyla»ine<75-04-7>
ethylbenzene<100-41-4>
ethylene chlorohydrin<107-07-3>
ethylene dibroslde (edb)<106-93-4>
ethylene dichlorlde<107-06-2>
919
-------
Accession Ho. 7301700902
(cont)
ethylene glycol diacetate
ethylene glycol dimethyl ether
ethylene glycol aonobutyl ether
acetate<112-07-2>
ethylene glycol lonobutyl ether
ethylene glycol aonoethyl ether
<110-80-5>
ethylene glycol aonoaethyl ether
ace tate
ethylene glycol Monoaethyl ether
<109-86-4>
ethylene glycol<107-21-l>
•thyltne oxide<75-21-8>
ethylene<74-85-l>
«thylenedia*lnt<107-15-3>
ethylnexanoic «cid<149-57-5>
f ensul f othion<115-90-2>
ferric aMonliui citrate<1185-57-5>
ferric araoniua oxalate
<14221-47-7>
ferric chloride<7705-08-0>
ferric fluoride< 77 83-50- 8>
ferric nitrate<10421-48-4>
ferric sulfate<10028-22-5>
ferrous aaaoniua sulfate
<10045-89-3>
ferrous chloride<7758-94-3>
ferrous sulfatc<7720-78-7>
fluoranthene<206-44-0>
fluorene<86-73-7>
fluoride<16984-48-8>
for»aldehyde<50-00-0>
f or«a»lde< 75-1 2-7>
foralc acld<64-18-6>
fu«aric acid<110-17-8>
furfural<98-01-l>
geraniol<106-24-l>
glutavic acid, aonosodiuB salt
<142-47-2>
glycerol (natural & synthetic)
<56-81-5>
glycerol dichlorohydrin
<26545-73-3>
glycerol tri(polyoxypropylene)
ether<25791-96-2>
glycidol<556-S2-5>
glycine<56-40-6>
glyoxal<107-22-2>
guthion<86-50-0>
hcliu»<7440-59-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
heptene<25339-56-4>
hexachlorobenzene<118-74-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
hexacloroethane<67-72-l>
hexadcecanoic acid<57-10-3>
hexadecyl alcohoi<36653-82-4>
hexaaethylene tetra»ine<100-97-0>
hexaaethy1enedianine<124-09-4>
hydrochloric acid<7647-01-0>
hydrofluoric acid<7664-39-3>
hydrogen cyanide<74-90-8>
hydrogen sulfide<7783-06-4>
hydrog«n<1333-74-0>
hydroxyethyl c«llulose<9004-62-0>
indeno (l,2,3-cd)pyrene<193-39-5>
lodlne<7553-56-2>
lsoa«yl«ne<26760-64-5>
isobutyl acetate<110-19-0>
isobutyraldehyde
isobutyrlc acid<79-31-2>
isoctyl alcohol<26952-21-6>
isodrln<465-73-6>
isop entane<7 8-7 8-4>
isophorone<78-59-l>
isophthalic acid<121-91-5>
isopiaaric acld<5835-26-7>
isoprene<78-79-5>
isopropanol<67-63-0>
isopropyl ac«tate<108-21-4>
Isopropyl alcohol<67-63-0>
Isopropyl chlorid«<75-29-6>
isopropyl ether<108-20-3>
isopropyl phenol<25168-06-3>
lsopropyla»ine<75-31-0>
kelthane<115~32-2>
kepone<143-50-0>
ketene<463-51-4>
lead acetate<301-04-2>
lead chloride<7758-95-4>
lead fluoride<7783-46-2>
lead fluoroborate<13814-96-5>
lead iodide<10101-63-0>
lead nitrate<10099-74-8>
lead stearate<1072-35-l>
lead sulfate<7446-14-2>
lead sulfide<1314-87-0>
lead thlocyanate<592-87-0>
920
-------
Accession So. 7301700902
(cent)
lead<7439-92-l>
lindane< 58-89- 9>
linear alkylate sulfonate
linoleic acid<60-33-3>
lithium chromate<14307-35-8>
m-chloroaniline<108-42-9>
ra-cresol
•-dichlorobenzene<541-73-l>
»-xylene<108-38-3>
malathion<121-75-5>
maleic acid<110-16-7>
•aleic anhydride<108-31-6>
maleic hydrazide
melamine<108-78-l>
•ercaptodimethur<2032-65-7>
mercuric cyanide<592-04-l>
mercuric nitrate<10045-94-0>
mercuric sulfate<7783-35-9>
mercuric thiocyanate<592-85-8>
mercurous nitrate<10415-75-5>
mercury<7439-97-6>
•esityl oxide<141-79-7>
•etanilic acid<121-47-l>
methacrylic acid 79 41-4
•ethallyl chloride<563-47-3>
methane<74-82-8>
methidathion<950-37-8>
methoxychlor<72-43-5>
methyl acetate<79-20-9>
methyl acetoacetate<105-45-3>
•ethyl butyl ketone<591-78-6>
methyl chloride<74-87-3>
methyl formate<107-31-3>
methyl iodide<74-88-4>
methyl isobutyl carbinol<108-ll-2>
methyl mercaptan<74-93-l>
methyl methacrylate<80-62-6>
methyl parathion<298-00-0>
methyl salicylate<119-36-8>
methyl sulfoxide<67-68-5>
methylamine<74-89-5>
methylcyclohexane<108-87-2>
methylene bis-thiocyanate
<6317-18-6>
methylene chioride<75-09-2>
methylene dianiline<101-77-9>
me thylpentynol<77-75-8>
•evinphos<7786-34-7>
mexacarbate<315-18-4>
monochlorodehydroabietic acid
<57055-38-6>
monoethylamine<75-04-7>
monomethylamine<74-89-5>
raorpholine<110-91-8>
nrn-diBethyl-£oroafflide<68-12-2>
n,n-dimethylaniline<121-69-7>
n,n-dimethylformamide<68-12-2>
n,n-diphenylhydrazine<530-50-7>
n-butene<25167-67-3>
n-butyl acetate<123-86-4>
n-butyl phthalate<84-74-2>
n-butylacrylate<141-32-2>
n-butylamineC109-73-9>
n-butyraldehyde<123-72-8>
n-butyric anhydride<106-31-0>
n-butyronitrile<98-73-7>
n-methylaniline<100-61-8>
n-nitrosodi-n-propylamine
<621-64-7>
n-nitrosodimethylamine<62-75-9>
n-nitrosodiphenyla«ine<86-30-6>
n-pentane<109-66-0>
n-propyl clcohal<71-23-8>
naled<300-76-5>
naphthalene<91-20-3>
naphthenic acid<1338-24-5>
neon<7440-01-9>
neopentaooic acid<75-98-9>
nickel ammonium sulfate<7785-20-8>
nickel chloride<7718-54-9>
nickel hydroxide<12054-48-7>
nickel nitrate<13138-45-9>
nickel sulfate<7786-81-4>
nickel<7440-02-0>
nitralin<4726-14-1>
nitrate<14797-55-8>
nitric acid<7697-37-2>
nitrobenzene<98-95-3>
ni troethane<7 9-24-3>
nitrogen dioxide<10102-44-0>
nitrogen oxide<11104-93-l>
nitroaethane<75-52-5>
nitrophenol<25154-55-6>
nitrotoluene
nomylphenol<25154-52-3>
nylon 6<25038-54-4>
o-chloroaniline<95-51-2>
o-chloronitrobenzene<88-73-3>
o-chlorotoluene<95-49-8>
o-cresol<95-48-7>
o-dichlorobenzene<95-50-l>
o-me thoxyphenoK 90-05-1>
o-nitroaniline<88-74-4>
o-xylene<95-47-6>
921
-------
Accession Mo. 7301700902
Ccont)
octadecanoic acid<57-ll-4>
octaaethylpyrophosphoraaide (OHPA)
<152-16-9>
octyl decyl phthalate<119-07-3>
octylphenol<27193-28-8>
oxy gen<778 2- 44-7>
P-a*Inophenol
p-chloro-«-cresol<59-50-7>
p-chloroto luene< 106- 43-4>
p-cresol<106-44-5>
p-hydroxybenzoic acid<99-96-7>
p-tert-butyl benzole acld<98-73-7>
P-xylene<106-42-3>
paraforaaldehyde<30525-89-4>
parathioiK 56-38- 2>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachloronltrobenzene (PCNB)
<82-68-8>
pentachl or ophenoK 87-86- 5>
pepchloronethyl >e reap tan
<594-42-3>
petroleua hydrocarbons
phenanthrene<85-01-8>
phenol<108-95-2>
phenols
phosgene<7 5- 44-5>
phosphoric acid<7664-38-2>
phosphorus oxychloride<10025-87-3>
phosphorus pentasulf ide<1314-80-3>
phosphorus trichloride<7719-12-2>
phosphorus<7723-14-0>
ph thai ate esters
phthalic acid esters
phthalic acid<88-99-3>
phthall»ide< 85-4i-6>
plperazine<110-85-0>
platinu«<7440-06-4>
polyanid«s<63428-83-l>
polybroainated biphenyls (PBBs)
polychlorlnated biphenyls (PCBs)
polyethyene terephthalate
<25038-59-9>
polyethylene glycol<25322-68-3>
polypropylene glycol<25322-69-4>
polyvinyl alcohol<9002-89-5>
polyvinyl chloride<9002-86-2>
polyvinyl pyrrolidone<9003-39-8>
potassiua arsenate<7784-41-0>
potassiua arsenite<10124-50-2>
potassiu* azide<20762-60-l>
potassiua bichro»ate<7778-50-9>
potassiua chro«ate<7789-00-6>
potassium cyanide<151-50-8>
potassiua hydroxide<1310-58-3>
potassiui per»anganate<7722-64-7>
prona»ide<23950-58-5>
propachlor<1918-16-7>
propane<74-98-6>
propanil<709-98-8>
propargite<2312-35-8>
propionaldehyde<123-38-6>
propionic acid<79-09-4>
propionic anhydride<123-62-6>
propyl acetate<109-60-4>
propyl chloride<540-54-5>
propylene dichloride<78-87-5>
propylene glycol<57-55-6>
propylene oxide<75-56-9>
propylene<115-07-l>
pyrene<129-00-0>
pyrethrin<121-29-9>
quinollne< 91-22-5>
resorcinol<108-46-3>
salicylic acid<69-72-7>
sec-butyl alcohol<78-92-2>
sec-butyla»ine<13952-84-6>
seleniua oxide<12640-89-0>
seleniu«<7782-49-2>
silica<7631-86-9>
silicones
silver nitrate<7761~88-8>
silver<7440-22-4>
silvex<93-72-l>
siaazine<122-34-9>
sodium acetate<127-09-3>
sodiuB arsenate<7631-89-2>
sodium acsenite<7784-46-5>
sodiuB benzoate<532-32-l>
sodiua bichro«ate<10588-01-9>
sodiua bifluoride
sodiu» bisulfite<7631-90-5>
922
-------
Accession No. 7301700902
(cont)
sodium carboxymethyl cellulose
<9004-32-4>
sodiun chloroacetate<3926-62-3>
sodium chromate<7775-ll-3>
sodiun cyanide<143-33-9>
sodiun dodecylbenzenesulfonate
<25155-30-0>
sodiun fluoride<7681-49-4>
sodiun fluoroacetate (1080)
<62-74-8>
sodiun fornate<14l-53-7>
sodiun hydrosulfide<16721-80-5>
sodiun hydroxide<1310-73-2>
sodiun hypochlorite<7681-52-9>
sodiun Bethylate<124-41-4>
sodiun nitrite<7632-00-0>
sodiun phosphate, dibasic
<7558-79-4>
sodiun phosphate, tribasic
<7601-54-9>
sodiun selenite<10102-l8-8>
sodiun<7440-23-5>
sorbic acid<110-44-l>
strontium chro«ate<7789-06-2>
strychine<57-24-9>
strychnine<57-24-9>
styrene<100-42-5>
succinic acid<110-15-6>
sucrose<57-50-l>
sulfanilic acid<121-57-3>
sulfate aerosols
sulfate<14808-79-8>
sulfolane<126-33-0>
sulfur aonochloride
sulfur<7704-34-9>
suIfuric acid<7664-93-9>
surfactants
tannic acld<1401-55-4>
tde<72-54-8>
terephtalic acid<100-21-0>
terpenes
tert-butyl alcohol<75-65-0>
tert-butylanine<75-64-9>
tetrachloroethylene<127-18-4>
tetrachlorophthalic anhydride
<117-08-8>
tetraethyl lead<78-00-2>
tetraethyl pyrophosphate<107-49-3>
tetra«ethyethlenedia»ine
tetranethyl lead<75-74-l>
thalliun sulfate<7446-18-6>
thalliun<7440-28-0>
thiophanate raethyl<23564-05-8>
thiophene<110-02-l>
titaniun dioxide<13463-67-7>
toluene-2, 4-diaraine<95-80-7>
toluene<108-88-3>
toluenesulfonaaide<1333-07-9>
toluenesulfonyl chloride<98-59-9>
toluidines
total suspended particulates
toxaphene<8001-35-2>
tribroraonethane<75-25-2>
tributyl phosphorotrithioate
<78-48-8>
trichlorfon<52-68-6>
trichloroethane<25323-89-l>
trichloroethylene<79-01-6>
trichlorof luoronethane<75-69-4>
trichlorophenol (TCP)<25167-82-2>
triethanolanine dodecylbenzenesulf
onate<27323-41-7>
triethyla«ine<121-44-8>
triethylene glycol<112-27-6>
triethylene tetranine<112-24-3>
trifluraline (tref lan)<1582-09-8>
trine thylanine<75-50-3>
tungsten<7440-33-7>
uraniu«<7440-61-l>
uranyl acetate<541-09-3>
uranyl nitrate<10102-06-4>
urea<57-13-6>
vanadlun pentoxide<1314-62-l>
vanadyl sulfate<27774-13-6>
vinyl acetate<108-05-4>
vinyl chloride<75-01-4>
vinyl toluene< 2501 3-1 5-4>
vinylidene chloride<75-35-4>
x-17 aminoethylethanolanine
xylene sulfonic acid<25321-41-9>
xylene<1330-20-7>
xylenol<1300-71-6>
xylidine<1300-73-8>
zinc acetate<557-34-6>
zinc annoniun chloride
zinc bora te
zinc broaide<7699-45-8>
zinc carbonate<3486-35-9>
zinc chloride<7646-85-7>
zinc cyanide
zinc fluoride<7783-49-5>
zinc fornate<557-41-5>
zinc hydrosulfite<7779-86-4>
923
-------
Accession Ho. 7301700902
(cont)
zinc nitrate<7779-88-6>
zinc phenol sulfonate<127-82-2>
zinc phosphide<1314-84-7>
zinc silicofluoride<1687l-71-9>
zinc sulfate<7733-02-0>
zinc<7440-66-6>
zirconium nitrate
zirconium potassium fluoride
<16923-95-8>
zirconium sulfate<14644-61-2>
zirconium tetrachloride
<10026-ll-6>
0,0-diethyl phosphoric acid,0-p-
nitrophenyl ester<3ll-45-5>
0,0-diethyl-0-(2-pyrazlnyl)
phoshorothiol,1-dimethyIhydrazi
ne<57-14-7>
1*2,3,4,10,10-hexachloro-l,4,4a,5,
8,8a-hexahydro-l,4:5,8-endo,
endo-dimetha
1^2^4,5-tetrachlorobenzene
<95-94-3>
I,2-diethylhydrazine<1615-80-l>
l,2-dimethylhydrazlne<540-73-8>
If2-propancdiol<57-55-6>
1,3-pentadiene<504-60-9>
1,3-propane sultone<1120-7l-4>
l,4-dichloro-2-butene<110-57-6>
1,4-dloxane<123-91-l>
1^ 4-napbth oquinone
1-(o-chlorophenyl)thiourea
<5344-82-l>
l-chloro-2,3-epoxypropane
<106-89-8>
1-naph thy1-2-1 hi ourea<86-88-4>
l-naphthylamine<134-32-7>
2/3,4,6-tetrachlorophenol<58-90-2>
2,4-dithiobiuret<541-53-7>
2,6-dichlorophenol<87-65-0>
2-bvtanone peroxlde<1338-23-4>
2-cyclohexyl-4^ 6-d ini trophenol
<131-89-5>
2-methyl-2-(methylthio)propionalde
hyde-o-(methylcarbonyl)oxime
<80-62-6>
2-»ethylaziridine<75-55-8>
2-»ethyllactonitrile<75-86-5>
2-naphthylamine<91-59-8>
2-picoline<109-06-8>
2-propyn-l-01<107-19-7>
2-sec butyl-4,6-dinitrophenol
<88-85-7>
3^3 '-dime thoxybenzidine<119-90-4>
3,3'-diaethylbenzidine<119-93-7>
3,4-dihydroxy-alpha-(methylamino>-
methyl benzyl alcohol
3-chloropropionitrile<542-76-7>
3-methylcholanthrene<56-49-5>
4,4*-dde(p,p»-ddx)<72-55-9>
4^4'-ddt<50-29-3>
4,4*-methylene-bis-(2-chloroanilin
4-chloro-o-toluidine hydrochloride
<3165-93-3>
5-nitro-o-toluidine<99-55-8>
6-amino-l/la,2,8,8as8b-hexahydro-
8-(hydroxymethyl)8-methoxy-5-
•ethyl
-caraba
7,12-diaethylbenz(a)ant 7-
oxabicycol(2. 2. l)heptane-2,3-
dicarboxylic
acid<145-73-3>
aluminum phosphide<20859-73-8>
aluninum<7429-90-5>
amltrole<61-82-5>
ammonium picrate<131-74-8>
ara«ite<140-57-8>
auramine<2465-27-2>
azaser ine< 115-02-6>
benz(c)acridine<225-51-4>
benzal chloride<98-87-3>
benzenesulfonyl chloride<98-09-9>
benzenethiol<108-98-5>
benzidine<92-87-5>
benzotr ichlor ide< 98-0 7-7>
beryllium dust
biphenyl<92-52-4>
bismuth compounds<7440-69-9>
boron co«pounds<7440-42-8>
bromine<7726-95-6>
bromoacetone<598-31-2>
brucine<357-57-3>
cacodylic acid and salts<75-60-5>
carbon monoxide<630-08-0>
carbonyl fluoride<353-50-4>
chloral<75-87-6>
chlor ambuciK 305-03-3>
chloranil<118-75-2>
chl oroacct aldehyde<107-20-0>
chloroethene<75-01-4>
chloroethyl vinyl ether<110-75-8>
chloromethyl methyl ether
<107-30-2>
924
-------
Accession Ho. 7301700902
(cont)
cobalt<7440-48-4>
copper cyanide<544-92-3>
cresylic acid<1319-77-3>
cu«ene<98-82-8>
cyanogen bro«ide<506-68-3>
cyanogen<460-l9-5>
cyclohexanone<108-94-l>
cyclophosphamide<50-18-0>
dauno«ycin<20830-81-3>
de«eton<8065-48-3>
di-n-propylnitrosanine<621-64-7>
dibenzofuran<132-64-9>
dlbenzol(a,i)pyrene<189-55-9>
dlbronochloronethane
dibro»o«ethane<74-95-3>
dichlorophenylarsine<696-28-6>
diethylarsina
dihydrosafrole<94-58-6>
diaethyl sulfate<77-78-l>
dl«ethylnitrosaBine<62-75-9>
dioxane<123-91-l>
diphenyl ether<101-84-8>
aipropyla«lne<142-84-7>
«rbon<136-25-4>
ethyl acetate<141-78-6>
ethyl acrylate<140-88-5>
ethyl ether<60-29-7>
ethyl »ethacrylate<97-63-2>
ethyl »ethanesulfonate<62-50-0>
ethyl parathion<56-38-2>
ethylcyanlde<107-12-0>
ethylene blsdlthiocarbaaate
ethylene thiourea<%-45-7>
ethylenei«ine<151-56-4>
fluorides
fluorine<7782-41-4>
fluorotrichloro«ethane<75-69-4>
furaiKllO-00-9>
hex achlorocyclohexane<58-89-9>
hexachloroethane<67-72-l>
hexachlorophene<70-30-4>
hexachloropropene<1888-7l-7>
hexaethyl tetraphosphate<757-58-4>
hydrazine<302-01-2>
hydrocarbons
hydrocyanic acid<74-90-8>
hydroxydiaethyl arsine oxide
<75-60-5>
iron dextran<9004-66-4>
iron<7439-89-6>
isobutyl alcohol<78-83-l>
isocyanic acidy nethyl ester
<624-83-9>
isosafrole<120-58-l>
lasiocarpine<303-34-4>
lead phosphate<7446-27-7>
lead subacetate<1335-32-6>
lithium and coipounds<7439-93-2>
•alononitrile<109-77-3>
»anganese<7439-96-5>
•ate
•elphalan<148-82-3>
•ercury fulBinate<628-86-4>
•ethanethiol<74-93-l>
•ethanol<67-56-l>
•ethapyrilene<91-80-5>
»etho«yl<16752-77-5>
•ethyacrylonitrile<126-98-7>
•ethyl chlorocarbonate<79-22-l>
•ethyl chlorofor»<71-55-6>
•ethyl ethyl ketone (aek)<78-93-3>
•ethyl ethyl ketone peroxide
<1338-23-4>
•ethyl hydrazine<60-34-4>
•ethyl Isobutyl lcetone<10€-10-l>
•ethylthiouracil<56-04-2>
•lrex<2385-85-5>
•onuron<150-68-5>
n^n-bia(2-chloroethyl)-2-naphthyla
•ine<494-03-l>
n-alkanes clO-c30
n-butyl alcohol<71-36-3>
n-aethyl-n'-nitro-n-nitrosoguanidi
ne<70-25-7>
n-nitroso-n-ethylurea<759-73-9>
n-nitroso-n-methylurea<684-93-5>
n-nitroso-n-aethyiurethane
<615-53-2>
n-nitrosodi-n-butyla»ine<924-16-3>
n-nitrosodi-n-propylaiine
<621-64-7>
n-nitrosodlethanolanineC1116-54-7>
n-nitrosodiethylaBine<55-18-5>
n-nitroscBethylvinylaaine
n-nitrosopiperidine<100-75-4>
n-nitrosopyrrolidine<930-55-2>
n-phenylthiourea<103-85-5>
n-propyla»ine
nickel carbonyl<12612~55-4>
nickel cyanide<557-19-7>
nicotine and salts<54-ll-5>
nitrates/nitrites
nitric oxide
925
-------
Accession Mo. 7301700902
(cont)
nitrogen peroxide<10102-44-0>
nitrogen tetroxide<10544-72-6>
nitrogen<7727-37-9>
nitroglycerine<55-63-0>
nitroso»ethylurea<684-93-5>
nitrosonorpholine< 59-89-2>
nonaphthalene
o-toluidine hydrochloride
<636-21-5>
oleyl alcohol condensed uith 2
•oles ethylene oxide
osmium tetroxlde<208!6-12-0>
ozone<10028-15-6>
p-chloroaniline<106-47-8>
p-dichlorobenzene<106-46-7>
p-di»ethyla»inoazobenzene<60-ll-7>
p-nitroaniline<100-01-6>
paraldehyde<123-63-7>
paraquat<4685-14-7>
pentachlorobenzene<608-93-5>
pentachloroetbane<76-01-7>
perchloroethylene<127-l8-4>
per thane<7 2-56-0>
phenacetin<62-44-2>
phenarsazine chlorlde<578-94-9>
phenyl dichloroarsine<696-28-6>
phenylBercury acetate<62-38-4>
phosophorotbiolc acid*o,o-
dimethyl ester,o-ester yith n,
ij-d i»etbyIb enzene
phosphine<7803-51-2>
phosphorus sulfide<1314-80-3>
phthalic anhydride<85-44-9>
piperonyl butoxide<51-03-6>
potassiua silver cyanide<506-61-6>
propionitrile<107-12-0>
propoxur<114-26-l>
propylene oxide<75-56-9>
pyridine<110-86-l>
qulnones
reserpine<50-55-5>
ronnel<299-84-3>
rotenone<83-79-4>
s,s,s-tributyl phosphorotrithioate
<78-48-8>
safrole<94-59-7>
secondary amines
selenious acid<7783-00-8>
selenium sulfide<7446-34-6>
selenourea<630-10-4>
silver cyanide<506-64-9>
sodium azide<26628-22-8>
sodiu«<7440-23-5>
strobane<8001-50-l>
strontiui sulfide<1314-96-l>
sulfates
sulfonamlde
sulfur dioxide<7446-09-5>
tetrachloroethene<127-l8-4>
tetrachloromethane<56-23-5>
tetraethyl dithiopyrophosphate
<3689-24-5>
tetrahydofuran<109-99-9>
tetranitro«ethane<509-14-8>
thallic oxide<1314-32-5>
thallium acetate<563-68-8>
thallium carbonate<29809-42-5>
thallium chloride<7791-12-0>
thallium nitrate<10102-45-l>
thalliua selenite
thioaceta«ide<62-55-5>
thiose«icarbazide<79-19-6>
thiourea<62-56-6>
thiur am< 137-26-8>
titaniu»<7440-32-6>
toluene diisocyanate<26471-62-5>
toluenedia«ine<25376-45-8>
triallate<2303-17-5>
tributyl phosphorotrithioate
<78-48-8>
trichloroethene<79-01-6>
trichloro»ethanethiol<75-70-7>
tris(2/3-dibro«opropyl)phosphate
<126-72-7>
tritiu»<10028-17-8>
trypan blue<72-57-l>
trysben<50-31-7>
uracil »ustard<66-75-l>
urethane<51-79-6>
vanadiu«<7440-62-2>
s 630-20-
926
-------
Accession Ho. 7301700902 (cont)
75-99.0; 1746-01-6; 602-01-7; 193-39-5; 95-95-4; 93-76-5;
93-72-1; 88-06-2; 94-75-7; 120-83-2; 94-75-7; 105-67-9;
51-28-5; 121-14-2; 584-84-9; 619-15-8; 606-20-2; 110-75-8;
91-58-7; 95-57-8; 108-01-0; 104-76-7; 640-19-7; 69-72-7; 50-21-5;
88-75-5; 79-46-9; 91-94-1; 205-99-2; 610-39-9; 72-55-9;
50-29-3; 534-52-1; 101-55-3; 59-50-7; 7005-72-3; 70-55-3;
100-02-7; 57-43-2; 50-06-6; 9003-56-9; 83-32-9; 208-96-8; 75-07-0;
107-89-1; 60-35-5; 103-84-4; 64-19-7; 108-24-7; 75-86-5; 67-64-1;
75-05-8; 98-86-2; 506-96-7; 75-36-5; 74-86-2; 107-02-8; 79-06-1;
79-10-7; 107-13-1; 124-04-9; 111-69-3; 15972-60-8; 309-00-2;
107-18-6; 107-05-1; 10043-01-3; 33089-61-1; 7664-41-7; 631-61-8;
1863-63-4; 1066-33-7; 7789-09-5; 1341-49-7; 10192-30-0; 1111-78-0;
506-87-6; 12125-02-9; 7788-98-9; 13826-83-0; 12125-01-8; 1336-21-6;
1113-38-8; 16919-19-0; 7773-06-0; 12135-76-1; 10196-04-0;
3164-29-2; 1762-95-4; 7783-18-8; 628-63-7; 110-58-7;
142-04-1; 62-53-3; 100-66-3; 120-12-7; 118-92-3; 84-65-1;
7647-18-9; 11071-15-1; 7789-61-9; 10025-91-9; 7783-56-4;
1309-64-4; 7440-36-0; 1327-52-2; 1303-32-8; 1303-28-2;
7784-34-1; 1327-53-3; 1303-33-9; 7440-38-2; 1332-21-4; 50-78-2;
1912-24-9; 1918-00-9; 542-62-1; 7440-39-3; 1861-40-1; 17804-35-2;
100-52-7; 55-21-0; 103-82-2; 71-43-2; 501-52-0; 98-11-3;
92-87-5; 56-55-3; 50-32-8; 191-24-2; 207-08-9; 65-85-0;
119-53-9; 100-47-0; 119-61-9; 98-88-4; 94-36-0; 100-51-6;
100-44-7; 98-87-3; 7787-47-5; 7787-49-7; 13597-99-4; 7440-41-7;
58-89-9; 319-84-6; 319-85-7; 319-86-8; 111-91-1; 111-44-4;
39638-32-9; 117-81-7; 542-88-1; 80-05-7; 108-86-1; 75-27-4;
75-25-2; 74-83-9; 106-99-0; 33629-47-9; 123-86-4; 85-68-7;
85-70-1; 109-73-9; 84-78-6; 107-92-6; 543-90-8; 7789-42-6;
7440-43-9; 58-08-2; 7778-44-1; 52740-16-6; 75-20-7;
13765-19-0; 592-01-8; 26264-06-2; 1305-62-0; 7778-54-3;
1305-78-8; 1592-23-0; 105-60-2; 133-06-2; 63-25-2; 1563-66-2;
124-38-9; 75-15-0; 558-13-4; 56-23-5; 75-73-0; 7440-44-0;
8001-79-4; 9005-81-6; 9004-35-7; 9004-70-0; 57-74-9;
7782-50-5; 79-11-8; 1341-24-8; 108-90-7; 510-15-6; 124-48-1;
75-45-6; 75-00-3; 67-66-3; 74-87-3; 126-99-8; 7790-94-5;
2921-88-2; 57-88-5; 67-48-1; 1066-30-4; 7738-94-5; 10101-53-8;
7440-47-3; 7440-47-3; 10049-05-5; 218-01-9; 156-59-2; 60-33-3;
8007-45-2; 7789-43-7; 544-18-3; 14017-41-5; 65996-81-8;
7440-50-8; 56-72-4; 8021-39-4; 1319-77-3; 4170-30-3;
3724-65-0; 80-15-9; 142-71-2; 12002-03-8; 7447-39-4;
3251-23-8; 814-91-5; 10380-29-7; 7758-98-7; 815-82-7;
21725-46-2; 57-12-5; 372-09-8; 506-77-4; 108-80-5; 108-77-0;
110-82-7; 108-93-0; 110-83-8; 108-91-8; 112-30-1; 1740-19-8;
84-69-5; 84-74-2; 117-84-0; 121-69-7; 123-42-2; 2303-16-4;
333-41-5; 53-70-3; 84-74-2; 1918-00-9; 1194-65-6; 117-80-6;
25321-22-6; 75-27-4; 75-71-8; 111-44-4; 26545-73-3; 75-09-2;
26952-23-8; 1320-37-2; 62-73-7; 101-83-7; 77-73-6; 84-77-5;
60-57-1; 1464-53-5; 84-66-2; 64-67-5; 109-89-7; 124-17-4;
112-34-5; 112-15-2; 111-77-3; 111-46-6; 56-53-1; 25167-70-8;
27554-26-3; 26761-40-0; 108-18-9; 674-82-8; 60-51-5; 131-11-3;
75-18-3; 67-68-5; 120-61-6; 124-40-3; 79-44-7; 25154-54-5;
25321-14-6; 828-00-2; 122-39-4; 102-08-9; 25265-71-8;
927
-------
Accession Ho. 7301700902 (cont)
2764-72-9; 298-04-4; 330-54-1; 112-55-0; 27176-87-0; 27193-86-8;
139-02-6; 60-00-4; 1031-07-8; 959-98-8; 33213-65-9; 115-29-7;
7421-93-4; 53494-70-5; 72-20-8; 106-89-8; 2104-64-5; 61788-97-4;
563-12-2; 141-97-9; 74-96-4; 75-00-3; 105-39-5; 75-08-1; 75-04-7;
100-41-4; 107-07-3; 106-93-4; 107-06-2; 111-55-7; 110-71-4;
112-07-2; 111-76-2; 110-80-5; 110-49-6; 109-86-4; 107-21-1;
75-21-8; 74-85-1; 107-15-3; 149-57-5; 115-90-2; 1185-57-5;
14221-47-7; 7705-08-0; 7783-50-8; 10421-48-4; 10028-22-5;
10045-89-3; 7758-94-3; 7720-78-7; 206-44-0; 86-73-7;
16984-48-8; 50-00-0; 75-12-7; 64-18-6; 110-17-8; 98-01-1;
106-24-1; 142-47-2; 56-81-5; 26545-73-3; 25791-96-2; 556-52-5;
56-40-6; 107-22-2; 86-50-0; 7440-59-7; 1024-57-3; 76-44-8;
25339-56-4; 118-74-1; 87-68-3; 77-47-4; 67-72-1; 67-72-1; 57-10-3;
36653-82-4; 100-97-0; 124-09-4; 7647-01-0; 7664-39-3; 74-90-8;
7783-06-4; 1333-74-0; 9004-62-0; 193-39-5; 7553-56-2; 26760-64-5;
110-19-0; 79-31-2; 26952-21-6; 465-73-6; 78-78-4; 78-59-1;
121-91-5; 5835-26-7; 78-79-5; 67-63-0; 108-21-4; 67-63-0;
75-29-6; 108-20-3; 25168-06-3; 75-31-0; 115-32-2; 143-50-0;
463-51-4; 301-04-2; 7758-95-4; 7783-46-2; 13814-96-5;
10101-63-0; 10099-74-8; 1072-35-1; 7446-14-2; 1314-87-0;
592-87-0; 7439-92-1; 58-89-9; 60-33-3; 14307-35-8; 108-42-9;
108-39-4; 541-73-1; 108-38-3; 121-75-5; 110-16-7; 108-31-6;
123-33-1; 108-78-1; 2032-65-7; 592-04-1; 10045-94-0; 7783-35-9;
592-85-8; 10415-75-5; 7439-97-6; 141-79-7; 121-47-1; 563-47-3;
74-82-8; 950-37-8; 72-43-5; 79-20-9; 105-45-3; 591-78-6;
74-87-3; 107-31-3; 74-88-4; 108-11-2; 74-93-1; 80-62-6;
298-00-0; 119-36-8; 67-68-5; 74-89-5; 108-87-2; 6317-18-6; 75-09-2;
101-77-9; 77-75-8; 7786-34-7; 315-18-4; 57055-38-6; 75-04-7;
74-89-5; 110-91-8; 68-12-2; 121-69-7; 68-12-2; 530-50-7;
25167-67-3; 123-86-4; 84-74-2; 141-32-2; 109-73-9; 123-72-8;
106-31-0; 98-73-7; 100-61-8; 621-64-7; 62-75-9; 86-30-6;
109-66-0; 71-23-8; 300-76-5; 91-20-3; 1338-24-5; 7440-01-9;
75-98-9; 7785-20-8; 7718-54-9; 12054-48-7; 13138-45-9;
7786-81-4; 7440-02-0; 4726-14-1; 14797-55-8; 7697-37-2; 98-95-3;
79-24-3; 10102-44-0; 11104-93-1; 75-52-5; 25154-55-6; 25154-52-3;
25038-54-4; 95-51-2; 88-73-3; 95-49-8; 95-48-7; 95-50-1;
90-05-1; 88-74-4; 95-47-6; 57-11-4; 152-16-9; 119-07-3; 27193-28-8;
7782-44-7; 123-30-8; 59-50-7; 106-43-4; 106-44-5; 99-96-7; 98-73-7;
106-42-3; 30525-89-4; 56-38-2; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 82-68-8; 87-86-5;
594.42-3; 85-01-8; 108-95-2; 75-44-5; 7664-38-2; 10025-87-3;
1314-80-3; 7719-12-2; 7723-14-0; 88-99-3; 85-41-6; 110-85-0;
7440-06-4; 63428-83-1; 25038-59-9; 25322-68-3; 25322-69-4;
9002-89-5; 9002-86-2; 9003-39-8; 7784-41-0; N>J24-50-2;
20762-60-1; 7778-50-9; 7789-00-6; 151-50-8; 1310-58-3; 7722-64-7;
23950-58-5; 1918-16-7; 74-98-6; 709-98-8; 2312-35-8; 123-38-6;
79.09-4; 123-62-6; 109-60-4; 540-54-5; 78-87-5; 57-55-6;
75-56-9; 115-07-1; 129-00-0; 121-29-9; ^-22-5; M*'46-** 0< 0.
69-72-7; 78-92-2; 13952-84-6; 12640-89-0; 7782-49-2; 7631-86-9;
7761-88-8; 7440-22-4; 93-72-1; 122-34-9; 127-09-3; 7631-89-2;
7784-46-5; 532-32-1; 10588-01^9; 1333-83-1; 7631-90-5;
9004-32-4; 3926-62-3; 7775-11-3; 143-33-9; 25155-30-0;
928
-------
Accession No. 7301700902 (cont)
7681-49-4; 62-74-8; 141-53-7; 16721-80-5; 1310-73-2; 7681-52-9;
124-41-4; 7632-00-0; 7558-79-4; 7601-54-9; 10102-18-8; 7440-23-5;
110-44-1; 7789-06-2; 57-24-9; 57-24-9; 100-42-5; 110-15-6; 57-50-1;
121-57-3; 14808-79-8; 126-33-0; 10025-67-9; 7704-34-9; 7664-93-9;
1401-55-4; 72-54-8; 100-21-0; 75-65-0; 75-64-9; 127-18-4; 117-08-8;
78-00-2; 107-49-3; 110-18-9; 75-74-1; 7446-18-6; 7440-28-0;
23564-05-8; 110-02-1; 13463-67-7; 95-80-7; 108-88-3; 1333-07-9;
98-59-9; 8001-35-2; 75-25-2; 78-48-8; 52-68-6; 25323-89-1; 79-01-6;
75-69-4; 25167-82-2; 27323-41-7; 121-44-8; 112-27-6; 112-24-3;
1582-09-8; 75-50-3; 7440-33-7; 7440-61-1; 541-09-3; 10102-06-4;
57-13-6; 1314-62-1; 27774-13-6; 108-05-4; 75-01-4; 25013-15-4;
75-35-4; 111-41-1; 25321-41-9; 1330-20-7; 1300-71-6; 1300-73-8;
557-34-6; 1332-07-6; 7699-45-8; 3486-35-9; 7646-85-7; 7783-49-5;
557-41-5; 7779-86-4; 7779-88-6; 127-82-2; 1314-84-7; 16871-71-9;
7733-02-0; 7440-66-6; 13746-89-9; 16923-95-8; 14644-61-2;
10026-11-6; 311-45-5; 57-14-7; 95-94-3; 1615-80-1; 540-73-8;
57-55-6; 504-60-9; 1120-71-4; 110-57-6; 123-91-1; 130-15-4;
5344-82-1; 106-89-8; 86-88-4; 134-32-7; 58-90-2; 541-53-7;
87-65-0; 1338-23-4; 131-89-5; 80-62-6; 75-55-8; 75-86-5; 91-59-8;
109-06-8; 107-19-7; 88-85-7; 119-90-4; 119-93-7; 542-76-7;
56-49-5; 72-55-9; 50-29-3; 101-14-4; 3165-93-3; 99-55-8;
145-73-3; 20859-73-8; 7429-90-5; 61-82-5; 131-74-8; 140-57-8;
2465-27-2; 115-02-6; 225-51-4; 98-87-3; 98-09-9; 108-98-5;
92-87-5; 98-07-7; 92-52-4; 7440-69-9; 7440-42-8; 7726-95-6;
598-31-2; 357-57-3; 75-60-5; 630-08-0; 353-50-4; 75-87-6; 305-03-3;
118-75^2; 107-20-0; 75-01-4; 110-75-8; 107-30-2; 7440-48-4;
544-92-3; 1319-77-3; 98-82-8; 506-68-3; 460-19-5; 108-94-1;
50-18-0; 20830-81-3; 8065-48-3; 621-64-7; 132-64-9; 189-55-9;
124-48-1; 74-95-3; 696-28-6; 94-58-6; 77-78-1; 62-75-9; 123-91-1;
101-84-8; 142-84-7; 136-25-4; 141-78-6; 140-88-5; 60-29-7;
97-63-2; 62-50-0; 56-38-2; 107-12-0; 96-45-7; 151-56-4;
7782-41-4; 75-69-4; 110-00-9; 58-89-9; 67-72-1; 70-30-4;
1888-71-7; 757-58-4; 302-01-2; 74-90-8; 75-60-5; 9004-66-4;
7439-89-6; 78-83-1; 624-83-9; 120-58-1; 303-34-4; 7446-27-7;
1335-32-6; 7439-93-2; 109-77-3; 7439-96-5; 148-82-3;
628-86-4; 74-93-1; 67-56-1; 91-80-5; 16752-77-5; 126-98-7; 79-22-1;
71-55-6; 78-93-3; 1338-23-4; 60-34-4; 108-10-1; 56-04-2; 2385-85-5;
150-68-5; 494-03-1; 71-36-3; 70-25-7; 759-73-9; 684-93-5; 615-53-2;
924-16-3; 621-64-7; 1116-54-7; 55-18-5; 100-75-4; 930-55-2;
103-85-5; 107-10-8; 12612-55-4; 557-19-7; 54-11-5; 10102-43-9;
10102-44-0; 10544-72-6; 7727-37-9; 55-63-0; 684-93-5; 59-89-2;
636-21-5; 20816-12-0; 10028-15-6; 106-47-8; 106-46-7; 60-11-7;
100-01-6; 123-63-7; 4685-14-7; 608-93-5; 76-01-7; 127-18-4;
72-56-0; 62-44-2; 578-94-9; 696-28-6; 62-38-4; 7803-51-2;
1314-80-3; 85-44-9; 51-03-6; 506-61-6; 107-12-0; 114-26-1;
75-56-9; 110-86-1; 50-55-5; 299-84-3; 83-79-4; 78-48-8; 81-07-2;
94-59-7. 7783-00-8; 7446-34-6; 630-10-4; 506-64-9; 26628-22-8;
7440-23-5; 8001-50-1; 1314-96-1; 7446-09-5; 127-18-4; 56-23-5;
3689-24-5; 109-99-9; 509-14-8; 1314-32-5; 563-68-8; 29809-42-5;
7791-12-0; 10102-45-1; 62-55-5; 79-19-6; 62-56-6; 137-26-8;
7440-32-6; 26471-62-5; 25376-45-8; 2303-17-5; 78-48-8;
79-01-6; 75-70-7; 126-72-7; 10028-17-8; 72-57-1; 50-31-7;
929
-------
Accession Mo. 7301700902 (cont)
66-75-1; 51-79-6* 7440-62-2
(CNM) Contact naae(s): Bradshay,J. ; Corbin,F. ; Quinlan,J,
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Offlee of Toxic Substances.Management Suppo
930
-------
Accession No. 7301700903
(DQ) Date of Questionaire: 12*02-82
(NAM) Name of Data Base of Model: Chenlcal Regulations and Guidelines
System
(ACR) Acronym of Data Base or Model: CRGS
(MED) Media/Subject of Data Base or Model: All aspects of regulatory
control of chemicals are covered including:* o Disposal
o Trade Restrictions* o Manufacture o
Transportation! o Occupational Health o Use* o
product Registration! * Fields covered Include:? * o
Aeronautics o Foodf o Agriculture
o Miningf o Consumer Products o Nuclear
Technology* o Cosmetics o Petrochemicals*
o Energy o Pharmaceuticals* o
Environment protection o Transportation* *
(ABS) Abstract/Overview of Data Base or Model: CHEMICAL REGULATIONS
AND GUIDELINES SYSTEM (CRGS) is an authoritative index to U.S.
federal regulatory material relating to the control of chemical
substances/ covering federal statutes, promulgated regulations and
available federal guidelines/ standards/ and support documents.
CRGS follows the regulatory cycle and includes an up-to-date
reference to each document. Including main documents and
revisions published in the Federal Register. Each chemical cited
in a regulatory document is indexed by name, CAS Registry
Number, and a chemical role tag. The latter gives information
on the context in which the substances appear in the document.
CRGS also provides links between the statutes, the regulations
promulgated under these statutes, and the support documents
generated prior to the promulgation of a regulation. Each
document is described in terms of publication date, title,
abstract, index terms, and chemical identifiers. Index terms are
assigned fro» the CRCS Thesaurus which will be available online in
the CRGS file. ^ ^ ^MM9t
(CTC) CONTACTS: Subject matter Paula Miles (202) 426-2447;
Computer-related Paula Miles (202) 426-2447; EPA Office Paula Miles
(202) 426-2447.
(DTP) Type of data collection or monitoring: CRGS represents data
obtained from official sources of regulatory material including
the U.S. Code and its supplements, Statutes at Large, Code of
Federal Regulations, Federal Register/ and other material
obtained directly from federal agencies. „,„„„
(STA) Data Base status: Federal segment available publically on DIALOG
information Retrieval Service. CRGS is not currently funded for
update.
(1PP) Non-pollutant parameters included in the data base: Statutes,
regulations, standards and guidelines currently in effect.
(DS) Time period covered by data base: 01-01-30 TO 12-30-81
(TRM) Termination of data collection: Currently terminated awaiting
funding for update.
(FRQ) Freguency of data collection or sampling: As funded; not
currently funded.
(NOB) Number of observations In data base: 3,000 records.
(NBI) Estimated annual Increase of observations in data base: 1,000
931
-------
Accession Mo. 7301700903 (cont)
records/yr.
(IMF) Data base includes: Regulatory citations ;Indicative abstract
^"Descriptors" common to all regulator Concept and index terms
(Thesaurus) chemical name ;CAS number ; Qualified "role" of
regulated substances
(NTS) Total number of stations or sources covered in data base: (N/A.)
(RCS) No. stations or sources currently originating/contributing data:
(N/A.)
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: National
(LOG) Data elements identifying location of station or source Include:
Promulgating agency ^Official document citation ;Geographic
regulatory coverage
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: CAS registry number
(ANL) Lab analysis based on EPA-approved or accepted methods? M/A
UUD) Lab Audit: N/A
(PRE) Precision: Precision and accuracy estimates are not applicable*
(EOT) Fdltting: Edit procedures used and documented.
(CBY) Data collected by: Contractor CRC Systems, Fairfax, Va.
(ABY) Data analyzed by: Data not analyzed
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Retrieval of federal
regulations or standards
(PR2) Secondary purpose of data collection: Compliance or enforcement
(AUT) Authorization for data collection: Statutory authorization Is P
L 94-469, Sections 9-10 (Toxic Substances Control of 1976-TSCA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
request.
(HUS) Number of regular users of data base: 200
(USR) Current regular users of data base: Government, industry,
academia
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) primary physical location of data: Dialog Information Services,
Inc.
(DST) Form of data storage: N/A
(DAC) Type of data access: interactive query on Dialog Information
Services
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: As funded; monthly
is objective
(RDBEPA) Related EPA data bases used in conjunction with this data base
NIB/EPA CIS's Federal Register Search System (FRSS)
(CMP) Completion of form:
Paula Milesi OFC: EPA/(OPTS)/{OTS)/(MSD)
AD: 401 N St., S.H. Washington, DC 20460
PH: (202) 382-3775
(DF) Date of form completion: 12-10-82
(CNM) Contact name(s): Miles, P. j Miles,?. ; Miles,P.
932
-------
Accession Ho. 7301700903 (cont)
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Management Suppo
933
-------
Accession No. 7301700904
(DQ) Date of Quest!onaire: 12-02-82
(HAM) Rame of Data Base of Model: On-Line Chemical Inventory System
(ACR) Acronym of Data Base or Model: OLCIS
(MED) Media/Subject of Data Base or Model: No specific aedia
(ABS) Abstract/Overview of Data Base or Model: The Toxic Substances
Control Act (TSCA) provides EPA uith authority to regulate
commercial chemical substances, which pose unreasonable risk to
•an and the environment* OLCIS supports this effort. Information
Maintained are chemical, plant, and production volumes. It
contains chemicals manu- factured or imported in the U.S., what
chemicals are manufactured or imported at a given site, where
plants are located, and their names. There are data for about
55,000 chemicals in OLCIS, including the approximately 700 in the
Clearinghouse.
(CTC) CONTACTS: Subject matter Geri Now ale (202)382-3568;
Computer-related Fred Zalss (202)382-3617
(DTP) Type of data collection or monitoring: Combination/Other
chemical manufacturing and production data
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters Included in the data base: Chemical
data ;Location ;Manufacturer production levels
(OS) Time period covered by data base: 01-01-77 TO 12-30-77
(TRM) Termination of data collection: Occurred 12/30/78
(FRQ) Frequency of data collection or sampling: one time only ;Other
TSCA allows EPA to collect additional information, as requi which
may serve to update the data base.
(NOB) Number of observations in data base: 54500
substances.(Estimated)
(NEI) Estimated annual increase of observations in data base: (unknown*
(INF) Data base includes: Summary aggregate observations
(NTS) Total number of stations or sources covered in data base: 7700
(sites.)
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
H/A
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ^Street address ;Dun Bradstreet ; Program
identifier
(CDE) Pollutant identification data are: CAS registry number
(LiM) Limitation/variation in data of which user should be aware: The
OLCIS On-line User's Guide should be consulted prior to
accessing the information. Quality assurance questions are not
applicable.
(EOT) Editting: Edit procedures used and documented.
(C8Y) Data collected by: Contractor Chemical Abstracts Service
(ABT) Data analyzed by: EPA headquarters Office of Pesticides and
Toxic Substances (OPTS)/Office of Toxic Substances (OTS)
(IDL) Laboratory identification: NO
934
-------
Accession No. 7301700904 (cont)
(PR1) Primary purpose of data collection: Development of regulations
or standards
(PR2) Secondary purpose of data collection: Risk assessment
(AUT) Authorization for data collection: Statutory authorization is
P L 94-469, Sections 8(a) and 8(b) Toxic Substances Control Act
(TSCA)
(OMB) Data collected/sub*itted using OMB-approved EPA reporting foras:
158S77011
(REP) Fora of available reports and outputs of data base: 055-007-00004
-7, 055-007-00003-9, 055-000-00189-8: Government Printing Office
TSCA chemical inventory, PB-295-108 National Technical
Information Service (NTIS) magnetic tape.
Printouts on request
Microfilm
On-line computer
(•US) Kumber of regular users of data base: 8 offices
(OSR) Current regular users of data base: EPA headquarter offices
Offices of Pesticides and Toxic Substances, Office of Toxic
Substances, Office of Enforcement, Office of Solid Haste, Office of
Research and Development, Office of Drinking Hater, Office of
Hater Program Operations, Office of Air Quality Planning and
Standards
Other federal agencies
(CNF) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for some data
(DLC) Primary physical location of data: Contractor
(OST) Form of data storage: Magnetic disc
(DAC) Type of data access: EPA software OLCIS MIDS:7301700904 ;
EPA hardware DECSYSTEM-2020. Also available from the NIH/EPA
Chemical Information System. Component name is TSCAPP (TOSCA
Plant and Production Data).
(CHG) Direct charge for non-EPA use: no outside use/access permitted
(UPDT) Frequency of data base master file up-date: Other selected
portions/chemicals updated as required
(CMP) Completion of form:
Substances (OPTS)/
Office of Toxic Substances (OTS)/Nanagement Support Division (MSD)
AD: 401 M St, SH, Washington, DC 20460
PH: (202)426-4697
(OF) Date of form completion: 12-10-82
(•MAT) Number of substances represented in data base: 570
(ICAS) Number of CAS registry numbers in data base: 577
(NAT) Substances represented in data base:
acenaphthene<83-32-9> acetyl bromide<506-96-7>
acenaphthylene<208-96-8> acetyl chloride<75-36-5>
acetaldehyde<75-07-0> acrolein<107-02-8>
acetic acid<64-19-7> acrylamide<79-06-l>
acetic anhydrlde<108-24-7> acrylic acid<79-10-7>
acetone cyanohydrin<75-86-5> adipic acid<124-04-9>
acetone<67-64-l> ally! alcohol<107-18-6>
acetonitrile<75-05-8> allyl chloride<107-05-l>
acetophenone<98-86-2>
935
-------
Accession Mo. 7301700904
(cont)
alpha*alpha-dinethylbenzylhydro-
peroxide<80-15-9>
alpha,alpha-di«ethylphenethyla»ine
<122-09-8>
alpha-chlorotoluene<100-44-7>
0,0-diethyl-0-<2-py 1,1,1-
trlchloroethane<71-55-6>
If If If1f-tetrachloroethane
<79-34-5>
l,l,2-trichloroethane<79-00-5>
l,l,2-trichloroethene<79-01-6>
l,l-dichloroethane<75-34-3>
l,l-dichloroethylene<75-35-4>
lfl-diaethylhydrazlne<57-14-7>
l,2,4,-trichlorobenzene<120-82-l>
l,2,4*5-tetrachlorobenz«ne
<95-94-3>
1, 2-dibro»o-3-chloropropane (dbcp)
<96-12-8>
1,2-dlbr o*o« thane<106-93-4>
If2-dichlorobenzene<95-50-l>
l,2-dichloroethane
1,2-dichloropropane<78-87-5>
U2-dlchloropropylene<563-54-2>
l*2-dlphenylhydrazlne<122-66-7>
If2-propanediol<57-55-6>
1,2-trans-dichloroethylene
<156-60-5>
1,3,4 trichlorobenz«ne<120-82-l>
1,3-dlchlorobenzene<541-73-l>
l,3-dichloroprop«ne<542-75-6>
l,3-pentadiene<504-60-9>
1,3-propane sultoo«<1120-7l-4>
l,4-dlchloro-2-butene<110-57-6>
U4-dlchlorobenzeQe<106-46-7>
l,4-dioxan
1,4-naphthoquinone<130-15-4>
l-(o-chlorophenyl)thlourea
<5344-82-l>
l-chloro-2/3-epoxypropane
<106-89-8>
l-naphthyl-2-thiour«a<86-88-4>
l-naphthyla«in«<134-32-7>
2,2-dlchloroproplonic acid
<75-99-0>
2f 4,5-trichlor ophenoK 95-95-4>
2,4,5-trlchloroph«noxyac«tlc acid
(T)<93-76-5>
If 4,5-trichlorophenoxypropionic
acid (TP)<93-72-l>
2,4,6-trichloroph«nol<88-06-2>
2,4-d acid<94-75-7>
2,4-dlchlorophenol<120-83-2>
2,4-dlchlorophenoxyacetic acid (2,
4-d)<94-75-7>
2, 4-di«ethy IphenoK 105-67-9>
2, 4-din itrophenol<51-28-5>
2,4-dinltrotolu«ne<121-14-2>
2,4-dithiobiuret<541-53-7>
2,6-dlchloroph«nol<87-65-0>
2,6-dinitrotoluene<606-20-2>
2-butanone peroxide<1338-23-4>
2-chlorocthylvlnyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-fluoroaceta«ide (l081)<640-19-7>
2-«e thy l-2-(«e thy Ithio) prop ionalde
hyde-o-(Bethylcarbonyl)oxl«e
<80-62
-6>
2-««thylaziridine<75-55-8>
2-«ethyllactonitrile<75-86-5>
2-naphthyla«lne<91-59-8>
2-nitrophenol<88-75-5>
2-nitropropane<79-46-9>
2-picollne<109-06-8>
2-propyn-l-01<107-19-7>
2-sec butyl-4,6-dinltrophenol
<88-85-7>
3^3'-dichlorobenzidine<91-94-l>
3,3'-di«ethoxybenzidine<119-90-4>
3,3 •-di»ethyl-l(»ethylthio)-2-
butanone-0-((«ethyla«ino)
carbonyDoxiae
3,3 *-dl»ethylbenzldlne
<119-9 3-chloropropionitrile
<542-76-7>
3-««thylcholanthrcne< 56-49- 5>
4,4--dd«Cp^P'-ddx)<72-55-9>
4,4'-ddt<50-29-3>
4,4'-»«ttoylen«-bis-(2-chloroanilin
4,6-dinitro-o-cresol<534-52-l>
4-A«inopyridine<504-24-5>
4-bro»ophenyl phenyl ether
<101-55-3>
4-chloro-o-toluidine hydrochloride
<3165-93-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nit rophenoK 100-02-7>
5-(a«ino«ethyl)-3-isoxazolol
<2763-96-4>
5-nltro-o-toluidine<99-55-8>
936
-------
Accession Ho* 7301700904
(cont)
<39196-18-4>
aliminiM phosphide<20859-73-8>
aluBinun sulf ate<10043-01-3>
aluffinun<7429-90-5>
aaitrole<61-82-5>
aaaoni a< 7664-41-7>
aaaoniua acetate<631-61-8>
aaaoniua benzoate<1863-63-4>
aaaoniua bicarbonate<1066-33-7>
aaaoniura blchroaate<7789-09-5>
aaaonlua bif luoride<1341-49-7>
aaaonlua bisulfite<10192-30-0>
aiioniun carbaaate
aaaonlua carbonate<506-87-6>
aMoniun chlorlde<12125-02-9>
aBBoniua chro«ate<7788-98-9>
aiaonlum citrate<7632-50-0>
aMcniua f luoborate<13826-83-0>
anonium f luoride<12125-01-8>
aMoniura hydroxide<1336-21-6>
aHonium oxalate<1113-38-8>
aaBoniuB picrate<131-74-8>
auoniu* silicof luoride
<16919-19-0>
aiBoniun sulfa«ate<7773-06-0>
anonium sulf ide< 121 35-7 6-l>
auoniua sulf ite<10!96-04-0>
anonium tartrate<3164-29-2>
aMonium thiocyanate<1762-95-4>
aiioniua thiosulfate<7783-18-8>
aiyl acetate<628-63-7>
anillne<62-53-3>
anthracene
antinony pentachloride<7647-18-9>
antiaony potassiun tar tr ate
antimony trichloride<10025-91-9>
antiaony trifluoride<7783-56-4>
antimony tri oxide<1309-64-4>
antimony<7440-36-0>
arsenic acid<1327-52-2>
arsenic pentoxide<1303-28-2>
arsenic trichloride<7784-34-l>
arsenic trloxide<1327-53-3>
arsenic trisulfide<1303-33-9>
arsenic<7440-38-2>
asbestos<1332-21-4>
atrazine<1912-24-9>
aura«lne<2465-27-2>
bariioi cyan! de< 5 42-62- 1>
bariua<7440-39-3>
benoayl<17804-35-2>
benzal chlorlde<98-87-3>
benzene<71-43-2>
benzenesulfonyl chloride<98-09-9>
benzene thiol<108-98-5>
benzidlne<92-87-5>
benzo(a)anthracen«<56-55-3>
benzo(a)pyrene<50-32-8>
benzole acid<65-85-0>
benzoni tr ile<100-47-0>
benzotrichloride<98-07-7>
benzoyl chloride<98-88-4>
benzyl chloride<100-44-7>
beryl 11 un chloride<7787-47-5>
bcrylllua fluoride<7787-49-7>
berylliuB nitrate<13597-99-4>
berylliua<7440-4i-7>
bhc (lindane)-gaaaa<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
biphenyl<92-52-4>
bls(2-chloroethoxy)ae thane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl)ether
<39638-32-9>
bls(2-ethylhexyl)phthalate
bis(chloroaethyl)ether<542-88-l>
bisauth coapounds<7440-69-9>
boron coapounds<7440-42-8>
broaine<7726-95-6>
broaobenzene<108-86-l>
bromodichloro«ethane<75-27-4>
broaoaethane<74-83-9>
brucine<357-57-3>
butyl acetate<123-86-4>
butyl benzyl phthalate<85-68-7>
butylaaioe<109-73-9>
butyric acid<107-92-6>
cacodylic acid and salts<75-60-5>
cadaiua acetate<543-90-8>
cadaiua bromide<7789-42-6>
cadalua<7440-43-9>
calciua arsenate<7778-44-l>
calciua carbide<75-20-7>
calciua chroaate<13765-19-0>
calciua cyanide<592-01-8>
calciua dodecylbenzenesulfonate
<26264-06-2>
calcium hydroxide<1305-62-0>
calciua hypochlorite<7778-54-3>
937
-------
Accession Ro. 7301700904
(cont)
calciu» oxide<1305-78-8>
captan
carbaryl<63-25-2>
carbon disulfide<75-15-0>
carbon Bonoxide<630-08-0>
carbon tetrachloride<56-23-5>
carbonyl fiuoride<353-50-4>
chloral<75-87-6>
chloranil<118-75-2>
chlorine<7782-50-5>
chloroacetaldehyde<107-20-0>
chlorobenzene
chlcrobenzilate<510-15-6>
chlorodibroBO«ethane<124-48-l>
chloroethane<75-00-3>
chloroethene<75-01-4>
chloroethyl vinyl ether<110-75-8>
chloro for»<67-66-3>
chloro»ethane<74-87-3>
chloronethyl aethyl ether
<107-30-2>
chloroprene<126-99-8>
chlorosulfonic acid<7790-94-5>
chroalc acetate<1066-30-4>
chroalc acid<7738-94-5>
chrcmlc sulfate<10101-53-8>
chrOMiiiM<7440>47-3>
chrysene<218-01-9>
cis-l,2-dichloroethylene<156-59-2>
coal tar<8007-45-2>
cobalt<7440-48-4>
cobaltous for«ate<544-18-3>
copper cyanlde<544-92-3>
cr eoso te<8 021-3 9-4>
cresol<1319-77-3>
cresylic acid<1319-77-3>
crotonaldehydc<4170-30-3>
cu««n«<98-82-8>
cupric acetate<142-7l-2>
cuprlc chloride<7447-39-4>
cupric nitrate<3251-23-8>
cuprlc oxalate<8!4-91-5>
cupric sulfate<7758-98-7>
cuprlc tartrate<815-82-7>
cyaiside<57-12-5>
cyanogen bro«lde<506-68-3>
cyanogen chloride<506-77-4>
cyarogen<460-19-5>
cyclohexanc<110-82-7>
cyclohexanone<108-94-l>
di-isopropylfluorophosphate
<55-91-4>
di-n-butyl phthalate<84-74-2>
dl-n-octyl phthalate<117-84-0>
d i-n-propyIni tros a>ine<621-64-7 >
diazinon<333-41-5>
dibenzo(a^h)anthracene<53-70-3>
d ibenzofur anC132-64-9>
dibro«ochloromethane<124-48-l>
dlbrOBO«ethane<74-95-3>
dlbutyl phthalate<84-74-2>
dichlone
dlchlorobroao>ethane<75-27-4>
dichlorodifluoro«ethane<75-71-8>
dichloro«ethan«<75-09-2>
dlchlorophenylarslne<696-28-6>
dichloropropane<78-87-5>
dlchloropropene<542-75-6>
dlchlorvos (ddvp)<62-73-7>
diepoxybutane<1464-53-5>
dlethyl phthalate<84-66-2>
dlethyla«lne<109-89-7>
dlhydrosafrolc<94-58-6>
di»ethoate<60-51-5>
dlaethyl phthalate<131-ll-3>
dimethyl sulfate<77-78-l>
dUethylamine<124-40-3>
diBethylcarbavoyl chloride
<79-44-7>
dUethylnitrosa«ine<62-75-9>
dinltrotoluene<25321-14-6>
dioxan«<123-91-l>
dioxin<828-00-2>
dlpropyla«lne<142-84-7>
dluron<330-54-l>
dodecylbenzenesulfonic acid
<27176-87-0>
edta<60-00-4>
epichlorohydrln<106-89-8>
ethyl ac€tate<141-78-6>
ethyl acrylate<140-88-5>
ethyl chloride<75-00-3>
ethyl eth«t<60-29-7>
ethyl iethacrylate<97-63-2>
ethyl •ethanesulfonate<62-50-0>
ethylb«nzene<100-41-4>
ethylcyanide<107-12-0>
ethylene dibrovlde (edb)<106-93-4>
ethylene dichloride<107-06-2>
ethylene oxide<75-21-8>
ethylene thlourea<96-45-7>
ethylenedia»ine
ethylenci«ine<151-56-4>
ferric ai«onlu» citrate<1185-57-5>
938
-------
Accession No. 7301700904
(cont)
ferric anaonlui oxalate
<14221-47-7>
ferric chloride<7705-08-0>
ferric fluoride<77 83-50-8>
ferric nitrate<10421-48-4>
ferric sulfate<10028-22-5>
ferrous aaaoniua sulfatc
<10045-89-3>
ferrous chlorlde<7758-94-3>
ferrous sulfate<7720-78-7>
fluoranthene<206-44-0>
fluorene<86-73-7>
fluorine<7782-41-4>
fluorotrichloroaethane<75-69-4>
foraaldehyde<50-00-0>
foraic acid<64-18-6>
fuaaric acid
furan<110-00-9>
furfural<98-01-l>
hexachlorobenzene<118-74-l>
hexachlorobutadiene< 87-68- 3>
hexachlorocyclohexane<58-89-9>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
hexachlorophene<70-30-4>
hexachloropropene< 188 8-71-7>
hydrazine<302-01-2>
hydrochloric acid<7647-01-0>
hydrocyanic acid<74-90-8>
hydrofluoric acid<7664-39-3>
hydrogen cyanide<74-90-8>
hydrogen sulfide<7783-06-4>
hydroxydiaethyl arsine oxide
<75-60-5>
indeno
lodome thane<74-88- 4>
lron<7439-89-6>
isobutyl alcohol<78-83-l>
Isocyanlc acid, aethyl ester
<624-83-9>
isopho rone<7 8-59-1 >
lsoprene<78-79-5>
isosaf role
lead acetate<301-04-2>
lead chloride<7758-95-4>
lead fluoride<7783-46-2>
lead fluoroborate<13814-96-5>
lead iodide
lead nitrate<10099-74-8>
lead phosphate<7446-27-7>
lead stear ate< 1072-35-1>
lead subacetate<1335-32-6>
lead suUate<7446-14-2>
lead sulfide<1314-87-0>
lead thiocyanate<592-87-0>
lead<7439-92-l>
lindane<58-89-9>
lithium and coapounds<7439-93-2>
lithium chroaate<14307-35-8>
«-cresol<108-39-4>
ra-xylene<108-38-3>
•aleic acid<110-16-7>
•aleic anhydride<108-31-6>
naleic hydrazlde<123-33-l>
•alononitrile<109-77-3>
•anganese<7439-96-5>
nercurlc cyanide<592-04-l>
nercurlc nitrate<10045-94-0>
•ercuric sulfate<7783-35-9>
mercuric thiocyanate<592-85-8>
•ercury<7439-97-6>
•ethane th iol< 7 4-93-l>
»ethanol<67-56-l>
methyacrylonitrile<126-98-7>
methyl chlorocarbonate<79-22-l>
•ethyl chlorofori<71-55-6>
•ethyl ethyl ketone (nek)<78-93-3>
•ethyl ethyl ketone peroxide
<1338-23-4>
•ethyl hydrazine<60-34-4>
•ethyl iodide<74-88-4>
•ethyl isobutyl ketone<108-10-1>
•ethyl «ercaptan<74-93-l>
•ethyl •ethacrylate<80-62-6>
•ethylthiouracil<56-04-2>
nolybdenua and coapounds
<7439-98-7>
monoethylaaine<75-04-7>
aono«ethyla«ine<74-89-5>
•onuron
n-butyl alcohol<71-36-3>
n-butyl phthalate<84-74-2>
n-nethyl-n'-nitro-n-nitrosoguanidi
ne<70-25-7>
n-nitroso-n-ethylurea<759-73-9>
n-nitroso-n-«ethylurea<684-93-5>
n-nltroso-n-aethylurethane
<615-53-2>
n-nltrosodi-n-butyla«ine<924-16-3>
n-nitrosodi-n-propylamine
<621-64-7>
n-nitrosodiethanolaalne<1116-54-7>
n-nitrosodiethyla«ine<55-18-5>
n-nitrosodiaethylamine<62-75-9>
939
-------
Accession No. 7301700904
(cent)
n-nitrosodiphenylaaine<86-30-6>
n-nitrosopiperidine<100-75-4>
n-nitrosopyrrolidine<930-55-2>
n-ph«nylthiourea<103-85-5>
n-propylamine<107-10-8>
naphthaiene<91-20-3>
naphthenlc acid
nickel chloride<7718-54-9>
nickel cyanide<557-19-7>
nickel hydroxide
nickel nitrate<13138-45-9>
nickel sulfate<7786-81-4>
nlckel<7440-02-0>
nicotine and salts<54-ll-5>
nitric acld<7697-37-2>
nitric oxid«<10102-43-9>
nitrobenzene<98-95-3>
nitrogen dioxide<10102-44-0>
nitrogen peroxide<10102-44-0>
nitrogen tetroxide<10544-72-6>
nitrogen<7727-37-9>
nitroglycerine<55-63-0>
nitrosoaethylurea<684-93-5>
o-cresol<95-48-7>
o-««thoxyphenol<90-05-l>
o-toluidine hydrochloride
<636-21-5>
o-xylene<95-47-6>
octavethylpyrophosphoraside
osaiua tetroxide<20816-12-0>
ozone<10028-15-6>
p-chloro-a-cresol<59-50-7>
p-chloroaniline<106-47-8>
p-cresol<106-44-5>
p-dichlorobenzene<106-46-7>
p-dinethyla«ijioazobei\zene<60-ll-7>
P-nitroanillne<100-01-6>
p-xylene<106-42-3>
parafor»aldehyde<30525-89-4>
par ald«hyd
pen tachlorob enzene<6 08-93-5>
pentachloroethane<76-01-7>
pentachloronltrobenzene (PCNB)
<82-68-8>
pentachlorophenol<87-86-5>
perchloroethylene<127-18-4>
phenacetin<62-44-2>
phenanthrene<85-01-8>
phenol<108-95-2>
phenyl dichloroarsine<696-28-6>
phenylacetic acid<103-82-2>
phenylaercury acetate<62-38-4>
phosgene<75-44-5>
phosphine<7803-51-2>
phosphoric acid<7664-38-2>
phosphorus oxychloride<10025-87-3>
phosphorus pentasulfide<1314-80-3>
phosphorus sulfide<1314-80-3>
phosphorus trichloride<7719-12-2>
phosphorus<7723-14-0>
phthalic acid<88-99-3>
phthalic anhydride<85-44-9>
piperonyl butoxide<51-03-6>
potassium arsenat«<7784-41-0>
potassiun bichroBate<7778-50-9>
potassluM chro«ate<7789-00-6>
potassiui cyanide<151-50-8>
potassium hydroxide<1310-58-3>
potassiu* pemanganate<7722-64-7>
potassiu* silver cyanide<506-61-6>
potass!u»<7440-09-7>
prop ionic acid<79-09-4>
propionic anhydride<123-62-6>
propionitrile<107-12-0>
proplyene oxide<75-56-9>
propylene oxide<75-56-9>
pyrene<129-00-0>
quinoline<91-22-5>
reserpine<50-55-5>
resorcinol<108-46-3>
s^s^s-tributyl phosphorotrithioate
<78-48-8>
saccharin<81-07-2>
safrole<94-59-7>
selenious acid<7783-00-8>
seleniua oxide<12640-89-0>
seleniuK7782-49-2>
selenourea<630-10-4>
silver cyanide<506-64-9>
silver nitrate<7761-B8-8>
silver<7440-22-4>
siBazine<122-34-9>
sodluB and conpounds<7440-23-5>
sodiua arsenate<7631-89-2>
sodiuB arsenite<7784-46-5>
sodium azide<26628-22-8>
sodium bichroBate<10588-01-9>
sodiua bifluoride<1333-83-l>
sodiuB bisulfite<7631-90-5>
sodiuB chro»ate<7775-ll-3>
sodlua cyanide<143-33-9>
sodiua dodecylbenzenesulfonate
<25155-30-0>
940
-------
Accession Ho. 7301700904
(cont)
sodium fluoride<7681-49~4>
sodium fluoroacetate (1080)
<62-74-8>
sodium hydrosulfide<16721-80-5>
sodium hydroxide<1310-73-2>
sodiue hypochlorite<7681-52-9>
sodium aethylate<124-41-4>
sodium nitrite<7632-00-0>
sodium phosphate, dibasic
<75 58-79-4>
sodium phosphate, tribasic
<7601-54-9>
sodium selenit
sodiuB<7440-23-5>
strontium chromate<7789-06-2>
strontium sulflde<1314-96-l>
strychine<57-2 4-9>
styrene<100-42-5>
sulfur dioxide<7446-09-5>
sulfur •onochloride<10025-67-9>
sulfuric acid<7664-93-9>
te trachloroethene<127-18-4>
tetrachloroethylene<127-18-4>
tetrachloromethane<56-23-5>
tetraethyl lead<78-00-2>
tetrahydofuran<109-99-9>
tetcanitromethane<509-14-8>
thallic oxide<13!4-32-5>
thallium acetate<563-68-8>
thai HUB chloride<7791-12-0>
thallium nitrate<10102-4S-l>
thallium sulfate<7446-18-6>
thalliura<7440-28-0>
thioaceta*ide<62-55-5>
thioseraicarbazide<79-19-6>
thiourea<62-56-6>
thiura«<137-26-8>
titaniun<7440-32-6>
toluene diisocyanate<26471-62-5>
toluene<108-88-3>
toluenediaaine<25376-45-8>
tribro«omethane<75-25-2>
tributyl phosphorotrithioate
<78-48-8>
trichloroethene<79-01-6>
trichloroethylene<79-01-6>
trichlorofluoro«ethane<75-69-4>
trichlorophenol (TCP)<25167-82-2>
triethanolamine dodecylbenzenesul
onate<27323-41-7>
triethylaiine<121-44-8>
trine thylanlne<7S-SO-3>
trinitrobenzene<99-35-4>
trls(2^3-dibroaopropyl)phosphate
<126-72-7>
trypan blue<72-57-l>
uranius<7440-61-l>
uranyl acetate<541-09-3>
uranyl nitrate<10102-06-4>
urethane<51-79-6>
vanadlc acid, amonlua salt
vanadium pentoxide<1314-62-l>
vanadiun<7440-62-2>
vanadyl sulfate<27774-13-6>
vinyl acetate<108-05-4>
vinyl chloride<75-01-4>
vinylidene chloride<7 5-35-4 >
xylene<1330-20-7>
xylenol<1300-71-6>
zinc ace tate< 557-3 4-6>
zinc borate<1332-07-6>
zinc bro«ide<7699-45-8>
zinc carbonate<3486-35-9>
zinc chloride<7646-85-7>
zinc fluoride<7783-49-5>
zinc for»ate<557-41-5>
zinc hydrosulfite<7779-86-4>
zinc nitrate<7779-88-6>
zinc phenol sulfonate<127-82-2>
zinc phosphidc<1314-84-7>
zinc silicofluoride<16871-71-9>
zinc sulfate<7733-02-0>
zinc<7440-66-6>
zirconium nitrate<13746-89-9>
zirconium potassium fluoride
<16923-95-8>
zirconium sulfate<14644-61-2>
zirconium tetrachloride
<10026-ll-6>
(CAS) CAS registry numbers of substances included in data base: 83-32-9
> 208-96-8; 75-07-0; 64-19-7; 108-24-7; 75-86-5; 67-64-1;
75-05-8; 98-86-2; 506-96-7; 75-36-5; 107-02-8; 79-06-1;
79-10-7; 124-04-9; 107-18-6; 107-05-1; 80-15-9; 122-09-8;
100-44-7; 71-55-6; 79-34-5; 79-00-5; 79-01-6; 75-34-3;
75-35-4; 57-14-7; 120-82-1; 95-94-3; 96-12-8; 106-93-4; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 57-55-6; 156-60-5; 120-82-1;
941
-------
Accession No. 7301700904 (cent)
541-73-1; 542-75-6; 504-60-9; 1120-71-4; 110-57-6; 106-46-7;
123-91-1; 130-15-4; 5344-82-1; 106-89-8; 86-88-4; 134-32-7;
75-99-0; 95-95-4; 93-76-5; 93-72-1; 88-06-2; 94-75-7;
120-83-2; 94-75-7; 105-67-9; 51-28-5; 121-14-2; 541-53-7;
87-65-0; 606-20-2; 1338-23-4; 110-75-8; 91-58-7; 95-57-8;
640-19-7; 80-62-6; 75-55-8; 75-86-5; 91-59-8; 88-75-5;
79-46-9; 109-06-8; 107-19-7; 88-85-7; 91-94-1; 119-90-4;
56-49-5; 72-55-9; 50-29-3; 101-14-4; 534-52-1; 504-24-5;
101-55-3; 3165-93-3; 7005-72-3; 100-02-7; 2763-96-4; 99-55-8;
39196-18-4; 20859-73-8; 10043-01-3; 7429-90-5; 61-82-5; 7664-41-7;
631-61-8; 1863-63-4; 1066-33-7; 7789-09-5; 1341-49-7; 10192-30-0;
1111-78-0; 506-87-6; 12125-02-9; 7788-98-9; 7632-50-0; 13826-83-0;
12125-01-8; 1336-21-6; 1113-38-8; 131-74-8; 16919-19-0; 7773-06-0;
12135-76-1; 10196-04-0; 3164-29-2; 1762-95-4; 7783-18-8; 628-63-7;
62-53-3; 120-12-7; 7647-18-9; 11071-15-1; 10025-91-9; 7783-56-4;
1309-64-4; 7440-36-0; 1327-52-2; 1303-28-2; 7784-34-1; 1327-53-3;
1303-33-9; 7440-38-2; 1332-21-4; 1912-24-9; 2465-27-2; 542-62-1;
7440-39-3; 17804-35-2; 98-87-3; 71-43-2; 98-09-9; 108-98-5;
92-87-5; 56-55-3; 50-32-8; 65-85-0; 100-47-0; 98-07-7;
98-88-4; 100-44-7; 7787-47-5; 7787-49-7; 13597-99-4;
7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8; 92-52-4;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 7440-69-9;
7440-42-8; 7726-95-6; 108-86-1; 75-27-4; 74-83-9; 357-57-3;
123-86-4; 85-68-7; 109-73-9; 107-92-6; 75-60-5; 543-90-8;
7789-42-6; 7440-43-9; 7778-44-1; 75-20-7; 13765-19-0; 592-01-8;
26264-06-2; 1305-62-0; 7778-54-3; 1305-78-8; 133-06-2; 63-25-2;
75-15-0; 630-08-0; 56-23-5; 353-50-4; 75-87-6; 118-75-2;
7782-50-5; 107-20-0; 108-90-7; 510-15-6; 124-48-1; 75-00-3;
75-01-4; 110-75-8; 67-66-3; 74-87-3; 107-30-2; 126-99-8; 7790-94-5;
1066-30-4; 7738-94-5; 10101-53-8; 7440-47-3; 218-01-9; 156-59-2;
8007-45-2; 7440-48-4; 544-18-3; 544-92-3; 8021-39-4; 1319-77-3;
1319-77-3; 4170-30-3; 98-82-8; 142-71-2; 7447-39-4; 3251-23-8;
814-91-5; 7758-98-7; 815-82-7; 57-12-5; 506-68-3; 506-77-4;
460-19-5; 110-82-7; 108-94-1; 55-91-4; 84-74-2; 117-84-0;
621-64-7; 333-41-5; 53-70-3; 132-64-9; 124-48-1; 74-95-3;
84-74-2; 117-80-6; 75-27-4; 75-71-8; 75-09-2; 696-28-6;
78-87-5; 542-75-6; 62-73-7; 1464-53-5; 84-66-2; 109-89-7;
94-58-6; 60-51-5; 131-11-3; 77-78-1; 124-40-3; 79-44-7;
62-75-9; 25321-14-6; 123-91-1; 828-00-2; 142-84-7; 330-54-1;
27176-87-0; 60-00-4; 106-89-8; 141-78-6; 140-88-5; 75-00-3;
60-29-7; 97-63-2; 62-50-0; 100-41-4; 107-12-0; 106-93-4;
107-06-2; 75-21-8; 96-45-7; 107-15-3; 151-56-4; 1185-57-5;
14221-47-7; 7705-08-0; 7783-50-8; 10421-48-4; 10028-22-5;
10045-89-3; 7758-94-3; 7720-78-7; 206-44-0; 86-73-7;
7782-41-4; 75-69-4; 50-00-0; 64-18-6; 110-17-8; 110-00-9;
98-01-1; 118-74-1; 87-68-3; 58-89-9; 77-47-4; 67-72-1;
70-30-4; 1888-71-7; 302-01-2; 7647-01-0; 74-90-8; 7664-39-3;
74-90-8; 7783-06-4; 75-60-5; 193-39-5; 74-88-4; 7439-89-6;
78-83-1; 624-83-9; 78-59-1; 78-79-5; 120-58-1; 301-04-2;
7758-95-4; 7783-46-2; 13814-96-5; 10101-63-0; 10099-74-8;
7446-27-7; 1072-35-1; 1335-32-6; 7446-14-2; 1314-87-0;
592-87-0; 7439-92-1; 58-89-9; 7439-93-2; 14307-35-8; 108-39-4;
942
-------
Accession No. 7301700904 (cont)
108-38-3; 110-16-7; 108-31-6; 123-33-1; 109-77-3; 7439-96-5;
592-04-1; 10045-94-0; 7783-35-9; 592-85-8; 7439-97-6;
74-93-1; 67-56-1; 126-98-7; 79-22-lj 71-55-6; 78-93-3;
1338-23-4; 60-34-4; 74-88-4; 108-10-1; 74-93-1; 80-62-6; 56-04-2;
7439-98-7; 75-04-7; 74-89-5; 150-68-5; 71-36-3; 84-74-2; 70-25-7;
759-73-9; 684-93-5; 615-53-2; 924-16-3; 621-64-7; 1116-54-7;
55-18-5; 62-75-9; 86-30-6; 100-75-4; 930-55-2; 103-85-5;
107-10-8; 91-20-3; 1338-24-5; 7718-54-9; 557-19-7; 12054-48-7;
13138-45-9; 7786-81-4; 7440-02-0; 54-11-5; 7697-37-2;
10102-43-9; 98-95-3; 10102-44-0; 10102-44-0; 10544-72-6;
7727-37-9; 55-63-0; 684-93-5; 95-48-7; 90-05-1; 636-21-5;
95-47-6; 152-16-9; 20816-12-0; 10028-15-6; 59-50-7; 106-47-8;
106-44-5; 106-46-7; 60-11-7; 100-01-6; 106-42-3; 30525-89-4;
123-63-7; 608-93-5; 76-01-7; 82-68-8; 87-86-5; 127-18-4;
62-44-2; 85-01-8; 108-95-2; 696-28-6; 103-82-2; 62-38-4; 75-44-5;
7803-51-2; 7664-38-2; 10025-87-3; 1314-80-3; 1314-80-3; 7719-12-2;
7723-14-0; 88-99-3; 85-44-9; 51-03-6; 7784-41-0; 7778-50-9;
7789-00-6; 151-50-8; 1310-58-3; 7722-64-7; 506-61-6; 7440-09-7;
79-09-4; 123-62-6; 107-12-0; 75-56-9; 75-56-9; 129-00-0; 91-22-5;
50-55-5; 108-46-3; 78-48-8; 81-07-2; 94-59-7; 7783-00-8;
12640-89-0; 7782-49-2; 630-10-4; 506-64-9; 7761-88-8;
7440-22-4; 122-34-9; 7440-23-5; 7631-89-2; 7784-46-5; 26628-22-8;
10588-01-9; 1333-83-1; 7631-90-5; 7775-11-3; 143-33-9;
25155-30-0; 7681-49-4; 62-74-8; 16721-80-5; 1310-73-2;
7681-52-9; 124-41-4; 7632-00-0; 7558-79-4; 7601-54-9;
10102-18-8; 7440-23-5; 7789-06-2; 1314-96-1; 57-24-9;
100-42-5; 7446-09-5; 10025-67-9; 7664-93-9; 127-18-4; 127-18-4;
56-23-5; 78-00-2; 109-99-9; 509-14-8; 1314-32-5; 563-68-8;
7791-12-0; 10102-45-1; 7446-18-6; 7440-28-0; 62-55-5; 79-19-6;
62-56-6; 137-26-8; 7440-32-6; 26471-62-5; 108-88-3; 25376-45-8;
75-25-2; 78-48-8; 79-01-6; 79-01-6; 75-69-4; 25167-82-2;
27323-41-7; 121-44-8; 75-50-3; 99-35-4; 126-72-7; 72-57-1;
7440-61-1; 541-09-3; 10102-06-4; 51-79-6; 11115-67-6;
1314-62-1; 7440-62-2; 27774-13-6; 108-05-4; 75-01-4; 75-35-4;
1330-20-7; 1300-71-6; 557-34-6; 1332-07-6; 7699-45-8;
3486-35-9; 7646-85-7; 7783-49-5; 557-41-5; 7779-86-4;
7779-88-6; 127-82-2; 1314-84-7; 16871-71-9; 7733-02-0; 7440-66-6;
13746-89-9; 16923-95-8; 14644-61-2; 10026-11-6
(CUM) Contact nane(s): Nouak,G.
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Offlee of Toxic Substances.Management Suppo
943
-------
Accession Mo. 7301700905
(DQ) Date of Questionalre: 12-02-82
(•AN) Name of Data Base of Model: Scientific Parameters for Health and
the Environment* Retrieval and Estimation
(ACR) Acronym of Data Base or Models SPHERE
(MED) Media/Subject of Data Base or Model: Other Toxicological end
effects ;0ther Environmental fate data
(ABS) Abstract/Overview of Data Base or Model: This system Is the
Office of Toxic Substances* repository for known toxicological
and environmental effects and environmental fate data on
chemicals* It will store scientific data collected for or
generated by OTS and uill provide a mechanism whereby these data
can be manipulated and retrieved as required for the assessment
of chemicals.
(CTC) CONTACTS: Subject matter Paula Miles (202) 755-8963 ;
Computer-related Paula Miles
(DTP) Type of data collection or monitoring: Combination/Other data
collection: literature and toxic substances data
(STA) Data Base status: Discontinued
(GRP) Groups of substances represented in Data Base: 54 TSCA
assessment
(MPP) Ron-pollutant parameters included in the data base: Health
effects ^Environmental effects >Environmental fate
(OS) Time period covered by data base: 10-01-81 TO 05-15-82
(TRM) Termination of data collection: lot anticipated
(FRQ) Frequency of data collection or sampling: as needed
(•OB) Number of observations in data base: 1000(Estimated)
(•El) Estimated annual increase of observations in data base: 3000
(IMF) Data base Includes: Reference data/citations
(ITS) Total number of stations or sources covered In data base: (H/A)
(ffCs) no. stations or sources currently originating/contributing data:
(•/A)
(•OF) Number of facilities covered In data base (source monitoring): (N
/A)
(GEO) Geographic coverage of data base: International-literature
(LOC) Data elements identifying location of station or source include.
lot applicable
(FAC) Data elements identifying facility include: lot applicable
(LIM) Limitation/variation In data of which user should be aware: Conce
ntratlons/levels of a chemical In a particular media are not
included in this data base* Toxicity, physical- chemical and
environmental fate data are Included. Summary con- centration may
be added in the future*
(DPR) Data collect./anal, procedures conform to ORD guidelines: Conform
to ORD QA Guidelines-lot applicable
(AH.) Lab analysis based on EPA-approved or accepted methods? Lab
analysis Is not applicable*
(ADD) Lab Audit: Lab audit is not applicable.
(PRE) Precision: Precision and accuracy estimates will exist for all
measurements*
(EOT) Editting: Mo known edit procedures exist.
(CBT) Data collected by: Contractor ?EPA headquarters Office of Toxic
Substances
944
-------
Accession No. 7301700905 (cont)
(ABY) Data analyzed by: Contractor
EPA headquarters Office of Toxic Substances Data base identifies
specific document references.
UOT) Authorization for data collection: Statutory authorization is
P.L. 94-469 Section 10
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QC
(REP) Form of available reports and outputs of data base: Unpublished
reports - to be established* } Printouts on request
On-line computer
(USR) Current regular users of data base: EPA headquarter offices
Office of Toxic Substances
(CNF) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for all data
(DLC) Primary physical location of data: Contractor
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: EPA software: unknown at this time
(CHG) Direct charge for non-EPA use: Mo outside use/access permitted.
(0PDT) Frequency of data base Master file up-date: Other-Unknown at
this time.
(CMP) Completion of fora:
Paula Miles
OFC: EPA/OPT S/OTS/MSD
AD: 401 M Street, S.W., Washington, D.C. 20460
PH: (202) 755-8963
(OF) Date of form completion: 12-10-82
(IMAT) Number of substances represented in data base: 55
(ICAS) Number of CAS registry numbers in data base: 52
(NAT) Substances represented in data base:
l,l,l-trichloroethane<71-55- chlorinated naphthalenes
6> chloroethane<75-00-3>
1,1,2,2-tetrachloroethane<79-34-5> chlorofluorocarbons
l,l,2-trlchloroethene<79-01-6> chloroform<67-66-3>
l,l-dlchloroethane<75-34-3> chloromethane<74-87-3>
l,2-dibromoethane<106-93-4> chloroprene<126-99-8>
l,2-dichlorobenzene<95-50-l> chromlum<7440-47-3>
l,2-dichloroethane<107-06-2> dichloromethane<75-09-2>
l,2-dichloropropane<78-87-5> dioxin<828-00-2>
1,3-dichlorobenzene<541-73-l> ethylbenzene<100-41-4>
1,4-dichlorobenzene<106-46-7> formaldehyde<50-00-0>
2,4-dinitrotoluene<121-14-2> hexachlorobenzene<118-74-l>
2-nltropropane<79-46-9> hexachlorobutadlene<87-68-3>
acetaldehyde<75-07-0> hexachlorocyclopentadiene<77-47-4>
acrolein<107-02-8> hexacloroethane
acrylonitrile<107-13-1> isophorone<78-59-l>
antimony<7440-36-0> lead<7439-92-l>
arsenic<7440-38-2> m-cresol<108-39-4>
asbestos<1332-21-4> m-xylene<108-38-3>
benzene<71-43-2> maleic anhydride<108-31-6>
benzidine<92-87-5> aercury<7439-97-6>
benzyl chlorlde<100-44-7> methyl iodide<74-88-4>
cadmium<7440-43-9> nltrobenzene<98-95-3>
945
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Accession Mo. 7301700905 (cent)
o-cresol<95-48-7> polychlorlnated biphenyls (PCBs)
o-xylene<95-47-6> <1336-36-3>
p-cresol<106-44-5> toluene<108-88-3>
p-xylene<106-42-3> trichloroethane<25323-89-l>
pbosgene<75-44-5> vinylldene chloride<75-35-4>
polybro«inated biphenyls (PBBs)
(CAS) CAS registry numbers of substances Included in data base: 71-55-6
; 79-34-5; 79-01-6; 75-34-3; 106-93-4; 95-50-1; 107-06-2;
78-87-5; 541-73-1; 106-46-7; 121-14-2; 79-46-9; 75-07-0;
107-02-8; 107-13-1; 7440-36-0; 7440-38-2; 1332-21-4; 71-43-2;
92-87-5; 100-44-7; 7440-43-9; 75-00-3; 67-66-3; 74-87-3;
126-99-8; 7440-47-3; 75-09-2; 828-00-2; 100-41-4; 50-00-0;
118-74-1; 87-68-3; 77-47-4; 78-59-1; 7439-92-1; 108-39-4;
108-38-3; 108-31-6; 7439-97-6; 74-88-4; 98-95-3; 95-48-7;
95-47-6; 106-44-5; 106-42-3; 75-44-5; 1336-36-3; 108-88-3;
25323-89-1; 75-35-4
(CUM) Contact nane(s): Miles,?. ; Miles,?. ; Miles,P.
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Offlee of Toxic Substances.Management Suppo
946
-------
Accession Mo. 7407000517
(DQ) Date of Questionaire: 12-02-82
(IAH) Kane of Data Base of Model: Stability Array Data File
(ACR) Acronya of Data Base or Model: STAR
(HED) Media/Subject of Data Base or Model: Air
(IBS) Abstract/Overview of Data Base or Model: The STAR data files
contain meterological data for 394 first order Heather stations
in the continental OS. STAR data consists of frequencies of
Hind direction by wind speed classes for each of up to seven
atmospheric stability categories. Hind directions are given for
16 sectors corresponding to coupass points and there are 6 Hind
speed categories. The data are vailable as annual average
frequencies based on at least five consecutive years of data*
(CTC) CONTACTS: Subject natter Loren Hall (202) 382-3931 ;
Computer-related Loren Hall (202) 382-3931 ; EPA Office William
Hood - OTS (202) 382-3928
(DTP) Type of data collection or aonitoring: Aabient
(STA) Data Base status: Presently Operational/Ongoing
(1PP) lion-pollutant parameters included in the data base: Hind
direction ; wind velocity
(IMF) Data base includes: Aggregate or sunoary observations
(CEO) Geographic coverage of data base: National
(LOG) Data elements identifying location of station or source include:
Latitude and longitude
(DPR) Data collect./anal, procedures confora to ORD guidelines: NO
(IIL) Lab analysis based on EPA-approved or accepted methods? NO
(ADD) Lab Audit: N/A: data not based on laboratory analysis
(PRB) Precision: None available
(EOT) Editting: No known edits
(CBY) Data collected by: Other- National A Heather Service
(ABT) Data analyzed by: Other- National Cliaatic Center
(IDL) Laboratory identification: NO
UOT) Authorization for data collection: NO
(OMB) Data collected/subaitted using OMB-approved EPA reporting forms:
NO
(REP) Fora of available reports and outputs of data base: On-line
computer terminal
(IDS) Nuaber of regular users of data base: 10-15
(VSR) Current regular users of data base: EPA Headquarters Offices,
Office of Toxic Substances, OPRM
(CIF) Confidentiality of data and Halts on access: None
(OLC) Primary physical location of data: NCC/RTP
(DST) Fora of data storage: Magnetic disc
(DAC) Type of data access: EPA Software Systea: Systea Naae- OTS
Graphical Exposure Modeling System/ Hardware- VAX 11/780
(CHG) Direct -charge for non-EPA use: No outside use/access permitted
(OPDT) Frequency of data base master file up-date: None
(RSS) Related EPA automated systems which use data base: Related EPA
Systems: ATM/SCCPOP (model)
(RDBBPA) Related EPA data bases used in conjunction with this data base
(RDB) Non-EPA data bases used in conjunction with this data base: None
(CMP) Coapletion of form: f Mllliam P. Hood* OFC: OPTS/OTS/EEDf AD:
947
-------
Accession lo. 7407000517 (cont)
EPA/ Headquarters! PH: (202) 382-39281
(DF) Date of for* completion: 01-25-83
(CUM) Contact naae(s): Hall,L. ; Hall,L. ; Wood,*.
(COR) Contact organization: OTS
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Exposure Evaluat
948
-------
Accession Mo. 7407000518
(DQ) Date of Questionalre: 12-02-82
(IAM) Name of Data Base of Model: 1977 Economic Census
(ACR) Acronym of Data Base or Model: Rone
(NED) Media/Subject of Data Base or Model: N/A data not related to
specific *edla: Economic Data
(ABS) Abstract/Overview of Data Base or Model: Data Base has 4
components: CD Census of manufacturers (geographic area series.
Industry series, location of manufacturing plants, fuels and
electricity consumed 1977 and 1978), (2) Census of Wholesale Trade
(geographic area series), (3) Census of Selected Service
industries, (4) Census of Transportation (commodity
transportation survey and truck inventory and use survey)*
(CTC) CONTACTS: Subject matter Loren Hall 382-3931 ; Computer-
related Loren Hall 382-3931 ; EPA Office Hilliam P. Hood,
Office of Toxic Substances 382-3928
(STA) Data Base status: Presently Operational/Ongoing
(IPP) Non-pollutant parameters included in the data base: Cost or
economic data > Information includes number of industries or
establishments by SIC code, number of employees and their wagtJ,
number of production workers, receipts or value added by
manufacturer for 1977*
(DS) Time period covered by data base: Single date: 1977
(tRM) Termination of data collection! lot applicable
(PRO) Frequency of data collection or sampling: Every S years
(IMF) Data base includes: Aggregate or summary observations
(CEO) Geographic coverage of data bases iational
(LOG) Data elements identifying location of station or source include:
State > county ; smsa (standard metropolitan statistical area) >
city
(PAC) Data elements identifying facility include: SIC code
(LlM) Limitation/variation in data of which user should be auare: The
location of manufacturing plants is as lightly misleading name,
since the file only provides the number of establishments in 7
employee size categories.
(DPR) Data collect./anal, procedures conform to QRD guidelines: Ho,
but other documentation available for each of the following:
collection method
(AIL) Lab analysis based on EPA-approved or accepted methods? MO
(AOD) Lab Audit: N/A: data not based on laboratory analysis
(PRE) Precision: None available
(EOT) Editting: No known edits
(CBY) Data collected by: Other- Bureau of Census
(ABY) Data analyzed by: Other- Bureau of Census
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Trend assessment
(PR2) Secondary purpose of data collection: None
(AUT) Authorization for data collection: NO
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
NO
(REP) Form of available reports and outputs of data base: On-line
computer terminal
(•OS) Number of regular users of data base: 10-15
949
-------
Accession Ho. 7407000518 (cont)
(OSR) Current regular users of data base: EPA Headquarters Offices*
Office of Toxic Substances
(CMF) Confidentiality of data and 1inits on access: Hone
(OLC) priaary physical location of data: HCC/RTP
(DST) For* of data storage: Magnetic Disc
COAC) Type of data access: EPA Software Systea: System Haae- OTS
Graphical Exposure Modeling System (GEMS), Hardware- ?AX 11/780
(CHG) Direct charge for non-EPA use: Ho outside use/access permitted
(OPDT) Frequency of data base master file up-date: 5 years
(RSS) Related EPA automated systems which use data base: Hone
(RDBEPA) Related EPA data bases used in conjunction with this data base
Hone
(ROB) Non-EPA data bases used in conjunction with this data base: lone
(CMP) Completion of fora: f William P. Hoodf OFC: OPTS/OfS/BBDf AD:
EPA/ Headquarters! PH: (202) 382-3928f
(DF) Date of fora completion: 01-20-83
(CHM) Contact na»e(s): Hall,L. ; Hall,L. ; Nood,tf.P.
(COR) Contact organization: Office of Toxic Substances
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances*Exposure Evaluat
950
-------
Accession No. 7407000519
(DQ) Date of Questionaire: 12-02-82
(IAN) Kane of Data Base of Model: Geoecology
(ACR) Acronym of Data Base or Model: None
(MED) Kedia/Subject of Data Base or Model: Air > Soil ; Surface Water
; Other- terrain, wildlife, climate
(ABS) Abstract/Overview of Data Base or Model: Data Base contains
county level data on a variety of environmental parameters.
Categories Include agriculture, climate, vegetation, forestry,
air quality, terrain, wildlife (endangered species). Each of these
contains files of interest in the exposure assessment process.
For example the agricultural files contain area under cultivation
and yield statistics for a variety of commercially important crops
from 1978 Census of Agriculture.
(CTC) CONTACTS: Subject natter Lor en Hall (202) 382-3931 ;
Computer-related Loren Hall (202) 382-3931 ; EPA Office William
P. Wood, Office of Toxic Substances (202) 382-3928
(DTP) Type of data collection or monitoring: Combinations and other:
county level
(STA) Data Base status: Presently Operational/Ongoing
(NPP) Non-pollutant parameters included in the data base: Geographic
subdivisions: county ; precipitation ; temperature ; Climatic
variables include annual average and monthly maximum and minimum
temperature and monthly precipitation and potential
evapotranspiration. Soil types by county with some physical and
chemical properties for general soil classes.
(DS) Time period covered by data base: 1940 TO 1980
(TRH) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Ongoing: as needed
(INF) Data base includes: Aggregate or summary observations
(6EO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
County
(DPR) Data collect./anal, procedures conform to ORD guidelines: No,
but other documentation available for each of the following:
collection method ^ * ~ «n
(ANL) Lab analysis based on EPA-approved or accepted methods? NO
(AOD) Lab Audit: N/A: data not based on laboratory analysis
(PRE) Precision: None available
(EOT) Editting: No known edits
(CBY) Data collected by: Department of Energy
UBY) Data analyzed by: Department of Energy
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Exposure Assessment
(PR2) Secondary purpose of data collection: None
(AOT) Authorization for data collection: NO
(OMB) Data collected/ submit ted using OMB-approved EPA reporting forms.
(RBP) Form of available reports and outputs of data base: On-line
computer terminal
(•OS) Number of regular users of data base: 10-15
(OSR) Current regular users of data base: EPA Headquarters Office,
Office of Toxic Substances
951
-------
Accession Ho. 7407000519 (cont)
(CHF) Confidentiality of data and Halts on access: None
(DLC) Prlaary physical location of data: HCC/RTP
(DST) form of data storage: Magnetic Disc
CDAC) Type of data access: EPA Software Syste»: Systea Naae- OTS
Graphical Exposure Modeling Systea (GEMS), Hardware- VAX 11/780
(CHG) Direct charge for non-EPA use: Ho outside use/access permitted
CRSS) Related EPA automated systems which use data base: None
(ROBEPA) Related EPA data bases used in conjunction with this data base
Hone
(RDB) lon-EPA data bases used in .conjunction tilth this data base: None
(CMP) Completion of fora: f Willlaa P. Voodf OFC: OPTS/OTS/EEDf AD:
EPA/ Headquarters* PH: (202) 382-3928*
(DP) Date of fora completion: 01-20-83
(CUM) Contact naae(s): Hall/L. j Hall/L. ; Wood,*.P.
(COR) Contact organization: Office of Toxic Substances
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Offlee of Toxic Substances*Exposure Evaluat
952
-------
Accession No. 7407000520
(DQ) Date of Questionaire: 12-02-82
(•AM) Name of Data Base of Model: Master Area Reference File of the
1980 Census
(ACR) Acronym of Data Base or Model: MARF
(MED) Media/Subject of Data Base or Model: N/A data not related to
specific media. Population Data
(ABS) Abstract/Overview of Data Base or Model: The complete corrected
MARF of 1980 Census with geographic coordinates for s»all
geographic areas. The file has a variety of location
identification, information, including region, state, county,
place, census tracts, and enumeration districts or block
groups, population country races, number of occupied and ouner
occupied housing units, and number of families for all the
enumeration districts/block groups*
(CTC) CONTACTS: Subject Batter Loren Hall (202) 382-3931 }
Computer-related Loren Hall (202) 382-3931 ; EPA Office William
Mood - OTS (202) 382-3928
(STA) Data Base status: Presently Operational/Ongoing
(IPP) Non-pollutant parameters included in the data base: Geographic
subdivisions ; population demographics ; population density
(DS) Tine period covered by data base: Single date: 1980
(TRM) Termination of data collection: Hot applicable
(FRQ) Frequency of data collection or sampling: 10 year Census
(INF) Data base includes: Aggregate or summary observations
(CEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
State ; county ; congressional district ; sisa( standard
metropolitan statistical area) > city ; tonn/tovnship ; latitude
and longitude
(FAC) Data elements identifying facility include: Not applicable
(DPR) Data collect./anal, procedures conform to ORD guidelines: No,
but other documentation available for each of the following:
Analysis method
(AIL) Lab analysis based on EPA-approved or accepted methods? NO
(ADD) Lab Audit: N/A: data not based on laboratory analysis
(PRE) Precision: None available
(EOT) Fditting: YES, documented edits
(CBY) Data collected by: Other- Census Bureau
(ABY) Data analyzed by: Other- Contractor, Donnelly Marketing Inc.
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Risk assessment
(PR2) Secondary purpose of data collection: Trend assessment
(AOT) Authorization for data collection: YES, citation: NON-EPA
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
NO
(REP) Form of available reports and outputs of data base: On-line
computer terminal
(•OS) Number of regular users of data base: 10-15
(USR) Current regular users of data base: EPA Headquarters Offices,
Office of Toxic Substances, ORP, OPRM, OAQPS
(CNF) Confidentiality of data and limits on access: Some data
confidential, limits on access outside the agency
953
-------
Accession No. 7407000520 (cont)
(DLC) Primary physical location of data: NCC/RTP
(DST) Fora of data storage: Magnetic Disc
(DAC) type of data access: EPA Software System: System Same- OTS
Graphical Exposure Modeling System (GEMS), Hardware- ¥AX 11/780
(CHG) Direct charge lor non-EPA use: Ho outside use/access permitted
(OPDT) Frequency of data base master file up-date: annually
(RSS) Related EPA automated systems which use data base: Related EPA
Systems: ATM/SECPOP
(RDBEPA) Related EPA data bases used in conjunction with this data base
Hone
(RDB) Von-EPA data bases used in conjunction with this data base: Hone
(CMP) Completion of form: f William P. Wood* OFC: OPTS/OTS/EEDf AD:
EPA/ Headquartersf PR: (202) 382-3928f
(DP) Date of form completion: 01-25-83
(CNN) Contact name(s): Hall,L. ; Hall,L. ; Wood,*.
{COR) Contact organization: OTS
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Offlee of Toxic Substances*Exposure Evaluat
954
-------
Accession Mo. 8213000513
(DQ) Date of Questionaire: 12-02-82
(VAN) Name of Data Base of Model: Whole-Body Count and Bioassay
(ACR) Acronym of Data Base or Model: NBC
(NED) Media/Subject of Data Base or Model: Tissue: Hunan whole body,
urine
(ABS) Abstract/Overview of Data Base or Model: Ingested and inhaled
radionnclides and humans, radiation workers and general public,
relative to Nevada Test site operations and laboratory
activities. Data collected since 1963 is being prepared for
entry into computer data base* Data is fron reports/ internal
memoranda, monitoring logs, and raw data stored in various
formats on hard copy, paper tape, magnetic tape, and disk.
(CTC) CONTACTS: Subject matter Director, Nuclear Radiation
Assessment Division 545-2305 ; Computer-related Anita A. Mullen
545-2650 ; EPA Office Charles F. Costa; Dir., Nuclear Radiation
Assessment Div., EMSL-LV 545-2305
(DTP) Type of data collection or monitoring: Combinations and other:
Whole-body counting for gamma and X rays, urine analysis for
tritium
(STA) Data Base status: Presently Operational/Ongoing
(GRP) Croups of substances represented in Data Base: Other- CS-137,
K-40, 1-131, 1-133, 1-135, H-187, PO-238, PO-239, H-3, and other
miscellaneous gamma-emitting radionuclides detected in humans.
(IPP) Non-pollutant parameters included in the data base: Biological
data ; concentration measures ; expousre data ; location ;
physical data ; political subdivisions / sampling date ;
volume/mass measures ; subject name, address and social security
number
(OS) Tine period covered by data base: 06-63 TO 12-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Ongoing: semi-annually
; ongoing: annually ; ongoing: as needed
(IOB) Number of observations in data base: 8000(Estimated to date)
(•El) Estimated annual increase of observations in data base: 800
(INF) Data base includes: Raw data/observations ; Other- Software for
data summary under development
(ITS) Total number of stations or sources covered in data base: 44
(ICS) No. stations or sources currently originating/contributing data:
37
(•OF) Number of facilities covered in data base (source monitoring): 2
(GEO) Geographic coverage of data base: Geographic Region: Nevada,
Utah, California
(LOG) Data elements identifying location of station or source include:
State ; town/township ; street address ; Name, social security
number
(FAC) Data elements identifying facility include: Other
(CDE) Pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Past
data not yet entered into data base/ specific data are personal
and private until released by subject(s) for use by other
organizations.
(OpR) Data collect./anal, procedures conform to QRD guidelines: NO,
955
-------
Accession Mo. 8213000513 (cont)
but other documentation available for each of the following:
sampling plan, collection method/ and analysis method
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: YES, urine ; M/A: data not based on laboratory
analysis- whole body count
(PRE) Precision: Not included in data base, precision and accuracy
measurements available from other sources
(EOT) Edittlng: YES, undocumented
(CBY) Data collected by: EPA Lab- Environmental Monitoring Systems
Laboratory, Las Vegas, NV ; other Federal Agency- US Public Health
Service, Las Begas, NV
(ABY) Data analyzed by: EPA Lab: E-M-S-L-, Las Vegas, NV ; other
Federal Agency: OS P-H-S- Las Vegas MV
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Risk Assessment
(PR2) Secondary purpose of data collection: Other- Historical trends
(AOT) Authorization for data collection: NO, data collection is part
of the total radiation safety program further Nevada Test Site
and the EMSL-LV.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
•o
(REP) Form of available reports and outputs of data base: Publications:
Offsite Environmental Monitoring Report for Nevada Test Site
published annually. Occasional Journal articles on specific
aspects. ; Printouts on request ; machine-readable raw data,
current only
(NOS) Number of regular users of data base: 3
(OSR) Current regular users of data base: EPA Laboratories ; other
Federal Agencies ; Other- EC&G
(CNF) Confidentiality of data and limits on access: All data
confidential, limits on access both within EPA and outside the
agency
(DLC) Primary physical location of data: EPA Lab
(DST) Fora of data storage: Presently, portions of data are A, B & D
(DAC) Type of data access: Commercially available software for recent
data System Name- MIDAS , Hardware- Nuclear Data 6620
(CHG) Direct charge for non-EPA use: NO
(UPDT) Frequency of data base master file up-date: Monthly
(RSS) Related EPA automated systems which use data base: None
(RDBEPA) Related EPA data bases used in conjunction with this data base
Related EPA data bases: Historical Dosimetry (film badge),
Thermoluminescent Dosimitry
(RDB) Non-EPA data bases used in conjunction with this data base: None
(CMP) Completion of form: f A. A. Mullenf OFC:
EPA/ORD/OMTS/EMSL-LVf AD: P.O. Box 15027, Las vegas, MV 89114*
PH: (702) 798-2650f
(DF) Date of form completion: 12-13-82
(NMAT) Number of substances represented in data base: 9
(NCAS) Number of CAS registry numbers in data base: 0
956
-------
Accession No. 8213000513 (cont)
(MAT) Substances represented in data base:
CS-137 M-187
K-40 P0-238
1-131 PO-239
1-133 H-3
1-135
(CNM) contact naae(s): Nullen,A.A. ; Costa,C.F
(COR) Contact organization: Nuclear Radiation Assessment Division/
EMSL-LY
(ROR) Responsible Organization: Office of Research and
Development.Office of Monitoring Systems and Quality Assurance
957
-------
Accession No. 8213000514
(DQ) Date of Questionaire: 12-02-82
(VAN) Kane of Data Base of Model: Pressurized Ion Chamber
(ACR) Acronym of Data Base or Model: PIC
(MED) Media/Subject of Data Base or Model: Emissions: Radioactives ;
Measure external gamma -ray dose
(ABS) Abstract/overview of Data Base or Model: Environmental radiation
data collected since 1/82 in the Mevand Test Site Offsite area
California, Nevada and Otah, data base contains measurements of
external gamma-ray exposure at 15 stations*
(CTC) CONTACTS: Subject matter Director, Nuclear Radiation
Assessment Division 545-2305 ; Computer-related Robert 6. Patzer
545-2324 j EPA Office Charles F. Costa; Dlr. Nuclear Radiation
Assessment Div., EMSL-L? 545-2305
(DTP) Type of data collection or monitoring: Combinations and other:
Ambient radiation, natural and man-made
(STA) Data Base status: Presently Operational/Ongoing
(CRP) Croups of substances represented in Data Base: Other- Externaly
gamma-ray exposure
(NPP) Non-pollutant parameters included in the data bases Collection
method or instrument ; elevation > exposure data ; location ;
political subdivisions ; sampling date
(OS) Time period covered by data base: 01-82 TO 12-82
(TRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: Ongoing: less than
hourly: maximum, minimum and average every 5 minutes
(NOB) Number of observations in data base: 2,300,000(Estimated to
date)
(NED Estimated annual increase of observations in data base: 2,300,000
(INF) Data base includes: Raw data/observations ? aggregate or summary
observations
(NTS) Total number of stations or sources covered in data base: 15
(NCS) No. stations or sources currently originating/contributing data:
IS
(NOF) Number of facilities covered In data base (source monitoring): 1
(CEO) Geographic coverage of data base: Geographic region: Nevada,
Utah, and California
(LOC) Data elements identifying location of station or source include:
State ; town/township 1 street address
(FAC) Data elements identifying facility include: Not applicable
(CDE) Pollutant identification data are: Oncoded
(DPR) Data collect./anal, procedures conform to ORD guidelines: No,
but other documentation avlilable for each of the following:
sampling plan, collection method, analysis method,
(AM.) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: N/A: data not based on laboratory analysis
(PRfi) Precision: YES, for all measurements
(EOT) Fditting: YES, undocumented
(CBY) Data collected by: EPA Lab, EMSL-LY
(ABY) Data analyzed by: EPA Lab, EMSL-L?
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Trend assessment
(PR2) Secondary purpose of data collection: Special study
958
-------
Accession No. 8213000514 (cont)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
•o
(REP) For* of available reports and outputs of data base: Publications:
Offsite Environmental Monitoring Report for the Nevada Test
Site/ published annually / Machine- readable ran data
(IBS) Nunber of regular users of data base: 2
(HSR) Current regular users of data base: EPA laboratories, EMSL-LV ;
other Federal Agencies/ DOE
(GIF) Confidentiality of data and 1 in its on access: Some data
confidential/ limits on assess outside the agency
(DLC) Prinary physical location of data: EPA Lab
(DST) Fora of data storage: Magnetic Disc
(OAC) Type of data access: EPA Software System: System Sane- CDC 6400,
Hardware- EPA
(CHG) Direct charge for n on-EPA use: NO
(UPDT) Frequency of data base master file up-date: Monthly
(RSS) Related EPA automated systems which use data base: None
(ROBEPA) Related EPA data bases used in conjunction with this data base
environmental Monitoring Systems Laboratory- Las Vegas Historical
Dosimetry (film badge)/ Thermoluminescent dosimetry
(RDB) Mon-EPA data bases used in conjunction with this data base: Rone
(CMP) Completion of for*: f Robert G. Patzer* OFC:
EPA/ORD/OMTS/EMSL-LVf AD: P.O. Box 15027, Las Vegas, NV 89114f
PH: (702) 798-2324*
(OF) Date of form completion: 12-13-82
(CIM) Contact natne(s): Patzer,R.€. ; Costa/C.F.
(COR) Contact organization: Nuclear Radiation Assessment Division
EMSL-LV
(ROR) Responsible Organization: Office of Research and
Development.Office of Monitoring Systems and Quality Assurance
959
-------
Accession Ho. 8213000515
(DQ) Date of Questionaire: 12-02-82
CHAM) Hame of Data Base of Model: Contract Laboratory Program Quality
Assurance
(ACR) Acronym of Data Base or Model: CLPQA
(MED) Media/Subject of Data Base or Model: Runoff: near Hazardous
Haste Sites j sediment ; soil ; solid waste ; surface water: near
Hazardous Haste Sites
(ABS) Abstract/Overview of Data Base or Model: Quality Assurance data
base for Superfund contract Laboratory Program, QA/QC
parameters for both organic and inorganic samples collected at
hazardous waste sites and analyzed under Contract Laboratory
Program. Current contents include surrogate and matrix spike
data as a function of contract, media, concentration, and
laboratory.
(CTC) CONTACTS: Subject matter Mike HOBSher, Lockhead Data Audits
Section Chief PTS 545-2633 ; Computer-related Hancy Fisher,
CSC Programmer/Analyst FTS 545-2665 ; EPA Office John M. Moore,
Quality Assurance Division/ EMSL-LV FTS 545-2132
(Dtp) Type of data collection or monitoring: Point source: Hazardous
Haste Site Sampling
(STA) Data Base status: Presently Operational/Ongoing
(MPP) Ron-pollutant parameters Included In the data base: Chemical
data } collection method or instrument ; location
(DS) Time period covered by data base: 06-82 TO 12-82
(TRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: Ongoing: daily
(HOB) number of observations in data base: 800(Estimated to date)
(HEI) Estimated annual increase of observations in data base: 2000
(IHF) Data base Includes: Raw data/observations
(HTS) Total number of stations or sources covered in data base: 200
(HCS) Ho. stations or sources currently originating/contributing data:
200
(HOF) Number of facilities covered in data base (source monitoring): 20
0
(GEO) Geographic coverage of data base: National
(LOC) Data elements Identifying location of station or source include:
Other- Region
(CDE) Pollutant identification data are: Oncoded
(LIN) Limitation/variation in data of which user should be aware: User
should be aware that comparisons can be affected by concentration
level, method of analysis, and media.
(DPR) Data collect./anal- procedures conform to ORD guidelines: YES
(AHL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: YES
(PRB) Precision: Partial: accuracy, yes j precision implicitly
calculated
(EOT) Bdittlng: YES, documented edits
(CBY) Data collected by: State agency ; regional office > EPA Lab j
contractor
(ABY) Data analyzed by: Contractor Lab
(IOL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Compliance or enforcement
960
-------
Accession No. 8213000515 (cont)
(PR2) Secondary purpose of data collection: None
(AW) Authorization for data collection: Yes, citation- CERCLA
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
NO
(REP) Form of available reports and outputs of data base: Machine-reada
ble ran data ; on-line computer terminal
(BOS) Run her of regular users of data base: 15
(HSR) Current regular users of data base: EPA Headquarters Offices-
OS ME R (OHER) ; EPA Regional Offices ; EPA Laboratories
(CNF) Confidentiality of data and Halts on access: Some data
confidential. Units on both within EPA and outside the Agency.
(DLC) Primary physical location of data: EPA Lab
(OST) Forn of data storage: Magnetic Disc
(DAC) Type of data access: EPA Software System: System Name- INFORM
Language, Hardware- PDP-11
(CHG) Direct charge for non-EPA use: Ho outside use/access permitted
(OPDT) Frequency of data base master file up-date: Weekly
(RSS) Related EPA automated systems which use data base: None
(RBBEPA) Related EPA data bases used in conjunction with this data base
Hone
(RDB) Hon-EPA data bases used in conjunction with this data base: None
(CMP) Completion of form: f John N. Moore* OFC: Quality Assurance
Division, EMSL-L?f AD: 944 E. Harmon, P.O. Box 15027, Las Vegas,
HV 89114f PH: (702) 798-2132f
(OF) Date of form completion: 12-14-82
(CUM) Contact name(s): Homsher,M. > Fischer,N. / Moore,J.M.
(COR) Contact organization: Quality Assurance Division, EMSL-LV
(ROR) Responsible Organization: Office of Research and
Development.Office of Monitoring Systems and Quality Assurance
961
-------
Accession Mo. 8411000521
fOQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Turbidity
(ACR) Acronym of Data Base or Model: TURB
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The data base includes
daily (Heather permitting) turbidity and supporting Meteorological
•easure*ents taken in the Research Triangle Park, N.C. fora
July 13, 1969 to the present. A sunphotometer is used to
directly Measure the. sun's intensity at 380 and 500 namometer
wavelengths*
(CTC) CONTACTS: Subject latter Dr. James Peterson / Director,
GMCC, ARL FTS 320-6811 ; Computer-related national Climatic
Center, Turbidity Section FTS 672-0683 ; EPA Office John
Rudislll, Meteorology & Assessment Div., EPA (919) 541-4551
(DTP) Type of data collection or monitoring: Ambient
(STA) Data Base status: Presently Operational/Ongoing
(NPP) Non-pollutant parameters included in the data base: Collection
method or instrument- sunphotometer ; location ; sampling date }
temperature ; wind direction ; wind velocity ; Dew point, sky
cover, visibility, turbidity
(DS) Time period covered by data base: 07-69 TO 02-83
CFRQ) Frequency of data collection or samplings Ongoing: daily-
Heather permitting
(MOB) Number of observations in data bases 13,000 (Estimated to date)
(MEI) Estimated annual increase of observations in data bases 1,000
(INF) Data base includes: Rau data/observations ; aggregate or summary
observations
(NTS) Total number of stations or sources covered in data bases 1
(NCS) No* stations or sources currently originating/contributing data:
1
(MOF) Number of facilities covered In data base (source monitoring): 0
(GEO) Geographic coverage of data base: Single county or smaller
location- one site
(LOC) Data elements identifying location of station or source Includes
State ; city ; latitude and longitude, OTM, or other coordinates
(FAC) Data elements identifying facility include: Other- site number
(LIM) Limitation/variation in data of which user should be aware: 1980'
1981 data instrument calibration needs verification
(DPR) Data collect./anal, procedures conform to ORD guidelines: NO
(ANL) Lab analysis based on EPA-approved or accepted methods? NO
(AUD) Lab Audits N/A: Data not based on laboratory analysis
(PRE) Precision: None available
(EOT) Edltting: Tes, undocumented
(CBY) Data collected bys EPA Lab- Environmental Protection Agency
(ABY) Data analyzed bys Other Federal Agency, National Oceanic fc
Atmospheric Administration
(IDL) Laboratory identifications NO
(PR1) Primary purpose of data collections Trend assessment
(PR2) Secondary purpose of data collection: Antlcipatory/researcn
(ACT) Authorization for data collections Yes, citation- Clean Air Act
/ Section 103 m
(OMB) Data collected/submitted using OMB-approved EPA reporting forms.
962
-------
Accession No. 8411000521 (cont)
10
(IV) Fora of available reports and outputs of data base: Publications-
•Atmospheric Turbidity Over Central North Carolina", Journal of
Applied Metorology Sporadic ; Printouts on request ;
machine-readable ran data ; on-line computer terminal
(MS) Number of regular users of data base: Unknown
(VSR) Current regular users of data base: Other Federal Agencies ;
Other- National Climatic Center
(CIF) Confidentiality of data and limits on access: None
(DLC) Primary physical location of data: Other- National Climatic
Center
(DST) Form of data storages Magnetic tape
(DAC) Type of data access: Other- User Software
(CflC) Direct charge for non-EPA use: YES
(OPDT) Frequency of data base master file up-date: Annually
(RSS) Related EPA automated systems which use data base: None
(ROBEPA) Related EPA data bases used in conjunction uith this data base
Hone
(ROB) Non-EPA data bases used in conjunction uith this data base: None
(CMP) Completion of form: #Joan H. Novafcf GFC: ORD, ESRL, MAD#
AD: MD-80, EPA, RTP, NC 27711f PH: (919) 541-544545*
(DF) Date of form completion: 09-09-81
(GIN) Contact name(s): Peterson/Dr.J. ; Rudisill,J.
(COR) Contact organization: Meteorology & Assessment Div./ EPA
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects Rese
963
-------
Accession Mo. 8412000526
(DQ) Date of Questionaire: 12-02-82
(•AM) Naae of Data Base of Model: Villaaette Valley Stream Survey
(ACR) Acronym of Data Base or Model: UVSS
(MED) Media/Subject of Data Base or Model: Sediaent ; Surface water-
Streaas
CABS) Abstract/Overview of Data Base or Model: Data base currently
contains fish coMunity information for 21 sites throughout the
Villaaette Valley/ Oregon* Data includes total nuabers, total
weights, relative coaaunity coaposition, nuabers per unit area,
and weight per unit area. Hater quality and physical habitat
characteristics, as well as, aicro Invertebrate data were
collected but are not yet stored on the CERL coaputer.
(CTC) COWTACTS: Subject Matter Jaaes D. Giattina, Senior Scientist
(503) 757-4900 } Computer-related Joanne C. Oshi.ro, Coaputer
Technician (503) 757-4813 ; EPA Office Corvailis Enivronaental
Research Lab., Freshwater Division (503) 757-4605
(DTP) Type of data collection or Monitoring: Combinations and other
(STA) Data Base status: Presently operational/ongoing
(6RP) Groups of substances represented in Data Base: Other- Mo
specific pollutants were aeasured- aost sites saapled were largely
affected by diffuse non-point source probleas, such as sediaent
runoff, in addition to possible cheaical pollutants.
(VPP) Non-pollutant paraaeters included in the data base: Biological
data ; cheaical data ; flow rates ; geographic subdivisions }
location y physical data ; sampling date ; site description }
teaperature
(DS) Tiae period covered by data base: 06-82 TO 09-82
(TRM) Termination of data collection: Has occurred 82-09
(FRQ) Frequency of data collection or sampling: Ongoing:aonthly
(•OB) Ruaber of observations in data base: 62(Actual to date)
(•SI) Estiaated annual Increase of observations in data base: H/A
(IMF) Data base includes: Raw data/observations ; aggregate or suaaaxy
observations
(ITS) Total number of stations or sources covered in data base: 22
(VCS) No. stations or sources currently originating/contributing data:
•/A
(•OF) Mumber of facilities covered in data base (source aonltoring): N/
A
(GEO) Geographic coverage of data base: Single state- Willamette
Valley, Oregon
(LOC) Data eleaents identifying location of station or source include:
State ; county ; latitude and longitude, OTM, or other
coordinates
(FAC) Data eleaents identifying facility Include: Not applicable
(LIM) Limitation/variation in data of which user should be aware: Data
was collected for valley bottoa streaas only and only during the
months of June, August, and Septeaber 1982.
(DPR) Data collect./anal, procedures conform to CRD guidelines: Mo,
but other documentation available for each of the following-
Sampling plan. Collection method. Analysis method, and QA
procedures
(AWL) Lab analysis based on EPA-approved or accepted aethods? YES
964
-------
Accession No. 8412000526 Ccont)
(100) Lab Audit: N/A:data not based on laboratory analysis
(PRE) Precision: Not included in data base, precision and accuracy
Measurements available from other sources
(EOT) Editting: Partial- All data entered into computer data based has
been checked against origional field data sheets and edited
appropriately.
(CBY) Data collected by: EPA Lab
(|B¥) Data analyzed by: EPA Lab
(IDL) Laboratory Identification: N/A
(PR1) Primary purpose of data collection: Anticipatory/research
(PR2) Secondary purpose of data collection: Special study
(iOT) Authorization for data collection: No. No specific requirement
for data collection; research initiated to aid In the development
of field assessment techniques.
(OMB) Data collected/ submit ted using OMB-approved EPA reporting forms:
HO
(REP) Form of available reports and outputs of data base: Printouts on
request ; on-line computer terminal
(IDS) Number of regular users of data base: 1
(BSR) Current regular users of data base: EPA Laboratories
(CIF) Confidentiality of data and limits on access: None
(BLC) Primary physical location of data: EPA Lab
fllST) Form of data storage: Magnetic tape ; origional fora/ hardcopy,
readings, etc.
flUC) Type of data access: Manually only ; commercially available
software ; EPA Software System- System name: INFORM, Cortex
Corporation, Hardware: POP 11/70
(CHG) Direct charge for non-EPA use: NO
(UPDT) Frequency of data base master file up-date: Weekly
(ESS) Related EPA automated systems which use data base: None
(8DBEPA) Related EPA data bases used in conjunction with this data base
(IDE) Non-EPA data bases used in conjunction with this data base: None
(C») Completion of form: i James D. Giattinaf OFC: Northrop
Environmental services, Corvallis Env. Res. Lab.f AD: 1350 SE
Goodnight Avenue, Corvallis, OR 97333f PH: (503) 757-4900f
(IF) Date of form completion: 12-14-82
(CIN) Contact name(s): Giattina,J.D. ; Oshiro,J.C.
CCOR) Contact organization: Corvallis Environmental Research Lab.,
Freshwater Division
(ROR) Responsible Organization: Office of Research and
Development.Off ice of Environmental Processes and Effects Rese
965
-------
Accession No. 8661262155
-------
Accession Mo. 8661262155 (cont)
be analyzed) } contractor* E. C. Jordan Co., Inc. (collected data
iron permittee for analysis)
(ABY) Data analyzed by: Contractor, E. C. Jordan Co., Inc. (analyzed
data; permittee analyzed saaples)
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Development of regulations
or standards
(PR2) Secondary purpose of data collection: None
(HUT) Authorization for data collection: Yes, citation- Clean Water
Act of 1977, P.L. 95-217, Section 308
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
NO
(REP) Form of available reports and outputs of data base: Other-
Printouts on request if EPA-EGD authorization received
(•OS) Number of regular users of data base: 2
(OSR) Current regular users of data base: EPA Headquarters Offices,
Effluent Guidelines Division ; Other, E. C. Jordan Co., Inc.
(CUF) Confidentiality of data and limits on access: Some data
confidential, limits on access both within EPA and outside the
agency
(DLC) Primary physical location of data: Contractor
(DST) Form of data storage: Other, Magnetic Diskette
(DAC) Type of data access: Manually only
(CHC) Direct charge for non-EPA use: No outside use/access permitted
without EPA Authorization
(OPDT) Frequency of data base master file up-date: Other, as necessary
to correct data
(CMP) Completion of form: fRobert E. Handy, Jr.f OFC: E. C. Jordan
Co., Inc.* AD: P. 0. Box 7050, DTS; Portland ME 04112* PH: (207)
775-5401*
(DP) Date of for* completion: 02-03-83
(•NAT) Number of substances represented in data base: 2
(ICAS) Number of CAS registry numbers in data base: 0
(NAT) Substances represented in data base:
BOD5 TSSS
(CUM) Contact name(s): Warren,H.C. ? Ryan,D.J. > Dellinger,R.W.
(COR) Contact organization: Effluent Guidelines Division
(ROR) Responsible organization: Office of Hater.Office of Hater
Regulations and Standards.Effluent Guidelines Divisi
967
-------
Accession Ho. 9015000901
(DQ) Date of Questlonaire: 12-02-82
(HAM) Name of Data Base of Model: Rational Pollutant Discharge
Elimination System (HPDES) Discharge Monitoring Re
CACR) Acronym of Data Base or Model: HPDES DMR
(MED) Media/Subject of Data Base or Model: Effluents Municipal and
nonmunlcipal
(ABS) Abstract/Overvieu of Data Base or Model: The data base consists
of the results of the Discharge Monitoring Reports that are
required as part of the Rational Pollutant Discharge Elimination
System (RPDES) permit. The data is manually maintained for the
major municipal and nonmunlcipal dischargers in Maine* and
computerized for Massachusetts/ Hew Hampshire and Rhode Island*
is and automated system.
(CTC) COIfTACTS: Subject matter Larry Brill (617) 223-5330; EPA
Office Enforcement Dlvls
(DTP) Type of data collection or monitoring: Point source data
collection effluent
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CtfA ;11
conventional uater
(HPP) Non-pollutant parameters included in the data base: Compliance
data ;Discharge points >Temperature
(DS) Time period covered by data base: 01-01*75 TO 12-31-82
(TRM) Termination of data collection: Rot anticipated
(FRQ) Frequency of data collection or sampling: quarterly ;semi
annually ;annually ;as needed ?0ther Monthly: most of data
(ROB) Number of observations in data base: 200000.(Estimated) manual,
60,000 automated
(RED Estimated annual increase of observations in data base: 60000.
(IMF) Data base includes: Summary aggregate observations
(ITS) Total number of stations or sources covered in data base: 432.
(HCS) Mo. stations or sources currently originating/contributing data:
432.
(HOF) Rumber of facilities covered in data base (source monitoring): 43
2.
(CEO) Geographic coverage of data base: Selected federal region Region
I }Geographic region Rev England
(LOC) Data elements identifying location of station or source include:
State ;County jCity ;Town/township ;Street address ;ProJect
identifier
(FAC) Data elements identifying facility Include: Plant facility name
/Plant location ;Parent corp location ^Street address ; SIC code
;NPDES ^program Identifier
(CDE) Pollutant identification data are: coded
(LIM) Limitation/variation In data of which user should be aware: Param
eters and frequency vary by permittee, numbers of facilities and
observations are for major dischargers only, minor dischargers
represent a data base of approximately equal size.
(DPR) Data collect./anal, procedures conform to CRD guidelines: ORD
Guidelines
(AML) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory for 85%.
968
-------
Accession Mo. 9015000901 (cont)
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected bys Self reporting Permittees ^Regional office
Region I
(ABY) Data analyzed by: Self reporting Pernittees
Regional office Region I
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Compliance or enforcement
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500, sections 301, 308 and 402 (Clean Hater Act-CMA)
(ONB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Quarterly Non-Compliance Report
(MUS) Number of regular users of data base: 80-100
(OSR) current regular users of data base: EPA headquarter offices
Office of Enforcement
EPA regional offices
EPA laboratories
States
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Microfich/film, computer
(DAC) Type of data access: automated for 1 year of data
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Semi-annually
(ROBEPA) Related EPA data bases used in conjunction yith this data base
Permit Compliance System (PCS)
(RDB) Non-EPA data bases used in conjunction with this data base: Maine
-automated Discharge Monitoring Report (ONR) file.
(CMP) Completion of form:
Larry Brill
OFC: EPA/Region I/Enforcement Division
AD: JFK Building Boston, MA 02203
PH: (617) 223-5330
(DF) Date of form completion: 01-20-82
(•MAT) Number of substances represented in data base: 140
(•CAS) Number of CAS registry numbers in data base: 129
(MAT) substances represented in data base:
l,l,l-trichloroethane<71-55- l,2-dichloropropylene<563-54-2>
6> l,2-diphenylhydrazine<122-66-7>
1,1,2,2,-tetrachloroethane 1,2-trans-dichloroethylene
<79-34-5> <156-60-5>
l,l,2-trichloroethane<79-00-5> l,3-dichlorobenzene<541-73-l>
l/l-dichloroethane<75-34-3> l,4-dichlorobenzene<106-46-7>
1,1-dlchlo ro e thy lene<7 5-35- 4> 2, 4, 6-tr ichlorophenoK 8 8-06-2>
l,2,4,-trichlorobenzene<120-82-l> 2,4,7,8-tetrachlorodibenzo-p-
l,2-dichlorobenzene<95-50-l> dioxin (tcdd)
l,2-dichloroethane<107-06-2> 2,4-dichlorophenol<120-83-2>
l,2-dichloropropane<78-87-5> 2,4-dimethylphenol<105-67-9>
969
-------
Accession Ho* 9015000901
(cont)
2, 4-dini trophenoK 51-2 8-5>
2, 4-dinitrotoluene<121-14-2>
2,6-dlnitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-nitrophenol<88-75-5>
3, 3 •-dlchlorobenzidine<91-94-l>
3, 4-benzof luoranthene<205-99-2>
4,4"-ddd(p,p'tde>
4,4'-dde
4,4'-ddt<50-29-3>
4,6-dinltro-o-cresol<534-52-l>
4-broMophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
acenaphthy lene<208-96- 8>
acidity
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
alkalinity
anthracene<120-12-7>
an ti«ony<7 440-36-0 >
ar senic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
ben2idine<92-87-5>
benzo
benzo(a)pyrene<50-32-8>
benzo(g,h, i)perylene<191-24-2>
ben20
beryll iu»<7440-41-7>
bhc (llndane)-gaaBa<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<3 19-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)«ethane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl)ether
<39638-32-9>
bis( 2-ethy IhexyDphthalate
bis€chloro«ethyl)eth«r<542-88-l>
bro«oaethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cad»iu»<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<5?-74-9>
chlorobenzene
chlorodibroao*ethane<124-48-l>
chloroethane<75-00-3>
chlorofora<67-66-3>
chloro«cthane<74-87-3>
chro«iu»<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-^>
di-n-octyl phthalate<117-84-0>
d ibenzo(a,h)anthracene<53-70-3>
dichlorobro>o>ethane<75-27-4>
dlchlorodifluoroietliane<7S-71-8>
dichloroaethane<75-09-2>
dleldrin<60-57-l>
diethy1 phthalate<84-66-2>
dUethyl phthalate<131-ll-3>
dissolved oxygen
dissolved solids
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<332!3-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fecal colifor*
fluoranthene<206-44-0>
fluorene< 86-7 3-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloro«thane<67-72-l>
indeno (l/2^3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
»ercury<7439-97-6>
n-nitrosodi-n-propyla«ine
<621-64-7>
n-nitrosodi»ethyla«ine<62-75-9>
n-nitrosodiphenyla»ine<86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nitrobenzene<98-95-3>
nitrogen<7727-37-9>
oil and grease
oxygen demand
p-chloto-»-cresol<59-50-7>
PH
970
-------
Accession No. 9015000901 (cont)
pcb-1016 (arochlor 1016) phenol<108-95-2>
u<}2674-ll-2> phosphorus<7723-14-0>
pcb-1221 (arochlor 1221) pyrene<129-00-0>
v seleniu«<7782-49-2>
pcb-1232 (arochlor 1232) silver<7440-22-4>
<1114l-16-5> suspended solids
pcb-1242 (arochlor 1242) tetrachloroethylene<127-18-4>
<53469-21-9> thailiu»<7440-28-0>
pcb-1248 (arochlor 1248) toluene<108-88-3>
<12672-29-6> toxaphene<8001-35-2>
pcb-1254 (arochlor 1254) tribroaonethane<75-25-2>
<11097-69-l> trichloroethylene<79-01-6>
pcb-1260 (arochlor 1260) trichlorofluororaethane<75-69-4>
<11096-82-5> vinyl chloride<75-01-4>
pentachlorophenol<87-86-5> zlnc<7440-66-6>
phenanthrene<85-01-8>
(CAS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1? 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 7727-37-9; 59-50-7;
12674-11-2; 11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6;
11097-69-1; 11096-82-5; 87-86-5; 85-01-8; 108-95-2; 7723-14-0;
129-00-0; 7782-49-2; 7440-22-4; 127-18-4; 7440-28-0; 108-88-3;
8001-35-2; 75-25-2; 79-01-6; 75-69-4; 75-01-4; 7440-66-6
(CUM) Contact naae(s): Brill,L.
(COR) Contact organization: Enforcement Division Region I
(KOR) Responsible Organization: Region I*Administrative Services
Division.
971
-------
Accession No. 9016000001
(DQ) Date of Questionaire: 12-02-82
(RAN) Have of Data Base of Model: Tetrachloroethylene Honitorlng Study
(ACR) Acronym of Data Base or Model: PCC
(MED) Media/Subject of Data Base or Model: Drinking water
(ABS) Abstract/Overview of Data Base or Model: Gathering water quality
data (pH, corrosivity, alkalinity, hardness), pipe data (length,
diameter and age), location and tetrachloroethylene
concentration* Data is used to perfor* trend analyses and
correlations*
(CTC) CONTACTS: Subject Batter David Chin (617) 223-4600 ;
Computer-related Steve Matt
(DTP) Type of data collection or monitoring: Point source data
collection from home taps. Hater main locations and "dead ends."
(STA) Data Base status: Discontinued
(NPP) Non-pollutant parameters included in the data base: Chemical
data ^Concentration measures ^Location ;Sampling date
(OS) Time period covered by data base: 01-01-80 TO 09-30-80
(TRM) Termination of data collection: Occurred 09/30/80
(PRQ) Frequency of data collection or sampling: Not applicable
(NOB) lumber of observations in data base: 800.(Estimated)
(NEI) Estimated annual Increase of observations in data base: 0
(INF) Data base Includes: Ray data/observations
(NTS) Total number of stations or sources covered in data base: 400.
(NCS) No* stations or sources currently originating/contributing data:
0
(HOP) Number of facilities covered in data base (source monitoring): (N
/A.)
(CEO) Geographic coverage of data base: Selected federal region Region
I ?Geographic region Hen England
(LOC) Data elements identifying location of station or source include:
State ;Town/township ;Street address ;City
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant Identification data are: STORET parameter codes
(LIM) Limitation/variation in data of which user should be aware: Data
is Indicative of New England region only. Due to many
variables only specific pipe correlation could be generated*
(DPR) Data collect./anal, procedures conform to CRD guidelines: Samplin
g plan documented ;Collection method documented ^Analysis method
document
(AML) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Data is not based on laboratory analysis.
(PRE) Precision: Precision and accuracy estimates exist for some
measurements. Measurements were assumed or estimated for pH,
temperature, alkalinity and hardness. All other measurements were
precise.
(EOT) Editting: No known edit procedures used.
(CBY) Data collected by: State agency five water supply sections of
New England state agencies excluding New Hampshire
(ABY) Data analyzed by: State agency five water supply sections of New
England state agencies, excluding New Hampshire.
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Trend assessment
972
-------
Accession No* 9016000001. (cont)
(AUT) Authorization for data collection: Statutory authorization is P
L 95-190, Section 1442(2b), (Safe Drinking Mater Act-SDHA)
(OMB) Data collected/submitted using OMB-approved EPA reporting for»s:
QQ
(REP) For* of available reports and outputs of data base: Printouts on
request
(IDS) Hunter of regular users of data base: 1
(OSR) Current regular users of data base: EPA Regional Offices:
Region I
(C1F) Confidentiality of data and Units on access: No Units on
access to data
(DLC) Primary physical location of data: Regional office and state
agency
(DST) Fora of data storage: Magnetic tape
(DAC) Type of data access: Commercial softnare HYLBUR ;EPA softuare
TCE-Nonitoring Study ; EPA hardware IBM 370/168
(CHC) Direct charge for non-EPA use: Yes D
(OPDT) Frequency of data base master file up-date: None (terminatedinch
(CMP) Completion of form:
David Chin
OFC: EPA/Region I/Hater Supply Branch, Water Management Div.
AD: JFK Bldg. Ra 2113 Boston, MA 02203
PH: (617) 223-4600
(OF) Date of form completion: 01-26-83
(IMAT) Number of substances represented in data base: 12-02-82 1
(1CAS) Number of CAS registry numbers in data base: 12-02-82 1
(MAT) Substances represented in data base:
tetrachoroethylene<127-18-4>
(CAS) CAS registry numbers of substances included in data base: 127-18-
(CIM) Contact name(s): Chln,D. ; watt,S. ; I/R«
(ROR) Responsible Organization: Region I.Administrative Services
Division.
973
-------
Accession Mo. 9018000901
(DQ) Date of Questionaire: 12-02-82
(RAM) Name of Data Base of Models Priority Pollutants
(ACR) Acronym of Data Base or Model: PRTYPOLS
(MED) Media/Subject of Data Base or Model: Sediment ;Surface water
River
(ABS) Abstract/Overview of Data Base or Model: River, water, and
sediment samples were analyzed for priority pollutants* The water
samples were reported in ail11grans per liter* Sedi»ent
samples were reported in Milligrams per kilogram.
(CTC) CORTACTS: Subject Batter Charles Porfert (617)861-6700 }
EPA Office William Hals
(DTP) type of data collection or monitoring: Ambient data collection
(STA) Data Base status; Operational/ongoing
(GRP) Croups of substances represented in Data Bases 129 307 CtfA
(HPP) Non-pollutant parameters included in the data base: Location
;Sampling date ;Site description
(OS) Time period covered by data base: 04-01-80 to 12-31-82
(TRW) Termination of data collection: Mot anticipated
(FRQ) Frequency of data collection or sampling* Other one time per
site
(MOB) Number of observations in data base: 617 (samples(Estimated)
(NED Estimated annual Increase of observations in data base: 50*
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 177.
(MCS) No. stations or sources currently originating/contributing data:
0.
(HOT) Number of facilities covered in data base (source monitoring): QA procedures documented
(AML) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is unknown-contractors do analysis.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Edittings Edit procedures used but undocumented.
(CSV) Data collected by: Regional office Region I, Surveillance and
Analysis Division .••••«
(ABf) Data analyzed by: EPA lab Region I, Surveillance and Analysis
Division
Contractor lab as used by Surveillance and Analysis Laboratory
(IDL) Laboratory identifications NO
CPRi) Primary purpose of data collections Risk assessment
(AOf) Authorization for data collections Ho statutory requirements
974
-------
Accession No. 9018000901
(cont)
Data collection requirement is the measuring of trends in the
concentrations of priority pollutants in sediment and surface
vater.
(OMB) Data collected/submit ted using OMB-approved EPA reporting forms:
lo QQ
(IEP) Form of available reports and outputs of data base: Unpublished
reports "Ambient Toxic Monitoring" in a given river
(105) Number of regular users of data base: 8
(DSD) Current regular users of data base: EPA headquarter offices
Monitoring and Data Support Division; Effluent Guidelines
Division
EPA regional offices
States
(CIF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: EPA lab
(DSt) Form of data storage: Original form (hardcopy, readings)
(OIC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(OPOT) Frequency of data base master file up-date: Other Samples are
collected once at each location
(CMP) Completion of form:
Charles porfert
OFC: EPA/Region I/Surveillance and Analysis Division
ID: 60 tfestvieu St. Lexington, MA 02173
PH: (617) 861-6700
(DF) Date of form completion: 01-18-83
(NUT) Number of substances represented in data base: 129
(ICiS) Number of CAS registry numbers in data base: 127
(NIT) Substances represented in data base:
1/1,1- tr ichlor oe thane< 71-55-
6>
1,1,2,2,-tetrachloroethane
<79-34-5>
l,l,2-trichloroethane<79-00-5>
l/l-dichloroethane<75-34-3>
l/l-dichloroethylene<75-35-4>
l,2,4,-trichlorobenzene<120-82-l>
l,2-dichlorobenzene<95-50-l>
l/2-dichloroethane<107-06-2>
l,2-dichloropropane<78-87-5>
l,2-diphenylhydrazine<122-66-7>
1,2-trans-dichloroethylene
<156-60-5>
lf 3-dichlorobenzene< 541-73-l>
l,3-dichloropropylene< 542-75-6>
l/4-dichlorobenzene<106-46-7>
2,4,6-trichlorophenol<88-06-2>
2, 4,7,8- tetrachlor odibenzo-p-
dioxin (tcdd)
2,4-dichlorophenoKl 20-83-2>
2,4-dimethylphenol<105-67-9>
2,4-dinitrophenol<51-28-5>
2^4-dinitrotoluene<121-14-2>
2,6-dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-nitrophenol<88-75-5>
3,3'-dichlorobenzidine<91-94-l>
3^ 4-benzofluoranthene<205-99-2>
4r4*-ddd(p/p*tde)
4,4*-dde
4,4"-ddt<50-29-3>
4,6-dinitro-o-cresol<534-52-l>
4-bromophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
975
-------
Accession Mo. 9018000901
(cont)
aldrin< 309-0 0-2>
anthracene<120-12-7>
anti»ony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
b«nzidlne<92-87-5>
benzo( a) an thracene<56- 55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h, i)perylene<191-24-2>
benzo(lc)fluoranthene<207-08-9>
b«rylliu»<7440-4l-7>
bhc (lindane)-gaM8< 58-89- 9>
bhc-alpha< 31 9* 84-6>
bhe-beta<319-85-7>
bhc-delta<319-86-8>
bis( 2-chloroethoxy)aethane
bis(2-chloroethyl)ether
bisC2-chloroisopropyl)«th«r
<39638-32-9>
bls(2-ethylh«xyl)phthalat«
bis(chloroM«thyl)«th«r<542-88-l>
bro«o««than«<74-83-9>
butyl benzyl phthalate<85-68-7>
cad»luX7440-43-9>
carbon tetrachlori
chlordane<57-74-9>
chlorobenzene< 10 8-90-7>
chlorodibro«o««than«<124-48-l>
chlcroet ha ne<7 5-00-3 >
chlorofor»<67-66-3>
chloro»«thane<74-87-3>
chro«luB<7440-47-3>
chrysene<218-01-9>
copper <7440-50-8>
cyanid«<57-12-5>
dl-n-butyl phthalat«<84-74-2>
dl-n-octyl phthalate<117-84-0>
dlbenzo( a, h) anthracen«<53-70-3>
dichlorobro«o««thane<75-27-4>
dlchlorodlfluoro»ethan«<75-71-8>
dlcbloro«ethaD«<75-09-2>
dleldrln<60-57-l>
die thy I phthalate<84-66-2>
dleethyl phthalate<131-ll-3>
endosulfan sulfate<1031-07-8>
endosu If an-a lpha< 959-9 8- 8>
endosulf an-be t a<3321 3-65-9>
endrin aldehyde<7421-93-4>
ethylbenzene
f luoranthene<206-44-0>
f luor ene<86-7 3-7>
heptachlor epoxide< 10 24-57- 3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlorobutadlene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
h«xachloroethane<67-72-l>
Indeno (1^2,3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
«ercury<7439-97-6>
n-nltrosodl-n-propylaalne
<621-64-7>
n-nltroaodl«ethylaBln«<62-75-9>
n-nltrosodiphenyla«lne<86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nl tr obenzene< 98-95- 3>
p-chloro-«-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arocblor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
pyrene<129-00-0>
sel«niue<7782-49-2>
sllver<7440-22-4>
tetrachloro«thylene<127-18-4>
thalliu»<7440-28-0>
toluene <108-88-3>
toxaphene<8001-35-2>
trlbro«o«ethane<75-25-2>
trichloroethylene<79-01-6>
trlchlorofluoro»ethane<75-69-4>
vinyl chloride<75-01-4>
zinc<7440-66-6>
976
-------
Accession No. 901800090) (cont)
(CAS) CAS registry lumbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 122-66-7* 156-60-5; 541-73-1; 542-75-6;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7* 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 7782-49-2;
7440-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2;
79-01-6; 75-69-4; 75-01-4; 7440-66-6
(CIM) Contact naae(s): Porfert,C.; Malsh/H.
(ROR) Responsible Organization: Region I.Environmental Services
Division.
977
-------
Accession Mo. 9018000902
(DQ) Date of Questionaire: 12-02-82
(RAN) Ra*e of Data Base of Model: Region I Source Test File
(ACR) Acronyn of Data Base or Model: SORTST
(HBO) Media/Subject of Data Base or Model: Air ;Emissions Ren Source
Perforsanee standards (MSPS) ;Emissions State Imp 1 em Emissions
Rational Emission Standards for Hazardous Air Pollutants (MESHAP)
;Eilssions Prevention of Significant Deterioration (PSD)
(ABS) Abstract/Overview of Data Base or Model: Results of Air Emission
tests with associated process and operating data at the ti»e of
the testing are the contents of this data base.
(CTC) COWTACTS: Subject Batter John M. Carlson (617) 861-6700 ;
EPA Office Donald P. Po
(DTP) Type of data collection or monitoring: Co»bination/0ther point
source and process and operating data pertinent to test
(STA) Data Base status: Operational/ongoing
(CRP) Groups of substances represented in Data Base: 5 HESRAPS ;7
criteria RAAQS
(RPP) Don-pollutant parameters included in the data base: Collection
•ethod Concentration Measures ;Flon rates ^Location ; Production
levels ;Sampling date jSite description ;Temperature ;
Test/analysis »ethod ^Treatment devices ;Yolume/mass measures
(DS) Time period covered by data base: 01-01-73 to 12-03-82
(TRM) Termination of data collection: Rot anticipated
(PRO) Frequency of data collection or sampling: as needed
(ROB) number of observations in data base: 230.(Estimated)
(HEI) Estimated annual increase of observations in data base: 40*
(IRF) Data base includes: Raw data/observations ;Summary aggregate
observations ;Reference data/citations
CRTS) Total number of stations or sources covered in data base: 120.
(HCS) Mo. stations or sources currently originating/contributing data:
(R/A.)
(ROT) number of facilities covered In data base (source monitoring): 55
(CEO) Geographic coverage of data base: Selected federal region Region
I ^Geographic region Mew England
(LOC) Data elements identifying location of station or source Include:
State >City jstreet address jProject Identifier
Plant location ^Parent corp name ;Street address
(COB) Pollutant identification data are: Uncoded
(LDO Limitation/variation in data of which user should be aware: Rone
(DPR) Data collect./anal. procedures conform to ORD guidelines: Samplln
g plan documented Collection method documented /Analysis method
document QA procedures documented
(AML) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory for SO* for these with
audit samples, no samples for total suspended particulates (TSP).
(PRE) Precision: Precision and accuracy estimates are not available
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Self reporting
(ABf) Data analyzed by: Self reporting primarily analysis
State agency secondary analysis, verification
978
-------
Accession No. 9018000902 (cont)
Regional office secondary analysis, verification
EPA lab secondary analysis, verification
Contractor as hired by sources
(IDL) Laboratory identification: YES
CPR1) Primary purpose of data collection: Compliance or enforcement
(A0T) Authorization for data collection: Statutory authorization is P
L 88-206 as amended. Sections 111 & 114 (Clean Air Act-CAA);
State Implementation Plans (SIPS)
(OMB) Data collected/submit ted using OMB-approved EPA reporting forms:
QQ
(SEP) Form of available reports and outputs of data base: none
(IDS) Number of regular users of data base: 2 offices
WSR) Current regular users of data base: EPA regional offices
States
(Cm?) Confidentiality of data and limits on access: Limits on outside
access for some data
ftUC) primary physical location of data: EPA lab
(DST) Form of data storage: Original form (hardcopy, readings)
(0AC) Type of data access: Manually
(CiC) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other as test files
completed
(CMP) Completion of form:
John M. Carlson
OFC: EPA/Region I/Surveillance and Analysis Division/
Air Section
AD: 60 Westview St. Lexington, MA 02173
PH: (617) 861-6700
(OF) Date of form completion: 01-18-83
(IMAT) Number of substances represented in data base: 4
(ICAS) Number of CAS registry numbers in data base: 3
(NAT) Substances represented in data base:
nltrogendioxide<10102-44-0> total suspended participates
sulfur dioxide<7446-09-5> vinyl chloride<75-01-4>
(CAS) CAS registry numbers of substances included in data base: 10102-4
4-0; 7446-09-5; 75-01-4
(CM) Contact name(s): Carlson,J.M. ; Porteous,D.P.
(ROR) Responsible Organization: Region I.Environmental Services
Division.
979
-------
Accession Ho. 9024000001
Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 40.
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(•OF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEQ) Geographic coverage of data base: Geographic region Region II
(Neu York and New Jersey only)
(LOC) Data elements identifying location of station or source include:
State ;County ^Coordinates latitude/longitude
(FAC) Data elements identifying facility Include: N/A
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: Time
variations: during the first year (1966) samples were taken
weekly to bi-weekly, then quarterly, and then, in about
1968-1974, only irregular sampling was done. No audit samples
were performed to test laboratory performance standards.
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates are not available
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division Laboratory, Region II
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division Laboratory, Region II
(IDL) Laboratory identification: YES
(PAD Primary purpose of data collection: Trend assessment
(PR2) Secondary purpose of data collection: Special study
(AOT) Authorization for data collection: No statutory requirement:
980
-------
Accession Ho. 9024000001 (cont)
Data collection requirement is foilOH up on pre-EPA water
sampling network.
(Offi) Data collected/submitted using QMS-approved EPA reporting forms:
QQ
(Iff) Fora of available reports and outputs of data base: Printouts on
request
Machine-readable raw data
On-line computer
(IBS) Number of regular users of data base: 1 office
(USR) Current regular users of data base: EPA regional offices
(Cm?) Confidentiality of data and limits on access: Mo limits on
access to data
(DLC) Primary physical location of data: HCC/IBM
(DST) Form of data storage: Magnetic disc
(D4C) Type of data access: EPA software STORET (Storage and Retrieval
of Hater Quality Data) M1DS:5303000101 ;BPA hardware IBM 370
Computer System
(CBG) Direct charge for non-EPA use: yes
(IPOT) Frequency of data base master file up-date: Other survey
discontinued in 1974
(Cm?) Completion of form:
George Hossa
OFC: EPA/Region II/Planning and Management Div.
AD: 26 Federal Plaza NY, NY 10278
PR: (212) 264-9850
(DF) Date of fora completion: 02-08-83
(MAT) Number of substances represented in data base: 18
OCAS) Number of CAS registry numbers in data base: 9
OUT) Substances represented in data base:
acidity mercury<7439-97-6>
alkalinity nickel<7440-02-0>
cadmium<7440-43-9> nitrogen<7727-37-9>
chromium<7440-47-3> oil and grease
copper<7440-50-8> oxygen demand
dissolved oxygen pH
dissolved solids phosphorus<7723-14-0>
fecal coliform suspended solids
leac<7439-92-l> xinc<7440-66-6>
(CAS) CAS registry numbers of substances Included in data base: 7440-43
-9; 7440-47-3; 7440-50-8; 7439-92-1; 7439-97-6; 7440-02-0;
7727-37-9; 7723-14-0; 7440-66-6
(CW) Contact name(s): Brezenskl,F. ; 0'Hare,Tom ; I1VR.
(BOB) Responsible Organization: Region II.Assistant Regional
Administrator for Policy.
981
-------
Accession Ho* 9024000002
(DQ) Date of Questionaire: 12-02-82
(VAN) name of Data Bas« of Model: State 208 Agencies Data
(ACR) Acronym of Data Base or Model: Rone
(MED) Media/Subject of Data Base or Model: Surface water estuaries and
rivers
(ABS) Abstract/Overview of Data Base or Model: Hater quality analysis
(with a small amount of effluent data taken at a few industries)
of estuaries and rivers in Region II on physical parameters,
bacteriological parameters, nutrients, and some heavy metals. This
data can be retrieved from STORET (Storage and Retrieval of
Hater Quality Data) by unit agency code REGII 208.
(CTC) CONTACTS: Subject matter J. Delama/M. Savedoff (212)
264-0958/(212) ; Computer- related Tom O'Rare (212)
264-9850 ; EPA Office Region II
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Discontinued
(GRP) Croups of substances represented in Data Base: 11 conventional
water
(HPP) Ion-pollutant parameters included in the data base: Location
^Physical data ;Sampling date jSite description ^Temperature
(DS) Time period covered by data base: 04-01-75 TO 07-30-78
(TRM) Termination of data collection: Occurred 07/30/78
(FRQ) Frequency of data collection or sampling: Other special surveys
for varying and limited sampling periods.
(•OB) lumber of observations in data base: 100000.(Estimated)
(•El) Estimated annual Increase of observations in data base: (R/A.)
(IRF) Data base includes: Raw data/observations ;Summary aggregate
observations
(VTS) Total number of stations or sources covered in data base: 850.
(RCS) Mo. stations or sources currently originating/contributing data:
0.
(•OF) Rumber of facilities covered in data base (source monitoring): (•
/A.)
(CEO) Geographic coverage of data base: Selected federal region Region
II
(LOC) Data elements Identifying location of station or source include:
State ;County ^Coordinates Latitude/Longitude
(FAC) Data elements identifying facility include: Plant facility name
iPlant location ;«PDES
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: As
stated above, surveys are varied with respect to sampling time and
locations, fery few audit samples performed.
(AIL) Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precisions precision and accuracy estimates are not available
(EOT) Editting: Edit procedures used but undocumented.
(CBf) Data collected by: Contractor various contractors collected this
data.
(ABT) Data analyzed by: Contractor lab various contractors analyzed
this data (analyses spot-check by EPA-Edison labs)
(IDL) Laboratory identification: HO
(PR1) Primary purpose of data collection: Special study
982
-------
Accession No. 9024000002 (cont)
(AUT) Authorization for data collections Statutory authorization is P
L 92-500 as amended, Section 208 (Clean Water Act-CifA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
request
Machine-readable raw data
On-line computer
(IDS) Number of regular users of data base: 20
(USR) Current regular users of data base: EPA regional offices
Freedom of Information Requests
: 26 Federal Plaza MY, MY 10278
PH: (212) 264-9850
(DF) Date of form completion: 02-08-83
(•MAT) Number of substances represented in data base: 11
(ICAS) Number of CAS registry numbers in data base: 2
(MAT) Substances represented in data base:
acidity oil and grease
alkalinity oxygen demand
dissolved oxygen Pj „,,.,, *- AN
dissolved solids phosphorus<7723-14-0>
fecal coliform suspended solids
nitrogen<7727-37-9> K™.
(CAS) CAS registry numbers of substances included in data base.
•g. 7723-14-0
(CiM) Contact name(s): Delama,J. ; 0*Hare,Tom ; «'*•
(ROR) Responsible Organization: Region II.Assistant Regional
Administrator for Policy.
983
-------
Accession Do. 9024000005
(DQ) Date of Questionaire: 12-02-82
(MAM) lame of Data Base of Model: Hater Enforcement Regional System
(ACR) Acronym of Data Base or Model: HERS
(MED) Media/Subject of Data Base or Model: Effluents Industrial,
•unicipal and federal facilities
(ABS) Abstract/Overview of Data Base or Model: Rational Pollutant
Discharge Elimination System (UPDBS) permittees and permit
applicants in Region II regulated under the Clean Water Act.
The data base contains facility Identification information (such as
name, facility/ location/ SIC codes)/ milestone dates in the
permit development process/ compliance action events (such as
reports required by the permit and associated dates/ inspections
performed/ enforcement actions and referrals) influent and
effluent limit dates/ and reported dates.
(CTC) COBIACTSI Subject matter Steve Rubin (212) 264-9850;
Computer-related Steve Rubin (212) 264-9850 /
(DTP) Type of data collection or monitoring: Point source data
collection industrial/ municipal and federal facilities
(STA) Data Base status: Operational/ongoing
(•PP) Ion-pollutant parameters included in the data base: Collection
method /Compliance data /Concentration measures /Discharge points /
Pi on rates /Geographic subdivision /Inspection data /Location /
Political subdivisions /Salinity /Sampling date /Temperature /
Treatment devices /conductivity /gallons distilled /discharge
duration / velocity
(OS) Time period covered by data base: 03-01-77 TO 01-31-83
(TRM) Termination of data collection: Mot anticipated
(PRO) Frequency of data collection or sampling: Meekly /monthly /Other
varies by parameter In the reported data
(•OB) lumber of observations in data base: 600000.(Estimated)
(•CI) Estimated annual Increase of observations in data base: 150000.
(IIP) Data base Includes: Summary aggregate observations
(ITS) Total number of stations or sources covered in data base: 7500.
(MCS) Mo. stations or sources currently originating/contributing data:
5000.
(•OP) lumber of facilities covered in data base (source monitoring): 50
00.
(CEO) Geographic coverage of data base: Selected federal region Region
II
(LOC) Data elements identifying location of station or source include:
State /County /City /Town/township /Coordinates Latitude and
longitude / Project identifier
(PAC) Data elements identifying facility include: Plant facility name
/Plant location /SIC code >HPDBS
(CDS) Pollutant identification data are: Storet parameter
Other coding scheme
(LIN) Limitation/variation in data of which user should be aware: Since
summary data is from permittees/ quality assurance methods are
questionable.
(AIR.) Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates are not available
(EOT) Editting: Edit procedures used and documented.
984
-------
Accession No. 9024000005 (cont)
(CBY) Data collected by: Self reporting Discharge Monitoring Reports
(99%) ;Regional office enforcement &
(ABY) Data analyzed by: Self reporting
State agency
Regional office Region II
EPA lab Regional Lab
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Trend assessment
(IUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Sections 301, 308, &402 (Clean Hater
Act-CUA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0073
(REP) Form of available reports and outputs of data base: Quarterly/»on
thly Hater Enforcement reports. Regional System Users Manual
Printouts on request
Microfilm
(•OS) Number of regular users of data base: 50
(OSR) Current regular users of data base: EPA headquarter offices
Office of Hater Enforcement
EPA Region II
EPA laboratories
States
Freedom of Information requests
(CIF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: NCC/IBM
(OST) Form of data storage: Magnetic tape ^Magnetic disc
(DAC) Type of data access: EPA software HERS 3 components: Status of
Permit Development (facility ID), Status of Permit Compliance,
Local Effluent Data System (parameter data) MIDS:9024000905
;EPA hardware IBM 370/168 ; retrieval package
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Other 4 components
of VERS are updated monthly; 1 is updated bi-ueekly.
(RSS) Related EPA automated systems which use data base: Permit
Compliance System (PCS); Facilities Index System (FINDS)
(ROBEPA) Related EPA data bases used in conjunction with this data base
Penit Compliance System (PCS); Facilities Index Systems (FINDS)
(RDB) Non-EPA data bases used in conjunction Hith this data base: Hen
fork Department of Environmental Conservation State Pollutant
Discharge Elimination System (SPDES) data base
(ODB) Other pertinent non-EPA data bases: New York Department of
Environmental Conservation's Industrial Chemical Survey; New
Jersey Department of Environmental Protection's Manifest System;
Delaware River Basin Commission's Industrial Exotic Haste Survey
(CMP) completion of form:
George Nossa
OFC: EPA/Region II/lnformation Systems Branch
AD: 26 Federal Plaza NY, NY 10278
PH: (212) 264-9850
985
-------
Accession No. 9024000005
(cont)
(OF) Date of form completion: 02-08-83
(RMAT) Runber of substances represented in data base; 132
2,2,dibromo-3-nitrilopropionamide
2*4,6-trichlorophenol<88-06-2>
acidity
alglcides
alkalinity
alumlnum<7 429-90-5>
ammonia<7664-41-7>
antimony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
barium<7440-39-3>
baroid §2 |7
ben*ene<71-43-2>
benzidine<92-87-5>
benzisothiozote
beryllium<7440-41-7>
bismuth co»pounds<7440-69-9>
boron compounds<7440-42-8>
bro»ine<7726-95-6>
bro»odichlorOBethane<75-27-4>
cad«lum<7440-43-9>
calcium
carbofuran
carbon tetrachlorlde<56-23-5>
chloral<75-87-6>
chloride
chlorinated hydrocarbons
chlorinated organics
chlorioe< 7782-50-5>
chlorobenzene<108-90-7>
chlorodibr omomethane<124-48-1>
chlorofor»<67-66-3>
chro»iu^7440-47-3>
cob al t<7 440- 48- 4>
color
copper<7440-50-8>
cyanid«<57-12-5>
cyclohexlaaine
diceyldimethyl auoniua chloride
dichlorobenzene<25321-22-6>
dichloro«ethane<75-09-2>
dichlorovinyl dimethyl phosphate
dicyclopentadine<77-73-6>
dlethylhexyl phthalate
dissolved oxygen
dissolved solids
dithiocarbonates
ethylbenzene<100-41-4>
ethylene dichlorlde<107-06-2>
fecal colifora
ferric cyanide
fluorides
fluoroborates
formaldehyde<50-00-0>
gold
gross alpha
gross beta
hardness
hexamethyl benzene
hydrazine<302-01-2>
hydrocarbons
iodine
iodine 129<15046-84-l>
iron<7439-89-6>
isotopic gamma
lead<7439-92-l>
magnesium
•anganese<7439-96-5>
mercury<7439-97-6>
methylene bis-thiocycanate
mirex<2385-'85-5>
molybdenum and compounds
<7439-98-7>
nickel<7440-02-0>
nitrates/nitrites
nitrobenzene<98-95-3>
nitrofurans
nitrogen<7727-37-9>
odors
oil and grease
ortho-phosphate
oxygen demand
PH
palladium,total
pesticides
phenol<108-95-2>
phosphorus<7723-14-0>
phthalate esters
phthalic acid<88-99-3>
platinum .
polybrominated biphenyls (PBBs)
polybrominated dlphenyl oxides
polychlorinated biphenyls
986
-------
Accession Mo. 9024000005 (cont)
seleniu»<7782-49-2> total organic carbon (TOO
settleable solids total phosphates
silica total strontium
silver<7440-22-4> total telluriu
sodlun nitrite<7632-00-0> tribro«o>ethane<75-25-2>
sodiu«<7440-23-5> trichloroethane<25323-89-l>
strontium 90<10098-97-2> trichloroethylene<79-01-6>
styrene<100-42-5> tritiu»<10028-17-8>
sulfates turbidity
sulfldes uranil
sulfite uranium 235<15117-96-l>
surfactants uraniua 238<7440-61-1>
suspended solids uraniua<7440-61-l>
tetrachloroethylene<127-18-4> vanadlu*<7440-62-2>
thalliua<7440-28-0> vinyl acetat«
tin vinyl chloride<75-01-4>
titaniu«<7440-32-6> volatile acids
toluene<108-88-3> xylene<1330-20-7>
total kjeldahl nitrogen zinc<7440-66-6>
(CIS) CAS registry nuabers of substances included in data base: 120-82-
1; 88-06-2; 7429-90-5; 7664-41-7; 7440-36-Oj 7440-38-2;
1332-21-4; 7440-39-3; 71-43-2; 92-87-5; 7440-41-7; 7440-69-9;
7440-42-8; 7726-95-6; 75-27-4; 7440-43-9; 1563-66-2; 56-23-5;
75-87-6; 7782-50-5; 108-90-7; 124-48-1; 67-66-3; 7440-47-3;
7440-48-4; 7440-50-8; 57-12-5; 25321-22-6; 75-09-2; 77-73-6;
100-41-4; 107-06-2; 50-00-0; 302-01-2; 15046-84-11 7439-89-6;
7439-92-1; 7439-96-5; 7439-97-6; 2385-85-5; 7439-98-7;
7440-02-0; 98-95-3; 7727-37-9; 108-95-2; 7723-14-0; 88-99-3;
7440-09-7; 7782-49-2; 7440-22-4; 7632-00-0; 7440-23-5; 10098-97-2;
100-42-5; 127-18-4; 7440-28-0; 7440-32-6; 108-88-3; 75-25-2;
25323-89-1; 79-01-6; 10028-17-8; 15117-96-1; 7440-61-1; 7440-61-1;
7440-62-2; 108-05-4; 75-01-4; 1330-20-7; 7440-66-6
(CM) Contact naae(s): Rub in, S. ; Rub in, S. ; Ludin,C.
(KOR) Responsible Organization: Region II.Assistant Regional
Administrator for Policy.
987
-------
Accession Ho. 9026000101
(OQ) Date of Questionaire: 12-02-82
CHAM) Kane of Data Base of Model: Carbon Monoxide Special Study
(JLCR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Air ;Mobile source
emissions
(ABS) Abstract/Overview of Data Base or Model: This is a regional
study to correct deficiencies in carbon monoxide network and to
determine hotspots and extent of carbon Monoxide problem.
(CTC) COMTACTS: Subject Batter Ray Werner (212) 264-2517; EPA
Office Ray Werner (212) 264-2517
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Discontinued
(CRP) Croups of substances represented in Data Base: 7 criteria HAAQS
(Carbon Monoxide)
(HPP) Non-pollutant parameters included in the data base: Chemical
data ^Concentration measures ^Exposure data ;Geographic subdivision
; Location ;Population density ;Sampling date ;Site description ;
Hind direction ;Hind velocity ;temperature
(OS) Time period covered by data base: 10-01-79 TO 10-30-80
CTRM) Termination of data collection: 04/30/81
(PRO) Frequency of data collection or sampling: hourly ;dally ;weekly
(HOB) Rumber of observations in data base: 56000.(Estimated)
(IHP) Data base Includes: Raw data/observations ;Summary aggregate
observations ;Reference data/citations
(HTS) Total number of stations or sources covered in data base: 38*
(HCS) Ho. stations or sources currently originating/contributing data:
0.
(HOP) Humber of facilities covered in data base (source monitoring): 0.
(GBO) Geographic coverage of data base: Geographic region upstate Hew
York, Hew York City, and Hew Jersey.
(LOC) Data elements identifying location of station or source includes
State ;County ;City ;Town/tounship ;Street address
(PAC) Data elements identifying facility include: H/A
(CDE) pollutant Identification data are: Oncoded
(LDO Limitation/variation in data of which user should be aware: This
data base is made up of data from three studies, with three months
of continuous sampling in each.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplln
g plan documented Collection method documented ;Analysis method
document QA procedures documented
(AWL) Lab analysis based on BPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory for 85%.
(PRE) Precision: Precision and accuracy estimates exist for all
measurements
(EOT) Editting: Ho known edit procedures exist.
(CBY) Data collected by: Contractor Hew York State Department of
Transportation; Environmental Research and Technology; HAPORA
(ABY) Data analyzed by: Contractor Hew York State Department of
Transportation; Environmental Research and Technology; HAPORA
(IDL) Laboratory identification: YES
(AOT) Authorization for data collection: Ho statutory requirement:
Data collection requirement is to determine "notspots" and
988
-------
Accession No* 9026000101 (cont)
correct deficiencies in carbon monoxide network
(0») Data collected/sub»itted using OMB-approved EPA reporting forms:
QQ
(Iff) Fora of available reports and outputs of data base: Unpublished
reports carbon monoxide hotspot study for Men jersey, upstate Hen
fork. New York City report anticipated by Fall, 1983.
(IIS} Number of regular users of data base: 50 or aore
(VSR) Current regular users of data bases EPA headquarter offices
Office of Air Quality Planning and Standards*
SPA regional offices
States
(Cm?) Confidentiality of data and limits on access: Mo limits on
access to data
0>LC) Primary physical location of data: Regional office
(BST) Form of data storage: Original fora (hardeopy, readings)
(DiC) Type of data access: Manually
(CMC) Direct charge for non-EPA use: yes
(SPOT) Frequency of data base master file up-date: other one time
only-report being written
(ODB) Other pertinent non-EPA data bases: Staten Island Benzine Study
(CMP) Completion of fora:
Ray tferner
OFC: EPA/Region II/Air and Hazardous Materials Division
AD: 26 Federal Plaza Men York, NY 10007
PH: (212) 264-2517
(DP) Date of fora completion: 01-14-83
(MAT) Number of substances represented in data base: 1
(ICIS) Number of CAS registry numbers in data base: 1
OAT) Substances represented in data base:
carbon aonoxide<630-08-0>
(CAS) CAS registry numbers of substances included in data base: 630-08-
0
(CIH) Contact naae(s): tferner/R. ; Verne r/R.
(tOR) Responsible Organization: Region II.Air and Haste Manageaent
Division*
989
-------
Accession Mo. 9026000102
-------
Accession Ho. 9026000102 Ccont)
(MUS) number of regular users of data base: 50
(OSR) Current regular users of data base: EPA headquarter offices
Office of Air Quality Planning and Standards
EPA regional offices
States
(CMF) Confidentiality of data and limits on access: Ho limits on
access to data
(DLC) Primary physical location of data: State agency
(DSt) Fora of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Other data base
update terminated
(CHP) Couplet ion of for*:
Debbie Broae
OFC: EPA/Region II/Air and Hazardous Materials Division
AD: 26 Federal Plaza Room 900 Hen York, HV 10007
PH: (212) 264-2517
(DF) Date of fora completion: 01-14-83
(•NAT) Number of substances represented in data base: 1
(NAT) Substances represented in data base:
total suspendedparticulates
(CNN) Contact name(s): Kerr,G.
(COR) Contact organization: Air and Hazardous Materials Division/
Region II
(ROR) Responsible Organization: Region II.Air and Haste Management
Division.
991
-------
Accession Mo. 9027000101
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Federal Reporting Data System
(ACR) Acronym of Data Base or Model: FRDS
(NED) Media/Subject of Data Base or Model: Drinking water
(ABS) Abstract/Overview of Data Base or Model: FRDS contains
identification and statistical summary information for each public
water supply (PUS). Inventory data includes capacity, source
information, monitoring requirements, data pertaining to
infringements of EPA standards by a specific PHS, data pertaining
to EPA authorized exceptions to the standard which are granted
to a specific PHS, and information pertaining to actions taken
against a PHS.
(CTC) COBTACTS: Subject matter Jaime A. Referent* (212) 264-1800
; Computer-related J Computer-related John Baglivi (212)
264-9580; EPA Office Jaime A. Reference (212) 264-1355
(DTP) Type of data collection or monitoring: Combination/Other Public
Hater Supply inventory and monitoring and surveillance.
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 22 drinking Hater
standards
(WPP) Ron-pollutant parameters included in the data base: Compliance
data ;Inspectiondata ;Location ^Physical data jPolitleal
subdivisions Population density ^Production levels *Sampling date
;Test/analysis method ; Treatment devices
(DS) Time period covered by data base: 10-01-78 TO 09-30-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: quarterly ;annually
(NOB) Number of observations in data base: 590000 observations
(per(Estimated)
(INF) Data base includes: Raw data/observations ;Summary aggregate
observations ^Reference data/citations
(NTS) Total number of stations or sources covered in data base: 65,115
Approx. (Region II) over 400,000 (nationally).)
(NCS) Ho. stations or sources currently originating/contributing data:
Approx. 63,285
(HOF) Number of facilities covered in data base (source monitoring): 21
,705 (public water supplies.)
(CEO) Geographic coverage of data base: Selected federal region Region
II
(LOG) Data elements Identifying location of station or source includes
State jCounty ;Clty ;Town/township jStreet address ^Coordinates
Latitude/long!tu Project Identifier
(FAC) Data elements identifying facility include: Plant facility name
;Plant location jStreet address ;SCC ^Program identifier
(CDE) Pollutant identification data are: Other coding scheme
(LIH) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplln
g plan documented ^Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
992
-------
Accession No. 9027000101 (cont)
included in data base
(EOT) Editting: Edit procedures used and docunented.
(CBY) Data collected by: Self reporting Primary responsibility for
both aonitoring and violation data co Local agency Soaetlmes
County Dept. of Health collects for purveyor. ; State agency
has primacy, receives data from purveyor. ;Regional office
Occasionally state Dept, of Environmental Protection collect data.
occasionally regional office samples where lore sophisticated
equipment is necessary. Contractor lab for permittee (purveyor) ;
Contractor for permittee (purveyor)
(ABY) Data analyzed by: EPA lab Surveillance and Analysis Lab; and
occasionally Cincinnati lab
EPA/state certified labs
(IOL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Inventory
(AOT) Authorization for data collection: Statutory authorization is P
L 93-523, Sections 1412, 1415, 1416, 1421 and 1422. (Safe Drinking
Water Act of 1974-SDWA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0155
(REP) Form of available reports and outputs of data base: Printouts on
request
Microfilm
Machine-readable ran data
On-line computer
(MUS) Number of regular users of data base: 2 offices
(OSR) Current regular users of data base: EPA headquarter offices
Office of Drinking Hater
EPA regional offices
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: NCC/IBM
(DST) Form of data storage: Magnetic Disc: national rftDS system
Original form: data from FY 1978
(DAC) Type of data access: Commercial software System 2000 ;EPA
hardware IBM 370 ^Manually: data from F
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Quarterly
(RDBEPA) Related EPA data bases used in conjunction with this data base
Model State Information System (MSIS)
(CMP) Completion of form:
Jaice A. Referente
OFC: EPA/Region II/Uater Division
AD: 26 Federal Plaza New York, NY 10278
PH: (212) 264-1800
(DF) Date of form completion: 03-23-83
(NMAT) Number of substances represented in data base: 21
(HCAS) Number of CAS registry numbers in data base: 17
993
-------
Accession No. 9027000101 (cont)
(MAT) Substances represented in data base:
2f4-dichlorophenoxyacetic «ethoxychlor<72-43-5>
add (2,4-d)<94-75-7> Microbiology colifora bacteria
arsenic<7440-38-2> nitrate<14797-55-8>
bariu»<7440-39-3> radiua 226<13982-63-3>
cad«iuaK7440-43-9> radiua 228<15262-20-1>
chro«iu«<7440-47-3> seleniua<7782-49-2>
endrin<72-20-8> silver<7440-22-4>
gross alpha silvex<93-72-l>
lead<7439-92-l> toxaphene<8001-35-2>
lindane<58-89-9> turbidity
nannade beta trihalo«cthane
•ercury<7439-97-6>
(CAS) CAS registry numbers of substances included in data base: 94*75-7
; 7440-38-2; 7440-39-3; 7440-43-9; 7440-47-3; 72-20-8;
7439-92-1; 58-89-9; 7439-97-6; 72-43-5; 14797-55-8;
13982-63-3; 15262-20-1; 7782-49-2; 7440-22-4; 93-72-1; 8001-35-2
(CNM) contact nane(s): Referente,J.A. ; Bagllui,J.;
Referente/J.A.
(ROR) Responsible Organization: Region II.Hater Manageaent Division.
994
-------
Accession No. 9028000511
(DQ) Date of Questionaire: 12*02-82
(NAM) Name of Data Base of Model: Niagara Frontier - Lake Erie
(ACR) Acronym of Data Base or Model: None
(MEO) Media/Subject of Data Base or Model: Sediment
(ABS) Abstract/Overview of Data Base or Model: The data base contains
priority pollutant values for about 40 stations in Lake Erie and
the Niagara River. Sediment was only examined and not the water
column.
(CIC) CONTACTS: Subject matter Roland B. Hemmett (201) 321-6687 ;
Computer-related George Hossa (212) 264-9850 ; EPA Office
Roland B. Hemmett, Environmental Services Div. (201) 321-6687
(DTP) Type of data collection or monitoring: Ambient
(STA) Data Base status: Presently Operational/Ongoing
(6RP) Groups of substances represented in Data Base: 129 307 CWA ;
Other- Particle size. Volatile solids
(NPP) Non-pollutant parameters Included in the data base: Precipitation
; Sampling date } Site description
(OS) Time period covered by data base: 06-82 TO 09-82
(TRM) Termination of data collection: Not applicable
(FRQ) Frequency of data collection or sampling: Ongoing: as needed
(NOB) Number of observations in data base: 5000(Estlmated to date)
(NEI) Estimated annual increase of observations in data base: N/A
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 40
(NCS) No. stations or sources currently originating/contributing data:
40
(NQF) Number of facilities covered In data base (source monitoring): 0
(GEQ) Geographic coverage of data base: International
(LOC) Data elements Identifying location of station or source include:
State / latitude and longitude, OTM, or other coordinates
(FAC) Data elements identifying facility include: Not applicable
(CDE) Pollutant identification data are: coded, storet parameter codes
(DPR) Data collect./anal, procedures conform to ORD guidelines: No,
but other documentation available for each of the following:
sampling plan, collection method, analysis method, and QA
procedures
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: YES
(PRE) Precision: Not included in data base, precision and accuracy
measurements available form other sources
(EOT) Fdltting: YES, documented edits
(CBY) Data collected by: Regional Office ; EPA Lab ; Contractor Lab >
EPA Headquarters
(ABY) Data analyzed by: EPA Lab ; Contractor Lab
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Special Study
(PR2) Secondary purpose of data collections None
(ADT) Authorization for data collection: YES, citation: PL92-500
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
NO
(REP) Form of available reports and outputs of data base: Printouts on
request ; Files
995
-------
Accession No. 9028000511
(cont)
(NOS) Number of regular users of data base: 10
(OSR) Current regular users of data base: EPA Regional Offices ; EPA
Laboratories ; states
(CNF) Confidentiality of data and Halts on access: Hone
(DLC) Primary physical location of data: Regional Office
(DST) For» of data storage: Magnetic Disc
(DAC) Type of data access: EPA Software System: System Name- STORE!,
Hardware- IBM/168
(CHG) Direct charge for non-EPA use: YES
(OPDT) Freguendy of data base master file up-date: Unknown
(RSS) Related EPA automated systems which use data base: Unknown
(RDBEPA) Related EPA data bases used in conjunction with this data base
Hone
(ROB) Non-EPA data bases used in conjunction with this data base: None
(CMP) Completion of fora: I Randy Braunf OFC: U.S.E.P.A., Region II,
Edison, N.J.f AD: Hoodbridge Ave., Edison, N.J. 08837f PH:
(201) 32l-6692f
(DF) Date of fora completion: 01-11*83
(RMAT) Number of substances represented in data base: 129
(NCAS) Number of CAS registry numbers in data base: 0128
(MAT) Substances represented in data base:
Acenaphthene <83-32-9>
Acenaphthylene <208-96-8>
Acrolein <107-02-8>
Acrylonitrile <107-13-1>
Aldrin <309-00-2>
Anthracene <120-12-7>
Antimony <7440-36-0>
Arsenic <7440-38-2>
Asbestos <1332-21-4>
BHC-. Alpha. <319-84-6>
BHC-.Beta. <319-85-7>
BBC (llndane)-. Gamma. <58-89-9>
BHC-. Delta. <319-86-8>
Benzene <71-43-2>
Benzidlne <92-87-5>
Ben2o( a) anthracene <56-55-3>
3, 4-Benzofluoranthene <205-99-2>
Benzo(k) fluoranthene <207-08-9>
Benzo
BenzoCalpyrene <50-32-8>
Beryllium <7440-41-7>
Bis (2- chloroethoxy) me thane
Bis(2-chloroethyl)ether
Bis(2-chloroisopropyl) ether
<39638-32-9>
Bis (chloromethyl) ether
<542-88-l>
Bis(2-ethylhexyl)phthalate
Bromomethane <74-83-9>
4-Bromophenyl phenyl ether
<101-55-3>
Butyl benzyl phthalate <85-68-7>
Cadmium <7440-43-9>
Carbon tetrachloride <56-23-5>
Chlordane <57-74-9>
Chlorobenzene <108-90-7>
Chiorodibromomethane <124-48-l>
Chloroethane <75-00-3>
2-chloroethylvinyl ether
<110-75-8>
Chloroform <67-66-3>
p-Chloro-m-cresol <59-50-7>
Chloromethane <74-87-3>
2-Chloronaphthalene <91-58-7>
2-Chlorophenol <95-57-8>
4-Chlorophenyl phenyl ether
<7005-72-3>
Chromium <7440-47-3>
Chrysene <218-01-9>
Copper <7440-50-8>
Cyanide <57-12-5>
4,4''-DDD(p,p*-TDE) <72-54-8>
4,4--DDB
4,4'-DDT <50-29-3>
DlbenzoCa,h]anthracene <53-70-3>
Dl-n-butyl phthalate <84-74-2>
1,2-Dichlorobenzene <95-50-l>
1,3-Dlchlorobenzene <541-73-l>
1,4-Dichlorobenzene <106-46-7>
996
-------
Accession No. 9028000511
(cont)
3/3'- Dichlorobenzidine <91-94-l>
Dichlorobronomethane <75-27-4>
Dichlorodifluoromethane <75-71-8>
1,1-Dichloroethane <75-34-3>
1,2-Dichloroethane <107-06-2>
1,1-Dichloroethylene <75-35-4>
1,2-trans-Dichloroethylene
<156-60-5>
Dichloronethane <75-09-2>
2,4-Dichlorophenol <120-83-2>
1,2-Dichloropropane <78-87-5>
1,2-Dichloropropylene <563-54-2>
Dieldrin <60-57-l>
Die thy 1 ph thai ate <84-66-2>
2,4- Diaethylphenol <105-67-9>
Dimethyl phthalate <131-ll-3>
4,6-Dinitro-o-cresol <534-52-l>
2,4-Dinitrophenol <51-28-5>
2,4-Dinitrotoluene <121-14-2>
2,6-Dlnitrotoiuene <606-20-2>
Di-n-octyl phthalate <117-84-0>
1,2-Diphenylhydrazine <122-66-7>
Endosulfan-.Alpha. <959-98-8>
Endosulfan-.Beta. <33213-65-9>
Sndosulfan sulfate <1031-07-8>
Endrin <72-20-8>
Endrin aldehyde <7421-93-4>
Ethylbenzene <100-41-4>
Fluoranthene <206-44-0>
Fluorene <86-73-7>
Heptachlor <76-44-8>
Heptachlor epoxide <1024-57-3>
Hexachlorebenzene <118-74-l>
Hexachlorobutadiene <87-68-3>
Hexachlorocyclopentadiene
<77-47-4>
Hexachloroethane <67-72-l>
Indeno
Isophorone <78-59-l>
Lead <7439-92-l>
Hercury <7439-97-6>
Naphthalene <91-20-3>
iickel <7440-02-0>
2-Nitrophenol <88-75-5>
4-Nitrophenol <100-02-7>
N-Nitrosodiaethylaiine <62-75-9>
N-Nitrosodiphenylaaine <86-30-6>
N-Hitrosodi-n- propylaaine
<621-64-7>
Pentachlorophenol <87-86-5>
Phenanthrene <85-01-8>
Phenol <108-95-2>
PCB-1016 (Arochlor 1016)
<12674-ll-2>
PCB-1221 (Arochlor 1221)
<11104-28-2>
PCB-1232 (Arochor 1232)
PCB-1242 (Arochlor 1242)
<53469-21-9>
PCB-1248 (Arochlor 1248)
<12672-29-6>
PCB-1254 (Arochlor 1254)
<11097-69-l>
PCB-1260 (Arochlor 1260)
<11096-82-5>
Pyrene <129-00-0>
Selenium <7782-49-2>
Silver <7440-22-4>
2,4/7/8-fetrachlorodibenzo-p-
dioxio (TCDD)
If If2f2-T etrachloroethane
<79-34-5>
Tetrachloroethylene <127-18-4>
Thallium <7440-28-0>
Toluene <108-88-3>
Toxaphene <8001-35-2>
Tribroaocethane <75-25-2>
1,2f4-Trichlorobenzene <120-82-l>
1,1,1-Trichloroethane <71-55-6
1,1,2-Trichloroethane <79-00-5>
Trichloroethylene <79-01-6>
Trichlorofluoronethane <75-69-4>
2,4,6- Trichlorophenol
<88-06-2>
Vinyl chloride <75-01-4>
Zinc <7440-66-6>
Nitrobenzene <98-95-3>
(CAS) CAS registry numbers of substances Included in data base: 83-32-9
} 208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-21 1332-21-4; 319-84-6; 319-85-7; 58-89-9; 319-86-8;
71-43-2; 92-87-5; 56-55-3; 205-99-2; 207-08-9; 191-24-2;
50-32-8; 7440-41-7; 111-91-1; 111-44-4; 39638-32-9; 542-88-1;
117-81-7; 74-83-9; 101-55-3; 85-68-7; 7440-43-9; 56-23-5;
57-74-9. 108-90-7; 124-48-1; 75-00-3; 110-75-8; 67-66-3J 59-50-7;
74-87-3; 91-58-7; 95-57-8; 7005-72-3; 7440-47-3; 218-01-9;
997
-------
Accession Ho* 9028000511 (cont)
7440-50-8; 57-12-5; 72-54-8; 72-55-9; 50-29-3; 53-70-3;
84-74-2; 95-50-1; 541-73-1; 106-46-7.; 91-94-1; 75-27-4; 75-71-8;
75-34-3; 107-06-2; 75-35-4; 156-60-5; 75-09-2; 120-83-2; 78-87-5;
563-54-2; 60-57-1; 84-66-2; 105-67-9; 131-11-3; 534-52-1; 51-28-5;
121-14-2; 606-20-2; 117-84-0; 122-66-7; 959-98-8; 33213-65-9;
1031-07-8; 72-20-8; 7421-93-4; 100-41-4; 206-44-0; 86-73-7;
76-44-8; 1024-57-3; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 91-20-3; 7440-02-0;
98-95-3; 88-75-5; 100-02-7; 62-75-9; 86-30-6; 621-64-7;
87-86-5; 85-01-8; 108-95-2; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 129-00-0;
7782-49-2; 7440-22-4; 79-34-5; 127-18-4; 7440-28-0; 108-88-3;
8001-35-2; 75-25-2; 120-82-1; 71-55-6; 79-00-5; 79-01-6;
75-69-4; 88-06-2; 75-01-4; 7440-66-6
CCHM) Contact naae(s): He»*ett,R.B. ; Nossa,G. ; Heuett,R.B.
(COR) Contact organization: Environmental Services Division
(ROR) Responsible Organization: Region II.Environmental Services
Division.
998
-------
Accession No. 9028000512
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Arthur Kill
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Sediment ; Surface water:
River
(ABS) Abstract/overview of Data Base or Model: 20 Stations on the
Arthur Kill were sampled. Samples uere collected of both the
sediment and water column. Sediment samples uere grams and water
column stations were composited over depth. Classical parameters
and priority pollutants were analyzed for.
(CTC) CONTACTS: Subject matter Roland B. Hemmett (201) 321- 6687 ;
Computer-related George Nossa (212) 264-9850 } EPA Office
Roland B. Hemmett (201) 321-6687
(DTP) Type of data collection or monitoring: Anbient
(STA) Data Base status: Presently Operational/Ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CWA ;
Other- TSS, Chloride, Oil & Grease, Phenol, Total Coliform,
Fecal Coliform, Cyanide, TOC, Temperature, Dissolved Oxygen
(NPP) Non-pollutant parameters included in the data base: Physical
data ; precipitation ; sampling date ; site description ?
temperature
(DS) Time period covered by data base: 04-82 TO 11-82
(TRM) Termination of data collection: Has occurred: 82-11
(FRQ) Frequency of data collection or sampling: Other- Two times only
(HOB) Number of observations in data base: 7000(Estimated to date)
(NED Estimated annual increase of observations in data base: N/A
(INF) Data base includes: Raw data/observations
(ITS) Total number of stations or sources covered in data base: 20
(NCS) No. stations or sources currently originating/contributing data:
20
(NOF) Number of facilities covered in data base (source monitoring): N/
A
(GEO) Geographic coverage of data base: Single county or smaller
location: one River the Arthur Kill
(LOG) Data elements identifying location of station or source include:
Latitude and longitude,, UTM, or other coordinates
(FAC) Data elements identifying facility include: Not applicable
(CDS) Pollutant identification data are: Coded, storet parameter codes
(DPR) Data collect./anal, procedures conform to CRD guidelines: YES
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Partial 90%
(PRE) Precision: Not included in data base, precision end accuracy
measurements available from other sources
(EDT) Editting: YES, documented edits
(CBY) Data collected by: Regional Office of EPA
(ABY) Data analyzed by: EPA Lab
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Special study
(PR2) Secondary purpose of data collection: Trend assessment
(AOT) Authorization for data collection: YES, citation: PL92-500,
Section 106 and 305
(OMB) Data col lee ted/submit ted using OMB-approved EPA reporting forms:
999
-------
Accession Ho. 9028000512
(cont)
NO
(REP) Form of available reports and outputs of data base: Unpublished
reports: Arthur Kill Hater Quality Survey ; Printouts on request
(MOS) Number of regular users of data base: 10
(USR) Current regular users of data base: EPA Regional Offices ; EPA
Laboratories ; other Federal Agencies ; States ? Other- ISC
(CNF) Confidentiality of data and Halts on access: None
(DLC) Primary physical location of data: Regional Office
(DST) Fora of data storage: Magnetic Disc ; Origional Fora, Hardcopy,
Readings, etc.
(DAC) Type of data access: EPA Software System: System Name- STORET,
Hardware- IBM 370/168
(CHG) Direct charge for non-EPA use: YES
(UPDT) Frequency of data base master file up-date: Unknown
(RSS) Related EPA automated systems which use data base: Unknown
(RDBEPA) Related EPA data bases used in conjunction with this data base
None
(ROB) Non-EPA data bases used in conjunction with this data base: None
(CMP) Completion of for*: f Randy Braunf OFC: U.S.E.P.A., Region II,
Edison, N.J.f AD; Woodbridge Ave., Edison, N.J. 088371 PH:
(201) 321-6692f
(OF) Date of for* completion: 12-28-82
(NMAT) NuBber of substances represented in data base: 138
(IfCAS) Number of CAS registry numbers in data base: 0128
(MAT) Substances represented in data base:
Acenaphthene < 83-32- 9>
Acenaphthylene <208-96-8>
Acrolein <107-02-8>
Acrylonitrile <107-13-1>
Aldrin <309-00-2>
Anthracene <120-12-7>
Antimony <7440-36-0>
Arsenic <7440-38-2>
Asbestos <1332-21-4>
BHC-. Alpha. <319-84-6>
BHC-«Beta. <319-85-7>
BHC (lindane)-.Ga««a. <58-89-9>
BHC-.Oelta. <319-86-8>
Benzene <71-43-2>
Benzldlne <92-87-5>
Benzo( a) anthracene <56-55-3>
3,4-Benzofluoranthene <205-99-2>
Benzo(k) fluoranthene <207-08-9>
Benzo(g,h, Operylene <191-24-2>
BenzoCalpyrene <50-32-8>
Beryllium <7 44 0-41-7 >
Bis (2- chloroethoxy) me thane
Bis (chloromethyl)ether
<542-88-l>
Bis(2-ethylhexyl)phthalate
Bis(2-chloroethyl) ether
Bis(2-chloroisopropyl) ether
<39638-32-9>
Bromomethane <74-83-9>
4-Broaophenyl phenyl ether
<101-55-3>
Butyl benzyl phthalate <85-68-7>
Cadmium <7440-43-9>
Carbon tetrachlorlde
Chlordane <57-74-9>
Chlorobenzene <108-90-7>
Chlorodibromomethane <124-48-l>
Chi or oe thane <75-00-3>
2-chloroethyl vinyl ether
<110-75-8>
Chloroform <67-66-3>
p-Chloro-m-cresol <59-50-7>
Chi or OB ethane <74-87-3>
2-Chloronaphthalene <91-58-7>
2-Chlorophenol <95-57-8>
4-Chlorophenyl phenyl ether
<7005-72-3>
Chromium <7440-47-3>
Chrysene <218-01-9>
Copper <7440-50-8>
Cyanide <57-12-5>
1000
-------
Accession No. 9028000512
(cont)
4,4'-DDD(p,p'-TDE) <72-54-8>
4,4--DDE(p,p*-nDX) <72-55-9>
4,4--DDT <50-29-3>
Dibcnzotaxhlanthracene <53-70-3>
Di-n-butyl phthalate <84-74-2>
It2-Dichlorobenzene <95-50-l>
1,3-Dichlorobenzene <541-73-l>
1,4-Dichlorobenzene <106-46-7>
3,3*- Dichlorobenzidine <91-94-l>
Dichlorobronone thane <75-27-4>
Dichlorodifluoroaethane <75-71-8>
1,1-Dichloroethane <75-34-3>
1,2-Dichloroethane <107-06-2>
1/1-Dichloroethylene <75-35-4>
It2-trans-Dichloroethylen«
<156-60-5>
Dichloroaethane <75-09-2>
2,4-Dichlorophenol <120-83-2>
1,2-Dichloropropane <78-87-5>
1/2-Dichloropropylene <563-54-2>
Dieldrin <60-57-l>
Dlethyl phthalate <84-66-2>
2,4- Dimethylphenol <105-67-9>
Dimethyl phthalate <131-ll-3>
4/6-Dinitro-o-cresol <534-52-l>
2/4-Dinitrophenol <51-28-5>
2,4-Dinltrotoluene <121-14-2>
2/6-Dlnitrotoluene <606-20-2>
Di-n-octyl phthalate <117-84-0>
1,2-Diphenylhydrazlne <122-66-7>
Endosulfan-.Alpha. <959-98-8>
Endosulfan-.Beta. <33213-65-9>
Sndosulfan sulfate <1031-07-8>
Endrln <72-20-8>
Endcin aldehyde <7421-93-4>
Ethylbenzene <100-41-4>
Fluoranthene <206-44-0>
Fluorene <86-73-7>
Heptachlor <76-44-8>
Heptachlor epoxide <1024-57-3>
Hexachlorobenzene
Hexachlorobutadiene <87-68-3>
Hexachlorocyclopentadlene
<77-47-4>
flexachloroethane <67-72-l>
Indeno (l,2,3-cd)pyrene <193-39-5>
Isophorone <78-59-l>
Lead <7439-92-l>
Mercury <7439-97-6>
naphthalene <91-20-3>
Nickel <7440-02-0>
Nitrobenzene <98-95-3>
2 -N it ro phenol <88-75-5>
4-Nitrophenol <100-02-7>
N-Nitrosodiaethyla«lne <62-75-9>
N-Nitrosodiphenylanine <86-30-6>
N-Nitrosodi-n- propylaaine
<621-64-7>
Pentachlorophenol <87-86-5>
Phenanthrene <85-01-8>
Phenol <108-95-2>
PCB-1016 (Arochlor 1016)
<12674-ll-2>
PCB-1221 < Arochlor 1221)
<11104-28-2>
PCB-1232 (Arochor 1232)
PCB-1242 (Arochlor 1242)
<53469-21-9>
PCB-1248 (Arochlor 1248)
<12672-29-6>
PCB-1254 (Arochlor 1254)
<11097-69-l>
PCB-1260 (Arochlor 1260)
<11096-82-5>
Pyrene <129-00-0>
Seleniun <7782-49-2>
Silver <7440-22-4>
2,4,7, 8-Tetrachlorodibenzo-p-
dioxin (TCDD)
1,1,2,2-Tetrachloroethane
<79-34-5>
Tetrachloroethylene <127-18-4>
Thallium <7440-28-0>
Toluene
Toxaphene <8001-35-2>
TribroBone thane <75-25-2>
1,2, 4-T r ichlorobenzene <120-82-l>
1,1,1-Trichloroethane <71-55-6>
1,1,2-Trichloroethane <79-00-5>
Trichloroethylene <79-01-6>
Trichlorofluoroaethane <75-69-4>
2,4,6- Trichlorophenol
<88-06-2>
Vinyl chloride <75-01-4>
Zinc <7440-66-6>,TSS
Oil and Grease
total Coliforn
Chloride
Phenol
Fecal Colifora
Cyanide
TOC
Dissolved Oxygen
1001
-------
Accession Mo. 9028000512 (cont)
(CAS) CAS registry numbers of substances included in data base: 83-32-9
; 208-96-8* 107-02-8; 107-13-1; 30*-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 319-84-6; 319-85-7; 58-89-9; 319-86-8;
71-43-2; 92-87-5; 56-55-3; 205-99-2; 207-08-9; 191-24-2;
50-32-8; 7440-41-7; 111-91-1; 111-44-4; 39638-32-9; 542-88-1;
117-81-7; 74-83-9; 101-55-3; 85-68-7; 7440-43-9; 56-23-5;
57.74-9. 108-90-7; 124-48-1; 75-00-3; 110-75-8; 67-66-3; 59-50-7;
74-87-3; 91-58-7; 95-57-8; 7005-72-3; 7440-47-3; 218-01-9;
7440-50-8; 57-12-5; 72-54-8; 72-55-9; 50-29-3; 53-70-3;
84-74-2; 95-50-1; 541-73-1; 106-46-7; 91-94-1; 75-27-4; 75-71-8;
75-34-3; 107-06-2; 75-35-4; 156-60-5; 75-09-2; 120-83-2; 78-87-5;
563-54-2; 60-57-1; 84-66-2; 105-67-9; 131-11-3; 534-52-1; 51-28-5;
121-14-2; 606-20-2; 117-84-0; 122-66-7; 959-98-8; 33213-65-9;
1031-07-8; 72-20-8; 7421-93-4; 100-41-4; 206-44-0; 86-73-7;
75.44.3; 1024-57-3; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 91-20-3; 7440-02-0;
98-95-3; 88-75-5; 100-02-7; 62-75-9; 86-30-6; 621-64-7;
87-86-5; 85-01-8; 108-95-2; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 129-00-0;
7782-49-2; 7440-22-4; 79-34-5; 127-18-4; 7440-28-0; 108-88-3;
8001-35-2; 75-25-2; 120-82-1; 71-55-6; 79-00-5; 79-01-6;
75-69-4; 88-06-2; 75-01-4; 7440-66-6
(CMN) Contact naie(s): Heraett,R.B. ; Nossa,G. ; He»nett,R.B.
(COR) Contact organization: Roland B. Renaett
(ROR) Responsible Organization: Region II.Environmental Services
Division*
1002
-------
Accession No. 9028000901
(OQ) Date of Questionalre: 12-02-82
(HAH) Name of Data Base of Model: PCBs in Lower Hudson River Sediments
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Sediment
(ABS) Abstract/Overview of Data Base or Model: Data base contains
results of 60 sediment samples which were analyzed for
polychlorlnated biphenyls (PCBs). Samples were collected from
Troy, N.Y. to New York City during December, 1976.
(CTC) CONTACTS: Subject matter Roland Henmett (201) 321-6687 ;
Computer-related Robert Messina (212) 264-9850 } EPA Office
Roland Henmett (201) 321-6687
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Update terminated
(NPP) Non-pollutant parameters included in the data base: Location
;Sampling date
(DS) Time period covered by data base: 12-01-76 TO 10-22-81
(TRM) Termination of data collection: Occurred 12/30/76 ; another set
of samples was collected in October 1981.
(FRQ) Frequency of data collection or sampling: twice
(NOB) Number of observations in data base: 60(estimated)
(INF) Data base includes: Raw data/observations
(ITS) Total number of stations or sources covered in data base: 40.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(CEO) Geographic coverage of data base: Geographic region Lower Hudson
River/ New York and Upper Hudson River
(LOG) Data elements identifying location of station or source include:
Coordinates latitude/longitude
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation In data of which user should be aware: See
abstract for study limitations.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplln
g plan documented ^Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: ~YYes
(CBY) Data collected by: Regional office Environmental Services
Division
(ABY) Data analyzed by: Regional office Environmental Services
Division
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collections Trend assessment
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 106 and 305 (Clean Hater Act-CVA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Publications
1003
-------
Accession No. 9026000901 (cont)
PCBs In Lover Hudson River Sediments: a preliminary survey
On-line computer
(NOS) Number of regular users of data base: 10
(USR) Current regular users of data base: EPA regional offices
States
(CNF) Confidentiality of data and li*its on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
-------
Accession No. 9028000902
(DQ) Date of Questionaire: 12-02-82
(HAN) Kane of Data Base of Model: Newark Bay
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Surface water estuary
(ABS) Abstract/Overview of Data Base or Model: Data base contains
dissolved oxygen and sulfide data from twenty stations within
Newark Bay. The saaples are collected at low slack tide from one
foot below the surface and one foot off the bottom.
(CTC) CONTACTS: Subject «atter Roland Hemaett (201) 321-6687 ;
Computer-related Jack S
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Complete
(HPP) Non-pollutant parameters included in the data base: Location
;Sampling date
(DS) Tine period covered by data base: 07-01-80 TO 10-30-80
(TRM) Termination of data collection: 10/30/80
(FRQ) Frequency of data collection or sampling: as needed
(•OB) Number of observations in data base: 20000.(Estimated)
(NEI) Estimated annual increase of observations in data base: None.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 20.
(NCS) No. stations or sources currently originating/contributing data:
20.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: County/smaller location Newark
Bay
(LOC) Data elements identifying location of station or source include:
State ^Coordinates latitude/longitude
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplln
g plan documented ^Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EDT) Fditting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Environmental Services
Division, Region II
(ABY) Data analyzed by: Regional office Environmental Services
Division/ Region II
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Trend assessment
(AUT) authorization for data collection: No statutory requirement:
Data collection requirement is State requested assistance
monitoring a sewage treatment plant by passing raw sewage into the
bay.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: On-line
computer
1005
-------
Accession No. 9028000902 (cont)
(NUS) Number of regular users of data base: 50
(OSR) Current regular users of data base: EPA regional offices
States
(CNF) Confidentiality of data and Halts on access: No Units on
access to data
(DLC) Primary physical location of data: Regional office
COST) Fora of data storage: Magnetic disc
(DAC) Type of data access: EPA software STORET MIDS:5303000101 ;EPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA uses yes
(OPDT) Frequency of data base master file up-date: Other originally
weekly now monthly
(CMP) Completion of form:
Roland Hemmett
OFC: EPA/Region II/Environmental Services Division
AD: Hoodbridge Ave, Edison, NJ
PH: (201) 321-6687
(DP) Date of form completion: 01-14-63
(NMAT) Number of substances represented in data base: 2
(MAT) Substances represented in data base:
dissolved oxygen sulfide
(CNM) Contact name(s): Hemmett,R.; Messina,R. ; Henmett/R
(ROR) Responsible Organization: Region II.Environmental Services
Division.
1006
-------
Accession No. 9028000903
tDQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: New York Bight Ocean Monitoring
Program
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject Of Data Base or Model: Surface water Ocean (Bight
apex)
(ABS) Abstract/Overview of Data Base or Model: Data Base contains
results from 177 sampling locations spread over the nearshore
waters of the New York Bight. Samples are collected weekly in the
water column (1 meter below surface and 1 aeter off botton) from
May 15 to September 30.
(CTC) CONTACTS: Subject natter Roland Hemaett (201) 321-6687 ;
Computer-related Messina,R. (212) 264-9850 ; EPA Office Roland
Hemaett (201) 321-6687
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CMA ;11
conventional water
(NPP) Non-pollutant parameters included in the data base: Location
;Sampling date ;Site description ;Temperature
(DS) Time period covered by data base: 05-01-77 TO 12-28-82
(TRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: as needed ;0ther
weekly: temperature and dissolved oxygen ;0ther monthly: othe
Other as needed: 129 sediment samples
(NOB) Number of observations in data base: 45000.(Estimated)
(NEI) Estimated annual increase of observations in data base: 7650.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 250.
(NCS) No. stations or sources currently originating/contributing data:
250.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GCO) Geographic coverage of data base: Geographic region New York
Bight
(LOG) Data elements identifying location of station or source include:
Coordinates latitude/longitude
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
(L1M) Limitation/variation in data of which user should be aware: Prior
ity pollutants sampled in sediment only. Not ail 177 stations are
sampled for the 129 priority pollutants.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented Collection method documented /Analysis method
document QA procedures documented
(AML) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Region II, Surveillance and
Analysis Division
(ABY) Data analyzed by: Regional office Region II, Surveillance and
1007
-------
Accession No. 9028000903
(cont)
Analysis Division
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Trend assessment
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended (Sections 403 and 405 (Clean Hater Act-CHA)
(OMB) Data col lee ted/ submit ted using OMB- approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Publications
Rev York Bight Report
On-line computer
(HUS) Number of regular users of data base: 10
(OSR) current regular users of data base: EPA regional offices
(CRF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: EPA software STORE? MIDS: 5303000101 ;EPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Veekly
(CMP) Completion of form:
Roland Hemmett
QFC: EPA/Region II/Surveillance and Analysis Division
AD: Hoodbridge Ave Edison, NJ
Pfl: (201) 321-6687
(DF) Date of form completion: 01-14-83
(RMAT) Number of substances represented in data base: 134
(•CAS) Number of CAS registry numbers in data base: 127
(MAT) Substances represented in data base:
f l-trichloroethane<71-55-
6>
1,1,2, 2,-tetrachloroethane
<79-34-5>
1, l,2-trlchloroethane<79-00-5>
1, l-dichloroethane<75-34-3>
If l-dlchloroethylene<75-35-4>
l,2,4,-trichlorobenzene<120-82-l>
1, 2-dlchlorobenzene<95-50-l>
l,2-dichloroethane<107-06-2>
l,2-dichloropropane<78-87-5>
l,2-dichloropropylene<563-54-2>
l,2-diphenylhydrazine<122-«6-7>
1,2-trans-dlchloroethylene
<156-60-5>
l,3-dlchlorobenz«ne<541-73-l>
l,4-dlchlorobenzene<106-46-7>
2,4,6-trichlorophenol<88-06-2>
2, 4,7, 8- te trachlorodibenzo-p-
cioxin (tcdd)
2f 4-dichlorophenol<120-83-2>
2, 4-dimethylphenol<105-67-9>
2,4-dlnitrophenol<51-28-5>
2,4-dlnitrotoluene<121-14-2>
2,6-dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-nit rophenol<88-75-5>
3,3*-dichlorobenzidlne<91-94-l>
3,4-benzof luoranthene<205-99-2>
4,4'-ddd(p,p'tde)
4,4'-dde
4,4'-ddt<50-29-3>
4,6-dinltro-o-cresol<534-52-l>
4-bromophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
1008
-------
Accession Mo. 9028000903
(cont)
aldrin< 309-0 0-2>
anthracene<120-12-7>
antiraony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine< 92-87-5>
benzo( a) anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo( g, h, i) pery lene< 1 91-24-2>
ben20< k) f luo ranthene<207-08-9>
berylllu«<7440-41-7>
bhc (lindane)-ga«»a<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-de lta<31 9-86-8>
bis( 2-chloroethoxy )aethane
bis(2-chloroethyl)eth«r
bis( 2-chloroisopropy 1) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloro»ethyl)ether<542-88-l>
bro»OBethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cad»lu«<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodibro«oBethane<124-48-l>
chloroethane<75-00-3>
chlorofora<67-66-3>
chloromethane<74-87-3>
chro»lu»<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
dl-n-octyl phthalate<117-84-0>
dibenz o< a, h) an thr acene<53-70-3>
dichlorobro«o«ethan«<75-27-4>
dichlorodifluoro»ethane<75-71-8>
dichloropethane<75-09-2>
dieldrln<60-57-l>
dl ethyl phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
dissolved solids
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endrln aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fluoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadlene<77-47-4>
hexachloroethane<67-72-l>
indeno (l,2,3-cd)pyrene<193-39-5>
1 sophor one<78-59-l>
lead<7439-92-l>
»ercury<7439-97-6>
n-n 1 1 rosed i-n-propy laai ne
<621-64-7>
n-ni t ro sodiae thyl an lne<62-7 5-9>
n-nitrosodiphenyla«ine<86-30-6>
naphthalen«<91-20-3>
nlckel<7440-02-0>
nitrobenzene<98-95-3>
p-chloro-B-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 {arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
p en tach 1 or ophenoK 87* 86-5>
Ph
phenanthrene<85-01-8>
phenol<108-95-2>
pyrene<129-00-0>
selenlua<7782-49-2>
sllver<7440-22-4>
tetrachloroethylene<127-18-4>
thalliu«<7440-28-0>
toluene<108-88-3>
total kjeldahl nitrogen
total suspended solids (TSS)
t oxaphene< 8001-35-2>
transparency
tribroBO«€thane<7 5-25-2 >
trichloroethylene<79-01-!-6>
1009
-------
Accession Ho. 9028000903 (cont)
trlchlorofluoroMethane<75-69-4> zinc<7440-66-6>
vinyl chloride<75-01-4>
(CAS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 7782-49-2;
7440-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2;
79-01-6; 75-69-4; 75-01-4; 7440-66-6
(CUM) Contact na*e(s): Renett,R.; Sweeney,J.; Hem»ett,R.
-------
Accession Ho. 9026000904
(DQ) Date of Questionaire: 12*02-82
(NAM) Name of Data Base of Model: ALDICARB Data Base
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Drinking Hater
(ABS) Abstract/Overview of Data Base or Model: The ALDICARB data base
Has collected from 8 drinking Mater Hells on Long Island/ NY,
(CTC) CONTACTS: Subject natter Francis Brezenski (201)321-6706;
Computer-related Robert
(DTP) Type of data collection or monitoring: Anbient data collection
(STA) Data Base status: Discontinued
(BPP) Non-pollutant paraaeters included in the data base: Collection
method ;Location ;Physical data ;Sampling date ;Site description
(DS) Ti»e period covered by data base: 07-00-79
(TRM) Termination of data collection: Not applicable
(FRQ) Frequency of data collection or sampling: one time only
(NOB) Number of observations in data base: 8.(Actual)
(NED Estimated annual increase of observations in data base: (N/A.)
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 8«
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOT) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: County/smaller location Long
Island, NY
(LOG) Data elements identifying location of station or source include:
State /City ;Street address
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Uncoded
(LIM) Limitation/variation in data of nhich user should be auare: Analy
ses done by U.S. Department of Agriculture Lab-unknown
performance evaluation.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Collect
ion method documented
(AHL) Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Local agency local health department
jRegional office Surveillance and Analysis
(ABY) Data analyzed by: Other federal agency U.S. Department of
Agriculture Lab-Beltsville, MD
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Risk assessment
(AOT) Authorization for data collection: No statutory requirements
Data is collected due to a special request to investigate
aldicarb in drinking nater-folloH up turned over to county.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Machine-reada
ble raw data
(•OS) Number of regular users of data base: 4 offices
(OSR) Current regular users of data base: EPA laboratories
1011
-------
Accession lo. 9028000904
(cont)
Other federal agencies
States
(CNF) Confidentiality of data and Ililts on access: Mo limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Fora of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base vaster file up-date: Other one ti»e study
(CMP) Completion of fora:
Randy Braun
OFC: EPA/Region II
AD: Edison, N.J.
PH: (201)321-6692
(OF) Date of fora completion: 01-14-83
(•NAT) Number of substances represented in data base: 1
(NCAS) Number of CAS registry numbers in data basei 1
(MAT) Substances represented in data bases
Aldicarb<116-06-3>
(CAS) CAS registry numbers of substances included in data base: 116-06-
3
(CMM) Contact name(s): Messlna,R« ; Brezenskl/F.
(ROR) Responsible Organization: Region II.Environmental Services
Division.
1012
-------
Accession Ho. 9028000905
(DQ) Date of Questionaire: 12-02-82
(MAN) Mane of Data Base of Model: Humacao Ambient Data Base
(ACR) Acronyn of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Effluents industrial
^Sediment ;Surface water creek
(ABS) Abstract/Overview of Data Base or Model: Intensive survey of
Frontera Creek in Humacao, Puerto Rico. Industries, creek
sedinent, and creek water column Here all sampled for metals
and selected organics.
(CTC) CONTACTS: Subject matter Roland Hemnett (201)321-6687 ;
Computer-related Archdeacon,B. (201)321-6787 ; EPA Office
Region II, Edison, NJ (201)321-6687
(DTP) Type of data collection or Monitoring: Ron point source data
collection
(STA) Data Base status: Discontinued
(GRP) Groups of substances represented in Data Base: 129 307 CtfA ;11
conventional water ;15 netals
(NPP) Non-pollutant parameters included In the data base: Collection
•ethod ^Physical data
(OS) Tine period covered by data base: 10-00-79
(TRM) Termination of data collection: Not applicable
(FRQ) Frequency of data collection or sampling: one tine only
(NOB) Number of observations In data base: 300.(Estimated)
(NEI) Estinated annual increase of observations in data base: 0.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 20.
(NCS) No. stations or sources currently originating/contributing data:
0.
(•OF) Number of facilities covered in data base (source monitorIng): 6.
(GEO) Geographic coverage of data base: County/smaller location
Frontera Creek, Humacao, Puerto Rico
(LOG) Data elements identifying location of station or source include:
State ;County ;City ;Town/township ;Project identifier
(FAC) Data elements identifying facility include: Plant facility name
;PIant location ;street address ;NPDES
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: Varyi
ng samples and parameters for different stations
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented Collection method documented ;Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Regional office Environmental Services
Division, Region II
(ABY) Data analyzed by: Regional office Environmental Services
Division, Region II
(IDL) Laboratory Identification: YES
(AOT) Authorization for data collection: No statutory requirement:
1013
-------
Accession Mo. 9028000905 (cont)
Data collection requirement is at request of Environaental
Quality Board (Puerto Rico) to assist in evaluating local problea.
COMB) Data collected/submitted using OMB-approved EPA reporting foras:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Frontera Creek Survey, Huaacao, Puerto Rico
Printouts on request
CMOS) Number of regular users of data base: 50
(OSR) Current regular users of data base: EPA regional offices
Other federal agencies
States
(CNF) Confidentiality of data and Halts on access: No Halts on
access to data
(DLC) Priaary physical location of data: Regional office
(DST) Fora of data storage: Magnetic disc
(DAC) Type of data access: EPA software STORET NIDS:5303000101 ;EPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base Master file up-date: Other study update
terminated
(CMP) Completion of fora:
Randy Braun
OFC: EPA/Region II
AD: Edison, N.J.
PH: (201)321-6692
(DF) Date of fora completion: 01-14-83
(NMAT) Nuaber of substances represented in data base: 140
(NCAS) Number of CAS registry nuabers in data base: 133
(MAT) Substances represented in data base:
l,l,l-trichloroethane<71-55- 2,4-dinitrotoluene<121-14-2>
6> 2,6-dinitrotoluene<606-20-2>
1,1,2,2,-tetrachloroethane 2-chloroethylvinyl ether<110-75-8>
<79-34-5> 2-chioronaphthalene<91-58-7>
l,l,2-trichloroethane<79-00-5> 2-chloroi>henol<95-57-8>
l,l-dichloroethane<75-34-3> 2-nitrophenol<88-75-5>
l,l-dichloroethylene<75-35-4> 3,3*-dichlorobenzidine<91-94-l>
l,2,4*-trichlorobenzene<120-82-l> 3,4-benzofluoranthene<205-99-2>
l,2-dichlorobenzene<95-50-l> 4,4'-ddd(p,p*tde)
l,2-dichloroethane<107-06-2> 4,4--dde
l,2-dichloropropane<78-87-5> 4,4*-ddt<50-29-3>
l,2-dichloropropylene<563-54-2> 4,6-dinitro-o-cresol<534-52-l>
l,2-dlphenylhydrazlne<122-66-7> 4-broaophenyl phenyl ether
1,2-trans-dichloroethylene <101-55-3>
<156-60-5> 4-chlorophenyl phenyl ether
1,3-dichlorobenzene<541-73-l> <7005-72-3>
l,4-dichlorobenzene<106-46-7> 4-nitrophenol<100-02-7>
2/4,6-trichlorophenol<88-06-2> acenaphthene<83-32-9>
2/4,7,8-tetrachlorodibenzo-p- acenaphthylene<208-96-8>
dioxin (tcdd) acidity
2,4-dichlorophenol<120-83-2> acrolein<107-02-8>
2,4-diaethylphenol<105-67-9> acrylonitrile<107-13-1>
2,4-dinitrophenol<51-28-5> aldriiK309-00-2>
1014
-------
Accession No* 9028000905
(cont)
alkalinity
anthracene<120-12-7>
anti«ony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
benzo( a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h,i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
berylliu«K7440-41-7>
bhc (lindane)-ganaa<58-89-9>
bhc-alpha<31 9-84-6>
bhc-beta<319-85-7>
bhc-delta< 31 9-86-8>
bis(2-chloroethoxy)nethane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethy Ihexy 1 )phthalate
bis(chloro»ethyl)ether<542-88-l>
broaomethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadBiua<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenz ene< 10 8-90-7>
chlcrodibroaomethane<124-48-l>
chloroethane<75-00-3>
chlorofor«<67-66-3>
chloronethane<74-87-3>
chro«iun<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenz o( a, h) anthrac«ne<53-70-3>
dichlorobrofflonethane<75-27-4>
dichlorodifluoroaethane<75-71-8>
dichloromethane<75-09-2>
dieldrin<60-57-l>
diethyl phthalate<84-66-2>
diiethyl phthalate<131-ll-3>
dissolved oxygen
dissolved solids
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulf an-beta< 3321 3-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fecal coliforn
f luoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
hep t achlor <76-44-8>
hexachlorobenzene<118-74-l>
hexachlcrobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeuo (1^2,3-cd)pyrene<193-39-5:
isophorone<78-59-l>
lead<7439-92-l>
mercury<7439-97-6>
n-ni t ro sodi-n-propy lamina
<621-64-7>
n-nitrosodiBethyla«ine<62-75-9>
n-nitrosodiphenyla«ine<86-30-6>
nap h tha lene<91 -20 -3>
nickel<7440-02-0>
nitrobenzene<98-95-3>
nitrogen<7727-37-9>
oil and grease
oxygen deaand
p-chloro-»-cresol<59-50-7>
PH
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
phosphorws<7723-14-0>
pyrene<129-00-0>
selenium<7782-49-2>
silver<7440-22-4>
suspended solids
tetrachloroethylene<127-18-4>
thalliu«<7440-28-0>
1015
-------
Accession No. 9028000905 (cont)
toluene<108-88-3> trichlorofluoro«ethane<75-69-4>
toxaphene<8001-35-2> vinyl chloride<75-Oi-4>
tribrow»ethane<75-25-2> zinc<7440-66-6>
trichloroethylen«<79-01-6>
CCAS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-51 79-00-5; 75-34-3; 75-35-41 120-82-U 95-50-1;
107-06-21 78-87-51 563-54-21 122-66-71 156-60-51 541-73-H
106-46-71 88-06-21 120-83-21 105-67-91 51-28-51 121-14-21
606-20-21 110-75-81 91-58-71 95^57-81 88-75-51 91-94-U 205-99-21
72-55-91 50-29-31 534-52-U 101-55-31 7005-72-31 100-02-71 83-32-91
208-96-81 107-02-81 107-13-11 309-00-21 120-12-71 7440-36-01
7440-38-21 1332-21-41 71-43-21 92-87-51 56-55-31 50-32-81 191-24-21
207-08-91 7440-41-71 58-89-91 319-84-61 319-85-71 319-86-81
111-91-U 111-44-41 39638-32-91 117-81-71 542-88-U 74-83-91
85-68-71 7440-43-91 56-23-Sl 57-74-91 108-90-71 124-48-U
75-00-31 67-66-31 74-87-31 7440-47-31 218-01-91 7440-50-81
57-12-51 84-74-21 117*84-0i 53-70-31 75-27-41 75-71-81
75-09-21 60-57-H 84-66-21 131-11-31 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 7727-37-9; 59-50-7;
12674-11-2; 11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6;
11097-69-1; 11096-82-5; 87-86-5; 85-01-8; 108-95-2; 7723-14-0;
129-00-0; 7782-49-2; 7440-22-4; 127-18-4! 7440-28-01 108-88-31
8001-35-2; 75-25-2; 79-01-6; 75-69-41 75-01-41 7440-66-6
CCNM) Contact naae(s): Heuett,R.i S«ith,R. ; II,R.
CROR) Responsible Organization: Region II,Environmental Services
Division.
1016
-------
Accession No. 9028000906
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: U.S. Virgin Islands-St. Thomas, St.
Croix
(ACR) Acronym of Data Base or Model: Rone
(MED) Media/Subject of Data Base or Model: Sediment ^Surface water
ocean
fABS) Abstract/Overview of Data Base or Model: Data consists of
station heading, location, time, date, and parameters (dissolved
oxygen, bacti, metals, nutrients) for water and priority
pollutants for sediment samples. Sampled every five years-next
sampling FY 84.
(CTC) CONTACTS: Subject matter R. Hemmett (201)321-6687 ;
Computer-related R. Smith (
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CtfA
(NPP) Non-pollutant parameters included in the data base: Location
;physical data ^Sampling date ;Site description ^Temperature
(DS) Time period covered by data base: 03-01-74 TO 11-30-79
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed ;Other
regularly every 5 years
(NOB) Number of observations in data base: 29520.(Estimated)
(NEI) Estimated annual increase of observations in data base: 1500.(O6
00 (samples) every )5 (years)
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 150.
(NCS) NO. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: Selected federal region Region
II (Virgin Islands)
(LOG) Data elements identifying location of station or source include:
State
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
(LiM) Limitation/variation in data of which user should be aware:
1,200 samples to date-90% water samples.
(DPR) Data collect./anal, procedures conform to QRD guidelines: Samplin
g plan documented Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division, Region II
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division, Region II
(IDL) Laboratory identification: NO
(AOT) Authorization for data collection: Statutory authorization is P
1017
-------
Accession Ho. 9028000906
(cont)
L 92-500 (Clean Hater Act-CM A)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports "U.S. Virgin Islands Ambient Hater Quality"-Surveillance
and Analysis Division
(MOS) Number of regular users of data base: 10
(USR) Current regular users of data base: EPA regional offices
Surveillance and Analysis Division, Region II
(CNF) Confidentiality of data and Units on access: Ho Units on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Fora of data storage: Magnetic tape
(DAC) Type of data access: EPA software STORET MIDS:5303000101 ;EPA
hardware IBM 370/168
(CH6) Direct charge for non-EPA use: yes
(UPDT) Frequency of data base master file up-date: Other every 5 years
(RSS) Related EPA automated systems which use data base: STORET
(Storage and Retrieval of Hater Quality Data)
(CMP) Completion of for*:
Billie Jo Johnson
OFC: EPA/Region Il/Surveillance and Analysis Division
AD: Hoodbridge Ave Edison, H.J. 08817
PH: (201)321-6713
(OF) Date of fora completion: 01-14-83
(HMAT) Number of substances represented in data base: 133
(MCAS) Number of CAS registry numbers in data base: 127
(MA?) Substances represented in data base:
l,l,l-trichloroethane<71-55-
6>
1, If 2, 2, -tetr achloroe thane
<79-34-5>
Iflf2-trichloroethane<79-00-5>
l,l-dichloroethane<75-34-3>
l,l-dichloroethylene<75-35-4>
l,2,4,-trlchlorobenzene<120-82-l>
1,2-dichlo robenzene<95-50-l>
l,2-dichloroethane<107-06-2>
1,2-dichloropropane<78-87-5>
l,2-dichloropropylene<563-54-2>
1,2-diphenylhydrazine<122-66-7>
1,2-trans-dichloroethylene
<156-60-5>
1,3-dichlorobenzene<541-73-l>
l,4-dlchlorobenzene<106-46-7>
2,4,6-tr ichloropheno1<88-0 6-2>
2,4,7,8-tetrachlorodibenzo-p-
dloxin (tcdd)
2,4-dichlorophenol
2,4-dlaethylphenol<105-67-9>
2,4-dinitrophenol<51-28-S>
2,4-dinitrotoluene<121-14-2>
2,6-dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-nitrophenol<88-75-5>
3,3 *-dichlorobenzidine< 91-94-l>
3,4-benzofluoranthene<205-99-2>
4,4*-ddd(p,p*tde)
4,4»-dde(p,p'-ddx)<72-55-9>
4,4*-ddt<50-29-3>
4,6-dinitro-o-cresol<53 4-52-l>
4-bromophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
acenaph thylene<20 8-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
anthracene<120-12-7>
antiaony<7440-36-0>
arsenic<7440-38-2>
1018
-------
Accession No. 9028000906
(cont)
asbestos
benzene<71 -43- 2>
benzid in e< 92-87- 5>
ben2o(a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h,i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
beryllium<7440-41-7>
bhc (lindane)-gamaa<58-89-9>
bhc-alpha< 31 9-84-6>
bhc-beta<3 19-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)nethane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bls(chlorofflethyl)ether<542-88-l>
bro«omethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cad»lum<7440-43-9>
carbon tetrachlorlde<56-23-5>
chlordane< 57-7 4- 9>
chlorobenzene<108-90-7>
chlcrodibroaomethane<124-48-l>
chloroe thane<7 5-00-3>
chlorofor«<67-66-3>
chloronethane<74-87-3>
chro«lu«<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dlbenzo(a,h) anthracene<53-70-3>
dichlorobro«omethane<75-27-4>
dichlorodifluoromethane<75-71-8>
dictiloronethan€<75-09-2>
dieldrin<60-57-l>
diethyl phthalate<84-66-2>
diaethyl phthalate<131-ll-3>
dissolved oxygen
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan -bet a< 3321 3-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fecal collfora
fluoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachiorobenzene<118-74-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeno (l,2,3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
nercury<7439-97-6>
n-nitrosodi-n-propylamine
<621-64-7>
n-nitrosodlB€thyla»ine<62-75-9>
n-nltrosodiphenylaaine< 86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nltrobenzene< 98-95-3>
nutrients
p-chlor o-B-cresol< 59- 50 -7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
pyrene<129-00-0>
seleniu«<7782-49-2>
silver<7440-22-4>
tetrachloroethylene<127-18-4>
thalliu»<7440-28-0>
toluene<108-88-3>
total coll form
toxaphene<8001-35-2>
tribroao«ethane<75-25-2>
tr ichloroethylene<79-01 -6>
trichlorofluoro«ethane<75-69-4>
vinyl chloride<75-01-4>
zinc<7440-66-6>
1019
-------
Accession No. 9028000906 (cont)
(CAS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 7782-49-2;
7440-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2;
79-01-6; 75-69-4; 75-01-4; 7440-66-6
(CRN) Contact name(s): HeanettsR.; Archdeacon, B.
(ROR) Responsible Organization: Region II.Environmental Services
Division.
1020
-------
Accession No. 9028000907
(DQ) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: Con da do Lagoon-San Juan, Puerto Rico
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Surface water lagoon
(ABS) Abstract/Overview of Data Base or Model: Data consists of
station headings, location, date sampled, tine of day, and
parameters (conforms).
(CTC) CONTACTS: Subject aatter R. Hemmett (201)321-6687 ; EPA
Office Region II (201)3
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(NPP) Ron-pollutant parameters included in the data base: Location
;Sampling date ;Site description
(DS) Time period covered by data base: 03-01-74 TO 11-30-79
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed ;0ther
generally some sampling each year
(NOB) Number of observations in data base: 200.(Estimated)
(NEI) Estimated annual Increase of observations in data base: 100.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 8.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: Geographic region Condado
Lagoon, Puerto Rico
(LOC) Data elements identifying location of station or source include:
State jCity ;TOHn/township ^Project identifier
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: 100
samples; lab identification not in machine form.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented ;Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy esti»ates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division, Region II
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division, Region II
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Program evaluation
(PR2) Secondary purpose of data collection: Special study
(AOT) Authorization for data collection: No statutory requirement:
Data collection requirement is Environmental Quality Board of
Puerto Rico requested ambient monitoring of lagoon to supplement
local monitoring
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
1021
-------
Accession Ho. 9028000907 (cont)
QQ
(REP) For* of available reports and outputs of data base: Unpublished
reports "Condado Lagoon"-Surveillance And Analysis Division,
Region II
(NOS) Runber of regular users of data base: 6
(USR) Current regular users of data base: EPA regional offices
(CNF) Confidentiality of data and limits on access: Ho Halts on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Fora of data storage: Magnetic disc
(DAC) Type of data access: EPA softMare STORET HIDS:5303000101 ;EPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base vaster file up-date: Annually
(RSS) Related EPA automated systems uhich use data base: STORET
(Storage and Retrieval of Hater Quality Data)
(CMP) Completion of for*:
Billle Jo Johnson
OFC: EPA/Region H/Surveillance and Analysis Division
AD: Uoodbridge Ave Edison, HJ
PH: (201)321-6713
(DF) Date of form completion: 01-14-83
(HHAT) Number of substances represented in data base: 2
(MAT) Substances represented in data base:
fecal coliform total coliforn
(CNM) Contact naae(s): Hemaett,R.; II,R.
(ROR) Responsible Organization: Region II.Environmental Services
Division.
1022
-------
Accession No. 9028000908
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Puerto Rico Beaches-San Juan
(ACR) Acronym of Data Base or Model: Rone
(MED) Media/Subject of Data Base or Model: Surface water ocean
(ABS) Abstract/Over view of Data Base or Model: Data base consists of
station designation (initial number), location, date sampled/
tine of day, depth, and parameters identified.
(CTC) CONTACTS: Subject natter R. Hemaett (201) 321-6687 ;
Computer-related R. Smith (
(DTP) Type of data collection or monitoring: Anbient data collection
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters included in the data base: Location
^Physical data ;Sampling date ;Site description
(OS) Time period covered by data base: 03-01-74 TO 11-30-79
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Other As needed:
basically annually
(NOB) Number of observations in data base: 1400.(Estimated)
(NEI) Estimated annual increase of observations in data base: 400.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 36.
(NCS) No* stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(6EO) Geographic coverage of data base: County/smaller location San
Juan, Puerto Rico
(LOG) Data elements identifying location of station or source include:
State ;City
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of uhich user should be ay arc: 700
samples included in the data base.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented ^Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: No known edit procedures exist.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division, Region II
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division, Region II
(IDL) Laboratory identification: NO
(AOT) Authorization for data collection: No statutory requirement:
Data collection requirement is requested by Puerto Rico
Environmental Quality Board
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Surveillance and Analysis Report: "San Juan Beaches1*
1023
-------
Accession No. 9028000908 (cont)
Printouts on request
(MOS) NuBber of regular users of data base: 6
(OSR) Current regular users of data base: EPA regional offices
(CNF) Confidentiality of data and Hilts on access: No Halts on
access to data
(DLC) Primary physical location of data: Regional office
COST) Fora of data storage: Magnetic disc
(DAC) Type of data access: EPA software STORET MIDS:5303000101 ;EPA
hardware IBM 370/168
Saith,R. ; Heaaett,R.
(ROR) Responsible Organization: Region II.Environmental Services
T*vision.
1024
-------
Accession Ho. 9028000909
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: San Juan, Puerto Rico Outfalls
(ACR) Acronym of Data Base or Model: Rone
(MED) Media/Subject of Data Base or Model: Effluents sewage treatment
plant outfalls ;Surface Hater ocean
(ABS) Abstract/Overview of Data Base or Model: This data base consists
of station headings, locations, date sampled, time of day, depth,
and parameters identified.
(CTC) CONTACTS: Subject matter R. Hemmett (201)321-6687 ;
Computer-related R. Smith (
(DTP) Type of data collection or monitoring: Point source data
collection sewage treatment plants
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters included in the data base: Discharge
points ;Location ;Physical data ^Sampling date ;Site description
(DS) Time period covered by data base: 02-01-78 TO 11-30-79
(TRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: Other annually
(generally)
(NOB) Number of observations in data base: 600.(Estimated)
(NEI) Estimated annual increase of observations in data base: 200.
(IMP) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 35.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 5,
(GEO) Geographic coverage of data base: Geographic region San Juan
area, Puerto Rico
(LOC) Data elements identifying location of station or source include:
State ;City ; Town/township jProject identifier
(FAC) Data elements identifying facility include: outfall identified
only
(CDE) Pollutant Identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: 300
samples taken; performance samples do not exist for bacti.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented ;Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Data not based on lab analysis.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EDT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division, Region II
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division, Region II
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Program evaluation
(PR2) Secondary purpose of data collection: Special study
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 (Clean Hater Act)
1025
-------
Accession No. 9028000909 (cont)
(OMB) Data collected/submitted using OMB-approved EPA reporting foras:
QQ
(REP) For* of available reports and outputs of data base: Unpublished
reports Surveillance and Analysis Division: "San Juan Outfalls*
Printouts on request
(NUS) Nuaber of regular users of data base: 10
(OSR) Current regular users of data base: EPA Regional Office: Region
(CNF) Confidentiality of data and Halts on access: No liaits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: EPA software STORET MIDS:5303000101 ;EPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA use: yes
(DPDT) Frequency of data base master file up-date: Annually
(RSS) Related EPA automated systems which use data base: STORET
(Storage and Retrieval of Hater Quality Data)
(CMP) Completion of fora:
61 Hie Jo Johnson
OFC: EPA/Region II/Surveillance and Analysis Division
AD: Uoodbridge Ave Edison, NJ 08817
PH: (201)321-6713
(DF) Date of fora completion: 01-14-83
(RMAT) Nuaber of substances represented in data base: 2
(MAT) Substances represented In data base:
fecal colifora total colifora
(CNM) Contact naae(s): Heaaett,R.; Archdeacon,B. ; Hemmett,R.
(RQR) Responsible Organization: Region II.Environmental Services
Division.
1026
-------
Accession No. 9028000910
(DQ) Date of Questioaaire: 12-02-82
(NAM) Name of Data Base of Hodel: Puerto Rico Reservoirs
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Sediment ^Surface water
reservoirs
(ABS) Abstract/Overview of Data Base or Model: Data consists of
station heading/ location/ sample date/ time of day/ and
parameters for sediment (priority pollutants/ metals).
(CTC) CONTACTS: Subject matter Roland Hemmett (201)321-6687 ;
Computer-related Jack S
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CMA ;15
metals
(NPP) Non-pollutant parameters included in the data base: Location
?Sampling date ;Site description
(DS) Time period covered by data base: 03-01-74 TO 12-28-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 4700.(Estimated)
(NEI) Estimated annual increase of observations in data base: 1000.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 37.
(NCS) No. stations or sources currently originating/contributing data:
0.
(HOP) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: Geographic region Puerto Rico
(LOC) Data elements identifying location of station or source include:
State jCity Coordinates Latitude and longitude ;Project identifier
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: Total
of 50 samples. No water samples taken since 1974. Priority
pollutants sampled only in sediment.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented ;Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division/ Region II
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division/ Region II
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Special study
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended/ Sections 403 and 405 (Clean Water Act-CMA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
1027
-------
Accession Bo. 9028000910
(cont)
reports "Puerto Rico Reservoirs"-Survelllance and Analysis
Division.
(•OS) Number of regular users of data base: 6
COSR) current regular users of data base: EPA regional offices
(CUP) Confidentiality of data and Halts on access: Ho Halts on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Por« of data storage: Magnetic disc
(DAC) Type of data access: EPA software STORE? MIDS:5303000101 jEPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA use: yes
(UPDT) Frequency of data base aaster file up-date: Other as
needed-tnice in 5 years to date
(RSS) Related EPA autoaated systeas which use data base: STORET
(Storage and Retrieval of Hater Quality Date)
(CMP) Completion of fora:
Billie Jo Johnson
OFC: EPA/Region II/Surveillance and Analysis Division
AD: Uoodbridge Ave Edison/ MJ 08817
PH: (201)321-6713
(DP) Date of fora completion: 01-14-83
(HMAT) Muaber of substances represented in data base: 129
(NCAS) Muaber of CAS registry nuabers in data base: 134
(MAT) Substances represented in data base:
l,l,l-trichloroethane<71-55-
6>
I*ls2,2,-tetrachloroethane
<79-34-5>
Ifl*2-trichloroethane<79-00-5>
1*l-dichloroethane<75-34-3>
l,l-dichloroethylene<75-35-4>
l,2,4,-trichlorobenzene<120-82-l>
If2-dlchlorobenzene<95-50-1>
l,2-dichloroethane<107-06-2>
1,2-dichloropropane<78-87-5>
ls2-dlchloropropylene<563-54-2>
1,2-diphenylhydrazine
1^2-trans-dichloroethylene
<156-60-5>
l/>3-dichlorobenzene< 541-73-1 >
ls4-dichlorobenzene<106-46-7>
2,4,6-trichlorophenol<88-06-2>
2*4*7,8-tetr achlorodibenzo-p-
dioxin (tcdd)
2f 4-dichlorophenol
2,4-diaethylphenol<105-67-9>
2f4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2f6-dinltrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthaiene< 91-5 8-7>
2-chlorophenol<95-57-8>
2-nitrophenol<88-75-5>
3,3*-dichlorobenzidine<91-94-l>
3,4-benzofluoranthene<205-99-2>
4^4'-dde(p/p*-ddx)<72-55-9>
4^4'-ddt<50-29-3>
4/6-dinltro-o-cresol<534-52-l>
4-broaophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrln<309-00-2>
anthr acene<120-l 2-7>
antiaony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
benzo( a) anthr acene< 56-55- 3>
benzo(a)pyrene<50-32-8>
benzo(g,h,i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
berylliua<7440-41-7>
1028
-------
Accession No. 9028000910
(cont)
bhc (lindane)-gamma<58-89-9>
bhc-al pha<31 9-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)aethane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis<2-ethylhexyl)phthalate
bis(chloromethyl)ether<542-88-l>
broaoiiethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadftiun<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodibronoaethane<124-48-l>
chloroethane<75-00-3>
chloroforia<67-66-3>
chloronethane<74-87-3>
chro«iu»<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74~2>
di-n-octyl phthalate<117-84-0>
dibenzo(a*h) anthracene<53-70-3>
dichlor obr OB one t hane<7 5-27-4>
dichlorodifluoromethane<75-71-8>
dichloromethane<75-09-2>
dieldrin<60-57-l>
diethyl ph thai at e< 84-66- 2>
diiethyl phthalate<131-ll-3>
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulf an-be ta<3321 3-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fluoranthene<206-44-0>
£luorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlorobutadiene<87~68-3>
hexachlotocyclopentadiene<77-47-4
hex achl oro e thane<67-7 2-1 >
indeno (l,2,3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
•ercury<7439-97-6>
n-nitroscdi-n-propylaaine
<621-64-7>
n-nltrosodimethyla«ine<62-75-9>
n-nitrosodiphenyla«ine<86-30-6>
naphthalene< 91-20-3>
nickel<7440>02-0>
nitrobenzene<98-95-3>
p-chloro-«-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
pyr ene< 129-00-0>
selenlu«<7782-49-2>
sllver<7440-22-4>
tetrachloroethylene<127-18-4>
thalllu«<7440-28-0>
toluene<108-88-3>
toxaphene<8001-35-2>
tribroBo«ethane<75-25-2>
trichloroethylene<79-01-6>
trlchlorof luoro«fethane<75-69-4>
vinyl chloride<75-01-4>
zinc<7440-66-6>
(CAS) CAS registry numbers of substances included In data base: 71*55-6
> 79-34-5; 79-00-5J 75-34-3> 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
1029
-------
Accession No. 9028000910 (cont)
7440-38-21 1332-21-4* 71-43-2; 92-87-5? 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 7782-49-2;
7440-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2;
79.01-6; 75-69-4; 75-01-4; 7440-66-6
(CNN) Contact na«e(s): HeuettsR.; Sweeney/J.; Ueuett/R*
CROR) Responsible Organization: Region ll.Environnental Services
Division*
1030
-------
Accession No. 9028000911
(DQ) Date of Questionaire: 12-02-82
(HAM) Same of Data Base of Model: Manasquan Rivec
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Sediment ;Surface
water-river ;Tlssue fish
CABS) Abstract/over view of Data Base or Model: The data base contains
water quality and sediment data on the Manasquan River. Fish
tissue samples were also collected.
(CTC) CONTACTS: Subject natter Roland Hemaett, Chief Surveillance
and? Computer-related B
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CHA
(NPP) Non-pollutant parameters included in the data base: Location
^Sampling data ;Site description
CDS) Time period covered by data base: 02-01-81 TO 12-28-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 3000(Estiaated)
(NEI) Estimated annual increase of observations in data base: (N/A)
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 12
(NCS) No. stations or sources currently originating/contributing data:
12
(NOF) Number of facilities covered in data base (source monitoring): 0
(CEO) Geographic coverage of data base: County/smaller
location-Nonmouth County
(LOC) Data elements identifying location of station or source include:
State ;County ;Coordinates-latitude/longitude
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
(DPR) Data collect./anal, procedures conform to CRD guidelines: Conform
to ORD QA Guidelines
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory
(PRE) Precision: Precision and accuracy estimates exist for all
measurements
(EDT) Editting: Edit procedures used and documented
(CBY) Data collected by: State agency-N.J. Dept. of Environmental
Protection ;Regional office-Region II, Division
(ABY) Data analyzed by: Regional office-Region II, Environmental
Services
Contractor lab-varies Hith each analysis
(IDL) Laboratory identification: YES
(A(ft) Authorization for data collection: No statutory requirement:
Data collection requirement is to perform a required number of
analysis per year. Type of analysis depends on state of N.J.
Department of Environmental Protection's need.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
request
1031
-------
Accession Ho. 9028000911
(cont)
(MOS) Umber of regular users of data base: ttio agencies
(OSR) Current regular users of data base: EPA regional offices
States
(CNF) Confidentiality of data and Halts on access: ffo Units on
access to data
(DLC) primary physical location of data: Regional office
(OST) Fora of data storage: STQRET
(DAC) Type of data access: EPA software: STORET
(CHG) Direct charge for non-EPA use: Mo
(UPDT> Frequency of data base Master file up-date: Other as necessary
(CMP) Completion of fora:
Randy Braun
OFC: USEPA-Region II/Environmental Services Division
AD: Hoodbridge Avenue/ Edison, N.J. 08837
PH: (201) 321-6692
(DF) Date of fora completion: 01-14-83
(NMAT) Number of substances represented in data base: 139
(RCAS) Number of CAS registry numbers in data base: 131
(MAT) Substances represented in data base:
If If l-trichloroethane<71-55-
6>
1,1,2,2,-tetrachloroethane
<79-34-5>
l,l,2-trichloroethane<79-00-5>
l,l-dichloroethane<75-34-3>
If1-dichloroethylene<75-35-4>
If2,4,-trichlorobenzene<120-82-l>
1,2-dlchlorobenzene< 95-50-l>
If2-dichloroethane<107-06-2>
l,2-dlchloropropane<78-87-5>
If2-dlchloropropylene<563-54-2>
If2-diphenylhydrazine<122-66-7>
1,2-trans-dichloroethylene
<156-60-5>
If3-dlchlorobenzene<541-73-l>
1,4-dlchlorobenzene<106-46-7>
2,4,6~trichlorophenol<88-06-2>
2, 4,7, 8-te tr achlorodibenzo-p-
dioxin (tcdd)
2,4-dichlorophenol<120-83-2>
2,4-dimethylphenol<105-67-9>
2,4-dinitrophenol<51-28-5>
2,4-dlnitrotoluene<121-14-2>
2,6-dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaph thal«ne< 91-58-7>
2-chloroph«nol<95-57-8>
2-nitrophenol<88-75-5>
3,3'-dichlorobenziaine<91-94-l>
3,4-benzofluor anthene< 20 5-99-2>
4,4*-ddd(p,p*tde)<72-54-8>
4,4'-dde(p,p'-ddx<72-55-9>
4,4*-ddt<50-29-3>
4,6-dinitro-o-cresol<534-52-l>
4-bromophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
Total KJeldajl Nitrogen (TKN)
Total Organic Carbon (TOC)
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
ammonia<7664- 41-7>
anthracene<120-12-7>
antimony<7440-36-0>
arsenic<7440-38-2>
asb«stoa<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
benzo (a) anthr acene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo (g,h, Dp eryien«<191-24-2>
benzo()c)f luor anthene< 207-0 8-9>
beryllium<7440-41-7>
bhc (lindane)-gamma<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)ne thane
bis(2-chloroethyl)ether
1032
-------
Accession No. 9028000911
(cont)
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloromethyl)ether<542-S8-l>
brononethane<74-83-9>
butyl benzyl phthalate<85-68-7>
c a daiuuK 7 4 40 - 43- 9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodibrononethane<124-48-l>
chloroethane<75-00-3>
chloroform<67-66-3>
chloronethane<74-87-3>
chro«iua<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
dl-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-Q>
dibenz o( a, h) an thracene<5 3-7 0-3>
dichlorobroiBO«ethane<75-27-4>
dichlorodifluoronethane<75-71-8>
dichloromethane<75-09-2>
dieldrin<60-57-l>
diethyl Phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
dissolved oxygen
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endcsulfan-beta<33213-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fluoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexschlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeno
isopho rone<78-59-l>
(CAS) CAS registry numbers of substances
79-34-5; 79-00-5; 75-34-3; 75-35-4;
lead<7439-92-l>
»ercury<7439-97-6>
n-nitroscdi-n-propylanine
<621-64-7>
n-n i t rosodine thy 1 an ine<62-75-9>
n-nitrosodiphenylaaine<86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nltrobenzene<98-95-3>
nitrogen dioxide and nitrate
nitrogen dioxlde<10102-44-0>
orthophosphate<14265-44-2>
p-chloro-»-cresol<59-50-7>
PH
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-2l-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene< 85-01- 8>
phenol<108-95-2>
pyrene<129-00-0>
selenium<7782-49-2>
silver<7440-22-4>
temperature
tetrachloroethylene<127-l 8-4>
thalliu«<7440-28-0>
toluene<108-88-3>
total phosphate
toxaphene<8001-35-2>
tribrononethane<75-25-2>
trichloroethylene<79-01-6>
trichloro£luorom«thane<75-69-4>
vinyl chloride<75-01-4>
zinc<7440-66-6>
included in data base: 71-55-6
120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-54-8; 72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7;
83-32-9; 208-96-8; 107-02-8; 107-13-1; 309-00-2; 7664-41-7;
1033
-------
Accession Ho. 9028000911 (cont)
120-12-7; 7440-36-0; 7440-38-2; 1332-21-4; 71-43-2; 92-87-5;
56-55-3; 50-32-8; 191-24-2; 207-08-9; 7440-41-7; 58-89-9;
319-84-6; 319-85-7; 319-86-8; 111-91-1; 111-44-4; 39638-32-9;
117-81-7; 542-88-1; 74-83-9; 85-68-7; 7440-43-9; 56-23-5;
57-74-9; 108-90-7; 124-48-1; 75-00-3; 67-66-3; 74-87-3;
7440-47-3; 218-01-9; 7440-50-8; 57-12-5; 84-74-2; 117-84-0;
53-70-3; 75-27-4; 75-71-8; 75-09-2; 60-57-1; 84-66-2; 131-11-3;
1031-07-8; 959-98-3; 33213-65-9; 7421-93-4; 72-20-8; 100-41-4;
206-44-0; 86-73-7; 1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4;
67-72-1; 193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7;
62-75-9; 86-30-6; 91-20-3; 7440-02-0; 98-95-3; 10102-44-0;
14265-44-2; 59-50-7; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 87-86-5;
85-01-8; 108-95-2; 129-00-0; 7782-49-2; 7440-22-4; 127-18-4;
7440-28-0; 108-88-3; 8001-35-2; 75-25-2; 79-01-6; 75-69-4;
75-01-4; 7440-66-6
(CNN) Contact na»e(s): Hemnett,R.; S«ith,B,
(COR) Contact organization: Roland Heaaett, Surveillance & Analysis/
(ROR) Responsible Organization: Region II.Environmental Services
Division.
1034
-------
Accession No. 9028000912
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Passaic River
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Sediment ;Surface
water-river ;Tissue - fish
(ABS) Abstract/Overview of Data Base or Model: This data base contains
water quality and sediment data on the Passaic River. Fish
tissue samples were also collected.
(CTC) CONTACTS: Subject matter Roland Hemmett, Chief Environmental
Svcs. Div. ; Computer-related Archdeacon, Barbara, Data
Handler (201) 321-6787 ; EPA Office Ronald Hemmett, Environmental
Services
(DTP) Type of data collection or monitoring: Ambient data collection
(GRP) Groups of substances represented in Data Base: 129 307 CVA
(NPP) Non-pollutant parameters included in the data base: Location
^Sampling data ;Site description
(DS) Tine period covered by data base: 03-01-81 TO 10-31-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 160(Estimated)
(NEI) Estimated annual Increase of observations in data base: (N/A)
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 19
(NCS) No. stations or sources currently originating/contributing data:
19
(NOF) Number of facilities covered in data base (source monitoring): 0
(GEO) Geographic coverage of data base: Single state New Jersey
(LOG) Data elements identifying location of station or source include:
State >County ^Coordinates latitude/longitude
(FAC) Data elements identifying facility include: Not applicable
(CDE) Pollutant identification data are: Storet parameter
(DpR) Data collect./anal, procedures conform to ORD guidelines: Conform
to ORD QA Guidelines
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory
(PRE) Precision: Precision and accuracy estimates exist for all
measurements
(EOT) Fditting: Edit procedures used but undocumented
(CBY) Data collected by: Regional office-Region II, Environmental
Services Div.
(ABY) Data analyzed by: Regional office-Region II, Environmental
Services Div.
(IDL) Laboratory identification: YES
(AUT) Authorization for data collection: No statutory requirement:
Data collection requirement is dependent on what the state of
New Jersey feels is needed at that time. The state decides what
types of tests are run.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
request
(USR) Current regular users of data base: EPA regional offices
1035
-------
Accession No. 9028000912
(cont)
States
2 agencies
(CNF) Confidentiality of data and Halts on access: Ho limits on
access to data
(DLC) Prinary physical location of data: Regional office
(DST) Form of data storage: STORET
(DAC) Type of data access: EPA software: STORET
(CHG) Direct charge for non-EPA use: Mo
(UPDT) Frequency of data base Master file up-date: Other as necessary
(CNP) Completion of fora:
Randy Braun
OFC: U.S.EPA/ Environmental Services Division/ Region II
AD: Voodbridge Avenue* Edison/ N.J. 08837
PH: (201) 321-6692
(OF) Date of fora conpletion: 01-14-83
(NMAT) Nuaber of substances represented in data base: 143
CNCAS) Nuaber of CAS registry numbers in data base: 131
(MAT) Substances represented in data base:
1, l,l-trichloroethane< 71-55-
6>
l,l,2,2-tetrachloroethane<79-34-5>
l,l,2-trichloroethane<79-00-5>
1, l-dichloroethane<75-34-3>
l,l-dichloroethylene<75-35-4>
l,2,4,-trichlorobenzene<120-82-l>
l,2-dichlorobenzene< 95-50- 1>
I/ 2-di chloro ethane< 1 07-06-2>
If 2-dichloropropane<78-87-5>
If 2-di chloropropyl ene< 563-54-2>
l,2-dlphenylhydrazine
\f 2-trans-dichloroethy lene
<156-60-5>
If 3-dlchlorobenzene<541-73-l>
l,4-dichlorobenzene<106-46-7>
2/ 4,6- trichlorophenoK 88-06- 2>
2f 4flf 8- tetr achlorodibenzo-p-
dioxin (tcdd)
2/ 4-di chlorophenoKl 20 -83-2>
2,4-diaethylphenol<105-67-9>
2f 4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2,6-dinltrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-ni tropheno 1< 88-75-5>
3,3'-dichiorobenzidine<91-94-l>
3
4,4'-ddd(p,p'tde)<72-54-8>
4, 4--dde(p/p*-ddx<72-55-9>
4-bronophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nltrophenol< 100-0 2-7>
Total Kjeldahl Nitrogen (TKN)
Total Organic Carbon (TOC)
Total Suspended Solids (TSS)
acenaphthene<83-32-9>
acenaphtby lene<20 8-96-8 >
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
aaiionia<7664-41-7>
anthracene
ant i«ony<7 440-36-0>
arsenlc<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
beozo(a)anthracene<56-55-3>
benzo(a )pyrene<50-32-8>
benzo(g/h, i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
berylliu»<7440-41-7>
bhc (lindane)-gaa«a<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis (2-chloroethoxy)«e thane
4/6-dinitro-o-cresol<534-52-l>
bis(2-chloroethyl)ether
bis(2-chloroisopropyl)ether
<39638-32-9>
1036
-------
Accession Ho. 9028000912
(cont)
bis(2-ethylhexyl)phthalate
bis(chloro«ethyl)ether<542-88-l>
bronoBethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cad«iura<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorine residuals
chlorobenzene<108-90-7>
chlorodibroRoaethane<124-48-l>
chloroethane<75-00-3>
chlorofor«<67-66-3>
chloronethane<74-87-3>
chro«ium<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenzo( a, h) anthracene<53-70-3>
dichlorobrofflowethane<75-27-4>
dichlorodifluoronethane<75-71-8>
dichloroaethane<75-09-2>
dieldrin<60-57-l>
diethyl phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
dissolved oxygen
endosulfan sulfate<1031-07-8>
endosulf an-alpha< 959-9 8- 8>
endosulfan-beta<33213-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fluoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorob«nzene<118-74-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeno (1, 2,3-cd)pyren«<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
n-nitrosodl-n-propylamine
<621-64-7>
n-nitrosodi»ethyla«lne<62-75-9>
n-nitrosodiphenylamine<86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
ni trobenzene< 98-95-3>
nitrogen dioxide and nitrate
nitrogen dioxide<10102-44-0>
orthophosphate<14265-44-2>
p-chloro-«-cresol<59-50-7>
PH
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
pyrene<129-00-0>
selenium<7782-49-2>
silver<7440-22-4>
tenperature
tetrachloroethylene<127-18-4>
thalliu»<7440-28-0>
toluene<108-88-3>
total dissolved solids
total phosphate
total solids
toxaphene<8001-35-2>
tribrononethane<75-25-2>
trichloroethylene<79-01-6>
trlchlorof luoron«thane<75-69-4>
vinyl chlorid«<75-01-4>
2lnc<7440-66-6>
•ercury<7439-97-6>
(CAS) CAS registry numbers of substances included in data base: 71-55*6
} 79-34*5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2? 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-54-8; 72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7;
1037
-------
Accession No* 9028000912 (cent)
83-32-9; 208-96-8; 107-02-8; 107-13-1; 309-00-2; 7664-41-7;
120-12-7; 7440-36-0; 7440-38-2; 1332-21-4; 71-43-2; 92-87-5;
56-55-3; 50-32-8; 191-24-2; 207-08-9; 7440-41-7; 58-89-9;
319-84-6; 319-85-7; 319-86-8; 111-91-1; 111-44-4; 39638-32-9;
117-81-7; 542-88-1; 74-83-9; 85-68-7; 7440-43-9; 56-23-5;
57-74-9; 108-90-7; 124-48-1; 75-00-3; 67-66-3; 74-87-3;
7440-47-3; 218-01-9; 7440-50-8; 57-12-5; 84-74-2; 117-84-0;
53-70-3; 75-27-4; 75-71-8; 75-09-2; 60-57-1; 84-66-2; 131-11-3;
1031-07-8; 959-98r8; 33213-65-9; 7421-93-4; 72-20-8; 100-41-4;
206-44-0; 86-73-7; 1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4;
67-72-1; 193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7;
62-75-9; 86-30-6; 91-20-3; 7440-02-0; 98-95-3; 10102-44-0;
14265-44-2; 59-50-7; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 87-86-5;
85-01-8; 108-95-2; 129-00-0; 7782-49-2; 7440-22-4; 127-18-4;
7440-28-0; 108-88-3; 8001-35-2; 75-25-2; 79-01-6; 75-69-4;
75-01-4; 7440-66-6
(CNM) Contact na«e(s): Hemett,R.; Archdeacon,B.
(COR) Contact organization: Roland Hewlett, Environmental Services
(ROR) Responsible Organization: Region II.Environmental Services
Division.
1038
-------
Accession No. 9038000528
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: National Pollutant Discharge
Elimination System
(ACR) Acronym of Data Base or Model: SPDES
(MED) Media/Subject of Data Base or Model: Effluents- Industrial &
Municipal
(ABS) Abstract/Overview of Data Base or Model: Data Base consists of
files containing NPDES applications, permits, discharge
nonitoriports (DMR's), inspection reports, and correspondence
regarding waste water discharge.
(DTP) Type of data collection or monitoring: Point source
(STA) Data Base status: Presently operarional/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CMA ; 11
conventional water ; 41 Of A potential criteria
(NPP) Non-pollutant parameters included in the data base: biological
data ; compliance data ; concentration measures ; discharge
points ; flow rates ; industry ; inspection data ; location ;
production levels ; sampling date ; temperature ; treatment
devices or processes ; volume/mass measures
(DS) Tine period covered by data base: 07-71 TO 02-83
(TRM) Termination of data collection: Not anticipated
(FRO) Frequency of data collection or sampling: Other- Varies
according to State & Discharge Type & size
(NOB) Number of observations in data base: l,000,000(Estimated to
(NED Estimated annual increase of observations in data base: 250,000
(INF) Data base includes: Aggregate or summary observations
(NTS) Total number of stations or sources covered in data base: 9000
-------
Accession Ho. 9038000528 (cont)
office ; EPA Lab ; EPA Headquarters
(ABT) Data analyzed by: Self-reporting ? state agency ; regional
office ; EPA Lab ; EPA Headquarters
3,4-Benzofluoranthene <205-99-2>
Acenaphthylene <208-96-8> Benzotk) fluoranthene <207-08-9>
Acrolein <107-02-8> Benio(g,h,i)peryiene <191-24-2>
Acrylonitrile <107-13-1> Benzotaapyrene <50-32-8>
Aldrin <309-00-2> Beryllium <7440-41-7>
Anthracene <120-12-7> Bls(2- chloroethoxy)aethane
Antimony <7440-36-0> <111-91-1>
Arsenic <7440-38-2> Bls(2-chloroethyl)ether
Asbestos <1332-21-4>
BHC-.Alpha. <3l9-84-6> Bls(2-chloroisopropyl)ether
BHC-.Beta. <319-85-7> <39638-32-9>
BHC (lindane)—Gaaaa. <58-89-9> Bis (ctiloroaethyl)ether
BHC-.Delta. <319-86-8> <542-88-l>
Benzene <7l-43-2> Bis(2-ethylhexyl)phthalate
Benzldtne <92-87-5> <117-81-7>
Benzo(a)anthracene <56-SS-3> Broaoaethane <74-83-9>
1040
-------
Accession No. 9038000528
(cont)
4-Bromophenyl phenyl ether
<101-55-3>
Butyl benzyl phthalate <85-68-7>
CadRium <7440-43-9>
Carbon tetrachloride <56-23-5>
Chlordane <57-74-9>
Chlorobenzene <108-90-7>
Chlorodibromomethane <124-48-l>
Chloroethane <75-00-3>
2-chloroethylvinyl ether
<110-75-8>
Chloroform <67-66-3>
p-Chloro-m-cresol <59-50-7>
Chloromethane <74-87-3>
2-Chloronaphthalene <91-58-7>
2-Chlorophenol <95-57-8>
4-Chlorophenyl phenyl ether
<7005-72-3>
Chromium <7440-47-3>
Chrysene <218-01-9>
Copper <7440-50-8>
Cyanide <57-12-5>
4,4*-DDD(p,p'-TDE) <72-54-8>
4, 4*-rDE(p,p'-DDX) <72-55-9>
4,4'-DDT <50-29-3>
Dlbenzota^Manthracene <53-70-3>
Dl-n-butyl phthalate <84-74-2>
1,2-Dichlorobenzene <95-SO-l>
1,3-Dichlorobenzene <541-73-l>
1,4-Oichlorobenzene <106-46-7>
3^3*- Dichlorobenzidine <91-94-l>
Oichlorobromomethane <75-27-4>
Olchlorodifluoromethane <75-71-8>
1^1-Dlchloroethane <75-34-3>
1,2-Dlchloroethane <107-06-2>
1,1-Dichloroethylene <75-35-4>
1,2-trans-Dichloroethylene
<156-60-5>
Olchloromethane <75-09-2>
2,,4-Dichlorophenol <120-83-2>
1^2-Dlchloroi>ropane <78-87-5>
1^2-Dichloropropylene <563-^54-2>
Dieldrin <60-57-l>
Dlethyl phthalate <84-66-2>
2,4- Dimethylphenol <105-67-9>
D lire thy I phthalate <131-ll-3>
4,6-Oinltro-o-cresol <534-52-l>
2,4-Dlnltrophenol <51-28-5>
2/4-Dlnitrotoluene <121-14-2>
2/6-Dlnltrotoluene <606-20-2>
Di-n-octyl phthalate <117-84-0>
1^2-Oiphenylhydrazlne <122-j66-7>
Endosulf an-. Alpha. <959-98-8>
Endosulfan-.Beta. <33213-65-9>
Endosulfan sulfate <1031-07-8>
Endrln <72-20-8>
Endrin aldehyde <7421-93-4>
Ethylbenzene <100-41-4>
Fluor anthene <206-44-0>
Fluorene <86-73-7>
Heptachlor <76-44-8>
Heptachlor epoxide < 102 4-57 -3>
Hexachlorobenzene <118-74-l>
Hexachlorobutadiene <87-68-3>
Hexachlorocyclopentadlene
<77-47-4>
Hex achloro ethane <67-72-l>
Indeno (l,2,3-cd)pyrene <193-39-5>
Isophorone <78-59-l>
Lead <7439-92-l>
Mercury <7439-97-6>
Naphthalene <91-20-3>
Nickel <7440-02-0>
Nitrobenzene <98-95-3>
2-Nitrophenol <88-75-5>
4-Hitrophenol <100-02-7>
N-Nltrosodlnethylanlne <62-75-9>
N-Nltrosodiphenylaraine <86-30-6>
N-Kitrosodi-n- propylamlne
<621-64-7>
Pentachlorophenol <87-86-5>
Phenanthrene <85-01-8>
Phenol <108-95-2>
PCB-1016 (Arochlor 1016)
<12674-ll-2>
PCB-1221 {Arochlor 1221)
<11104-28-2>
PCB-1232 (Arochor 1232)
PCB-1242 (Arochlor 1242)
<53469-21-9>
PCB-1248 (Arochlor 1248)
<12672-29-6>
PCB-1254 (Arochlor 1254)
<11097-69-l>
PCB-1260 (Arochlor 1260)
<11096-82-5>
Pyrene <129-00-0>
Selenium <7782-49-2>
Silver <7440-22-4>
1f \t If 8-t etrachlorodlbenzo-p-
dloxin (TCDO)
1,1/2,2-Tetrachloroethane
<79-34-5>
1041
-------
Accession Ho. 9038000528
(cont)
Tetrachloroethylene <127-18-4>
Thallium <7440-28-0>
Toluene <108-88-3>
Toxaphene <8001-35-2>
Tribroaoaethane <75-25-2>
1,2,4-Trichlorobenzene <120-82-l>
1,1,1-Trichloroethane <71-55-6>
1,1,2-Trichloroethane <79-00-5>
Trichloroethylene <79-01-6>
Trichlorofluoroaethane <75-69-4>
It 4,6- Trichlorophenol
<88-06-2>
?inyl chloride <75-01-4>
Zinc <7440-66-6>
Acidity
Alkalinity
Dissolved Oxygen
Dissolved Solids
Fecal colifora
Nitrogen <7727-37-9>
Oil and Grease
Oxygen deaand
PH
Phosphorus <7723-14-0>
Suspended solids Acetone <67-64-1>
n-alkanes (clO - c30)
Aluiinua <7429-90-5>
Aaaonia <7664-41-7>
Barium <7440-39-3>
Biphenyl <92-52-4>
Bisauth and compounds <7440-69-9>
Boron and compounds <7440-42-8>
Broaine <7726-95-6>
Chlorine <7782-50-5>
2,4-d acid <94-75-7>
Deraeton <8065-48-3>
Dialkyl ethers
Dibenzofuran <132-64-9>
Diphenyl ether <101-84-8>
Fluorides
Guthion <86-50-0>
Iron <7439-89-6>
Kepone <143-50-0>
Lithiun and compounds <7439-93-2>
Malathion <121-75-5>
Manganese and conpounds
<7439-96-5>
Hethoxychlor <72-43-5>
Methyl ethyl ketone (NEK)
<78-93-3>
Mirex <2385-85-5>
Molybdenun and compounds
<7439-98-7>
Nitrates/Nitrites
Nitriloacetates
Parathion <56-38-2>
Phosphorus <7723-14-0>
Polybroninated biphenyls (PBBS)
Secondary aalnes
Sodiua <7440-23-5>
Styrene <100-42-5>
Sulfates
Sulfides
Terpenes
If*r5-Trichlorophenoxypropionic
acid (TP) <93-72-l>
Uraniua <7440-61-1>
Vanadiun <7440-62-2>
Cobalt <7440-48-4>
(CAS) CAS registry nuabers of substances included in data base: 83-32-9
; 208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 319-84-6; 319-85-7; 58-89-9; 319-86-8;
71-43-2; 92-87-5; 56-55-3; 205-99-2; 207-08-9; 191-24-2;
50-32-8; 7440-41-7; 111-91-1; 111-44-4; 39638-32-9; 542-88-1;
117-81-7; 74-83-9; 101-55-3; 85-68-7; 7440-43-9; 56-23-5;
57-74-9; 108-90-7; 124-48-1; 75-00-3; 110-75-8; 67-66-3; 59-50-7;
74-87-3; 91-58-7; 95-57-8; 7005-72-3; 7440-47-3; 218-01-9;
7440-50-8; 57-12-5; 72-54-8; 72-55-9; 50-29-3; 53-70*3;
84-74-2; 95-50-1; 541-73-1; 106-46-7; 91-94-1; 75-27-4; 75-71-8;
75-34-3; 107-06-2; 75-35-4; 156-60-5; 75-09-2; 120-83-2; 78-87-5;
563-54-2; 60-57-1; 84-66-2; 105-67-9; 131-11-3; 534-52-1; 51-28-5;
121-14-2; 606-20-2; 117-84-0; 122-66-7; 959-98-8; 33213-65-9;
1031-07-8; 72-20-8; 7421-93-4; 100-41-4; 206-44-0; 86-73-7;
76-44-8; 1024-57-3; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 91-20-3; 7440-02-0;
98-95-3; 88-75-5; 100-02-7; 62-75-9; 86-30-6; 621-64-7;
1042
-------
Accession No. 9038000528 (cont)
87-86-5; 85-01-8; 108-95-2; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 129-00-0;
7782-49-2; 7440-22-4; 79-34-5; 127-18-4; 7440-28-0; 108-88-3;
8001-35-2; 75-25-2; 120-82-1; 71-55-6; 79-00-5; 79-01-6;
75-69-4; 88-06-2; 75-01-4; 7440-66-6; 7727-37-9; 7723-14-0;
67-64-1; 7429-90-5; 7664-41-7; 7440-39-3; 92-52-4; 7440-69-9;
7440-42-8; 7726-95-6; 7782-50-5; 7440-48-4; 94-75-7; 8065-48-3;
132-64-9; 101-84-8; 86-50-0; 7439-89-6; 143-50-0; 7439-93-2;
121-75-5; 7439-96-5; 72-43-5; 78-93-3; 2385-85-5; 7439-98-7;
56-38-2; 7723-14-0; 7440-23-5; 100-42-5; 93-72-1; 7440-61-1;
7440-62-2
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1043
-------
Accession No. 9038000901
(DQ) Date of Questionaire: 12-02-82
(NAN) Rarae of Data Base of Model: Unleaded Fuel Sanpling Program
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Other gasoline
(ABS) Abstract/Overview of Data Base or Model: Lead content of
unleaded gasoline sold to consumers is the subject of the
contents of this data base.
(CTC) CONTACTS: Subject Batter Steve Copeland (215)597-3989 ;
EPA Office Robert Krame
(DTP) Type of data collection or nonitoring: Combination/Other
gasoline pumps and storage tanks
(STA) Data Base status: Discontinued
(NPP) Non-pollutant parameters included in the data base: Concentration
measures ;Inspect!on data ^Location ^Sampling date ; Site
description
(DS) Time period covered by data base: 01-01-75 TO 09-30-79
(TRM) Termination of data collection: Occurred 09/30/79
(FRQ) Frequency of data collection or sampling: annually
(NOB) Number of observations in data base: 4300.(Estimated)
(NEI) Estimated annual Increase of observations in data base: 0.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 4300.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 43
00.
(GEO) Geographic coverage of data base: Selected federal region Region
III
(LOC) Data elements identifying location of station or source include:
State ;County /City ;Town/township ^Street address ^Project
identifier
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ^Parent corp name
(CDE) Pollutant identification data are: Oncoded
(LIN) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplln
g plan documented ;Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional Office Environmental Services
Division
(ABY) Data analyzed by: Regional Office Environmental Services
Division
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Compliance or enforcement
(AUT) Authorization for data collection: Statutory authorization is P
L 88-206 as amended, Section 223 (Clean Air Act-CAA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
1044
-------
Accession Mo. 9038000901 (cont)
QQ
(REP) Form of available reports and outputs of data base: ray data
(NOS) Number of regular users of data base: 1 office
(DSR) Current regular users of data base: EPA headquarter offices
Mobile Source Division
(CNF) Confidentiality of data and Halts on access: No Halts on
access to data
(DLC) Primary physical location of data: Headquarters office
(DST) Form of data storage: Original fora (hardcopy, readings)
(OAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Other progra*
terminated at Wheeling Office
(CMP) Completion of form:
Steve Copeland
OFC: EPA/Region ill/
Environmental Services Division! AD: 6th & Walnut St.,
Philadelphia, PA I9106f PH: (215)597-3989
(OF) Date of form completion: 01-13-83
(RMAT) Number of substances represented in data base: 12-02-82 l
(ICAS) Number of CAS registry numbers In data base: 12-02-82 1
(MAT) Substances represented In data base:
lead<7439-92-l> .
(CAS) CAS registry numbers of substances included in data base:
(CUM) Contact name(s): Copeland,S. 9 Kramer,R,
(ROR) Responsible Organization: Region III.Environmental Services
Division*
1045
-------
Accession Mo. 9038000903
(DQ) Date of Questionaire: 12-02-82
(RAM) Kane of Data Base of Model: State Intensive Survey Files: MY,
VA, MO, DE, PA, OC
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Effluents Municipal and
industrial ;Surface water estuary stream
(ABS) Abstract/Overview of Data Base or Model: Intensive survey data
that is not stored in STORET is usually included in the States*
reports on intensive surveys which Bust be conducted to support
AWT/AST Justifications and Basic Water Monitoring Program. Most
used to support 201 grants (AWT/AST).
(CTC) CONTACTS: Subject Batter Larry S. Miller, Chief Toxics and
Hater Monitoring Section Region III ; EPA Office Toxics and
Water Monitoring Section, Region III (215) 597-9823
(DTP) Type of data collection or Monitoring: Combination/Other
effluents and receiving streams
(STA) Data Base status: Operational/ongoing
(CRP) Groups of substances represented in Data Base: 11 conventional
water
(NPP) Non-pollutant parameters included in the data base: Biological
data ;Concentration Measures ^Discharge points ;Flou rates }
Location ;Sampling date ;Site description jTenperature ;Volume/aass
measures
(OS) Time period covered by data base: 06-01-78 TO 09-30-82
(TRM) Termination of data collection: Not anticipated
(FRO) Frequency of data collection or sampling: one time only
(HOB) Number of observations in data base: 5000.(Estimated)
(NEI) Estimated annual increase of observations in data base: 2000.
(INF) Data base includes: Raw data/observations ;SuMmary aggregate
observations
(NTS) Total nuMber of stations or sources covered in data base: 300
(estimated).
(NCS) No. stations or sources currently originating/contributing data:
100 (estimated).
(•OF) Number of facilities covered in data base (source Monitoring): 30
(estimated).
(GEO) Geographic coverage of data base: Selected federal region Region
III
(LOG) Data elements identifying location of station or source include:
Hot applicable
(FAC) Data elements identifying facility include: Not applicable
(CDE) Pollutant identification data are: encoded
(LIM) Limitation/variation in data of which user should be aware: Few
observations are made for each survey - only 15 or 20 surveys per
year.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ^Analysis Method documented ;QA procedures
documented
(ANL) Lab analysis based on EPA-approved or accepted Methods? YES
(ADD) Lab Audit: Lab audit Is satisfactory for various labs over
time-recent observations better.
(PRE) Precision: Precision and accuracy estimates exist but are not
1046
-------
Accession Ho. 9038000903 (cont)
included in data base
(EDT) Editting: No known edit procedures exist.
(CBY) Data collected by: State agency States of Vest Virginia,
Virginia/ Maryland, Delaware* Pennsylvani
(ABY) Data analyzed by: State agency States of West Virginia,
Virginia, Maryland, Delaware, Pennsylvania and District of
Columbia
(IDL) Laboratory identification: YES
(ADT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended, Sections 106 and 201 (Clean Water Act-CHA),
Basic Hater Monitoring Program
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Forn of available reports and outputs of data base: Unpublished
reports
(ROS) Number of regular users of data base: 2 EPA Offices, 6 States
(USR) Current regular users of data base: EPA regional offices
States
(CNF) Confidentiality of data and limits on access: Limits on outside
access for some data
(DLC) Primary physical location of data: State agency
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(UPDT) Frequency of data base master file up-date: Annually
(RSS) Related EPA automated systems which use data base: Hater Quality
Models
(RDBEPA) Related EPA data bases used in conjunction with this data base
None
(RDB) Non-EPA data bases used in conjunction with this data base: Hone
(CMP) Completion of form:
John Ruggero
OFC: EPA/Region Ill/Environmental Services Division/Toxics and
Hater Monitoring Section* AD: 6th and Halnuts St., Philadelphia,
PA 19106
PH: (215) 597-9839
(OF) Date of form completion: 01-14-83
(NCAS) Number of CAS registry numbers in data base: 2
(MAT) Substances represented in data base:
alkalinity oxygen demand
dissolved oxygen pH
dissolved solids phosphorus<7723-14-0>
ni trogen<7727-37-9>
(CAS) CAS registry numbers of substances included in data base: 7727-37
-9; 7723-14-0
(CNM) Contact nane(s): John Ruggero
(COR) Contact organization: Toxics and Hater Monitoring Section,
Region III
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1047
-------
Accession No. 9038000904
COQ) Date of Questionaire: 12-02-82
(STATUS) Status of entry: Inactive
(MAM) Nave of Data Base of Model: National Air Sampling Network
(ACR) Acronym of Data Base or Model: NASH
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: Checked operation of
National Air Sampling Network (NASN) sites vhich were run by
states or volunteers. If heeling Field Office (Vest Virginia)
collected filters at end of 12 day (one 24 hour run cycle),
neighed them* and sent them to Research triangle Park, NC.
35-40 stations in the netuorfc collecting particulate and sulfur
dioxide level data.
County ;City ;Tonn/township
(FAC) Data elements identifying facility Include: N/A
(COB) Pollutant identification data are: Saroad parameter
(LIN) Limitation/variation in data of which user should be aware: Hot
all stations had sulfur dioxide (S0(2)). Sulfur dioxide
samples processed by Annapolis.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplln
g plan documented ^Collection method documented ^Analysis method
document QA procedures documented
(AM.) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Local agency various agency volunteers ;State
agency various agency volunteers
(ABY) Data analyzed by: EPA lab Region III Surveillance and Analysis
Division, Research Triangle Park and Annapolis Field Office*
(IDL) Laboratory identification: YES
1048
-------
Accession No. 9038000904 (cont)
(PR1) Primary purpose of data collection: Development of regulations
or standards
(PR2) Secondary purpose of data collection: Program evaluation
(AUT) Authorization for data collection: Statutory authorization is P
L 88-206 as amended/ Section 309 (Clean Air Act-CAA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
request
raw data
(KUS) Number of regular users of data base: 8
(USR) Current regular users of data base: EPA headquarter offices
Office of Air Quality Planning and Standards
States
(CNF) Confidentiality of data and limits on access: Ho limits on
access to data
(DLC) Primary physical location of data: Headquarters office
(DST) Form of data storage: Magnetic tape
(DAC) type of data access: EPA software SAROAD NIDS:4504000918 ;EPA
hardware UNIVAC 1110
(OPDT) Frequency of data base master file up-date: Monthly OFC:
EPA/Region Ill/Surveillance and Analysis Division/Wheeling Field
AD: 303 Methodist Bldg. llth and Champline Streets Wheeling, ¥?
26003 PH: (304) 923-1049
(DF) Date of form completion: 01-28-83
(NMAT) Number of substances represented in data base: 2
(NCAS) Number of CAS registry numbers in data base: 1
(MAT) Substances represented in data base:
sulfur dioxide<7446-09-5> total suspended particulates
(CAS) CAS registry numbers of substances included in data base: 7446-09
-5
(CNM) Contact name(s): 0*Brien,D.
(COR) Contact organization: Air Quality Monitoring Branch Region III
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1049
-------
Accession No. 9038000905
(DQ) Date of Questionalre: 12-02-82
(HAN) Name of Data Base of Model: Waste Load Allocation-Model
Verification
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Effluents municipal sewage
treatment plants ^Surface Hater receiving streams (ri
(ABS) Abstract/Overview of Data Base or Model: Data in this data base
is derived from verifying waste load allocations and sampling
river reach upstream and downstream over 3-4 day periods.
Three to five different plants per year-1 tine per plant-were
sampled.
(CTC) CONTACTS: Subject matter Dale Wismer (215)597-9991 ; EPA
Office Technical Assista
(DTP) Type of data collection or Monitoring: Combination/Other ambient
& point source (municipals)
(STA) Data Base status: Funded for development
(OPO) Projected operational date of Data Base: 09-00-79
(GRP) Groups of substances represented in Data Base: 11 conventional
water
(MPP) Non-pollutant parameters included in the data base: Chemical
data ^Concentration measures ;Flow rates ;Inspection data ;
Location ;Sampling date ;Site description ;ti»e data ;travel data
(DS) Time period covered by data base: 01-01-77 TO 09-30-79
(TRM) Termination of data collection: Occurred 09/30/79
(FRQ) Frequency of data collection or sampling: as needed
(ROB) Number of observations in data base: 3426.(Estimated)
(INF) Data base Includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 65
((approximately).)
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(HOP) Number of facilities covered in data base (source monitoring): 7.
(GEQ) Geographic coverage of data base: Geographic region West
Virginia, Western Pennsylvania, Southwest Virginia
(LOC) Data elements identifying location of station or source include:
State /County ^Coordinates latitude/longitude and river mile points
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ;NPDES
(CDE) Pollutant identification data are: Storet parameter
(LiM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samp1in
9 plan documented Collection method documented ;Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory for .
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance Analysis
Division, Wheeling Field Office, Region I
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division, Wheeling Field Office, Region III
1050
-------
Accession No. 9038000905 (cont)
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Development of regulations
or standards
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 Sections 208 and 303 (Clean Mater Act-CHA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Forn of available reports and outputs of data base: Trip reports
and tabulated raw data
(NUS) Number of regular users of data base: 3
(USR) Current regular users of data base: EPA regional offices
States
(CNF) Confidentiality of data and Units on access: No Halts on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other As requested
(RDBEPA) Related EPA data bases used in conjunction with this data base
Storage and Retrieval of Hater Quality Data (STORET)
(RDB) Non-EPA data bases used in conjunction with this data base: U.S.
Geological Survey: Stream Flow Data (if available).
(CMP) Completion of form:
John Ruggero
OFC: EPA/Region III/
Environmental Services Division^ AD: 6th & Walnut St.,
Philadelphia, PA 19106# PH: (215)597-9839
(DF) Date of form completion: 02-24-83
(NMAT) Number of substances represented in data base: 7
(MCAS) Number of CAS registry numbers in data base: 12-02-82 1
(MAT) Substances represented in data base:
acidity nitrogen<7727-37»9>
alkalinity oxygen demand
dissolved oxygen pH
dissolved solids
(CAS) CAS registry numbers of substances included in data base: 7727-37
-9
(CNM) Contact name(s): Hismer,D.
(COR) Contact organization: Technical Assistance and Special Program
Section,
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1051
-------
Accession No. 9038000910
(DQ) Date of Questionaire: 12-02-82
(NAM) Naae of Data Base of Model: Spill Report Date Base
(ACR) Acronym of Data Base or Model: WILBUR
(MED) Media/Subject of Data Base or Model: Other Spills
(ABS) Abstract/Overview of Data Base or Model: This data base is a
record of spills reported to EPA and includes information on
quantity and type of pollutant spilled, the discharger, and Spill
Prevention Control and Counteraeasure Systea (SPCCS) inforaation/
if appropriate. WILBUR, a national systea, is concerned only with
oil spills; however, Regional Manual Logs include oil and
hazardous waste spills. Data Regional Logs are used as input to
WILBUR.
(CTC) CONTACTS: Subject Batter Vivienne Villiaas 215-597-4554 ;
Coaputer-related Oil
(DTP) Type of data collection or aonitoring: Coablnation/Other Spills
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant paraaeters included in the data base: Industry
^Location ;Voluae/aass aeasures Jpollutant type
(DS) Tiae period covered by data base: 01-01-71 TO 09-30-81
(TRM) Teraination of data collection: Not anticipated
(FRQ) Freguency of data collection or saapling: as needed
(MOB) Nuaber of observations in data base: 11217.(Actual)
(NED Estiaated annual increase of observations in data base: 1998.
(IMF) Data base includes: Raw data/observations
(NTS) Total nuaber of stations or sources covered in data base: 11217.
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(NOF) Nuaber of facilities covered in data base (source aonitoring): (N
/A.)
(CEO) Geographic coverage of data base: Selected federal region Region
III
(LOC) Data eleaents identifying location of station or source include:
State jCounty ;City
(FAC) Data eleaents identifying facility include: Plant facility name
;plant location ^Street address jcase nuaber
(CDE) Pollutant identification data are: Oncoded
(LIM) Liaitation/variation in data of which user should be aware: Hazar
dous waste spills beginning in March 1978. Oil spill data since
1971. FY 1980 spills (1820) included
79.6% oil spills, 6.4% PCB spills, 14% other hazardous waste
spills. Not all spills require lab analysis. Where required,
analysis is done by EPA labs (covered by quality assurance) or
non-EPA labs (quality assurance is covered by a national
prograa.)
(EOT) Emitting: HO known edit procedures exist.
(CBY) Data collected by: Self reporting anyone seeing a spill or its
effects ;Local agency various ones a State agency various ones
^citizens seeing spill take place or its effects
(ABY) Data analyzed by: Regional office Region III
(IDL) Laboratory identification: MO
(PR1) Priaary purpose of data collection: Coapliance or enforceaent
(PR2) Secondary purpose of data collection: Prograa evaluation
1052
-------
Accession No. 9038000910 (cont)
(AOT) Authorization foe data collection: Statutory authorization is P
L 92-500 as amended. Section 311 (Clean Water Act) Monitor against
Spill Prevention Control and Countermeasure system (SPCCS) plan;
and log phone calls in compliance with 24 hour access phone
required in President's Contingency Plan
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Manual Logs of Spills
Printouts on request
(MUS) Number of regular users of data base: 2 offices
(OSR) Current regular users of data base: EPA headquarter offices Oil
and Special Materials Control Division (oil portion)
EPA regional offices
(CNF) Confidentiality of data and Halts on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office ^Headquarters
office
(DST) For* of data storage: Original fora (hardcopy/ readings)
(OAC) type of data access: EPA software WILBUR (for Spill Prevention
Control and Countermeasure System) ; Manually: hazardous waste
portion
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Quarterly
(RSS) Related EPA automated systems which use data base: Spill
Prevention Control and Countermeasure System (SPCCS)
(CMP) Completion of form:
Bruce Smith
OFC: EPA/Region Ill/Environmental Services Division* AD: 6th &
Walnut Philadelphia, PA 19106
PH: (215) 597-9075
(DF) Date of form completion: 01-28-83
(NMAT) Number of substances represented in data base: 2
(MAT) Substances represented in data base:
oil and grease polychlorinated biphenyls (PCBs)
(CNM) Contact name(s): 215,B.P. ; DIvision,O.S.
(COR) Contact organization: Oil and Special Materials Control Division
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1053
-------
Accession No. 9038000911
CDQ) Date of Questionaire: 12-02-82
(HAM) Nave of Data Base of Model: Potomac River
(ACR) Acronym of Data Base or Model: None
(MED) Podia/Subject of Data Base or Model: Surface water estuary and
river
CABS) Abstract/Overview of Data Base or Model: Long tern uater quality
monitoring of the Potomac River and estuary for nutrient
cheatstry, selected physical, chemical, and biological parameters.
Data includes some fresh water and sewage treatment plant
sampling also.
(CTC) CONTACTS: Subject matter Orterio filla. Jr. (301) 224-2740
} Computer-related M
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Terminated 09/30/81
(GRP) Groups of substances represented in Data Base: 11 conventional
water
(NPP) Non-pollutant parameters Included in the data base: Biological
data ;Chemical data ;Salinity ^Sampling date ;Site description /
Temperature ^Physical data
(OS) Time period covered by data base: 06-01-65 TO 09-30-81
(TRM) Termination of data collection: Hot anticipated
(FRO) Frequency of data collection or sampling: monthly ;as needed
;Qther monthly, plus various special studies.
(HOB) Number of observations in data base: 135000.(Estimated)
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 30.
(NCS) No. stations or sources currently originating/contributing data:
22.
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: Geographic region Potomac
Estuary
(LOG) Data elements identifying location of station or source include:
State ^Coordinates Latitude/longitude
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
Oneoded
(LIM) Limitation/variation in data of which user should be aware: Frequ
ency of sampling varies year to year; not all stations sampled
each year; light studies in 1978-80.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base Edit data since 1972 has more complete
editing and quality control.
(CBY) Data collected by: EPA lab Central Regional Lab-Region III
(ABY) Data analyzed by: EPA lab Central Regional Lab-Region III
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Trend assessment
1054
-------
Accession Ho. 9038000911 (cont)
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended (Clean Mater Act-CWA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Publications
Technical Reports of Region III, Central Regional Laboratory
printouts on request
(NOS) Number of regular users of data base: 50
(USR) Current regular users of data base: EPA regional offices
EPA laboratories
Other federal agencies
States
research institutes
(CNF) Confidentiality of data and Units on access: No limits on
access to data
(DLC) primary physical location of data: EPA lab
(DST) Fora of data storage: Magnetic tape
(DAC) Type of data access: EPA software STORET HIDS:5303000101 ;EPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Annuallyeg
(RDBEPA) Related EPA data bases used in conjunction with this data base
STORET (Storage and Retrieval of Mater Quality Data)
(ROB) flon-EPA data bases used in conjunction with this data base: Resea
rch Institutions in Delaware and Chesapeake Bay areas; U.S.
Geological Survey, Hater Resources Division-National Hater Data
Storage and Retrieval System (HATSTORE)
(ODB) Other pertinent non-EPA data bases: States of Maryland and
Virginia
(CMP) Completion of fora:
Dan Donnelly
OFC: EPA/Region Ill/Central Regional Laboratory
Annapolis/Surveillance and Analysis Division
AD: 839 Bestgate Road Annapolis, MD 21401
PH: (301) 224-2740
(DP) Date of for* completion: 01-19-83
(HMAT) Number of substances represented in data base: 22
(NCAS) Number of CAS registry numbers in data base: 2
(NAT) Substances represented in data base:
acidity algal identifications
alkalinity chlorophyll
dissolved oxygen photometry
dissolved solids photosynthetic rate
fecal coliform polonium 210
nitrogen<7727-37-9> respiration rate
oxygen demand secchi disk
pH total carbon (TO
phosphorus<7723-14-0> total coliform
suspended solids total organic carbon (TOO
NBOD turbidity
(CAS) CAS registry numbers of substances included in data base: 7727-37
-9; 7723-14-0
1055
-------
Accession No. 9038000911 (cont)
£onta<* na»e
-------
Accession No. 9038000912
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Delaware River Estuary
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Surface Hater estuary
(ABS) Abstract/Overview of Data Base or Model: The Delauare Estuary
Mater Quality Study uas a three year study of nutrients, oxygen
demand, and selected physical and chemical paraaeters in
estuarine portion of the river.
(CTC) CONTACTS: Subject natter Leo Clark (301) 224-2740 ;
Computer-related Central Reg
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Discontinued
(GRP) Groups of substances represented in Data Base: 11 conventional
water
(NPP) Non-pollutant parameters included in the data base: Biological
data ;Chemical data ^Location ;Salinity ;Sampllng date / Site
description ;Temperature ^Physical data
(DS) Time period covered by data base: 04-01-74 TO 12-30-78
(TRM) Termination of data collection: Occurred 12/30/78
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 13700.(Estimated)
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 180.
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: Geographic region Delauare
River
(LOC) Data elements identifying location of station or source include:
State Coordinates latitude/longitude
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: Three
year study of selected stations of Delauare estuary monthly during
growing season; seasonally in remainder of year.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented ;Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used and documented.
-------
Accession No. 9038000912 (cont)
(REP) Form of available reports and outputs of data base: Publications
Technical Reports of Region III, Central Regional Lab.
Printouts on request
(BUS) Dumber of regular users of data base: 40
(USR) Current regular users of data base: EPA regional offices
Other federal agencies
States
Research Institutions
(CNF) Confidentiality of, data and Units on access: No limits on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Magnetic tape
secchi disk
oxygen demand total carbon (TC)
pH total coliform
phosphorus<7723-14-0> total organic carbon (TOO
suspended solids
(CAS) CAS registry numbers of substances included in data base: 7727-37
-9; 7723-14-0
(CUM) Contact name(s): Clark/L. ; Lab,C.R. ; Lab,C.R.
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1058
-------
Accession No. 9038000913
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model; Chesapeake Bay
(ACR) Acronym of Data Base or Model: None
(NED) Media/Subject of Data Base or Model: Surface water estuary
CABS) Abstract/Overview of Data Base or Model: Long term water quality
monitoring of upper Chesapeake Bay for nutrient chemistry and
selected physical, biological, and chemical parameters.
CCTC) CONTACTS: Subject matter Orterio Villa, Jr. (301) 224-2740
; Computer-related S
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Terminated 09/79
(GRP) Groups of substances represented in Data Base: 11 conventional
water
(NPP) Non-pollutant parameters included in the data base: Biological
data ;Chemical data ^Location ^Physical data ;Salinity ;
Sampling date /Site description ;Temperature
(DS) Time period covered by data base: 04-01-67 TO 09-30-79
(TRM) Termination of data collection: Occurred 07/30/79
(FRQ) Frequency of data collection or sampling: monthly ;as needed
;0ther monthly, plus various special studies
(NOB) Number of observations in data base: 145000.(Estimated)
(NEI) Estimated annual increase of observations in data base: 0.
(INF) Data base includes: Ran data/observations
(NTS) Total number of stations or sources covered in data base: 65.
(NCS) No. stations or sources currently originating/contributing data:
25.
(NOF) *Number of facilities covered in data base (source monitoring): (N
/*•> ...
(GEO) Geographic coverage of data base: Geographic region upper
Chesapeake Bay
(LOC) Data elements identifying location of station or source include:
State Coordinates Latitude and longitude
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
Uncoded
(LIM) Limitation/variation in data of yhich user should be aware: Frequ
ency of sampling varies year to year; not all stations sampled
each year; light studies in 1978-79.
(DPR) Data collect./anal, procedures conform to CRD guidelines: Saaplin
g plan documented ;Collection method documented ;Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base Edit data since 1972 has more complete
editing and quality control..
(CBY) Data collected by: EPA lab Central Regional Lab - Region III
(ABY) Data analyzed by: EPA lab Central Regional Lab - Region III
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Trend assessment
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended (Clean Water Act)
1059
-------
Accession No. 9038000913 (cont)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ - lab sheets used
(REP) Fora of available reports and outputs of data base: Publications
Technical Reports of Region III* Central Regional Lab.
Printouts on request
(HOS) Vunber of regular users of data bases 50
(OSR) Current regular users of data base: EPA regional offices
EPA laboratories
Other federal agencies
States
research institutes
(CHF) Confidentiality of data and limits on access: Mo 1inits on
access to data
(DLC) priaary physical location.of data: EPA lab
(DST) Fora of data storage: Magnetic tape
(DAC) Type of data access: EPA software STORET «IDS:5303000101 ;EPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Annuallyeg
(RDBEPA) Related EPA data bases used in conjunction with this data base
STORET (Storage and Retrieval of Hater Quality Data)
(ROB) Hon-EPA data bases used in conjunction with this data base: Resea
rch institutions in Delaware and Chesapeake Bay area; U.S.
Geological Surveys/ Mater Resource Division - National Water
Data Storage and Retrieval Systea (HATSTORE)
(ODB) Other pertinent non-EPA data bases: States of Maryland and
flrglnia
(CMP) Completion of fora:
Dan Donnelly ,. .
OFC: EPA/Region Ill/Central Regional Laboratory-Annapolis/
Surveillance and Analysis Division
AD: 839 Bestgate Road Annapolis/ MD 21401
PH: (301) 224-2740
(DF) Date of fora completion: 01-19-83
(RMAT) Muaber of substances represented in data base: 16
(•CAS) Muaber of CAS registry numbers in data base: 2
(MAT) Substances represented in data base:
HBOD
algal identifications
dissolved oxygen
dissolved solids
fecal colifora
ni trogen<7727-37-9>
oxygen demand
PH
phosphorus<7723-14-0>
polonium 210
respiration rate
seechi disk
suspended solids
total coliform
total organic carbon (TOC)
1060
-------
Accession Mo. 9038000913 (cont)
turbidity
(CAS) CAS registry numbers of substances included In data base: 7727-37
-9; 7723-14-0
(CNN) Contact naae(s): Vllla,0. ; Couger*S. ; Lab,C.R.
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1061
-------
Accession No. 9038000914
(DQ) Date of Questionaire: 12-02-82
(8AM) Mane of Data Base of Model: Ocean Dmping
(ACR) Acronym of Data Base or Model: None
(MED) Pedia/Subject of Data Base or Model: Surface water narine
(ABS) Abstract/Overview of Data Base or Model: Environmental surveys
of ocean dump sites off aid- Atlantic coast of U.S. are the
sources of the contents of this data base.
(CTC) CONTACTS: Subject matter Donald Lear (301) 224-2746; EPA
Office Region III Philad
(DTP) Type of data collection or nonitoring: Ambient data collection
(STA) Data Base status: Terminated 09/30/81
(NPP) Non-pollutant parameters included in the data base: Biological
data ;Chemlcal data ^Location ;Salinity ;Temperature ; secchi disk
;benthic invertebrates >Sediment size ;bacteriological data
(DS) Time period covered by data base: 06-01-73 TO 09-30-81
(TRM) Termination of data collection: Occurred 09/30/81
(FRQ) Frequency of data collection or sampling: semi annually ;as
needed
(NOB) Number of observations in data base: 43500.(Estimated)
(INF) Data base includes: Ran data/observations ^Summary aggregate
observations ;Reference data/citations
(NTS) Total number of stations or sources covered in data base: 200.
(NCS) No. stations or sources currently originating/contributing data:
150.
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: Geographic region coastal
mid-Atlantic area
(LOC) Data elements identifying location of station or source include:
Coordinates
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
Uncoded
(LIM) Limitation/variation in data of vhich user should be auare: Data
from various laboratories documented in survey reports. Some
pollutant data coded with STORET codes and other data is not
coded at all.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ^Collection method documented ;Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Regional office Region III Ocean Dumping
Program
(ABY) Data analyzed by: Regional office Region III Central Regional
Laboratory
(IDL) Laboratory identification: YES
(AUT) Authorization for data collection: Statutory authorization is P
L 92-532 (Marine Protection, Research and Sanctuaries Act of 1972)
1062
-------
Accession No. 9038000914 (cont)
(OMB) Data collected/submitted using OMB-approved EPA reporting foras:
QQ
(REP) Form of available reports and outputs of data base: Publications
Technical Reports of Region III
(NOS) Nuaber of regular users of data base: 50
(USR) Current regular users of data base: EPA regional offices
EPA laboratories
Other federal agencies
States
research institutes
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(OLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Annually
(ODB) Other pertinent non-EPA data bases: Oceanographic Research
Institutes in the Middle Atlantic area.
(CMP) Completion of form:
Dan Donnelly
OFC: EPA/Region Ill/Central Regional
Laboratory-Annapolis/Surveillance
and Analysis Division
AD: 839 Bestgate Road, Annapolis, MD 21401
PH: (301) 224-2740
(DF) Date of form completion: 01-19-83
(NMAT) Number of substances represented in data base: 13
(RCAS) Number of CAS registry numbers in data base: 9
(MAT) Substances represented in data base:
zinc<7440-66-6> aercury<7439-97-6>
cad«ium<7440-43-9> nickel<7440-02-0>
chromiura<7440-47-3> polychlorinated biphenyls (PCBs)
copper<7440-50-8> silver<7440-22-4>
dissolved oxygen total carbon (TO
iron<7439-89-6> total organic carbon (TOO
lead<7439-92-l> ,,^A
(CAS) CAS registry numbers of substances included in data base: 7440-66
-6> 7440-43-9; 7440-47-3; 7440-50-8; 7439-89-6; 7439-92-1;
7439-97-6; 7440-02-0; 7440-22-4
(CNM) Contact narae(s): Lear,D. ; Philadelphia,R.I.
(ROR) Fesponsible Organization: Region III.Environmental Services
Division.
1063
-------
Accession Wo. 9038000915
(DQ) Date of Questions!re: 12-02-82
(NAN) Mate of Data Base of Model: Dredging-Special Studies Metals
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Sediment
(ABS) Abstract/Overview of Data Base or Model: Elizabeth River and
Baltimore Harbor grid sampling for metals in sediments.
(CTC) CONTACTS: Subject natter P.C. Johnson (301) 224-2740 ;
EPA Office Central Regi
(DTP) Type of data collection or Monitoring: Ambient data collection
(STA) Data Base status: Discontinued
(IfPP) Non-pollutant parameters included in the data base: Location
;Sampling date ;Site description ;Test/analysis method
(DS) Time period covered by data bases 09-01-74 TO 04-30-75
(TRM) Termination of data collection: Occurred 04/30/75
(FRQ) Frequency of data collection or sampling: one time only
(NOB) Number of observations in data base: 2700.(Estimated)
(NED Estimated annual increase of observations in data base: 0.
(IMF) Data base includes: Raw data/observations ; Summary aggregate
observations ;Reference data/citations
(NTS) Total number of stations or sources covered in data base: 272.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: Geographic region Baltimore
Harbor; Elizabeth River/Hampton Roads/ Virginia
(LOG) Data elements identifying location of station or source include:
State jmaps in reports
(FAC) Data elements identifying facility include: N/A
(CDS) Pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of Which user should be anare: Hone
(DPR) Data collect./anal, procedures conform to QRD guidelines: Samplin
g plan documented Collection method documented ^Analysis method
document QA procedures documented
(AML) Lab analysis based on EPA-approved or accepted methods? YES
(PRB) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Edittlng: Edit procedures used and documented*
(CBT) Data collected by: EPA lab Central Regional Lab, Region III
(AST) Data analyzed by! EPA lab Central Regional Lab/ Region III
(IDL) Laboratory identification: YES
(AOT) Authorization for data collection: Statutory authorization is P
L 95-217 (Clean Hater Act of 1977) Statutory authorization is P L
91-611 (River and Harbor Act of 1970)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ-laboratory sheet* used
(REP) Form of available reports and outputs of data base: Publications
Annapolis Field Office Technical Reports not. 59 & 61
(•OS) Mumber of regular users of data base! 30
(OSR) Current regular users of data base: EPA regional offices
Other federal agencies
States
research institutes
1064
-------
Accession No. 9038000915 (cont)
(CNF) Confidentiality of data and liaits on access: Ho Units on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other None - study
completed
(CMP) Completion of form:
Dan Donnelly
OFC: EPA/Region Ill/Central Regional Lab Annapolis/
Surveillance and Analysis Division
AD: 639 Bestgate Road Annapolis, MD 21401
PH: (301)224-2740
(DF) Date of form completion: 01-19-83
(NMAT) Number of substances represented in data base: 15
(NCAS) Number of CAS registry numbers in data base: 11
(MAT) Substances represented in data base:
cadmium<7440-43-9> nickel<7440-02-0>
chemical oxygen demand (COD) oil and grease
chrc»ium<7440-47-3> silver<7440-22-4>
copper<7440-50-8> total organic carbon (TOO
iron<7439-89-6> total volatile solids
lead<7439-92-l> trihaloaethanes
raanganese<7439-96-5> zinc<7440-66-6>
raercury<7439-97-6>
(CAS) CAS registry numbers of substances included in data base: 7440-43
-9; 7440-47-3; 7440-50-8; 7439-89-6; 7439-92-1; 7439-96-5;
7439-97-6; 7440-02-0; 7440-22-4; 7440-66-6
(CNM) Contact name(s): Johnson^P.G. ; LabsC.R.
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1065
-------
Accession No. 9038000916
-------
Accession No. 9038000916 (cont)
(NUS) Number of regular users of data base: 2
(USR) Current regular users of data base: EPA laboratories
(CNF) Confidentiality of data and Units on access: No limits on
access to data
(DLC) primary physical location of data: EPA lab
(DST) Forra of data storage: Original form (hardcopy/ readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Other discontinued
sampling
(ODB) Other pertinent non-EPA data bases: State drinking water data
(CMP) Completion of form:
Dan Donnelly
OFC: EPA/Region Ill/Central Regional Lab-Annapolis/
Surveillance and Analysis Division
AD: 839 Bestgate Road Annapolis, MD 21401
PH: (301)244-2740
(DF) Date of form completion: 01-19-83
(NMAT) Number of substances represented in data base: 13
(NCAS) Number of CAS registry nuabers in data base: 9
/MAT) Substances represented in data base:
arsenic<7440-38-2> microbiology coliform bacteria
bariu«<7440-39-3> nitrate<14797-55-8>
cadnium<7440-43-9> residual chloride
chromiua<7440-47-3> seleniua<7782-49-2>
fluoride silver<7440-22-4>
lead<7439-92-l> turbidity
mercury<7439-97-6>
(CAS) CAS registry numbers of substances included in data base: 7440-38
-2; 7440-39-3; 7440-43-9; 7440-47-3; 7439-92-1; 7439-97-6;
14797-55-8; 7782-49-2; 7440-22-4
(CNM) Contact naae(s): Villa,0. ; Lab,C.R.
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1067
-------
Accession So, 9038010902
(DQ) Date of Questionaire: 12>02-82
(HAN) Kame of Data Base of Model: national Pollutant Discharge
Elimination System (NPDES) Perait Compliance
(ACR) Acronym of Data Base or Model: NPDES
(MED) Media/Subject of Data Base or Model: Effluents industrial and
•unicipal jSurface water receiving
(ABS) Abstract/Overview of Data Base or Model: Data from compliance
inspections of discharging facilities comprise the NPDES data
base.
(CTC) CONTACTS: Subject matter Orterlo filla, Jr. (301) 224-2740
; Computer-related N
(DTP) Type of data collection or monitoring: Combination/Other
effluents and receiving stream
(STA) Data Base status: Operational/ongoing
(CRP) Groups of substances represented in Data Base: 11 conventional
water ;15 metals
(HPP) lion-pollutant parameters included in the data base: Chemical
data ;Collection method ;flow rates flnspectiondata ; Location
^Manufacturer ;Physical data ^Political subdivisions ; Production
levels ;Sampling date ;Slte description ^Temperature >
Treatment devices ;Yolume/mass measures
(DS) Time period covered by data base: 09-01-74 TO 12-31-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(ROB) Number of observations in data base: 15000.(Estimated)
(IMF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 650.
(NCS) So. stations or sources currently originating/contributing data:
(not available.)
(NOF) Number of facilities covered in data base (source monitoring): 19
0.
(GEO) Geographic coverage of data base: Selected federal region Region
III
(LOC) Data elements identifying location of station or source include:
State ;City ;Town/township ^street address ;Project identifier
(FAC) Data elements identifying facility include: Plant facility name
;PIant location ;NPDES
(CDE) Pollutant identification data are: Storet parameter
(LlM) Limitation/variation in data of which user should be aware: Param
eters vary from site to site* Frequency is irregular and depends
on program needs of Enforcement Division*
(OPR) Data collect./anal, procedures conform to CRD guidelines: Collect
ion method documented >Analysis method documented ;QA procedures
document
(AND Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(BUT) Editting: Fdit procedures used and documented.
(CBY) Data collected by: Regional office Central Regional
Lab-Annapolis, Surveillance and Analysis Division Region III
(ABY) Data analyzed by: Regional office Central Regional
1068
-------
Accession No. 9038010902 (cont)
Lab-Annapolis, Environmental Services Division, Region III.
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Compliance or enforcement
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended, Sections 308 and 402 (Clean Water Act-CMA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Facility
Inspection Reports
(NUS) Number of regular users of data base: 157
(OSR) Current regular users of data base: EPA regional offices
States
permittees
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other as requested
by Enforcement Division
(ROB) Non-EPA data bases used in conjunction tilth this data base: State
and Permittee Data Bases
(OOB) Other pertinent non-EPA data bases: State and Remitter effluent
data
(CMP) completion of form:
Dan Donnelly
OFC: EPA/Region Ill/Central Regional Lab-Annapolis
AD: 839 Bestgage Road, Annapolis, MD 21401
PH: (301) 224-2740
(DF) Date of form completion: 01-19-83
(NMAT) Number of substances represented in data base: 32
(NCAS) Number of CAS registry numbers in data base: 17
(MAT) Substances represented In data base:
acidity fluoride
alkalinity iron<7439-89-6>
dissolved oxygen lead<7439-92-l>
dissolved solids «ercury<7439-97-6>
fecal coliform nlckel<7440-02-0>
nltrogen<7727-37-9> phenols
oil and grease sulfur and compounds
oxygen demand tltanlu«<7440-32-6>
pH vanadiun<7440-62-2>
phosphorus<7723-14-0> a««ooia<7664-41-7>
suspended solids benztnt<71-43-2>
arsenic<7440-38-2> chlorine
b"Jlllum <7782-50-S nitrat«<14797-55-8>
<7440-41-7 chro«tu«<7440-47-3> suifates
copper<7440-50-8> sulfides
-------
Accession No. 9038010902 (cent)
7439-92-1; 7439-97-6; 7440-02-0; 7440-32-6; 7440-62-2;
7664-41-7; 71-43-2; 7782-50-5
(CRN) Contact nane(s): ?illa,0. ; Lab,C.R.
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1070
-------
Accession No. 9038010906
(DQ) Date of Questionaire: 12-02-82
(NAM) Same of Data Base of Model: Priority Pollutants
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Effluents municipal and
industrial ;Sediient ;Surface water rivers ; Tissue fish and
shellfish
(ABS) Abstract/Overview of Data Base or Model: Support of Effluent
Guidelines Program and Monitoring and Data Support Division (MDSD)
Anbient Program-Risk Assessment? guideline developnent.
(CTC) CONTACTS: Subject natter Orterio Villa, Jr. (301) 224-2740
; Computer-related Envir. Services Div., Central Reg. ; EPA
Office Central Regional Lab-Annapolis, Region III (301)
(DTP) Type of data collection or monitoring: Combination/Other Anbient
and municipal and industrial effluents and receiving water.
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CW.A
(NPP) Non-pollutant parameters included in the data base: Discharge
points ;Flow rates ;Industry ;Location ^Production levels ;
Sampling date ;Site description ;Temperature ;Treatnent devices
(DS) Time period covered by data base: 01-01-78 TO 12-31-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: one time only
(NOB) Number of observations in data base: 28000.(Estimated)
(NED Estimated annual increase of observations in data base: 500.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: ISO.
(NCS) No. stations or sources currently originating/contributing data:
l(/facility.)
(NOF) Number of facilities covered in data base (source monitoring): 15
(GEO) Geographic coverage of data base: Selected federal region Region
(LOC) Data elements identifying location of station or source include:
State ;City }town/township ^Street address Coordinates
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ;NPDES
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to CRD guidelines: Samplin
g plan documented Collection method documented ;Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(AOD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EDT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office ESD, Central Regional
Lab-Annapolis, Region III. ^Contractor lab various under contract
to Effluent Guidelines Division
(ABY) Data analyzed by: Regional office ESD, Central Regional
Lab-Annapolis, Region III
(IDL) Laboratory identification: YES
1071
-------
Accession No. 9036010906
(cont)
(PR1) Primary purpose of data collection: Development of regulations
or standards
(PR2) Secondary purpose of data collection: Risk assessment
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500, Section 307 (Clean Water Act-CWA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: On-line
computer
Lab Data Sheets
(BOS) number of regular users of data base: 6
(OSR) Current regular users of data base: EPA headquarter offices
Effluent Guidelines Division
States
(CMP) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for some data
(DLC) Primary physical location of data: EPA lab ;Headquarters office
(DST) Form of data storage: Magnetic tape ;Original form (hardcopy,
readings)
(DAC) Type of data access: Manually JEPA softuare STORET
MIDS:5303000101 ;EPA hardware IBM 370/168
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Annuallyna
(CMP) Completion of form:
Dan Donnelly
OFC: EPA/Region Ill/Central Regional Lab-Annapolis/Surveillance and
Analysis Division
AD: 839 Bestgate Road, Annapolis, MD 21401
PH: (301) 244-2740
(OF) Date of form completion: 01-28-83
(HMAT) Number of substances represented in data base: 134
(•CAS) lumber of CAS registry numbers in data base: 129
(NAT) Substances represented in data base:
l,l,l-trichloroethane<71-55-
6>
l,l,2,2s-tetrachloro«thane
<79-34-5>
l/l,2-trichloroethane<79-00-5>
1,l-dichloroethane<75-34-3>
1,1-dlchlorotthyl«nt<75-35-4>
l,2,4,-trichlorobtnzen*<120-82-l>
1,2-dichlorobenz«ne<95-50-l>
1,2-dichloroeth«ne<107-06-2>
l/2-dlchloropropane<78-87-5>
l,2-diph«nylhydrazine<122-66-7>
I/2-trans-dlchloroethylent
<156-60-5>
l,3-dichlorobenzene<541-73-l>
l/3-dlchloropropyl«ne<542-75-6>
It4-dichlorobenzene<106-46-7>
2,4,6-trlchlorophenol<88-06-2>
2,4,7,8-tetracblorodibenzo-p-
dloxin (tcdd)
2,4-dlchlorophenol<120-83-2>
2,4-dlmethylphenol<105-67-9>
2,4-dinltrophenol<51-28-5>
2,4-dinltrotoluene<121-14-2>
2,6-dinitrotoluent<606-20-2>
2-chloroethylvlnyl ether<110-75-8>
2-chloronaphthaUne<91-58-7>
2-chlorophenol<95-57-8>
2-nltrophenol<88-75-5>
3/3'-dichlorobenzidine<91-94-l>
3f4-btnzofluoranth«ne<205-99-2>
4,4'-ddd(p,p'tde)
4,4'-dde(p/p'-ddx)<72-55-9>
4,4'-ddt<50-29-3>
4/6-dinitro-o-cresol<534-52-l>
4-bromophenyl phenyl ether
<101-55-3>
1072
-------
Accession No. 9038010906
(cont)
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
acenaphthyiene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
anthracene<120-12-7>
antimony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h,i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
berylliun<7440-41-7>
bhc (lindane)-ga«ffla<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
biological oxygen demand (BOD)
bis(2-chloroethoxy)nethane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis
bro»omethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadmiun<7440-43-9>
carbon tetrachloride<56-23-5>
chemical oxygen demand (COD)
chlordane<57-74-9>
chlorobenzene<108-90-7>
chl r»rodibromca«thane<124-48-l>
chlcroethane<75-00-3>
chloroform<67-66-3>
chloroi»ethane<74-87-3>
chromium<7 440- 47-3>
chrysene<218-01-9>
color analysis
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenzo(a/-h)anthracene<53-70-3>
dichlorobronomethane<75-27-4>
dichlorodifluoro«ethane<75-71-8>
dlchloronethane<75-09-2>
dieldrin<60-57-l>
diethyl phthalate<84-66-2>
diaethyl phthalate<131-ll-3>
endosulfan sulfate<1031-07-8>
endosul£an-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
f Uioranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hex achlorobenzene< 118-7 4-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeno (l,2,3-cd)pyrene<193-39-5>
i sophorone<78-59-l>
lead<7439-92-l>
nercury<7439-97-6>
n-nitrosodi-n-propylamine
<621-64-7>
n-nitrosodimethylamlne<62-75-9>
n-nitrosodiphenyIanine<86-30-6>
naphthalene<9l-20-3>
nickel<7440-02-0>
nitrobenzene<98-95-3>
p-chloro-«-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
pyrene<129-00-0>
seleniu»<7782-49-2>
silver<7440-22-4>
suspended solids
1073
-------
Accession No. 9038010906 (cont)
tetrachloroethylene<127-18-4> tri.broraoraethane<75-25-2>
thalliu»<7440-28-0> trichloroethylene<79-01-6>
toluene<108-88-3> trichlorofluororaethane<75-69-4>
total coliforn vinyl chloride<75-01-4>
toxaphene<8001-35-2> zinc<7440-66-6>
(CAS) CAS registry nunbers of substances included in data base: 71-55-6
- 79-34-5; 79-00-5? 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 122-66-7; 156-60-5; 541-73-1; 542-75-6;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2>
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3? 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193.39-5. 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 7782-49-2;
7440-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2;
79.01-6; 75-69-4; 75-01-4; 7440-66-6
(CUM) contact naae(s): Villa,Q. ; Div.,S.A. ; Lab/C.R.
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1074
-------
Accession No. 9038010907
CDS) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: Hazardous and Toxic Hastes
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Effluents leachates ;Ground
water ;Sediraent ;Soil ;Surface water streams
(ABS) Abstract/Overview of Data Base or Model: Data base consists of
abandoned waste site surveys, sanitary landfills, chemical dump
sites, waste storage areas, etc. - parameters include general
organics scans (by GC/MS), netals, cyanide, phenols, etc.
(CTC) CONTACTS: Subject matter Bob Allen (215) 597-0980; EPA
Office Region III, Centr
(DTP) Type of data collection or monitoring: Combination/Other ambient
and non-point and point source data collection Methods used
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CHA ;15
•etals
(NPP) Non-pollutant parameters included in the data base: Chemical
data ^Discharge points ;industry ; Inspection data ^Location ;
Sampling date ;Site description ^Temperature /Treatment devices
(OS) Time period covered by data base: 01-01-78 TO 12-31-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 215000.(Estimated)
(NED Estimated annual increase of observations in data base: 50,000.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 1500.
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(NOT) Number of facilities covered in data base (source monitoring): 90
•
(6EO) Geographic coverage of data base: Selected federal region Region
III
(LOG) Data elements identifying location of station or source include:
State ;City jTown/township ^Street address
(FAC) Data elements identifying facility include: Plant facility name
;Plant location
(CDE) Pollutant identification data are: Storet parameter
Uncoded
(LIM) Limitation/variation in data of which user should be aware: par an
eters vary from station to station
(DPR) Data collect./anal, procedures conform to ORD guidelines: Collect
ion method documented ^Analysis method documented ;QA procedures
document
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADO) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist for all
measurements
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division, Annapolis Lab ; Contractor lab ARL, JTC, Mead, Nest
Coast Technology and Versar ; Contractor Ecology and Environment
(ABY) Data analyzed by: Regional office Surveillance and Analysis
1075
-------
Accession Mo. 9038010907 (cont)
Division Annapolis Lab
Contractor lab nationally contracted labs (HQ contract)
CIDL) Laboratory identifications YES
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Risk assessment
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended/ Section 311 (CMA) Statutory authorization
is P L 94-580 as amended (RCRA 3001) Statutory authorization is
P L 94-469 as amended (TSCA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: lab data
reports
(RUS) Number of regular users of data base: 8
(USR) Current regular users of data base: EPA headquarter offices Oil
and Special Materials Control Division/ Office of Enforcement
EPA regional offices
EPA laboratories
States
other federal agencies - Department of Justice
(CNF) Confidentiality of data and limits on access: Some data
confidential-limits on access both within and outside the Agency
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Other as needed
(RDB) Hon-EPA data bases used in conjunction with this data base: contr
actor lab data; state agency data OFC: EPA/Region
Ill/Surveillance and Analysis Division/Central Regional Lab AD:
839 Bestgate Rd, Annapolis, MD 21401 PH: (301) 224-2760
(OF) Date of form completion: 01-28-83
(NMAT) Number of substances represented in data base: 136
(RCAS) Number of CAS registry numbers in data base: 142
(MAT4) Substances represented in data base:
l,l,l-trichloroethane<71-55- 2,4,6-trichlorophenol<88-06-2>
6> 2,4,7/8-tetrachlorodibenzo-p-
1,1,2,2,-tetrachloroethane dioxin (tcdd)
<79-34-5> 2,4-dichlorophenol<120-83-2>
I/If2-trichloroethane<79-00-5> 2,4-dimethylphenol<105-67-9>
l,l-dichloroethane<75-34-3> 2,4-dinitrophenol<51-28-5>
l,l-dichloroethylene<75-35-4> 2,4-dinitrotoluene<121-14-2>
l/2,4/-trichlorobenzene<120-82-l> 2,6-dinitrotoluene<606-20-2>
l,2-dichlorobenzene<95-50-l> 2-chloroethylvinyl ether<110-75-8>
l,2-dichloroethane<107-06-2> 2-chloronaphthalene<91-58-7>
l,2-dichloropropane<78-87-5> 2-chlorophenol<95-57-8>
l,2-diphenylhydrazine<122-66-7> 2-nitrophenol<88-75-5>
1,2-trans-dichloroethylene 3,3'-dichlorobenzidine<91-94-l>
<156-60-5> 3,4-benzofluoranthene<205-99-2>
l,3-dichlorobenzene<541-73-l> 4,4'-ddd(p,p'tde)
I/3-dichloropropylene<542-75-6> 4,4*-dde(p,p'-ddx)<72-55-9>
l,4-dichlorobenzene<106-46-7> 4,4*-ddt<50-29-3>
1076
-------
Accession No. 9038010907
(cont)
4, 6-dinitro-o-cresol<534-52-l>
4-bromophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene< 83-32-9>
aceraphthylene<208-96-8>
acrolein<107-02-8>
acryloni tr ile<107-13-l >
aldrin<309-00-2>
anthracene<120-12-7>
antimony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
barluffl<7440-39-3>
benzene<71-43-2>
benzidine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h, l)perylene<191-24-2>
benzoOOf luoranthene<207-08-9>
beryll iu«<7440-41-7>
bhc (lindane)-ganaa<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)«ethane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bls(chloromethyl)ether<542-88-l>
bronowethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadBlu»<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenzene
chlorodibromomethane<124-48-l>
chloroethane<75-00-3>
chlorofor»<67-66-3>
chl orome thane<7 4-87- 3>
chro»lua<7 440-47-3>
chrysene<218-01-9>
cobalt<7440-48-4>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dlbenzo(a,h)anthracene<53-70-3>
dlchlorobro«omethane<75-27-4>
dichlorodifluoromethane<75-71-8>
dlchloroiethane<75-09-2>
dleldrin<60-57-l>
dlethyl phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
endosulfan sulfate<1031-07-8>
•ndosulfan-alpha<959-98-8>
endosulfan-beta<332!3-65-9>
endrin aldehyde<7421-93-4>
endrirK72-20-8>
ethylbenzene<100-41-4>
fluoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxlde<1024-57-3>
heptachlor<76-44-8>
hex achlorobenzene
hexachl or o but adiene<87- 68-3 >
hexachlorocyclopentadlene<77-47-4>
hexachloroethane<67-72-l>
Indeno
lron<7439-89-6>
isophorone<78-59-l>
l«ad<7439-92-l>
•anganese<7439-96-5>
•ercury<7439-97-6>
n-nltrosodl-n-propylamlne
<621-64-7>
n-nitrosodinethylanine<62-75-9>
n-nltrosodiphenyla«lne<86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nltrobenzene<98-95-3>
organic GC/NS scans for slgnlfican
t organics
p-chloro-«-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
1077
-------
Accession No. 9038010907 (cont)
phenanthrene<85-01-8> toluene<108-88-3>
phenol<108-95-2> toxaphene<8001-35-2>
pyrene<129-00-0> tribronoiethane<75-25-2>
seleniun<7782-49-2> trichloroethylene<79-01-6>
silver<7440-22-4> trichlorofluoro«ethane<75-69-4>
tetrachloroethylene<127-18-4> vanadiu»<7440-62-2>
thalliun<7440-28-0> vinyl chloride<75-01-4>
titanium<7440-32-6> zinc<7440-66-6>
(CAS) CAS registry nuabers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 122-66-7; 156-60-5; 541-73-1; 542-75-6;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 7440-39-3; 71-43-2; 92-87-5; 56-55-3;
50-32-8; 191-24-2; 207-03-9; 7440-41-7; 58-89-9; 319-84-6;
319-85-7; 319-86-8; 111-91-1; 111-44-4; 39638-32-9; 117-81-7;
542-88-1; 74-83-9; 85-68-7; 7440-43-9; 56-23-5; 57-74-9;
108-90-7; 124-48-1; 75-00-3; 67-66-3; 74-87-3; 7440-47-3;
218-01-9; 7440-48-4; 7440-50-8; 57-12-5; 84-74-2; 117-84-0;
53-70-3; 75-27-4; 75-71-8; 75-09-2; 60-57-1; 84-66-2;
131-11-3; 1031-07-8; 959-98-8; 33213-65-9; 7421-93-4; 72-20-8;
100-41-4; 206-44-0; 86-73-7; 1024-57-3; 76-44-8; 118-74-1; 87-68-3;
77.47.4. 67-72-1; 193-39-5; 7439-89-6; 78-59-1; 7439-92-1;
7439-96-5; 7439-97-6; 621-64-7; 62-75-9; 86-30-6; 91-20-3;
7440-02-0; 98-95-3; 59-50-7; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 87-86-5;
85-01-8; 108-95-2; 129-00-0; 7782-49-2; 7440-22-4; 127-18-4;
7440-28-0; 7440-32-6; 108-88-3; 8001-35-2; 75-25-2; 79-01-6;
75-69-4; 7440-62-2; 75-01-4; 7440-66-6
(CUM) Contact naae(s): S»ith,B.
(COR) Contact organization: Region III, Central Regional Lab
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1078
-------
Accession No. 9038010909
(DQ) Date of Questionaire: 12*02*82
(MAM) Name of Data Base of Model: Drinking Mater
(ACR) Acronym of Data Base or Model: None
(MED) fedia/Subject of Data Base or Model: Drinking water ;Ground
water ;Sediment ;Soil ^Surface water intake
(ABS) fbs tract/Over view of Data Base or Model: Data fro- studies to
define contamination problems of water and sources of
contamination are contained in this data base*
(CTC) CONTACTS: Subject natter Orterio ¥illa, Jr. (301) 224-2740
; EPA Office Region
(DTP) Type of data collection or monitoring: Combination/Other
Ambient, Point source (treated and untreated wells distribution
systems) and non-point source.
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CHA ;21
drinking water standards ;9 potential drinking water ; 29 drinking
water monitoring
(NPP) Non-pollutant parameters included in the data base: Location
^Physical data ;Sampling date ;Site description ^Temperature ;
Test/analysis method
(DS) Time period covered by data base: 06-01-78 TO 12-31-82
(TRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 4500.(Estimated)
(NEI) Estimated annual increase of observations in data base: 1000.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 350.
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: Selected federal region Region
III
(LOC) Data elements identifying location of station or source include:
State ;City ?Town/township jStreet address
(FAC) Data elements identifying facility include: Plant facility name
;Plant location
(CDE) Pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Param
eters vary from site to site. Sampling frequency is irregular and
depends on program needs.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Collect
ion method documented ^Analysis method documented ;QA procedures
document
(AND Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precisions Precision and accuracy estimates exist but are not
Included in data base
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Environmental Services
Division, Central Regional Lab-Annapolis, Region III
(ABY) Data analyzed by: Regional office Environmental Services
1079
-------
Accession No. 9038010909 (cont)
Division, Central Regional Lab-Annapolis* Region III
(IDL) Laboratory identification: YES
(AOT) Authorization for data collection: Statutory authorization is P
L 93-523 as amended (Safe Drinking Hater Act-SDHA)
COMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data base: nemos and
lab data sheets
(MOS) Umber of regular users of data base: 50 or over
(USR) Current regular users of data base: EPA headquarter offices
Office of Drinking Water
EPA regional offices
EPA laboratories
States
facilities saapled
(CNF) Confidentiality of data and Halts on access: No limits on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Other as studies
completed (one time studies)
(ODB) Other pertinent non-EPA data bases: Slailar State Data bases
(CMP) Completion of for*:
Dan Donnelly
OFC: EPA/Region Ill/Central Regional Lab-Annapolis/Surveillance
Analysis
Division
AD: 839 Bestgate Road Annapolis, MD 21401
PH: (301) 224-2740
(DF) Date of form completion: 01-19-83
(WHAT) Number of substances represented in data base: 37
(NCAS) Number of CAS registry numbers in data base: 33
(MAT) Substances represented in data base:
l,l,l,2-tetrachloroethane<63 chlorobenzene<108-90-7>
0-20-6> chlorofor»<67-66-3>
l,l,l-trichloroethane<71-55-6> chro«iu«<7440-47-3>
l,l,2-trichloroethane<79-00-5> cis-l,2-dichloroethylene<156-59-2>
l,2-dlchlorobenzene<95-50-l> dichloroiodo«ethane<594-04-7>
1,2-dichloroethane<107-06-2> endrin<72-20-8>
1,2-trans-dichloroethylene fluoride
<156-60-5> lead<7439-92-l>
l,3-dichlorobenzene<541-73-l> lindane<58-89-9>
l,4-dlchlorobenzene<106-46-7> »ercury<7439-97-6>
2^4-dichlorophenoxyacetic acid (2* •ethoxycfclor<72-43-5>
4-d)<94-75-7> microbiology coliform bacteria
arsenic<7440-38-2> nitrate<14797-55-8>
bariu«<7440-39-3> seleniu»<7782-49-2>
bro«odichloro«ethane<75-27-4> silver<7440-22-4>
cad»iu»<7440-43-9> silvex<93-72-l>
carbon tetrachloride<56-23-5> tetrachloroethylene<127-18-4>
1080
-------
Accession No. 9038010909 (cont)
toxaphene<8001-35-2> trihalonethanes
tribronomethane<75-25-2> turbidity
trichloroethylene<79-01-6> vinyl chloride<75-01-4>
(CAS) CAS registry numbers of substances included in data base: 630-20-
6; 71-55-6; 79-00-5; 95-50-1; 107-06-2; 156-60-5; 541-73-1;
106-46-7; 94-75-7; 7440-38-2; 7440-39-3; 75-27-4; 7440-43-9;
56-23-5; 108-90-7; 67-66-3; 7440-47-3; 156-59-2; 594-04-7;
72-20-8; 7439-92-1; 58-89-9; 7439-97-6; 72-43-5; 14797-55-8;
7782-49-2; 7440-22-4; 93-72-1; 127-18-4; 8001-35-2; 75-25-2;
79-01-6; 75-01-4
(CNM) Contact name
-------
Accession No. 9038020902
(OQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: Permit Compliance Monitoring
(ACR) Icronya of Data Base or Model: NPDES
(MED) Kedia/Subject of Data Base or Model: Effluents municipal and
Industrial ;Surface water receiving stream
(ABS) Abstract/Overview of Data Base or Model: Data froa compliance
inspections of discharging facilities. Parameter information,
as contained in permittee's National Pollutant Discharge
Elimination System (NPDES) permit, is also included.
(CTC) CONTACTS: Subject matter Len Mangiaracina (215)597-4564 ;
EPA Office Enforcement
(DTP) Type of data collection or monitoring: Point source data
collection municipal & industrial effluents
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 11 conventional
water ;41 CNA potential criteria ;15 metals
(NPP) Non-pollutant parameters included in the data base: Chemical
data ^Discharge points ;Flow rates ^Inspection data ; Location
;Sampling date ;Site description
(DS) Time period covered by data base: 09-01-74 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: annually
(NOB) Number of observations in data base: 4664.(Estimated)
(NEI) Estimated annual increase of observations in data base: 242.
(INF) Data base includes: Rau data/observations
(NTS) Total number of stations or sources covered in data base: 341
(NCS) No. stations or sources currently originating/contributing data:
17.
(NQF) Number of facilities covered in data base (source monitoring): 34
1.
(GEQ) Geographic coverage of data base: Selected federal region Region
III
(LOC) Data elements identifying location of station or source include:
State jCounty ;City ;Toun/township ^Coordinates latitude/longitude
(FAC) Data elements identifying facility include: Plant facility name
;PI ant location ;NPDES
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of Hhich user should be aware: None
(OPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented Collection method documented ;Analysis method
document QA procedures documented
(ANL) Lai) analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit Is satisfactory for 90.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EDT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division, Wheeling Field Office, Region III
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division-Wheeling Field Office, Region III
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Compliance or enforcement
1082
-------
Accession No. 9038020902 (cont)
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 308 and 402 (Clean Water Act-CWA)
(OMB) Data collected/submitted using OHB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: EPA form
3560-3
data tabulated
(NUS) K umber of regular users of data base: 150
(USR) Current regular users of data base: EPA headquarter offices
Water Enforcement Division
EPA regional offices
industrial and municipal facilities
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other as requested
(RSS) Related EPA automated systems which use data base: Permit
Compliance System (PCS)- analytic
(CMP) Completion of form:
Robert Cantor
OFC: EPA/Region III/ Surveillance and Analysis
Division/Wheeling Field Office
AD: 303 Methodist Bldg. Wheeling, HV 26003
PH: (304)233-1271
CDF) Date of form completion: 11-06-80
(NMAT) Number of substances represented in data base. 29
(NCAS) Number of CAS registry numbers in data base: 16
(MAT) Substances represented in data base:
ar-iditv lead<7439-V2-l>
alkalinity nanganese<7439-96-5>
alu*inuiB<7429-90-5> "f^^^ll^o^flf
ammonia<7664-41-7> nickel<7440-02-0>
arsenic<7440-38-2> nitrates/nitrites
ben2ene<7t-43-2> nitrogen<7727-37-9>
cad»ium<7440-43-9> oil and grease
carbon tetrachloride<56-23-5> oxygen demand
co">ounds
Ph.r,z.r«
fecal editor. *"JI?S!!
fluorides sulfides
aswaraaass ?K2S! ^JS"
contact name(s): Mangiaracina,L«
) Contact organization: Enforcement Division, Region III
1083
-------
Accession No. 9038020902 (cont)
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1084
-------
Accession No. 9038020906
(DQ) Date of Questionaire: 12-02-82
(NAM) Nane of Data Base of Model: Ambient Priority Pollutant Program
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Sediment ;Surface water
rivers and streams ;Tissue fish
(ABS) Abstract/Overview of Data Base or Model: This data base contains
concentrations of priority pollutants in navigable waters to
determine possible problem areas and sources.
(CTC) CONTACTS: Subject matter John Ruggero (215)597-9839; EPA
Office Larry Miller (21
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Discontinued
(6RP) Groups of substances represented in Data Base: 129 307 CHA
(NPP) Non-pollutant parameters included in the data base: Chemical
data ;Concentration measures ;Inspect!on data ;Location ;
Sampling date ;Site description
(DS) Time period covered by data base: 05-01-78 TO 10-31-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: annually ;as needed
(NOB) Number of observations in data base: 5160.(Estimated)
(NEI) Estimated annual increase of observations in data base: 1290.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 40.
(NCS) No. stations or sources currently originating/contributing data:
10.
(NOF) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: Selected federal region Region
III
(LOC) Data elements identifying location of station or source include:
State ;County ^Coordinates latitude/longitude; river mile point ;
name of river
(FAC) Data elements identifying facility include: N/A
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to CRD guidelines: Samplin
g plan documented Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EDT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division, Wheeling Field Office, Region III
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division, Wheeling Field Office, Region III
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Trend assessment
(PR2) Secondary purpose of data collection: Risk assessment
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 104 (Clean Mater Act-CHA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
1085
-------
Accession No. 9038020906
Ccont)
QQ
(REP) Form of available reports and outputs of data base: raw data
tabulated
(NUS) Nunber of regular users of data base: 4 offices
(USR) Current regular users of data base: EPA regional offices
States
ORSANCO
(CNF) Confidentiality of data and 1is its on access: No liaits on
access to data
(DLC) Prinary physical location of data: Regional office
(DST) Forn of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(OpDT) Frequency of data base Master file up-date: Other as requested
(CMP) Completion of form:
Robert Cantor
OFC: EPA/Region Ill/Surveillance and Analysis
Division/Wheeling Field Office
AD: 303 Methodist Bldg. Wheeling, UV 26003
PH: (304)233-1271
(OF) Date of form completion: 02-24-83
(NMAT) Number of substances represented in data base: 129
(NCAS) Nunber of CAS registry nuabers in data base: 127
(HAT) Substances represented in data base:
l,l,l-trichloroethane<71-55-
6>
1,1,2,2,-tetrachloroethane
<79-34-5>
l,l,2-trichloroethane<79-00-5>
l,l-dichloroethane<75-34-3>
Ifl-dichloroethylene<75-35-4>
l,2,4,-trichlorobenzene<120-82-l>
l,2-dichlorobenzene<95-50-l>
l,2-dichloroethane<107-06-2>
It2-dichloropropane<78-87-5>
l,2-dichloropropylene<563-54-2>
l,2-diphenylhydrazine<122-66-7>
\f2-trans-dichloroethylene
<156-60-5>
It3-dichlorobenzene<541-73-l>
\t 4-dichlorobenzene<106-46-7>
2,4,6-trichlorophenol<88-06-2>
2f 4,7, 8-tetr achlorodibenzo-p-
dioxin (tcdd)
2f4-dichlorophenol<120-83-2>
2, 4-di me thylphenoKl 05-67-9>
2, 4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2f6-dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-nitrophenol<88-75-5>
3,3 *-dichlorobenzidine<91-9 4-l>
3,4-benzofluoranthene<205-99-2>
4,4*-ddd(p,p*tde>
At 4*-dde(p/p*-ddx)<72-55-9>
4^4'-ddt<50-29-3>
4, 6-dinitro-o-cresol<534-52-l>
4-bronophenyl phenyl ether
<101-S5-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
anthracene<120-12-7>
antinony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a>pyrene<50-32-8>
benzo(g,b^i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
berylliu*<7440-41-7>
1086
-------
Accession No* 9038020906
(cont)
bhc (liadane)-gamraa<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)ae thane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl)ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloronethyl)ether<542-88-l>
bro»omethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadniun<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodibromomethane<124-48-l>
chloroethane<75-00-3>
chlorofora<67-66-3>
chloro»ethane<74-87-3>
chromiun<7440-47-3>
chry sene< 218-0 l-9>
copper <7440-50-8>
cy anide<57-l 2-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dlbenzo(a, h) anthracene<53-70-3>
dichlorobroaomethane<75-27-4>
dichlorodifluoro»ethane<75-71-8>
dichloroiRethane<75-09-2>
dieldrln<60-57-l>
dlethyl phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
endosulfan sulf ate<1031-07-8>
endosulf an-alpha<959-98-8>
endcsulfan-beta<33213-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene
fluoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
(CAS)
hex achlorobenzene
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadlene<77-47-4
hexachloroethane<67-72-l>
indeno (l,2/3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
nercury<7439-97-6>
n-nit roscdi-n-propy laaine
<621-64-7>
n-nitrosodimethyla«ine<62-75-9>
n-nitrosodiphenyla«ine<86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nitrobenzene<98-95-3>
p-chloro-«-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 {arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
pyrene<129-00-0>
seleniu«<7782-49-2>
silver<7440-22-4>
tet r achlor oethy lene
thalliuiB<7440-28-0>
toluene<108-88-3>
toxaphene<8001-35-2>
tribro«o»ethane<75-25-2>
trichloroethylene<79-01-6>
trichlorofluoro»ethane<75-69-4>
vinyl chloride<75-01-4>
zinc<7440-66-6>
CAS registry numbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67^9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
1087
-------
Accession Mo. 9038020906 (cont)
744C-38-2; 1332-21-4; 71-43-2; 92-87-5? 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 7782-49-2;
744C-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2;
79-01-6; 75-69-4; 75-01-4; 7440-66-6
(CNN) Contact naae(s): Ruggero,J.; Miller,L.
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1088
-------
Accession Ho. 9038020907
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Resource Conservation and Recovery
Act (RCRA)- Hazardous Haste Site Inspections
(ACR) Acronym of Data Base or Model: Hone
(MED) Kedia/Subject of Data Base or Model: Drinking water ;Ground
water jRunoff leachate ;Surface water receiving streams a
(ABS) Abstract/Overview of Data Base or Model: This data base is
concerned with the presence of toxic or hazardous Materials In
order to determine the need for remedial or enforcenent action on
hazardous waste dump sites.
(CTC) CONTACTS: Subject natter Linda Boornazian (215)597-9407 ;
EPA Office Bruce Smith
(DTP) Type of data collection or monitoring: Son point source data
collection
(STA) Data Base status: Discontinued
(GRP) Groups of substances represented in Data Base: 129 307 CHA ;15
metals
(NPP) Non-pollutant parameters included In the data base: Chemical
data Concentration measures ;Discharge points ;Flou rates ;
Inspection data ;Location ^Sampling date ;Site description ;sorae
toxiclty data
(DS) Time period covered by data base: 01-01-80 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 384.(Estimated)
(NEI) Estimated annual increase of observations in data base: 192.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 32.
(NCS) No. stations or sources currently originating/contributing data:
1 (time per site.)
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: Selected federal region Region
III
(LOG) Data elements identifying location of station or source include:
State ;County ;City }Town/township
(FAC) Tata elements identifying facility include: Plant facility name
;PI ant location
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: Sampl
es collected for this program are not perfect.
(DPR) Data collect./anal. procedures conform to QRD guidelines: Samplin
g plan documented Collection method documented ;Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division, Wheeling Field Office, Region III
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division-Wheeling and Annapolis Field Office, Region III
1089
-------
Accession Ho. 9038020907
(cont)
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Conpliance or enforcement
(AUT) Authorization for data collection: Statutory authorization is P
L 94-580 as amended, Section 3007 (Resource Conservation and
Recovery Act-RCRA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: trip report
EPA form T 2070-3
data tabulated
(BUS) Nunher of regular users of data base: 5
(OSR) Current regular users of data base: EPA headquarter offices
Water Enforcement-Hazardous Haste Task Force
EPA regional offices
States
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Other as requested
(CMP) Completion of form:
Robert Cantor
OFC: EPA/Region Ill/Surveillance and Analysis
Division-Wheeling Field Office
AD: 303 Methodist Bldg. Wheeling, WY 26003
PH: (304)233-1271
(OF) Date of fora completion: 02-24-83
(RMAT) Number of substances represented in data base: 131
(MCAS) Number of CAS registry numbers in data base: 131
(NAT) Substances represented in data base:
l,l,l-trichloroethane<71-55-
6>
If If 2f 2, -tetrachloroethane
<79-34-5>
1, l,2-trichloroethane<79-00-5>
l,l-dlchloroethane<75-34-3>
lf1-dichloroethylene<75-35-4>
It "it 4r -trichlorobenzene<120-82-l>
1*2-dichlorobenzene<95-50-l>
If2-dichloroethane<107-06-2>
If2-dichloropropane<78-87-5>
l,2-dichloropropylene<563-54-2>
1,2-diphenylhydrazine<122-66-7>
1,2-trans-dichloroethylene
<156-60-5>
If3-dichlorobenzene<541-73-l>
l,4-dichlorobenzene<106-46-7>
2,4,6-trichlorophenol<88-06-2>
2f Af If 8- te tr achlorod ibenzo-p-
dioxin (tcdd)
2,4-dichlorophenol<120-83-2>
2,4-dimethylphenol<105-67-9>
2,4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2,6-dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-nltrophenol<88-75-5>
3,3*-dichlorobenzidlne<91-94~l>
3,4-benzofluoranthene<205-99-2>
4,4'-ddd(p/p*tde)
4,4'-dde(p,p'-ddx)<72-55-9>
4,4*-ddt<50-29-3>
4f6-dlnitro-o-cresol<53 4-52-l>
4-bromophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
1090
-------
Accession No. 9038020907
(cont)
acenaphthene< 83-32 -9>
acenaphthylene< 208-96- 8>
acrolein<107-02-8>
acrylonltriie<107-13-l>
aldrin<309-00-2>
anthracene<120-12-7>
antimony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71 -43-2>
benzidine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrerie<50-32-8>
benzo(g,h,l)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
beryllium<7440-41-7>
bhc (llndane)-gaBma<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)methane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyi)phthalate
bis(chloro«ethyl)ether<542-88-l>
bro«onethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cad»iuit<7440-43-9>
carbon tetrachloride<56-23-5>
cheirical oxygen demand (COD)
chlordane<57-74-9>
chlorobenzene< 10 8- 90-7>
chlorodibromomethane
chloroethane<75-00-3>
chloroform<67-66-3>
chloromethane<74-87-3>
chroniiuni<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenzo(a/h) anthracene<53-70-3>
dichlorobro»onethane<75-27-4>
di chlorodl f 1 uorome thane<75-71 -8>
dichloromethane<75-09-2>
dleldrln<60-57-l>
diethyl phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<3 3213-6 5- 9>
endrln aldehyde<742l-93-4>
endrln<72-20-8>
ethylbenzene<100-41-4>
f luoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hex achlorobenzene
hexachlorobutadlene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeno (l,2,3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
mercury<7439-97-6>
n-nitrosodi-n-propylanine
<621-64-7>
n-nitrosodimethylaraine<62-75-9>
n-nitrosodiphenyianine< 86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nltrobenzene< 98-95- 3>
p-chloro-n-cresoi<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 {arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
pyrene<129-00-0>
seleniuni<7782-49-2>
silver<7440-22-4>
tetr achloroethylene<127-l 8-4>
thalliun<7440-28-0>
toluene<108-88-3>
total oxidizable carbon
toxaphene<8001-35-2>
t r ibr omoiae thane<7 5-25-2 >
1091
-------
Accession No. 9038020907 (cont)
trichloroethylene<79-01-6> vinyl chloride<75-01-4>
trIchlorofluoroaethane<75-69-4> zinc<7440-66-6>
(CAS) CAS registry numbers of substances included in data base: 71-55-6
. 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67*9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57*8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67r66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 7782-49-2;
7440-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2;
79-01-6; 75-69-4; 75-01-4; 7440-66-6
(CUM) Contact nawe(s): Boornazian/L. ; Saith,B*
(ROR) Responsible Organization: Region III.Environmental Services
Division.
1092
-------
Accession Ho. 9038020909
(DQ) Date of Questionaire: 12-02-82
(NAN) Kane of Data Base of Model: Pi*lie Mater Supplies
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Drinking water
(ABS) Abstract/Overview of Data Base or Model: The data base is used
to determine compliance with public drinking water standards.
Samples of rain water influents are included in the data base.
(CTC) CONTACTS: Subject natter Ray Lee (215) 597-8227 ; EPA
Office Ray Lee (215) 59
(DTP) Type of data collection or monitoring: Combination/Other public
water supplies-ambient and finished
(STA) Data Base status: Discontinued
(GRP) Groups of substances represented In Data Base: 21 drinking water
standards ;9 potential drinking water
(NPP) lion-pollutant parameters included in the data base: Chemical
data ;Inspect!on data /Sampling date ;Site description
(OS) Tine period covered by data base: 01-01-77 TO 09-30-81
(TRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 164.(Estimated)
(NEI) Estimated annual increase of observations in data base: 40.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 22.
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(NQF) Number of facilities covered in data base (source monitoring): 22
•
(GEO) Geographic coverage of data base: Selected federal region Region
III
(LOC) Data elements identifying location of station or source include:
State /County /City ;Town/township
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ;name of stream
(CDE) Pollutant identification data are: Storet parameter
(LiM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ;Collection method documented ;Analysis method
document QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory for 90%.
(PRE) Precision: Precision and accuracy estimates exist but are not
Included in data base
(EDT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division-Wheeling Field Office, Region III
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division-wheeling Field Office/ Region III
(IDL) Laboratory identification: YES
(AUT) Authorization for data collection: Statutory authorization is P
L 93-523 (Safe Drinking Water Act (SOWA))
(OMB) Data collected/submitted using QMB-approved EPA reporting forms:
QQ
1093
-------
Accession No. 9038020909 (cont)
(REP) Fora of available reports and outputs of data base: raw data
tabulated
(NUS) Number of regular users of data base: 4
(OSR) Current regular users of data base: EPA regional offices
States
(CNF) Confidentiality of data and 1inits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Other as requested
(CMP) Completion of form:
Robert Cantor
OFC: EPA/Region III/Surveillance and Analysis Division-Wheeling
Field
Office
AD: 303 Methodist Bldg. Wheeling, MV 26003
PH: (304) 233-1271
(OF) Date of form completion: 02-24-83
(NMAT) Number of substances represented in data base: 27
(NCAS) Number of CAS registry numbers in data base: 25
(MAT) Substances represented in data base:
l,l,l-trichloroethane<71-55- lead<7439-92-l>
6> lindane<58-89-9>
It2-dichlorobenzene<95-50-1> mercury<7439-97-6>
1,2-dichloroethane<107-06-2> methoxychlor<72-43-5>
l microbiology coliform bacteria
l,4-dichlorobenzene<106-46-7> nitrate<14797-55-8>
2,4-dichlorophenoxyacetic acid (2, selenium<7782-49-2>
4-d)<94-75-7> silver<7440-22-4>
arsenic<7440-38-2> silvex<93-72-l>
barium<7440-39-3> tetrachloroethylene<127-18-4>
cadnium<7440-43-9> toxaphene<8001-35-2>
carbon tetrachloride<56-23-5> trichloroethylene<79-01-6>
chlorobenzene<108-90-7> turbidity
chromium<7440-47-3> vinyl chloride<75-01-4>
endrin<72-20-8>
(CAS) CAS registry numbers of substances included in data base: 71-55-6
; 95-50-1; 107-06-2; 541-73-1? 106-46-7; 94-75-7; 7440-38-2;
7440-39-3; 7440-43-9; 56-23-5; 108-90-7; 7440-47-3; 72-20-8;
7439-92-1; 58-89-9; 7439-97-6; 72-43-5; 14797-55-8; 7782-49-2;
7440-22-4; 93-72-1; 127-18-4; 8001-35-2; 79-01-6; 75-01-4
(CNM) Contact name(s): Lee,R. ; Lee,R.
(RQR) Responsible Organization: Region III.Environmental Services
Division.
1094
-------
Accession No. 9038030906
(DQ) Date of Questioaaire: 12-02-82
(HAM) Kane of Data Base of Model: Priority Pollutants Effluent
Guidelines
(ACR) Acronym of Data Base or Model: None
-------
Accession Ho* 9038030906
(cont)
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division, Wheeling and Annapolis Field Office, Region III
(IDL) Laboratory Identification: YES
(PR1) Primary purpose of data collection: Development of regulations
or standards
CAUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended (Clean Hater Act-CMA)
COMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data base: tabulated
raw data
(ROS) Number of regular users of data base: 2
(USR) Current regular users of data base: EPA headquarter offices
Effluent Guidelines Division
(CNF) Confidentiality of data and limits on access: Limits on access
within EPA and outside agency for soae data
(DLC) Primary physical location of data: Headquarters office
(DST) Form of data storage: Original fora (hardcopy, readings)
CDAC) Type of data access: Manually
CCHG) Direct charge for non-EPA use: no
(DpDT) Frequency of data base master file up-date: Other As requested
(CMP) Completion of fora:
Robert Cantor
OFC: EPA/Region Ill/Surveillance and Analysis
Division/Wheeling Field Office
AD: 303 Methodist Bldg. Wheeling, W? 26003
PH: (304)233-1271
(OF) Date of fora coupletion: 02-24-83
(NMAT) Nuaber of substances represented in data base: 129
(HCAS) Nuaber of CAS registry numbers in data base: 127
(MAT) Substances represented in data base:
1,1*1-trichloroe than e<71-55-
6>
1,1,2,2,-tetrachloroethane
<79-34-5>
1, l,2-trichloroethane<79-00-5>
1,1-di chloroethane<75-34-3>
l,l-dichloroethylene<75-35-4>
1, 2,4,-trichlorobenzene<120-82-l>
l,2-dichlorobenzene<95-50-l>
1,2-di chlo roethane<107-06-2>
1,2-dichloropropane<78-87-5>
l,2-dichloropropylene<563-54-2>
l,2-c!iphenylhydrazine<122-66-7>
If 2-trans-dichloroethy lene
<156-60-5>
l,3-dichlorobenzene<541-73-l>
1,4-dichlorobenzene<106-46-7>
2, 4,6-trichlorophenol<88-06-2>
2, 4,7, 8-te tr achlorodlbenzo-p-
dloxin (tcdd)
2,4-dichlorophenol<120-83-2>
2,4-dimethylphenol<105-67-9>
2,4-dlnitropnenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2,6-dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-nitrophenol<88-75-5>
3,3•-dichlorobenzidine<91-94-l>
3,4-benzofluoranthene<205-99-2>
4,4'-ddd(p,p'tde)
4,4'-dde(p,p--ddx)<72-55-9>
4,4'-ddt<50-29-3>
4,6-dlnitro-o-cresol<534~52-l>
4-broaophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene< 83-32-9>
acenaphthylene<208-96-8>
1096
-------
Accession No. 9038030906
(cont)
acrolein<107-02-8>
aery lonitrile<107- 13-1 >
aldrin<309-00-2>
anthracene
antimony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
benzo{ a) anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h,i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
berylliu«<7440-41-7>
bhc (lindane)-ga»ma<58-89-9>
bhc-alpha< 31 9-8 4-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis (2-chloroet ho xy)ae thane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloromethyl)ether<542-88-l>
bronomethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadwiun<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodibr on one thane< 1 24-4 8-1 >
chloroethane<75-00-3>
chloroform<67-66-3>
chloromethane<74-87-3>
chronium<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenzo( a/ h) anthracene<53-70-3>
dlchlorobromonethane<75-27-4>
dichlorodifluoronethane<75-71-8>
dlchloromethane<75-09-2>
dleldrin<60-57-l>
die thy 1 phthalate<84-66-2>
dimethyl phthalate<13l-ll-3>
endosulfan sul£ate<103l-07-8>
endosulfan-alpha<9 59-98- 8>
endosulfan-beta<33213-65-9>
endcin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
f luoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
hep tachlor<76-44-8>
hex achlorobenzene
hex achlorobutadiene<87- 68-3 >
hexachlotocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeno (1, 2,3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
mercury<7439-97-6>
n-nitrosodi-n-propylanine
<621-64-7>
n-nitrosodinethyla«ine<62-75-9>
n-nltrosodiphenyla«ine<86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nit robe nzene<98-95-3>
p-chloro-B-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene< 85-01- 8>
phenol<108-95-2>
pyrene
seleniuffl<7782-49-2>
silver<7440-22-4>
tetrachloroethylene<127-18-4>
thalliua<7440-28-0>
toluene<108-88-3>
toxaphene<8001-35-2>
trlbroaoaethane<75-25-2>
tr ichloroethylene<79-01 -6>
trichlorofluorotnethane<75-69-4>
vinyl chloride<75-01-4>
zinc<7440-66-6>
1097
-------
Accession No. 9038030906 (cont)
-------
Accession No. 9043000501
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Sample Analyses and Managemant
System/ Region IV
(ACR) Acronym of Data Base or Model: SAAMS
(MED) Media/Subject of Data Base or Model: Air ;Drinking Hater
;Effluents/ Municipal and industrial uastewater ;Ground Water
>Runoff ;Sediment >Soil ;Solid Haste ;Surface Water, stream/
lake, estuarine ;Tissue/ aquatic plant and animal /oil/ gasoline
(ABS) Abstract/Overview of Data Base or Model: The "Sample Analyses
and Management System** is a computerized data storage and
retrieval system designed and used by EPA Region IV. The
Analytical Support Branch of the Environmental Services Division
enters all of its sample logging information and results of
chemical analyses into this system. Hard copy-formated
retrieval of data is available at this time. The system also
furnishes the lab backlog and other management information.
(CTC) CONTACTS: Subject matter Tom B. Bennett/ Jr. PH: (404)
546-3112 FTS 250-3112 ; Computer-related Daylor Conner (404)
881-2316 FTS 257-2316 ; EPA Office Enivronmentai Services
Division/ Region IV, Athens/ 6A
(DTP) Type of data collection or monitoring: Combinations and Other
(STA) Data Base status: Presently Operational/Ongoing
(6RP) Groups of substances represented in Data Base: 43 air priority
chemicals ; 5 NESHAPS except asbestos ; 129 307 CVA ; 11
conventional water / 41 CWA potential criteria ; 21 drinking
water standards except Radioactive Pollutants ; 9 potential
drinking water except Radioactive Pollutants y 29 drinking water
monitoring / 299 hazardous substances except Salts of the organic
and inorganic compounds ; 48 cancelled pesticides ; 9 monitoring
pesticides ; 54 TSCA assessment ; RCRA hazardous wastes ; 16
Pre-RPAR ; 15 metals ; Other- The data base is flexible in that
new parameters not presently in the data base can be added easily
by the system user, some of the above compounds are not in the
data base at present but can be added as needed.
(NPP) Non-pollutant parameters included in the data base: Chemical
data ; Compliance data / Concentration measures ; Discharge
points ; Flow rates ; Industry ; Location ; Manufacturer > Physical
data ; Political Subdivisions ; Salinity ; Sampling Date ; Site
Description ; Temperature •/ Test/Analysis method ; Treatment
devices or processes ; all sample collection information (where/
when/ how/ who/ etc.)/ all sample custody information
(DS) Time period covered by data base: 79 TO 01-83
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Ongoing:Daiiy ;
Ongoing:As needed ; At least daily.
(NOB) Number of observations in data base: 500/000(Estimated to date)
(NEI) Estimated annual increase of observations in data base: Not Known
(INF) Data base includes: Raw data/observations ; Sample logging
information.
(NTS) Total number of stations or sources covered in data base: Not
Known
(GEO) Geographic coverage of data base: Single or selected Federal
1099
-------
Accession Ho. 9043000501 (cont)
Regions Region IV, SB-US
acetic acid,methyl chlorobenze
2,5-furandione,3-ethyl-4-methyl ne
<355-33-8> aldehyde,endrin
acetic acid,benzene alkyl acid,C14 methyl ester
acetic acid,biphenyl alkyl acid,C15 methyl ester
1100
-------
Accession No. 9043000501
(cont)
alkyl acid,C!6 Methyl ester
alkyl acid,C18 aehtyl ester
amlne/diethyl nethoxy trlazlnedl
amlne/n-nitrosodlphenyl
an thra cene di one
anthracenone/7H-benz(de)
benzaldehyde/hydroxy
benzaldehyde/hydroxy nethoxy
benzanthracene-1/2
benzenamide/n->ethyl nitroso
benzene/alkyl
benzene/C6 alkyl
benzene, ethoxy aethyl
benzene /methylene bis
benzeneacetic acld<103-82-2>
benzenepropanoic acid
<501-52-0>
benzimldazole/ehtyl
benzo(GHI)fluoranthene<203-12-3>
benzofluoranthene,11,12<207-08-9>
benzofluoranthene/3,4<205-99-2>
benzofluoranthene/7/10<203-12-3>
benzole acid/aaino
benzole acid,C4 alkyl
benzole acid/chloro
benzole acid/dimethyl
benzonaphthlophene
benzoperylene/ lf 12<191-24-2>
benzopyrene/3,4<50-32-8>
benzylcanide/ chloronethyl
BHC(llndane)ganaa
BHC-alpha
BBC-beta
BHC-delta
BHC-gamma
blcycloheptanone/trlmethyl
blcyclooctane/dlbromo
blcyclooctane/ tribroao
blphenyl/tetrachloro<26914-33-0>
blphenyl/trlchloro<25323-68-6>
br OB ide/methyl
butane/bis methylene bls(oxy)
butanoic acid
butanolc acid, dine thy 1
butanoic acld/aethyl
bxitanol,2-Bethyl/2
carboxyllc acid/benzendi
chlordane/alpha
chlordane/ gamma
chlordene/hydroxy
chloride/chlorobenzoyl
chlorlde/methyl
chlor Ide/methy lene
chrysene/ C2 alkyl
chrysene,methyl
cresol/parachloroaeta/
cyclohexane
cyclohexanone/trlnethyl
cyclopentanol/iethyl
cyclopentenone/hydroxy methyl
cyclopentenone/methyl
DDD/O'P*
ODE/O-P*
DDT/0'P*
decanolc acld/nethyl ester
<110-42-9>
decanoic acid/penta
dibenzanthracene-1/ 2/5/6
<53-70-3>
dibenzofur an/methyl
dlbenz.othlophene/methyl
debenzyl/ tetramethyl
dlchlorobenzene-l/2<95-50-l>
dichlorobenzane-1,3<541-73-l>
dichlorobenzene-l/4<106-46-7>
diphenylamine/n-nltroso<86-30-6>
dipropetryn
dodecanoic acid/methyl ester
eicosanolc acid/methyl ester *
endosulfan-beta<32313-65-9>
endrin ketone
epoxlde/heptachlor<1024-57-3>
ethane/1/1/1-dlchloro
ethane/1,/1/1-trifluorocMoro
ethane/1/1/2/2- tetrachloro
e thane/1/1/ 2-trlchloro
ehtane,I/2-dichloro/l/l/2-
trifluoro
ethane/trlchloro trifluoro
ethanone/dlhydroxynethoxyphenyl
ethene/ trlfluoro-chloro
ethylene/l/2-trans
ethylene/I/2-trans-dichloro
fur an
furan/dlethyl tetrahydro
furandlone/ethyl methyl
heptachlor epoxide<1024-57-3>
heptadecanoic acld<506-12-7>
heptadecanol
heptanolc acid
heptanol/2-propyl-l-
heptanoI/methyl
heptanone/2-<110-43-0>
heptanone/aethyl
1101
-------
Accession Ho. 9043000501
(cont)
hexadecanoic acid,methyl ester
hexadecanoic acid,methyl ester of
methyl
hexanedioic acid, demethyi ester
<627-93-0>
hexanoic acid<142-62-1>
hexanoic acid, ethyl ester of
ethyl
hexanoic acid,aethyl
hexanone,cyclo<108-94-l>
hydrofuran,tetra<109-99-9>
indenone,dihydro
indole,methyl
isobenzofuranone
isocyanatobenzene,chloro
ketene,aethylpropyl<29336-29-6>
ketone, aethyl ethyl
•ethane,chlorodibrono<124-48-l>
•ethane,dichlorobromo <75-27-4>
•ethane,dichlorodifluoro<75-43-4>
•ethane,dichlorofluoro
<75-43-4>
methane,trichlorofluoro<75-69-4>
nethanol,benzene<100-51-6>
•ethanol,dibutoxy<54518-04-6>
•ethanol,ethenyl benzene
•ethanone,bis (2-ethyIhexyl)
•ethanone, diphenyl
•ethyl benzoic acid,Methyl ester
•ethyl pentanoic acid,Methyl ester.
•ethyl ene, chloride<75-09-2>
•ycrenol
naphthalene, C5 alkyl
naphthalene/octachloro<2234-13-l>
naphthalene,phenyl
naphthalene, tri« ethyl dihydro
<53156-12-0>
nonadecenoic acid,methyl ester
nonanedioc acid,methyl ester
nonanedioic ac i d, b is (e thy Ihexyl)
ester of
nonanediol,methyl
nonanoic acid
nonanoic acid,methyl ester
<1731-84-6>
octadecadienoic acid, Methyl ester
octadecanoic acid<57-ll-4>
octadecanoic acid,methyl ester
octadecanoic acid, em thy 1 ester of
•ethyl
octadecenolc acid<57-ll-4>
octadecenoic acid,aethyl ester
octanoic acid,nethyl ester
pentadecanoic acid<1002-84-2>
pentadecanolc acid, nethyl
pentadecanoic acid, methyl ester
pentadecanoic acid, methyl ester
of Methyl
pentadiene, pentachlorocyclo
<25154-43-2>
pentadiene, tetrachlorocyc lo
<29590-82-7>
pentanediotlc acid, dimethyl ester
pentanoic acid<109-52-4>
pentanone, hydroxy methoxy
pentanone,hydroxy Methyl
pent ene, octachlorocyclo
<706 -78-5>
perylene<198-55-0>
phenanthrene, C2, alkyl
phenanthrene, C3 alkyl
phenanthrene,C4 alkyl
phenanthrene, C5 alkyl
phenanthrene, dimethyl
phenanthrene, aethyl
phenanthtenecarboxylicacid
octahydrodimethyl
phenanthrenedione
phenol, 2,4-dimethyl
phenol, bis dimethyl ethyl
pehnol,C2 alkyl
phenol, C4 alkyl
phenol, C8 alkyl
phenol, €9 alkyl
phenol^ dichloro methyl
phenol, dim ethyl ethyl
phenol, me thoxy
phenol, methoxypropenyl
pheno I/ Met hoxypropy 1
phenol, nitro,4<100-02-7>
phenol, tetrachloro<25167-83-3>
phosphoric acid/octyl diphenyleste
r <115-88-8>
phosphoric aicd/tributyl ester
<126-73-8>
phosphoric acid ,triphenyl
ester<115-86-6>
phthalate, di(methylpropyl)
phthalate, dip ropylphenyl
phtahla te, die thy 1< 84-66 -2>
phthalate, dodecyl
phthalate/ aethyl butyl
propane, 1,1-tr if luoro, 1,3-dlchloro
1102
-------
Accession So. 9043000501
(cont)
propanoic acid,benzene
propanolc acid,methyl
propanol,methoxy methyl ethoxy
propanone, hydroxymethoxyphenyl
propenoic acid,phenyl
pyrene,indeno(l,2, 3-CD)
<193-39-5>
pyrene,methyl
pyridine,methyl<1333-41-4>
qulnone,di- tertbutyl-benzo
sinatryne
sulfonamide,butyl methyl benzene
sulfonamide, nethyl benzene
sulfonaroide/triraethyl benzene
sulfonamide, triaethylbenzyl
sulfur<7704-34-9>
surfuric acid,dimethyl ester of
tetradecanoic acid <544-63-8>
tetradecanoic acid,methyl ester
<124-10-7>
tetradecanoic acid,methyl
ester of methyl
tetradlfon
triazine/trimethoxy
trichlorobenzene- 1*2,4
<120-82-l>
undecanoic acid/methyl ester of
cyclopentane
Acetaldehyde <75-07-0>
Acrolein <107-02-8>
Acrylonitrile <107-13-1>
allyl chloride <107-05-1>
Benzyl chloride <100-44-7>
Bis(chloromethyl)ether <542-88-l>
Carbon tetrachloride <56-23-5>
Chlorobenzene <108-90-7>
Chloroform <67-66-3>
Chloroprene <126-99-8>
o-Cresol <95-48-7>
m-Cresol <108-39-4>
p-Cresol <106-44-5>
p-Dichlorobenzene<106-46-7>
Dichloromethane <75-09-2>
Dimethylnitrosoamine <62-75-9>
Dioxane <123-91-1>
Dioxin <828-00-2>
Epichlorohydrin <106-89-8>
Ethylene dibromide (£DB)
<106-93-4>
Ethylene dichloride <107-06-2>
Ethylene oxide <75-21-8>
Forffialdehyde <50-00-0>
Hexachlorocyclopentadiene
<77-47-4>
Maleic anhydride <108-31-6>
Manganese and compounds
<7439-96-5>
Methyl chloroform <71-55-6>
Methyl iodide <74-88-4>
Nickel <7440-02-0>
Nitrobenzene <98-95-3>
2-Nitropropane <79-46-9>
N-Nitrosodiethylamine <55-18-5>
Nitrosomethylurea <684-93-5>
Nitrosonorpholine <59-89-2>
Perchloroethylene <127-18-4>
Phenol <108-95-2>
Phosgene <75-44-5>
Polychlorinated biphenyls (PCBs)
Toluene <108-88-3>
Vinylidene chloride <75-35-4>
Xylene <1330-20-7>
o-Xylene <95-47-6>
ra-Xylene <108-38-3>
p-Xylene
<106-42-3> Proplyene oxide
<75-56-9>
Trichloroethylene
<79-01-6> Benzene <71-43-2>
Beryllium <7440-41-7>
Mercury <7439-97-6>
¥inyl chloride
<75-01-4> Acenaphthene
<83-32-9>
Acenaphthylene <208-96-8>
Acrolein <107-02-8>
Acrylonitrile <107-13-1>
Aldrin <309-00-2>
Anthracene <120~12-7>
Antimony <7440-36-0>
Arsenic <7440-38-2>
Asbestos <1332-21-4>
BHC-.Alpha. <319-84-6>
BHC-.Beta. <319-85-7>
BHC (lindane)-.Gamma. <58-89-9>
BHC-.Delta. <319-86-8>
Benzene <71-43-2>
Benzidine <92-87-5>
Benzo(a)anthracene <56-55-3>
3,4-Benzofluoranthene <205-99-2>
Benzo(k) fluoranthene <207-08-9>
Ben2o(g,h,i)perylene <191-24-2>
BenzoCalpyrene <50-32-8>
Berylliui <7440-41-7>
1103
-------
Accession Mo. 9043000501
(cont)
Bis (2- chloroethoxy)me thane
<111-91-1>
Bis(2-chloroethyl)ether
Bls(2-chloroisopropyl) ether
<39638-32-9>
Bis (chloronethyi) ether
<542-88-l>
Bis(2-ethylhexyl)phthalate
BroBoaethane <74-83-9>
4-Bronophenyl phenyl ether
<101-55-3>
Butyl benzyl phthalate <85-68-7>
Cadmium <7440-43-9>
Carbon tetrachloride <56-23-5>
Chlordane <57-74-9>
Chloro benzene <1 08-90- 7>
Chlorodlbromomethane <124-48-l>
Chloroethane <75-00-3>
2-chloroethylvinyl ether
<110-75-8>
Chloroform <67-66-3>
P-Chloro-m-cresol <59-50-7>
Chloromethane <74-87-3>
2-Chloronaphthalene <91-58-7>
2-Chlorophenol <95-57-8>
4-Cfclorophenyl phenyl ether
<7005-72-3>
Chromium <7440-47-3>
Chrysene <2l8-01-9>
Copper <74 40-50- 8>
Cyanide < 57-1 2-5 >
<72-54-8>
<72-55-9>
4, 4 '-DDT <50-29-3>
Dlb«nzoCa^h3 anthracene <53-70-3>
Oi-n-butyl phthalate <84-74-2>
1,2-Dichlorobenzene <95-50-l>
1, 3-Dichlorobenzene <541-73-l>
1,4-Dichlorobenzene <106-46-7>
3,3'- Dichlorobenzldine <9l-94-l>
Dichlorobromomethane <75-27-4>
Dlchlorodifluoromethane <75-71-8>
1,1-Oichloroethane < 7 5- 34-3 >
1,2-Di chloro ethane <107-06-2>
1,1-Dichloroethylene <75-35-4>
1^2-trans-Dichloroethylene
<156-60-5>
DlcMorome thane <75-09-2>
2/4-Dlchlorophenol <120-83-2>
1^2-Dlchloropropane <78-87-5>
1/2-Dichloropropylene <563-54-2>
Oieldrin <60-57-l>
Oiethyl phthalate <84-66-2>
2,4- Dim ethyl phenol <105-67-9>
Dimethyl phthalate <131-ll-3>
4,6-Dinitro-o-cresol <534-52-l>
2/4-Dinitrophenol <51-28-5>
2,4-Dinitrotoluene <121-14-2>
2,6-Dinitrotoluene <606-20-2>
Di-n-octyl phthalate <117-84-0>
1/2-Diphenylhydrazine <122-66-7>
Endosul fan-, Alpha. <959-98-8>
Endosulfan-.Beta. <33213-65-9>
Endosulfan sulfate <1031-07-8>
Endrin <72-20-8>
Endrln aldehyde <7421-93-4>
Ethylbenzene <100-41-4>
Fluoranthene <206-44-0>
Fluorene <86-73-7>
Heptachlor <76-44-8>
Heptachlor epoxide <1024-57-3>
Hexachlorobenzene <118-74-l>
Hexachlorobutadiene <87-68-3>
Hexachlorocyclopentadiene
<77-47-4>
H ex ac hi or o ethane <67-72-l>
Indeno (1, 2,3-cd)pyrene < 193-3 9-5>
Isophorooe <78-59-l>
Lead <7439-92-l>
Mercury <7439-97-6>
•aphthalene < 91-20 -3>
•ickel <7440-02-0>
Nitrobenzene <98-95-3>
2-iitrophenol <88-75-5>
4-iitrophenol <100-02-7>
M-iitrosodimethylamine <62-75-9>
H-Mitrosodiphenylamine <86-30-6>
M-Iitrosodi-n- propylaalne
<621-64-7>
Pentachlorophenol <87-86-5>
Phenanthrene <85-01-8>
Phenol <108-95-2>
PCB-1016 (Arochlor 1016)
<12674-ll-2>
PCB-1221 (Arochlor 1221)
<11104-28-2>
PCB-1232 (Arochor 1232)
PCB-1242 (Arochlor 1242)
<53469-21-9>
PCB-1248 (Arochlor 1248)
<12672-29-6>
1104
-------
Accession Ho. 9043000501
(cont)
PCB-1254 (Arochior 1254)
<11097-69-l>
PCB-1260 (Arochior 1260)
<11096-82-5>
Pyrene <129-00-0>
Selenium <7782-49-2>
Silver <7440-22-4>
2,4,7,8-Tetrachlorodibenzo-p-
dioxin
Tetrachloroethylene <127-18-4>
Thallium <7440-28-0>
Toluene <108-88-3>
Toxaphene <8001-35-2>
Tribromomethane <75-25-2>
1,2,4-Trichlorobenzene <120-82-l>
1,1,1-Trichloroethane <71-55-6>
1,1,2-Trichloroethane <79-00-5>
Trichloroethylene <79-01-6>
Trichlorofluoronethane <75-69-4>
2,4,6- Trichlorophenol
<88-06-2>
Vinyl chloride <75-01-4>
Zinc <7440-66-6>
Acidity
Alkalinity
Dissolved Oxygen
Dissolved Solids
Fecal colifora
Nitrogen <7727-37-9>
Oil and Grease
Oxygen demand
PH
Phosphorus <7723-14-0>
Suspended solids
Arsenic <7440-38-2>
Barium <7440-39-3>
Cadmium <7440-43-9>
Chromium <7440-47-3>
2/4t-Dichlorcphenoxyacetic acid (2/
4-D) <94-75-7>
Endrin <72-20-8>
Lead <7439-92-l>
Lindane <58-89-9>
Mercury <7439-97-6>
Methoxychlor <72-43-5>
Microbiology-coliform bacteria
Nitrate <14797-55-8>
Selenium <7782-49-2>
Silver <7 440-2 2-4>
Silvex <93-72-l>
Toxaphene <8001-35-2>
Turbidity
Acetone <67-64-l>
n-alkanes (clO - c30)
Aluminum <7429-90-5>
Ammonia <7664-41-7>
Bariua <7440-39-3>
Biphenyl <92-52-4>
Bismuth and compounds <7440-69-9>
Boron and compounds <7440-42-8>
Bromine <7726-95-6>
Chlorine <7782-50-5>
Cobalt <7440-48-4>
2^4-d acid <94-75-7>
Demeton <8065-48-3>
Dialkyl ethers
Dibenzofuran <132-64-9>
Diphenyl ether <101-84-8>
Fluorides
Guthion <86-50-0>
Iron <7439-89-6>
Kepone <143-50-0>
Lithium and compounds <7439-93-2>
Malathion <121-75-5>
Manganese and compounds
<7439-96-5>
Methoxychlor <72-43-5>
Methyl ethyl ketone (MEK)
<78-93-3>
Mirex <2385-85-5>
Molybdenum and compounds
<7439-98-7>
Nitrates/Nitrites
Nltriloacetates
Parathion <56-38-2>
Phosphorus <7723-14-0>
Polybrominated biphenyls (PBBS)
Secondary amines
Sodium <7440-23-5>
Styrene <100-42-5>
Sulfates
Sulfides
Terpenes
2r4/5-Trichlorophenoxypropionic
acid (TP) <93-72-l>
Vanadium
<7440-62-2> Carbon
tetrachloride <56-23-5>
Chlorobenzene <108-90-7>
1^2-Dichlorobenzene <95-50-l>
Ir3-Dichlorobenzene <541-73-l>
1,,4-Dichlorobenzene <106-46-7>
1105
-------
Accession No. 9043000501
(cont)
1,2-Dichloroethane <107-06-2>
Radon <10043-92-2>
Tetrachloroethylene <127-18-4>
1,1,1-Trichloroethane <71-55-6>
Trichloroethylene <79-01-6>
UraniiiH <7440-61-1>
Vinyl chloride <75-01-4>
Alachlor <15972-60-8>
Atrazine <1912-24-9>
Banvel-D <1918-00-9>
Benefln <1861-40-1>
Bromobenzene <108-86-l>
Bromochlorobenzene <28906-38-9>
Bromodichloromethane <75-27-4>
Butachlor <23184-66-9>
ChlorodibrOBonethane
<124-48-1>
Cyanazine <21725-46-2>
Oibutyl ph thai ate <84-74-2>
cis-1,2-Dichloroethylene
<156-59-2>
I/2-trans- Oichloroethylene
<156-60-5>
Dichlorolodoreethane <594-04-7>
Diethyl phthalate <84-66-2>
Diphenylhydrazine <38622-18-3>
Ethyl chloride <75-00-3>
0-Methoxyphenol <90-05-1>
Mitralin <4726-14-l>
Phenylacetic acid <103-82-2>
Phorate <298-02-2>
Phthalic acid <88-99-3>
Propachlor <1918-16-7>
Propanil <709-98-8>
Propazine <139-40-2>
Simazine
<122-34-9> Acetaldehyde
<75-07-0>
Acetic acid <64-19-7>
Acetic anhydride <108-24-7>
Acetone cyanohydrin <7S-86-5>
Acetyl bromide <506-96-7>
Acetyl chloride <75-36-5>
Acrolein <107-02-8>
Acrylonitrile <107-13-1>
Adipic acid <124-04-9>
Aldrin <309-00-2>
Allyl alcohol <107-18-6>
Allyl chloride <107-05-1>
Aluminum sulfate <10043-01-3>
Ammonia <7664~41-7>
Ammonium acetate <631-61-8>
Ammonium benzoate <1863-63-4>
Ammonium bicarbonate <1066-33-7>
Amnonium bichromate <7789-09-5>
Amaoniuoi bifluoride <1341-49-7>
Amnonium bisulfite <10192-30-0>
Ammonium carbamate
Ammoniuffl carbonate <506-87-6>
Amaonium chloride <12125-02-9>
Ammonium chroaate <7788-98-9>
Amaonium citrate <7632-50-0>
Amaonium fluoborate <13826-83-0>
Ammonium fluoride <12125-01-8>
Amaonium hydroxide <1336-21-6>
Ammonium oxalate <1113-38-8>
Ammonium silicofluoride
<16919-19-0>
Ammoniun sulfaiate <7773-06-0>
Ammonium sulf ide <12135-76-l>
Aoaoniua sulfite <10196-04-0>
Ammoniun tartarate <3164-29-2>
Ammonium thiocyanate <1762-95-4>
Ammoniuffl thiosulf ate <7783-18-8>
Amyl acetate <628-63-7>
Aniline <62-53-3>
Antimony pentachloride
<7647-18-9>
Antimony potassium tartrate
Antimony tribromide <7789-61-9>
Antimony trichloride
<10025-91-9>
Antimony trifluoride <7783-56-4>
Antimony trioxide <1309-64-4>
Arsenic disulfide <1303-32-8>
Arsenic pentoxide <1303-28-2>
Arsenic trichloride <7784-34-l>
Arsenic trioxide <1327-53-3>
Benomyl <17804-35-2>
Benzac <50-31-7>
Benzole acid <65-85-0>
Benzonitrile <100-47-0>
Benzoyl chloride <98-88-4>
Benzyl chloride <100-44-7>
Beryllium chloride <7787-47-5>
Beryllium fluoride <7787-49-7>
Beryllium nitrate <13597-99-4>
Butyl acetate <123-86-4>
Butylaraine <109-73-9>
M-Butyl phthalate <84-74-2>
Butyric acid <107-92-6>
Cadmium acetate <543-90-8>
Cadmium bromide <7789-42-6>
1106
-------
Accession No. 9043000501
(cont)
Cadmium chloride
Calcium arsenate <7778-44-l>
Calcium arsenite <52740-16-6>
Calcium carbide <75-20-7>
Calcium chroraate <13765-19-0>
Calcium cyanide <592-01-8>
Calcium dodecylbenzenesulfonate
<26264-06-2>
Calcium hydroxide <1305-62-0>
Calcium hypochlorite <7778-54-3>
Calcium oxide <1305-78-8>
Captan <133-06-2>
Carbaryl <63-25-2>
Carbofuran <1563-66-2>
Carbon disulfide <75-15-0>
Carbon tetrachloride <56-23-5>
Chlordane <57-74-9>
Chlorine <7782-50-5>
Chlorobenzene <108-90-7>
Chloroform <67-66-3>
Chlorosulfonic acid <7790-94-5>
Chlorpyrifos <2921-88-2>
Chromic acetate <1066-30-4>
Chromic acid <7738-94-5>
Chromic sulfate <10101-53-8>
Chromous chloride <10049-05-5>
Cobaltous bromide <7789-43-7>
Cobaltous formate <544-18-3>
cobaltous sulfamate <14017-41-5>
Coumaphos <56-72-4>
Cresol <1319-77-3>
Crotonaldehyde <4170-30-3>
Cupric acetate
Cupric acetoarsenite <12002-03-8>
Cupric chloride <7447-39-4>
Cupric nitrate <3251-23-8>
Cupric oxalate <814-91-5>
Cupric sulfate <7758-98-7>
Cupric sulfate amreoniated
<10380-29-7>
Cupric tartrate <815-82-7>
Cyanogen chloride <506-77-4>
Cyclohexane <110-82-7>
2,4-D acid <94-75-7>
2/4-D esters
DDT
Diazinon <333-41-5>
Dicamba <1918-00-9>
Dichlobenil <1194-65-6>
Dichlone <117-80-6>
DicMorobenzene <25321-22-6>
Dichloropropen & Dichloropropane
mixture
2,2-Dichloropropionic acid
<75-99-0>
Dichlorvos (DDVP) <62-73-7>
Dieldrin <60-57-l>
Diethylamine <109-89-7>
Dimethylamine <124-40-3>
Dinitrobenzene <25154-54-5>
Dinitrophenol
Dinitrotoluene <25321-14-6>
Diquat <2764-72-9>
Disulfoton <298-04-4>
Diuron <330-54-l>
Dodecylbenzenesulfonic acid
<27176-87-0>
EDTA <60-00-4>
Endosulfan <115-29-7>
Endrin <72-20-8>
Epichlorohydrin <106-89-8>
Ethion <563-12-2>
Ethylbenzene <100-41-4>
Ethylenediamine <107-15-3>
Ethylene dibromide (EDB)
<106-93-4>
Ethylene dichloride <107-06-2>
Ferric aamonlum citrate
<1185-57-5>
Ferric ammonium oxalate
<14221-47-7>
Ferric chloride <7705-08-0>
Ferric fluoride <7783-50-8>
Ferric nitrate <10421-48-4>
Ferric sulfate <10028-22-5>
Ferrous ammonium sulfate
<10045-89-3>
Ferrous chloride <7758-94-3>
Ferrous sulfate <7720-78-7>
Formaldehyde <50-00-0>
Formic acid <64-18-6>
Fumaric acid <110-17-8>
Furfural <98-01-l>
Guthion <86-50-0>
Heptachlor <76-44-8>
Hexachlorocyclopentadiene
<77-47-4>
Hydrochloric acid <7647-01-05
Hydrofluoric acid <7664-39-3>
Hydrogen cyanide <74-90-8>
Hydrogen sulfide <7783-06-4>
Isoprene <78-79-5>
1107
-------
Accession No. 9043000501
(cont)
Isogropanolanine Dodecy I benzene
Sulfonate <54590-52-2>
Kelthane <115-32-2>
Kepone <143-50-0>
Lead acetate <301-04-2>
Lead arsenate <3687-31-8>
•Lead chloride <7758-95-4>
Lead fluoborate <13814-96-5>
Lead fluoride <7783-46-2>
Lead iodide <10101-63-0>
Lead nitrate <10099-74-8>
Lead stearate <1072-35-l>
Lead sulfate <7446-14-2>
Lead sulfide <1314-87-0>
Lead thiocyanate <592-87-0>
Lindane <58-89-9>
Lithium chronate <14307-35-8>
Malathion <121-75-5>
Maleic acid <110-16-7>
Maleic anhydride <108-31-6>
Mercaptodiraethur <2032-65-7>
Mercuric cyanide <592-04-l>
Mercuric nitrate <10045-94-0>
Mercuric sulfate <7783~35-9>
Mercuric thiocyanate <592-85-8>
Mercurous nitrate Methoxychlor
<72-43-5>
Methyl nercaptan <74-93-l>
Methyl methacrylate <80-62-6>
Methyl parathion <298-00-0>
Mevinphos <7786-34-7>
Mexacarbate <315-18-4>
Monoethylanine <75-04-7>
Mononethylamine <74-89-5>
Haled <300-76-5>
Naphthalen <91-20-3>
Naphthenic acid <1338-24-5>
Nickel ammonium sulfate
<7785-20-8>
Nickel chloride <7718-54-9>
Nickel hydroxide <12054-48-7>
Nickel nitrate <13138-45-9>
Nickel sulfate <7786-81-4>
Nitric acid <7697-37-2>
Nitrobenzene <98-95-3>
Nitrogen dioxide <10102-44-0>
Nitrophenol <25154-55-6>
Nitrotoluene
PotassiuB arsenate <7784-41-0>
Potassium arsenite <10124-50-2>
Potassiui bichroaate <7778-50-9>
Potassia chro«ate <7789-00-6>
Potassium cyanide <151-50-8>
Potassiua hydroxide <1310-58-3>
PotassiuB permanganate <7722-64-7>
Propargite <2312-35-8>
Propionic acid <79-09-4>
Propionic anhydride <123-62-6>
Pyrethrin <121-29-9>
Quinoline <91-22-5>
Resorcinol <108-46-3>
Seleniua oxide <12640-89-0>
Silver nitrate <7761-88-8>
Sodiun <7440-23-5>
Sodiui arsenate <7631-89-2>
Sodiun arsenile <7784-46-5>
Sodlua bichromate <10588-01-9>
Sodiun bifluoride <1333-83-l>
Sodiun bisulfite <7631-90-5>
Sodiui chroaate <7775-ll-3>
Sodium cyanide <143-33-9>
Sodium dodecylbenzenesulfonate
<25155-30-0>
Sodium fluoride <7681-49-4>
Sodium hydrosufide <16721-80-5>
Sodiun hydroxide <1310-73-2>
Sodiun hypochlorite <7681-52-9>
Sodiun nethylate <124-41-4>
Sodiun nitrite <7632-00-0>
Sodiun phosphate^ dibasic
<7558-79-4>
Sodiun phosphate, tribasic
<7601-54-9>
Sodiun selenite
Strontiun chronate <7789-06-2>
Strychnine <57-24-9>
Styrene <100-42-5>
Sulfuric acid <7664-93-9>
Sulfur nonochlorlde <10025-67-9>
IDE <72-54-8>
Tetraethyl pyrophosphate
<107-49-3>
Thallium sulfate 7446-18-6>
Toluene <108-88-3>
Toxaphene <8001-35-2>
Trichlorfon <52-68-6>
Trichloroethylene <79-01-6>
Trichlorophenol (TCP)
<25167-82-2>
2,4/5-Trichlorophenoxyacetic acid
(T) <93-76-5>
2,4/5-T anlnes
2,4,5-T esters
1108
-------
Accession No. 9043000501
(cont)
2,4,5- Trichlorophenoxypropionic
acid (TP) <93-72-l>
2,4,5-TP acid esters
Triethanolanine dodecylbenzenesulf
on-ate <27323-41-7>
Triethylamine <121-44-8>
Trinethylamine <75-50-3>
Oraryl acetate <541-09-3>
Oranyl nitrate <10102-06-4>
Vanadium pentoxide <1314-62-l>
Vanadyl sulfate <27774-13-6>
Vinyl acetate <108-05-4>
Vinylidene chloride <75-35-4>
Xylene <1330-20-7>
Xylenol <1300-71-6>
Zinc acetate <557-34-6>
Zinc ammonium chloride
Zinc borate <1332-07-6>
Zinc bronide <7699-45-8>
Zinc carbonate <3486-35-9>
Zinc chloride <7646-85-7>
Zinc cyanide <557-21-l>
Zinc fluoride <7783-49-5>
Zinc formate <557-41-5>
Zinc hydrosulfite
<7779-86-4>+ Zinc nitrate
<7779-88-6>
Zinc phenol sulfonate <127-82-2>
Zinc phosphide <1314-84-7>
Zinc silicofluoride <16871-71-9>
Zinc sulfate <7733-02-0>
Zirconium nitrate <13746-89-9>
Zirconium potassium fluoride
<16923-95-8>
Zirconium sulfate <14644-61-2>
Zirconium tetrachlorlde
<10026-ll-6>
Acrylonitrile <107-13-1>
Aldrln <309-00-2>
Aaitraz (Baam) <33089-61-1>
Aramite <140-57-8>
Arsenic <7440-38-2>
Arsenic acid <1327-52-2>
Arsenic pentoxide <1303-28-2>
Arsenic trioxide <1327-53-3>
Benomyl <17804-35-2>
Benzac <50-31-7>
Cadmium <7440-43-9>
Chloranil <118-75-2>
Chlordane <57-74-9>
Chlorobenzilate <510-15-6>
Chloroform <67-66-3>
Coal tar <8007-45-2>
Creosote <8021-39-4>
DDO(TDE)
DDT
Diallate <2303-16-4>
1*2-0ibromo-3-chloropropane (DBCP)
<96-12-8>
Dieldrin <60-57-l>
Dimethoate <60-51-5>
Endrin <72-20-8>
EBDC's (ethylenebisdithiocarbamate
s)
Ethylene adibromide (EDB)
<106-93-4>
Ethylene oxide <75-21-8>
EPN (ethyl p-nitrophenyl thiono-
benzenephosonate) <2104-64-5>
2-Fluoroacetamide (1081)
<640-19-7>
Heptachlor <76-44-8>
Kepone 143-50-0>
Lindane <58-89-9>
Naleic hydrazide <123-33-l>
Nirex <2385-85-5>
Honucon <150-68-5>
Octamethylpyrophosphoramide (ONPA)
<152-16-9>
Pentachloronltrobenzene {PCIB)
<82-68-8>
Pentachlorophenol <87-86-5>
Phenarsazine chloride <578-94-9>
Pronamidc <23950-58-5>
Safrole <94-59-7>
Silvex <93-72-l>
Sodium arsenate <7631-89-2>
Sodium arsenlte <7784-46-5>
Sodium fluoroacetate (1060)
<62-74-8>
Strobane <8001-50-1>
Strychnine <57-24-9>
Thiophanate methyl <23564-05-8>
Toxaphene <8001-35-2>
2,4,5-Trichlorophenol <95-95-4>
2,4/5-Trichlorophenoxyacetic acid
(I) <93-76-5>
Trifluraline (treflan) <1582-09-8>
Trysben <50-31-7>
Carbofuran <1563-66-2>
Chlocpyrifos <2921-88-2>
2,4-D acid <94-75-7>
Dialkyl phosphates
Dicamba <1918-00-9>
1109
-------
Accession No. 9043000501
(cont)
Ethyl parathion <56-38-2>
Malathion <121-75-5>
Methyl parathion <298-00-0>
Polychlorinated blphenyls (PCBs)
Propoxur <114-26-l>
Acetaldehyde <75-07-0>
Acrolein <107-02-8>
Acrylonitrile <107-13-1>
Antimony <7440-36-0>
Arsenic <7440-38-2>
Asbestos <1332-21-4>
Benzene <71-43-2>
Benzldine <92-87-5>
Benzyl chloride <100-44-7>
CadBium <7440-43-9)
Chlorinated ethanes
Chlorinated naphthalenes
Chloroethane <75-00-3>
Chlorofluorocarbons
Chiorofora <67-66-3>
Chloromethane <74-87-3>
Chloroprene <126-99-8>
Chromium <7440-47-3>
o-Cresol <95-48-7>
•-Cresol <108-39-4>
p-Cresol <106-44-5>
1, 2-Dibroao-3-chloropropane (DBCP)
<96-12-8>
1,2-Dichlorobenzene <95-50-l>
1,3-Dichlorobenzene <541-73-l>
1,4-Dichlorobenzene <106-46-7>
1,1-Dichloroethane <75-34-3>
1,2-Dichloroethane <107-06-2>
Dichloroaethane <75-09-2>
1,2-Dichloropropane <78-87-5>
2,4-Dinitrotoluene <121-14-2>
Oioxin <828-00-2>
Ethylnenzene <100-41-4>
Forsaldehyde <50-00-0>
Hexachlorobenzene <118-74-l>
flexachlorobutadiene <87-68-3>
Rexachlorocyclopentadiene
<77-47-4>
Hexachloroethane <67-72-l>
Isophorone <78-59-l>
Lead <7439-92-l>
Maleic anhydride <108-31-6>
Mercury <7439-97-6>
Methyl iodide <74-88-4>
Nitrobenzene <98-95-3>
2-Nitropropane <79-46-9>
Phosgene <75-44-5>
Polybroninated biphenyls (PBBs)
Polychlorinated biphenyls (PCBs)
If If2f2-Tetrachloroethane
<79-34-5>
Toluene <108-88-3>
Trichloroethane <25323-89-l>
1,1,1-trichloroethane <71-55-6>
1,1,2-Trichloroethene <79-01-6>
Vinylidece chloride <75-35-4>
o-Xylene <95-47-6>
m-Xylene <108-38-3>
p-Xylene <106-42-3>
Cacodylic acid <75-60-5>
Captan <133-06-2>
Carbaryl <63-25-2>
Carbon tetrachloride <56-23-5>
Dichlorvos (DD?P) <62-73-7>
Erbon <136-25-4>
Methanearsonates
Paraquat <4685-14-7>
Perthane <72-56-0>
Piperonyl butoxide <51-03-6>
Ronel <299-84-3>
Rotenone <83-79-4>
Triallate <2303-17-5>
S^S^S-Tributyl phosphorotrithioate
<78-48-8>
Trichlorfon <52-68-6>
-Trichlorfon <52-68-6>
Triputyl phosophorotrithioate
<78-48-8>
Acetaldehyde <75-07-0>
Acetone <67-64-l>
Acetonitrile <75-05-8>
Acetophenone <98-86-2>
2-Acetyla*inoflourene
Acetyl chloride <75-36-5>
Acrolein <107-02-8>
Acrylamide <79-06-l>
Acrylic acid <79-10-7>
Acrylonitrile <107-13-1>
Aldrin <309-00-2>
Allyl alcohol <107-18-6>
AlUBinuM phosphide <20859-73-8>
5-(Amino«ethyl)-3-isoxa70lol
<2763-96-4>
4-Aiinopyridine <504-24-5>
1110
-------
Accession No. 9043000501
(cont)
8-
(hydroxyaethyl)8-raethoxy-5-
nethyl-carbanate aririno
(2*,3*:3,4)pyrrolo(l,2-a)
indole-4,7-dione (ester)
Am it role <61-82-5>
Annonium picrate <131-74-8>
Aniline <62-53-3>
Arsenic acid <1327-52-2>
Arsenic pentoxide <1303-28-2>
Arsenic trioxide <1327-53-3>
Asbestos <1332-21-4>
Auranine <2465-27-2>
Azaserine <115-02-6>
Barium cyanide <542-62-l>
8enzCc3 acridine <225-51-4>
Benzal chloride <98-87-3>
Benzene <71-43-2>
Benzenesulfonyi chloride <98-09-9>
Enzenethiol <108-98-5>
Benzidine <92-87-5>
Benzo(a)anthracene <56-55-3>
BenzoCalpyrene <50-32-8>
Benzotrichloride <98-07-7>
Beryllium dust
Bis(2-chloroethozy)nethane
Bis(2-chloroethyl) ether
n.n-bis(2-chloroethyl)-2-naphthyla
nine <494-03-l>
bis(2-chloroisopropyl) ether
<39638-32-9>
bis(chloronethyl)ether <542-88-l>
Bls(2-ethylhexyl)phthalate
bronoacetone <598-31-2>
brofliomethane <74-83-9>
4-bronophenyl phenyl ether
<101-55-3>
brucine <357-57-3>
2-butanone peroxide <1338-23-4>
n-Butyl alcohol <71-36-3>
2-sec Butyl-4^6-dinitrophenol
<88-85-7>
calcium chro«ate <13765-19-0>
calcium cyanide <592-01-8>
carbob disulfide <75-15-0>
carbonyl fluoride <353-50-4>
chloroacetaldehyde <107-20-0>
chloral <75-87-6>
chloranbucil <305-03-3>
chloranil<118-75-2>
chlordane <57-74-9>
p-chloroaniline <106-47-8>
chlorobenzilate <510-15-6>
l-(p-chloroben2oyl)-5-raethoxy-2 -
methylindole-3-acetic acid
chlorodibromonethane <124-48-l>
l-chloro-2^3-epoxypropane
<106-89-8>
chloroethene <75-01-4>
chloroethyl vinyl ether <110-75-8>
chloroform <67-66-3>
p-chloro-m-cresol <59-50-7>
chloronethane <74-87-3>
chloronethyl nethyl ether
<107-30-2>
2-chloronaphthalene <91-58-7>
2-chlorophenol <95-57-8>
l-(o-chloropehnyl) thiourea
<5344-82-l>
3-chloropropionitrile <542-76-7>
.alpha.-chlorotoluene <100-44-7>
4-chloro-o-toluidine hydrochloride
<3165-93-3>
chrysene <218-01-9>
cooper cyanide <544-92-3>
Cresylic acid <1319-77-3>
Crotonaldehyde <4170-30-3>
cumene <98-82-8>
cyanide <57-12-5>
cyanogen <460-19-5>
cyanogen bromide <506-68-3>
cyanogen chloride <506-77-4>
cyclohexane <110-82-7>
cyclohexanone <108-94-l>
2-cyclohexyl-4^6-dinitrophenol
<131-89-5>
cyclophosphamide <50-18-0>
ddd(tde)
ddt
daunomvcin <20830-81-3>
diallate <2303-16-4>
dibenzoCa^hlanthracene <53-70-3>
dibenzolca^i] pyrene
<189-55-9>
dibroHochloromethane <124-48-l>
1^2-dibroBO-3-chloropropane Cdbcp)
<96-12-8>
1,2-dibromoethane <106-93-4>
dibronomethane <74-95-3>
di-n-butyl phthalate <84-74-2>
1111
-------
Accession Ho. 9043000501
(cont)
1,2-dlchloro benzene <95-50-l>
If 3-dichlorobenzene <541-73-l>
1,4-dichlorobenzene <106-46-7>
3,3'- dichlorobenzidlne <91-94-l>
l,4-dichloro-2-butene
dichlorodifluorovethane <75-71-8>
1,1-dichloroethane <75-34-3>
1, 2- dichloro ethane <107-06-2>
1,1-dichloroethylene <75-35-4>
1,2-trans-dichloroethylene
<156-60-5>
dichlorome thane <75-09-2>
2,4-dichlorophenol <120-83-2>
1t 6-dichlorophenol<87*65-0>
2/4-dichlorophenoxyacetic acid (2/
4-d) <94-75-7>
dichlorophenylarsine <696-28-6>
1,2- dlchloropropane <78-87-5>
1,3-dichloropropene <542-75-6>
dl«ldrin <60-57-l>
dlepoxybutane <1464-53-5>
di«thylarslna
1,2-diethylhydrazine <1615-80-1>
0, 0-diethyl-s-(2-«thylthio)
ethyl) ester of phosphor othioic
acid
0,0-diethyl-s-iethyl ester of
phosphorodithioic acid
phosphoro-thioate <297-97-2>
Ox 0-di ethyl phosphoric acidr 0-p-
nitrophenyl ester <311-45-5>
diethyl ph thai ate < 8 4- 66-2 >
diethylstilbestrol <56-53-l>
dihydrosafrole <94-58-6>
3^4 dl hydroxy- alpha- (» ethyl aaino) -
•ethyl benzyl alcohol
di-isopropylfluorophosphate
<55-91-4>
diaethoate <60-51-5>
3,3--diBethoxybenzidine <119-90-4>
3,3-dlBethyl-KBethylthio) -2*
butanone-O-C(aetiiylailno)
car bony IJoxiae <39196-18-4>
dlaethylajiine <124-40-3>
p-di«ethylaBinoazobenzene
If 1 2-dimethy IbenzC al anthracene
<57-97-6>
3,3*- diaethylbenzidine
<11 9-93-7 >
.alpha.,.alpha.- dlaethylbenzyl
hydro-peroxide <80-15-9>
diaethylcarba»oyl chloride
<79-44-7>
1,2-dUethylhydrazine <540-73-8>
diwethylnitrosoaaine <62-75-9>
• alpha*/.alpha.- diaethylphenethy
laaine <122-09-8>
2,4-diaethylphenol <105-67-9>
dUethyl phthalate <131-ll-3>
diaethyl sulfate <77-78-l>
4,6-dinitro-o-cresol <534-52-l>
2f4-d initrophenol <51-28-5>
2,4-dinitrotoluene <121-14-2>
2/6-dinitrotoluene <606-20-2>
dl-n-octyl phthalate <117-84-0>
1,4-dioxane <123-91-1>
1,2-diphenylhydrazine <122-66-7>
dlpropylaaine <142-84-7>
di-n-propylnitrosaBine <621-64-7>
2,4-dlthiobluret <541-53-7>
endosulfan <115-29-7>
endrin <72-20-8>
ethyl acetate <141-78-6>
ethyl acrylate <140-88-5>
ethylcyanide <107-12-0>
ethylene bisdithiocarbaiate
ethylenedia»ine <107-15-3>
ethyleneiaine <151-56-4>
ethylene oxide <75-21-8>
ethylene thiourea <96-45-7>
ethyl ether <60-29-7>
ethyl «ethaerylate <97-63-2>
ethyl aethanesulfonate <62-50-0>
ferric cyanide
fluoranthene <206-44-0>
fluorine <7782-41-4>
2-fluoroacetaaide (1081)
<640-19-7>
fluoroacetic acid/ sodiua salt
fluorotrichloroiiethane <75-69-4>
formaldehyde <50-00-0>
foralc acid <64-18-6>
furan <110-00-9>
furfural <98-01-l>
glycidylaldehyde
heptachlor <76-44-8>
hexachlorobenzene <118-74-1>
hexachlorobutadiene <87-68-3>
hexachlorocyclohexane <58-89-9>
hexachlorocyclopentadiene
<77-47-4>
1112
-------
Accession No. 9043000501
(cont)
hexachloroethane <67-72-l>
1,2,3, 4,10,10-hexachloro-l,4, 4a,5,
8,8a-hexahydro-l,425, 8-endo,
endo-diraethanonaphthalene
hexachlorophene <70-30-4>
hexaethyl tetraphosphate
<757-58-4>
hydrazine <302-01-2>
hydrocyanic acid <74-90-8>
hydrofluoric acid <7664-39-3>
hydrogen sulfide <7783-06-4>
hydroxydimethyl arsine oxide
<75-60-5>
indeno (1, 2,3-cd)pyrene
<193-39-5>
io do me thane <74-88-4>
iron dextran <9004-66-4>
isobutyl alcohol <78-83-l>
isocyanic acid, methyl ester
<624-83-9>
isosafrole <120-58-l>
kepone <143-50-0>
lasiocarpine <303-34-4>
lead acetate <301-04-2>
lead phosphate <7446-27-7>
lead subacetate <1335-32-6>
raaleic anhydride <108-31-6>
maleic hydrazide <123-33-l>
malononitrile <109-77-3>
melphalan <148-82-3>
mercury <7439-97-6>
mercury fulminate <628-86-4>
methanethiol <74-93-l>
methanol <67-56-l>
methapyrilene <91-80-5>
methomyl <16752-77-5>
methoxyphenol <90-05-1>
2- methylaziridine <75-55-8>
methyl chlorocarbonate <79-22-l>
3-nethylcholanthrene <56-49-5>
4,4'-methylene-bis-(2- chloroanili
ne) <101-14-4>
methyl ethyl ketone (nek)
<78-93-3>
methyl ethyl ketone peroxide
<1338-23-4>
methyl hydrazine <60-34-4>
methyl isobutyl ketone <108-10-1>
2-methyllactonitrile <75-86-5>
methyl methacrylate <80-62-6>
2-methyl-2-(methylthio)propionalde
hyde-o-(methylcarbonyl)oxime
n-methyl-n*-nitro-n-nitrosoguanidi
ne <70-25-7>
methyl parathion <298-00-0>
methylthiouracil <56-04-2>
naphthalene <91-20-3>
Ir4-naphthoquinone <130-15-4>
1-naphthylamine <134-32-7>
2-naphthylamine <91-59-8>
l-naphthyl-2-thiourea
<86-88-4>
nickel carbonyl <12612-55-4>
nickel cyanide <557-19-7>
nicotine <54-ll-5>
nitric oxide <10102-43-9>
p-nitroaniline <100-Ol-6>
nitrobenzene <98-95-3>
nitrogen dioxide <10102-44-0>
nitrogen peroxide <10l02-44-0>
nitrogen tetroxide <10544-72-6>
nitroglycerine <55-63-0>
4-nitrophenol <100-02-7>
2-nitropropane <79-46-9>
n-ni trosodi-n-butylamine
<924-16-3>
n-niftrosodlethanolamine
<1116-54-7>
n-nitrosodiethylamine <55-18-5>
n- nitrosodimethylamine <62-75-9>
n-nitrosodiphenylamine <86-30-6>
n-nitrosodi-n-propylaaine
<621-64-7>
n-nitroso-n- ethylurea
<759-73-9>
n-nitroso-n-methylurea <684-93-5>
n-nitroso-n-methylurethane
<615-53-2>
n- nitrosomethylvinylanine
n-nitrosopiperidine <100-75-4>
n-nitrosopyrrolidine <930-55-2>
5-nitro-o-toluidine <99-55-8>
octanethyIpyrophosphoramide (ompa)
<152-16-9>
oleyl alcohol condensed uith 2
•oles ethylene oxide
osmium tetroxide <20816-12-0>
7-oxabicycol(2.2.1)heptane-2x3-
dicarboxylic acid <145-73-3>
paraldehyde <123-63-7>
parathion <56-38-2>
pentachlorobenzene <608-93-5>
pentachloroethane <76-01-7>
1113
-------
Accession No. 9043000501
(cont)
pentachloronitrobenzene (pcnb)
<82-68-8>
pentachlorophenol <87-86-5>
1,3-pentadiene <504-60-9>
phenacetin <62-44-2>
phenol <108-95-2>
phenyl dichloroarsine <696-28-6>
phenylnerucry acetate
<62-38-4>
n-phenylthiourea <103-85-5>
phorate <298-02-2>
phosgene <75-44-5>
phosphlne <7803-51-2>
phosophorothioic acid, 0,0-
dinethyl ester, 0-ester with n,
n-dinethyl benzene sulfonanide
phosphorus sulfide <1314-80-3>
phthalic anhydride <85-44-9>
2-picoline <109-06-8>
potassiun cyanide <151-50-8>
potassium silver cyanide
<506-61-6>
pronaaide <23950-58-5>
1,2-propanediol <57-55-6>
1,3-propane sultone <1120-71-4>
propionitrile <107-12-0>
n-propylaraine <107-10-8>
2-propyn-l-Ol <107-19-7>
pyridine <110-86-l>
guinones
reserpine <50-55-5>
resorcinol <108-46-3>
saccharin <81-07-2>
safrole <94-59-7>
selenlous acid <7783-00-8>
seleniua sulfide <7446-34-6>
selenourea <630-10-4>
silver cyanide <506-64-9>
sodium azide <26628-22-8>
sodlua cyanide <143-33-9>
streptozotocin <18883-66-4>
strontium sulfide <1314-96-l>
strychnine <57-24-9>
1,2,4,5-tetrachlorobenzene
<95-94-3>
1,1,1,2-tetrachloroethane
<630-20-6>
If If7f2-tetrachloroethane
<79-34-5>
tetrachloroethene <127-18-4>
tetrachloroaethane <56-23-5>
2,3,4,6-tetrachlorophenol
<58-90-2>
tetraethylyl dithiopyrophospha
te <3689-24-5>
tetraethyl lead <78-00-2>
tetraethyl pyrophosphate
<107-49-3>
tetrahydrofuran <109-99-9>
tetranitronethane <509-14-8>
thallic oxide <1314-32-5>
thallium acetate <563-68-8>
thalliun carbonate
<29809-42-5>
thallium chloride <7791-12-0>
thalliun nitrate <10102-45-l>
thalliun selenite
thalliun sulfate <7446-18-6>
thioacetamide <62-55-5>
thiosenicarbazide <79-19-6>
thiourea <62-56-6>
thiuran <137-26-8>
toluene <108-88-3>
toluenedianine <25376-45-8>
toluene diisocyanate <26471-62-5>
o-toluidine hydrochloride
<636-21-5>
toxaphene <8001-35-2>
tribromonethane <75-25-2>
1,1,1-trichloroethane <71-55-6>
trichloroethene <79-01-6>
trichlorofluoronethane
<75-69-4>
trichloronethanethiol <75-70-7>
2,4,5- trichlorophenol
<95-95-4>
2^4,6-trichlorophenol <88-06-2>
2,4,5-trichlor ophenoxyacetic aci d
(t) <93-76-5>
2,4,5- trichlorophenoxypropion
ic acid (tp) <93-72-l>
trinitrobenzene <99-35-4>
t ri s(2f3-dibronopropy1)phosphate
<126-72-7>
trypan blue <72-57-l>
uracil nustard <66-75-l>
urethane <51-79-6>
vanadic acid <11115-67-6>
vanadiun pentoxide <1314-62-l>
xylene <1330-20-7>
zinc cyanide <557-21-l>
zinc phosphide <1314-84-7>
Arsenic <7440-38-2>
1114
-------
Accession No. 9043000501 (cont)
BariuiD <7440-39-3> Manganese and compounds
Beryllium <7440-41-7> <7439-96-5>
CadeiuB <7440-43-9> Mercury <7439-97-6>
ChroBiun <7440-47-3> Nickel <7440-02-0>
Cobalt <7440-48-4> Selenium <7782-49-2>
Copper <7440-50-8> Titanium <7440-32-6>
Iron <7439-89-6> Vanadium <7440-62-2>
Lead <7439-92-l>
(CAS) CAS registry numbers of substances included in data base: 50598-5
0-0; 103-82-2; 501-52-0; 203-12-3; 207-08-9; 205-99-2;
203-12-3; 191-24-2; 50-32-8; 26914-33-0; 25323-68-6; 110-42-9;
53-70-3; 95-50-1; 541-73-1; 106-46-7; 86-30-6; 1024-57-3;
1024-57-3; 506-12-7; 111-14-8; 110-43-0; 627-93-0; 142-62-1;
108-94-1; 109-99-9; 29336-29-6; 124-48-1; 75-27-4; 75-43-4;
75-43-4; 75-69-4; 100-51-6; 54518-04-6; 75-09-2; 2234-13-1;
53156-12-0; 1731-84-6; 57-11-4; 57-11-4; 111-11-5; 1002-84-2;
25154-43-2; 29590-82-7; 109-52-4; 706-78-5; 198-55-0; 100-02-7;
25167-83-3; 115-88-8; 126-73-8; 115-86-6; 84-66-2; 193-39-5;
7704-34-9; 544-63-8; 124-10-7; 120-82-1; 75-07-0; 107-02-8;
107-13-1; 107-05-1; 100-44-7; 542-88-1; 56-23-5; 108-90-7;
67-66-3; 126-99-8; 95-48-7; 108-39-4; 106-44-5; 106-46-7;
75-09-2; 62-75-9; 123-91-1; 828-00-2; 106-89-8; 106-93-4;
107-06-2; 75-21-8; 50-00-0; 77-47-4; 108-31-6; 7439-96-5;
71-55-6; 74-88-4; 7440-02-0; 98-95-3; 79-46-9; 55-18-5; 684-93-5;
59-89-2; 127-18-4; 108-95-2; 75-44-5; 108-88-3; 75-35-4;
1330-20-7; 95-47-6; 108-38-3; 106-42-3; 75-56-9; 79-01-6;
71-43-2; 7440-41-7; 7439-97-6; 75-01-4; 83-32-9; 208-96-8;
107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0; 7440-38-2;
1332-21-4; 319-84-6; 319-85-7; 58-89-9; 319-86-8; 71-43-2;
92-87-5; 56-55-3; 205-99-2; 207-08-9; 191-24-2; 50-32-8;
7440-41-7; 111-91-1; 111-44-4; 39638-32-9; 542-88-1; 117-81-7;
74-83-9; 101-55-3; 85-68-7; 7440-43-9; 56-23-5; 57-74-9;
108-90-7; 124-48-1; 75-00-3; 110-75-8; 67-66-3; 59-50-7; 74-87-3;
91-58-7; 95-57-8; 7005-72-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 72-54-8; 72-55-9; 50-29-3; 53-70-3; 84-74-2; 95-50-1;
541-73-1; 106-46-7; 91-94-1; 75-27-4; 75-71-8; 75-34-3;
107-06-2; 75-35-4; 156-60-5; 75-09-2; 120-83-2; 78-87-5;
563-54-2; 60-57-1; 84-66-2; 105-67*9; 131-11-3; 534-52-1; 51-28-5;
121-14-2; 606-20-2; 117-84-0; 122-66-7; 959-98-8; 33213-65-9;
1031-07-8; 72-20-8; 7421-93-4; 100-41-4; 206-44-0; 86-73-7;
76-44-8; 1024-57-3; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 91-20-3; 7440-02-0;
98-95-3; 88-75-5; 100-02-7; 62-75-9; 86-30-6; 621-64-7;
87-86-5; 85-01-8; 108-95-2; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 129-00-0;
7782-49-2; 7440-22-4; 79-34-5; 127-18-4; 7440-28-0; 108-88-3;
8001-35-2; 75-25-2; 120-82-1; 71-55-6; 79-00-5; 79-01-6;
75-69-4; 88-06-2; 75-01-4; 7440-66-6; 7727-37-9; 7723-14-0;
7440-38-2; 7440-39-3; 7440-43-9; 7440-47-3; 94-75-7; 72-20-8;
7439-92-1; 58-89-9; 7439-97-6; 72-43-5; 14797-55-8; 7782-49-2;
7440-22-4; 93-72-1; 8001-35-2; 67-64-1; 7429-90-5; 7664-41-7;
7440-39-3; 92-52-4; 7440-69-9; 7440-42-8; 7726-95-6; 7782-50-5;
1115
-------
Accession No. 9043000501 (cont)
7440-48-4; 94-75-7; 8065-48-3; 132-64-9; 101-84-8; 86-50-0;
7439-89-6; 143-50-0; 7439-93-2; 121-75-5; 7439-96-5; 72-43-5;
78-93-3; 2385-85-5; 7439-98-7; 56-38-2; 7723-14-0; 7440-23-5;
100-42-5; 93-72-1; 7440-62-2; 56-23-5; 108-90-7; 95-50-1; 541-73-1;
106-46-7; 107-06-2; 10043-92-2; 127-18-4; 71-55-6; 79-01-6;
7440-61-1; 75-01-4; 15972-60-8; 1912-24-9; 1918-00-9; 1861-40-1;
108-86-1; 28906-38-91 75-27-4; 23184-66-9; 124-48-1; 21725-46-2;
84-74-2; 156-59-2; 156-60-5; 594-04-7; 84-66-2; 38622-18-3;
75-00-3; 90-05-1; 4726-14-1; 103-82-2; 298-02-2; 88-99-3;
1918-16-7; 709-98-8; 139-40-2; 122-34-9; 75-07-0; 64-19-7;
108-24-7; 75-86-5; 506-96-7; 75-36-5; 107-02-8; 107-13-1;
124-04-9; 309-00-2; 107-18-6; 107-05-1; 10043-01-3;
7664-41-7; 631-61-8; 1863-63-4; 1066-33-7; 7789-09-5;
1341-49-7; 10192-30-0; 1111-78-0; 506-87-6; 12125-02-9; 7788-98-9;
7632-50-0; 13826-83-0; 12125-01-8; 1336-21-6; 1113-38-8;
16919-19-0; 7773-06-0; 12135-76-1; 10196-04-0; 3164-29-2;
1762-95-4; 7783-18-8; 628-63-7; 62-53-3; 7647-18-9; 11071-15-1;
7789-61-9; 10025-91-9; 7783-56-4; 1309-64-4; 1303-32-8;
1303-28-2; 7784-34-1; 1327-53-3; 17804-35-2; 50-31-7; 65-85-0;
100-47-0; 98-88-4; 100-44-7; 7737-47-5; 7787-49-7; 13597-99-4;
123-86-4; 109-73-9; 84-74-2; 107-92-6; 543-90-8; 7789-42-6;
7778-44-1; 52740-16-6; 75-20-7; 13765-19-0; 592-01-8;
26264-06-2; 1305-62-0; 7778-54-3; 1305-78-8; 133-06-2;
63-25-2; 1563-66-2; 75-15-0; 56-23-5; 57-74-9; 7782-50-5; 108-90-7;
67-66-3; 7790-94-5; 2921-88-2; 1066-30-4; 7738-94-5; 10101-53-8;
10049-05-5; 7789-43-7; 544-18-3; 14017-41-5; 56-72-4; 1319-77-3;
4170-30-3; 142-71-2; 12002-03-8; 7447-39-4; 3251-23-8; 814-91-5;
7758-98-7; 10380-29-7; 815-82-7; 506-77-4; 110-82-7; 94-75-7;
333-41-5; 1918-00-9; 1194-65-6; 117-80-6; 25321-22-6; 75-99-0;
62-73-7; 60-57-1; 109-89-7; 124-40-3; 25154-54-5; 25321-14-6;
2764-72-9; 298-04-4; 330-54-1; 27176-87-0; 60-00-4; 115-29-7;
72-20-8; 106-89-8; 563-12-2; 100-41-4; 107-15-3; 106-93-4;
107-06-2; 1185-57-5; 14221-47-7; 7705-08-0; 7783-50-8;
10421-48-4; 10028-22-5; 10045-89-3; 7758-94-3; 7720-78-7;
50-00-0; 64-18-6; 110-17-8; 98-01-1; 86-50-0; 76-44-8; 77-47-4;
7647-01-0; 7664-39-3; 74-90-8; 7783-06-4; 78-79-5; 54590-52-2;
115-32-2; 143-50-0; 301-04-2; 3687-31-8; 7758-95-4; 13814-96-5;
7783-46-2; 10101-63-0; 10099-74-8; 1072-35-1; 7446-14-2;
1314-87-0; 592-87-0; 58-89-9; 14307-35-8; 121-75-5; 110-16-7;
108-31-6; 2032-65-7; 592-04-1; 10045-94-0; 7783-35-9; 592-85-8;
72-43-5; 74-93-1; 80-62-6; 298-00-0; 7786-34-7; 315-18-4;
75-04-7; 74-89-5; 300-76-5; 91-20-3* 1338-24-5* 7785-20-8;
7718-54-9; 12054-48-7; 13138-45-9; 7786-81-4; 7697-37-2; 98-95-3;
10102-44-0; 25154-55-6; 7784-41-0; 10124-50-2; 7778-50-9;
7789-00-6; 151-50-8; 1310-58-3; 7722-64-7; 2312-35-8;
79-09-4; 123-62-6; 121-29-9; 91-22-5; 108-46-3; 12640-89-0;
7761-88-8; 7440-23-5; 7631-89-2; 7784-46-5; 10588-01-9;
1333-83-1; 7631-90-5; 7775-11-3; 143-33-9; 25155-30-0;
7681-49-4; 16721-80-5; 1310-73-2; 7681-52-9* 124-41-4;
7632-00-0; 7558-79-4; 7601-54-9; 10102-18-8; 7789-06-2;
57-24-9; 100-42-5; 7664-93-9; 10025-67-9; 72-54-8; 107-49-3;
108-88-3; 8001-35-2; 52-68-6; 79-01-6; 25167-82-2; 93-76-5;
1116
-------
Accession No. 9043000501 (cont)
93-72-1; 27323-41-7; 121-44-8; 75-50-3; 541-09-3; 10102-06-4;
1314-62-1; 27774-13-6; 108-05-4; 75-35-4; 1330-20-7;
1300-71-6; 557-34-6; 1332-07-6; 7699-45-8; 3486-35-9; 7646-85-7;
557-21-1; 7783-49-5; 557-41-5; 7779-86-4; 7779-88-6; 127-82-2;
1314-84-7; 16871-71-9; 7733-02-0; 13746-89-9; 16923-95-8;
14644-61-2; 10026-11-6; 107-13-1; 309-00-2; 33089-61-1;
140-57-8; 7440-38-2; 1327-52-2; 1303-28-2; 1327-53-3;
17804-35-2; 50-31-7; 7440-43-9; 118-75-2; 57-74-9; 510-15-6;
67-66-3; 8007-45-2; 8021-39-4; 2303-16-4; 96-12-8; 60-57-1;
60-51-5; 72-20-8; 106-93-4; 75-21-8; 2104-64-5; 640-19-7; 76-44-8;
58-89-9; 123-33-1; 2385-85-5; 150-68-5; 152-16-9; 82-68-8; 87-86-5;
578-94-9; 23950-58-5; 94-59-7; 93-72-1; 7631-89-2; 7784-46-5;
62-74-8; 8001-50-1; 57-24-9; 23564-05-8; 8001-35-2; 95-95-4;
93-76-5; 1582-09-8; 50-31-7; 1563-66-2; 2921-88-2; 94-75-7;
1918-00-9; 56-38-2; 121-75-5; 298-00-0; 114-26-1; 75-07-0;
107-02-8; 107-13-1; 7440-36-0; 7440-38-2; 1332-21-4; 71-43-2;
92-87-5; 100-44-7; 7440-43-9; 75-00-3; 67-66-3; 74-87-3;
126-99-8; 7440-47-3; 95-48-7; 108-39-4; 106-44-5; 96-12-8;
95-50-1; 541-73-1; 106-46-7; 75-34-3; 107-06-2; 75-09-2;
78-87-5; 121-14-2; 828-00-2; 100-41-4; 50-00-0; 118-74-1;
87-68-3; 77-47-4; 67-72-1; 78-59-1; 7439-92-1; 108-31-6;
7439-97-6; 74-88-4; 98-95-3; 79-46-9; 75-44-5; 79-34-5; 108-88-3;
25323-89-1; 71-55-6; 79-01-6; 75-35-4; 95-47-6; 108-38-3; 106-42-3;
75-60-5; 133-06-2; 63-25-2; 56-23-5; 62-73-7; 136-25-4; 4685-14-7;
72-56-0; 51-03-6; 299-84-3; 83-79-4; 2303-17-5; 78-48-8; 52-68-6;
52-68-6; 78-48-8; 75-07-0; 67-64-1; 75-05-8; 98-86-2; 75-36-5;
107-02-8; 79-06-1; 79-10-7; 107-13-1; 309-00-2; 107-18-6;
20859-73-8; 2763-96-4; 504-24-5; 61-82-5; 131-74-8; 62-53-3;
1327-52-2; 1303-28-2; 1327-53-3; 1332-21-4; 2465-27-2;
115-02-6; 542-62-1; 225-51-4; 98-87-3; 71-43-2; 98-09-9;
108-98-5; 92-87-5; 56-55-3; 50-32-8; 98-07-7; 111-91-1;
111-44-4; 494-03-1; 39638-32-9; 542-88-1; 117-81-7; 598-31-2;
74-83-9; 101-55-3; 357-57-3; 1338-23-4; 71-36-3; 88-85-7;
13765-19-0; 592-01-8; 75-15-0; 353-50-4; 107-20-0; 75-87-6;
305-03-3; 118-75-2; 57-74-9; 106-47-8; 510-15-6; 124-48-1;
106-89-8; 75-01-4; 110-75-8; 67-66-3; 59-50-7; 74-87-3;
107-30-2; 91-58-7; 95-57-8; 5344-82-1; 542-76-7; 100-44-7;
3165-93-3; 218-01-9; 544-92-3; 1319-77-3; 4170-30-3; 98-82-8;
57-12-5; 460-19-5; 506-68-3; 506-77-4; 110-82-7; 108-94-1;
131-89-5; 50-18-0; 20830-81-3; 2303-16-4; 53-70-3; 189-55-9;
124-48-1; 96-12-8; 106-93-4; 74-95-3; 84-74-2; 95-50-1; 541-73-1;
106-46-7; 91-94-1; 110-57-6; 75-71-8; 75-34-3; 107-06-2;
75-35-4; 156-60-5; 75-09-2; 120-83-2; 87-65-0; 94-75-7;
696-28-6; 78-87-5; 542-75-6; 60-57-1; 1464-53-5; 1615-80-1;
297-97-2; 311-45-5; 84-66-2; 56-53-1; 94-58-6; 55-91-4; 60-51-5;
119-90-4; 39196-18-4; 124-40-3; 60-11-7; 57-97-6; 119-93-7;
80-15-9; 79-44-7; 540-73-8; 62-75-9; 122-09-8; 105-67-9;
131-11-3; 77-78-1; 534-52-1; 51-28-5; 121-14-2; 606-20-2;
117-84-0; 123-91-1; 122-66-7; 142-84-7; 621-64-7; 541-53-7;
115-29-7; 72-20-8; 141-78-6; 140-88-5; 107-12-0; 107-15-3;
151-56-4; 75-21-8; 96-45-7; 60-29-7; 97-63-2; 62-50-0;
206-44-0; 7782-41-4; 640-19-7; 75-69-4; 50-00-0; 64-18-6;
1117
-------
Accession Ho. 9043000501 (cont)
110-00-9; 98-01-1; 76-44-8; 118-74-1; 87-68-3; 58-89-9; 77-47-4;
67-72-1; 70-30-4; 757-58-4; 302-01-2; 74-90-8; 7664-39-3;
7783-06-4; 75-60-5; 193-39-5; 74-88-4; 9004-66-4; 78-83-1;
624-83-9; 120-58-1; 143-50-0; 303-34-4; 301-04-2; 7446-27-7;
1335-32-6; 108-31-6; 123-33-1; 109-77-3; 148-82-3; 7439-97-6;
628-86-4; 74-93-1; 67-56-1; 91-80-5; 16752-77-5; 90-05-1;
75-55-8; 79-22-1; 56-49-5; 101-14-4; 78-93-3; 1338-23-4;
60-34-4; 108-10-1; 75-86-5; 80-62-6; 70-25-7; 298-00-0;
56-04-2; 91-20-3; 130-15-4; 134-32-7; 91-59-8; 86-88-4;
12612-55-4; 557-19-7; 54-11-5; 10102-43-9; 100-01-6; 98-95-3;
10102-44-0; 10102-44-0; 10544-72-6; 55-63-0; 100-02-7; 79-46-9;
924-16-3; 1116-54-7; 55-18-5; 62-75-9; 86-30-6; 621-64-7; 759-73-9;
684-93-5; 615-53-2; 100-75-4; 930-55-2; 99-55-8; 152-16-9;
20816-12-0; 145-73-3; 123-63-7; 56-38-2; 608-93-5; 76-01-7;
82-68-8; 87-86-5; 504-60-9; 62-44-2; 108-95-2; 696-28-6;
62-38-4; 103-85-5; 298-02-2; 75-44-5; 7803-51-2; 1314-80-3;
85-44-9; 109-06-8; 151-50-8; 506-61-6; 23950-58-5; 57-55-6;
1120-71-4; 107-12-0; 107-10-8; 107-19-7; 110-86-1; 50-55-5;
108-46-3; 81-07-2; 94-59-7; 7783-00-8; 7446-34-6; 630-10-4;
506-64-9; 26628-22-8; 143-33-9; 18883-66-4; 1314-96-1;
57-24-9; 95-94-3; 630-20-6; 79-34-5; 127-18-4; 56-23-5; 58-90-2;
3689-24-5; 78-00-2; 107-49-3; 109-99-9; 509-14-8; 1314-32-5;
563-68-8; 29809-42-5; 7791-12-0; 10102-45-1; 7446-18-6; 62-55-5;
79-19-6; 62-56-6; 137-26-8; 108-88-3; 25376-45-8; 26471-62-5;
636-21-5; 8001-35-2; 75-25-2; 71-55-6; 79-01-6; 75-69-4; 75-70-7;
95-95-4; 88-06-2; 93-76-5; 93-72-1; 99-35-4; 126-72-7; 72-57-1;
66-75-1; 51-79-6; 11115-67^6; 1314-62-1; 1330-20-7; 557-21-1;
1314-84-7; 7440-38-2; 7440-39-3; 7440-41-7; 7440-43-9; 7440-47-3;
7440-48-4; 7440-50-8; 7439-89-6; 7439-92-1; 7439-96-5; 7439-97-6;
7440-02-0; 7782-49-2; 7440-32-6; 7440-62-2
(CNM) Contact naae(s): Bennett,Jr,T«B. ; Conner,D.
(COR) Contact organization: Environmental Services Division/ Region
IV, Athens, GA
(ROR) Responsible Organization: Region IV.Environnental Services
Division.
1118
-------
Accession No. 9045000910
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Discharge Monitoring Report Files
(ACR) Acronym of Data Base or Model: DMRFILE
(MED) Media/Subject of Data Base or Model: Effluents point source
discharges
(ABS) Abstract/overview of Data Base or Model: Files contain discharge
monitoring reports (DMRs) submitted by holders of National
Pollutant Discharge Elimination System (NPDES) permits. It
contains chemical analyses of the effluents for those parameters
limited by their permit-any pollutants limited by a permit uould
be included.
(CTC) CONTACTS: Subject natter J.R. Patrick, Jr. (404)881-3973;
Computer-related J.R. P
(DTP) Type of data collection or monitoring: Point source data
collection industrial and municipal
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters included in the data base: Biological
data Collection method Compliance data Concentration measures ;
Discharge points ;Flou rates ^Geographic subdivision ;Industry ;
Inspection data Manufacturer ^Political subdivisions ;Production
levels ; Sampling date ;Site description ^Temperature
;Test/analysis method ; Treatment devices ;Use ;Volume/mass
measures
(DS) Time period covered by data base: 01-01-74 TO 09-30-80
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: quarterly ;0ther
Monthly for major sampling
(NOB) Number of observations in data base: 600000.(Estimated)
(NED Estimated annual increase of observations in data base: 100000.
(INF) Data base includes: Ran data/observations ;Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 15000.
(NCS) No. stations or sources currently originating/contributing data:
10000(()1800 (majors).)
(NOT) Number of facilities covered in data base (source monitoring): 15
000.
(GEO) Geographic coverage of data base: Selected federal region Region
IV
(LOC) Data elements identifying location of station or source include:
State ;County ;City ;Town/township ;Street address ^Coordinates
Latitude and Ion Project Identifier
(FAC) Data elements identifying facility include: Plant facility name
;PI ant location ^Parent corp name ^Parent corp location ; Street
address ;SIC code ;NPDES
(CDE) Pollutant identification data are: Uncoded
(LIM) Limitation/variation in data of which user should be aware: None
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Fditting: No known edit procedures exist.
(CBY) Data collected by: Self reporting discharge monitoring report
data ;State agency inspections data } Regional office Region IV,
1119
-------
Accession No. 9045000910 Ccont)
Surveillance and Analysis Lab inspection data / Contractor lab
headquarters inspection contractor ^Contractor inspections ;
EPA headquarters Rational Enforcement Investigations Center
(ABY) Data analyzed by: Self reporting discharge monitoring report
data
State agency inspection data
Regional office Region I?, Surveillance and Analysis Lab
inspections
Contractor lab inspections
Contractor inspections
EPA headquarters national Enforcement Investigations Center
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Compliance or enforcement
(AUT) Authorization for data collection: statutory authorization is P
L 92-500 as amended, Section 308 (Clean Hater Act-CHA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0073
(REP) Form of available reports and outputs of data base: Unpublished
reports Inspection Report (for inspection) Discharge Monitoring
Report data used for effluent guidelines reports; 208 plans.
(NUS) Number of regular users of data base: 15 offices
(OSR) Current regular users of data base: EPA headquarter offices
Effluent Guidelines Division; Office of Enforcement
EPA regional offices
EPA laboratories
States
EPA lab: National Enforcement Investigations Center
(CNF) Confidentiality of data and limits on access: 80 limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original .form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Semi-annually
(RSS) Related EPA automated systems which use data base: Permit
Compliance System II (PCS II); System for Consolidated Permitting
and Enforcement (SCOPE).
(RDBEPA) Related EPA data bases used In conjunction with this data base
Permit Compliance System (PCS); STORET (Storage Retrieval of Hater
Quality Data).
(ROB) Non-EPA data bases used in conjunction tilth this data base: state
systems-Mississippi
(CMP) Completion of form:
J.R. Patrick/ Jr.
QFC: EPA/Region If/Enforcement Division
AD: 345 Courtland St HE Atlanta, 6A 30365
PH: (404)881-3973
(DP) Date of form completion: 12-22-82
(NMAT) Number of substances represented in data base: 6
(NCAS) Number of CAS registry numbers in data base: 3
1120
-------
Accession io. 9045000910 (cont)
(NAT) Substances represented in data base:
biological oxygen de»and nickel<7440-02-0>
(BOD) ph
chroBium<7440-47-3> suspended solids
cyaitide<57-12-5>
(CAS) CAS registry nunbers of substances included in data base: 7440-47
-3; 57-12-5; 7440-02-0
(CNM) Contact naae(s): Patrick,J.R. ; Patrick,J.R.
(COR) Contact organizations Enforcement Division/ Region IV
(ROR) Responsible Organization: Region IV.Water Management Division*
1121
-------
Accession No* 9046000006
(OQ) Date of Questionalre: 12-02-82
(STATUS) status of entry: Inactive
(NAM) Name of Data Base of Model: Wasteload Allocation File
CACR) Acronym of Data Base or Model: VLA
(MED) Media/Subject of Data Base or Model: Effluents wastewater
UBS) Abstract/Overview of Data Base or Model: The MLA is a listing of
uasteload allocations which have been done by or approved by
Region. Pollutant data is partial and includes observed values
used to set uasteload allocations as received from states and
reviewed for impact on water quality by EPA (vodel
correlation).
(CTC) CONTACTS: Subject natter Joseph O'Connor (404)881-4793 ;
Computer-related Joseph
(DTP) Type of data collection or Monitoring: Point source data
collection industrial and.municipal facilities
(STA) Data Base status: Operational/ongoing
(6RP) Croups of substances represented in Data Base: 129 307 CHA ;11
conventional water ;15 metals
(NPP) Non-pollutant parameters included in the data base: Concentration
measures ^Discharge points ;Flou rates ;Geographic subdivision ;
Temperature
(DS) Time period covered by data base: 10-01-72 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: quarterly
(NOB) Number of observations in data base: 1300.(Estimated)
(NEI) Estimated annual increase of observations in data base: 100.
(IMF) Data base includes: Summary aggregate observations
(NTS) Total number of stations or sources covered in data base: 300.
(NCS) No. stations or sources currently originating/contributing data:
1 (time only/facility.)
(ROF) Number of facilities covered in data base (source monitoring): 30
0.
(GEO) Geographic coverage of data base: Selected federal region Region
IV
(LOO Data elements identifying location of station or source include:
State /Project identifier
(FAC) Data elements identifying facility include: Plant facility name
;Plant location
(CDE) Pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Recog
nize that data is incomplete at this time. Data is not stored
by pollutant, but rather on a facility basis in individual
reports. Sampling Plans, collection methods, and quality assurance
procedures are only documented in some cases (where submitted by
states).
(DPR) Data collect./anal, procedures conform to QRD guidelines: Samplln
g plan documented ^Collection method documented ;QA procedures
documented
(AMD Lab analysis based on EPA-approved or accepted methods? NO
(A0D) Lab Audit: Lab audit is satisfactory for generally not known.
(PRE) Precision: Precision and accuracy estimates partially -exist for
for some small portion of the state submissions
1122
-------
Accession Mo. 9046000006 (cent)
(EDT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: State agency all states in region I? and
their contractors jRegional office Regi
(ABY) Data analyzed by: Regional office Region IV, Water Division
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Reference system
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended, Section 303(d) (Clean Water Act-CWA)
(OMB) Data collected/submit ted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
request
(MUS) Number of regular users of data base: 6
(USR) Current regular users of data base: EPA regional offices
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Magnetic disc ;0riginal fora (hardcopy,
readings) ;0riginal form (hardcopy, read Magnetic disc: index only
(DAC) Type of data access: Manually ;EPA hardware PDP II
(CHG) Direct charge for non-EPA use: No
(DPDT) Frequency of data base master file up-date: Quarterly
(CMP) Completion of form:
R. F. HeGhee
OFC: EPA/Region IV/Water Division
AD: 345 Courtland St., ME Atlanta, GA 30308
Pfl: (404)881-4793
(DF) Date of form completion: 12-22-82
(NMAT) Number of substances represented in data base: 22
(NCAS) Number of CAS registry numbers in data base: 15
(MAT) Substances represented in data base:
ammonia<7664-41-7>
arsenic<7440-38-2>
cadmium<7440-43-9>
chromium<7440-47-3>
copper<7440-50-8>
cyanide<57-12-5>
dissolved oxygen
dissolved solids
fecal coliform
lead<7439-92-l>
manganese<7439-96-5>
mercury<7439-97-6>
nickel<7440-02-0>
ni trogen<7727-37-9>
oil and grease
oxygen demand
PH
phenol<108-95-2>
phosphorus<7723-14-0>
silver<7440-22-4>
suspended solids
1123
-------
Accession Mo* 9046000006 (cont)
zinc<7440-66-6>
(CAS) CAS registry numbers of substances includeo in data base: 7664-41
-7; 7440-38-2; 7440-43-9; 7440-47-3; 7440-50-8; 57-12-5;
7439-92-1; 7439-96-5; 7439-97-6; 7440-02-0; 7727-37-9;
108-95-2; 7723-14-0; 7440-22-4; 7440-66-6
(CNN) Contact naae(s): O'Connor,J. ; 0'Connor,J*
(COR) Contact organization: Region Ift Mater Division
(RQR) Responsible Organization: Region If.Hater Manageaent Division*
1124
-------
Accession No. 9048000909
(DQ) Date of Questionaire: 12-02-82
(NAM) Kame of Data Base of Model: Bioassay Studies
(ACR) Acronym of Data Base or Model: None
(MED) Pedia/Subject of Data Base or Model: Effluents all point sources
;Runoff urban/ rural and industrial ; Sediment ^Surface water
streams, lakes, estuary ;0ther hazardous waste
(ABS) Abstract/Overview of Data Base or Model: Bioassay studies which
include SIC codes/ industry/ location of tests/ results/
receiving water/ along with results of organism affect lethality
(LC50) or effect (EC 50), Have so»e chemical data for earlier
studies FY75-76 in the data base.
(CTC) CONTACTS: Subject matter Environmental Research Lab - Athens/
GA ; Computer-relat
(DTP) Type of data collection or monitoring: Combination/Other
ambient, non-point source and point source (municipal and
industrial)
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters Included in the data base: Biological
data ;Concentration measures ;Geographic subdivision ; Industry
^Location ^Salinity ^Sampling date ;Test/analysis method ;
Volume/mass measures ;lethality (LC 50) ;effect (EC 50)
(DS) Time period covered by data base: 08-01-74 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 349 bioassays.(Estimated)
(NEI) Estimated annual increase of observations in data base: 70
(bioassays.)
(INF) Data base includes: Summary aggregate observations ;summary of
results
(NTS) Total number of stations or sources covered in data base: 286
(or less.)
(NCS) No. stations or sources currently originating/contributing data:
(N/A.)
(NOF) Number of facilities covered in data base (source monitoring): 20
0 (or less.)
(GCO) Geographic coverage of data base: Selected federal region Region
IY
(LOC) Data elements identifying location of station or source include:
State
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ;Parent corp name ^Parent corp location ; Street
address ;SIC code JNPDES
(CDE) Pollutant identification data are: Other coding scheme STORET
compatible scheme under development.
Dncoded
(LIM) Limitation/variation in data of which user should be aware: Basic
approach at all times. LC 50 (lethality) measures for more than 50%
of tests-EC 50 (effect) measures for fewer. Have more data on
flow through tests (31% of data base) than on static tests
(69%)
(DPR) Data collect./anal, procedures conform to ORD guidelines: ORD
Guidelines
1125
-------
Accession No. 9048000909 (cont)
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist for all
measureaents
(EOT) Editting: No known edit procedures exist,
(CBY) Data collected by: Regional office Surveillance and Analysis
Laboratory
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Laboratory
(IDL) Laboratory identification: NO
(AUT) Authorization for data collection: Statutory authorization is P
L 95-217, Section 308 (Clean Hater Act-CHA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Fora of available reports and outputs of data base: Publications
by survey title
Unpublished reports so»e combined into summary
printouts on request
Machine-readable raw data
(NUS) Number of regular users of data base: 1 office
(DSR) Current regular users of data base: EPA regional offices
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Magnetic tape /Original form (hardcopy,
readings)
(DAC) Type of data access: Coaaercial software Inform 11 application
being developed >EPA hardware IBM 370/ water quality parameters
tracking systea software
(CHG) Direct charge for n on-EPA use: No
(OPDT) Frequency of data base master file up-date: Quarterly
(RDBEPA) Related EPA data bases used in conjunction with this data base
STORET (Storage and Retrieval of Hater Quality Data)
(CMP) Completion of form:
William H. Peltier
OFC: EPA/Region lY/Environaental Research Lab-Athens/
Surveillance and Analysis Division
AD: College Station Road, Athens, GA 30613
PH: (404)546-2294
(OF) Date of form completion: 02-01-83
(NMAT) Number of substances represented in data base: 4
(MAT) Substances represented in data base:
alkalinity pH
dissolved oxygen total hardness
(CNM) Contact name{s): Lab,E.R. ; Lab,E.R.
(COR) Contact organization: Environmental Research Lab - Athens, GA
(ROR) Responsible Organization: Region IV.Environaental Services
Division.
1126
-------
Accession No. 9048000910
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Listing of Organic Compounds
Identified in Region IV
(ACR) Acronym of Data Base or Model: LUCIFER
(MED) Media/Subject of Data Base or Model: Drinking vater ;£ffluents
industrial and municipal ;Ground water ; Sediment ;Soil
;Surface water all types ^Tissue fish
(ABS) Abstract/Overview of Data Base or Model: LUCIFER contains a
listing of all organic compounds identified in all environmental
samples taken in Region IV during January 1971 thru December 1977,
and analyzed by the Surveillance and Analysis Division laboratory
of Region IV. Included in the data base are: name of
compound, concentration, sample source, date sampled, receiving
stream, SIC code, CAS number, media sampled, sample type, project
type, chemical class, and analytical method. Data base contains
216 additional pollutants not listed here. Selected projects
from 1978, 1979 and 1980 have also been entered.
(CTC) CONTACTS: Subject matter E. William Loy, Jr. (404) 546-3165
; Computer-related U
(DTP) Type of data collection or monitoring: Combination/Other all
types of data collection
(STA) Data Base status: Discontinued
(GRP) Groups of substances represented in Data Base: 43 air priority
chemicals ;5 NESHAPS ;129 307 CMA ;41 CMA potential criteria ; 21
drinking Hater standards ;9 potential drinking yater ;29 drinking
vater monitoring ; 299 hazardous substances >48 cancelled
pesticides ;9 monitoring pesticides ; 54 TSCA assessment ;16
Pre-RPAR
(NPP) Non-pollutant parameters included in the data base: Chemical
data /Collection method Compliance data ;Concentration measures ;
Discharge points ;lndustry ^Location ;Sampling date jTest/analysis
method
(DS) Time period covered by data base: 01-01-71 TO 02-20-80
(TRM) Termination of data collection: Terminated June *81
(FRQ) Frequency of data collection or sampling: Other as time none
available (when needed)
(NOB) Number of observations In data base: 8333.(Actual)
(INF) Data base includes: Ran data/observations ;Su«mary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 649.
(NCS) No. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 18
n
(€EO) Geographic coverage of data base: Selected federal region Region
IV
(LOC) Data elements identifying location of station or source include:
State >City ;Town/township
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ;SIC code
(CDE) Pollutant identification data are: Uncoded
(LIM) Limitation/variation in data of which user should be aware: Colle
1127
-------
Accession No. 9048000910 (cont)
ction method identified, not entity collecting/ in data
collection and analysis procedures documentation.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Collect
ion method docuaented ;Analysis method documented ;QA procedures
document
CAUL) Lab analysis based on EPA-approved or accepted methods? YES
(AOD) Lab Audit: Lab audit is satisfactory.
(PRE) Precisions Precision and accuracy estimates exist but are not
included in data base
(EOT) Emitting: No known edit procedures exist.
(CBY) Data collected by: Regional office Lab Services Branch,
Surveillance and Analysis Division, Region
(ABY) Data analyzed by: Regional office Lab Services Branch,
Surveillance and Analysis Division, Region IV
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collections Compliance or enforcement
(PR2) Secondary purpose of data collection: Special study
CAOT) Authorization for data collection: Mo statutory requirement:
Data collection requirement is Data base needed for retrieval of
organics identified by Region I¥ because no SfORET codes Here
available.
COMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
request
(HUS) Number of regular users of data base: 5 per year
(USR) Current regular users of data base: EPA headquarter offices
Office of Toxic Substances
(CMF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: (Tape, storage)
(DAC) Type of data access: EPA software LOCIFER jEPA hardware POP 1170
Region I? ._ ,
(CHG) Direct charge for non-EPA use: no outside use/access permitted
because no edit proofing of data
(OPDT) Frequency of data base master file up-date: Terminated June '82
(CMP) Completion of form:
E. Milliam Loy, Jr.
OFC: EPA/Region 17/Surveillance and Analysis Division
AD: Athens, 6A
PH: (404) 546-3165
(DP) Date of form completion: 01-28-83
(HMAT) Number of substances represented in data base: 373
(MCAS) Number of CAS registry numbers in data base: 202
(MAT) Substances represented in data base:
l,l-dichloro«thane<75-34-3> l,4-dichlorobenzene<106-46-7>
l,2,4,-trichlorobenzene<120-82-l> 2,4,7,8-tetrachlorodibenzo-p-
l,2-dichlorobenzene<95-50-l> dioxin (tcdd)
l,2-dichloroethane<107-06-2> 2,4-dichlorophenol<120-83-2>
1,2-dichloropropane<78-87-5> 2-chloroethylvinyl ether<110-75»8>
If3-dichlorobenzene<541-73-l> 2-nitrophenol<88-75-5>
1128
-------
Accession No. 9048000910
(cont)
2-nitropropane<79-46-9>
4,4--ddd(p,p'tde)
4, 4 '-dde(p,p '-ddx)<72-55-9>
4,4'-ddt<50-29-3>
4,6-dinitro-o-cresol<534-52-l>
4-nitrophenol<100-02-7>
acenaphthene< 83-32-9>
ace tal deny de<75-07-0>
acrylonitrile<107-13-l>
aldrin<309-00-2>
benzene<71-43-2>
bis(2-chloroethoxy)methane
bis{2-chloroethyl)ether
bis(2-chlorolsopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
broBoniethane<74-83-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodibroaomethane<124-48-l>
chloroform<67-66-3>
chlcromethane<74-87-3>
chrysene<218-01-9>
dichloroaethane<75-09-2>
dieldrin<60-57-l>
die thy 1 phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
dio>ane<123-91-l>
dioxin<828-00-2>
endrin<72-20-8>
ethylbenzene<100-41-4>
fluoranthene<206-44-0>
f luorene< 86-73-7>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene< 77-47- 4>
hexachloroethane<67-72-l>
isophorone<78-59-l>
m-cresol<108-39-4>
m-xylene<108-38-3>
nitrobenzene<98-95-3>
o-cresol<95-48-7>
o-xylene<95-47-6>
p-cresol
P-xy lene< 1 06 -42-3>
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1248 (arochlor 1248)
<12672-29-6>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorophenol<87-86-5>
phenanthrene<85-01-8>
phenol<108-95-2>
polychlorinated biphenyls (PCBs)
pyrene<129-00-0>
tetrachloroethylene<127-18-4>
toluene<108-88-3>
toxaphene<8001-35-2>
tribrooo«ethane<75-25-2>
trichloroethylene<79-01-6>
l/l-dichloroethane<75-34-3>
1,2-dichlorob 1,2-dichl or oe thane
<107-06-2>
lf3-dichlorobenzene<541-73-l>
1^4-dichlorobenzene<106-46-7>
2^4/5-t esters
2,4,5-trichlorophenoxyacetic acid
(T)<93-76-5>
2r4-d acid<94-75-7>
2,4-dichlorophenoxyacetic acid (2,
4-d)<94-75-7>
2/-4-dinitrotoluene<121-14-2>
2-nitropropane<79-46-9>
acetone<67-64-l>
acrylonitrile<107-13-l>
aldrin<309-00-2>
aniline<62-53-3>
atrazine<1912-24-9>
benzene<71-43-2>
benzole acid<65-85-0>
biphenyl<92-52-4>
bromodichloroaethane<75-27-4>
carbon disulfide<75-15-0>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorofor«<67-66-3>
chloroaethane<74-87-3>
cresol<1319-77-3>
ddd(tde)
ddt
dibenzofuran<132-6 4-9>
dicaaba<1918-00-9>
dichlorobenzene<25321-22-6>
dichlorofflethane<75-09-2>
dichloropropane<78-87-5>
dieldrin<60-57-l>
1129
-------
Accession No. 9048000910
(cent)
diethyl phthalate<84-66-2>
dinitrobenzene<25154-54-5>
dini tr otoluene< 25321-14-6>
dioxin<828-00-2>
diphenyl ether<101-84-8>
endrin<72-20-8>
ethyl parathion<56-38-2>
ethylbenzene<100-41-4>
ethylene oxide<75-21-8>
heptachlor<76-44-8>
hexachlorobenzene
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
tiexacloroethane<67*72-l>
isophorone<78-59-1>
«-cresol<108-39-4>
M-xylene<108-38-3>
methyl parathion<298-00-0>
mirex< 2385-8 5-5>
naphthalene<91-20-3>
nitrobenzene<98-95-3>
nitrophenol<25154-55-6>
nitrotoluene
o-cresol<95-48-7>
o-nethoxyphenol<90-05-l>
o-xylene<95-47-6>
p-crcsol<106-44-5>
p-xylene<106-42-3>
parathlon<56-38-2>
pentachlorophenol<87-86-5>
phenol<108-95-2>
phosgene<75-44-5>
phthalic acid<88-99-3>
polychlorinated biphenyls (PCBs)
propachlor<1918-16-7>
propionic acid<79-09-4>
strobane<8001-50-l>
styrene<100-42-5>
tde<72-54-8>
terpenes
tetrachloroethylene<127-l8-4>
toluene<108-88-3>
toxaphene<8001-35-2>
trichloroethylene<79-01-6>
trichlorophenol (TCP)<25167-82-2>
triethylaaine<121-44-8>
xylene<1330-20-7>
xylenol<1300-71-6>
BHC-alpha<319-84-6>
BHC-beta<319-85-7>
BHC (lindane)-ganna<58-89-9>
BHC-delta<319-86-8>
broao«ethane<74-83-9>
butyric acid<107-92-6>
chlorofor«<67-66-3>
p-chloro-«-cresol
cycloh€xane<110-82-7>
dibenzota,h3anthracene<53-70-3>
1,4-dichlorobenzene <106-46-7>
dichlorobrononethane<75-27-4>
dichlorodifluoromethane <75-71-8>
2,4-diaethylphenol<105-67-9>
endosulfan-beta<33213-65-9>
indeno(l/2/3-cd)pyrene<193-39-5>
lindane
•ethyl ethyl ketone (MEK)
<78-93-3>
1^1/2,2-tetrachloroethane<79-34-5
1^1/2^2- tetcachloroethane
<79-34-5>
l,l,2-trichloroethane<79-00-5>
trichlorofluoronethane<75-69-4>
propylene oxide<75-56-9>
(CAS) CAS registry numbers of substances included in data base: 75-34-3
; 120-82-1; 95-50-1; 107-06-2; 78-87-5; 541-73-1; 106-46-7;
120-83-2; 110-75-8; 88-75-5; 79-46-9; 72-55-9; 50-29-3;
534-52-1; 100-02-7; 83-32-9; 75-07-0; 107-13-1; 309-00-2;
71-43-2; 111-91-1; Hl-44-4; 39638-32-9; 117-81-7; 74-83-9;
56-23-5; 57-74-9; 108-90-7; 124-48-1; 67-66-3; 74-87-3; 218-01-9;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 123-91-1; 828-00-2; 72-20-8;
100-41-4; 206-44-0; 86-73-7; 76-44-8; 118-74-1; 87-68-3; 77-47-4;
67-72-1; 78-59-1; 108-39-4; 108-38-3; 98-95-3; 95-48-7; 95-47-6;
106-44-5; 106-42-3; 53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5;
87-86-5; 85-01-8; 108-95-2; 129-00-0; 127-18-4; 108-88-3;
8001-35-2; 75-25-2; 79-01-6; 75-34-3; 107-06-2; 541-73-1;
106-46-7; 93-76-5; 94-75-7; 94-75-7; 121-14-2; 79-46-9;
67-64-1; 107-13-1; 309-00-2; 62-53-3; 1912-24-9; 71-43-2;
65-85-0; 92-52-4; 75-27-4; 75-15-0; 56-23-5; 57-74-9; 67-66-3;
1130
-------
Accession No. 9048000910 (cont)
74-87-3; 1319-77-3; 132-64-9; 1918-00-9; 25321-22-6; 75-09-2;
78-87-5; 60-57-1; 84-66-2; 25154-54-5; 25321-14-6; 828-00-2;
101-84-8; 72-20-8; 56-38-2; 100-41-4; 75-21-8; 76-44-8;
118-74-1; 87-68-3; 77-47-4; 67-72-1; 78-59-1; 108-39-4;
108-38-3; 298-00-0; 2385-85-5; 91-20-3; 98-95-3; 25154-55-6;
95-48-7; 90-05-1; 95-47-6; 106-44-5; 106-42-3; 56-38-2;
87-86-5; 108-95-2; 75-44-5; 88-99-3; 1918-16-7; 79-09-4;
75-56-9; 8001-50-1; 100-42-5; 72-54-8; 127-18-4; 108-88-3;
8001-35-2; 79-01-6; 25167-82-2; 121-44-8; 1330-20-7; 1300-71-6;
319-84-6; 319-85-7; 58-89-9; 319-86-8; 74-83-9; 107-92-6;
67-66-3; 59-50-7; 110-82-7; 53-70-3; 106-46-7; 75-27-4;
75-71-8; 105-67-9; 33213-65-9; 193-39-5; 58-89-9; 78-93-3;
79-34-5; 79-34-5; 79-00-5; 75-69-4
(CMM) Contact nane(s): Loy/E.H. ; Holsomback,H. ; Loy/E.N.
(ROR) Responsible Organization: Region IV.Environmental Services
Division.
1131
-------
Accession No. 9048000911
(DO) Date of Questionaire: 12-02-82
(NAM) Sane of Data Base of Model: State Intensive Surveys (water)
(ACR) Acronym of Data Base or Model: None
(MED) Fedia/Subject of Data Base or Model: Effluents all point source*
fRunoff urban and rural (occasionally) ; Sediment ;Surface water
streams ;Other Ground Hater: only occasionally sampled
(A8S) Abstract/Over view of Data Base or Model: Under the Basic Hater
Monitoring Program and 106 funds, each state conducts special
purpose studies (e.g. for waste- load allocations. In Region
IV: AL, FLA, GA, K¥, and MS do not put the data into STORET/NC,
SC, and IN data are included in STORED. GA maintains its own
computer data base without the station location information
needed by STORET. EPA does receive (generally) abstracts or
reports of these studies.
(CTC) CONTACTS: Subject natter Each individual state ; EPA
Office Appropriate Regional 0
(DTP) Type of data collection or monitoring: Combination/Other
Ambient, non-point source, and point source
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters Included in the data base: Biological
data ;Cheaical data ;Collection method ;Compliance data ;
Concentration measures /Discharge points ^Disposal ;Elevation ;
Flow rates ;Geographic subdivision ^Location ^Physical data ;
Political subdivisions ;Salinity ;Sampling date ;Site description ;
Temperature ;Test/analysis method ;Yolume/mass measures
^conductivity } transparency
(DS) Time period covered by data base: 01-01-76 TO 12-01-82
(TRM) Termination of data collection: Not applicable
(FRQ) Frequency of data collection or sampling: one time only ;as
needed jOther repeated as necessary (theoretically every 5 yea
(NOB) Number of observations in database: 15000.(Estimated)
(INF) Data base includes: Raw data/observations ; Summary aggregate
observations ; whatever is needed for th
(NTS) Total number of stations or sources covered in data base: (no
way to estimate.)
(NCS) No. stations or sources currently originating/contributing data:
(no way to estimate.)
(NOF) Number of facilities covered in data base (source monitorinq): (n
o way to estimate.)
(GEO) Geographic coverage of data base: National ^Selected federal
region Region IV included
(LOC) Data elements identifying location of station or source include:
State ;Pro3ect identifier ;bridge number or station code
(FAC) Data elements identifying facility include: Plant facility name
^station code
(CDE) Pollutant identification data are: Storet parameter
Other coding scheme states may have special codes
Oneoded
(LIM) Limitation/variation in data of which user should be aware: Every
survey is different: tailor-made to its own purpose. Quality
assurance procedures vary from survey to survey. Edit varies
from state to state.
1132
-------
Accession No. 9048000911 (cont)
(CBY) Data collected by: State agency all states
(ABY) Data analyzed by: State agency all states
Contractor lab some under state contract
(IDL) Laboratory identification: NO
(AUT) Authorization for data collection: Statutory authorization is P
L 95-217 Section 106 (Clean Water Act-CMA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Publications
By Individual survey title
(•US) Number of regular users of data base: 2
(OSR) Current regular users of data base: EPA regional offices
States
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) primary physical location of data: State agency
(DST) Fora of data storage: Magnetic tape ;0riginal form (hardcopy*
readings)
(OAC) Type of data access: Manually-some states by automated data
processing
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other as surveys
are completed
(RDBEPA) Related EPA data bases used in conjunction with this data base
STORE? (Storage and Retrieval of Hater Quality Data)
(RDB) Non-EPA data bases used in conjunction with this data base: e.g.
Georgia Computer System
(ODB) Other pertinent non-EPA data bases: County and local health
departments and environmental agency data from fixed station and
special purpose studies
(CMP) Completion of form:
David Hill
OFC: EPA/Region If/Environmental Research Lab-Athens/Environmental
Services Division
AD: College Station Road Athens 6A 30613
PH: (404) 546-3113
(DF) Date of form completion: 12-07-82
(NMAT) Number of substances represented in data base: 14
(NCAS) Number of CAS registry numbers in data base: 4
(MAT) Substances represented in data base:
fecal coliform methoxychlor<72-43-5>
nitrogen<7727-37-9> total organic carbon (TOC)
oxygen demand Biochemical oxygen demand (BOD)
pH chlorides
phosphorus<7723-14-0> metals
suspended solids nitrates/nitrites
hexachlorocyclohexane<58-89-9> temperature
(CAS) CAS registry numbers of substances included in data base: 7727-37
-9; 7723-14-0; 58-89-9; 72-43-5
(CNM) Contact name(s): state,E.
(COR) Contact organization: Appropriate Regional Office
(ROR) Responsible Organization: Region IV.Environmental Services
1133
-------
Accession Mo. 9048000911 (cont)
Division*
1134
-------
Accession No. 9048000912
(DQ) Date of Questionaire: 12-02-82
(SAM) Name of Data Base of Model: Missing Parameter Codes
(ACR) Acronym of Data Base or Model: PARACDS
(MED) Media/Subject of Data Base or Model: Effluents all point sources
^Ground water ;Runoff all types ; Sediment ;Soil ;Solid waste
;Surface water all ;Tissue fish
(ABS) Abstract/Overview of Data Base or Model: Data base contains all
Information necessary for STORET (Storage and Retrieval of Hater
Quality Data) storage except the parameter code. When this code
is assigned, the appropriate entries are put into STORET and
purged from this data base.
(CTC) CONTACTS: Subject natter Margaret Hale (912) 250-3548 ;
Computer-related Margaret Hale (912) 250-3548; EPA Office
Environmental Services Division/ Region I? (912)
(DTP) Type of data collection or monitoring: Combination/Other
Ambient, non-point source, and point source
(STA) Data Base status: Operational/ongoing
(NPP) Non-pollutant parameters included in the data base: Chemical
data ^Concentration measures ^Sampling date
(DS) Time period covered by data base: 01-01-79 TO 09-30-81
(TRM) Termination of data collection: Anticipated 12/30/81
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 2808.(Actual)
(NEI) Estimated annual increase of observations in data base: 500.
(INF) Data base includes: Ran data/observations
(NTS) Total number of stations or sources covered in data base: 69.
(NCS) No. stations or sources currently originating/contributing data:
69 (or more.)
(NOF) Number of facilities covered in data base (source monitoring): 50
(or more,)
(GEO) Geographic coverage of data base: Selected federal region Region
IV
(LOC) Data elements identifying location of station or source include:
STORET location codes
(FAC) Data elements identifying facility include: STORET nomenclature
(CDE) Pollutant identification data are: Other coding scheme
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: ORD
Guidelines
(AND Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist for all
measurements
(EDT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Regional office Environmental Services Lab,
Region I?
(ABY) Data analyzed by: Regional office Environmental Services Lab,
Region IV
(IDL) Laboratory identification: NO
(AUT) Authorization for data collection: Statutory authorization is P
L 95-217, Section 106 (Clean Hater Act-CHA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
1135
-------
Accession Ho. 9048000912
(cont)
QQ
(REP) Fora of available reports and outputs of data base: Printouts on
request
On-line computer
(MOS) Sumber of regular users of data base: 10 or less
(OSR) Current regular users of data base: EPA regional offices
Environmental Services Division (storage only)
(CNF) Confidentiality of data and Halts on access: Mo Halts on
access to data
(DLC) Primary physical location of datas Regional office
(DST) Fora of data storage: Magnetic disc
(OAC) Type of data access: Commercial softyare INFORM-11 ;EPA hardyare
POP 11 ^Regionally developed data sy
(CHG) Direct charge for non-EPA uset no
(OPDT) Frequency of data base aaster file up-date: Other as needed
(RDBEPA) Related EPA data bases used in conjunction with this data base
STORET (Storage and Retrieval of Hater Quality Data)
(CMP) Completion of fora:
Ron Estes
QFC: EPA/Region If/Environmental Services Division
AD: College Station Rd Athens, 6A 30613
PH: (912) 250-3301
(DP) Date of fora completion: 12-07-82
(•MAT) number of substances represented in data base: 483
1,1,1, 3, 3, 3-h ex afluoro propane
Itl,l-trichloroethane<71-55-6>
1,1,1-trichlorofluoroaethane,
1,1,2-chloroethyl vinyl ether
1*l,2-trichloroethane<79-00-5>
l,l-dichloroethane<75-34-3>
I,1-dichloroethylene<75-35-4>
1,1-oxy bix/2-aethoxy-etnane
1,1-thibisethane
1,1-thio bisethane
If 12-benzopery lene
1,2,3,3,3 pentafluoro-propene
l,2,4,-trichlorobenzene<120-82-l>
1,2,5,6-dibenzanthracene
1,2-benzanthracene
l,2-dlchloro-l,l,2-tribluoroethane
l,2-dichloro-l,12-trichloroethane
l,2-dichlorobenzene<95-50-l>
l,2-dichloroethane<107-06-2>
1,2-dichloropropane<78-87-5>
1, 2-diphenylhydrazine<122-66-7>
1,2- trans-dichloroethy lene
<156-60-5>
l,3,5-triaethyl-l,3,5-triazine
trlone
l,3-dlchlorobenzene<54l-73-l>
1,3-dichloropropylene
1,3-dloxolane
l,4-dichlorobenzene<106-46-7>
1,4-dioxane
1,4-dloxolane
l-C12-brethane
1-H-perfluorohexane
l-chloro-2 bromomethane
l-chloro-2-borao ethane
1-chlorobutane
1-hydroxy chlordene
ll,12-benzofluoranthene<207-08-9>
2 ethyl 1,3-dloxolane
2,4 dimethyl furan
2,4,6-trichlorophenol<88-06-2>
2,4-dichlorophenol<120-83-2>
2,4-diaethylphenol<105-67-9>
2,4-dinitrophenoK 51-28-5>
2,4-dinitrotoluene<121-14-2>
2,6*dinitrotoluene<606-20-2>
2-H-perfluorohexane
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
1136
-------
Accession No. 9048000912
(cont)
2-nethyl 3-pentanone
2-«ethyl pentane
2-nethyl propanol
2-nethyl-l,3-dioxelene
2-nethy1-1,3-dioxolane
2-nethyl-l-phenyl-l-propanone
2-nethyifuran
2-nitrophenol<88-75-5>
2-pentenenitrile
3, 3'-dichlorobenzidine<91-94-l>
3,4-benzopyrene
3-hexanone
3-nonanone
4 nethyl-1-hexene
4,4'-DDE (P,P'-DDE)
4, 4 '-DDT (P,P"-DDT)
4,4'-ddd(p,p'tde)
4,6-dinitro-o-cresol
4,6-dinitro-o-cresol<534-52-l>
4-4 dimethyl-l,3-dioxane
4-broaophenyl phenyl ether
<101-55-3>
4-cfclorophenyl phenyl ether
<7005-72-3>
4-hydroxy-4-nethyl pentanone
4-hydroxy-4-nethyl-2-pentanone
4-nitrophenol<100-02-7>
8~nethyl-8-nonanediol
A-BBC-alpha
A-chlordane-alpha
A-chlorodane-alpha
A-endosulfan-alpha
B-BHC-beta
B-endosulfan-beta
C12 alkylphenol
C14 alkyl acid
C14 alkyl acid methyl ester
CIS alkyl acid methyl ester
C16 alkyl acid
C16 alkyl acid (2 isoners)
C16 alkyl acid methyl ester
C18 alkyl acid (2 isoners)
C18 alkyl acid methyl ester
C2 alkyl benzole acid
C2 alkyl naphthalene
C2 alkyl naphthalene (2 isoaers)
C2 alkyl naphthalene (3 isoaers)
C2 alkyl nat phthalene (2 isoners)
C2 alkyl phenanthrene
C2 alkyl phenanthrene (2 isoners)
C2 alkyl phenol (2 isomers)
C2 aikyl phenol (4 isoners)
C2 alkyl phenoxy benzene (3
isoners)
C2 alkyl styrene
C2 alkyl styrene (2 isoners)
C2 alkylbenzoic acid (3 isoaers)
C2 alkylnaphthalene (2 isoaers)
C3 alkyl benzene
C3 alkyl benzene (2 isomers)
C3 alkyl benzene (3 isoners)
C3 alkyl benzene (5 isosers)
C3 alkyl benzoic acid
C3 alkyl naphthalene
C3 alkyl naphthalene (2 isoaers)
C3 alkyl naphthalene (3 isoners)
C3 alkyl naphthalene (4 isoners)
C3 alkyl phenanthrene
C3 alkyl phenol
C3 alkyl phenol (2 isomers)
C3 alkyl phenol (3 isoners)
C3 alkyl styrene (2 isoners)
C3 alkylbenzenesulfonanide
C3 alkylphenanthrene (2 isoners)
C3 benzene
C4 alkyl benzene
C4 alkyl benzene (2 isoners)
C4 alkyl benzene (3 isoners)
C4 alkyl benzene (5 isoners)
C4 alkyl benzoic acid
C4 alkyl naphthalene
C4 alkyl naphthalene (3 isoners)
C4 alkyl phenanthrene
C4 alkyl phenol
C4 alkyl phenol (2 isoners)
C4 alkyl styrene
C4 alkylblfaenzyl (2 isoners)
C4 alkyIcylohexanol
C4 alkylcylohexanone
C5 alkyl acid
C5 alkyl benzene
C5 alkyl benzene (2 isoners)
C5 alkyl benzene (5 isoners)
C5 alkyl naphthalene
C5 alkyl phenanthrene
C5 alkylbenzenesulfonamide
C6 alkyl acid
C6 alkyl benzene
C6 alkyl benzene (2 Isoners)
C6 alkyl naphthalene
C8 alkyl phenol
C8 alkylbenzene (2 isoners)
C9 alkyl acid
C9 alkyl phenol
1137
-------
Accession No. 9048000912
(cont)
N, N-dimethy If oraamide
H- methyl nitroso benzenanide
OP DOD
OP DDT
T-butanol
acenaphthene< 83-32-9>
acenaphthylene<208-96-8>
acetone<67-64-l>
acetonitrile<75-05-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
alkyl hydrocarbons
alpha chlordane
alpha chlorodane
alpha cyano pyridine
alpha- terpineol
anthracene<120-12-7>
arochlor 1256
asbestos<1332-21-4>
atrazine<1912-24-9>
benzene acetic acid
benzene triol
benzene<71-43-2>
benzenebutanoic acid
benzenediol
benzenepropanoic acid
benzidine<92-87-5>
benzo fur an
benzole acid<65-85-0>
beta-naphthonitrile
bhc (llndane)-ga«»a< 58-89- 9>
bhc-delta< 31 9-86- 8>
biphenol
biphenyl<92-52-4>
bis (20-ethylhexyl) ph thai ate
bisCl 2-ethylhexyl)phthalate
bis(2-chloroethoxy)methane
bis(2-chloroisopropyl)ether
<39638-32-9>
bis<2-ethylhexyl)phthalate
bromacil
bromoform
bromomethane<74-83-9>
butoxy propanol
butoxybutanoic acid
butyl benzyl phthalate<85-68-7>
butyl ester of benzole acid
butyl aethyl benzene sulfonavide
butylMethylpropyl phthalate
butyloctanol (2 isomers)
carbon disulfide<75-15-0>
carbon tetrachloride<56-23-5>
carbophenolthion
chlordane (tech. mixture &
metabolites)
chlordane<57-74-9>
chlordene
chlorobenzene<108-90-7>
chlorodibromonethane<124-48-l>
chloroethane<75-00-3>
chloroethoxybenzene
chlorofluoromethane
chlorofor»<67-66-3>
chloroaethane<74-87-3>
chloronethylbenzeneanine
chiorotoluene
cineol
co alcohol
cyclohexane<110-82-7>
de odecanoic acid
decanoic acid
decanoic acid, methyl ester
di-2-propenyl phthalate
di-iso-propyl ether
di-aethyl propyl-phthalate
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenzothiophene
dichlorobenzene<25321-22-6>
dichlorobenzeneaalne
dichlorobromomethane<75-27-4>
dichlorodifluoroaethane<75-71-8>
dichlorofluoronethane
dichloromethyl phenol
dichlorophenol
dichlorotoluene
dieldrln<60-57-l>
diethyl dlsulfide
diethyl phthalate<84-66-2>
dihydro indenone
dihydrodiaethyl furanone
dlhydroethenonaphthalene
dihydrotrimethylpurinedlone
diaethyl butanoic acid
dimethyl disulphide
dimethyl ester of butenediolc acid
dimethyl ether
dimethyl phthalate< 131-11-3>
dimethyl pyridine (2 isomers)
dimethyl sulfide
dinethylbenzenebutanoic acid
1138
-------
Accession No. 9048000912
(cont)
dlmethylbenzenemethanol
dimethylbenzoic acid
dimethyIphenylmethybenzene
dioctyl adipate
dipropenyl phthalate
dipropyl phthalate
dissolved carbon
dodecanoic acid
dodecanoic acid, methyl ester
dodecanol
dodecanthiol
endosulfan sulfate<103l-07-8>
endrin aldehyde<7421-93-4>
endrin keytone
endrin<72-20-8>
ethane thiol
ethion (carbophenolthion)
ethoxy ethanol
ethoxyethanol acetate
ethoxymethylbenzene
ethyl (methylpropyl) disulfide
ethyl acetate<141-78-6>
ethyl hexanoic acid
ethylbenzene<100-41-4>
ethylhexanol
ethylmethyIpyr rolidinedione
fluoranthene<206-44-0>
flucrene<86-73-7>
gamma chlordane
haptachlornorbornene
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
beptachloronorborene
heptanol
heptanone
hexachlornorbornadiene
hexachlorobenzene<118-74-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
hexadecanoic acid
hexamethylphosporamide
hexane
hexanoic acid
hydroxy chlordene
hydroxy methoxy benzaldehyde
hydroxy methoxy phenyl ethanone
hydroxy methyl pentanone
hydr oxybenzaIdehyde
hydroxybenzthiazole
hydroxymethoxyphenyl propanone
hydroxymethyl cyclopentenone
hydroxymethyl pentanone
indeno (l,2,3*cd)pyrene
iso-propyl acetate
isodrin
isomer of trichlorophenol
isophorone<78-59-l>
isopropanol
malathion<121-75-5>
methanethiol<74-93-l>
aethly ester of benzene carboxylic
acid
methoxy aethyl benzene
Bethoxy phenol
nethy ester of octadecanoic acid
methyl acetate
methyl benz(a)anthracene
•ethyl benzene sulfonamide
methyl benzoic acid (2 isoners)
methyl benzoic acid methylester
methyl bronide
methyl chloride
methyl cyclhexane
methyl cyclohexane
methyl cyclopentane
methyl cyclopentanol
methyl dibenzothioprene
methyl dichlorophenol
methyl ester C14 alkyl acid
methyl ester €15 alkyl acid
methyl ester C16 alkyl acid
methyl ester C17 alkyl acid
methyl ester CIS alkyl acid
methyl ester methyl pentadecanoic
acid
methyl ester octadecenoic acid
methyl ester of hexadecanoic acid
methyl ester of methylhexadecanoic
acid
methyl ester of octacandienoic
acid
methyl ester of octadecatrienoic
acid
methyl ester of oxopentanoic acid
methyl ethyl ketone (mek)<78-93-3>
methyl fluorene
methyl heptanol
methyl heptanone
methyl Isobutyl ketone<108-10~l>
methyl isopropyl ketone
methyl naphthalene
methyl naphthalene (2 isoners)
methyl parathion<298-00-0>
1139
-------
Accession No. 9048000912
(cont)
•ethyl pentanoic acid nethylester
•ethyl phenanthrene
•ethyl phenanthrene (2 isomers)
•ethyl phenol
•ethyl phenol (2 isoners)
•ethyl phenyl ester of benzole
acid
•ethyl phenyl ethanone
•ethyl propyl ester of benzole
acid
•ethyl pyrene
•ethyl pyridine
•ethyl pyrrolidinone
•ethyl styrene
•ethyl sulfide
•ethyl thioethane
•ethyl thiophene (2 isoners)
•ethylbenzoic acid
•ethylbutanoic acid
•ethylcyclopentenone
•ethylene chloride
•ethylene phenanthrene
•ethylhydroxybenzeneacetic acid
•ethylnonanediol
•ethylpentanedione
•ethylpropoxypropanol
•ethylpyrene (4 isoners)
•irex<2385-85-5>
n-nitrosodi-n-propylaaine
<621-64-7>
n-nitrosodiphenyla»ine<86-30-6>
naphthalene<9l-20-3>
naphthopyrandione
nitrobenzene<98-95-3>
nitrosodiphenylaaine
nonadecanol
nonyl phenol
octa yldiphenylester phosphoric
acid
octachlorcyclopentene
oc tachlorocyclop entene
octachloronaphthalene
octadecanal
octadecanoic acid
octadecanoic acid nethylester
octahydrotetra«ethylcyclopropylazu
lene
octanoic acid
octyldiphenyl ester of phosphoric
acid
oxazole
parachloroaeta eresol
parathion<56-38-2>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
pcb-1254 (arochlor 1254)
<11097-69-l>
pcb-1260 (arochlor 1260)
<11096-82-5>
pentachlorobenzene<608-93-5>
pentachlorocyclopentadiene
pentachlorophenol<87-66-5>
pentadecanoic acid
pentadecanoic acid lethyl-aethyl
pentadecanoic acid Methyl-Methyl
ester
pentanoic acid
percent aoisture
perfluoropropene
phenanthrene<85-01-8>
phenanthrenedione
phenol (gc/as)
phenol<108-95-2>
phenyl ether
phenyl pyridine (2 isoners)
phenylbutanone
phenylethanone
phenylnaphthalene (2 isovers)
phosphoric acid octyldiphenylester
phosphoric acid tributyl ester
phosphoric acid triphenyl ester
phthalic acid<88-99-3>
proneton
propachlor (rairod)
propanediol
propanoic acid
pro poxy butane
propyl acetate
pyr ene< 129-00-0>
silica
sodiua chlorate
styrene<100-42-5>
sulfur
terephthalalonitrile
tetrachlorobenzene
tetrachlorobenzene (2 isoaers)
tetrachlorobiphenyl
tetrachlorodibenzo-p-dioxin (TCDD)
1140
-------
Accession No. 9048000912 (cont)
tetrachloroethylene<127-18-4> tridecanolc acid, methyl ester
tetradecanal tri»ethyl benzene sulfonamide
tetradecanoic acid triaethyl ester of phosphoric aci
tetradecanoic acid, aethyl ester triaethyl pyrazine
tetrahydronaphthalenol trlaethylbicycloheptane
thiobisdodecane triaethylbicycloheptanedione
thiophene trinethyIblcycloheptanone
thlopropane triaethylbicycloheptanone, (2
toluene<108-88-3> isoners)
toluidie ne trivethylcyclohexane
toluidine - triBethylcyclohexanol
toxaphene<8001-35-2> trinethyIcyclohexanone
trans-1,2,-dichloroethylene triaethylcyclohexene«ethanol
traps-1, 2-dichloroethene triaethylcyclopentenone
trans-1,3-dichloropropene trlphenyl ester
tr1(2-chloroethyl)phosphate tris-beta-chloroethylphosphate
trlbutylester of phosphoric acid vinyl chloride<75-01-4>
trichlorobenzene (not 1/2,4) uBethoxychlor
trichlorobenzenes xylene (2 isovers)
trichlorobiphenyl xylen«<1330-20-7>
trichloroethylene<79-Ol-6> y-chlordane-gama
trichlorof luoroB0thane<75-69-»4> ychlorone thane
tridecanoic acid
(CAS) CAS registry numbers of substances included in data base: 630-20*
6; 71-55-6; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-Ij
107-06-2; 78-87-5; 122-66-7; 156-60-5; 541-73-1; 106-46-7;
207-08-9; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 88-75-5; 91-94-1; 534-52-1; 101-55-3;
7005-72-3; 100-02-7; 83-32-9; 208-96-8; 67-64-1; 75-05-8; 107-02-8;
107-13-1; 309-00-2; 120-12-7; 1332-21-4; 1912-24-9; 71-43-2;
92-87-5; 65-85-0; 58-89-9; 319-86-8; 92-52-4; 111-91-1;
39638-32-9; 117-81-7; 74-83-9; 85-68-7; 75-15-0; 56-23-5;
57-74-9; 108-90-7; 124-48-1; 75-00-3; 67-66-3; 74-87-3;
110-82-7; 84-74-2; 117-84-0; 25321-22-6; 75-27-4; 75-71-8;
60-57-1; 84-66-2; 131-11-3; 1031-07-8; 7421-93-4; 72-20-8;
141-78-6; 100-41-4; 206-44-0; 86-73-7; 1024-57-3; 76-44-8;
118-74-1; 87-68-3; 77*47-4; 67-72-1; 193-39-5; 78-59-1; 121-75-5;
74-93-1; 78-93-3; 108-10-1; 298-00-0; 2385-85-5; 621-64-7; 86-30-6;
91-20-3; 98-95-3; 56-38-2; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 11097-69-1; 11096-82-5; 608-93-5; 87-86-5; 85-01-8;
108-95-2; 88-99-3; 129-00-0; 100-42-5; 127-18-4; 108-88-3;
8001-35-2; 79-01-6; 75-69-4; 75-01^-4; 1330-20-7
(CffM) Contact naae(s): Hale,M.
(COR) Contact organization: Envlronaental Services Division, Region If
(ROR) Responsible Organization: Region IV.Environaental Services
Division.
1141
-------
Accession No. 9048000913
(DQ) Date of Questionaire: 12-02-82
(MAM) Mane of Data Base of Model: Whatley Standard
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Other Publicly owned
treatment works (PQTW) operational data
(ABS) Abstract/Overview of Data Base or Model: The data base contains
information taken from the EPA 7500-5 for* dealing uith
publicly owned treatment works (POTHs) operations. Information
such as permit compliance, treatment efficiency, costs of operation
and maintenance, operational problems, etc. is included. Small
amounts of data on metals, PCBs and organics as covered in
permits are also Included.
(CTC) CONTACTS: Subject matter Charles Sweatt (404)546-3351 ;
Computer-related Ron Es
(DTP) Type of data collection or monitoring: Combination/Other
municipal uastewater treatment plants
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 11 conventional
water
(NPP) Non-pollutant parameters included in the data base: Chemical
data ;Compliance data ;Concentration measures ;Cost/economic data ;
Discharge points ^Disposal ;Flow rates ^Funding data ;Geographic
subdivision ; Industry ^Inspection data ^Location ;Physical data
^Political subdivisions ; Population demographics ;Population
density ;Site description J Treatment devices
(OS) Time period covered by data base: 08-01-77 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: daily
(NOB) Number of observations in data base: 32600 plus.(Estimated)
(NED Estimated annual increase of observations in data base: 1600*
(INF) Data base includes: Summary aggregate observations
(NTS) Total number of stations or sources covered in data base: 2700.
(NCS) No. stations or sources currently originating/contributing data:
1600.
CNOF) Number of facilities covered in data base (source monitoring): 27
00.
(GEO) Geographic coverage of data base: Selected federal region Region
I?
(LOC) Data elements identifying location of station or source include:
State ^County ?City jStreet address
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ^Street address ;NPDES
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: Hater
quality parameters are from Discharge Monitoring Reports (DMR)
self-reporting data, therefore quality assurance protocols are
unknown.
(AM.) Lab analysis based on EPA-approved or accepted methods? Lab
analysis is based on EPA-approved or accepted methods.
(PRE) Precision: Precision and accuracy estimates are not available
(EOT) Editting: No known edit procedures exist.
(CBY) Data collected by: State agency States in Region IV (Tennessee,
1142
-------
Accession No. 9048000913 (cont)
North Carolina, South Carolina, A lab ana, Florida, Georgia, Kentucky
& Mississippi) ; Regional office Surveillance and Analysis
Division, Region 17
(ABY) Data analyzed by: State agency States in Region IV (Alabama,
Florida, Georgia, Kentucky, Mississippi, North Carolina, South
Carolina, and Tennessee)
Regional office
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Trend assessment
(PR2) Secondary purpose of data collection: Program evaluation
CAOT) Authorization for data collection: No statutory requireaent:
Data collection requirement is collected for 210 Report to
Congress
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0035
(REP) Form of available reports and outputs of data base: Printouts on
request
(NUS) Nunber of regular users of data base: 300
(USR) Current regular users of data base: EPA regional offices
States
consultants
(CNF) Confidentiality of data and Halts on access: Ho limits on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Form of data storage: Magnetic tape
(DAC) Type of data access: Commercial software Inform 11 JEPA hardware
PDP-11
(CflG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Meekly
(CMP) Completion of form:
Charles Sueatt
QFC: EPA/Region IV/Environmental Research Lab-Athens/
Surveillance and Analysis Division
AD: College Station Rd. Athens, GA 30613
PH: (404)546-3351
(DF) Date of form completion: 08-20-80
(NMAT) Number of substances represented in data base: 13
(NCAS) Number of CAS registry numbers in data base: 2
(MAT) Substances represented in data base:
acidity organics
alkalinity oxygen demand
dissolved oxygen pH
fecal collform phosphorus<7723-14-0>
metals polychlorinated biphenyls (PCBs)
nitrogen<7727-37-9> suspended solids
oil and grease
(CAS) CAS registry numbers of substances included in data base: 7727-37
-9; 7723-14-0
(CNM) Contact name(s): S«eatt,C. ; Estes,R. ; Sueatt,C.
(ROR) Responsible Organization: Region IV.Environmental Services
Division*
1143
-------
Accession No. 9048000914
(DQ) Date of Questionaire: 12-02-82
(HAM) Kane of Data Base of Model: Metals Data Base
(ACR) Acronym of Data Base or Model: Hone
(NED) Media/Subject of Data Base or Model: Other Municipal sludge;
influent and effluent
(ABS) Abstract/Overview of Data Base or Model: Metals detected in
municipal uastewater treatment facilities in Region I?. Six heavy
metals in influent and effluent from municipal treatment plants
reported in milligrams per liter (mg/1). Sludge samples reported
in milligrams per kilogram (mg/kg).
(CTC) CONTACTS: Subject matter Bruce Ferguson 404-546-3351 ;
Computer-related Ron Es
(DTP) Type of data collection or monitoring: Combination/Other
municipal wastewater treatment plants
(STA) Data Base status: Operational/ongoing
(6RP) Groups of substances represented in Data Base: 15 metals
(NPP) Non-pollutant parameters included in the data base: Chemical
data Inspection data ^Location ;Site description
(DS) Time period covered by data base: 07-01-75 TO 05-27-81
(TRM) Termination of data collection: lot anticipated
(FRQ) Frequency of data collection or sampling: monthly
(NOB) Number of observations in data base: 5500.(Estimated)
(NED Estimated annual increase of observations in data base: 600.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 960.
(NCS) No. stations or sources currently originating/contributing data:
50.
(NOF) Fumber of facilities covered in data base (source monitoring): 24
0.
(6EO) Geographic coverage of data base: Geographic region Southeast US
(LOC) Data elements identifying location of station or source include:
State /City ^Project identifier ^sample source
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ;NPDES
(CDE) Pollutant Identification data are: Dncoded
(LIM) Limitation/variation in data of which user should be aware: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: Analysl
a method documented ;QA procedures documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: No known edit procedures exist.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division/ Region IV.
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division/ Region IV.
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Trend assessment
(AUT) Authorization for data collection: No statutory requirement:
Data collection requirement is to measure trends in the
concentrations of metals in municipal sludge.
1144
-------
Accession No. 9048000914 (cont)
(OMB) Data collected/ subaitted using OMB-approved EPA reporting for MS:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Metals, PCBs and Chlordane in Municipal Sludge.
Printouts on request
Machine-readable ran data
(NUS) number of regular users of data base: 50
(USR) Current regular users of data base: EPA headquarter offices Land
Disposal Division/ Office of Hater and Haste Management
EPA regional offices
States
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: EPA lab
(DST) Fora of data storage: Magnetic disc
(DAC) Type of data access: EPA software STORE? MIDS:5303000101 ;EPA
hardware IBM 370/168
(CHG) Direct charge for non-EPA use: No
(UPDT) Frequency of data base naster file up-date: Monthly
(CMP) Completion of form:
Bruce Ferguson
OFC: EPA/Region IV/Environmental Research Lab-Athens/
Surveillance and Analysis Division
AD: College Station Road/ Athens/ Georgia 30613
PH: (404) 546-3351
(DF) Date of form completion: 02-01-83
(NMAT) Number of substances represented in data base: 6
(NCAS) Number of CAS registry numbers in data base: 6
(NAT) Substances represented in data base:
cadmium<7440-43-9> lead<7439-92-l>
chromium<7440-47-3> nickel<7440-02-0>
copper<7440-50-8> zinc<7440-66-6>
(CAS) CAS registry numbers of substances included in data base: 7440-43
-9; 7440-47-3; 7440-50-8; 7439-92-1; 7440-02-0; 7440-66-6
(CNM) Contact name(s): 404/B.F. ; 404,R.E. ; Ferguson,B.
(ROR) Responsible Organization: Region IV.Environmental Services
Division.
1145
-------
Accession Ho. 9051700002
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Great Lakes Sediment Quality Data
and Reports
CACR) Acronym of Data Base or Model: Hone
CUED) Media/Subject of Data Base or Model: Sediment ;0ther Elutriate
and bcnthic biological samples uere taken intermittently.
(ABS) AbstracVOverview of Data Base or Model: Describes sediment
quality in Great Lakes' rivers and harbors. Total sediment
chemistry and to a »ore limited extent elutriate data, benthic
•acrolnvertebrate data, as well as a physical descriptions of the
samples (e.g. color, particle size, etc.) are contained in the
reports. Total chemistry data is also available in STORET under
Agency Code 1115GLSB.
(CTC) CQBTACTS: Subject matter Tony Kizlauskas (312)353-3576; EPA
Office Great Lakes National Program Office (GLNPO)
CDTP) Type of data collection or monitoring: Combination/Other Ambient
monitoring, industrial monitoring, toxics monitoring.
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 15 metals, 129
consent decree priority pollutants
CMPP) Ion-pollutant parameters included in the data base: Biological
data ;Chemical data ;Collection method ^Concentration measures >
Elevation ^Geographic subdivision ^Location jPhysical data
;Sampling date ; Site description
(OS) Time period covered by data base: 01-01-60 to 09-30-82
(TRM) Termination of data collection: Mot anticipated
(FRQ) Frequency of data collection or sampling: as needed
(MOB) Number of observations in data base: 35000.(Estimated)
(MEI) Estimated annual increase of observations in data base: (variable
(IMF) Data base includes: Raw data/observations ;Summary aggregate
observations ,.»«.._ ^ Ann.
(UTS) Total number of stations or sources covered in data base. i*uw.
(MCS) Mo. stations or sources currently originating/contributing data:
1200. ,»,>,.
(MOF) lumber of facilities covered In data base (source monitoring): (M
(GEO) 'Geographic coverage of data base: Geographic region Great Lakes
Basin . ...
(LOG) Data elements identifying location of station or source Include:
Project identifier ;O.S. Army Corps of Engineers' maps
(FAC) Data elements Identifying facility include: N/A
CCDE) Pollutant Identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Sampl
es are primarily surface grab samples from navigation channels.
(DPR) Data collect./anal. procedures conform to ORD guidelines: Sanplin
g plan documented ^Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory for 80.
(PRE) Precision: Precision and accuracy estimates partially exist for
Intermittent time periods
1146
-------
Accession No. 9051700002 (cont)
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Regional office Region V Surveillance and
Analysis Division ; Contractor as needed ;Other federal agency
U.S. Army Corps of Engineers ; Great Lakes National Program
Office/EPA
(ABY) Data analyzed by: Regional office Region V Surveillance and
Analysis Division
EPA lab Environmental Research Lab-Duluth, HN
Contractor lab as needed
(IDL) Laboratory identification: YES
(AUT) Authorization for data collection: statutory authorization is P
L 92-500 as amended Section 104b (Clean Water Act)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Sediment Data for the Milwaukee Estuary
Great Lakes National Progran Office Files
(NUS) Number of regular users of data base: 15 organizations 50-100
(USR) Current regular users of data base: EPA headquarter offices
Marine Activities Branch (other branches intermittently)
EPA regional offices
BPA laboratories
Other federal agencies
States
Regions II, III and V
U.S. Fish and Wildlife Service
U.S. Army Corps of Engineers
consultants
local governments
universities
public interest groups
(CNF) Confidentiality of data and limits on access: Limits on outside
access for some data
(DLC) Primary physical location of data: Great Lakes National Program
Office, Chicago, IL
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Reports: Manually; Total Chemistry data =
STORET on Agency Code 1115GLSB.
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Other as results
become available
(RDBEPA) Related EPA data bases used in conjunction tilth this data base
Great Lakes National Program Office (GLNPO) Fish Monitoring and
Lake Water Monitoring Programs (most of this data is in STORET)
(RDB) Kon-EpA data bases used in conjunction with this data base: Great
Lakes* States - State Monitoring Programs, U.S. Army Corps of
Engineers, researchers and consultants data, dredging permit
applications.
(CMP) Completion of form:
Anthony Kizlauskas
OFC: Great Lakes National Program Office
AD: Rm 932 536 S. Clark St, Chicago, IL 60605
1147
-------
Accession Mo. 9051700002 (cont)
PH: (312)353-3576
(OF) Date of fora coapletion: 01-17-83
(MMAT) Number of substances represented in data base: 25
(NCAS) Nunber of CAS registry numbers in data base: 12
(MAT) Substances represented in data base:
ammonia nitrogen oil and grease
arsenic<7440-38-2> ortho-phosphate
cadBiuB<7440-43-9> phenols
chemical oxygen demand (COD) total kjeldahl nitrogen
chro«iu»<7440-47-3> total organic carbon (TOO
copper<7440-50-8> total phosphorus
iron<7439-89-6> total solids
lead<7439-92-l> trace metals
•anganese<7439-96-5> volatile solids
•ercury<7439-97-6> aluminum<7429-90-5>
nickel<7440-02-0> cyanide
nitrate nitrogen <57-12 129 consent decree
nitrite nitrogen Priority Pollutants
(CAS) CAS registry numbers of substances included in data base: 7440-38
-2; 7440-43-9; 7440-47-3; 7440-50-8; 7439-89-6; 7439-92-1;
7439-96-5; 7439-97-6; 7440-02-0; 7429-90-5
(CHM) Contact narae(s): Kizlauskas/A.
(COR) Contact organization: Great Lakes National Program Office
(GLNPO)
(ROR) Responsible Organization: Region V.Great Lakes National Program.
1148
-------
Accession Mo. 9055000903
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Industrial Process Evaluations
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Effluents industrial
;Runoff Bother in plant chenical process wastes
(ABS) Abstract/Overviey of Data Base or Model: Evaluation of specific
industries and industrial processes regarding the
presence/formation of toxicants by (1) National Pollutant
Discharge Elimination System (NPDES) permit or Clean Hater Act,
Section 308 request to industry, (2) EPA contractor, or (3)
state pollution control agency* Toxicants are not United to
the 129 Consent Decree Priority Pollutants. Initial worfc is dry
lab paper study of industrial process folloyed by chemical
and/or biomonitoring testing by facility. Most of the data
<90%) is supplied by industry. Emphasis is placed on chemicals
that are highly toxic, that tend to bio-accumulate, and are
carcinogenic or mutagenic. Organic scans are run and the
significant peaks are analyzed quantitatively.
Geographic subdivision ;Industry ;Location ^Production
levels ; Test/analysis method ^Treatment devices
(DS) Time period covered by data base:M>1-01-79 to 01-03-83
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 1200
(NEI) Estimated annual increase of observations in data base: 300(Estim
ated)
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 80
(NCS) No. stations or sources currently originating/contributing data:
15.
(NOF) Number of facilities covered In data base (source monitoring): 60
•
(GEO) Geographic coverage of data base: Selected federal region Region
f
(LOC) Data elements identifying location of station or source Include:
State ;City ; Town/township ;Street address
(FAC) Data elements identifying facility include: Plant facility name
IPlant location ;Parent corp name ;Parent corp location ; Street
address ;SIC code /NPDES
(CDE) pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Evalu
1149
-------
Accession No. 9055000903 (cont)
ation for toxicants only (sometimes conventional also).
Quality assurance varies by facility. Limited amount of actual
monitoring data.
(DPR) Data collect./anal. procedures conform to ORD guidelines: ORD
Guidelines
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AOD) Lab Audit: Lab audit is satisfactory for part of the data base.
(PRE) Precision: Precision and accuracy estimates partially exist for
the data base.
(EOT) Editting: So known edit procedures exist.
CCBY) Data collected by: Self reporting ;Regional office Surveillance
and Analysis Division ; Contractor State Pollution Control Agency
(ABY) Data analyzed by: Self reporting
Regional office Surveillance and Analysis Division
Contractor lab through Surveillance and Analysis Division
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Development of NPDES permit
or pretreatnent limitations
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 308 (Clean Water Act-CHA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Individual undistributed reports
(HDS) Number of regular users of data base: 40
(OSR) Current regular users of data base: EPA headquarter offices
Effluent Guidelines Division
EPA regional offices
States
(CNF) Confidentiality of data and limits on access: Limits on access
outside agency for some data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(OPDT) Frequency of data base master file up-date: Other as completed
(RDBEPA) Related EPA data bases used in conjunction with this data base
Compliance Sampling Inspections for Toxicants
(CMP) Completion of form:
Glenn Pratt
OFC: EPA/Region V/Hater Division
AD: 230 S. Dearborn Chicago, 111 60604
PH: (312)353-2098
(DP) Date of form completion: 01-06-83
(NMAT) Number of substances represented in data base: 13.
(NCAS) Number of CAS registry numbers in data base: 129
(MAT) Substances represented in data base:
lslxl-trichloroethane<71-55- l,l-dichloroethane<75-34-3>
6> l,l-dichloroethylene<75-35-4>
1,1,2,2,-tetrachloroethane 1,2,4,-trichlorobenzene<120-82-l>
<79-34-5> 1,2-d ichlorobenzene<95-50-l>
If 1,2-trie hi o roe than e< 79-0 0-5> 1, 2-dichloroethane< 107-06-2 >
1150
-------
Accession No. 9055000903
(cont)
2-dichloropropane<78-87-5>
2-dichloropropylene<563-54-2>
2-diphenylhydrazine<122-66-7>
2-trans-dichloroethylene
<156-60-5>
3-dichlorobenzene<541-73-l>
4-dichlorobenzene<106-46-7>
4,6-trichlorophenol<88-06-2>
4,1, 8- te tr achl or od ibenzo-p-
dioxin (tcdd)
4-di chlorophenoKl 20-83-2>
4-dimethylphenol<105-67-9>
4-dinitrophenol<51-28-5>
4-dinitrotoluene<121-14-2>
6-dinitrotoluene<606-20-2>
chloroethylvinyl ether<110-75-8>
chloronaphthalene<91-58-7>
chlorophenol<95-57-8>
ni t r opheno 1< 88-7 5-5>
3 '-dichlor obenzidine<91-94-l>
4-benzof luoranthene<205-99-2>
4*-ddd(p,p*tde)
l,
l,
l,
2,
2,
2,
2,
2,
2,
2,
2-
2-
2-
2-
3,
3,
4,
4,4'-ddt<50-29-3>
4, 6-dinitro-o-cresol<534-52-l>
4-broBiophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitr opheno l<100-02-7>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
anthracene<120-12-7>
antimony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrene<5Q-32-8>
benzo(g^h,i)perylene<19l-24-2>
benzo(k)fluoranthene<207-08-9>
berylliuu<7440-41-7>
bhc (lindane)-ga»JBa<58-89-9>
bhc-al pha<31 9-84-6>
bhc-beta<319-85-7>
bhc-delta<31 9-86-8>
bis(2-chloroethoxy)methane
bis(2-chloroethyl)ether
bis(2-chloroisopropyl)ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloromethyl)ether<542-88-l>
bromomethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cad«ium<7 440- 43-9>
carbon tetrachloride<56-23-5>
chl or dane< 57-7 4-9>
chl orobenzene<108-90-7>
chlorodibroffionethane<124-48-l>
chloroethane<75-00-3>
chl or of OOK67-66- 3>
chloronethane<74-87-3>
chronluin<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
dl-n-butyl phthalate<84-74-2>
dl-n-octyl phthalate<117-84-0>
dibenzo(a,h)anthracene<53-70-3>
dichlorobroffloraethane<75-27-4>
dichlorodifluoroaethane<75-71-8>
dichloro»ethane<75--09-2>
dieldrin<60-57-l>
diethyl phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
endosulfan sulfate<1031-07-8>
endosul f an-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fluoranthene<206-44-0>
f luor ene<86-73-7>
heptachlor epoxide<1024-57-3>
hep tachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlorobutadiene<87-68-3>
hex achl orocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeno (U 2,3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
mercury<7439-97-6>
n-nit rosodi-n-propy lanine
<621-64-7>
n-nit rosodimethylainif)e<62-75-9>
n-nit rosodiphenylanine<86-30-6>
naphthalene<9l-20-3>
1151
-------
Accession No. 9055000903 (cont)
nickel<7440-02-0> pentachlorophenol<87-86-5>
nitrobenzene<98-95-3> phenanthrene<85-01-8>
p-chloro-B-cresol<59-50-7> phenol<108-95-2>
pcb-1016 (arochlor 1016) pyrene<129-00-0>
<12674-ll-2> radon<10043-92-2>
pcb-1221 (arochlor 1221) seleniua<7782-49-2>
<11104-28-2> silver<7440-22-4>
pcb-1232 (arochlor 1232) tetrachloroethylene<127-18-4>
<1114l-16-5> thalliu«<7440-28-0>
pcb-1242 (arochlor 1242) toluene<108-88-3>
<53469-21-9> toxaphene<8001-35-2>
pcb-1248 (arochlor 1248) tribroao«ethane<75-25-2>
<12672-29-6> trichloroethylene<79-01-6>
pcb-1254 (arochlor 1254) trlchlorofluoroaethane<75-69-4>
<11097-69-l> uraniuB<7440-61-l>
pcb-1260 (arochlor 1260) vinyl chloride<75-01-4>
<11096-82-5> zlnc<7440-66-6>
(CAS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 10043-92-2;
7782-49-2; 7440-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2;
75-25-2; 79-01-6; 75-69-4; 7440-61-1; 75-01-4; 7440-66-6
(CNN) Contact naae(s): Pratt,G.D.; Pratt/G.D.
(ROR) Responsible Organization: Region f. Hater Management Division.
1152
-------
Accession Mo. 9055000904
(DQ) Date of Questionaire: 12>02-82
(NAN) Name of Data Base of Model: Compliance Sampling Inspections for
Toxicants
(ACR) Acronym of Data Base or Model: CSI-T
(MED) Media/Subject of Data Base or Model: Effluents of various
industries and sewage treatment plants with high potential for
toxicant discharge ;Ground Hater ;In plant process wastes > Sludge
(ABS) Abstract/Overview of Data Base or Model: Detailed sampling
inspections of industries (some municipalities) with high potential
for toxicant discharge. 10-15 surveys per year. Data for
pernit/pretreatment limit and enforcement development* Broad
chemical scans, specific analysis and biomonitoring.
Engineering analyses of manufacturing process for toxicant
formation. Tests include algal assay/ Ames/ static/ and other
biomonitoring. Emphasis is on organic chemical industry/ and
herbicide & pesticide producers. Toxicants are not limited to 129
Consent Decree Priority Pollutants. Emphasis is placed on
chemicals that are highly toxic/ tend to bio-accumulate and are
carcinogenic or mutagenic. Organic scans are run and the
significant peaks are analyzed quantitatively.
(CTC) CONTACTS: Subject matter Glenn Pratt/Jon Barney (312)
353-2098 ; EPA Office 61
(DTP) Type of data collection or monitoring: Point source data
collection industrial and municipal effluents and groundwater
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CHA ;9
potential drinking water
(MPP) Non-pollutant parameters Included in the data base: Biological
data ;Chemical data ;Collection method ;Compliance data /
Concentration measures ;Discharge points ^Disposal ?Flow rates ;
Geographic subdivision ;Industry ;Inspection data ;Location ;
Physical data ^Production levels ; Sampling date ;Site description ;
Temperature ^Treatment devices
(DS) Time period covered by data base: 10-01-79 to 01-03-83
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: as needed
(NOB) Number of observations in data base: 550.(Estimated)
(NEI) Estimated annual increase of observations in data base: 100.
(INF) Data base includes: Raw data/observations ;Summary aggregate
observations
(ITS) Total number of stations or sources covered in data base: 75.
(NCS) No. stations or sources currently originating/contributing data:
5.
(NOF) tiumber of facilities covered in data base (source monitoring): 40
.
(GEO) Geographic coverage of data base: Selected federal region Region
V
(LOC) Data elements identifying location of station or source include:
State jCounty ;City ; Town/township ;Street address
(FAC) Data elements identifying facility include: Plant facility name
jPlant location ^Parent corp name ^Parent corp location ; Street
address ;SIC code ;HPDES
1153
-------
Accession Ho* 9055000904 (cont)
(CDE) Pollutant identification data are: Uncoded
(LlM) Limitation/variation in data of which user should be auare: Soae
plant data is confidential. Primarily organic chemical industry
related data.
(DPR) Data collect./anal, procedures conform to QRD guidelines: ORD
Guidelines
(AMD Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist for all
measurements
(EOT) Editting: NO known edit procedures exist.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division
(ABY) Data analyzed by: Regional office Surveillance and Analysis
Division
(IDL) Laboratory identification: YES
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 308 (Clean Hater Act-CVA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports undistributed report on each facility
(USR) Current regular users of data base: 40
EPA regional offices
States
(CNF) Confidentiality of data and limits on access: Limits on outside
access for some data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHC) Direct charge for non-EPA use: NoJon
(OPDT) Frequency of data base master file up-date: Other Hone-not
compiled as a total
(RDBEPA) Related EPA data bases used in conjunction with this data base
Industrial Process Evaluations
(CMP) Completion of form:
Glenn Pratt, Jon Barney
OFC: EPA/Region V/Hater Division
AD: 230 S. Dearborn Chicago, 111 60604
PH: (312) 353-2098
(DF) Date of form completion: 01-06-83
(NMAT) Number of substances represented in data base: 132
(NCAS) Number of CAS registry numbers in data base: 129
(MAT) Substances represented in data base:
l,l,l-trichloroethane<71-55- l,2-dichlorobenzene<95-50-l>
6> l,2-dichloroethane<107-06-2>
1,1,2,2,-tetrachloroethane l,2-dichloropropane<78-87-5>
<79-34-5> l,2-dichloropropylene<563-54-2>
l,l,2-trichloroethane<79-00-5> l,2-diphenylhydrazine<122-66-7>
l,l-dichloroethane<75-34-3> 1,2-trans-dichloroethylene
l,l-dichloroethylene<75-35-4> <156-60-5>
l*2,4,-trichlorobenzene<120-82-l> l,3-dichlorobenzene<541-73-l>
1154
-------
Accession No. 9055000904
(cent)
It 4-dichlorobenzene<106-46-7>
2,4,6-trichlorophenol<88-06-2>
2*4,7, 8-tetrachlorodibenzo-p-
dioxin (tcdd)
2,4-dichlorophenol<120-83-2>
2, 4-dimethylphenol<105-67-9>
2,4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2, 6~dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene< 91-58-7>
2-chlorophenol<95-57-8>
2-nitrophenol<88-75-5>
3,3*-dichlorobenzidine<91-94-l>
3, 4-benzof luor anthene<205-99-2>
4,4*-ddd(p,p'tde)
4, 4 *-dde (p, p '-ddx) <72-55-9>
4/4--ddt<50-29-3>
4/6-dinitro-o-cresol<534-52-l>
4-bronophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
aceraphthylene<208-96-8>
acrolein
acrylonitrile<107-13-l>
aldrin<309-00-2>
anthracene<120-12-7>
antimony<7440-36-0>
ars€nic<7440-38-2>
asbestos<1332-21-4>
benzene<71-43-2>
benzidine<92-87-5>
benzo{a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g^h^i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
beryllium<7440-41-7>
bhc (lindaae)-gamraa<58-89-9>
bhc-alpha<31 9-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)methane
bis(2-chloroethyl)ether
bis (2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloromethyl)ether<542-88-l>
bronoraethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadniua<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodlbroiBomethane<124-48-l>
chloroethane<75-00-3>
chlorofor«<67-66-3>
chloromethane<74-87-3>
chrooiura<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenzo(a,h)anthracene<53-70-3>
dichlorobroffloraethane<75-27-4>
dichlorodifluoromethane<75-71-8>
dichloro»ethane<75-09-2>
dieldrin<60-57-l>
diethyl phthalate<84-66-2>
dinethyl phthalate<131-ll-3>
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<332!3-65-9>
endrin aldehyde<7421-93-4>
endriiK72-20-8>
ethylbenzene<100-41-4>
fluorantbene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlorobutadiene<87-68-3>
hexachlcrocyclopentadiene<77-47-4>
hexachloroethane<67«72-l>
indeno (l/2,3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
mercury<7439-97-6>
n-nitrosodi-n-propylamin
n-nitrosodimethylamine<62-75-9>
n-nitrosodiphenyla»ine<86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nitrobenzene<98-95-3>
organics
P-chloro-B-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
1155
-------
Accession Ho. 9055000904 (cont)
pcb-1221 (arochlor 1221) pyrene<129-00-0>
<11104-28-2> radon<10043-92-2>
pcb-1232 (arochlor 1232) seleniuu<7782-49-2>
<11141-16-5> silver<7440-22-4>
pcb-1242 (arochlor 1242) tetrachloroethylene<127-18-4>
<53469-21-9> thalliu«<7440-28-0>
pcb-1248 (arochlor 1248) toluene<108-88-3>
<12672-29-6> toxaphene<8001-35-2>
pcb-1254 (arochlor 1254) tribromo«ethane<75-25-2>
<11097-69-l> trichloroethylene<79-01-6>
p J?J°
<11096-82-5> uraniu«<7440-61-l>
pentachlorophenol<87-86-5> vinyl chloride<75-01-4>
phenanthrene<85-01-8> zinc<7440-66-6>
phenol<108-95-2>
-£AS re9is*ry nuabers of substances included in data base: 71-55-6
Z9"34"5; 79-°°-5* 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2;
207-08-9; 7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8;
111-91-1; 111-44.4. 39638-32-9; 117-81-7; 542-88-1; 74-83-9;
85-68-7; 7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1;
75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8;
57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
2!;??"2£ 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 78-59-1; 7439-92-1; 7439-97-6; 621-64-7; 62-75-9;
86-30-6; 91-20-3; 7440-02-0; 98-95-3; 59-50-7; 12674-11-2;
11104-28-2; 11141-16-5; 53469-21-9; 12672-29-6; 11097-69-1;
11096-82-5; 87-86-5; 85-01-8; 108-95-2; 129-00-0; 10043-92-2;
7782-49-2; 7440-22-4; 127-18-4; 7440-28-0; 108-88-3; 8001-35-2;
75-25-2; 79-01-6; 75-69-4; 7440-61-1; 75-01-4; 7440-66-6
(CNM) Contact name(s): Pratt,G. ; Pratt,G. ; Barney,J.
(ROR) Responsible Organization: Region f.Water Management Division.
1156
-------
Accession No. 9055000905
(DQ) Date of Questionaire: 12-02-82
(»AM) Name of Data Base of Model: Toxicant Control Fish Tissue
Analyses
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Tissue fish
(ABS) Abstract/Overview of Data Base or Model: As part of Region ?*s
surface water toxicant control program, fish from major tributaries
ar« JLin,, fef, £ef and the Ohio and Mississippi Rivers basins
are being analyzed for persistant bioaccumulative toxicants.
Toxicant problems surfaced by this work will result in specific
li.i?na P«nh^tanJ Difcha^« Elimination System (HPDES) permit
limit. Emphasis is placed on chemicals that are highly toxic,
that tend to bio-accumulate and are carcinogenic or mutagenic.
°ur?nm™?yare CUn and the si*>«ica«< »•*• a« analyzed
Type of data collection or monitoring: Ambient data collection
Tata Base status: Operational/ongoing
Non-pollutant parameters included in the data base: Biological
data ;Chemical data Collection method ;Exposure data $
C^M^< .,,..,_,._ .Location ?Saapling date slte
Tlme period covered by data base: 02-01-78 to 01-03-83
Termination of data collection: Anticipated 03-84
Frequency of data collection or sampling: Other As needed in the
summer and fall, 1 to 5 times per site
2U?ber °! observations in data base: 3100. {Estimated)
Estimated annual increase of observations in data base: 350
CIRF) Data base includes: Ran data/ observations
/JJ!% T,°tal nuwber of stations or sources covered in data base: 146.
30 sta*lons or sources currently originating/contributing data:
«HOF> N«»ber of facilities covered in data base (source monitoring): C
/A» )
C6EO) Geographic coverage of data base: Selected federal region Region
Data elements identifying location of station or source include:
State ;Project identifier >river mile
(FAC) Data elements identifying facility include: M/A
(CDE) Pollutant identification data are: Uncoded
aiM) Limitation/variation in data of which user should be aware: locat
ions may be sampled from one to five times.
-------
Accession No. 9055000905 (cont)
federal agency Fish and Wildlife Service
(ABY) Data analyzed by: Regional office Region V
EPA lab Environmental Research Lab-Duluth
Contractor lab various Environmental Research Lab contractors
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Development of regulations
or standards
(PR2) Secondary purpose of data collection: Compliance or enforcement,
surveillance
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended, (Clean Water Act-CWA)
mercury<7439-97-6>
chromium<7440-47-3> organic GC/KS scans for signified
copper<7440-50-8> t organics
lead<7439-92-l> zinc<7440-66-6>
(CAS) CAS registry numbers of substances Included in data base: 7440-43
-9; 7440-47-3; 7440-50-8; 7439-92-1; 7439-97-6; 7440-66-6
(CNM) Contact name(s): Pratt,G. ; Pratt,G. ; Barney,J.
(ROR) Responsible Organization: Region Y.Water Management Division.
1158
-------
Accession No. 9055000906
(DQ) Date of Questionaire: 12-02-82
(JAM) Name of Data Base of Model: Hazardous Materials Site Files
lACR) Acronym of Data Base or Model: HMS
(MED) Media/Subject of Data Base or Model: Drinking water ;Ground
water ;Soil ;Surface water
(ABS) Abstract/overview of Data Base or Model: The files contain
information relating to hazardous waste sites in Region V. They
are arranged alphabetically by site name and state, and contain
tne following items as appropriate: site identification,
preliminary assessment, tentative dispostion, final disposition,
and site inspection forms and reports. Internal enforcement
records and records of formal state and federal enforcement
actions are kept, as well as relevant correspondence and
communication records.
(CTC) CONTACTS: Subject matter Arnold Leder (312) 353-2114 ;
Computer-related Arnold
(DTP) Type of data collection or monitoring: Point source data
collection hazardous waste sites
(STA) Data Base status: Discontinued
(CRP) Groups of substances represented in Data Base: RCRA hazardous
wastes
(NPP) Non-pollutant parameters included in the data base: Chemical
data Compliance data ;Disposal ;Location ^Sampling date ; Site
description
(OS) Time period covered by data base: 02-01-80 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Other As needed varies
by site
(NOB) Number of observations in data base: over 100.(Estimated)
(MED Estimated annual increase of observations in data base: 50-100.
(INF) Data base includes: Summary aggregate observations
(MTS) Total number of stations or sources covered in data base: 160,
(WCS) ho. stations or sources currently originating/contributing data:
10 (or less.)
(NOF) number of facilities covered in data base (source monitoring): 16
0 •
(GEO) Geographic coverage of data base: Selected federal region Region
(LOC) Data elements identifying location of station or source include:
State ;County ;City ;Town/township ;street address ^Project
identifier
(FAC) Tata elements identifying facility include: Plant facility name
;Plant location ;Street address ;Program identifier
(CDE) Pollutant identification data are: Oncoded
(LlM) Limitation/variation in data of which user should be aware: Infor
nation is generated internally and also comes from state agencies.
Level of detail may vary from one file to another. Approximately
400 sites are covered in the file. Sampling has been carried out
on 160 of those sites.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Saaplin
g plan documented ^Collection method documented ;Analysis method
document QA procedures documented
1159
-------
Accession No. 9055000906 (cent)
(ANL) Lab analysis based on EPA-approved or accepted Methods? NO
Leder,A.
(ROR) Responsible Organization: Region V.Water Management Division.
1160
-------
Accession No* 9055000907
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Rational Pollutant Discharge
Elimination System (NPDES) Compliance Files
(ACR) Acronym of Data Base or Model: None
(MED) Jedia/Subject of Data Base or Model: Effluents from National
pollutant Discharge Elimination System (NPDES) permitted
facilities.
(ABS) Abstract/Overview of Data Base or Model: Files containing
information relating to the compliance status of permit holders
under the National Pollutant Discharge Elimination System (NPDES)
pernit program. Files are arranged in alphabetical order by
State in the Water and Hazardous Materials Compliance Section.
?i™-»ontaln Natlonal Pollutant Discharge Elimination System
(NPDES) permits, self monitoring reports, state and federal
inspection reports, state and federal enforcement actions,
notices of noncompliance from permittees and other correspondence
relating to the status of permittee compliance.
(CTC) CONTACTS: Subject matter Arnold Leder (312)353-2114s EPA
Office Arnold Leder (31
(DTP) Type of data collection or monitoring: Point source data
collection industrial and municipal
(STA) Data Base status: Operational/ongoing
(CRP) Groups of substances represented in Data Base: 11 conventional
Hater
(NPP) Non-pollutant parameters included in the data base: Compliance
data Discharge points ;Flow rates ;Inspection data ; Location
/Sampling date
(OS) Time period covered by data base: 09-01-74 TO 09-30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: daily Bother monthly
discharge monitoring reports contain data typically collected
daily, some may vary in frequency.
(NOB) Number of observations in data base: 500000 or more.(Estimated)
(NEI) Estimated annual increase of observations in data base: 90000.
(INF) Data base includes: Raw data/observations ^Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 1069
(majors.)
(NCS) No. stations or sources currently originating/contributing data:
1069 (majors.)
(NOF) Number of facilities covered in data base (source monitoring): 10
69 (majors.)
(GEO) Geographic coverage of data base: Selected federal region Region
(LOC) Data elements identifying location of station or source include:
State ;City ;Toun/township ;Street address jProject Identifier
NPDES number
(FAC) Data elements identifying facility include: Plant facility name
jPlant location ;NPDES
(CDE) Pollutant identification data are: Dncoded
(LIM) Limitation/variation in data of uhich user should be aware: Typic
ally there is a three month delay in receipt of discharge
1161
-------
Accession Ho. 9055000907 (cont)
monitoring reports. Variations in pernit requireaents nay cause
variations in data being available.
(DPR) Data collect./anal, procedures conforn to ORD guidelines: Samplin
g plan documented
(AML) Lab analysis based on EPA-approved or accepted Methods? NO
(PRE) Precision: Precision and accuracy estiaates exist but are not
included in data base (froa compliance evaluation sampling only)
(EOT) Editting: No known edit procedures exist.
(CBY) Data collected by: Self reporting Permittees ;State agency
perform compliance evaluation inspection compliance sampling
inspections. ^Regional office Surveillance and Analysis Divisions
(ABY) Data analyzed by: Self reporting Permittees
State agency state environmental protection agencies
Regional office Surveillance and Analysis Divisions
(IDL) Laboratory identification: HO
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Program evaluation
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 309 (Clean Hater Act-CHA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Unpublished
reports Quarterly Mon-Compliance Evaluation/Report
(ROS) Number of regular users of data base: 1 office
(USR) Current regular users of data base: EPA regional offices
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(DPDT) Frequency of data base master file up-date: Monthly
(RDBEPA) Related EPA data bases used in conjunction with this data base
Permit Compliance System (PCS); National Pollutant Discharge
Elimination System (NPDES); Grants Information and Control
System (GICS), ENF-Q (Region V-report on violations and actions)
(ODB) Other pertinent non-EPA data bases: State maintained National
Pollutant Discharge Elimination System (NPDES) permit and
compliance files for minor discharges
(CMP) Completion of form:
S.K. Swanson
OFC: EPA/Region V/Compliance Section
AD: 230 So. Dearborn Chicago, IL 60604
PH: (312)886-6708
(OF) Date of form completion: 01-06-83
(NMAT) Number of substances represented in data base: 11
(NCAS) Number of CAS registry numbers in data base: 2
(MAT) Substances represented in data base:
acidity fecal collform
alkalinity nitrogen<7727-37-9>
dissolved oxygen oil and grease
dissolved solids oxygen demand
1162
-------
Accession lo. 9055000907 (cont)
PH suspended solids
phosphorus<7723-14-0>
(CAS) CAS registry numbers of substances Included in data base* 7727*37
-9; 7723-14-0
(CUM) Contact nane(s): Leder,A. * Led«r,A.
(ROR) Responsible Organization: Region f. Mater Nanagesient Division.
1163
-------
Accession Mo. 9057000002
-------
Accession Mo. 9057000002 (cont)
Contractor lab University of Nebraska
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Compliance or enforcement
(AUT) Authorization for data collection: Ho statutory requirement:
Data collection requirement is to determine whether health
complaints could be linked to a specific incinerator*
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Published
paper & raw data
(IfUS) Number of regular users of data base: 6
(USR) Current regular users of data base: EPA headquarter offices
EPA regional offices
States
University of Illinois
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office ;State agency
(DST) Form of data storage: Original form (hardcopy* readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Other one time
sampling program only
(CMP) Completion of form:
Carolyn Hesse
OFC: EPA/Region ?/Toxic Substances Office
AD: 230 S. Dearborn St. Chicago, IL 60604
PH: (312)353-2291
(DF) Date of form completion: 01-27-83
(IIMAT) Number of substances represented in data base: 23
(NCAS) Number of CAS registry numbers in data base: 14
(MAT) Substances represented in data base:
aluminum<7429-90-5> molybdenum and compounds
antimony<7440-36-0> <7439-98-7>
arbenzodioxin(s) organic 6C/MS scans for signified
arsenic<7440-38-2> t organics
broffide palladium
cadmium<7440-43-9> polybrominated biphenyls (PBBs)
calcium polychlorinated biphenyls (PCBsJ
chloride silver<7440-22-4>
chrcmium<7440-47-3> sodium<7440-23-5>
copper<7 440-50-8> tIn
dibenzofuran<132-64-9> titanium<7440-32-6>
lead<7439-92-l> zinc<7440-66-6>
mercury<7439-97-6>
(CAS) CAS registry numbers of substances included in data base: 7429-90
-5; 7440-36-0; 7440-38-2; 7440-43-9; 7440-47-3; 7440-50-8;
132-64-9; 7439-92-1; 7439-97-6; 7439-98-7; 7440-22-4;
7440-23-5; 7440-32-6; 7440-66-6
(CNN) Contact name(s): Hesse/C.
(COR) Contact organization: Toxic Substance Office/ Region T
(ROR) Responsible Organization: Region V.Air Management Division.
1165
-------
Accession Ho. 9057000002 (cont)
1166
-------
Accession No. 9057000003
(DQ) Date of Questionaire: 12-02-92
(NAM) Name of Data Base of Model: Hemlock, Michigan Environmental
Samples
(ACR) Acronym of Data Base or Model: HEMLOCK
(MED) Kedia/Subject of Data Base or Model: Drinking water JGround
water ;Sediment ;Soil ^Surface water fish from rivers, bi Tissue
fish, goose, chicken, squirrel, deer, con.
UBS) Abstract/Overview of Data Base or Model: Data collection was a
one tine study to determine if the Hemlock, MI area had been
contaminated yith toxic substances. Numerous samples Here
collected and analyzed for a variety of parameters. This is not
a continuous program.
(CTC) CONTACTS: Subject natter Karl Breaer (312) 353-2291; EPA
Office Karl Bremer (312
(DTP) Type of data collection or monitoring: Ambient data collection
(STA) Data Base status: Discontinued
(GRP) Groups of substances represented in Data Base: 129 307 CHA ;41
CWA potential criteria ;9 potential drinking Mater j 48 cancelled
pesticides ;9 monitoring pesticides
(NPP) Non-pollutant parameters included in the data base: Health
Effects Center for Disease Control generated
(OS) Tine period covered by data base: 10-00-79
(TRM) Termination of data collection: Not applicable
(FRQ) Frequency of data collection or sampling: one time only
(NOB) Number of observations in data base: 500 or more.(Estimated)
(NED Estimated annual increase of observations in data base: 0.
(INF) Data base includes: Summary aggregate observations
(NTS) Total number of stations or sources covered in data base: (about
/15.
(NCS) No. stations or sources currently originating/contributing data:
V.
(NOF) Nuiiber of facilities covered in data base (source monitoring): 1.
(GEO) Geographic coverage of data base: County/smaller location
Hemlock, Michigan area
(LOC) Data elements identifying location of station or source include:
State /County ;Toun/tounship ;Street address
(FAC) Data elements identifying facility include: Plant facility name
;PI ant location ^Parent corp name
(CDE) Pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Rone
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented ^Analysis method documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(A00) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: Edit procedures used but undocumented.
(CBY) Data collected by: Regional office Surveillance and Analysis
Division
-------
Accession Mo. 9057000003 (cont)
Nebraska; (fright State University
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collections Special study
(AOT) Authorization for data collection: No statutory re quire sent:
Data collection requirement is Senate Coaaittee mandated special
study in response to public complaints.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Report in
document fora
(NOS) Number of regular users of data base: 5 or »ore
(DSR) Current regular users of data base: EPA regional offices
local populace (toun Meeting)
(CNF) Confidentiality of data and Halts on access: No Halts on
access to data
(DLC) Primary physical location of data: Regional office
(OST) Fora of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: Mo
(UPDT) Frequency of data base aaster file up-dates Other data was
gathered for a special study
(QDB) other pertinent non-EPA data bases: Center for Disease Control
conducted health study in conjunction with EPA's environaental
aonitoring in Hemlock, Michigan
(CMP) Completion of fora:
Carolyn Hesse
OFC: EPA/Region V/Toxic Substances Office
AD: 230 S. Dearborne St. Chicago, IL 60525
PH: (312) 353-2291
(OF) Date of fora completion: 01-27-83
(MHAT) Number of substances represented in data base: 145
(IICAS) Nuaber of CAS registry numbers In data base: 147
(MAT) Substances represented in data base:
l,l,l-trichloroethane<71-55- 2,4,6-trlchlorophenol<88-06-2>
6> 2,4,7,8-tetrachlorodibenzo-p-
1,1,2, 2,-tetrachloroethane dtoxin (tcdd)
<79-34-5> 2,4-dichlorophenol<120-83-2>
l,l,2-trlchloroethane<79-00-5> 2,4-dimethylphenol<105-67-9>
1, l-dichloroethane<75-34-3> 2,4-dinltrophenol<51-28-5>
l,l-dlchloroethylene<75-35-4> 2,4-dlnitrotoluene<121-14-2>
l,2,4,-trichlorobenzen«<120-82-l> 2,6-dinitrotoluene<606-20-2>
l,2-dichlorobenzene<95-50*l> 2-chloroethylvlnyl ether<110-75-8>
1,2-dichloroethane<107-06-2> 2-chloronaphthalene<91-58-7>
l,2-dichloropropane<78-87-5> 2-chlorophenol<95-57-8>
l,2-dlchloropropylene<563-S4-2> 2-nitrophenol<88-75-5>
l,2-diph«jiylhydrazine<122-66-7> 3,3'-dichlorobenzldin«<91-94-l>
1,2-trans-dichloroethylene 3,4-benzofluoranthene<205-99-2>
<156-60-5> 4,4'-ddd(p,p'td«)
l,3-dichlorobenzene<541-73-l> 4,4'-dde(p,p'-ddx)<72-55-9>
l/4-dichlorobenzene<106-46-7> 4,4'-ddt<50-29-3>
2f 4^5-trlchlorophenoxyproplonlc 4/6-dinitro-o-cresol<534-52-l>
acid (TP)<93-72-l>
1168
-------
Accession No. 9057000003
(cont)
4-broBiophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acetone<67-64-l>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrin<309-00-2>
anthracene<120-12-7>
arsenic<7440-38-2>
benzene<71-43-2>
benzidine<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h,i)perylene<191-24-2>
benzo(k)fluoranthene<207-08-9>
berylliuin<7440-41-7>
bhc (lindane)-ga««a<58-89-9>
bhc-alpha<31 9-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
biphenyl<92-52-4>
bis(2-chloroethoxy)nethane
bis(2-chloroethyl)ether
bis (2-chloroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloromethyl)ether<542-88-l>
bro«ine<7726-95-6>
broffio«Bethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadniuB<7440-43-9>
carbon tetrachloride<56-23-5>
chlordane<57-74-9>
chl orine<778?-50-5>
chlorobenzene
chlorodibr omo0ethane
chloroethane<75-00-3>
chloroform<67-66-3>
chloroaethane<74-87-3>
chrysene<218-01-9>
copper <7440-50-8>
cyaride<57-12-5>
dene ton< 8065-48- 3>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dlalkyl ethers
d Ibenzo (a, h)anthracene<53-70-3 >
dibenzofuran<132-64-9>
dichlorobroBoaethane<75-27-4>
dichlorodifluoro«ethane<75-71-8>
dichloro«ethane<75-09-2>
dieldrin<60-57-l>
diethyl phthalate<84-66-2>
dimethyl phthalate<131~ll-3>
diphenyl ether<101-84-8>
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
£luoranthene<206-44-0>
t luor ene< 86-7 3-7>
fluorides
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene< 118-7 4-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hex achloroe thane< 67-7 2-l>
indeno (l/2/3-cd)pyrene
isophorone<78-59-l>
kepone<143-50-0>
lead<7439-92-l>
•alathion<121-75-5>
»ercury<7439-97-6>
methoxychlor<72-43-5>
•ethyl ethyl ketone (nek)<78-93-3>
airex<2385-85-5>
n-alkanes clO-c30
n-nitrosodi-n-propylamine
<621-64-7>
n-nitrosodiBethyla«ine<62-75-9>
n-ni trosodiphenyl aaine< 86-30-6>
naphthalene<91-20-3>
nitriloacetates
nitrobenzene<98-95-3>
p-chloro-«-cresoi<59-50-7>
parathion<56-38-2>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<1 11 04-28- 2>
pcb-1232 (arochlor 1232)
pcb-1242 (arochlor 1242)
<53469-21-9>
1169
-------
Accession Ho. 9057000003 (cont)
pcb-1248 (arochlor 1248) sodium and compounds<7440-23-5>
<12672-29-6> styrene<100-42-5>
pcb-1254 (arochlor 1254) terpencs
<11097-69-l> tetrachloroethylene
pcb-1260 (arochlor 1260) thalliu«<7440-28-0>
<11096-82-5> toluene<108-88-3>
pentac hloropheno1< 87-86-5> toxaphene<8001-35-2>
phenanthrene<85-01-8> tribromoaethane<75-25-2>
phenol<108-95-2> trichloroethylene<79-01-6>
polychlorinated biphenyls (PCBs) trichlorofluoro«ethane<75-69-4>
pyrene<129-00-0> vinyl chloride<75-01-4>
silver<7440-22-4>
(CAS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5? 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 93-72-1; 88-06-2; 120-83-2; 105-67-9; 51-28-5;
121-14-2; 606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1;
205-99-2; 72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3;
100-02-7; 83-32-9; 208-96-8; 67-64-1; 107-02-8; 107-13-1;
309-00-2; 120-12-7; 7440-38-2; 71-43-2; 92-87-5; 56-55-3;
50-32-8; 191-24-2; 207-08-9; 7440-41-7; 58-89-9; 319-84-6;
319-85-7; 319-86-8; 92-52-4; 111-91-1; 111-44-4; 39638-32-9;
117-81-7; 542-88-1; 7726-95-6; 74-83-9; 85-68-7; 7440-43-9;
56-23-5; 57-74-9; 7782-50-5; 108-90-7; 124-48-1; 75-00-3;
67-66-3; 74-87-3; 218-01-9; 7440-50-8; 57-12-5; 8065-48-3;
84-74-2; 117-84-0; 53-70-3; 132-64-9; 75-27-4; 75-71-8; 75-09-2;
60-57-1; 84-66-2; 131-11-3; 101-84-8; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1; 193-39-5;
78-59-1; 143-50-0; 7439-92-1; 121-75-5; 7439-97-6; 72-43-5;
78-93-3; 2385-85-5; 621-64-7; 62-75-9; 86-30-6; 91-20-3;
98-95-3; 59-50-7; 56-38-2; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 87-86-5;
85-01-8; 108-95-2; 129-00-0; 7440-22-4; 7440-23-5; 100-42-5;
127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2; 79-01-6;
75-69-4; 75-01-4
(CRN) Contact nane(s): Brener,K. ; Bre»er>K.
(ROR) Responsible Organization: Region V.Air Management Division.
1170
-------
Accession No. 9057000004
-------
Accession No* 9057000004 (cont)
COSR) Current regular users of data base: EPA regional offices
individual gardeners
(CNF) Confidentiality of data and liaits on access: No Units on
access to data
(DLC) prinary physical location of data: Regional office
(OST) Forn of data storage: Manual sumary of data
COAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: No
(UPDT) Frequency of data base naster file up-date: Other Seasonal-Most
calls in spring
(CMP) Completion of fora:
Carolyn Hesse
QFC: EPA/Region V/Toxic Substances Office
AD: 230 S. Dearborn St. Chicago, IL 60604
PH: <312) 353-2291
(OF) Date of forn completion: 01-27-83
(NMAT) Nunber of substances represented in data base: 2
CNCAS) Nunber of CAS registry nunbers in data base: 1
(MAT) Substances represented in data base:
cadniun<7440-43-9> ph
(CAS) CAS registry nunbers of substances included in data base: 7440-43
-9
(CNN) Contact nane(s): Hesse,C«
(COR) Contact organization: Region ?/ Toxic Substances Office
(RQR) Responsible Organization: Region V.Air Managenent Division.
1172
-------
Accession Mo. 9065000903
(DQ) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: Discharge Monitoring Report Files
(ACR) Acronym of Data Base or Model: DMR
(MED) Media/Subject of Data Base or Model: Effluents point source
effluents
(ABS) Abstract/Overvien of Data Base or Model: This data base contains
all of the Discharge Monitoring Reports submitted to the
Enforcement Division by National Pollutant Discharge Elimination
Systems (NPDES) permittees in Region YI. It is a manual (non-
automated) data base. It covers all conventional Hater
pollutants, as well as other pollutants for the petrochemical and
organic chemical Industries (estimated 20-30% of permittees).
(CTC) CONTACTS: Subject matter Glenn E. Bingham (214) 767-2765;
Computer-related Glenn
(DTP) Type of data collection or monitoring: Point source data
collection industrial and municipal
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 11 conventional
(NPP) Kon-pollutant parameters Included in the data base: Collection
method Compliance data ^Concentration measures ^Discharge points ;
Flow rates ;Location ;Physical data ;Salinity ;Sampling date ;
Site description ;Temperature jTest/analysis method ;Yolume/mass
measures
(DS) Time period covered by data base: 03-01-73 TO 08-30-80
(TRM) Termination of data collection: Mot anticipated
(FRQ) Frequency of data collection or sampling: dally ;Meekly >monthly
(NOB) Number of observations in data base: 4000000 or more.(Estimated)
CNEI) Estimated annual increase of observations in data base: 1000000
(or more.)
(INF) Data base includes: Ran data/observations ^Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 538o.
(MCS) No. stations or sources currently originating/contributing data:
4567. f % __
(NOF) Number of facilities covered in data base (source monitoring): 53
86.
(GEO) Geographic coverage of data base: Selected federal region Region
VI
(LOC) Data elements identifying location of station or source include:
State ;County >CUy ;Town/tounshlp jStreet address >description of
discharge loc
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ;Parent corp name ;NPDES
(CDE) Pollutant identification data are: Oneoded
(LIM) Limitation/variation in data of Mhich user should be aware: Data
is permittee supplied and, in most cases, is unverified^overs
both major and minor discharges.
(DPR) Data collect./anal. procedures conform to ORD guidelines: Samplin
g plan documented ;Collection method documented ^Analysis method
document QA procedures documented
-------
Accession No. 9065000903 (cont)
fecal coliform suspended solids
nitrogen<7727-37-9>
(CAS) CAS registry numbers of substances included in data base: 7727-37
-9; 7723-14-0
(CHH) Contact name(s): Bingham,G.E. ; Bingham,G.E.
(COR) Contact organization: Enforcement Division, Region ?I
(ROR) Responsible Organization: Region IT.Hater Management Division.
1174
-------
Accession No. 9067000502
(DQ) Date of Questionalre: 12-02-82
(NAN) Name of Data Base of Model: Discharge Monitoring Report Piles
(ACR) Acronym of Data Base or Model: DMR PCS
(MED) Kedia/Subject of Data Base or Model: Effluents ; Runoff Rainfall
(ABS) Abstract/ Over view of Data Base or Model: This au ton a ted data
base contains all DMRs submitted to the Water Mgnst Division by
NPDES permittees in Region 6. It contains major permittees and
selected minors* Facilities not included in data base are in
manual system - DMRs on file.
(CTC) CONTACTS: Subject matter Robert Stender, Chief, Admin.
Section 767-9929 ; Computer-related Glenn Bingham, Computer
Spec. 767-4379 ; EPA Office Robert Stender, Water Mgmt. Div.
767-9929
(DTP) Type of data collection or monitoring: Point Source
(STA) Data Base status: Presently Operational/Ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CHA ; 11
conventional water
(NPP) Non-pollutant parameters included in the data base: collection
method or instrument ; compliance data ; concentration measures
; discharge points ; fIon rates ; geographic subdivisions ;
industry ; inspection data ; location ; physical data ?
precipitation ; salinity > sampling date ; site description ;
temperature } test/analysis method ; treatment devices or processes
/ volume/mass measures
(DS) Time period covered by data base: 01-73 TO 09-82
(TRM) Termination of data collection: Not Anticipated
(FRQ) Frequency of data collection or sampling: Ongoing:Daily ;
Ongoing:Weekly ; Ongoing:Monthly ; Ongoing:guarterly
(NOB) Number of observations in data base: 5248800(Sstimated to Date)
(NED Estimated annual increase of observations in data base: 583200
(INF) Data base includes: Aggregate or summary observations
(NTS) Total number of stations or sources covered in data base: 6698
(NCS) No. stations or sources currently originating/contributing data:
6698
(NOF) Number of facilities covered in data base (source monitoring): 66
98
(GEO) Geographic coverage of data base: Single or selected Federal
Regions - Region 6
(LOC) Data elements identifying location of station or source include:
State ; county ; city ; town/township ; street address ; Other-
description of discharge locations
CFAC) Data elements identifying facility include: plant or facility
name ; plant location ; parent corporation-name / street address >
sic code ; duns number ; NPDES number
(CDS) Pollutant identification data are: coded, storet parameter codes
; uncoded for DRMs not in PCS
(LiM) Limitation/variation in data of vhich user should be aware: Data
is permittee supplied and quality control numbers may vary.
(DPR) Data collect./anal, procedures conform to GRD guidelines: YES
(AND Lab analysis based on EPA-approved or accepted methods? YES
(EOT) Editting: partial - major DMRs in QA program
(CBY) Data collected by: self-reporting permittee
1175
-------
Accession No. 9067000502 (cont)
(ABY) Data analyzed by: self-reporting ; contractor lab
-------
Accession No. 9067000502
Ccont)
2-chloronaphthalene
2-chlorophenol
chromium
4- ehlorophenyl phenyl ether
chrysene
copper
cyanide
4,4*-DDD(p,p--TDE)
4,4*-DDE{p,p*-DDX)
4,4'-DDT
dibenzoC a/hJ anthracene
di-n-butyl phthalate
It2-dichlorobenzene
1/3-dichlorobenzene
1* 4-dichlorobenzene
3,3 '-dichlorobenzidine
dichlorobromomethane
dichlorodifluoromethane
1,1-dichloroethane
1,2-dichloroethane
1,1-dichloroethylene
1^2-trans- dichloroethylene
It4-dichlorophenol
I/2-dichloropropane
1,2-dichloropropylene
(I/3-dichloropropane)
dieldrin
diethyl phthalate
1,4-dimethylphenol
dimethyl phthalate
4/6-dinitro-o-cresol
If4-dinitrophenol
2,4- dinitrotoluene
2,6-dinitrotoluene
di-n-octyl phthalate
1/2- diphenylhydrazine
endosulfan-alpha
endosulfan-beta
endosulfan sulfate
endrin
endrin aldehyde
ethylbenzene
fluoranthene
fluorene
heptachlor
heptachlor epoxide
hexachlorobenzene
hexachlorobutadiene
hexachlorocyclopentadiene
hexachloroethane
indeno (l,2,3-cd)pyrene
isophorone
lead
mercury
aethyl bromide(bromonethane)
methyl chloride (ch1oroaethane)
nethylene chloride(dichloroaethane
)
naphthalene
nickel
nitrobenzene
2-nitrophenol
4-nitrophenol
n-nitrosodinethylanine
n-nitrosodiphenylasine
n-nitrosodi-n-propylaaine
pentachlorophenol
phenanthrene
phenol
PCB-1016(arochlor 1016)
PCB-1221(arochlor 1221)
PCB-1232(arochlor 1232)
PCB-1242(arochlor(1242)
PCB-1248(arochlor 1248)
PCB-1254(arochlor 1254)
PC8-1260(arochlor 1260)
pyrene
selenium
silver
2/4,7,8-tetrachlorodibenzo-p-
dioxin(TCDD)
1/1,2,2-tetrachloro ethane
tetrachloroethylene
thallium
toulene
toxaphene
1/2,4-trichlor obenzene
If If1-trichloroethane
1,1,2-trichloroethane
trichloroethylene
trichlorofluoromethane
2,4,6-trichlorophenol
vinyl chloride
zinc
acidity
alkalinity
dissolved oxygen
dissolved solids
fecal coliform
nitrogen and compounds
oil & grease
oxygen demand
PH
phosphorus and compounds
1177
-------
Accession lo. 9067000502 (cont)
suspended solids PCBs
aluBinun and compounds bar lira
avaonla cadaius
fluorides chroBiuB
Iron and compounds coppar
aolybdanuB and compounds iron
nltratas/nltrltas laad
styrna aarcury
vanadliM nlckal
aldrln sallaniim
dlaldrln vanadlua
andrln
CCiN) Contact naaaCs)* Sta«dar,R. » Btngha^C.
(COR) Contact organization: Vatar laiisgaaant Division
(ROR) Rasponslbla Organizations Ragion YI.Hatar Managaaont Division,
1178
-------
Accession Ho. 9067000503
(DQ) Date of Questionaire: 12-02-82
(RAH) Name of Data Base of Model: STORET: Storage and Retrieval of
W.Q. Data
(ACR) Acronym of Data Base or Model: STQRET
(MED) Media/Subject of Data Base or Model: Drinking water raw ;
Effluents (NPDES) } Ground water ; Runoff ; Sedinent ; Surface
water (all) ; Tissue (fish)
(ABS) Abstract/Overview of Data Base or Model: Mostly aabient surface
water quality observations sone sediment and tissue residue
observations occasional ground water and fff effluent and runoff
observations. Observation can be once in tile or composite over
space as time.
(CTC) CONTACTS: Subject Batter Charles S. Conger 8-382-7220 ;
Computer-related Charles S. Conger 8-382-7220 } EPA Office
Charles S. Conger 8-382-7220
(DTP) Type of data collection or monitoring: Ambient
(STA) Data Base status: Presently Operational/Ongoing
(GRP) Groups of substances represented in Data Base: 129 307 CHA EPA
Lab except asbestos & 2,3/7,8-TCDD ; 11 conventional wate; 41
CHA potential criteria ; 21 drinking water standards
(NPP) Non-pollutant parameters included in the data base: Biological
data ; chemical data > concentration measures ; discharge points
; elevation } flow rates ; geographic subdivisions ; location ;
physical data ; political data > political subdivision ; salinity
; sampling date ; site description > temperature
(DS) Time period covered by data base: 01-01 TO 99-99
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Gne tine only ;
ongoing:weekly ; ongoing:monthly } ongoing:quarterly ;
ongoing:semi-annually ; ongoing:annually ; ongoing:as needed
(NOB) Number of observations in data base: 60,000(£stimated to date)
(NEI) Estimated annual increase of observations in data base: 12,000
(INF) Data base includes: Raw data/observations } aggregate or summary
observations
(NTS) Total number of stations or sources covered in data base: 1000
state only
(NCS) No* stations or sources currently originating/contributing data:
1000
(NOF) Number of facilities covered in data base (source monitoring): ?
(GEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
State ; county ; latitude and longitude, UTM, or other coordinates
; Other- Agency code, basin, HRC Hydrologic Unit.
(FAC) Data elements identifying facility include: Other- Depends who
stores site.
(CDE) Pollutant identification data are: coded, storet parameter codes
(LIM) Limitation/variation in data of which user should be aware: M/0
contacting collecting agency use - should not utilize data for more
than indicated studies
(DPR) Data collect./anal, procedures conform to QRD guidelines: YES
State/EPA Data only
(AND Lab analysis based on EPA-approved or accepted methods? YES
1179
-------
Accession No. 9067000503 (cont)
State/EPA Data only
(AUD) Lab Audit: Partial varys
(PRE) Precision: None available
(EOT) Editting: Partial
(CBY) Data collected by: state agency, ADPC4E, LNDR, NMEID, DSHD, TDUR
•f regional office S&A Lab ; Other Federal Agencies, OSGS,
CDE-Districts, BLM, USFS, USER
(ABY) Data analyzed by: State agency, ADDC&E, LDNR, MM, SLS ; Regional
office, S&A Lab Contractor Lab, Several ; Other Federal agencies,
USGS, CQE, 6LN, USFS, USBR
(IDL) Laboratory identification: NO
-------
Accession No. 9067000503
(cont)
•ercury
nickel
pentachlorophenol
PCB~1016(arochlor 1016)
PCB-1221(arochlor 1221)
PCB-1232(arochlor 1232)
PCB-1242(arochlor 1242)
PCB-1248(arochlor 1248)
PCB-1254(arochlor 1254)
PCB-1260( arochlor 1260)
selenium
silver
toxaphene
zinc
alkalinity
dissolved oxygen
dissolved solids
fecal colifom
nitrogen and compounds
oil & grease
oxygen demand
PH
phosphorus and compounds
suspended solids
ammonia
(CNN) Contact name(s): Conger,C.s. >
(COR) Contact organization: Charles S.
(ROR) Responsible Organization: Region
chlorine
2,4-0
fluorides
iron and compounds
•ethoxychlor
nitrates/nitrites
phosphorus and compounds
sulfates
2,4,5-TP
arsenic
cadniua
chromium
2,4-D
endrin
lead
llndane
•ercury
•ethoxycblor
nitrate
selenium
silver
silvex
toxaphene
turbidity
Conger/C.S. ; Conger,C.S.
Conger
TI.Hater Management Division.
1181
-------
Accession No. 9067000504
(DQ) Date of Questionaire: 12-02-82
(MAM) Mane of Data Base of Model: National Emissions Data System
-------
Accession No. 9067000504 (cent)
YES: OMB form number 20000022
(REP) Form of available reports and outputs of data base: Publications
- Refer to Hafl NEDs Description Regional Office doesn't print
reports ; Printouts on request
(HOS) Number of regular users of data base: 11, 10 Regional Offices &
Hdqtrs.
(BSR) Current regular users of data base: EPA Headquarters Offices,
DAQPS, RTP, NC ; EPA Regional Offices ; Other Federal Agencies ;
Other- Consultants
(CNF) Confidentiality of data and Units on access: Sooe data
confidential/ limits on access both uithin EPA and outside the
agency
(DLC) Primary physical location of data: NCC/RTP
(DST) Form of data storage: Magnetic Disc
(OAC) Type of data access: Refer to National Report
(CH6) Direct charge for non-EPA use: No outside use/access permitted,
could be B for centralized ETS Ststera; none to date in Region 6.
(UPDT) Frequency of data base master file up-date: Annually
(RSS) Related EPA automated systems uhich use data base: Refer to
National NEDS Description
(RDBEPA) Related EPA data bases used in conjunction with this data base
Refer to National NEDS Description
(RDB) Non-EPA data bases used in conjunction with this data base: Refer
to National NEDS Description
(CMP) Completion of form: # Ruth Tatorafc OFC: 6#ES-SA Region 6£ AD:
6ES-SA EPA Region 6, 1201 Elm, Dallas, TX 75270$ PH: (214)
767-9772$
(DP) Date of form completion: 01-19-83
(MMAT) Number of substances represented in data base: 7
(NCAS) Number of CAS registry numbers in data base: 0005
(MAT) Substances represented in data base:
Carbon monoxide <630-08-0> Ozone <10028-15-6>
Hydrocarbons Sulfur dioxide <7446-09-5>
Lead <7439-92-l> Total suspended particulates
Nitrogen dioxide <101C2-44-0>
(CAS) CAS registry numbers of substances included in data base: 630-08-
0; 7439-92-1; 10102-44-0; 10028-15-6; 7446-09-5
(CNH) Contact name(s): Tatom,R. ; Smiley,V.
(COR) Contact organization: Environmental Analysis Section 6ES-SA
(ROR) Responsible Organization: Region VI.Mater Management Division.
1183
-------
Accession No. 9067000505
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: Storage and Retrieval of Aerometric
Data
(ACR) Acronym of Data Base or Model: SAROAD
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: Refer to Description of
National System
(CTC) CONTACTS: Subject Matter Ruth Tatorn Data Manager <214)
767-97*72 ; Computer-related Pat Nelson Computer Technician
(214) 767-3542 ; EPA Office Environmental Analysis Section
6ES-SaA (214) 767-9772
(DTP) Type of data collection or Monitoring: Anbient
(STA) Data Base status: Presently Operational/Ongoing
(GRP) Groups of substances represented in Data Base: 7 criteria NAAQS
; 15 metals } other - consult SAROAD FARM FILE
(MPP) Non-pollutant parameters included in the data base: Collection
•ethod or instrument ; concentration measures ; elevation ;
physical data ; political subdivisions ; population demographics >
precipitation ; sampling date ; site description ; temperature ;
test/analysis method / volume/mass measures ; wind direction >
Hind velocity
CDS) Time period covered by data base: 01-59 TO 09-82
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Ongoing:hourly ;
ongoing: daily
(MCA) Number of observations in data base: Unknown
(NED Estimated annual increase of observations in data base: Unknown
(INF) Data base Includes: Ran data/observations > aggregate or summary
observations } reference data or citations
(ITS) Total number of stations or sources covered in data base: Unknown
(NCS) No. stations or sources currently originating/contributing data:
52 States & territories
(•OF) Number of facilities covered in data base (source monitoring): Un
known
(GEO) Geographic coverage of data base: National
(LOC) Data elements identifying location of station or source include:
State ; county ; SMSA (Standard Metropolitan Statistical Area) ;
city ; town/township ; street address > latitude and longitude/
UTM, or other coordinates ; individual project identifier
(CDS) pollutant identification data are: Coded, Storet parameter codes
(OPR) Data collect./anal, procedures conform to ORD guidelines: YES
(AIL) Lab analysis based on EPA-approved or accepted methods? YES
(AOD) Lab Audit: NO
(PRE) Precision: Partial
(EOT) Editting: YES, documented edits
(CBY) Data collected by: Local agency J State agency ; Other Federal
Agency ; EPA Headquarters } other
(ABY) Data analyzed by: Local agency ; State agency ; Other Federal
Agency ; EPA Headquarters ; other
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection:
9067000505 40
1184
-------
Accession No. 9067000505 (cont)
(AUT) Authorization for data collection: YES, citation 40CFR
(OMB) Data collected/submitted using OHB-approved EPA reporting forms:
YES, multiple forms
(REP) Form of available reports and outputs of data base: Publications,
Refer to Nat'l Description Region 6 has not published SAROAD
Reports ; Printouts on request ; microfilm
(NUS) Number of regular users of data base: 11, 10 Regional Offices
and Rdgtrs.
(OSR) Current regular users of data base: EPA Headquarters Offices-
OAQPS, RfP, NC ; EPA Regional Offices ; Other Federal Agencies ;
States ; Other- Consultants
(CNF) Confidentiality of data and Units on access: None
(DLC) Primary physical location of data: RCC/RTP
(OST) Form of data storage: Magnetic Disc
(DAC) Type of data access: Refer to national Report
(CH6) Direct charge for non-EPA use: No outside use/access permitted,
could be B for State Agency Users of NCC; none to date in R-6.
(UPDT) Frequency of data base master file up-date: Quarterly
(RSS) Related EPA automated systems which use data base: Refer to
Nat'l SAROAD Description
(RDBEPA) Related EPA data bases used in conjunction with this data base
Refer to Nat'l SARQAD Description
(RDB) Non-EPA data bases used in conjunction with this data base: Refer
to Nat'l SAROAD Description
(CNP) Completion of form: f Ruth Tatomf OFC: 6ES-SA Region 6# AD:
6ES-SA EPA Region 6, 1201 Elm, Dallas, TX 75270# PH: (2fl4)
767-9772*
(DF) Date of form completion: 01-19-83
(NMAT) Number of substances represented in data base: 22
(HCAS) Number of CAS registry numbers in data base: 20
(NAT) Substances represented in data base:
Carbon monoxide <630-08-0> Cobalt <7440-48-4>
Hydrocarbons Copper <7440-50-8>
Lead <7439-92-l> Iron <7439-89-6>
Nitrogen dioxide <10102-44-0> Lead <7439-92-l>
Ozone <10028-15-6> Manganese and compounds
Sulfur dioxide <7446-09-5> <7439-96-5>
Total suspended particulates Mercury <7439-97-6>
Arsenic <7440-38-2> Nickel <7440-02-0>
Barium <7440-39-3> Selenium <7782-49-2>
Beryllium <7440-41-7> Titanium <7440-32-6>
Cadmium <7440-43-9> Vanadium <7440-62-2>
Chromium <7440-47-3>
(CAS) CAS registry numbers of substances included in data base: 630-08
0; 7439-92-1; 10102-44-0; 10028-15-6; 7446-09-5; 7440-38-2;
7440-39-3; 7440-41-7; 7440-43-9; 7440-47-3; 7440-48-4;
7440-50-8; 7439-89-6; 7439-92-1; 7439-96-5; 7439-97-6;
7440-02-0; 7782-49-2; 7440-32-6; 7440-62-2
(CNM) Contact nane(s): Tatom,R. ; Nelson,P.
(COR) Contact organization: Environmental Analysis Section 6ES-SA
(ROR) Responsible Organization: Region VI.Water Management Division.
1185
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Accession Ho* 9075000901
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Consolidated Permits
Program-Application Fora l,2b*2c
(ACR) Acronyn of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Effluents point
soutces-nonmunicipal (industrial)
(ABS) Abstract/Overview of Data Base or Model: National Pollutant
Discharge Elimination Systen (HPDES) application fora indicates
data on pollutants contained in wastewater discharges. Data is
currently Manual-Hill be automated in Permit Compliance System II
(PCS II) or in the system for Consolidated Permitting and
Enforcement (SCOPE)
(CTC) CONTACTS: Subject matter Carl f. Blomgren (816)374-2281;
Computer-related Paul Hirth (816)374-2018; EPA Office Carl f.
Bloagren (816)374-2281
(DTP) Type of data collection or monitoring: Point source data
collection nonmunicipal (industrial)
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented In Data Base: 129 307 CHA ;11
conventional water ;41 CtfA potential criteria
(NPP) Non-pollutant parameters included in the data base: Chemical
data Discharge points ;Flow rates ;Industry ^Location ; Population
density ;Site description ^Treatment devices
(DS) Time period covered by data base: 06-01-80 TO 09*30-81
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: one time only
(NOB) Number of observations in data base: 1080.(Estimated)
(NEI) Estimated annual increase of observations in data base: 21600.
(INF) Data base includes: Reference data/citations
(NTS) Total number of stations or sources covered in data base: 10
(current )800(projected.)
(HCS) No. stations or sources currently originating/contributing data:
10.
(NOF) Number of facilities covered in data base (source monitoring): 10
(current )800 (projected.)
(GEO) Geographic coverage of data base: Selected federal region Region
¥11
(LOC) Data elements identifying location of station or source include:
State ;County ;City ;street address ^Coordinates Latitude and
longitude
(FAC) Data elements identifying facility include: Plant facility name
;Plant location ;Street address ;SIC code ; Dun Bradstreet
;NPDES: Hill change to Duns number
(COE) Pollutant identification data are: Uncoded
(LIM) Limitation/variation in data of which user should be aware: Case
by case variation in parameters
(DPR) Data collect./anal, procedures conform to ORD guidelines: Analysi
s method documented
(AND Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base Edit during review of application and in
development of permit.
1186
-------
Accession Ho. 9075000901 (cont)
(CBJO Data collected by: Self reporting ^Contractor lab for
dischargers
(ABY) Data analyzed by: State agency Environmental Quality Agencies
Regional office Surveillance and Analysis Division, Region VII.
Contractor lab for dischargers
(IDL) Laboratory identification: NO
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended, Section 402 (Clean Water Act-CWA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0173
(REP) Form of available reports and outputs of data base: Printouts on
request
(N0S) Nuvber of regular users of data base: 10
(OSR) Current regular users of data base: EPA headquarter offices
Office of Hater Enforcement
EPA regional offices
EPA laboratories
States
(CNF) Confidentiality of data and limits on access: Limits on outside
access for some data
(DLC) Primary physical location of data: State agency
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Other on as need
basis-uhen additional information available
(RSS) Related EPA automated systems Mhich use data base: STORET
(Storage and Retrieval of uater Quality Data): Permit compliance
System (PCS)
(RDBEPA) Related EPA data bases used in conjunction with this data base
other consolidated permit programs: Resource Conservation and
Recovery Act (RCRA), Underground Injection Control (UIC), Point
Source Discharges (PSD).
(CMP) Completion of form:
Carl V. Bloagren
OFC: EPA/Region Vll/Vater Management Division
AD: 324 E. llth St. Kansas City, MO 64106
PH: (816) 374-2281
(DF) Date of form completion: 01-14-83
(NMAT) Number of substances represented in data base: 143
(MCAS) Number of CAS registry numbers in data base: 131
(MAT) Substances represented in data base:
l,l,l-trichloroethane<71-55- l,2-dichloropropane<78-87-5>
6> l,2-dichloropropylene<563-54-2>
1,1,2,2,-tetrachloroethane l,2-diphenylhydrazine<122-66-7>
<79-34-5> 1,2-trans-dichloroethylene
l,l,2-trichloroethane<79-00-5> <156-60-5>
Ifl~dichloroethane<75-34-3> l,3-dichlorobenzene<541-73-l>
l,l-dichloroethylene<75-35-4> l,4-dichlorobenzene<106-46-7>
l,2,4,-trichlorobenzene<120-82-l> 2,4,6-trichlorophenol<88-06-2>
l,2-dichlorobenzene<95-50-l> 2,4,7,8-tetrachlorodibenzo-p-
l,2-dichloroethane<107-06-2> dioxin (tcdd)
1187
-------
Accession Mo. 9075000901
(cont)
2f 4-dichlorophenol<120-83-2>
2, 4-diaethylphenol<105-67-9>
1f 4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2f 6-dini tr ot o lue ne <6 06-20-2>
2-chioroethylvinyi ether<110-75-8>
2-chloronaph thalene< 91-58- 7>
2-chlorophenol<95-57-"8>
2-nitrophenol<88-75-5>
3,3'-dichlorobenzidine<91-94-l>
3f 4-benzof luoranthene<205-99-2>
4,4*-ddd(p,p*td«)
4, 4 *-dde(p,p •-ddx)<72-55-9>
4,4'-ddt<50-29-3>
4,6-dinitro-o-cresol<534-52-l>
4-bronophenyl phenyl ether
< 10 1-55-3 >
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02~7>
acenaphthene<83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
ac ry lonit r 11 e< 107-13 -1>
aldrin<309-00-2>
a««onla<7664-41-7>
an thracene
antl»ony<7440-36-0>
arsenlc<7440-38-2>
asbestos<1332-21-4>
benzen«<71-43-2>
ben2ldlne<92-87-5>
benzof a) anthracene<56-55-3>
ben7o(a)pyrene<50-32-8>
benzo(g,h^i)perylene<191-24-2>
ben2o(k)fluorantbene<207-08-9>
berylllu»<7440-4l-7>
bhc (Hndane)-gaB«a<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)«ethane
bls<2-chloroethyl)ether
bis(2-chioroisopropyl) ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloronethyl)ether<542-88-l>
bromo«ethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cad«ium<7440-43-9>
carbon tetrachlorlde<56-23-5>
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodibroaonethane<124-48-l>
chloroethane<75-00-3>
chloroform<67-66-3>
chloroaethane<74-87-3>
chro»iua<7440-47-3>
chrysene<218-01-9>
copper< 7440-50-8>
cyanide<57-12-5>
di-n-butyl phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenzo(a^h)anthracene<53-70-3>
dlchlorobrono«ethane<75-27-4>
dlchlorodifluoronethane<75-71-8>
dichloroiethane<75-09-2>
dleldrin<60-57-l>
diethyl phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
dissolved solids
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fecal colIforn
fluoranthene<206-44-0>
fluorene<86-7 3-7>
fluorides
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-7 4-l>
hexachlorobutadiene<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hex achloro ethane< 67-7 2-l>
Indeno (1,2,3-cd)pyrene<193-39-5>
iron and compounds<7439-89-6>
lsophorone<78-59-l>
lead<7439-92-l>
•ercury<7439-97-6>
n-nltrosodl-n-propylamine
<621-64-7>
n-nitrosodimethylaalne<62-75-9>
n-nltrosodiphenylanine< 86-30-6>
naphthalene<91-20-3>
nickel<7440-02-0>
nitrates/nitrites
nitrobenzene<98-95-3>
nitrogen<7727-37-9>
oil and grease
1188
-------
Accession Ho. 9075000901 (cont)
oxygen demand phenanthrene<85-01-8>
p-chloro-»-creso 1< 59-50-7> p henoKlO 8-95-2>
pH phosphorus<7723-14-0>
pcb-1016 (arochlor 1016) pyrene<129-00-0>
<12674-ll-2> seleniura<7782-49-2>
pcb-1221 (arochlor 1221) silver<7440-22-4>
<11104-28-2> sulfates
pcb-1232 (arochlor 1232) sulfides
<11141-16-5> suspended solids
pcb-1242 (arochlor 1242) tetrachloroethylene<127-18-4>
<53469-21-9> thalliuin<7440-28-0>
pcb-1248 (arochlor 1248) toluene<108-88-3>
<12672-29-6> toxaphene<8001-35-2>
pcb-1254 (arochlor 1254) tribro«o«ethane<75-25-2>
<11097-69-l> trichloroethylene<79-01-6>
pcb-1260 (arochlor 1260) trlchlorofluoroaethane<75-69-4>
<11096-82-5> vinyl chlorlde<75-01-4>
pentachlorophenol<87-86-5> zinc<7440-66-6>
(CAS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57^8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 7664-41-7; 120-12-7;
7440-36-0; 7440-38-2; 1332-21-4; 71-43-2; 92-87-5; 56-55-3;
50-32-8; 191-24-2; 207-08-9; 7440-41-7; 58-89-9; 319-84-6;
319-85-7; 319-86-8; 111-91-1; 111-44-4; 39638-32-9; 117-81-7;
542-88-1; 74-83-9; 85-68-7; 7440-43-9; 56-23-5; 57-74-9;
108-90-7; 124-48-1; 75-00-3; 67-66-3; 74-87-3; 7440-47-3;
218-01-9; 7440-50-3j 57-12-5; 84-74-2; 117-84-0; 53-70-3;
75-27-4; 75-71-8; 75-09-2; 60-57^1; 84-66-2; 131-11-3;
1031-07-8; 959-98-8; 33213-65-9; 7421-93-4; 72-20-8; 100-41-4;
206-44-0; 86-73-7; 1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4;
67-72-1; 193-39-5; 7439-89-6; 78-59-1; 7439-92-1; 7439-97-6;
621-64-7; 62-75-9; 86-30-6; 91-20-3; 7440-02-0; 98-95-3; 7727-37-9;
59-50-7; 12674-11-2; 11104-28-2; 11141-16-5; 53469-21-9;
12672-29-6; 11097-69-1; 11096-82-5; 87-86-5; 85-01-8;
108-95-2; 7723-14-0; 129-00-0; 7782-49-2; 7440-22-4; 127-18-4;
7440-28-0; 108-88-3; 8001-35-2; 75-25-2; 79-01-6; 75-69-4;
75-01-4; 7440-66-6
(CHM) Contact nane(s): Bloagren,C.V.; Hirth,P.; Blomgren,C.V.
(ROR) Responsible Organization: Region VII.Hater Management Division.
1189
-------
Accession No. 9075000902
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: national Pollutant Discharge
Elimination System (IIPDES) Discharge Monitoring Reports
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Effluents National
Pollutant Discharge Elimination System (NPDES) permittees
(ABS) Abstract/Overview of Data Base or Model: Manually maintained
file of discharge monitoring reports submitted by designated major
dischargers in Region VII.
(CTC) CONTACTS: Subject matter Ron McCutcheon (816)374-2281; EPA
Office Region VII, Mater Management Division (816)374-2281
(DTP) Type of data collection or monitoring: Point source data
collection National Pollutant Discharge Elimination System (NPDES)
permittees
(STA) Data Base status: Discontinued
(6RP) Groups of substances represented in Data Base: 11 conventional
water ;41 CMA potential criteria ;15 metals
(NPP) Kon-pollutant parameters included in the data base: Collection
method ;Concentration measures ;Flou rates ^Sampling date ;
Test/analysis method
(OS) Time period covered by data base: 01-01-74 TO 09-30-81
(TRM) Termination of data collection: Has Occurred 09-30-81
(FRQ) Frequency of data collection or sampling: daily ;weekly ;nonthly
;quarterly ;semi annually ;annually
(NOB) Number of observations in data base: 175000.(Estimated)
(REI) Estimated annual increase of observations in data base: 0.
(IMF) Data base includes: Raw data/observations ;Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 400.
(NCS) 80. stations or sources currently originating/contributing data:
0.
(NOF) Number of facilities covered in data base (source monitoring): 40
0.
(GEO) Geographic coverage of data base: Selected federal region Region
VII
(LOG) Data elements identifying location of station or source include:
State
(PAC) Data elements identifying facility include: Plant facility name
;NPDES
(CDE) Pollutant identification data are: encoded
(LIM) Limitation/variation in data of which user should be aware: Data
varies as to sampling frequency, pollutants covered, and sampling
technique depending on National Pollutant Discharge Elimination
System (NPDES) permit.
(DpR) Data collect./anal, procedures conform to ORD guidelines: Collect
ion method documented ^Analysis method documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(PRE) Precision: Precision and accuracy estimates are not available
(EDT) Edittlng: No known edit procedures exist.
(CBY) Data collected by: Self reporting
(ABY) Data analyzed by: Self reporting
(IDL) Laboratory identification: HO
1190
-------
Accession No. 9075000902 (cont)
(PRl) Primary purpose of data collection: Compliance or enforcement
(AOT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 402 (Clean Water Act-CMA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forns:
QQ
(REP) Form of available reports and outputs of data base: data
available to copy
(SOS) Number of regular users of data base: 1 office
(OSR) Current regular users of data base: EPA regional offices
(CNF) Confidentiality of data and limits on access: Ho limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original fora (hardcopy, readings)
(DAC) type of data access: Manually
(CHG) Direct charge for non-EPA use: No
(OPDT) Freguency of data base aaster file up-date: None
(RDBEPA) Related EPA data bases used in conjunction with this data base
Permit Compliance System (PCS)
(CMP) Completion of fora:
Donald Toensing
OFC: EPA/Region VII/Hater Management Division
AD: 324 E. llth St. Kansas City, Mo. 64106
PH: 816-374-2281
(DF) Date of form completion: 01-10-83
(NMAT) Number of substances represented in data base: 63
(NCAS) Number of CAS registry numbers in data base: 42
(MAT) Substances represented in data base:
2,4,5-trichlorophenoxypropio dissolved solids
nic acid (TP)<93-72-l> fecal coliform
2,4-d acidC94-75-7> fluorides
acetone<67-64-l> guthion<86-50-0>
acidity iron and compounds<7439-89-6>
alkalinity iron<7439-89-6>
aluwinum<7 429-90-5> kepone<143-50-0>
ammonia<7664-4l-7> lead<7439-92-l>
arsenic<7440-38-2> lithium and compounds<7439-93-2>
barium<7440-39-3> malathion<121-75-5>
beryllium<7440-41-7> manganese<7439-96-5>
biphenyl<92-52-4> mercury<7439-97-6>
bismuth compounds<7440-69-9> methoxychlor<72-43-5>
boron compounds<7440-42-8> methyl ethyl ketone (mek)<78-93-3>
broitine<7726-95-6> mirex<2385-85-5>
cadmium<7440-43-9> molybdenum and compounds
chlorine<7782-50-5> <7439-98-7>
chrcraium<7440-47-3> n-alkanes clO-c30
cobalt<7440-48-4> nickel<7440-02-0>
copper<7440-50-8> nitrates/nitrites
demeton<8065-48-3> nitriloacetates
dialkyl ethers nitrogen<7727-37-9>
dibenzofuran<132-64-9> oil and grease
diphenyl ether<101-84-8> oxygen demand
dissolved oxygen pH
1191
-------
Accession Ho. 9075000902 (cont)
parathion<56-38-2> styrene<100-42-5>
phosphorus and compounds sulfates
<7723-14-0> sulfides
phosphorus<7723-14-0> suspended solids
polybroainated biphenyls
seleniua<7782-49-2> uraniun<7440-61-l>
sodiua and coapounds<7440-23-5> vanadiu»<7440-62-2>
(CAS) CAS registry numbers of substances included in data base: 93*72*1
; 94-75-7; 67-64-1; 7429-90-5; 7664-41-7; 7440-38-2; 7440-39-3;
7440-41-7; 92-52-4; 7440-69-9; 7440-42-8; 7726-95-6;
7440-43-9; 7782-50-5; 7440-47-3; 7440-48-4; 7440-50-8;
8065-48-3; 132-64-9; 101-84-8; 86-50-0; 7439-89-6; 7439-89-6;
143-50-0; 7439-92-1; 7439-93-2; 121-75-5; 7439-96-5;
7439-97-6; 72-43-5; 78-93-3; 2385-85-5; 7439-98-7; 7440-02-0;
7727-37-9; 56-38-2; 7723-14-0; 7723-14-0; 7782-49-2; 7440-23-5;
100-42-5; 7440-32-6; 7440-61-1; 7440-62-2
(CNN) Contact na«e(s): McCutcheon/R.
(COR) Contact organization: Region VII/ Hater Management Division
(RQR) Responsible Organization: Region VII.Water Management Division.
1192
-------
Accession No. 9075000903
(DQ) Date of Quest!onaire: 12-02-82
(HAM) Name of Data Base of Model: Quarterly Excess Emission Reports
(ACR) Acronym of Data Base or Model: None
(NED) Media/Subject of Data Base or Model: Air ^Emissions stationary
source
(ABS) Abstract/Overview of Data Base or Model: Various categories of
new sources are subject to requirements of reporting and record
keeping (40 CFR
60.7) related to continuous emission monitoring
equipment measuring any one or a combination of nitrogen oxides,
opacity/ sulfur dioxide and particulates. Opacity is measured in
percent and the other emissions in Ibs/hr or gr/scf or fos/nmBTU.
(CTC) CONTACTS: Subject matter A.P. Wayne (816)374-2576 } EPA
Office A.P. Wayne (816)
(DTP) Type of data collection or monitoring: Point source data
collection New Source Performance Standards sources required to
have continuous emission monitors
(STA) Cata Base status: Operational/ongoing
(6RP) Groups of substances represented in Data Base: 7 criteria HAAQS
(NPP) Non-pollutant parameters included in the data base: Collection
method Concentration measures ;Flow rates ;Industry ; Production
levels ;Sampling date ;Treatment devices ;compliance data (all
excesses)
(DS) Time period covered by data base: 12-01-75 to 01-30-83 ongoing
(TPM) Termination of data collection: Mot anticipated
(FRQ) Frequency of data collection or sampling: quarterly
(NOB) Number of observations in data base: 8000.(Estimated)
(HEI) Fstiraated annual increase of observations in data base: 1800.
(INF) Data base includes: Raw data/observations ;Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 25.
(NCS) No. stations or sources currently originating/contributing data:
12,
(NOF) Number of facilities covered in data base (source monitoring): 2t
(GEO) Geographic coverage of data base: Selected federal region Region
VII
(LOG) Data elements identifying location of station or source include:
State ;County ;City ;Street address
(FAC) Data elements identifying facility Include: Plant facility name
;Plant location ;Street address
(CDE) Pollutant identification data are: Other coding scheme
Compliance Data System
(LIM) Limitation/variation in data of which user should be aware: Does
not provide information other than source emissions over allowable
limits
(DPR) Data collect./anal, procedures conform to ORD guidelines: ORD
Guidelines
(ABL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit Is satisfactory for 50%,
(PRE) precision: Precision and accuracy estimates exist but are not
included in data base
1193
-------
Accession Ho. 9075000903 (cent)
(EOT) Editting: Edit procedures used and documented*
(CBY) Data collected by: Self reporting ^Regional office Overvien
inspections by Environmental Services Division/ Region 711 ;EPA
headquarters Stationary Source Compliance Division ;Contractor
^State.
(ABY) Data analyzed by: Regional office Air & Haste Management
Division/
Region Vllf EPA headquarters Stationary Source Compliance
Division
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Continuous compliance or
enforcement
(AOT) Authorization for data collection: Statutory authorization is P
L 88-206 as amended/ Section 114 (40 CFR 60.7) (Clean Air Act-CAA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
No
(REP) Form of available reports and outputs of data base: Unpublished
reports Quarterly excess emission report
(NDS) Number of regular users of data base: 4 offices
(USR) Current regular users of data base: EPA headquarter offices
Stationary Source Compliance Division.! Stationary Source
Compliance Division contractors ;Reglon Til
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original form (hardcopy/ readings)
(OAC) Type of data access: Manually & Automated
(CHG) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: Quarterly
(ROBSPA) Related EPA data bases used in conjunction ulth this data base
Compliance Data System
(ODB) Other pertinent non-EPA data bases: Missouri excess emission
reporting; Nebraska excess emission reporting; Iowa excess emission
• reporting
(CMP) Completion of form:
A. P. Vayne
OFC: EPA/Region VII/Air £ Waste Management Division
AD: 324 E. llth St. Kansas City/ Mo.
PH: (816)374-2576
(DF) Date of form completion: 01-20-83
(ftMAT) Number of substances represented in data base: 5
(NCAS) Number of CAS registry numbers in data base: 2
(MAT) Substances represented in data base:
hydrocarbons sulfur dioxide<7446-09-5>
nitrogen dioxide<10102-44-0> total suspended participates
opacity
(CAS) CAS registry numbers of substances included in data base: 10102-4
4-0; 7446-09-5
(CHM) Contact name(s): Uayne/A.P.; Vayne/A.P.
(RQR) Responsible Organization: Region VII.Water Management Division.
1194
-------
Accession Ho. 9078000902
(DQ) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: Publicly Owned Treatment Works
(POTH) Quality Control
UCR) Acronym of Data Base or Model: lone
(MED) Media/Subject of Data Base or Model: Effluents Publicly Owned
Treatment Works
(ABS) Abstract/Overview of Data Base or Model: All quality control
data from EPA and contractor laboratories for the national
Publicly Owned Treatment Works (POTW) study* Data is not in any
computer-readable form.
(CTC) CONTACTS: Subject matter Billy Fairless (816)374-4461 9
EPA Office Region VII
(DTP) Type of data collection or monitoring: Point source data
collection Publicly Owned Treatment Works
(STA) Data Base status: Operational/ongoing*
(GRP) Groups of substances represented in Data Base: 129 307 CWA ;15
metals
(HPP) Non-pollutant parameters included in the data base: Chemical
data Collection method >Compliance data >Concentration measures ;
Discharge points /Disposal ;Flow rates geographic subdivision >
inspection data ;Location ^Physical data iSalinity ;Sampling date }
Site description ;Temperature >Test/analysis method
(OS) Time period covered by data base: 08-01-78 TO 09-30-80
(TRM) Termination of data collection: Anticipated 12/30/80
(FRQ) Frequency of data collection or sampling: one time only
(NOB) Number of observations in data base: 180000.(Estimated)
(NED Estimated annual increase of observations in data base: 18000*
(IRF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 200,
(NCS) No. stations or sources currently originating/contributing data:
(HOP)* number of facilities covered in data base (source monitoring): 40
(GEO) Geographic coverage of data base: National
(LOO Data elements identifying location of station or source include:
State ;County ;SMSA ;City >Town/township ;Street address
Coordinates Latitude a Project identifier
(FAC) Data elements Identifying facility Include: Plant facility name
jPlant location ;Street address ;SIC code > SCC ;NPDES
(CDS) pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Hone
(DPR) Data collect./anal. procedures conform to ORD guidelines: ORD
Guidelines ;Sampling plan documented ;Collection method documented
; Analysis method documented ;QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(A00) Lab Audit: Lab audit is satisfactory.
(PRE) Precision: Precision and accuracy estimates exist for all
measurements
(EOT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Contractor lab various ^Contractor Burns and
(ABY) Data analyzed by: Regional office Surveillance and Analysis
1195
-------
Accession No. 9078000902 (cont)
Division, Region VII
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Development of regulations
or standards
(AUT) Authorization for data collection: No statutory requirement:
Data collection requirement is to collect data on toxic
pollutants in municipal sewer systems and their removal by
Publicly Owned Treatment Works to complement data on industrial
toxic discharges collected to develop criteria in conformance with
the consent decree.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
SSKJ Forf of availabl« reports and outputs of data base: raw lab data
(NUS) Number of regular users of data base: 100 or less
(OSR) Current regular users of data base: EPA headquarter offices
Office of Hater Regulations and Standards
EPA regional offices
EPA laboratories
Other federal agencies
States
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
COST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHC) Direct charge for non-EPA use: yes
(OPDT) Frequency of data base master file up-date: other as
received-weekly
JSnSL.?61^^ EPA auto"at«d systems which use data base: STORET, TOXET
fKDBEPA) Related EPA data bases used in conjunction with this data base
STORET (Storage and Retrieval of Mater Quality Data), PQTH
Analytical Data D5302000102
(ODB) other pertinent non-EPA data bases: the state of Missouri has
not used STORET for several years-considerable environmental
data is involved.
(CMP) Completion of form:
Billy Fairless
OFC: EPA/Region VII/Surveillance and Analysis Division
AD: 25 Funston Rd. Kansas City, KS 66115
PH: (816)374-4461
(DP) Date of form completion: 01-31-83
(NMAT) Number of substances represented in data base: 149
(IfCAS) Number of CAS registry numbers in data base: 134
(NAT) Substances represented in data base:
l,l,l-trichloroethane<71-55- l,2-dichlorobenzene<95-50-l>
, ,6> l,2-dichloroethane<107-06-2>
1,1,2,2,-tetracnloroethane l*2-dichloropropane<78-87-5>
, , l,2-dichloropropylene<563-54-2>
l,l,2-trichloroethane<79-00-5> l,2-diphenylhydrazine<122-66-7>
l,l-dichloroethane<75-34-3> 1,2-trans-dichloroethylene
lsl-dichloroethylene<75-35-4> <156-60-5>
l/2,4,-trichlorobenzene<120-82-l> l,3-dichlorobenzene<541-73-l>
1196
-------
Accession No. 9078000902
(cont)
1, 4-dichlorobenzene<106-46-7>
2,4,6-trichlorophenol<88-06-2>
2, 4,1, 8- te tr achlor odibenzo-p-
oioxin (tcdd)
2, 4-dichiorophenol<120-83-2>
2, 4-dimethylphenol<105-67-9>
2,4-dinitrophenol<51-28-5>
2,4-dinitrotoluene<121-14-2>
2,6-dinitrotoluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chloronaphthalene<91-58-7>
2-chlorophenol<95-57-8>
2-n itr opheno 1< 88-75-5>
3,3'-dichlorobenzidine<91-94-l>
3,4-benzofluoranthene<205-99-2>
4,4'-ddd(p,p-tde)
4,4*-dde(p,p*-ddx)<72-55-9>
4,4'-ddt<50-29-3>
4^6-dinitro-o-crcsol<534-52-l>
4-bronophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
acenaphthene< 83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrln<309-00-2>
alu«inuM<7429-90-5>
a»monla<7664-41-7>
anthracene
anti»ony<7440-36-0>
arsenic<7440-38-2>
asbestos<1332-21-4>
bariu«<7440-39-3>
benzene<71-43-2>
benzidlne<92-87-5>
benzo(a)anthracene<56-55-3>
benzo(a)pyrene<50-32-8>
benzo(g,bv i)perylene<191-24-2>
benzoC k) f luo ranthene<207-08-9>
beryll ium<7440-41-7>
bhc
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<31 9-86-8>
biological oxygen demand (BOD)
bls(2-chloroethoxy)»ethane
bis( 2-chloroethyl) ether
bis(2-chloroisopropyl)ether
<39638-32-9>
bis(2-ethylhexyl)phthalate
bis(chloro«ethyl)ether<542-88-l>
broao»ethane<74-83-9>
butyl benzyl phthalate<8S-68-7>
cad«lu«<7440-43-9>
calcium
carbon tetrachloride<56-23-5>
cheaical oxygen demand (COD)
chlordane<57-74-9>
chlorobenzene<108-90-7>
chlorodibroaonethane<124-48-l>
chloroethane<75-00-3>
chlorofor»<67-66-3>
chloroaethane<74-87-3>
chro«iuM<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
di-n-butyi phthalate<84-74-2>
di-n-octyl phthalate<117-84-0>
dibenzo(a/h)anthracen«<53-70-3>
dichlorobro«o»ethane<75-27-4>
dichlorodifluoro»ethane<75-71-8>
dichloro«ethane<75-09-2>
dieldrin<60-57-l>
diethyl phthalate<84-66-2>
dimethyl phthalate<131-ll-3>
dissolved solids
endosulfan sulfate<1031-07-8>
endosulfan-alpha<959-98-8>
endosulfan-beta<33213-65-9>
endrin aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fluorantbene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
hep tachlor<76-44-8>
hexachlorobenzene<118-74-l>
hexachlorobutadieae<87-68-3>
hexachlorocyclopentadiene<77-47-4>
hexachloroethane<67-72-l>
indeno (l,2,3-cd)pyrene<193-39-5>
iron<7439-89-6>
isophorone<78-59-l>
lead<7439-92-l>
magnesium
manganese<7439-96-5>
mercury<7439-97-6>
1197
-------
Accession No. 9078000902 (cont)
n-nitrosodi-n-propylanine pentachlorophenol<87-86-5>
<621-64-7> phenanthrene<85-Ol-8>
n-nitrosodinethylanine<62-75-9> phenol<108-95-2>
n-nitrosodiphenylanine<86-30-6> pyrene<129-00-0>
naphthalene<91-20-3> seleniua<7782-49-2>
nickel<7440-02-0> silver<7440-22-4>
nltrobenzen€<98-95-3> sodiun<7440-23-5>
nitrogen<7727-37-9> suspended solids
oil and grease tetrachloroethylene<127-18-4>
p-cbloro-«-cresol<59-50-7> thalliun<7440-28-0>
pcb-1016 (arochlor 1016) toluene<108-88-3>
<12674-ll-2> total organic carbon (TOO
pcb-1221 (arochlor 1221) total phenol
<11104-28-2> total solids
pcb-1232 (arochlor 1232) total volatile dissolved solids
<11141-16-5> total volatile solids
pcb-1242 (arochlor 1242) total volatile suspended solids
<53469-21-9> toxaphene<8001-35-2>
pcb-1248 (arochlor 1248) tribroaonethane<75-25-2>
<12672-29-6> trichloroethylene<79-Ol-6>
pcb-1254 (arochlor 1254) trichlorofluoronethane<75-69-4>
<11097-69-l> vinyl chloride<75-01-4>
pcb-1260 (arochlor 1260) zinc<7440-66-6>
<11096-82-5>
(CIS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-5; 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 7429-90-5; 7664-41-7;
120-12-7; 7440-36-0; 7440-38-2; 1332-21-4; 7440-39-3; 71-43-2;
92-87-5; 56-55-3; 50-32-8; 191-24-2; 207-08-9; 7440-41-7; 58-89-9;
319-84-6; 319-85-7; 319-86-8; 111-91-1; 111-44-4; 39638-32-9;
117-81-7; 542-88-1; 74-83-9; 85-68-7; 7440-43-9; 56-23-5; 57-74-9;
108-90-7; 124-48-1; 75-00-3; 67-66-3; 74-87-3; 7440-47-3; 218-01-9;
7440-50-8; 57-12-5; 84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8;
75-09-2; 60-57-1; 84-66-2; 131-11-3; 1031-07-8; 959-98-8;
33213-65-9; 7421-93-4; 72-20-8; 100-41-4; 206-44-0; 86-73-7;
1024-57-3; 76-44-8; 118-74-1; 87-68-3; 77-47-4; 67-72-1;
193-39-5; 7439-89-6; 78-59-1; 7439-92-1; 7439-96-5; 7439-97-6;
621-64-7; 62-75-9; 86-30-6; 91-20-3; 7440-02-0; 98-95-3;
7727-37-9; 59-50-7; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 87-86-5;
85-01-8; 108-95-2; 129-00-0; 7782-49-2; 7440-22-4; 7440-23-5;
127-18-4; 7440-28-0; 108-88-3; 8001-35-2; 75-25-2; 79-01-6;
75-69-4; 75-01-4; 7440-66-6
(CNM) Contact naae(s): Fairless,B. ; ?II,R.
(ROR) Responsible Organization: Region ¥11.Environmental Services
Division*
1198
-------
Accession No. 9085000901
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: TRACK
-------
Accession No. 9085000901 (cent)
(AUT) Authorization for data collection: Ho statutory requirement:
Data collection requirement is administrative tracking of
perBits development predated development of Permit compliance
System.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0073
beryllium, total
cadmium<7440-43-9> beta, total
copper<7440-50-8> bod/ 5-day
dissolved oxygen boron, total
dissolved solids calcium, total
fecal collform carbon, total organic
lead<7439-92-1> chem. oxygen demand
mercury<7439-97-6> chloride
nitrogen<7727-37-9> chlorine, total
oil and grease chlorine/ free
oxygen demand chromium cr, diss
pH chromium/ hex-val
phosphor us <7 72 3-14-0 > chromium, total
suspended solids cobalt, total
zinc<7440-66-6> acidity, total conform, fecal
alkalinity, total colifora, total
aluminum, dissolved color (pt-co units)
aluminum, total copper, total
arsenic, total cyanide
1200
-------
Accession No
9085000901
(cont)
cyanide, free
sid alpha emit radium isotopes
flouride/ total
flow in conduit
floH rate
flow, stream
gold, total
hardness/ total
inflnt susp solids total
influent bod
iron/ dissolved
iron, total
lead, dissolved
lead, total
magnesium/ total
maganese, total
mercury, total
methylene blue act.subst
molybdenum, total
nickel ni, diss
nickel, total
nitrate
nitrate nitrogen
nitrite
nitrite + nitrate
total
influent
ammonia tl
ammonia, unionized
amm/ total
nitrogen, kjeldahl, total oil
grease, visual
oil-grease-total
oxygen, dissolved
nitrogen,
nitrogen,
nitrogen/
nitrogen,
nitrogen,
phenols
phosphate/ total
phosphorus, total
radium 226, diss
radium 226/ total
residue, total fixed
selenium, dissolved
selenium, total
silver, dissolved
silver/ total
sodium/ total
solids/ dissolved
solids, settleable
solids, suspended
solids/ total diss
solids, total susp
solids, total volatile
solids, dissolved
specif/ conductance
sulfate
sulfide
sulfide, dissolved
sulfide, diss
temperature, water
temperature/ stream
tin, total
turbidity
turbidity
uranium 238, total
uranium/ nat total
uranium, total
uranium, nat diss
vanadium/ total
zinc, total
PH, field
(CAS) CAS registry numbers of substances included in data base: 7440-38
-2; 7440-43-9; 7440-50-8; 7439-92-1; 7439-97-6; 7727-37-9;
7723-14-0; 7440-66-6
(CNM) Contact name(s): Afshar/P. ; Morster/C.; Burm/R.J.
(RDF.) Responsible Organization: Region VIII.Hater Management Division*
1201
-------
Accession No. 9085000902
(D
Location >Sampling date ;Temp«rature >?olume/mass measures
(DS) Time period covered by data base: 01-01-72 TO 12-31-82
(TRM) Termination of data collection: Hot anticipated
(FRQ) Frequency of data collection or sampling: weekly ^monthly
quarterly ;s«mi annually ;annually
(HOB) Humber of observations in data base: 30000-40000.(Estimated)
(MED Estimated annual increase of observations in data base: 5000.
(IMF) Data base includes: Summary aggregate observations
(MTS) Total nu.ber of stations or sources covered in data base. 5000.
(BCS) Ho. stations or sources currently originating/contributing data.
(HOT) number of facilities covered in data base (source monitoring): 30
(GEO) "Geographic coverage of data base: Selected federal region Region
(LOC^Data elements identifying location of station or source include:
State jCity s Town/town ship ^Street address
(FAC) Data elements identifying facility include: Plant facility name
;PIant location ;Street address >SIC code J HPDES
(CDE) Pollutant identification data are: Oncoded
(LIN) Limitation/variation in data of which «s«r *5ould *»« aMa5€; *!>??„
(DPR) Data collect./anal. procedures conform to ORD guidelines: Samplin
g plan documented >Collection method documented
(AM.) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Data not based on lab analysis.
(PRE) Precision: Precision and accuracy estimates are not available
(EDT) Editting: Ho known edit procedures exist.
(CBY) Data collected by: Self reporting .«,,««4« *«r
(ABY) Data analyzed by: State agency State labs do the Analysis for
permittees TTT
Regional office Enforcement Division/ Region fin
(IDL) Laboratory identification: MO ..„.„„»
(PR1) Primary purpose of data collection: Compliance or enforcement
-------
Accession No. 9085000902 (cont)
(PR2) Secondary purpose of data collection: Program evaluation
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 308 (Clean Water Act-CWA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
3320-01
(REP) Form of available reports and outputs of data base: Unpublished
reports internal reports, violation reports
(NOS) Number of regular users of data base: 75
(USR) Current regular users of data base: States
Region VIII
(CNF) Confidentiality of data and Units on access: No Units on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Fora of data storage: Original fora (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: yes
(CMP) Completion of form:
Theresa Matassoni
OFC: EPA/Region VIII/Enforcement Division
AD: 1860 Lincoln St. Denver, CO 80295
PH: (303) 837-5094
(DP) Date of form completion: 01-06-83
(NMAT) Number of substances represented in data base: 17
(NCAS) Number of CAS registry numbers in data base: 8
(NAT) Substances represented in data base:
acidity calcium, total
alkalinity carbon, total organic
arsenic<7440-38-2> chem. oxygen demand
cadmium<7440-43-9> chloride
copper<7440-50-8> chlorine, total
dissolved oxygen chlorine, free
dissolved solids chromium cr, diss
fecal coliform chromium, hex-val
lead<7439-92-l> chromium, total
mercury<7439-97-6> cobalt, total
nitrogen<7727-37-9> coliform, fecal
oil and grease coliform, total
oxygen demand color (pt-co units)
ph copper, total
phosphorus<7723-14-0> cyanide
suspended solids cyanide, free
zinc<7440-66-6> acidity, total sid alpha emit radium isotopes
alkalinity, total flouride, total
aluminum, dissolved flow in conduit
aluminum, total flow rate
arsenic, total flow, stream
barium, dissolved gold, total
barium total hardness, total
beryllium, total inflnt susp solids total
beta, total influent bod
bod, 5-day iron, dissolved
boron, total iron, total
1203
-------
Accession No. 9085000902
(cont)
lead, dissolved
lead, total
•agnesiun/ total
•aganese? total
mercury, total
methylene blue act.subst
molybdenum, total
nickel ni,diss
nickel, total
nitrate
nitrate nitrogen
nitrite
nitrite + nitrate
nitrogen, total
nitrogen, influent
nitrogen, ammonia tl
nitrogen, ammonia/ unionized
nitrogen, ama, total
nitrogen, kjeldahl, total oil &
grease, visual
oil-grease-total
oxygen, dissolved
pH, field
phenols
phosphate, total
phosphorus, total
radium 226, diss
radlua 226, total
selenium, dissolved
selenium, total
silver, dissolved
silver/ total
sodiui/ total
solids/ dissolved
solids, settleable
solids, suspended
solids/ total diss
solids/ total susp
solids/ total volatile
solids/ dissolved
specif/ conductance
sulfate
sulfide
sulfide, dissolved
sulfide/ diss
temperature/ water
temperature, stream
tin, total
turbidity
turbidity
uranium 238, total
uranium/ nat total
uranium/ total
uranium/ nat diss
vanadium/ total
zinc, total
residue/ total fixed
(CAS) CAS registry numbers of substances included in data base: 7440-38
-2; 7440-43-9; 7440-50-8; 7439-92-1; 7439-97-6; 7727-37-9;
7723-14-0; 7440-66-6
(CMM) Contact naae(s): Skie/D.N. ; Skie/D.M.
(ROR) Responsible Organization: Region fill.Hater Management Division.
1204
-------
Accession No. 9095000902
(DQ) Date of Questionaire: 12-02-82
(RAM) Name of Data Base of Model: Discharge Monitoring Report
(ACR) Acronym of Data Base or Model: DMR
(NED) Kedia/Subject of Data Base or Model: Effluents discharge fro»
point sources to D.S. waters.
(ABS) Abstract/over view of Data Base or Model: Data base contains
measurements of pollutant parameters specified by the National
Pollutant Discharge Elimination System (ffPDES).
(CTC) CONTACTS: Subject Batter Steve Fuller (415)974-8306 ;
Computer-related Carey Houk (415)974-8271> EPA Office Hater
Management Division (415)974-8306
(DTP) Type of data collection or monitoring: Point source data
collection Municipal and industrial
(STA) Data Base status: Operational/ongoing
(GRP) Croups of substances represented In Data Base: 11 conventional
water ;15 aetals
(HPP) Non-pollutant parameters Included In the data base: Collection
•ethod Concentration measures ;Discharge points > Flow rates
;Location ^Precipitation ;Sampling date ^Temperature
(OS) Tine period covered by data base: 02-01-75 TO present
(TRM) Termination of data collection: Rot anticipated
(PRQ) Frequency of data collection or sampling: less than hourly
continuous sampling (e.g. flow) ;hourly ;dally > weekly >monthly
;quarterly >seni annually ^annually >as needed
(MOB) Kumber of observations In data base: 420000.(Estimated)
(BED Estimated annual increase of observations in data base: 70000.
(IKF) Data base includes: Summary aggregate observations
(ITS) Total number of stations or sources covered In data base: 2100.
(MCS) No. stations or sources currently originating/contributing data:
2100.
(•OF) Number of facilities covered In data base (source monitoring): 21
00.
(GEO) Geographic coverage of data base: Selected federal region Region
IX
(LOC) Data elements identifying location of station or source include:
State /City jTown/township ;Street address ;Coordinates Latitude
and longitude
(FAC) Data elements identifying facility Include: Plant facility name
;Street address ;SIC code ;NPDES
(CDE) Pollutant identification data are: Oncoded
(LIM) Limitation/variation in data of which user should be aware: Sampl
ing periods and measurement parameters vary for each discharger.
Some parameters may be permitted zero discharge during certain
periods.
(DPR) Pata collect./anal, procedures conform to ORD guidelines: Samplln
g plan documented ^Collection method documented ^Analysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory for majors discharges
only-high(%).
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
1205
-------
Accession Ho. 9095000902 (cont)
(EDT) Editting: Edit procedures used and documented.
(CBY) Data collected by: Self reporting
(ABY) Data analyzed by: Self reporting
State agency California Regional Board, Nevada Department of
Environmental Protection, Arizona Department of Health Services/
Hauaii Department of Health Services, Guaa EPA, Trust
Territories board, etc*
Water Management Division
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Compliance or enforcement
(AUT) Authorization for data collection: Statutory authorization is P
L 95-217, Section 308 (Clean Mater Act of 1977-CWA)
alkalinity mercury<7439-97-6>
arsenic<7440-38-2> nickel<7440-02-0>
cadmium<7440-43-9> nitrogen<7727-37-9>
chromium<7440-47-3> oil and grease
copper<7440-50-8> oxygen demand
dissolved oxygen ph
dissolved solids phosphorus<7723-14-0>
fecal coliform selenium<7782-49-2>
iron<7439-89-6> settleable solids
lead<7439-92-l> suspended solids
1206
-------
Accession No. 9095000902 (cont)
titaniu»<7440-32-6> total coliform
(CAS) CAS registry nunbers of substances included in data base: 7440-38
-2; 7440-43-9; 7440-47-3; 7440-50-8; 7439-89-6; 7439-92-1;
7439-96-5; 7439-97-6; 7440-02-0; 7727-37-9; 7723-14-0;
7782-49-2; 7440-32-6
[CNH) Contact natnc(s): Pasek,J. ; Houk,C.
(COR) Contact organization: Hater Management Division
(ROR) Responsible Organization: Region IX.Hater Managenent Division.
1207
-------
Accession Mo. 9096000001
(DQ) Date of QuesUonaire: 12-02-82
CMAN) Mane of Data Base of Model: Baseline Survey of Public Hater
Supplies on Indian Lands
(ACR) Acronym of Data Base or Model: Mone
(MED) Media/Subject of Data Base or Model: Drinking uater
CABS) Abstract/overview of Data Base or Model: Hater Quality Files for
Public Mater Supplies on Indian Lands in EPA Region IX contains
results of analysis performed for the 21 contaminants covered
by drinking water regulations. There is a regional computer
system (Safe Vater Information Module-SHIM) which tracks type of
analyses performed i.e. inorganic, organic/ radionuclide,
bacteriological. SHIM is an ad»inistrative data base which does
not contain environmental data „.»,..-
CCTC) CONTACTS: Subject matter Tom Berkins 1415)794-8212 ;
Computer-related Steven Gross (415)974-8107 ; EPA Office William
M. Thurston {415)974-8226
CDTP) Type of data collection or Monitoring: A»bient data collection
CSTA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 21 drinking water
standards
CMPP) Non-pollutant parameters included in the data base: Biological
data ;Chemical data ^Collection method ^Location ; Sampling
date ;Site description jTest/analysis-method Bact.l ; Sadler
City ;Town/township jPro^ect identifier ; system name
CFAC) Data elements identifying facility include: Plant facility name
;Plant location ;Program Identifier
(CDE) Pollutant identification data are: Oncoded
CLIM) Limitation/variation in data of which user should be aware: None
CDPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented jCollection method documented ^Analysis method
(AUL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Lab audit is satisfactory for 83%, excluding
radiochemistry.
1208
-------
Accession No. 9096000001 (cont)
(PR£) Precision: Precision and accuracy estimates exist but are not
included in data base Edit data base is edited/ procedure is not
fully documented.
(CBY) Data collected by: Regional office Region IX ;0ther federal
agency Bureau of Indian Affairs and Ind Health Service ;Tribal
Organizations
(ABY) Data analyzed by: Regional office Region IX
Other federal agency Bureau of Indian Affairs and Indian Health
Service
Tribal Organizations
(IDL) Laboratory identification: YES
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Program evaluation
(AUT) Authorization for data collection: Statutory authorization is P
L 93-523 as amended, SDMA-Safe Drinking Mater Act
(OMB) Data collected/submitted using OMB-approved EPA reporting fonts:
QQ
(REP) Form of available reports and outputs of data base: hand written
summaries for each system
(NUS) Number of regular users of data base: 4 offices
(USR) Current regular users of data base: Region IX
Bureau of Indian Affairs
Tribal Organizations
Indian Health Services
Private water suppliers
{CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Original form (hardcopy, readings)
(DAC) Type of data access: Manually
(CHG) Direct charge for non-EPA use: no
(UPDT) Frequency of data base master file up-date: Other On-going
(RDBEPA) Related EPA data bases used in conjunction with this data base
Safe Hater Information Module (SWIM)
(CMP) Completion of form:
Steven Gross
OFC: EPA/Region IX/tfater Division
AD: 215 Fremont St. San Francisco, CA 94105
PH: (415)974-8107
(DF) Date of form completion: 12-09-82
(NMAT) Number of substances represented in data base: 22
(NCAS) Number of CAS registry numbers in data base: 17
(MAT) Substances represented in data base:
2,4-dichlorophenoxyacetic llndane<58-89-9>
acid (2,4-d)<94-75-7> manmade beta
arsenic<7440-38-2> mercury<7439-97-6>
barium<7440-39-3> methoxychlor<72-43-5>
cadmium<7440-43-9> microbiology coliform bacteria
chromiu«<7440-47-3> nitrate<14797~55-8>
endrin<72-20-8> photon emitters
gross alpha radium 226<13982-63-3>
lead<7439-92-l> radium 228<15262-20-1>
1209
-------
Accession No. 9096000001 (cont)
selenii»<7782-49-2> toxaphene<8001-35-2>
silver<7440-22-4> turbidity
sil*ex<93-72-l> __
(CAS) CKS registry nunbers of substances included in data base: 94-75-7
; 7440-38-2; 7440-39-3; 7440-43-9; 7440-47-3; 72-20-8;
7439-92-1; 58-89-9; 7439-97-6; 72-43-5; 14797-55-8;
13982-63-3; 15262-20-1; 7782-49-2; 7440-22-4; 93-72-1; 8001-35-2
(CRN) Contact na»e(s): Gross/S.R. ; Grosses.R.
(COR) Contact organization: Hillia* M. Thurston
(ROR) Responsible Organizations Region IX.Hater Management Division.
1210
-------
Accession No. 9098000901
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Toxics Monitoring
(ACR) Acronym of Data Base or Model: None
0ther
One time only at each site
(NOB) Number of observations in data base: 50,000.(Estimated)
(HEI) Estimated annual increase of observations in data base: 10000.
(INF) Data base includes: Raw data/observations
(NTS) Total number of stations or sources covered in data base: 150.
(NCS) No. stations or sources currently originating/contributing data:
35.
(NOF) Number of facilities covered in data base (source monitoring): 0
(CEO) Geographic coverage of data base: Selected federal region Region
(LOC) Data elements Identifying location of station or source include:
State jCounty Coordinates latitude and longitude
(FAC) Data elements identifying facility include: Plant facility name
;PIant location
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of nhich user should be anare: None
(DPR) Data collect./anal, procedures conform to ORD guidelines: Collect
ion method documented ^Analysis method documented ;
-------
Accession No. 9098000901 (cont)
(PRl) Primary purpose of data collection: Risk assessment
(PR2) Secondary purpose of data collection: Special study
(AUT) Authorization for data collection: Statutory authorization is P
L 92-500 as amended. Section 307 (Clean Hater Act)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) Form of available reports and outputs of data base: Printouts on
reguest
Machine-readable raw data
On-line computer
(NOS) Number of regular users of data base: unknown-through STORE?
only
(OSR) Current regular users of data base: EPA headquarter offices
Monitoring and Data Support Division/ OHWM
Other federal agencies
States
all users cannot be identified
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: NCC/IBM
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: EPA software STORET MIDS:5303000101 ;EPA
hardware IBM 370
(CHG) Direct charge for non-EPA use: yes/ but may be waived
(OPDT) Freguency of data base master file up-date: Weekly
(RSS) Related EPA automated systems which use data base: STORET-graphic
, analytic
(ODB) Other pertinent non-EPA data bases:
conducted by AZ, CA/ HI/ HV; (2)Special Studies by 208 agencies;
(3)Non-BWMP fixed station; (4)Monitoring programs operated by
AZ/ CA, GO, HI, MIT/ U.S. Forest Service, U.S. Water and Power
Resources Service/ Corps of Engineers/ Geological Survey/ Soil
Conservation.
(CMP) Completion of form:
William E. Lewis
updated by David R. Minard/ EPA Region 9/ Hater Management
Division (415) 974-8284 OFC: EPA/Region IX/Surveillance and
Analysis Division
AD: 215 Fremont St. San Francisco, CA 94105
PH: (415)556-7550
(DF) Date of form completion: 02-15-83
(•MAT) Number of substances represented in data base: 127
(NCAS) Number of CAS registry numbers in data base: 126
(MAT) Substances represented in data base:
l/l,l-trichloroethane<71-55- l/2-dichlorobenzene<95-50-l>
6> l/2-dichloroethane<107-06-2>
1,1,2/2,-tetrachloroethane l,2-dichloropropane<78-87-5>
<79-34-5> l,2-dichloropropylene<563-54-2>
l,l,2-trichloroethane<79-00-5> l,2-diphenylhydrazine<122-66-7>
l,l-dlchloroethane<75-34-3> 1,2-trans-dtchloroethylene
l,l-dichloroethylene<75-35-4> <156-60-5>
l/2/4/-trichlorobenzene<120-82-l> l,3-dichlorobenzene<541-73-l>
1212
-------
Accession Ho. 9098000 901
(cont)
If 4-dichlorobenzene<106-46-7>
2/4,6-trichlorophenol<88-06-2>
2, 4-dichlorophenol
2, 4-dlaethylphenol<105-67-9>
2, 4-dinitrophenol<51-28-5>
2, 4-dinitrotoluene<121-14-2>
2f 6-dini trot oluene<606-20-2>
2-chloroethylvinyl ether<110-75-8>
2-chlor onaphthalene< 91-58- 7>
2- chlorophen ol< 95-57- 8>
2-nitrophenol<88-75-5>
3,3'-dichlorobenzidine<91-94-l>
3,4-benzof luoranthene<205-99-2>
4,4'-ddd(p,p*tde)
4,4--dde(p,p'-ddx)<72-55-9>
4,4'-ddt<50-29-3>
4, 6-dinitro-o-cresol<534-52-l>
4-bronophenyl phenyl ether
<101-55-3>
4-chlorophenyl phenyl ether
<7005-72-3>
4-nitrophenol<100-02-7>
aceraphthene<83-32-9>
acenaphthylene<208-96-8>
acrolein<107-02-8>
acrylonitrile<107-13-l>
aldrln<309-00-2>
anthracene<120-12-7>
antimony<7440-36-0>
arsenic<7440-38-2>
be«2ene<71-43-2>
benzldine<92-87-5>
benzo( a) an thracene<56- 55-3>
benzo(a)pyrene<50-32-8>
benzo(g,h,i)perylene<191-24-2>
benzo(lc)fluoranthene< 207-0 8-9>
beryllium<7440-4l-7>
bhc (lindane)-ga«raa<58-89-9>
bhc-alpha<319-84-6>
bhc-beta<319-85-7>
bhc-delta<319-86-8>
bis(2-chloroethoxy)Me thane
bls(2-chloroethyl)ether
bis(2-chloroisopropyl) ether
<39638-32-9>
bis<2-ethylhexyl)phthalate
bis(chloromethyl)ether<542-88-l>
bro»oaiethane<74-83-9>
butyl benzyl phthalate<85-68-7>
cadiluiK 7440-43- 9>
carbon tetrachloride<56-23-5>
chlordane<57-7 4-9>
chlorobenzene<108-90-7>
chlorodibroBonethane<124-48-l>
chloroethane<75-00-3>
chloroform<67-66-3>
chloro«ethane<74-87-3>
chroniun<7440-47-3>
chrysene<218-01-9>
copper<7440-50-8>
cyanide<57-12-5>
dl-n-butyl phthalate<84-74-2>
dl-n-octyl phthalate<117-84-0>
dibenzo(a/h)anthracene<53-70-3>
dichlorobro«o»ethane<75-27-4>
dlchlorodlfluoronethane<75-71-8>
dichloro«ethane<75-09-2>
dleldrln<60-57-l>
diethyl phthalate<84-66-2>
dlaethyl phthalate<131-ll-3>
endosulfan sulfate<1031-07-8>
endosulf an-alpha< 95 9-98-8>
endosulfan-beta<332!3-65-9>
endrln aldehyde<7421-93-4>
endrin<72-20-8>
ethylbenzene<100-41-4>
fluoranthene<206-44-0>
fluorene<86-73-7>
heptachlor epoxide<1024-57-3>
heptachlor<76-44-8>
hexachlorobenzene<118-74-l>
hex achlorobutadiene<87-68-3>
hexachlorocyclopentadlene<77-47-4>
hexachloroethane<67-72-l>
indeno (1,2/3-cd)pyrene<193-39-5>
isophorone<78-59-l>
lead<7439-92-l>
»ercury<7439-97-6>
n-nltrosodi-n-propylamine
<621-64-7>
n-nitrosodi«ethyla«ine<62-75-9>
n-nitrosodiphenyla>ine<86-30-6>
naphthalene<91-20-3>
nlckel<7440-02-0>
nltrobenzene<98-95-3>
p-chloro-«-cresol<59-50-7>
pcb-1016 (arochlor 1016)
<12674-ll-2>
pcb-1221 (arochlor 1221)
<11104-28-2>
pcb-1232 (arochlor 1232)
1213
-------
Accession No. 9098000901 (cent)
pcb-1242 (arochlor 1242) seleniu»<7782-49-2>
<53469-21-9> silver<7440-22-4>
pcb-1248 {arochlor 1248} tetrachloroethylene<127-18-4>
<12672-29-6> thalliua<7440-28-0>
pcb-1254 (arochlor 1254) toluene<108-88-3>
<11097-69-l> toxaphene<8001-35-2>
pcb-1260 (arochlor 1260) tribronoBethane<75-25-2>
<11096-82-5> trichloroethylene<79-01-6>
pentachlorophenol<87-86-5> trichlorofluoromethane<75-69-4>
phenanthrene<85-01-8> vinyl chloride<75-01-4>
phenol<108-95-2> zinc<7440-66-6>
pyrene<129-00-0>
(CAS) CAS registry numbers of substances included in data base: 71-55-6
; 79-34-51 79-00-5; 75-34-3; 75-35-4; 120-82-1; 95-50-1;
107-06-2; 78-87-5; 563-54-2; 122-66-7; 156-60-5; 541-73-1;
106-46-7; 88-06-2; 120-83-2; 105-67-9; 51-28-5; 121-14-2;
606-20-2; 110-75-8; 91-58-7; 95-57-8; 88-75-5; 91-94-1; 205-99-2;
72-55-9; 50-29-3; 534-52-1; 101-55-3; 7005-72-3; 100-02-7; 83-32-9;
208-96-8; 107-02-8; 107-13-1; 309-00-2; 120-12-7; 7440-36-0;
7440-38-2; 71-43-2; 92-87-5; 56-55-3; 50-32-8; 191-24-2; 207-08-9;
7440-41-7; 58-89-9; 319-84-6; 319-85-7; 319-86-8; 111-91-1;
111-44-4; 39638-32-9; 117-81-7; 542-88-1; 74-83-9; 85-68-7;
7440-43-9; 56-23-5; 57-74-9; 108-90-7; 124-48-1; 75-00-3;
67-66-3; 74-87-3; 7440-47-3; 218-01-9; 7440-50-8; 57-12-5;
84-74-2; 117-84-0; 53-70-3; 75-27-4; 75-71-8; 75-09-2; 60-57-1;
84-66-2; 131-11-3; 1031-07-8; 959-98-8; 33213-65-9; 7421-93-4;
72-20-8; 100-41-4; 206-44-0; 86-73-7; 1024-57-3; 76-44-8;
118-74-1; 87-68-3; 77-47-4; 67-72-1; 193-39-5; 78-59-1;
7439-92-1; 7439-97-6; 621-64-7; 62-75-9; 86-30-6; 91-20-3;
7440-02-0; 98-95-3; 59-50-7; 12674-11-2; 11104-28-2; 11141-16-5;
53469-21-9; 12672-29-6; 11097-69-1; 11096-82-5; 87-86-5; 85-01-8;
108-95-2; 129-00-0; 7782-49-2; 7440-22-4; 127-18-4; 7440-28-0;
108-88-3; 8001-35-2; 75-25-2; 79-01-6; 75-69-4; 75-01-4; 7440-66-6
(CNM) Contact name(s): Minard,D»E.; ffilson,E.; Minard,D.E.
(ROR) Responsible Organization: Region IX.Toxics and Haste Management
Division.
1214
-------
Accession No. 9098000902
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: DBCP Monitoring
(ACR) Acronym of Data Base or Model: None
(NED) Media/Subject of Data Base or Model: Ground water > Surf ace Hater
canals, rivers
(ABS) Abstract/Overview of Data Base or Model: DBCP monitoring of
municipal and agricultural water supplies is contained in this
data base.
(CTC) CONTACTS: Subject matter William Thurston (415)974-8226 ;
EPA Office Hilliam Thurston (415)974-8226
(DTP) Type of data collection or monitoring: Non point source data
collection
(STA) Data Base status: Update Terminated
(IPP) Non-pollutant parameters included in the data base: Sampling
date ;Site description ;past use of DflCP in area ;soil type ;
geography ;nuraber of users ;well description /geology jname of
system
(OS) Time period covered by data base: 06-01-79 TO 10-30-80
(TRM) Termination of data collection: Rot Applicable
(FRQ) Frequency of data collection or sampling: as needed
(IOB) Number of observations in data base: 1000.(Estimated)
(NED Fstimated annual increase of observations in data base: 0.
(INF) Data base includes: Raw data/observations ;Summary aggregate
observations ;Reference data/citations
(ITS) Total number of stations or sources covered in data base: 300.
(ICS) No. stations or sources currently originating/contributing data:
0
(MOP) Number of facilities covered in data base (source monitoring): 0.
(GEO) Geographic coverage of data base: Selected federal region Region
IX
(LOG) Data elements identifying location of station or source include:
State ;County ;Clty ; Town/township ;street address
(FAC) Data elements identifying facility include: Plant facility name
yPlant location ^Parent corp name ^Parent corp location } Public
Hater Supply code number
(CDE) Pollutant identification data are: Uncoded
(LIM) Limitation/variation in data of which user should be aware: Possi
ble quality control problems with this data base.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
g plan documented Collection method documented ^Analysis method
document QA procedures documented
(ABL) Lab analysis based on EPA-approved or accepted methods? YES
(ADD) Lab Audit: Data not based on lab analysis.
(PRE) Precision: Precision and accuracy estimates exist but are not
included in data base
(EOT) Editting: No known edit procedures exist.
(CBY) Data collected by: State agency Hawaii Department of Health
Arizona Department of Health Services ;Regional office
Surveillance and Analysis Division, Region IX
(A8Y) Data analyzed by: State agency California Department of Food and
Agriculture EPA lab Drinking Hater Technological Support Division
in Cincinnati
-------
Accession No. 9098000902 (cont)
CIDL) Laboratory identification: YES
(CAS) CAS registry numbers of substances included in data base: 96-12-8
(CUM) Contact name(s): Thurston, HI 111 am; Thurston, if ill lam
1216
-------
Accession No. 9098000903
(DQ) Date of Questionaire: 12*02-82
(RAM) Name of Data Base of Model: United Nuclear Corporation (UNC)
Spill-Rio Puerco Monitoring
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Ground water ;Sediment
^Surface uater river
(ABS) Abstract/Overview of Data Base or Model: A monitoring program to
detect the effects on drinking water of the United Nuclear
Corporation Spill in ChurchrocJc, New Mexico into the Rio Puerco
River.
(CTC) CONTACTS: Subject natter Harold Takenaka (415)974-7484 ;
EPA Office Horald Takenaka (415)974-7484
(DTP) Type of data collection or Monitoring: Point source data
collection tailings pond spill
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 18 radioactive
;129 307 CWA jll conventional water ;41 CMA potential criteria }
21 drinking water standards }15 metals
(NPP) Non-pollutant parameters included in the data base: Chemical
data Collection method ^Location ^Sampling date >Site description
(DS) Time period covered by data base: 07-01-79 TO 11-30-82
(TRM) Termination of data collection: Anticipated 12-30-82
(FRQ) Frequency of data collection or sampling: one time only ;weekly
;morthly ;0ther one time: soil-9/26/79 ; Other weekly:
groundwater-9/04/79-10/15/79 ;0ther monthly:
groundwater-lO/17/79-present j Other monthly: surface water until
May 1980.
(NOB) Number of observations in data base: 1500.(Estimated)
(NEI) Estimated annual increase of observations in data base: (N/A.)
(INF) Data base includes: Raw data/observations ^Summary aggregate
observations
(NTS) Total number of stations or sources covered in data base: 30.
(NCS) No. stations or sources currently originating/contributing data:
(NOF) Number of facilities covered in data base (source monitoring): (N
/A.)
(GEO) Geographic coverage of data base: Geographic region Arizona and
New Mexico
(LOO Data elements identifying location of station or source include:
State ;county ;City ;Pro3ect identifier
(CDE) Pollutant identification data are: Uncoded
(LIM) Limitation/variation in data of which user should be aware: Sampl
ing of surface water was very inconsistent (i.e. irregular and
varied in location). Current parameters: sulfates, chloride,
gross alpha, radium 226, and total uranium.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Saaplin
g plan documented ^Collection method documented jAnalysis method
document QA procedures documented
(ANL) Lab analysis based on EPA-approved or accepted methods? YES
(AUD) Lab Audit: Lab audit is satisfactory for 50%, most parameters
not covered by PE samples* radiological only some..
(PRE) Precision: Precision and accuracy estimates exist but are not
1217
-------
Accession No. 9098000903 (cent)
Included in data base Edit erratic results revieued and
reanalyzed.
(CBY) Data collected by: State agency Arizona Department of Health
Services ^Regional office, Office of Technical and Scientific
Assistance, Region IX; Other federal agency Indian Health Service
(ABY) Data analyzed by: State agency Arizona Department of Health
Services, Men Mexico Environmental Improvement Division
Regional office Region VI and Region IX (through contract)
Navajo Tribe
(IDL) Laboratory identification: YES
(PR1) Prlnary purpose of data collection: Special study
(AOT) Authorization for data collection: Statutory authorization is P
L 93-523 as amended, Section 141 (SDUA) P L 95-217 as amended,
Section 104 (CWA)
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
QQ
(REP) For» of available reports and outputs of data base: package of
all ran data summarized with graphs nailed out.
(•US) Number of regular users of data base: 5
(OSR) Current regular users of data base: EPA headquarter offices
Office of Enforcement Office of Radiation Programs
EPA regional offices
Other federal agencies
States
National park Service, Nuclear Regulatory Commission
Navajo Tribe
Arizona & Keu Mexico state governments
(CMP) Confidentiality of data and limits on access: No limits on
access to data
(DLC) primary physical location of data: Regional office
(DST) For* of data storage: summary sheet
(DAC) Type of data access: Manually
(OPDT) Frequency of data base »aster file up-date: Other as data
becomes available
(CMP) Completion of form:
Laura J. Tom
OFC: EPA/Region IX
AD: 215 Freaont St. San Francisco, CA 94105
PH: (415)974-8379
CDF) Date of fora completion: 02-16-83
(•MAT) Number of substances represented in data base: 39
(•CAS) Number of CAS registry numbers in data base: 28
(MAT) Substances represented in data base:
potassiu»<7440-09-7> cad«ium<7440-43-9>
uranium 234<13966-29-5> calcium
uranium 238<7440-61-1> chloride
alu»inum<7429-90-5> chlorine<7782-50-5>
anti«ony<7440-36-0> chro«iu«<7440-47-3>
arsenic<7440-38-2> cobalt<7440-48-4>
barium<7440-39-3> copper<7440-50-8>
beryllium<7440-41-7> gross alpha
boron co«pounds<7440-42-8> lron<7439-89-6>
1218
-------
Accession No* 9098000903 (cont)
lead 210 radium 228<15262-20-1>
l«ad<7439-92-l> selenium<7782-49-2>
•agnesiun silver<7440-22-4>
manganese<7439-96-5> sodium and compounds<7440-23-5>
•ercury<7439-97-6> specific conductivity
molybdenum and compounds sulfates
<7439-98-7> thorium 230
nickel<7440-02-0> thorium 232
PH uraniu»<7440-61-l>
Plutonium 210 vanadiun<7440-62-2>
radiun 226<13982-63-3> zinc<7440-66-6>
(CAS) CAS registry numbers of substances included in data base: 7440-09
-7; 13966-29-5; 7440-61-1; 7429-90-5; 7440-36-0; 7440-38-2;
7440-39-3? 7440-41-7; 7440-42-8; 7440-43-9; 7782-50-5;
7440-47-3; 7440-48-4; 7440-50-8; 7439-89-6; 7439-92-1;
7439-96-5; 7439-97-6; 7439-98-7; 7440-02-0; 13982-63-3; 15262-20-1;
7782-49-2; 7440-22-4; 7440-23-5; 7440-61-1; 7440-62-2; 7440-66-6
(CHM) Contact name(s): Takenaka,H. ; Takenaka,H.
(ROR) Responsible Organization: Region IX.Toxics and Waste Management
Division.
1219
-------
Accession Ho. 9102000516
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Control and Prevention System
(ACR) Acronym of Data Base or Model: CAPS
(MED) Media/Subject of Data Base or Model: Emissions: Any stationary
man-made* source of air contaminants
(A8S) Abstract/Overview of Data Base or Model: The system captures
descriptive data regarding companies and other sources of air
pollution including investigative* complaint* sampling and
enforcement activities. Also captured is permit activies for
new point sources of emissions since 1972* this includes emission
description* pollutant* process and statement data. Presently
this emission data is being expanded to include major grand
smothered sources.
(CTC) CONTACTS: subject matter Data Services Section Chief* Technical
Services Division (512) 451-5711 j Computer-related Manager of
Software Development* Data Processing Division (512) 451-5711
(DTP) Type of data collection or monitoring: Point source: Any
man-made source of air contaminants
(STA) Data Base status: Presently Operational/Ongoing
(GRP) Groups of substances represented in Data Base: 5 NESHAPS } 7
criteria NAAQS except ozone ; 3 HID CAA
(MPP) Non-pollutant parameters included in the data base: Compliance
data ; discharge points ; industry ; inspection data > location ;
political subdivisions ; sampling date ; permit data
(DS) Time period covered by data base: 06-72 TO 01-83
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: Ongoing: annually /
ongoing: as needed
(MOB) Number of observations in data base: 40,000(Estimated to date)
(NED Estimated annual increase of observations in data base: 15,000
(INF) Data base includes: Aggregate or summary observations
(NTS) Total number of stations or sources covered in data base: 18K
(HOP) Number of facilities covered in data base (source monitoring): 12
K
(GEO) Geographic coverage of data base: Single state: Texas
(LOG) Data elements identifying location of station or source include:
State ; county ; city ; town/township ; street address ;
latitude and longitude* OTM, or other coordinates
(FAC) Data elements identifying facility include: Plant or facility
name ; plant location > parent corporation-name ; parent
corporation-location ; street address ? sic code ; sec (source
classification code)
(CDE) Pollutant identification data are: Coded* other coding scheme
(DPR) Data collect./anal, procedures conform to CRD guidelines: No*
but other documentation available for each of the following:
collection method and analysis method
(AND Lab analysis based on EPA-approved or accepted methods? NO
(AUD) Lab Audit: NO
(PRE) Precision: Not included in data base* percision and accuracy
measurements available from other sources
(EDT) Editting: YES* undocumented
(CBY) Data collected by: Self-reporting* Permittee ? Local agency,
1220
-------
Accession No. 9102000516 (cent)
Federally Funded Program only ; State agency, Texas Air Control
Board
(*BY) Data analyzed by: State agency, Texas Air Control Board
(IDL) Laboratory identification: NO
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Program evaluation
(AUT) Authorization for data collection: No, Data Base provides a
management tool for state agency activities, source of data for
modeling and provides EPA required reports.
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
NO
(REP) Fora of available reports and outputs of data base: Printouts on
reguest ; on-line computer terminal
(MOS) Number of regular users of data base: 10
(OSR) Current regular users of data base: EPA regional offices ;
Other- consultants
(CNF) Confidentiality of data and limits on access: None
(DLC) Primary physical location of data: State agency
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: Commercially available Software: System
Same- Burroughs DMS II, Hardware- Burroughs 6800
(CHG) Direct charge for non-EPA use: YES
(OPDT) Frequency of data base master file up-date: Other- Daily
(RSS) Related EPA automated systems which use data base: Related EPA
systems: CDS - stationary source information management system for
enforcement and surveillance programs.
(RDBEPA) Related EPA data bases used in conjunction with this data base
None
(ROB) Non-EPA data bases used in conjunction with this data base: None
(CMP) Completion of form: f Richard P. Leef OFC; Texas Air Control
Board! AD: 6330 Highway 290 East, Austin, TX 787231 PH: (512)
451-5711f
(•NAT) Number of substances represented in data base: 12
(RCAS) Number of CAS registry numbers in data base: 9
(NAT) Substances represented in data base:
Asbestos <1332-21-4> Hydrocarbons
Benzene <71-43-2> Lead <7439-92-l>
Beryllium <7440-41-7> Nitrogen dioxide <10102-44-0>
Mercury <7439-97-6> Sulfur dioxide <7446-09-5>
Vinyl chloride <75-01-4> Total suspended particulates
Carbon monoxide <630-08-0>
(CAS) CAS registry numbers of substances included in data base: 1332-21
-4; 71-43-2; 7440-41-7; 7439-97-6; 75-01-4; 630-08-0;
7439-92-1; 10102-44-0; 7446-09-5
(ROR) Responsible Organization: Texas Air Control Board.
1221
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Accession No. 9104000911
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: EPA, Region X, Point Source File
(ACR) Acronym of Data Base or Model: PSF
(MED) Media/Subject of Data Base or Model: Effluents National
Pollutant Discharge Elimination System (NPDES) permittees in Region
X ;Runoff Rain/Snowmelt ;Surface water rain/snowmelt
(ABS) Abstract/Overview of Data Base or Model: Facility location
information, permit conditions, and discharge water quality data
required for the Regional Office to conduct and to assess the
impact of control measures under the National Pollutant
Discharge Elimination System (NPDES) permit program.
(CTC) CONTACTS: Subject matter Florence Carroll (206)442-2723;
Computer-related €us ParHer (206)442-2987; EPA Office Mater
Compliance Section, Region x (206)442-2723
(DTP) Type of data collection or monitoring: Point source data
collection Region 10 Permittees
(STA) Data Base status: Operational/ongoing
(GRP) Groups of substances represented in Data Base: 11 conventional
water ;15 metals
(MPP) lion-pollutant parameters included in the data base: Compliance
data Concentration measures Discharge points ;Flow rates ;
Industry Inspection data ;Location political subdivisions ;
Production levels ;Site description ;Temperature jVolume/mass
measures
(DSJ Time period covered by data base: 01-01-79 to current
(TRM) Termination of data collection: Not anticipated
(FRQ) Frequency of data collection or sampling: daily ;weekly ^monthly
^quarterly ;se«i annually ;annually ;as needed
(MOB) Number of observations in data base: 250000.(Estimated)
(MEI) Estimated annual increase of observations in data base: 85000.
(INF) Data base includes: Raw data/observations ^Summary aggregate
observations ;Reference data/citations
(NTS) Total number of stations or sources covered in data base: 750.
(NCS) No. stations or sources currently originating/contributing data:
i / j .
(WOF) Number t>f facilities covered in data base (source monitoring): 75
0.
(GEO) Geographic coverage of data base: Selected federal region Region
(LOC) Data elements identifying location of station or source Include:
State ;County ;City ;street address
(FAC) Data elements identifying facility include: Plant facility name
;PIant location ;Parent corp name ;Parent corp location ; Street
address ;SIC code ;NPDES
(CDE) Pollutant identification data are: Storet parameter
(LIM) Limitation/variation in data of which user should be aware: Stree
t address sometime not available. Frequency varies by permit. 98%
of data presently covers conventional water pollutants and
metals* Toxics and organlcs are being added in some new permits.
Laboratory analysis not always based on EPA-approved or accepted
methods, varying by industry.
(DPR) Data collect./anal, procedures conform to ORD guidelines: Samplin
1222
-------
Accession Mo. 9104000911 (cont)
g plan documented ;Collection method documented ;Analysls method
document
(AND Lab analysis based on EPA-approved or accepted methods? YES
(AOD) Lab Audit: Lab audit is satisfactory for 85% compliance
inspections conducted on major discharges by states and/or EPA,
Contractor to
permittees ;0ther federal agency as permittees (e.g. shipyards.
Forest Service campgrounds)
(ABY) Data analyzed by: Self reporting most of data from permittees
State agency Environmental Agencies
Regional office Surveillance and Analysis Division
Contractor lab to permittees
(IDL) Laboratory identification: HO
(PR1) Primary purpose of data collection: Compliance or enforcement
(PR2) Secondary purpose of data collection: Program evaluation
(AOT) Authorization for data collection: Statutory authorization is P
L 95-217, Sections 308 and 402 (Clean Water Act of 1977), NPDES
Per lit Program
(OMB) Data collected/submitted using OMB-approved EPA reporting forms:
158-R-0073 M . .
(REP) Form of available reports and outputs of data base: Unpublished
reports Reports related to violations and special conditions.
Printouts on reguest
Machine-readable raw data
On-line computer
(It US) Number of regular users of data base: 46
(OSR) Current regular users of data base: EPA regional offices
EPA laboratories
States
freedom of information requestors
(CNF) Confidentiality of data and limits on access: No limits on
access to data
(DLC) Primary physical location of data: Regional office
(DST) Form of data storage: Magnetic disc
(DAC) Type of data access: EPA software Point Source File
MIDS:9104000911 ;EPA hardware POP 11/70
(CHG) Direct charge for non-£PA use: yes
(UPDT) Frequency of data base master file up-date: Other daily
(RDBEPA) Related EPA data bases used in conjunction with this data base
Permit Compliance System (PCS)
(CMP) Completion of form: «....• *.
Florence Carroll/Gus ParlierS OFC: EPA/Region X/Hater Division!
AD: 1200 Sixth Ave. Seattle, MA 91801
PH: (206)442-2723
(DF) Date of form completion: 01-24-83
1223
-------
Accession Ho. 9104000911 (cont)
CRNAT) Number of substances represented in data base: 21
(NCAS) Nuaber of CAS registry nuibers in data base: 12
(MAT) Substances represented in data base:
acidity aanganese<7439-96-5>
alkalinity »ercury<7439-97-6>
arsenic<7440-38-2> nickel<7440-02-0>
cad»iuio<7440-43-9> nitrogen<7727-37~9>
chro«iu«<7440-47-3> oil and grease
copper<7440-50-8> oxygen deaand
dissolved oxygen pH
dissolved solids pHosphorus<7723-14-0>
fecal coliforn seleniu«<7782-49-2>
iror<7439-89-6> suspended solids
lead<7439-92-l>
(CAS) CAS registry nutf>ers of substances included in data base: 7440*38
-2; 7440-43-9; 7440-47-3; 7440-50-8; 7439-89-6; 7439-92-1;
7439-96-5; 7439-97-6; 7440-02-0; 7727-37-9; 7723-14-0;
7782-49-2
(CUM) Contact naMe(s): Florence Carroll ; Section,h.C.
(ROR) Responsible Organization: Region X.Management Division.
1224
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Accession No. 12302000901
(DQ) Date of Questionaire: 12-02-82
(STATUS) Status of entry: Inactive
(NAM) Name of Data Base of Model: U.S. Copper Industry Model
(ACR) Acronym of Data Base or Model: COPMOD1
(MED) Pedia/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: The
financial-econometric simulation model of the U.S. Copper Industry
has been developed to assess the industry-wide economic impact of
compliance with the air and water pollution abatement legislation.
The model consists of a market clearing nodule and a dynamic
investment module programmed in FORTRAN. COPKOD1 was constructed
by Arthur D. Little, Cambridge, Massachusetts.
(CTC) CONTACTS: James Titus EPA-OPM-Office of Planning and
Evaluation „„_ „.„,,.
Loc: PM-220 401 M St., Sti Washington, DC 20460 Ph: 202-287-0725
(STA) Data Base status: Discontinued
(DF) Date of form completion: 01-31-83
(CAP) Functional capabilities of model: COPMOD1 incorporates two
versions of the U.S. Copper model, linear and nonlinear. The model
identifies three alternative modes of pricing behavior for the
primary producers in the linear and nonlinear cases:
1. Price = Average Variable Cost (slack demand)
2. Price = Average Total Cost (normal demand)
3. Marginal Revenue = Marginal Cost(demand 'crunch')
The nonlinear version permits the introduction of capacity
contraints in supply and cost curves, whereas the linear version
yields unconstrained production estimates. Plant capacity could be
exceeded in the linear simulation experiment. In addition,
subroutines are included to plot average total cost, average
variable cost, average fixed cost and compare historical period
simulation results with actual data.
(ASM) Basic assumptions of model: The model explicity assumes the
following market classifications:
1. Primary producers
2. Secondary refiners
3. Producers of non-refined scrap
These classifications are based upon pricing behavior and
production technology. More importantly, primary producers are
analyzed as behaving oligopolistically while secondary refiners and
producers of non-refined scrap are treated as behaving
competitively. -«»M«««
(IHP) Input to model: Alteration of the scenario file in COPMODi can
take two forms:
1. Card input
2. File editor . .
Due to the structure of the program, modification of the scenario
file is most easily accomplished using the file editor.
Modification through card input can only occur if the entire
program subroutine with the new cards is reloaded into the
computer. As of this writing, program modification remains
non-interactive. CQPMOD1 provides for the following input options:
1. Specification of model version:
1225
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Accession No. 12302000901 (cont)
a. Linear
b. Nonlinear
c. Both
2. Printing of all endogenous and exogenous variables*
3. Printing of various diagnostic variables.
4. Which of the three paranetrlc solutions (P » ATC, P = A?C,
MR = MC) is «ost probable.
(OUT) Output of model: Depending upon the version chosen, COPMOD1 Hill
generate a vide range of subsidiary calculations such as production
estimates/ sales estimates, and payroll estimates. Financial
estimates (pollution abatement investment, depreciation, dividends,
etc.) derived from primary producer's estimated fixed costs are
printed in constant and current dollars.
(CSR) computational Systei Requirements: COPMODI is coded In (ASCII)
FORTRAN V and requires approximately 65K words of core storage for
execution. The program is compatible with the Onlvac 1110 and
requires a moderate amount of computer skills and a working
knowledge of econometrics to modify and execute.
(APP) Applications of model: COPMODI was developed primarily for
estimating the impact on copper producer's costs from pollution
abatement expenditure. The model nay also be utilized in
evaluating the effects of noncompllance fees on the producers of
copper and non-refined scrap.
(HDW) computational system requirements - Hardware: Mainframe Onlvac
1110 ;Disc storage 65K words
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramning ;Econometrics
(REF) References - Oser manuals, documentation, etc.:
Arthur D. Little, October 1976. "Economic Impact
of Environmental Regulation on the O.S. Copper Industry".
Draft report.
Arthur D. Little, April 1978. "COPMOD1 Program,
Documentation1*, Cambridge, Massachusetts.
Raymond S. Hartman, January 1977. "An Oligopolistic Model
of the U.S. Copper Industry" Ph.D thesis, M.I.T.
(CNN) Contact name(s): Titus,J.
(COR) Contact organization: EPA-OPM-Office of Planning and Evaluation
(ROR) Responsible Organization: Office of Policy and Resource
Management.Office of Policy Analysls.Economic Analysis Division.
1226
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Accession No. 12302000902
(DQ) Date of Questionaire: 12-02-82
(STATUS) status of entry: Inactive
(RAM) Name of Data Base of Model: Construction Model
(ACR) Acronym of Data Base or Model: CQHMOD
(MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: The construction model
is an econometric Model designed for the evaluation of sever line
and treatment plant expenditures by the Environmental Protection
Agency. The model estimates impacts on labor supply/ investment/
and prices from EPA sewer-related expenditures. CQNMOD Has
developed by the Center for Naval Analyses (CNA). CORMOD resides
on the IPS/TROLL system at the Massachusetts Institute of
Technology.
(CTC) CONTACTS: James Titus EPA-OPM-Office of Planning and
Evaluation
Loc: PM-220 401 M St., SW Washington, DC 20460 Ph: 202*287-0725
(STA) Data Base status: Discontinued
(DP) Date of form completion: 01-31-83
(CAP) Functional capabilities of model: The TROLL system allows for
direct user interaction with CQHMOD. Simulation of any equation or
the production of graphs is accomplished through simple
conversation with TROLL. This system also provides for a variety
of output options In addition to the printing of standard
regression statistics. Econometric techniques ranging from OLS to
2SLS with autocorrelation correction procedures are readily
available. CONMOD utilizes GLS because of the small sample sizes.
TROLL'S unique file system allows all relevant files associated
with a given model to be accessed automatically be referencing the
model Itself. THe user doesn't need to be concerned with loading
data or parameters. TROLL also contains a file editor and provides
for off line printing.
(ASM) Basic assumptions of model: CORMOD was developed assuming the
construction industry to be competitive. For any type of
construction, the composition of construction between trades
remains fixed. Stock of structures equations imply a stock
adjustment mechanism where actual stocks adjust to desired stocks
at a constant rate (estimated by regression analysis). Lastly, the
labor supply schedule is derived from a constant elasticity of
substitution production function (CES).
(IMP) Input to model: Once CONMOD has been accessed, the TROLL system
automatically provides the required data input. The user can then
specify the equation technique, simulation period, required
statistics, and any graphic output desired. After the model has
been simulated once, TROLL will automatically create a 'data set*
file which includes the model, data, and estimated coefficient
values. In this way performing a variety of simulation experiments
at a later time is a simple task. Data can be printed when desired
and results from the output stream can be stored for later use.
(CSR) Computational System Requirements: There are no specific system
resource requirements needed to run CONMOD on TROLL. The system is
conversational and costs approximately $9.00 per CPU minute and
$2.00 per hour connect time to operate.
1227
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Accession No. 12302000902 (cont)
fAPP) Applications of model: CONMOD is used for estimating the
economic impact resulting from the EPA"3 massive sever line and
sewer treatment plant expenditure program. The 00del may also be
used for other applications involving the construction industry.
(HDH) Computational system requirements - Hardware: Mainframe No
specific systea requirements
(LUG) Conputational system requirements - Language(s) used: Fortran
(REP) References - User manuals, documentation, etc.:
Center for Haval Analyses, March 1978. "The
Economic Effects of Environmental Regulations on the Construction
Industry" Arlington, Virginia.
Rational Bureau of Economic Research, June 1972. "TROLL/1
Users Guide** Cambridge, Massachusetts.
(CNM) Contact name(s): Titus,J.
(COR) Contact organization: EPA-OPM-Office of Planning and Evaluation
(ROR) Responsible Organization: Office of Policy and Resource
Management.Office of Policy Analysis.Economic Analysis Division.
1228
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Accession No. 12302000903
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Steel Industry Model
(ACR) Acronym of Data Base or Model: PTM
(MED) Vedia/Subject of Data Base or Model: Industry/econonic
(ABS) Abstract/Overview of Data Base or Model: PTM Has developed by
Temple/ Barker/ and Sloane (TBS) for the purpose of systematically
analyzing the effects on the steel industry resulting from
environmental regulations/ input price changes/ or from other cost
variations. The model partially relies on a modeling effort
previously done by Arthur D. Little in Cambridge/ Massachusetts.
PTM contains four nodular components: production/ pollution
control, and finance/ and economic impact. The three later
components depend upon the production and capacity data from the
production component in order to execute. Exogenous variable
values for siaulation were obtained through Data Resources Inc.
(CTC) CONTACTS: Robert Greene EPA-OPM-Office of Policy Analysis! Loci
PM-220 401 M St./ SW Washington, DC 20460 Ph: 202-382-2780
(STA) Data Base status: Operational/Ongoing
(DF) Date of fora completion: 01-31-83
(CAP) Functional capabilities of model: PTM has the capability of
performing many different sensitivity analyses by altering data
inputs such as the rate of return on equity/ degree of cost pass
through, cost of capital/ etc. In addition, effects on energy
usage/ production employment/ prices and the balance of trade
stemming from environmental regulations can be estimated. Cost
impacts of the Clean Air Act and other air pollution regulations
can be calculated utilizing different engineering, cost estimated.
The resulting revenue requirements and price effects are also
computed by model.
(ASM) Basic assumptions of model: The baseline forecast for steel
shipments by 1990 is 108 million net tons. The other baseline
indicators needed to simulate the baseline forecast are capital
expenditures/ external financing needs/ operations and maintenance
expenses/ revenue requirements/ and the average price of steel per
ton. TBS has calculated the following numbers for the baseline
forecast.
Short Run
1981-1985
Capital Expenditures S 18.11 Financing Needs
3.2 30.3f Revenue Requirements 52.8
5.6* Average Price 554.52 556.72# (in
1980 dollars per ton)# The theoretical assumptions used in
constructing PTM were not available as of this writing.
(IMP) Input to model: PTM requires many cost inputs. These consist of
production costs and pollution control costs. Under these two
headings there are several subdivisions. Pollution control costs
can be broken down into water pollution and air pollution control
costs. Each type of pollution control cost has two (main) cost
categories; operations and maintenance expenditures and capital
costs. Production costs include capital expenditures/ operations
and maintenance cost/ ran materials cost, and 'other costs*. PTM
(Steel) produces the following outputs:
1229
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Accession Ho. 12302000903 (cent)
1. Income statement
2. Flow of funds suaueary
3. Balance sheet
tOUf) Output of aodel: These outputs contain all the information
necessary to analyze the impacts on the industry. All output
figures are in current dollars.
(CSR) Computational Systea Requirements: PTM is coded in FORTRAH ? and
can be run on the IBM 370/158 or UHIVAC 1110 computers, Unless
alterations to the baseline or scenario forecasts are desired/ the
•odel can be run immediately after being loaded into the Machine.
Direct alterations to the program would require a working knowledge
of FORTRAN and econometries.
(APP) Applications of model: PTM Steel has been priaarily used for
environmental impact/sensitivity analyses by the U.S. Environmental
Protection Agency. The «odel could also be used in forecasting
impacts on the steel industry resulting from changes in factors of
production, factor prices, or technological advancement.
CHDM) Computational system requirements - Hardware: Mainframe IBM
370/158 or Univac 1110
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: operator Knowledge/Skills: Pro
grammlng ;Econometrics
-------
Accession No. 12302000904
(DQ) Date of Questionaire: 12-02-82
(STATUS) Status of entry: Inactive
(HAM) Name of Data Base of Model: Automobile Demand Model
(ACR) Acronym of Data Base or Model: CARMOD
(MED) Media/Subject of Data Base or Model: Industry/econonic
(ABS) Abstract/Overview of Data Base or Model: CARMOD is a 400
equation simultaneous econometric model* The model is concerned
primarily yith estimating long run levels of automobile demand.
CARMOD was developed by Wharton Econometric Forecasting Associates
(HEFA). The model is long run and movements toward equilibrium are
governed by a stock adjustment mechanism. CARMOD resides on the
IPS/TROLL system at the Massachusetts Institute of Technology.
(CTC) COHTACTS: Mahesh Podar EPA-OPM-Office of Planning and
Evaluation *-,.
Locs PM-220 401 M St., SM Washington/ DC 20460 Ph: 202-287-0734
(STA) Data Base status: Discontinued
(DF) Date of fora completion: 01-31-83
(CAP) Functional capabilities of model: The TROLL system allows for
direct user interaction with Carmod. Simulation of any equation or
the production of graphs is accomplished through simple
conversation with TROLL. This system also provides for a variety
of output options in addition to the printing of standard
regression statistics. Econometric techniques ranging from OLS to
2SLS with autocorrelation correction procedures are readily
available. CARMOD*s equations were estimated using ordinary least
squares. TROLL's unique file system allows all relevant files
associated with a given model to be accessed automatically be
referencing the model itself. The user doesn't Heed to be
concerned with loading data or parameters. TROLL also contains a
file editor and provides for off line printing.
(ASM) Basic assumptions of model: The assumptions concerning model
forecasts (baseline projection) fall into three categories;
demographic trends, the economic environment, and automobile
characteristics.
1. The major demographic assumptions are:
Slow population growth: the growth-rate falls from 0.17% per annum
for 1976-1985 to just over 0.3% for 1995-2000. Family formation
outspaces population: the number of family units rises from 75.3
million in 1975 to 87.4 million in 1985 (a 1.5% per annum rate) to
100.7 million by 2000 (a 0.9% per annum rate). Families become
smaller: the proportion with five or more members falls sharply,
while that for three or four remains constant. An aging population:
the percentage between 20 and 29 years of age falls, especially
after 1980.
2. The fcey economic assumptions are:
Strong real income growth: real GNP growth in excess of 5% per
annum through 1978, slowing to 2% for 1979-1980, stabilizing at
around 3% per annum thereafter. Slowing inflation: the overall GMP
deflator rises at around 5.5% per annual through 1980, slowing
towards 4% by 1985, and reaching 3% per annum by 2000. Declining
unemployment-rate: unemployment falls towards a 5% rate by the
mid-1980-5, then slowly trends towards 3% by 2000. Slowly
1231
-------
Accession Mo. 12302000904 (cont)
increasing 'teal* automobile costs: operating costs are expected
to outpace the overall consumer price index, expecially the price
of gasoline - projected to increase over 20% in 1972 prices by
1985; however/ 'real* purchase prices are expected to be quite
stable.
3. The auto characteristics assumptions are:
Sharply reduced weights and displacements: a major domestic
downsizing program, applied to each size-class in succession,
reducing curb-weights about 30%, and engine displacements about
40%, by 1990. Efficiency improvements: technological developments
are projected to yield Increases in fuel efficiency totalling 11%
for 1976-80; thereafter these gains are held to 1% per annum on the
assumption of more stringent pollution standards.
(IIP) Input to model: Once CARMOD has been accessed, the TROLL system
automatically provides the required data input. The user can then
specify the equation technique, simulation period, required
statistics, and any graphic output desired. After the model has
been simulated once, TROLL Hill automatically create a 'data set'
file which includes the model, data, and estimated coefficient
values. In this way performing a variety of simulation experiments
at a later time is a simple task.
(CSR) Computational System Requirements: There are no specific system
resources requirements needed to run CARMOD on TROLL. The system
is conversational and costs approximately $9.00 per CPU minute and
$2.00 per hour connect time to operate.
(APP) Applications of model: CARMOD has been used by the Department of
Transportation to forecast the long run size and composition of
U.S. auto demand and stock. More recently, the model has been
employed by the Environmental Protection Agency in forecasting
impacts on the U.S. automobile industry resulting from
environmental regulations*
CHDV) Computational system requirements - Hardware: Mainframe No
specific system requirements
(LUG) Computational system requirements - Language(s) used: Fortran
(KEF) References - User manuals, documentation, etc.:
Hharton Econometric Forecasting Associations,
"An Analysis of the Automobile Market: Modeling the Long
Run Determinants of the Demand for Automobiles" Philadelphia,
PA, February 1977.
National Bureau of Economic Research, "TROLL/1 User's Guide"
Cambridge, Massachusetts, June 1972.
(CVM) Contact name(s): Podar,M.
(COR) Contact organization: BPA-OPM-Office of Planning and Evaluation
(ROR) Responsible Organization: Office of Policy and Resource
Management.Office of Policy Analysis.Economic Analysis Division.
1232
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Accession No. 12302000905
(DQ) Date of Questionaire: 12-02-82
(STATUS) Status of entry: Inactive
(RAN) Name of Data Base of Model: Pulp and Paper Industry Model
(ACR) Acronym of Data Base or Model: P&PMOO
(MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: PSPMQD is a
nonsimultaneous model of the pulp and paper industry. The model
contains supply and demand equations for sectors of the pulp and
paper industry and aggregate industry equations. A flow of funds
model is used to estimate the amount of capital and external
financing needed to support the forecasted demand values. The flow
of funds model and supply/demand model are not interfaced. P&PMOD
was developed by Arthur D. Little, Inc. for the U.S. Environmental
Protection Agency.
(CTC) CONTACTS: James Titus EPA-OPM-Office of Planning and
Evaluation
Loc: PM-220 401 M St., SW Washington/ DC 20460 Ph: 202-287-0725
(STA) Data Base status: Discontinued
(DF) Date of form completion: 01-31-83
(CAP) Functional capabilities of model: The pulp and paper industry is
divided into ten product sectors by the ADL study. For each sector
the model has supply and demand equations. The equations can be
estimated using any regression package with auto correlation
correction procedures {ADL used Time Series Processor (TSP)). Mith
the proper software, supply and demand can be forecasted for each
product sector and the subsequent flow of funds model which depends
upon the result form the supply/demand is the production forecast
froB the aggregate equation. Assuming that the data base resides
on the computer, the models can be interfaced by someone with
programming experience. The econometric supply/demand model
utilizes ordinary least squares and two-stage least squares
estimation procedures.
(ASH) Basic assumptions of model: P&PMOD assumes that over the
forecast period 1976 and 1983, the industry will continue to pursue
its traditional financial policies and to price its products
consistent with the demand schedule it faces to achieve its
required rate of return. Although it is rarely the case,
equilibrium is assumed to exist in the produce and capital matters.
To this extent, observed values will fluctuate around the
^orecast-v values.
(IN?'; Input -o model: The demand equations require macroeconoaic data
for simulation. ADL used Chase Econometrics macro forecasts for
this input. However, other firms with large scale macro models
would also be able to produce macro forecasts for P&PMOD. The
American Paper Institute provided the capacity utilization figures
which were used in a trend analysis for extrapolating capacity
utilization (adjusted by the results from the mill closure
analysis). These numbers were used as inputs for the flow of funds
(OUT) Output of model: Outputs from the supply/demand model Include
demand (consumption) and prices. As a result, the price increase
necessary for existing mills to recover their increase in average
1233
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Accession No. 12302000905 (cont)
total cost resulting from compliance with the studied regulations
can be computed. Financial calculations are done after the
econometric analysis because of the dependency on the forecasts.
Financial outputs include the amount of external financing required
to Beet forecasted demand, cash flow to equity ratios, net increase
in working capital and more.
(CSR) Computational System Requirements: PiPMOO can be run on any
computer equipped with an econometric software package. ADL used
an IBM 370/135. A programmer with a knowledge of economics is
required.
-------
Accession No. 12302000906
(DQ) Date of Questionaire: 12-02-82
(STATUS) Status of entry: Inactive
(•AM) Nane of Data Base of Model: Abatement and Residual Forecasting
Model
(KR) Acronym of Data Base or Model: ABTRES
(MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: The Abatement and
Residual Forecasting Model (ABTRES) forecasts and reports the costs
associated with pollution control systems, and the concomitant
residual levels. The system is based upon "sectors*1; that is*
processes or technologies which have Identifiable pollution control
costs. These sectors are aggregated to "chapters" for reporting
purposes. Chapters are industrial segments, organized in a manner
determined by the analyst. This aggregation is useful since there
are often several sequential operations uithin an industry/ each
with separate pollution control systems, or an industry may be
defined in a general manner, to include several different end
products, such as "Organic Chemicals."
(CTC) CONTACTS: Anne Cassin EPA-OPM-Office of Planning and
Evaluation
Loc: PM-220 401 M St., SH Washington, DC 20460 Ph: 202-382-2778
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-31-83
(CAP) Functional capabilities of model: The ABTRES model allows the
user to compute costs associated with meeting the pollution control
standards in effect through Internal calculations based upon
certain input parameters, or the user may enter these costs
exogenously. In conjunction with these cost forecasts, the nodel
projects estimated residual levels associated with the treatment
methods of each abatement technology sector. There are two
standards which apply to existing industries to meet Federal
guidelines for water pollution control, and these are the Best
Practicable Technology (BPT) and the Best Available Technology
(BAT). There are separate standards promulgated for plants
established after a particular date (which varies by industry), and
the set of records is referred to as New Source Performance
Standards (NSPS). Sectors dealing with air pollution have a single
standard to implement, which is based upon state implementation
plans (SIP). There are also more stringent regulations dealing
with new plants. Types of pollution considered by the model
include; particulates, sulfur oxides, nitrogen oxides,
hydrocarbons, carbon monoxides, vinyl chloride, other gases and
mists, biological oxygen demand, chemical oxygen demand, suspended
solids, dissolved solids, acids, bases, and oils and greases.
(ASM) Basic assumptions of model: ABTRES is an accounting model that
subcategorizes industries and computes costs associated with
meeting the pollution control standards in effect through internal
calculations based upon certain input parameters. Costs may also be
entered exogenously. A straight line interpolation method is used
to find the growth rates for years not specified as corresponding
to these rates* Growth is held constant for the intervals between
interpolation years. The conceptual growth curves are smooth; for
1235
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Accession No. 12302000906 (cont)
computational purposes, the step curve is used/ allocating all
growth to the beginning of the fiscal year.
(IMP) Input to aodel: Input to the »odel is in card inage fora/ and
the following types of information are included: abatement
technology description, number of residuals, equipment life,
interest rates, exogenous costs, loading factors, capacity
utilization, number of plants, average capacity, growth percentage
by interpolation year, percentage of capacity pretreating wastes
prior to minicipal treatment by interpolation year, residual codes
for pollution types, base residual coefficients (to yield total
pollutant level generated without any treatment), and fraction of
waste treated.
(OUT) Output of model: Once forecasts of costs and residuals have been
generated by the computational program of ABTRES, a report
generator is implemented using the output files. The costs for
several abatement technology sectors are aggregated as a "chapter
level". Different reports are Issued for air and water treatment
systems.
(CSR) Computational System Requirements: Two programs must be
implemented in the ABTRES system. The first is a forecasting
model, and the second a report generator. The model requires 100K
bytes of core storage. Model users should have a knowledge of
programming and an awareness of the model's theory and limitations.
(APP) Applications of model: ABTRES can be used to forecast and report
the cost associated with pollution control systems and the
concomitant residual levels. It has been applied to manufacturing
plants and the levels of water pollution associated with these
plants.
(RDM) Computational system requirements - Hardware: Mainframe IBM 370
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
granmlng ^Awareness of the model's theory and limitations
(REF) References - User manuals, documentation, etc.:
Wing, B.J., Abatement and Residual Forecasting
Model (ABTRES), Prepared by the Professional Services Division,
Control Data Corporation, Rockville, Maryland, for the Office
of Planning and Evaluation, 0. S. Environmental Protection
Agency, Washington, D.C., April, 1977.
(CNH) Contact name(s): Titus,J.
(COR) Contact organization: EPA-OPM-OffIce of Planning and Evaluation
(ROR) Responsible Organization: Office of Policy and Resource
Management.Office of Policy Analysis.Econonic Analysis Division.
1236
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Accession Ho. 13403000903
(OQ) Date of Questionaire: 12-02-82
(IAM) Kane of Data Base of Model: S120 Noncompliance Penalty Model
UCR) Acronym of Data Base or Model: PERALTV
(NED) Media/Subject of Data Base or Model: Air } Indus try/ economic
(IBS) Abstract/Overview of Data Base or Model: The Section 120
Honcompliance Penalty Model (PENALTY) is an economic model used to
calculate the economic benefit of delayed compliance with the
requirements of the Clean Air Act as amended, August 1977. The
noncoapliance penalty is based on the concept that it is usually in
a source's best economic interest to delay the commitment of funds
for pollution control equipment, and that Incentive should be
eliminated. The program was completed in February, 1979, by
Putnam, Hayes & Bartlett, Inc. of Newton, Massachusetts, for the
U.S. EPA, Office of Planning and Management.
(CTC) CONTACTS: Howard F. Wright U.S. EPA, Stationary Source
Compliance Division Office of Air Quality Planning & Standards Loc:
401 M St, S.B., Washington DC 20460 Ph: (202) 382-2833
(STA) Data Base status: Operational/Ongoing
(OP) Date of form completion: 12-08-82
(CAP) Functional capabilities of model: PENALTY compares two cash
flows, that which the source would have experienced had it achieved
compliance on the date it received a notice of noncompllance, and
that which it is estimated it will experience as a result of its
delay. Because these cash flews occur at different times, a basis
of comparison is provided by discounting them to their present
value equivalents. The model then calculates the difference
between these two cash flows and the appropriate quarterly payment
schedule that the source should follow. It can also make a final
adjusted penalty calculation when the source has achieved
compliance. The capital investment portion of the penalty is
calculated using standard and rapid amortization. Under both types
of amortization the program calculates the depreciation tax savings
using straight line, sum-of-the-years-digits, and double declining
balance depreciation methods. The program will automatically
choose the method which will result in the lowest penalty.
iiSM) Basic assumptions of model: The relative mix of debt, preferred
stock and common equity allocated to pollution control equipment is
the same as that found in the firm's capital structure as shown on
its balance sheet. Cash flows are discounted using the equity
method. The noncompliance penalty is computed as a
non-tax-deductible expense to the firm. Cash flows take place at
the end of each month. The rate of inflation of pollution control
operating and maintenance expenditures is the same as that for
pollution control capital costs. The noncompliance penalty is
calculated using a thirty-year time horizon. The salvage value of
any equipment with useful life remaining at the end of the thirty
year time horizon is zero. The discount rate is not less than the
inflation rate.
(I») Input to model: Input to the model includes source-related data:
facility life, months of noncompliance, income tax rate, discount
rate, and preferred stock dividend ratej equipment-related data;
capital expenditures, operating and maintenance costs, financing
1237
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Accession No. 13403000903 (cont)
(industrial bonds; equity share, preferred stock share, and debt
share of investment), equipment useful life and depreciation life;
and a forecasted inflation rate. This information nay coae fron
the firm itself as Hell as the Internal Revenue Service, Chemical
Engineering Plant Cost Inflation index, the Federal Trade
Commission, and Moody*s Bond Record.
(OUT) Output of model: Output consists of two user-selected formats; a
lump SUB settlement, or a schedule of quarterly payments, both
expressed in thousands of dollars.
(APP) Applications of model: It Hill be used by HQ, EPA regional
offices and States as Hell as sources and contractors to coapute
noncoBpliance penalties.
(HDV) Computational system requirements - Hardware: Mainframe IBM
360/370
(LNG) Computational system requireaents - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: eco
noBics, finance (neither, however, is essential)
(OAQ) Model reviewed and approved by OAQPS? YES
(SRC) Source of pollutant: N/A
(REF) References - User manuals, documentation, etc.:
Monday, July 28, 1980 Federal Register
Part II - EPA - Assessment and Collection of Non-conpliance
Penalties by EPA and approval of State Noncospliance Penalty
Program. Appendix A - Technical Support Document
Appendix B - CAA Section 120 Noncompl. Penalties Instruction
Manual
(CUM) Contact name(s): Wright,H.F.
(COR) Contact organization: D.S. EPA, Stationary Source Compliance
Division Office of Air Quality Planning &
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Quality Planning and Standards.Stationary
Source Compliance Division.
1238
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Accession No. 14203000001
(DQ) Date of Quest!onaire: 12*02-82
(NAN) Kane of Data Base of Model: High Level Radioactive
Haste-Repository Risk Model
(ACR) Acronym of Data Base or Model: REPRISK
(NED) Media/Subject of Data Base or Model: Radiation
(ABS) Abstract/Overview of Data Base or Model: This conputer code
calculates the expected genetic and somatic health effects at a
generic high level radioactive waste geologic repository* The code
calculates radionuclide releases to air, land surface/ and rivers
or lakes from a repository as a result of expected events and
accident events* The accidents are human intrusion (drilling),
breccia pipes, faults, meteorites and volcanoes. The expected
events are shaft and borehole leakage and bulk rock transport. The
releases result either from destruction of waste packages or
disturbance of the contaminated repository backfilled tunnels. The
concentration of radioactivity in the backfilled tunnels depends on
availability of water in the tunnels, the dissolution of
radionuclides (solubility), and the characteristics of the waste
matrix and canisters. Movement of contaminated water in the
tunnels is either directly to land surface or to aquifers overlying
the repository. Movement of the radioactivity in the aquifer is
governed by groundwater flow in the aquifer and retardation of
radionuclides in the aquifer.
(CTC) CONTACTS: C. Bruce Smith U.S. EPA, Office of Air, Hoise and
Radiation Office of Radiation Programs, Criteria and Standards Diw
Loc: Crystal Mall #2 1921 Jefferson Davis Hwy Arlington, VA 22202
Ph:
(703) 557-7604
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-01-83
(CAP) Functional capabilities of model: The model calculates the total
release of radionuclides over a time period and converts these
releases to health effects. To calculate releases the flow rate of
radioactivity in curies per year is integrated either analytically
or numerically over the time period of interest. The numerical
integrator is 90% accurate. Flow in the aquifer is 1 dimensional
nondispersive. The tunnel mixing volume is assumed homogeneous.
Parameters are constant over all time, but flow rates of water from
the repository are time dependent* The health effects are combined
with event probabilities to calculate probability consequence
curves and overall risk.
(ASM) Basic assumptions of model:
1) 1 dimensional non dispersive aquifer
2) Homogeneous mixing volumes whose radionuclide concentrations
can be described by first order differential equations.
3) Inout parameters are constant over all time.
4) Probabilities of accident events are constant over various
tine bands. A reasonable number of time bands can be input.
(IBP) Input to model: Users Manual Hill be published. Representative
input data will be contained in the two EPA documents listed in
Section 3 of References.
(OUT) Output of model: Two types of output are available for somatic
1239
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Accession Mo. 14203000001 (cont)
health effects, genetic health effects, or release limit ratios.
1) Integrated risk or release limit ratios*
2) Probability consequence curves.
(APP) Applications of model: EPA/ORP is using the code to
conservatively evaluate 5 generic high level uaste repositories -
bedded salt, granite, shale, basalt. This effort is support for
the EPA/ORP EIS and standard for high level uaste repositories.
Subroutines and linkages IMSL Mathematical function DCAORE is used
as the numerical integrator.
(HDV) Computational system requirements - Hardware: Mainframe IBM 370
;Magnetic tape storage 2 tapes >Printer Li
CREF) References - User manuals, documentation, etc.:
Users Manual to be published.
Smith, C.B., D.J. Eganr H.A. Williams, J.M. Gruhlke, C-Y
Hung, and B. Strini Population Risk from Disposal of High-Level
Radioactive Hastes in Geologic Repositories. EPA/520/3-80-006
Smith, J.M., T.W. Fowler, and A.S« Goldin Environmental Pathnay
Models for Evaluating Population Risks from Disposal of
High-Level Radioactive Hastes In Geologic Repositories EPA
520/5-80-002.
-------
Accession No. 14203000002
(DQ) Date of Questionaire: 12-02-82
(HAH) Name of Data Base of Model: Maximum Individual Dose Model
(ACR) Acronya of Data Base or Model: MAXDOSE
(MED) Kedia/Subject of Data Base or Model: Air ;Radiation ;Water
/Nuclear Wastes
(ABS) Abstract/Overview of Data Base or Model: The Haxdose code
calculates accidential releases frosi a nuclear waste repository*
Both geological and human events are modelled. Each event produces
a given set of dose rates at different times and distances. A
second set of tables estittate contaminated areas and individual
risk. Both leaching and dissolution remove wastes from the matrix
into the accessible environment. The releases are used to
calculate the dose table.
(CTC) CONTACTS: Barry L. Serini U.S. SPA, Office of Air Noise and
Radia Office of Radiation Programs, Criteria Standards Div.
Loc: Crystal Mall #2 Ph: (703) 557-7604
Loc: 1921 Jefferson Davis Hwy, Arlington, VA 22202
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-01-83
(CAP) Functional capabilities of model: The code can calculate the
dose for up to 10 distances, 13 dose times, and 20 nuclides per
run. All transport models are 2 dimensional, yielding the highest
dose along the centerline. Error on numerical integration is less
than 10%, using cautious adaptive Romberg extrapolation.
(ASM) Basic assumptions of irodel: For atmospheric releasas, Maxdose
uses AIRDOSE equations, no direction is specified for the Hind.
Hater releases are calculated along the centerline, where the
maximum concentration occurs. Area calculations assume parabolic
distribution for contaminates in the groundvater and a circular
distribution for air releases.
(IMP) Input to model: Input to model includes initial inventories of
waste, their falflines, retardation factors, 3 sets of dose
conversion factors, solubilities, bioaccumulation factors. The
boreholes and the flow thru the boreholes are modelled.
Peroiability and its rate of change are input, numerical constants
for approximating the gradient, the canister life, leach rate,
groundwater velocity, size of tank, porosities, dose times and
distances.
(DOT) Output of model: Output consists of an echo check of the input
data in a standard format. A table of dose rates at various dose
times and distances, and areas contaminated by a given event are
presented.
(APP) Applications of model: Two routines, CTIME and DCADRE are not in
the code, they are in the linkage step of the job control ? DCADRE
is a numerical integration from the International Mathematics and
Statistics Library. CTIME returns the time of day and date the Job
is run. The code has been used to estimate risks to individual and
in IDAR (Individual Dose Assessment Report).
(BDM) Computational system requirements - Hardware! Mainframe IBM 360
;Magnetic tape storage any 132 positions p
(LiG) Computational system requirements - Language(s) used: Fortran
Machine language is used in routine TIMER which a subroutine calls
1241
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Accession Mo. 14203000002 (cont)
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
graiming ^Engineering >Job control language of the Intern
Statistics Library (IMSL)
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? MO
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atoaosphere: negligible
removal
(TUB) Sample averaging time used: more than 24 hours
CSRC) Source of pollutant: Faulting-multiple point; Drilling-limited
point
(AR) Area where sample was collected: level or gently rolling terrain.
(RMG) Distance traveled by pollutant fro* source: less than 60 km
(MTP) Hater Models - Type of model: Mater quality
(EOT) Environment(s) to Bhich model applies: Mon-polnt Aquifers
(COD Processes and constituents included in modal: Erosion and
sediment ^Temperature ^Biological effects jHydro Hydraulics
(CPL) Complexity level of model: Simplified
(RED References - User manuals, documentation, etc.:
MAXDOSE - EPA Users Manual
(CMM) Contact naae(s): Serini,B.L.
(COR) Contact organization: U.S. EPA, Office of Air loise and
Radiation, Office of Radia
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Radiation Programs.Criteria and Standards
Division.
1242
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Accession No. 14203000003
(DQ) Date of Questionaire: 12-02-82
(IAN) Fame of Data Base of Model: Great Lakes Dose/Concentration
(ACR) Acronym of Data Base or Model: GLA-1
(MED) fedia/Subject of Data Base or Model: Radiation ;Uater
(IBS) Abstract/Overview of Data Base or Model: This model uses a
simplified representation of the Great Lakes along with the time
dependent dose equations of International Conisslon on
Radiological Protection (ICRP) 10A to predict ambient lake
concentrations on the dose rates resulting from chronic ingestion
of radioactivity in Lake waters. However, the program is
applicable to other pollutants.
(CTC) CONTACTS: R.E. Sullivan O.S. EPA, Office of Air Noise and
Radiation, of Radiation Programs, CSD
Loc: Crystal Mall #2, 1921 Jefferson Davis Buy. Ph: (703)557-9380
Loc: Arlington, VA 22202
(STA) Data Base status: Operational/Ongoing
CDF) Date of form completion: 02-01-83
(CAP) Functional capabilities of model: The model comprises a
simplified physical representation of the Great Lakes chain which
considers only total volume of each lake, assumes annual mixing but
allows for changes in dilution volume required by thermoclines, and
corrects for sedimentation and equilibration where required. Dose
rates due to chronic ingestion of 2.2 liters of water per day are
calculated according to ICRP 10 and ICRP 10A.
(ASM) Basic assumptions of model: Assumes constant total volume,
constant outflow and Inflow, and constant surface area. Assumes
that thermocline exists for 1/2 year at a depth of 17 meters and
that Inflow and outflow are from the epilimnion during the period
but that perfect mixing occurs during balance of the year.
Concentration equations are convoluted with the ICRP equation for
organ burden and solved in closed form. Only six Isotopes, Tritium
(H-3), Cobalt-60 (Co-60), Strontium-90 (Sr-90), Cesium-134
(Cs-134), and Cesium-137 (Cs-137) are treated at present.
(IMP) Input to model: Input required is: Source terms, time results
desired, initial concentrations, and lake volumes and outflows. As
currently programmed individual sources discharging into lakes can
be used or parameters for sets of nuclear power plants having
differing types of rad waste systems may be substituted.
(DOT) Output of model: Lake concentrations for the five isotopes at
each time specified along with dose rate and dose equivalents.
Concentration as a function of time for other pollutants can be
found without altering the program. Degradable pollutants can be
treated like radlonuclides by selection of an appropriate decay
constant. .. ^ . .
-------
Accession No. 14203000003 (cont)
(HTP) Water Models - Type of model: Mater quality
(ENV) Environment(s) to which model applies: Lake
(COM) Processes and constituents included in model: Biological effects
(CPL) Complexity level of model: transient mass balance /one
dimensional
(REF) References - User manuals, documentation/ etc.:
Sullivan, R. E. and Ellett, H.H., 1977. The
Effect of nuclear Power Generation on Water Quality in the
Great Lakes. ORP/CSD-77-5.
(CNM) Contact name(s): Sullivan,R.E.
(COR) Contact organization: U.S. EPA, Office of Air Noise and
Radiation, office of Radia
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Radiation Programs.Criteria and Standards
Division.
1244
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Accession Ho. 14203000004
(DQ) Date of Questionaire: 12-02-82
(RAM) Kane of Data Base of Model: Radionudide Dose Rate/Risk
(ACR) Acronym of Data Base or Model: RADRISK
(MED) Media/Subject of Data Base or Model: Radiation
(ABS) Abstract/Overview of Data Base or Model: RADRISK is a model
designed to estimate the health risk due to inhalation or ingestion
of radionuclides for arbitrary exposure periods, the end result of
the system is a set of values relating fatal cancers and
genetically significant radiation doses to a unit intake of
radionuclides. The model is a greatly revised combination of two
previously existing programs—IHREM II and CAIRO. The health risk
fros external exposures is also estimated by the CAIRO model using
dose rates from a separate model—DOSFACTER.
(CTC) CONTACTS: R.E. Sullivan U.S. EPA/ Office of Air Roise and
Radiation/ of Rad. Programs* CSD
Loc: Crystal Mali f2/ 1921 Jefferson-Davis Hwy.
Loc: Arlington/ VA 22202
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-01-83
(CAP) Functional capabilities of model: RADRISK calculates the
radiation dose rates and estimated fatal cancers resulting from the
chronic Inhalation or ingestion of one pico Curie/yr of
radioisotope. All radioactive decay products of the parent isotope
are also considered. Dose rates are calculated over a 110-year
period for eighteen organs. Cross irradiation dose rates are
incorporated using Monte Carlo results from the S-factor model.
These dose rates are then combined in a life table/ using U.S.
population mortality rates/ to compensate for competing risks in
estimating radiation health effects. External dose rates/ taken
from DOSFACTER/ are treated similarly in the life table analysis.
An integration of the gonadal dose rate is also performed to obtain
the 30-year genetically significant dose. Input units are pico
Curies/yr/ pico Curies or squared centimeter pico Curies/cubed
centimeter. Dose rates are given in mrad/yr for both high- and
IOH-LET radiation and the life table returns estimated premature
deaths to a cohort of 100/000 for each cancer.
(ASM) Basic assumptions of model: The dose rate calculational model
incorporates the International Commission on Radiological
Protection (ICRP) lung and gastro-intestinal tract models and uses
exponential retention functions and standard metabolic parameters
for the post blood organs. Non- exponential retention functions
are fitted/ by means of an auxiliary program/ to an exponential
series of up to five terms. The life table calculation is based on
a cohort of 100/000 persons whose mortality rate is that of the
U.S. 1969-1971 population. The additional risk/ either absolute or
relative, from radiation is then followed from birth (0 years) to
death (110 years) of the cohort. At present/ no age dependence is
allotted in the dose rate calculation (reference man is assumed)
although the life table dose rate or risk may be age adjusted.
(IIP) Input to model: Input required for the dose rate portion of the
code includes the physical (half life/ energy) and metabolic
(transfer fractions/ retention functions) data for the parent and
1245
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Accession No. 14203000004 (cont)
each daughter product. In addition/ a library of cross-irradiation
terns nust be supplied. The life table calculation/ in addition to
the tine dependent dose/ requires specification of the risk/
including latency and plateau periods, associated with the
radiation. For relative risk cases/ mortality rates must be
supplied for each cancer to be considered.
(DOT) Output of model: Normal output comprises the total dose rate/
for both high- and lon-LET radiation/ to each of 18 organs at the
•idpoint of specified tire intervals. Options are available for
printing out each daughter contribution as well as the
cross-irradiation terms. The integrated genetically significant
dose to the gonads, along with an average value/ is also output.
The life table calculation outputs the number of premature deaths/
the average years of life lost for each/ and the decrease in
overall life expectancy for each cancer type as well as the totals.
(APP) Applications of model: Model has been used to produce set of
dose/ risk values for a unit intake/ or unit exposure/ of most
common radioisotopes. Program has been run extensively at Oak
Ridge National Laboratory. Major external link is S-Factor output*
(RDM) Computational system requirements - Harduare: Mainframe IBM
360/370 ;Disc storage 500K bytes ;Printer any
(LNG) Computational system requirements - Language(s) used: Fortran
COSK) Computational system requirements: Operator Knowledge/Skills: Pro
graining ;Engineering ;Health/Medical Physics
(REF) References - User manuals/ documentation/ etc.:
RADRISK (to be published)
Dunning/ D.E./ Jr./ et aI./ 1977. S-FACTOR: A computer
Code for Calculating Dose Equivalent to a Target Organ per
Microcurie-Day Residence of a Radionuclide in a Source Organ.
Cook/ J.R./ et al./ 1978. CAIRO: a Computer Code for
Cohort Analysis of Increased Risks of Death.
EPA 520/4-78-012.
Kocher, D.C./ 1979. DOSFACTER: Dose-Rate Conversion Factors
for External Exposure to Photon and Electron Radiation from
Radionuclides Occurring in Routine Releases from Nuclear
Fuel Facilities. ORNL/NOREG/TM-283.
Killough, G.G./ et al./ 1978. INREM-II: A Computer
Implementation of Recent Models for Estimating the Dose
Equivalent to Organs of Man from an Inhaled or Ingested
Radionuclide. ORNL/N0REG/TM-84.
(CUM) contact name(s): Sullivan/R.E.
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Accession No. 14203000005
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: Plutonium Air Inhalation Dose
(ACR) Acronym of Data Base or Model: PAID
(MED) Media/Subject of Data Base or Model: Radiation
UBS) Abstract/Overview of Data Base or Model: The model is designed
to calculate dose rates and doses resulting from the acute or
chronic lifetime inhalation or ingestion of tcansuranic
radio!sotopes.
(CTC) CONTACTS: R.E. Sullivan U.S. EPA, Office of Air, Noise, and
Radiatio Office of Radiation Programs, CSD
Loc: Crystal Mall #2 1921 Jefferson-Davis Buy. Ph: (703) 557-9380
Loc: Arlington, VA 22202
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-01-83
(CAP) Functional capabilities of model: The model is designed for
long-live parents or daughters. Only one daughter is permitted
and, uhile gastro-intestinal tract (GIT) and blood transfer
fractions are used, no time delay for either is included.
(ASM) Basic assumptions of no del: The model is, basically, a
combination of the International Commission on Radiological
Protection (ICRP) lung model and a standard organ model using
exponential retention functions. The resulting solutions are
analytical, requiring no numerical integration, and are obtained
rapidly and exactly for the times desired.
(IMP) Input to model: Input required: The acute or chronic intake,
deposition fractions for the lung compartments, the mass for post
blood organs and physical and biological half-lives, transfer
fractions, and average energies for the parent and daughter
isotopes.
(OUT) Output of model: Output is: For all input times, the dose rates
and doses for each lung compartment, including lymph nodes, and for
the reference organs. The values for the trachiobronchial
compartment due to clearance from the pulmonary are also given
explicitly.
(APP) Applications of model: Model has been used to calculate lung and
organ doses for transuranic, and other radioisotopes. Used
primarily by ORP/EPA.
(BOV) Computational system requirements - Hardware: Mainframe IBM
360/370 ;Printer any Standard model
(LUG) Computational system requirements - Language(s) used: Fortran
(QSK) Computational system requirements: Operator Knowledge/Skills: Pro
graiming
(KEF) References - User manuals, documentation, etc.:
Sullivan, R.E., 1977, PAID: A Code for
Calculating Organ Doses Due to the Inhalation and
Ingestion of Radioactive Aerosols. ORP/CSD-77-4.
(CUM) Contact name(s): Sullivan,R.E.
(COR) Contact organization: U.S. EPA, Office of Air, Noise, and
Radiation, Office of Rad
(80R) Responsible Organization: Office of Air, Noise and
Radiation.Office of Radiation Programs.Criteria and Standards
Division.
1247
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Accession No. 14203000005 (cont)
1248
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Accession Ho. 14203000006
.- I-gJ-f
for radionuclide chains subsequent to deposition can be calculated
by providing a set of ingrowth factors. Air concentrations of
short-lived radon-222 progeny are calculated in working level units
for a splclfIII Salue of equilibrium. Output for DARTAB is in an
unformatted file. The basic calculational methodology is that of
ilKS-II with modifications for area sources, radon progeny
conceptions, terrestrial ingrowth for radionuclide chains and an
1249
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Accession Mo. 14203000006 (cont)
updated food pathway model.
(IMP) Input to nodel: Model inputs include: grid size values; wind
data; stack or area source data; radionuclide release rates,
deposition and settling velocities, scavenging rates, and decay
constants; arrays of neat animals, dairy cattle, crop areas, and
population data for each grid location, fraction of each food
category consumed from outside the assessment area, fraction of
that consulted food produced Hi thin the assessment area which is
produced of the grid location, ingestlon, agricultural model
parameters, ingestion rates by food category, inhalation rate;
radionuclide decay and environmental removal rate constants soil to
vegetation, intake to meat, and intake to milk conversion factors,
radionuclide chain ingrowth factors, clearance class, and gastro
intestinal absorption fraction*
(OUT) Output of model: Printed outputs available include: predicted
air concentrations; dry and wet deposition rates for each location
and radionuclide; ground-level Chl/Q for each location by
radionuclide; agricultural and population data for each grid
location; list of nuclide Independent variables; list of computer
totals of population, food production, and food consumption for
assessment area; list of nuclide dependent data for each nuclide;
individual or population weighted concentration and intake rates
for each location by nuclide, radon-222 progeny concentration for
each location; dose summaries (supplementary * not used for
AIRDOS-EPA/DARTAB assessments). An unformatted file is created of
concentration and intake data for each location to be used with
OARTAB for a dose and risk assessment.
(APP) Applications of model: This model provides a means for the
radiological assessment of radionuclides released to the
atmosphere. It has been used by EPA and the Oak Ridge National
Laboratory for this purpose. The model is generally used in
conjunction with DARTAB for dose and risk assessments.
(RON) Computational system requirements - Hardware: Mainframe IBM 360,
370 or equivalent ;Printer 132 position 1
(LNG) Computational system requirements - Language(s) used: Fortran IV
(H extended)
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? HO
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Physical
(TME) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: 1, 3, 4
(AR) Area where sample was collected: level or gently rolling terrain.
(RUG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
Begovlch, C.L., E. C. Schlatter, S.Y. Qhr,
K.R. Eckerman, 1980. DARTAB: A Program to Combine Airborne
Radionuclide Environmental Exposure Data with Dosimetric and
Health Effects Data to Generate Tabulations of Predicted Impacts.
ORHL-5692 (To be published).
Mo77 Moore, R.E., 1977. The AIRDOS-II Computer Code for
1250
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Accession Ho. 14203000006
-------
Accession No. 14205000903
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Exposure Rates Over Uranium Bearing
Soils As Function of De
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Radiation
(ABS) Abstract/Overview of Data Base or Model: Analytical model of
exposure rates at ground level and at one meter above ground from
all nuclides of the Uranium 238 decay chain (assuming equilibrium)
uniformly distributed throughout a slab of finite thickness
(variable to infinity, if required) covered with a slab of
overburden of finite thickness (variable to zero, if desired); both
slabs being of infinite areal extent. The model is based on
results obtained by means of a computer implemented technique (not
a program) described (along with the resulting model) in "Basic
Technique and Models for Calculating Exposure Rates Over Uranium
Bearing Soils," by George V. Qksza-Chocimowski, U.S. EPA, Las Vegas
Facility, to be published In 1981.
(CTC) CONTACTS: George V. Oksza-Chocimowski U.S. EPA, Office of
Radiation Vegas Facility
Loc: P.O. Box 18416 Ph: (702) 798-2446
Loc: Las Vegas, NV 89114
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-18-83
(CAP) Functional capabilities of model: The model describes exposure
rates, as described in 1), as function of tiio variables - thickness
of uranium-bearing soil slab and depth of overburden slab. No
limitations have been observed, although a simplified version of
the model (also in cited publication) is expected to apply to
depths of cover no smaller than 1 centimeter and no greater than
200 centimeters. A maximum error of +/- 4% with respect to results
obtained by H.L. Beck (used in "Guidance") has been observed.
(ASM) Basic assumptions of model: The model is based on results
obtained via computer employing the following: 1) Taylor's Buildup
Factor parameters and attenuation coefficient for water (the latter
adjusted for soil density). 2) Berger's coefficients (limited to
producing a maximum exposure rate term, in conjunction with
Taylor's parameters. 3) Curve-fitting equations for all relevant
coefficients, as functions of energy. Basic assumptions included
infinite areal extent of slabs, equilibrium conditions, homogeneous
distribution, similarity of soil and cover properties, flat
interfaces, no radon emanation and absence of soil moisture.
(INP) Input to model: The mathematical model required two variables as
input:
1) Thickness of uranium-bearing soil slab
2) Thickness of overburden slab
A maximum exposure rate has been incorporated into the model,
obtained by the sane basic techniques which produced the results on
which the model is based. However, the maximum exposure or
exposure rate is independent of the model, and can be replaced by
any required quantity, as additional input.
(DOT) Output of model: Exposure rates, at ground level or one meter
above ground level are the outputs of this model
1252
-------
Accession No. 14205000903 (cont)
(APP) Applications of model: The model can be applied to uranium mill
tailings pile/ uith Minor adjustment in the maximum exposure rate,
including cases uith radon penetration of the pile cover Material.
(HDH) Computational system requirements - Hardware: Calculator
(LUG) Computational system requirements - Language(s) used: English
(OSK) Computational systea requlreaents: Operator Knowledge/Skills: kno
ulecge of exponentials and logarithms
-------
Accession No. 14205000904
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Generalized Model of the
Time-Dependent Weathering Half-Lif
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Air ;Radiation
(ABS) Abstract/Overview of Data Base or Model: The Generalized Model
of the time-dependent weathering half-life of the resuspension
factor (for contaminants from soil) is an analytical aodel
describing the changes in weathering "half-life" or "half-tine" as
a function of time and of local conditions, represented as initial
and final resuspension factors observed or expected at a given
locality. The corresponding tine-dependent resuspension factor is
obtained by Modifying an exponential decay function by means of the
above time-dependent half-life. The model was published in 1977 as
"Generalized Model of the Time-Dependent Meathering Half-Life of
the Resuspension Factor," by George ?. Oksza-Chocimowski, Technical
Note ORP/LV-77-4.
(CTC) CONTACTS: George V. Oksza-Chocimouski U.S. EPA, Office of
Radiation Programs, Las Vegas Facility
Loc: P.O. Box 18416 Ph: (702) 798-2446
Loc: Las Vegas, NV 89114
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-18-83
(CAP) Functional capabilities of model: The model describes the
increase in "half-life" or "half-time" and corresponding decrease
of the resuspension factor, as function of time (days), for any set
of conditions characterized by initial resuspension factors as high
as 10-(2) m-(l) and final resuspension factors as Ion as 10-(13)
m-(l), with any combination of factors between these limits, with
the provision that the initial resuspension factor must be at least
one order of magnitude greater than the final resuspension factor.
The model conforms to empirical models obtained by various
investigators for specific conditions. Neither the "half-life" nor
the corresponding resuspension factor model is readily integrable
by analytical methods, and integration requires numerical
techniques.
(ASM) Basic assumptions of model: The model is based on the
assumptions that empirically observed "half-times" of resuspension
from soil at various locations, noted to increase with increasing
time following pollutant deposition, represent the "weathering
effect" whereby pollutant particles gradually lose their facility
to be resuspended, and that this rate of increase with time of the
"tice-dependent half-time" will approach asymptotically a value
corresponding to a constant final resuspension factor
characteristic of the location of interest. The model represents a
curve-fit to data obtained by various investigators.
(INP) Input to model: Input to the model includes observed and/or
expected initial and final resuspension factors for a given area.
Once these initial and final conditions have been set, time (in
days) is used as the independent variable.
(ODT) Output of model: The model preduces a resuspension factor. Both
the "half-time" and resuspension factors models are continuous
1254
-------
Accession No. 14205000904 (cont)
functions of tine and can be graphed, but are not readily
integrable except by numerical nethods.
(APP) Applications of model: Both the models of the time-dependent
half-time of the resuspension factor and that of the corresponding
tiae- dependent resuspension factor may be useful criteria in
determining the extent to which the tine dependent behavior of
various resuspension factor models conforms to reasonable
expectations. Given a set of initial and final resuspension
factors, the model permits estimating the time interval required to
approach the latter value to a degree required by the user.
(HDW) Computational system requirements - Hardware: Calculator
(LN6) Computational system requirements - Language(s) used: English
(OSK) Computational system requirements: Operator Knowledge/Skills: kno
uledge of exponential functions and logarithms
(OAQ) Model reviewed and approved by OAQPS? NO
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Negligible
removal
(THE) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20)
(AR) Area where sample was collected: level or gently rolling terrain.
(REF) References - User manuals, documentation, etc.:
"Generalized Model of the Time-Dependent Weathering
Half-Life of the Resuspension Factor,** George V.
Oksza-Chociraowski, Technical Mote ORP/L?-77-4, February 1977,
U.S. EPA, Office of Radiation Programs, Las Vegas Facility,
Las Vegas, Nevada 89114
(CUM) Contact name(s): Oksza-Chocimouski,G.
(COR) Contact organization: U.S. EPA, Office of Radiation Programs,
Las Vegas Facility
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Radiation Programs.Office of Radiation
Programs, Las Vegas Facility.
1255
-------
Accession No. 14206000904
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Health Risk Model for Shallow Land
Disposal of Lou-Level Ra
(ACR) Acronym of Data Base or Model: PRESTO
(MED) Media/Subject of Data Base or Model: Air ;Radiation ;Ground
Migration ;Water
(ABS) Abstract/Overview of Data Base or Model: The Health Risk Model
for Shallow Land Disposal of Low-Level Radioactive Haste (PRESTO)
is a generic simulation nodel which will analyze the potential
environmental impact and health risk froa the shallow land disposal
of low-level radioactive waste (LLH). The model will consider
waste disposal "system" which includes the waste disposed of at the
facility, the method of emplacement, the meteorology, the
hydrogeology, release mechanisms, environmental pathways from the
facility, receptors, and will calculate the amount of radioactivity
released over time and in space, individual and population doses,
and individual and population health risks. The model is to
estimate the health risks from several different shallow land
disposal methods (usually from 0 to 50 meters depth) and be
sufficiently flexible to take into account different hydrogeologic
and meteorologic settings and changes in engineering design. The
purpose of the model is to identify changes in benefits (i.e.,
reduction in health risk) from disposing of LLH by different
methods to support cost- benefit analyses and development of a
generally applicable environmental standard for the disposal of
LLW. The model is under development now and is to be operational by
the end of FY 1982. PRESTO also has potential application to the
analysis of amount of contaminant released and health risk from the
shallow land disposal of hazardous waste(s) if the appropriate
hydrogeocheaical and health risk data are available for the
hazardous waste(s) of concern.
(CTC) CONTACTS: Jon Broadway U.S. EPA, Eastern Environmental
Radiation Fa Loc: 1890 Federal Drive Ph: (205) 534-7615
Loc: Montgomery, Alabama 36109
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-13-83
(CAP) Functional capabilities of model: IN DEVELOPMENT - NOT COMPLETE
(ASM) Basic assumptions of model: IN DEVELOPMENT - NOT COMPLETE
(IMP) Input to model: IN DEVELOPMENT - NOT COMPLETE
(OUT) Output of model: IN DEVELOPMENT - NOT COMPLETE
(APP) Applications of model: PRESTO will be used by ORP to support the
development of an environmental standard for the disposal of LLW
and for making benefit-cost comparisons of various shallow land
disposal method such as engineered surface storage, sanitary
landfills, shallow land disposal, and Intermediate depth disposal*
It could also be used by other Federal agencies and industry check
whether proposed or exising disposal facilities would meet EPA's
LLH standard. Also, it has potential application to analysis of
health risk from shallow land disposal of hazardous wastes if
appropriate hydrogeochemical and health risk data is available for
the hazardous uaste of concern.
(HDH) Computational system requirements - Hardware: Mainframe IBM 370
1256
-------
Accession No. 14206000904 (cont)
System
(LNG) Computational system requirements - Language(s) used: Fortran IV
(H)
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming IBB OS JCL
(ATP) Air Models - Type of wo del: Gaussian dispersion
(OAQ) Kodel reviewed and approved by OAQPS? NO
(PHP) Production method of primary pollutant in aodel: Primary
(emitted directly into atmosphere and ground Hater)
(MPR) Process used to remove pollutant from atomosphere: Physical and
chemical
(TME) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: limited area
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(WTP) Water Models - Type of model: Water run-off
Ground water
(ENV) Environment(s) to which model applies: Lake ;Stream/river
;Non-point
(CQN) Processes and constituents included in model: Erosion and
sediment ;Toxic chemicals ;Hydrology ^Hydraulics
(CPL) Complexity level of model: one dimensional ;siaplifled
(RBF) References - User manuals, documentation/ etc*:
ORHL/TM-7943
(CNM) Contact name(s): Broadway,J.
(COR) Contact organization: U.S. EPA, Eastern Environmental Radiation
Facility
(ROR) Responsible organization: Office of Air, Noise and
Radiation.Office of Radiation Programs.Eastern Environmental
Radiation Facility.
1257
-------
Accession Ho. 14401200001
(DQ) Date of Questionalre: 12-02-82
(HAM) Kane of Data Base of Model: Cash Flow Model (Railroads)
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Hoise
(ABS) Abstract/overview of Data Base or Model: The cash flow Model
estimates the present discounted value of each firm's future cash
flov streao. To deterBine this the net north of each railroad fir«
is subtracted fron the ? present value of future cash flow. The
•odel yas developed by contractor in order to perform the economic
analysis for the railroad regulation. To date the nodel is in the
hands of the contractor and not available for EPA's use. The nodel
was implicitly developed through contract funding. At a later date
the BOdel may become available to EPA.
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy and
Evaluation,! Office of Air, Roise and Radiation! Loc: 401 M Street,
S.V., Washington, D.C. 20460 PH: (202) 382-7758
(STA) Data Base status: Operational/ Ongoing
(DP) Date of fora completion: 12-13-82
(CAP) Functional capabilities of model: Two versions of the aodel
exist. They support different revisions of proposed railroad
regulations.
(ASM) Basic assumptions of model: N/A
(HDW) Computational system requirements - Hardware: Mainframe Not yet
determined ;Disc storage Not yet determine
(LNG) Computational system requirements - Language(s) used: Fortran
(REF) References - User manuals/ documentation, etc.:
Hone to date.
(CUM) Contact name(s): Robert C. Rose
(COR) Contact organization: O.S. EPA, Office of Policy and
Evaluation,! office of Air, Hoise and Radiation, 401 M St., S.H.,
Washington, D.C. 20460 (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1258
-------
Accession No. 14401200002
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Econometric Impact Model
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Over view of Data Base or Model: The Econometric Inpact
Model provides generalized econometric forecasts of a specified
industry. It has been applied to light-duty trucks. Forecasts
Price, Output, Employment, and Energy effect associated with noise
impact emissions. Based on two modules. The affected industry
module uses econometric analysis and the module for the rest of the
economy uses input-output analysis.
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy and
Evaluation, Office of Air, Nois Loc: 401 M Street, S.H.,
Washington, D.C. 20460 (202) 382-7758*
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-13-82
(CAP) Functional capabilities of model: See "Model Overview" section.
(ASM) Basic assumptions of model: See "Model Overview" section.
(INP) Input to model: Input data are data on sectors of industry/
elasticities, and trend projections. The model uses 1967
input-output table of U.S. economy, energy and employment models,
and final demand model.
(OUT) Output of model: The model's output is changes in Output,
Employment, and Energy consumption by the industrial sector.
(APP) Applications of model: The model was developed and is operated
by Research Triangle Institute.
(HDH) Computational system requirements - Hardware: Mainframe IBM 360
(LNG) Computational system requirenents - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;economics
(REF) References - User manuals, documentation, etc.:
References not yet available.
(CNH) Contact name(s): Robert C. Rose
(COR) Contact organization: U.S. EPA, Office of Policy and Evaluation,
Office of Air, Noise, Radiation 401 M Street, S.W., Washington,
D.C. 20460 (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1259
-------
Accession No. 14401200003
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Decision Model
(ACR) Acronym of Data Base or Model: RDM
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The Decision Model
permits analysis of the benefits and costs of noise regulation. It
elucidates proninant regulatory options according to tine-phased
implementations, uniform annualized costs, average annual
individual benefit metrics by baseline impact, change in input and
output from the "Health and Welfare Model.'1
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy and
Evaluation, Office of Air, Hois Loc: 401 M Street, S.W.,
Washington, D.C. 20460 Ph: (202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of fora completion: 12-13-82
(CAP) Functional capabilities of model: The Decision Model computes
all possible combinations of a given product's subcategories,
applicable standards, and lead-times, and calculates costs and
benefits for each such combination, it then draws a curve
combining a sub-set of these combinations similar to Pareto
optlmality conditions.
(ASM) Basic assumptions of model: Contact Mr. Rose for a description
of the basic assumptions of this model.
(IHP) Input to model: Machine Type Growth Rates for Equipment Types
Hoise Levels - pre and post - Regulation D&M Costs/Yr. of
Timestream Prices Equipment Life Cycles Capital Investment Costs
Plant Closings Unemployment Output froa EPA Health and Welfare
Models Population data of Regulated Models and Costs of Regulation
(OUT) Output of Bodel: Benefit summary measures (cumulative benefit,
average benefit, discounted benefits). Option Cost measures,
(cumulative cost, average cost, discounted costs), Manufacturer
cost summary measures (capital investment, average and cumulative,
discounted), and Unemployment summary measures (cumulative,
average).
(APP) Applications of model: The model has been used in noise
regulation review to bring to management's attention cost effective
options in a product regulation.
(HDtf) Computational system requirements - Hardware: Mainframe IBM 370
;Printer any model
(LHG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming
(REF) References - User manuals, documentation, etc.:
Contact Mr. Rose for references describing
the model.
(CRN) Contact name(s): Robert C. Rose
(COR) Contact organization: U.S. EPA, Office of Policy and Evaluation,
Office of Air, Hoise, and Radiation,* 401 M Street, S.W.,
Washington, D.C. 20460 (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1260
-------
Accession No. 14401200004
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Strategy Model
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: Determines the minimun
cost nix of regulations to achieve level of reduction In noise or
gives a cost Unit to achieve the maximum reduction of noise*
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy and
Evaluation, Office of Air, Nois 401 M Street, S.H., Washington,
D.C. 20460 (202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-13-82
(CAP) Functional capabilities of model: The Strategy Model prioritizes
the cost effectiveness of a given number of products being
considered for noise regulations.
(ASM) Basic assumptions of nodel: Contact Mr* Rose for a description
of the basic assumptions of this model*
(INP) Input to model: Costs of regulation of different types of
machines at various noise levels and the benefits of regulation are
the inputs to this model*
(DOT) Output of model: Listing of different regulations to achieve a
certain fixed level of noise reduction are the outputs of the model
(APP) Applications of nodel: The model has been used in noise
regulation review to bring to management's attention cost effective
options in a set of products regulations.
(HDV) Computational system requirements - Hardware: Mainframe IBM 370
^Printer any nodel
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: pro
granming ;economics
(REF) References - User manuals, documentation, etc.:
Contact Mr. Rose for references describing
the model.
(CNM) Contact name(s): Robert C. Rose
(COR) Contact organization: U.S. EPA, Office of Policy & Evaluation,
Office of Air, Noise and Radiationf 401 M Street, S.M., Washington,
D.C. 20460 (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1261
-------
Accession No. 14401200005
CDQ) Date of Questionaire: 12-02-82
(HAM) Kane of Data Base of Model: Pricing Model
(ACR) Acronym of Data Base or Model: TPRICES
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: Determines price
increase of projected sales of a given nuaber of products or
sub-products needed to cover increased cost of noise regulation
over some long period of time.
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy S.
Evaluation Office of Air, Moise a 401 M Street, S.H., Washington,
D.C. 20360 Ph: (202) 382-7758
(STA) Data Base status: Operational/Ongoing
(OF) Date of fora completion: 12-13-82
(CAP) Functional capabilities of Model: The Pricing Model gives to
management the increased prices of products to be regulated so that
the economic impacts of the regulations can be measured prior to
promulgation.
(ASM) Basic assumptions of model: Contact Mr. Rose for a description
of the basic assumptions of this model.
(INP) Input to model: Inputs to the model are baseline production,
component cost, development cost, testing cost and enforcement cost.
(DOT) Output of model: Original and revised sales, price increase, and
percent price increases are produced by the model.
(APP) Applications of model: The model has been used in noise
regulation review to bring to management's attention cost effective
options to proposed regulations.
(HDW) Computational system requirements - Hardware: Mainframe IBM
370/168 ^Printer any model
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
graiming ;economics
(REF) References - User manuals, documentation, etc.:
Contact Mr. Rose for references describing
the model.
(CNM) Contact name(s): Rose,R.
(COR) Contact organization: O.S. EPA, Office of Policy & Evaluation,
Office of Air, Hoise and Radiation, 401 M Street, S.W., Washington,
D.C. 20460 (202) 382-7758
(ROR) Responsible Organization: Office of Air, Moise and
Radiation.Office of Policy and Evaluation.
1262
-------
Accession No. 14402000001
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Truck Mounted Solid Haste Compactors
Health and Welfare Mod
(ACR) Acronym of Data Base or Model: TNEW2
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: Computes health and
welfare impacts of noise of truck-Mounted solid waste compactors
(TMSWC) for baseline condition and selected regulatory options;
computes health and welfare benefits to the year 2000 in terns of
noise impact reduction for the various options. Impacts analyzed
include:
1) Generalized adverse response (annoyance)., 2) Indoor and
outdoor speech interference, 3) Sleep disturbance, and 4) Sleep
awakening.
(CTC) CONTACTS: R. C. Rose U.S. EPA, Office of Air, Noise and
Radiation Loc: 401 M Street S.W., Washington, D.C. 20460 Ph:
(202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-15-82
(CAP) Functional capabilities of model: Note: No user's or
programmer's documentation available* (See References).
(ASM) Basic assumptions of model: The fractional impact functions used
are those accepted as of mid-1977 and described in the Regulatory
Analysis (EPA-550/9-79-257).
(INP) Input to model: The data base built into the model include:
1) Population distribution by five types of residential areas,
2) Population distribution of the 3 types of compactors,
3) Frequency and duration of refuse collection activities for
the 5 types of residential areas, 4) Typical time-history of noise
for a refuse collection cycle, and 5) Sound propagation function
for the various types of residential areas. Energy average noise
level (L*s for each regulatory option considered, and Effective dates.
(OUT) Output of model: Health and welfare baseline impact and Impacts
under various regulatory options (including iapact reductions).
(APP) Applications of model: Used for calculation (computation) of
health and welfare impact of refuse vehicle noise in regulatory
analysis of truck-mounted solid waste compactor noise regulation.
(HDW) Computational system requirements - Hardware: Mainframe IBM
370/168
(LNG) Computational system requirements - Language(s) used: Fortran I?
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(REF) References - User manuals, documentation, etc.:
Truck-mounted Solid Waste Compactor Regulatory
Analysis (EPA-550/9-79-257) and GE-Tempo draft final report
on Health and Welfare Analysis of TMSWC.
(CHM) Contact narae(s): Rose,R.C.
(COR) Contact organization: U.S. EPA, Office of Air, Noise and
Radiation Ph: (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1263
-------
Accession No. 14402000001 (cont)
1264
-------
Accession No. 14402000002
(DQ) Date of Questionairc: 12-02-82
(NAM) Name of Data Base of Model: Construction Site Health and Welfare
Model
(ACR) Acronym of Data Base or Model: CSM
(MED) Pedia/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The model computes
noise impacts on the population surrounding the more than two
million construction sites that are active every year in the U.S.
in addition, the relief accruing to the various populations
affected by construction site noise as a result of individual and
combined regulations for one or more of the operational types of
equipnent is analyzed.
(CTC) CONTACTS: R. C. Rose U.S. EPA, Office of Air, Noise and
Radiation
Washington, D.C. 20460 22202 Ph: (202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-15-82
(CAP) Functional capabilities of model: Not all elements of the model
are functional. The complete model contains the following:
1. Time stream
2. Curve
3. Output of impact reduction
4. Distribution of Level Weighted Population (LHP) and
population exposed with respect to 1 decible (Idb) level of noise
day-nigh average (Ldn) intervals.
5. Usage factors
6. Duration of construction site activity
7. Daytime population density shifts.
(ASM) Basic assumptions of model: There are no basic assumptions.
(IMP) Input to model:
1) Noise levels of construction equipment, 2) Equipment usage
factors, 3) Number of construction sites by the type of site and by
population density category, 4) Population density, and 5) Duration
of construction activity by phase of construction
(OUT) Output of model:
1) Yearly L 2) Equivalent sound level 3) Population exposed, 4)
Level weighted population (LHP), 5) Sound propagation distance to
criteria levels, and 6) Relative Change in Impact (Relative Lwp,
LliP<2>/LWP Applications of model: No outside use allowed unless designated
!•••' Office jf Air, Noise and Radiation.
(HDH) Computational system requirements - Hardware: Mainframe IBM
370/168
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(REF) References - Oser manuals, documentation, etc.:
No references are available.
(CNM) Contact name(s): Rose, R.C.
(COR) Contact organization: U.S. EPA, Office of Air, Noise and
Radiation Control 22202 Ph: (202) 382-77
(ROR) Responsible Organization: Office of Air, Noise and
1265
-------
Accession Io. 14402000002 (cont)
Radiation.Offlee of Policy and Evaluation.
1266
-------
Accession No. 14402000003
(DQ) Date of Questions!re: 12-02-82
(RAN) Name of Data Base of Model; Railroad Health and Welfare Model
(ACR) Acronym of Data Base or Model: RMBA 79N3
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The model estimates
national noise exposure due to railroad operations*
(CTC) CONTACTS: R. C. Rose U.S. EPA, Office of Air, Noise and
Radiation Loc: 401 M St., S.W., Washington, D.C. 20460 Ph: (202)
382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-15-82
(CAP) Functional capabilities of nodel: There are no provisions for
time stream variations.
(ASM) Basic assumptions of model: Refer to "Description of Railroad
Health and Welfare Model" for basic assumptions of the model.
(INP) Input to model: Input to the model consists of 1) Engine noise
from locomotives and snitch engines, 2) Retarder squeal, 3)
Refrigerator car noise, 4) Car-coupling noise, 5) Load cell
testing, repair facilities, and locomotive service area noise,
6) kheel/rall noise, and 7) Horns, address systems.
(DOT) Output of model: National assessment of level weighted
population (LWP) and describes annualized benefits (health and
welfare, rather than economic) of decreased noise production.
(APP) Applications of model: Model has been used for internal
EPA-office of Noise Abatement and Control decision-making purposes,
(HDV) Computational system requirements - Hardware: Mainframe IBM 370
;Disc storage one unit ;Printer any model
(LNG) Computational system requirements - Language(s) used: ANSI
Fortran
(REF) References - User manuals, documentation, etc.:
1. Description of Railroad Health and Welfare
Model
2. Users* Manual for the Railroad Health and Welfare Model
3. Programmer's Manual for the Railroad Health and Welfare
Model
(CUM) Contact name(s): Rose, R.C.
(COR) Contact organization: U.S. EPA, Office of Air, Noise and
Radiation Control Ph: (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radlation.Qffice of Policy and Evaluation.
1267
-------
Accession No. 14402000004
(DQ) Date of Questionaire: 12-02-82
(SAM) Rame of Data Base of Model: Truck Transport Refrigeration Dnit
Health and Welfare Model
(ACR) Acronym of Data Base or Model: TTRU
(MED) kedia/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The model computes
health and welfare impacts' of noise of Truck Transport
Refrigeration Units (TTRU) for baseline condition and selected
regulatory options. lapacts analyzed include: 1) Generalized
adverse response (annoyance),
2) Indoor and outdoor -speech interference, 3) Sleep disturbance,
and 4) Sleep awakening.
(CTC) CONTACTS: R. C. Rose U.S. EPA, Office of Air, Noise and
Radiation Loc: 401 M Street S.W., Washington, D.C. 20460 22202
ph: (202) 382-7758
(ST-A) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-15-82
(CAP) Functional capabilities of model: See "Model Overview" for
functional capabilities of the model.
(ASM) Basic assumptions of model: The fractional impact functions used
are those accepted as of mid-1977, and are described in the draft
final report on TTRU by GE-Tempo.
(OUT) Output of model: The data bases built into the model include:
1) Population distribution by 5 types of residential areas, 2)
Distribution of the population of various types of TTRU,
3) Usage patterns and noise histories of TTRU in various types
of residential areas, and 4) Sound propagation function for the
various types of residential areas. Characteristic noise level of
each type of TTRU, Regulatory noise limits, and Effective dates for
each option. OUTPUT: The model's output consists of the health and
welfare baseline impact and impacts under various regulatory
options (including impact reductions).
(APP) Applications of model: The model is used in the analysis of
health and welfare Impact of truck transport refrigeration unit
•noise in pre-regulatory studies.
(HOW) Computational system requirements - Hardware: Mainframe IBM
370/168 -
(LNG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system* iSequfrements: Operator Knowledge/Skills: Eng
ineering
(REF) References - User manuals/ documentation, etc.:
Truck transport Refrigeration Unit Background
Document (draft) and GE-Tempo draft final report. Health and
Welfare Analysis of TTRU.
(CNM) Contact name(s): Rose/ R.C.
(COR) Contact organization: U.S. EPA, Office of Air, Hoise and
Radiation Control 22202 Ph: (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1268
-------
Accession No. 14402000005
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Lawnmower Health and Welfare Model
CACR) Acronym of Data Base or Models LAW 1 & LAW 2
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Over view of Data Base or Model: This model consists of
two programs which are interrelated. Lawn 1 sets up a data file
containing input data required by Lawn 2. Latin 2 calculates and
displays hearing loss, speech interference/ annoyance, and impacts
for a given year, regulatory option or base line/ and aachine type.
(CTC) CONTACTS: R. c. Rose o.s. EPA, Office of Air, Hoise and
Radiation Loc: 401 M St., S.W., Washington, D.C. 20460 22202
Phs (202-Y) 382-7758
CSTA) Data Base status: Operational/Ongoing
(DP) Date of for* completion: 12-15-82
(CAP) Functional capabilities of model: There is no published
documentation of the functional capabilities for these aodels. The
programs are self explanatory for the user and a program listing is
available with explanatory comments.
(ASM) Basic assumptions of model: The models are based on an
analytical development by a contractor, Booz, Allen, and Hamilton,
Inc.
(INP) input to model: Lawn 1: 1) Mo. of geographical regions, 2) Ho.
of cachine categories, 3) Mo. of regulatory options for each
machine category, 4) Mo. of tiers of regulated machines per option,
5) year in uhich tier goes into effect, 6) Regional growing season
in weeks per year, 7) Regional cutting rates in no. of cuts per
week, 8) Regional machine distribution,
9) Sales figures for each category of mower by year (that
is, 1964-2000), 10) Retirement rate for each category of mower by
age since sale, 11) Machine sound level at the bystander and
operator, 12) Usage duration description in hours per cut, 13)
Maximum length of lawn mower use for each category, 14) Machine
market saturation, 15) Mean blade width in inches, 16) Cutting
efficiency, 17) Mower ground speed in miles per hour, 18) Lot site
per grass area proportionality for lawn areas (less than or equal
to 20,000 square feet, greater than 20,000 square feet, less than
or equal to 34,000 square feet, greater than 34,000 square feet),
19) Open space proportionality,
20) Household size coordinates (year, size), 21) loisa
propagation effects (dB per doubling of distance), and 22)
Attenuation due to walls and windows of buildings. Lawn 2: Choice
of 1) Impact, 2) Year, 3) Regulatory option, and 4) Type of machine.
(OUT) Output of model: The output of the Model is a summary sheet of:
1) Environmental noise impact (EMI) for each geographical region,
2) Ambient or background level, 3) National EMI, and 4)
Population by distribution of levels.
(APP) Applications of model: Lawn 1 and Lawn 2 are used in determining
health and welfare impact of lawnmower noise and benefits (impact
reduction) for various regulatory scenarios in pre-regulatory
studies.
(HDW) computational system requirements - Hardware: Mainframe Data
General Nova 2/10
1269
-------
Accession No. 14402000005 (cont)
(LNG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements: Operator Knouledge/Skills: Eng
ineering
(REF) References - User manuals, documentation/ etc.:
Assessment of Environmental Noise Impact of
Noise Regulations for Power Launmouers. Booz Allen Draft
Final Report, EPA Contract Mo. 68-01-3239, March 1978.
(CNM) Contact nane(s): Rose,R.C.
(COR) contact organization: U.S. EPA, Office of Air, Noise, and
Radiation control 22202 Ph: (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1270
-------
Accession No. 14402000006
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Air Conditioner Health and Me If are
Model
(ACR) Acronym of Data Base or Model: AGO Thru ACS
(MED) Pedia/Subject of Data Base or Model: Noise
(ABS) Abstract/overview of Data Base or Model: This model is Bade up
of 9 interrelated programs. The output fron one is used as input
for another* AGO through AC4 generate annoyance and hearing loss
impacts. ACS through ACS generate sleep and speech interference
impacts.
(CTC) CONTACTS: R. C. Rose U.S. EPA, Office of Air, Noise and
Radiation Loc: 401 M Street S.V., Washington, D.C. 20460 22202
Ph: (202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-15-82
(CAP) Functional capabilities of model: Interrelationship of programs
needs to be understood from report cited below. Execution of
program is self-explanatory. Program listing and explanatory
comments given in Appendix of report cited in "Reference" section.
(ASM) Basic assumptions of model: See model references for full
explanation of assumptions of the model.
(IMP) Input to model: Model input is: 1) Room correction factor, 2)
Sound power level, 3) Distance to source in feet, 4) Distance
between building fronts, 5) Room constant for courtyards, 6)
Location factor, 7) Choice of impacts, 8) Years, and 9) Regulatory
option
(DOT) Output of model: The outputs of the model are: 1) Environmental
Noise Impact (END, 2) Ambient or background level 3) National ENI,
4) Population by Distribution of Levels, and 5) National Noise
Impact Index (LHP).
(APP) Applications of model: This model is used in pre-regulatory
studies of air conditioner noise, determining baseline health and
welfare impact and impact reductions for various regulatory
scenarios.
(HDH) Computational system requirements - Hardware: Mainframe Data
General Nova 2/10
(L»G) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(REF) References - User manuals, documentation, etc.:
Noise Impact Analysis of Room and Residential Air
Conditioners. Cambridge Collaborative Draft Final Report
EPA Contract So. 68-0 No. 68-01-4411, July 1978.
(CNM) Contact name(s): Rose,R.C.
(COR) Contact organization: U.S. EPA, Office of NoiseAir, Noise and
Radiation Control 22202 Ph: (202) 382-
CROR) Responsible Organization: Office of Air, Moise and
Radiation.Office of Policy and Evaluation.
1271
-------
Accession No. 14402000007
(DQ) Date of Questionaire: 12-02-82
(NAM) Nave of Data Base of Model: Chain Saw Health and Welfare
(ACR) Acronyn of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The Chain Sau Health
and Welfare Model calculates individual noise exposures, cumulative
exposure, fractional impacts and other related quantities.
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Air, Noise and
Radiation Loc: 401 M St., S.W., Washington, D.C. 20460 22202
Ph: (202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-15-82
(CAP) Functional capabilities of »odel: The model and documentation of
all of Its functional capabilities is not complete.
(ASM) Basic assumptions of Model: The fractional impact functions are
those accepted as of mid-1978, as outlined in the levels document
and other publications by the Scientific Assistants staff.
(INP) Input to model: Data bases include:
1. Population trends of chain sans by types
2. Estimates of chain saw usage by type
3. Estimates of chain sau noise emissions
4. Sound propagation functions for areas in which chain saws
are used.
5. Fractional impact functions
inputs are: Regulatory scenarios (noise level Units and effective
dates).
(OUT) Output of nodel: Output consists of health and welfare IMPact of
chain saw noise for baseline condition and various regulatory
scenarios; also, reductions in impact for the regulatory scenarios.
(APP) Applications of model: The Model is used in pre-regulatory
studies of chain saw noise, to provide estimates of health and
welfare impacts and benefits.
(HOW) Computational system requirements - Hardware: Mainframe IBM 370
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(REF) References - User Manuals, documentation/ etc.:
References are still under development
(CUM) Contact name(s): Rose,R.C.
(COR) Contact organization: U.S. EPA, Office of Air, Noise and
Radiation Control 22202 Ph: (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Offlee of Policy and Evaluation.
1272
-------
Accession No. 14402000008
(DQ) Date of Questionaire: 12-02-82
(NAM) Eame of Data Base of Model: Consumer Product Health and Welfare
Model
(ACR) Acronym of Data Base or Model: CONSUMER PRODUCT MODEL
(M5D) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The Consumer Product
Health and Welfare Model calculates individual noise exposures,
cumulative exposure/ fractional inpacts/ and other related
quantities.
(CTC) CONTACTS: R. C. Rose U.S. EPA, Office of Air, Noise and
Radiation Loc: 401 M St., S.W., Washington, D.C. 20460 Ph:
(202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-15-82
(CAP) Functional capabilities of model: Documentation will be complete
by the end of FY 81.
(ASM) Basic assumptions of model: See reference for documentation of
basic assumptions.
(JNP) Input to model: The input to the model is the product noise
emissions. Use data, Noise isolation data between product use and
affected populations/ and description of persons affected.
(OUT) Cutout of model: This model predicts sound levels at listener's
position.
(APP) Applications of model: The model is used in pre-regulatory
studies of possible noise standards and/or noise labeling
regulations for consumer products, determining health and welfare
impact of noise of various products - one of the factors in
selecting priorities for labeling.
(HDW) Computational system requirements - Hardware: Mainframe IBM 370
(LNG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational systea requirements: Operator Knowledge/Skills: Eng
ineering
(REF) References - User manuals, documentation, etc.:
Consumer Product Noise: A Basis for Regulation.
Heissler, Zerdy/ and Revoile, National Bureau of Standards,
NBSIR 74-606, Nov., 1974.
(CNM) Contact narae(s): Rose,R«C.
(COR) Contact organization: U.S. EPA, Office of Air, Noise and
Radiation (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1273
-------
Accession No. 14402000009
(00) Date of Questionaire: 12-02-82
(RAN) game of Data Base of Model: Urban High Density Traffic Noise
Impact Model
(ACR) Acronym of Data Base or Model: CATNIP
(NED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The Urban High Density
Traffic Noise Impact Model developed to assess the effects of urban
traffic noise on people. Present or future vehicle noise
regulatory scenarios can be specified to evaluate the potential
benefits of such regulations on the noise climate in densely
populated areas.
(CTC) CONTACTS: R. C. Rose O.S. EPA, Office of Air, Noise and
Radiation Loc: 401 M St., S.H., Washington, D.C. 20460 Ph: (202)
382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of fora completion: 12-15-82
(CAP) Functional capabilities of model: See "Model Overview" section
above and documentation
(ASM) Basic assumptions of model: See reference given for description
of todel's basic assumptions
(INP) Input to model: Input to the model consists of: 1) Baseline
vehicular noise levels by vehicle and by 4 operating modes,
acceleration, deceleration, cruise (various speeds), and Idle, 2)
Regulatory scenario; 3) Fraction of time each vehicle spends in
each operating mode (DVP); 4) traffic volume for each vehicle class
by time period (DVP); 5) Vehicle speeds for each vehicle type
(DVP); 6) Street widths; 7) Block length (DYP); 8) sidewalk width
(DTP); 9) Building configuration; 10) Presence or absence of
building opposite (DVP); 11) Average building height; 12) Optional
enclosed streetuay; 13) Pedestrian flow volume; and 14) Population
inside buildings. DVP means default value provides.
(OUT) Output of model: The model's output consists of the equivalent
noise level (Leg) at a defined point and urban traffic noise levels
and resultant health and welfare Impact (LHP).
(APP) Applications of model: Model is available for state and local
government use.
(BDH) Computational system requirements - Hardware: Mainframe
Unspecified
(LNC) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(REF) References - user manuals, documentation, etc.:
Development of an Urban High Density Traffic loise
Impact Model, Volume I: Model Description and Computation
Procedures.
(CNN) Contact name(s): Rose,R.C.
(COR) Contact organization: O.S. EPA, Office of Air, Noise and
Radiation, 401 M Street S.V., Washington, D.C
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Offlee of Policy and Evaluation.
1274
-------
Accession No. 14402000010
(DQ) Date of Questionaire: 12-02-82
(BAM) Kane of Data Base of Model: National Roadway Traffic Noise
Exposure Model
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The nodel
deterministically estimates extent and severity of noise exposure
in the U.S. due to motor vehicles operating on the national roaduay
network. The model is used primarily for assessing the national
impact of various noise control strategies/ including source
control. The structure of the model is based on extensive roaduay
data, demographic data, and vehicle use and noise data. Time
series projections are also calculated on all tiae dependent
variables where data are available.
-------
Accession No. 14402000010 (cont)
(ROR) Responsible Organization: Office of Air, Noise and
Radiation,Office of Policy and Evaluation.
1276
-------
Accession No. 14403000106
(DQ) Date of Questionaire: 12-02-82
(NAN) Kane of Data Base of Model: Workplace Noise Evaluation Model
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: Model assesses the
occupational noise impact in industrial factory spaces. Model
determines the daily noise dose of exposure for each class of
production workers, and determines the contribution of each machine
to this dose. It will identify the benefits to be gained in terms
of reduced exposure from reducing noise levels of one or more
machines.
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy and
Evaluation, Loc: 401 K Street, S.W., Washington, D.C. 20460
Ph:« (202) 382-7758 Office of Air, Soise and Radiation
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 12-13-82
(CAP) Functional capabilities of model: A weighted sound level and
statistical confidence Units are calculated.
(ASM) Basic assumptions of model: . Worker activities can be
characterized by a common work assignment schedule. . Noise levels
generated by similar equipment is normally distributed. • Primary
contributor to no'ise exposure is the machine being operated by
operator in question. . Secondary sources are grouped into the
background level with appropriate ueighting factors. . Statistics
used to describe noise and work assignments worker job assignments
Number of workers Machinery noise levels at operator locations
(OUT) Output of model: The output of the model consists of: .
OSHA-personnel noise exposure by job description and industry .
Distribution of noise exposure by job description i.e. mean & worst
case . Rank ordering of noisy machines by contribution to noise
exposure . Calculation of minimum noise reduction requirements to
meet OSHA . Same for EPA except impact applies rather than exposure.
(APP) Applications of model: Model is in final review. The model will
support assessment and implementation of noise control programs at
specific plants and Health and Welfare analyses by Federal
Regulatory and Enforcement Agencies.
(HDW) Computational system requirements - Hardware: Mainframe IBM 360
(LNG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(CNM) Contact name(s): Robert C. Rose
(COR) Contact organization: U.S. EPA, Office of Policy & Evaluation,
Office of Air, Noise and Radiation, 401 M Street, S.H., Washington,
D.C. 20460 (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1277
-------
Accession No. 14403000107
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Urban Traffic Noise Prediction Model
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/QvervieM of Data Base or Model: Model based on City of
Portland blank configurations, classes of vehicles operating in the
city, and related noise sources. Model has been verified through a
noise survey.
-------
Accession No. 14403000107 (cont)
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1279
-------
Accession No. 14403000108
-------
Accession No. 14403000108 (cont)
Rad1ation.Office of Policy and Evaluation.
1281
-------
Accession No. 14403000109
(DQ) Date of Questionaire: 12-02-62
(RAM) Name of Data Base of Model: Highway Noise Control Strategy
Assessment Model
(ACR) Acronym of Data Base or Model: HINCSAM
(M£D) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The model simulates the
year to year change
distribution of a noise source subject to regulations. User
specifies original distribution, regulations, and microscopic
effects of regulations. Any seguence or combination of new product
standards and in-use standards »ay be specified. Energy average
noise level is computed for each year.
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 12-13-82
(CAP) Functional capabilities of model: The model can handle any
original distribution, described by a histogram tilth a
user-specified bin width. User specifies regulations as any
combination of the two regulation types. Details of regulatory
effects, i.e. compliance ratios and distribution of
modified/redesigned products are user-specified.
(ASM) Basic assumptions of model: No assumptions other than
representation of distributions by histograms and annual (rather
than continuous) updating.
(IHP) input to model:
specifying year, regulatory level, compliance ratio, and
distribution of modified/redesigned models for each regulation .
Replacement/retirement data for each year
(OUT) Output of »odel: Energy average noise level each year. Also can
output modified distribution for each year.
(APP) Applications of model: Has been used by Kyle in various projects
for EPA to evaluate motor vehicle regulations.
(HDH) Computational system requirements - Hardware: Mainframe Xerox
940 or IBM 370 ;Disc storage varies, depend! Printer line printer
or terminal
(LUG) Computational systen requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Kno
uledge of mathematical basis of model Robert C. Rose U.S. EPA,
Office of Policy and Evaluation, Office of Air, Noise & Radiation,
401 M Street, S.H., Washington, D.C. 20460 (202) 382-7758
(REF) References - User manuals, documentation, etc.:
NA Kodel for the Prediction of Highway Noise and
Assessment of strategies for its Abatement Through Vehicle
Noise Control", Hyle Research Report MR 74-5, September 1974.
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Offlee of Policy and Evaluation.
1282
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Accession No. 14403000110
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Regulation Impact Model
(ACR) Acronym of Data Base or Model: REGIM
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Over view of Data Base or Model: The model projects
ten-city data prepared by
totals. Future growth, by city size, is based on census department
projections. User specifies a year and noise level changes for
automobiles and trucks at high and low speeds. Program returns
total population exposed to decibel level (day-night average) (Ldn)
between 60-65 decibels, 65-70 decibels, 70-75 decibels, and above
75 decibels.
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 12-13-82
(CAP) Functional capabilities of model: The model can handle effective
vehicle level changes from *3 to 150 decibels (automobiles) and +3
to -16 decibels (trucks), years from 1974 to 2000, Inputs are in
decibels, outputs in numbers of people.
(ASM) Basic assumptions of model: Projects ten city data to nation, as
described in cited reference. Assumes 87/13 day/night traffic
split. Inputs are cases to be handled - year and vehicle noise
level changes re: baseline. Noise level change inputs are outputs
from HINCSAM
-------
Accession lo. 14403000111
(D
-------
Accession Ho. 14403000112
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Highway Construction Noise
Evaluation and Mitigation
(ACR) Acronym of Data Base or Model: HIMCOM
(MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: The model allous the
determination of noise levels arising from highway construction
activities. It is site specific, that is applying to one given
construction site, it Is a tool for assessing the potential noise
impact from construction activities, and for supporting the
development and implementation of abatement measures.
Specifically, the relative importance of a given piece of equipment
to the noise levels at a boundary can be determined. Also, noise
reduction benefits to be gained from various control measures,, such
as equipment substitution and movement, or installation of
barriers, can be readily calculated.
(CTC) CONTACTS: Robert C. Rose, U.S. EPA, Office of Policy and
Evaluation, Office of Air, Noise and Radiation. 401 M Street,
S.W., Washington, D.C. 20460 Ph: (202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DP) Date of form completion: 12-13-82
(CAP) Functional capabilities of model: The model's functional
capabilities are: . full scale . time averages . units-set by user
e.g. feet, decibels, cubic feet
(ASM) Basic assumptions of model: The model's basic assumptions are: .
Noise propagation-algorithias for point, line, area noise sources •
Noise levels versus equipment operations . Equipment capacities .
Equip duty cycles . Cycle averaged Noise levels
(INP) Input to model: 1. Name of various construction equipments
2. Model of equipment
3. Equipment location
4. Activity level-No, of vehicles operating, hours of operation
per day
5. Task inter-relationships
6. Site Geometry e.g. barrier locations
(OUT) Cutput of model: Outputs of the model consist of:
1. Decibel equivalency (level of noise) at each observer
2. Decibel equivalency (level of noise) contribution from each
activity or task
(APP) Applications of model: Model is in final review. It would be of
use to construction contractors in construction project planning,
and various governments for environmental planning and enforcement
(HDW) Computational system requirements - Hardware: Mainframe IBM 360
;Disc storage 3 drums ^Printer any model
(LNG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements? Operator Knowledge/Skills: Non
-technical user
(REF) References - User manuals, documentation, etc.:
User Manuals and scientific supporting documentation
Hill be available on completion of the project
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1285
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Accession Mo. 14403000112 (cont)
1286
-------
Accession Mo. 14403000113
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Air Pumping Noise Model for Tires
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The model's primaiy use
is to determine the noise caused by air pumping for heavy duty
truck tires.
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy and
Evaluation/ Office of Air, Noise and Radiaion, 401 M Street, S.W.,
Washington, D.C. 20460 (202) 382-7758
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-13-82
(CAP) Functional capabilities of model: The model's function is to
determine what effect air pumping of a heavy duty truck tire has on
the noise output of the tire
(ASM) Basic assumptions of model: None identified to date.
(IMP) Input to model: Under development
(OUT) Output of model: Under development
(HDW) Computational system requirements - Hardware: Mainframe PDF 11
;Disc storage not known as yet ;Magnetic ta Printer any model
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knouledge/Skills: Eng
inhering
(REF) References - user manuals, documentation, etc.:
Documentation to be developed
(CSM) Contact name(s): Robert C. Rose
(COR) Contact organization: U.S. EPA, Office of Policy and Evaluation,
Office of Air, Noise and Radiation. 401 M Street, S.W.,
Washington, D.C. 20460 (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1287
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Accession No. 14403000114
(DQ) Date of Questionaire: 12-02-82
(RAM) Name of Data Base of Model: Fleet Noise Level
(ACR) Acronym of Data Base or Model: FNL
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: The aodel calculates
noise level of aircraft fleet based on reference noise levels for
each type of aircraft in the fleet and weighted by the number of
operations conducted by each type. It could be used for fleets
other than aircraft (e.g., trucks or busses)
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy and
Evaluation/ Office of Air, Noise and Radiation, 401 M Street, S.H.,
Washington, D.C. 20460 Ph: (202) 382-7758
(STA) Data Base status: Operatlonal/Ongiong
(OF) Date of forn completion: 12-13-82
(CAP) Functional capabilities of Model: Model includes FAR 36 aircraft
noise levels and CY 1979 departures.
(ASM) Basic assumptions of model: Energy averaging of noise levels.
(INP) Input to model: Noise levels of particular types of aircraft
when performin specified operations and number of annual departures.
(OUT) Output of model: Fleet noise level in decibels is the model's
output*
(HDH) Computational system requirements - Hardware: IBM 370 at NCC
(OSK) Computational system requirements: Operator Knouledge/Skills: Eng
ineering
(REF) References - User manuals, documentation, etc.:
Documentation to be complete by end of FY 81.
(CNM) Contact name(s): Robert C. Rose
(COR) Contact organization: U.S. EPA, Office of Policey & Evaluation;
Office of Air, Noise and Radiation, 401 M Street, S.V., Washington,
D.C. 20460 (202) 382-7758
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1288
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Accession No. 14403100509
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Computer Assisted Procedure for the
Design and Evaluation of Wastewater Treatment Facilities
(ACR) Acronym of Data Base or Model: CAPDET
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/overview of Data Base or Model: The CAPDET program
represents a Mstate-of-the- art" technique for preparation of
facilities Planning level cost estimates. The basic objective of
CAPDET is to provide a screening tool capable of simultaneously
designing a number of vasteuater treatment system alternatives to
meet specified effluent criteria and then ranking these
alternatives on the basis o£ their cost. Conveyance costs are not
considered. The CAPDET program will design four different
uastewater treatment schemes. A treatment scheme consists of
blocks on the liquid line, the secondary sludge line/ and the
primary sludge line. A block is a treatment process location. The
CAPDET user specifies or selects the treatment process desired for
each block. Up to ten alternative treatment processes may be used
in each block or treatment process location.
(CTC) CONTACTS: Wen H. Huang O.S. EPA (WH-595) Facility Requirements
Division LOG: 401 M Street., S.W., Washington, D.C. 20460 PH:
(202) 382-7288
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-16-83
(CAP) Functional capabilities of model: The program contains a library
of unit processes which may be selected by the user and placed in
one of the blocks to treat a waste stream. The CAPDET model
contains 79 liquid stream processes and 14 sludge stream processes.
Three land treatment alternatives as well as many of the advanced
wasteuater treatment (AWT) processes are included. CAPDET also
contains a separate set of treatment processes particularly
applicable to small flows of under 500,000 gallons per day, such as
package plants and lagoon upgrading processes. In addition, a user
specified process allows the user to add innovative, alternative,
or other processes not included In the current CAPDET library.
(ASM) Basic assumptions of model: This program allows the user to
specify various types of unit processes for the treatment of
uasteuaters. A treatment process consists of one or more of these
unit processes. The combination of unit processes into treatment
processes is accomplished automatically by the CAPDET program.
Treatment processes may then be assembled in sequence to form a
treatment scheme. A maximum of four treatment schemes may be
specified. Each scheme contains a liquid line, a secondary sludge
scheme. Each block may contain up to 10 alternative treatment
processes. This program is designed for planning tool and used for
selecting a best planning approach.
(INP) input to model: Input to the CAPDET program is the description
of the wasteaater characteristics. This input must include at
least the average design flow rate. The program contains built-in
or "default" data for all other uasteuater characteristics. These
are mid-range values normally found in domestic uastevaters and
include biochemical oxygen demand, suspended solids concentration,
1289
-------
Accession Ho. 14403100509 (cent)
temperature, concentrations of nutrients, and maximum and minimum
flov rates as ratios of the average flow. The CAPDET user needs to
specify only the uasteiiater characteristics which are different
than the default values. The program will assign the default
values to all the uasteuater characteristics remaining unspecified.
(OUT) Output of aodel: THO types of output nay be obtained. The first
output lists the cost data for up to the 100 nost cost-effective
trains. The user nay also specify which of these trains (or all if
he chooses) he desires to investigate further. The second output
gives detailed unit process design information for all chosen
trains. Optionally, this output nay include the quantities of
•aterials required for construction.
(APP) Applications of model: This model provides a Beans for analysis
of the sizing of unit process units and material quantities.
Further the cost estimate Hill be made based on material quantity
and sizing of unit processes. The purpose of this analysis is to
aid in selecting the most cost effective processes and the most
cost effective processes and the most cost effective process trains
in facility planning processes. CAPOET has been widely used by
U.S. governmental agencies, states, facility owners, engineering
communities and general public.
(HOW) Computational system requirements - Hardware: Mainframe IBM 370
and comparable computers ; Disc Storage (or tape) 400,000 words
core storage. ; Magnetic Tape Storage (or disk) ; 132 Position Line
Printer ; Card Reader/Punch or Tape/Disc (input)
(LN6) Computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Com
puter Programming ; Engineering
(CON) Processes and constituents Included in model: Temperature ;
Biological Effects ; Hydraulics ; Quality Processes
(CPL) complexity level of model: Steady State Mass Balance ; Simplified
(REF) References - User manuals, documentation, etc.: 1. CAPOET
Program/ User's Guide and 2. CAPDET Design Manual
(CNM) Contact name(s): Wen H. Huang
(COR) Contact organization: U.S. EPA (HH-595) Facility Requirements
Division
(ROR) Responsible Organization: Office of Hater.Office of Hater
Programs Operations.Facilities Requirements Division.
1290
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Accession No. 14404000909
(DQ) Date of Questionaire: 12-02-82
{STATUS) Status of entry: Inactive
(NAM) Name of Data ease of Model: Acoustic I»pact Prediction Model:
Forest Facility Noise Mod
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: This model is an
engineering and psychological model to aid in laying out forest
facilities as a function of noise-producing elements.
(CTC) CONTACTS: Robert C. Rose U.S. EPA, Office of Policy and
(ANR-445) 401 M St., S.V., Washington, D.C. 20460 Ph: (202)
382-7758
(STA) Data Base status: Operational/Ongoing
(DP) Date of form completion: 01-14-83
(CAP) Functional capabilities of model: The model is based on a
detectability node! developed for the ailitary. The accuracy of
the model is heavily dependent on the input which may be accurately
measured on generally estimated*
(ASM) Basic assumptions of model: The model is based on personal
annoyance. The detectability and annoyance factors are considered
in utilizing the model results in laying out a forest/park for its
many appropriate uses.
(INP) Input to model: . Input data required: . sound source location •
listener atmospheric temp . mean atmospheric temp . mean elevation
. mean wind direction . sound source description . background sound
source description . highest barrier: - height, distance .
predominant vegetation type . recreation opportunity . mean wind
angle . day/night . mean relative humidity . exp. sky coner . Hind
speed
(DOT) Output of model: The output product of this model is the
detectability and annoyance levels of noise in Decibles (d).
(APP) Applications of model: Used by the 0.S. Park Service, Forest
Service, State and local parks to lay out a forest/park area that
each visitor can find the type of noise environment they effect.
(HDH) Computational system requirements - Hardware: Calculator
(REF) References - User manuals, documentation, etc.:
Predicting Impact of Noise on Recreationists -
Project Record - April 1980 - USDA - Forest Service - 8023 -
1202 1202
(CNM) Contact name(s): Rose,R.
(COR) Contact organization: U.S. EPA, Office of ^Policy and
Evaluation, ONAR, (202) 382-7758.
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1291
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Accession No. 14404000910
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Noise Optimization Models
(ACR) Acronym of Data Base or Model: NQIZOP
(MED) Media/Subject of Data Base or Model: Noise
(ABS) Abstract/Overview of Data Base or Model: NCIZOP provides a tool
for rational and objective decision staking in policy and regulatory
activity concerning a community's environmental acoustic noise from
all sources. The objective is to distribute a given hypothetical
SUB of money in such a way as to obtain the greatest possible
benefit in terns of reduction of the number of people adversely
affected by environmental noise*
(CTC) CONTACTS: R. Rose U.S. EPA, Office of Policy and Evaluation,
OANRft Loc: 401 M Street, S.W., Washington, D.C., 20460
(STA) Data Base status: Operational/Ongoing
(DF) Date of fora completion: 01-14-83
(CAP) Functional capabilities of model: The noise levels in the
community are defined by the metric: Equivalent Sound Level,
L. This level Is the energy average of the momentary
A-weighted levels measured over a specified period of time. The
A-neight equivalent sound levels assumed in this manual for Zero
Impact (Nil (see par* 3)) = 0 by land use and for day use are:
Single Family Duelling - 54 Multi-Family Duelling = 59 Commercial
= 59 Industrial = 70 Schools = 50
Hospitals = 50 The sound levels for night use are 8
decibels less for single family duellings, 13 for multi-family
dwellings and same for all the other type of land use (schools are
not applicable).
(ASM) Basic assumptions of model: The inherent non-linearity of the
mathematics that describe the basic problem of this model presents
the use of well developed methods of linear algebra* A
sophisticated searching algorithm is utilized in the program to
find the nost cost-effective Hay of distributing the given sum of
money among the alternative noise abatement measures. A quantity is
defined that rates the quality of the environmental noise climate
of a community. This quantity is called the Noise Impact Index
(Nil), it is derived by: Nil - Number of people in a Given
Community Impacted by Noise Total number of people in the community
The Noise Climate quality improves with declining Nil. In
operations research language, the Nil is the objective function
(i.e., it is the single function to be minimized by the judicious
distribution of a given sum of money). In choosing the best set of
abatement measures NOIZOP spends money in incremental amounts until
a preset maximum is reached.
(INP) Input to model: Input to the model includes: community is
divided into cells (land use which is homogeneous in terms of land
use, population and noise level); cell population, cost to relocate
cells, floor area of building in each cell, noise measurements for
up to 20 sources (obtained from Acoustical Survey), countermeasures
(alternative noise control measures) - costs and decibel reductions
possible, and land use areas affects; and a total societal budget
for the noise program*
(OUT) Cutput of model: The main output is a list of total expenditures
1292
-------
Accession No. 14404000910 (cont)
oDtimi™ti«nf°r each abate»«nt "easure; these are displayed as the
!»P^H?tion process proceeds in discrete steps. The total
tS rf J f It brok«« down by costs to the local government and to
asso 1 t d 1 society. Accompanying this cost breakout is the
adverse effects of noise on people in the community. The Nil is
t«CthfS8f *? an optinal fashion as more and more money is allocated
«*rh *H ? *measure" The assoclated degree of implementation for
eacn abatement measure is also given. Each abatement measure must
^De evaluated for political, social or legal feasibility.
T* *pP*ications of model: Model has been used for Allentoun, Pa.
I*,!* i* *ued fo*Kansas City, Mo. (data collection phase has
started). The model is used in a research and demonstration
project for developing a community noise assessment program, which
^Cf } e Qulet Community Program. A necessary linkage to this
model is the Community Noise Assessment Program's Acoustical Survey
Social Science Workbook (Attitudinal survey).
(HDh) Computational system requirements - Hardware: Mainframe Univac
1110 ;Dlsc storage ;Magnetic tape storage o
5n2S! Computational system requirements - Language(s) used: Fortran
(05K) Computational system requirements: Operator Knowledge/Skills: Pro
granting
(REF) References - user manuals, documentation, etc.:
Strategy Guidelines (NOIZOP)
Community Noise Countermeasure,
Cost Effectiveness, Optimization
Computer Program (NOIZIP), Vol. 1
Volume 1 of above
Volume 3 of above.
(CUM) Contact name(s): Rose,R.
(COR) Contact organization: U.S. EPA, Office of "Policy and
Evaluation, OANR
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Policy and Evaluation.
1293
-------
Accession No. 14404000912
(DQ) Date of Questionalre: 12-02-82
(HAM) Name of Data Base of Model: Hunan Activity Profiles
(ACR) Acronym of Data Base or Model: Hone
-------
Accession Ho. 14404000912 (cont)
1975. These data bases are described in detail within the user
•anual. The only inputs required by the user is the specification
of the type of analyses desired and level of detail*
(OUT) Output of model: Six forms of tabular output at level of detail
as specified by the user.
(APP) Applications of model: We are only now in the process of
finalizing the set up on the EPA computer system.
(HDW) Computational system requirements - Hardware: Mainframe IBM 370
;Disc storage not yet known ;Printer any m
(LNG) Computational system requirements - Language(s) used: Fortran
(REF) References - User manuals, documentation, etc.:
Wyle Research Report MR 79-39, "Analysis of Human
Activity Profiles - User Manual, prepared for the U.S.
Environmental Protection Agency, Contract No. 68-01-4922,
July 1980
(CNM) Contact narae(s): Rose,R.
(COR) Contact organization: U.S. EPA, Office of Policy and Evaluation,
OANR (202) 382-7758
(ROR) Responsible Organization: Office of Air/ Noise and
Radiation.Office of Policy and Evaluation.
1295
-------
Accession No. 14504000911
(DQ) Date of Questionaire: 12-02-82
(HAM) Mace of Data Base of Model: The Plume visibility Model
(ACR) Acronym of Data Base or Model: PLUYUE
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The design objective of
the model is to calculate visual range reduction and atmospheric
discoloration caused by the plumes consisting of primary
particulates, nitrogen oxides, and sulfur oxides emitted by a
single emissions source. The model is designed to predict the
impacts of a single emissions source on visibility in Federal Class
I areas. The model is a refinement of the plume model developed in
1978 publications EPA450/378110a, b, c available from NTIS and PB
293118 set. PLUVUE predicts the transport/ atmospheric diffusion,
chemical conversion, optical effects and surface deposition of
point source emissions. The model uses the Gaussian formulation for
transport and dispersion. The spectral radiance (intensity of
light) at 39 visible wavelengths is calculated for views with and
without the plume; the changes in the spectrum are used to
calculate various parameters that predict the perceptibility of the
plume and contrast reduction caused by the plume. PLUYUE performs
plume optics calculations in a plume-based mode and an observer-
based node.
(CTC) CONTACTS: James Dicke EPA/Office of Air Quality Planning and
Stand Loc: RTP, MC 27711 Ph: (919) 541-5681
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-06-83
(CAP) Functional capabilities of model: The model calculates four
perception parameters useful for predicting visual impact:
reduction in visual range, contrast of the plume against a viewing
background at the 0.55 micrometer wavelength, the blue-red ratio
(color shift) of the plume, and the color change perception
parameter triangle E (L*a*b*). Yislbility impairment is caused by
changes in light intensity as a result of light scattering and
absorption in the atmosphere. Impairment can be qualified once the
spectral light intensities or radiance has been calculated for the
specific lines of sight of an observer at a given location in an
atmosphere with known aerosol and pollutant concentrations. PLUfDE
is a near-source plume visibility model, e.g., within 200 km of the
source.
(ASM) Basic assumptions of model: PLUYUE is based on Gaussian
atmospheric dispersion assumptions, contains Briggs' plume rise
equations, allows for surface deposition during the day and
contains atmospheric chemistry modules that allow for conversion of
nitric oxide to nitrogen dioxide and sulfur dioxide to sulfate
aerosol. Scattering and absorption properties are calculated for
particles and gases. For nitrogen dioxide the absorption at a
particular wavelength is a tabulated function multiplied by the
concentration. The effect of particle size on the wavelength
dependence of the scattering coefficient and the phase function is
calculated and the Mie equations are also solved. Calculation of
light Intensity follows from the radiative transfer equation.
(IMP) Input to model: The input data required for PLUVUE include: wind
1296
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Accession No. 14504000911 (cont)
speed aloft/ stability category, lapse rate nixing depth, relative
humidity, sulfur dioxide, nitrous oxides and particulate emission
rates, stack gas parameters, stack gas oxygen content, ambient
temperature, anbient nitrous oxides, nitrogen dioxide, ozone and
sulfur dioxide concentrations, properties of background and eaitted
aerosols in two size nodes, background visual range, deposition
velocities for sulfur dioxide, nitrous oxides, coarse mode and
accumulation mode aerosol, UTM coordinates and elevation of the
source, UTM coordinates and elevation of the observer location.
(DOT) Output of model: The principal PLUVOE run output is the print
file written on logical unit six* All runs have the data tables
for the emissions source, meteorological and ambient air quality,
and background radiative transfer. Plot files can also be written
by PLOVUE. if a PLUVUE run is for either observer-based or
plume-based calculations, either an observer-based or a plume-based
plot file will be centered. These files are written on DISC
storage units.
(APP) Applications of model: PLUVUS has been used by EPA primarily in
a research mode and to provide estimates for hypothetical scenarios
such as power plant siting impact.
(HDW) Computational system requirements - Hardware: Mainframe Univac
1110 series ;Disc storage 25k ;Printer Syst System card reader
(LNG) computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
granming ;Engineering ;
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? OAQPS has reviewed this
model but made no recommendation
(PMP) Production method of primary pollutant in model: Secondary
(produced in atmosphere by chemical reactions)
(MPR) process used to remove pollutant from atomosphere: Combination
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: limited point (less than 10-20)
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: 1-100 km
(REF) References - User manuals/ documentation/ etc.:
EPA, User's Manual For the Plume Visibility
Model (PLUVUE), November 1980, EPA-450/4-80-032 (NTIS
#P881-163-297K
La timer, '-.A. et. al., The Development of Mathematical
.dels f : the Prediction of Anthropogenic Visibility
impairment. 1978, EPA 450/3-78-110a,b,c.
Latimer, D.A. Power Plant Impacts on Visibility in the
West: Siting and Emissions Control Implications. JAPCA,
Vol. 30, pp. 142-146, 1980.
Bergstrom, R.V., et. al., Comparison of the Observed and
Predicted Visual Effects Caused by Power Plant Plumes
Symposium on Plumes and Visibility, November 10-14,
1980, published in Atmospheric Environment/ 1981.
(CNM) Contact name(s): Dicke/J.
(COR) Contact organization: EPA/Office of Air Quality Planning and
Standards
1297
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Accession Mo. 14504000911 (cont)
(ROR) Responsible Organization: Office of Air/ Noise and
Radiation.Office of Quality Planning and Standards.Monitoring and
Data Analysis Division.
1298
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Accession No. 14504000924
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data ease of Model: Modified Rollback
(ACR) Acronym of Data Base or Model: ROLLBACK
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The Modified Rollback
Model is a computerized air quality si ml at ion model that has been
used for assessing the relative air quality impacts of alternative
control strategies which are national in scope. Air quality
projections for carbon monoxide and nitrogen oxides are aade using
the Morris-deNevers modified rollback equations. Ozone projections
are made using the Empirical Kinetic Modeling Approach (EKMA)
standard isopleth diagram. Emission inventory projections are made
using data on mobile and stationary source emission factors, YMf
growth rates/ and stationary source retirement rates, growth rates
and control efficiencies.
(CTC) CONTACTS: Warren P. Freas U.S. EPA, Office of Air Quality
Plannln Standards, Monitoring and Data Analysis Division
Loc: MD-14 Research Triangle Park Ph: (919) 541-5522
Loc: North Carolina 27711
(STA) Tata Base status: Operational/Ongoing
(Dp) Date of form completion: 01-06-83
(CAP) Functional capabilities of model: Modified Rollback can be used
to estimate changes in carbon monoxide (CO) and annual average
nitrogen dioxide (N0<2» levels due to assumed changes in CO and
N0 emissions, respectively. Changes in ozone air quality levels
are estimated using the standard isopleth diagram of EKMA. These
procedures are best used to compare the relative air quality
impacts of alternative area source control strategies. The model
requires county level, or larger, emissions inventories by major
source category.
(ASM) Basic assumptions of model: The simple rollback model is based
on the assumption that the air quality concentration of a pollutant
at a point is equal to the background concentration of that
pollutant and some linear function of the total emission rate of
that pollutant which influences the concentration at that point.
Modified Rollback uses the deNevers-Morris equations to account for
differing rates of growth/reduction in emissions from a number of
source categories. The model assumes that the spatial and temporal
distributions of emissions and the meteorological conditions remain
constant between the base year and the projection year. However,
for ozone projections, the model uses the standard EKMA isopleths
described in Reference 3.
(INP) Input to model: For each study area, the user must furnish data
on the base year air quality level; background concentration;
emissions, growth and retirement rates, and control efficiencies
for each major mobile and stationary source category and strategy
scenario. The air quality data Is typically obtained from the
Storage and Retrieval of Aerometrlc Data Base (SAROAD) and the
emissions data from the National Emissions Data System (REDS).
(OUT) Output of model: Output reports consist of individual source
area emissions inventories for the base year and each projection
year/strategy combination and air quality summary reports. The air
1299
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Accession No. 14504000924 (cont)
quality summary reports/ grouped by strategy, display the base year
air quality concentration and projection year air quality levels
and expected nuaber of violations of the National Aibient Air
Quality Standards (NAAQS) for each study area.
(APP) Applications of model: The Modified Rollback Model has been used
by EPA to evaluate the relative air quality impacts of revisions to
the automotive emission standards. Other applications include the
regulatory analyses conducted in association with the review of the
ambient air quality standards.
(HDH) Computational system requirements - Hardware: Mainframe IBM 360,
Onivac 1108 ;Printer 132 character line p Card reader/punch
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
grasming Engineering
(OAQ) Model reviewed and approved by OAQPS? Y.ES
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant fron atomosphere: Negligible
removal
(THE) Sample averaging time used: less than 24 hours ;more than 24
hours
(SRC) Source of pollutant: multiple point, limited area
(AR) Area where sample was collected: level or gently rolling terrain.
(RMG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
N. deNevers and J.R. Morris, "Rollback Modeling:
Basic and Modified," Journal of the Air Pollution Control
Association, ¥ol. 25, September 1975.
J. H. Wilson, Jr., "Methodologies for Projecting the Relative
Air Quality impacts of Emission Control Strategies," Presented
at the 71st Annual APCA Meeting, Houston, Texas, June 25-29,
1978.
Uses, Limitations and Technical Basis of Procedures for
Quantifying Relationships Between Photochemical Oxidants and
Precursors, EPA-450/2-77-021a, U.S. SPA, Research Triangle
Park, NC, November 1977.
(CNM) Contact name(s): Freas,U.P.
(COR) Contact organization: U.S. EPA, Office of Air Quality Planning
and Standards, Moni
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Quality Planning and Standards.Monitoring and
Data Analysis Division.
1300
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Accession No. 14504000925
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Kinetics Model and Ozone Isopleth
Plotting Package
(ACR) Acronym of Data Base or Model: OZIPP
(MED) Vedia/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The Kinetics Model and
Ozone Isopleth Plotting Package (OZIPP) computer program can be
used to simulate ozone formation in urban atmospheres. OZIPP
calculates maximum one-hour average ozone concentrations given a
set of input assumptions about initial precursor concentrations,
light intensity, dilution/ diurnal and spatial emission patterns,
trarsported pollutant concentrations/ and reactivity of the
precursor mix. The results of multiple simulations are used to
produce an ozone isopleth diagram tailored to particular cities.
Such a diagram relates maximum ozone concentrations to
concentrations of nonmethane organic compounds and oxides of
nitrogen, and can be used in the Empirical Kinetic Modeling
Approach (EKMA) to calculate emission reductions necessary to
achieve air quality standards for photochemical oxidants.
(CTC) CONTACTS: Gerald L. Gipson U.S. EPA/ Office of Air Quality
Plannin Standards/ Monitoring & Data Analysis Division
Loc: MD-14 Research Triangle Park Ph: (919) 541-5522
Loc: North Carolina
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-06-83
(CAP) Functional capabilities of model: The major function of the
OZIPP Model is to generate an ozone isopleth diagram representative
of a particular city. The diagram explicitly depicts maximum/
one-hour average concentrations of ozone occurring within or
downwind of a city as a function of precursor levels existing
within the city in the early morning. These diagrams are based on
mathematical simulations of ozone formation occurring during a day.
As such, the model is limited in applicability to ozone problems
within or immediately downwind of urban areas and cannot consider
the following: (1) rural ozone problems; <2) ozone problems
occurring in the early morning or at night; and (3) contributions
of single or snail groups of sources to ozone problems. The OZIPP
model is best used to study the effectiveness of areawide control
strategies in reducing peak/ one-hour average ozone concentrations
within or downwind of a city.
(ASM) Basic assumptions of model: The model underlying OZIPP is
similar in concept to a trajectory-type photochemical model which
simulates the formation of ozone from precursors within a migrating
column of air. A column of uniformly mixed air extends from the
earth's surface throughout the mixed layer. The height of the
column rises according to the diurnal variation in mixing height/
resulting in dilution of pollutants within the column and
entrainment of pollutants which were initially above the column.
As the column moves/ eaissions of fresh precursors are encountered.
The model mathematically calculates the formation of ozone within
the column as a function of time in accordance with a chemical
kinetic mechanism. The model employs a gear-type integration
1301
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Accession No. 14504000925 (cont)
scheme to solve numerically the set of differential evaluations
which describe the model assumptions. To generate an ozone isopleth
diagram, the model performs repeated simulations with differing
pollutant levels initially within the column. Using the results of
these simulations, a diagram is constructed which expresses the
calculated peak, one-hour average ozone concentrations as a
function of the initial precursor concentrations. The program
incorporates a hyperbolic spline interpolation scheme to construct
the graph.
(INP) Input to model: Data are supplied to the model to make an ozone
isopleth diagram specific to a particular city. These data
Include: latitude, longitude and time zone of the city; the day,
•onth and year; the minimum morning and maximum afternoon mixing
heights; sets of emission fractions which reflect the effect of
precursor emissions occuring throughout the day; and the
concentrations of ozone and precursor transported into the city.
Additional input parameters are supplied to control the generation
of the ozone Isopleth diagram (e.g., scales of the diagram, size of
the diagram, accuracy, interpolation smoothing, etc). All input
data are processed in a simple manner, and no extensive
computerized data base is required.
(DOT) Output of model: The primary output of the model is the ozone
isopleth diagram. The diagram is depicted on a line printer plot,
and can be generated as an option on a Calcomp Plotter. A report
is also produced which summaries the Input data and results of the
simulations that were performed to generate the diagram.
CAPP) Applications of model: The OZIPP Model has been used to generate
ozone isopleth diagrams to calculate emission reductions necessary
to achieve the ambient air quality standard for ozone. The model
was used by state/local air pollution control agencies as the basis
for estimating emission reductions for 1979 and 1982 submittals of
the State Implementation Plans.
(HDH) Computational system requirements - Hardware: Mainframe Univac
1100 ;Printer 132 position line printer ;Ca
(LNG) Computational system requirements - Language(s) used: Fortran
Calcomp Plotter (optional)
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;Engineering
(ATP) Air Models - Type of model: Numerical reactive
(OAQ) Kodel reviewed and approved by OAQPS? YES
(PMP) Production method of primary pollutant in model: Secondary
(produced in atmosphere by chemical reactions)
(MPR) Process used to remove pollutant from atomosphere: Chemical
(TME) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20)
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
Kinetics Model and Ozone Isopleth Plotting
Package (OZIPP), EPA-600/8/770014b, U.S. Environmental
Protection Agency, Research Triangle Park, NC, July 1978.
G. Z. Hhitten and B. Hugo, User's Manual for Kinetics Model
1302
-------
Accession No. 14504000925 (cont)
and Ozone Isopleth Plotting Package, EPA-600/8-78-014a,
U.S. Environmental Protection Agency, Research Triangle Park,
NC, July 1978.
Uses, Limitations and Technical Basis of Procedures for
Quantifying Relationships Between Photochemical Qxidants and
precursors, EPA-450/2-77-021a, U.S. Environmental Protection
Agency, Research Triangle Park, NC, November 1977.
(CNM) Contact name(s): Gipson,G.L.
(COR) Contact organization: U.S. EPA, Office of Air Quality Planning
Standards, Monito
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Quality Planning and standards.Monitoring and
Data Analysis Division.
1303
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Accession No. 14504000926
CDQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Industrial Source Complex Model
(ACR) Acronym of Data Base or Model: ISC
(MED) Media/Subject of Data Base or Model: Air
(ABS) abstract/Overview of Data Base or Model: The Industrial Source
Complex (ISC) Dispersion Model is a Gaussian plume model used to
evaluate the air quality impact of emissions from industrial source
complexes. The ISC Model consists of tuo computer programs, one
for short-term analyses and one for long-term analyses. The
short-term model program, ISCST, uses sequential hourly
meteorological data to estimate concentration or deposition
patterns from one hour to one year. The long-term model program,
ISCLT, uses statistical wind summaries to estimate seasonal and
annual concentration or deposition patterns. The ISC Model has
rural and urban options. Major features of the ISC Model program
are: (1) effects of aerodynamic building wakes and stack tip
downwash; (2) effects of variations In terrain height; (3) plume
rise due to momentum and buoyancy as a function of downwind
distance; (4) dispersion of emissions from stack area, line, and
volume sources where line sources are simulated by multiple volume
sources; (5) physical separation of multiple sources; (6)
time-dependent exponential decay of pollutants; and (7) effects of
gravitational settling and dry deposlton.
(CTC) CONTACTS: Joseph A. Tikvart U.S. EPA, Office Air Quality
Planning a Standards
Loc: MD-14 Research Triangle Park Ph: (919) 541-5561
Loc: North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-06-83
(CAP) Functional capabilities of model: The ISC Model programs are
written in FORTRAN IV and require approximately 65,000 UHIVAC 1110
computer words. The programs may be used on a medium to large IBM
or CDC computer system with little or no modification. The number
of sources and receptors are interdependent; however, 300 is the
maximum number of sources accepted, arbitrarily located. Receptors
can be specified on a polar or rectangular grid and Briggs* early
plume rise formulations, including the momentum terms, are used.
Deposition can be calculated or allowed for only over flat terrain.
The short-term program calculates values of average concentration
or deposition for time periods of 1, 2, 3, 4, 6, 8, 12, and 24
hours. Additionally, the ISCST may be used to calculate M-day
concentration or deposition values where the maximum value of N is
366 days. The units option allows the user to specify the input
emissions units and/or output concentration or deposition units.
Applications that do not require at least one of the ISC Model
features should utilize a less comprehensive computer model.
(ASM) Basic assumptions of model: Meteorological homogenity is assumed
following the conversion of surface wind-speed to that at plume
height. All plumes remain level, regardless of terrain elevation,
unless significant terminal fall velocity is specified. Emission
rates can be varied according to specified meteorological classes
or as a function of time (hour of day, season or month, or both).
1304
-------
Accession No. 14504000926 (cont)
A simple time-dependent exponential decay of the pollutant is
optional.
(IMP) Input to model: For ISCST meteorological data required are mean
«in€ speed and measurement height; average random flow vector/ wind
profile exponents*, ambient air temperature/ height of nixing
layer, Pasquill stability/ and vertical potential temperature
gradient*. These data may be input directly using the same
preprocessed meteorological data tape as the CRSTER Model or
alternatively input by card deck. For ISCLT, joint frequencies of
occurrence of wind speed and direction and stability are required.
Source data consists of emission rate (total emissions for
deposition); dimensions of stack/ building area or volume source;
effluent characteristics; surface reflection coefficients for each
settling-velocity category; receptor data; and receptor terrain
elevation data.
(OUT) Output of model: Output can be directed to a line printer and/or
magnetic tape. Five categories of printed output can be acquired
from ISCST; input source-receptor and hourly meteorological data
listings; concentration or deposition values calculated for any
combination of sources at all receptors for any specified day(s) or
time period; highest and second-highest such values; a maximum of
50 such values. ISCLT output provides input source-receptor and
meteorological data listings; long-term mean concentration or
deposition values calculated at each receptor for each source and
for combined emission sources; contributions of individual sources
to the maximum 10 such values calculated for the combined emission
sources or as contributed to user specified receptors.
(APP) Applications of model: The ISC Model is recommended for use in
air quality assessments of stack/ area and volume industrial
complex sources in urban and rural areas where short-term/ seasonal
and/or annual air quality concentration estimates of stable
pollutants are required. The source program f°r this dispersion
model is available as part of ONAMAP (Version 4), PB81-164600 for
$840 from Computer Products/ NTIS/ Springfield/ VA, 22161.
(REF) References - User manuals/ documentation/ etc.:
Industrial Source Complex (ISC) Dispersion Model
User's Guide/ Volume I; NTIS f PB 80-133044. Industrial
Source Complex (ISC) Dispersion Model User's Guide/ Volume II
(Appendices A through I; NTIS # PB 80-133051.
Magnetic Tape of programs; NTIS # PB 80-133036.
(CNM) Contact name(s): Tikvart/J.A. .
(COR) Contact organization: U.S. EPA, Office Air Quality Planning and
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Quality Planning and Standards.Monitoring and
Data Analysis Division.
1305
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Accession No. 14504000927
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Air Quality Display Model
(ACR) Acronym of Data Base or Model: AQDM
(NED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The Air Quality Display
Model (AQDM) is a three-dimensional, steady-state air model used in
the evaluation of area sources in "rough" urban areas. The AQDM
treats the physical processess of both transport and diffusion.
The model is appropriate for examining areas ranging in size from
small localized vicinities to Hhole urban areas, and it has a
long-term application for the evaluation of seasonal or annual air
quality variations*
(CTC) CONTACTS: Joe Tlkvart O.S. EPA, Office of Air Quality Planning
and Standards/ MD-14, RTP
Loc: Research Triangle Park Ph: (919) 541-5561
Loc: North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-06-83
(CAP) Functional capabilities of model: The AQDM model does not
simulate chemical processes, but it does treat the physical
processes of transport and diffusion in "rough" urban areas. It
uses a one layer discretization and a user-specified 14 x 14 grid.
A 225 grid receptor with 12 additional receptor points is also
user-specified. The fixed-point meteorological data does not
describe micrometerorological variations within the city, nor does
it describe "urban heat island" air circulations. The model has a
sensitivity to effective stack height, wind speed, and wind
stability. It is limited to S0<2> and suspended participates, and
it is designed for annual average and seasonal applications.
(ASM) Basic assumptions of model: The AQDM is a deterministic model
that uses an analytically Integrated solution technique. It
assumes a steady state for air quality constituents, and assumes
Gaussian diffusion and homogeneous, discrete atmospheric conditions.
(INP) Input to model: Input to the model for initial set-up and
calibration include: point and area residual discharges and stack
parameters which consist of height, diameter, temperature, and exit
velocity; meteorological data containing wind speed and direction,
stability, and mixing height; and several ambient air concentration
measurements. Model data requirements for verification incorporate
the above meteorological data and ambient air concentration
measurements.
(OUT) Output of model: Output for the model include ambient
concentration values given at grid locations, ground level, or
other user-selected points. These values are given in the form of
tabular printouts or card decks for use with CALCOMP or SYMAP plot
programs. Some of the special features of the AQDM output are its
statistical output routines, receptor contribution analysis, and
calibration subroutine.
(APP) Applications of model: AQDM can be used in the evaluation of
area sources in "rough" urban areas for seasonal or annual air
quality variations. This model has been supereeded by such models
as CDM/CDMQC and RAM; thus AQDM Is primarily of historical
1306
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Accession No. 14504000927 (cont)
interest. TECHNICAL COUTACT: Joseph Tikvart U.S. Environmental
Protection Agency Air and Hater Programs Mutual Building 411 V.
Chapel Hill Street Durham, NC 28801 FTS 629-5262 COM 919/541-5262
(HDU) Computational system requirements - Hardware: Mainframe IBM
360/40 or equivalent ;Dlsc storage 300K bytes
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ^Engineering ^Mathematical ability and experienc the model
or access to consultations
(ATP) Air Models - Type of model: Gaussian dispersion
(PMP) Production method of primary pollutant in model: (emitted
directly Into atmosphere).
(MPR) Process used to remove pollutant from atomosphere: Physical
(TME) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: multiple point and area
(AR) Area where sample Has collected: urban areas.
(REF) References - User manuals, documentation, etc.:
Croke, E.J., et al., "Regional Implementation
Plan Evaluation Process,** ANC/ES-DA-001, Argonne National
Laboratory, Argonne, Illinois, (July 1970).
National Air Pollution Control Administration, "Air
Quality Display Model," PB 189 194, Washington, D.C.,
(November 1969).
(CNM) Contact name(s): Tikvart,J.
(COR) contact organization: U.S. EPA, Office of Air Quality Planning
and Standards, MO-1
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Quality Planning and Standards.Monitoring and
Data Analysis Division.
1307
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Accession No. 14504000928
(DQ) Date of Questionaire: 12-02-82
(MAM) Kane of Data Base of Model: Complex Terrain Gaussian Plume
Dispersion Algorithm
(ACR) Acronym of Data Base or Model: VALLEY
(MED) Pedia/Subject of Data Base or Model: Air
CABS) Abstract/overview of Data Base or Model: VALLEY is a
steady-state^ univariate Gaussian Plune dispersion algorithm
designed for estimating either 24-hour or annual concentrations
resulting from emissions from up to 50 (total) point and area
sources. Calculations of ground-level pollutant concentrations are
•ade for each frequency designed in an array defined by six
stabilities, 16 uind directions, and six speeds for 112
program-designed receptor sites on a radial grid of variable scale.
Empirical dispersion coefficients are used and include adjustments
for plume rise and limited nixing. Plume height is adjusted
according to terrain elevations and stability classes.
(CTC) CONTACTS: D. Bruce Turner U.S. EPA, Environmental
Applications Br Loc: Mail Drop 80 Ph: (919) 541-4564
Loc: Research Triangle Park North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-06-83
(CAP) Functional capabilities of model: This dispersion model is
capable of estimating concentrations resulting from emissions from
up to 50 point and area sources for a time frame of either 24 hours
or an annual basis. The model performs calculations of ground-level
pollutant concentrations in an array defined by six stabilities, 16
vind directions, and six uind speeds for 112 program-designed
receptor sites on a radial grid of variable scale. The model
accounts for plume rise and limited mixing.
(ASM) Basic assumptions of model: Source-Receptor Relationship. Each
point source is assigned an arbitrary location. Each area source
is given an arbitrary location and size. The model provides 112
receptors on a radial grid for 16 directions; relative radial
distances are internally fixed, and the overall scale may be
modified by the user. The location of the grid center is defined
by the user. A unique release height for each point and area
source is given by VALLEY. Receptors are at ground level, and
ground level elevations above mean sea level are defined by the
user. The total number of sources for the model is less than or
equal to 50. Emission Rate. A single rate is utilized by each
point and area source. Each source is treated by an effective
point source approximation, and no temporal variation is allowed.
Chemical Composition. This is not applicable to VALLEY. Plune
Behavior. The model uses Briggs (1971, 1972) plume rise formula
for both point and area sources. Alternately, a single constant
plume rise value may be input for any or all sources. VALLEY does
not treat fumigation or dounuash. If the plume height exceeds the
mixing height: 1) for long-term calculations, the ground level
concentrations are assumed to be equal to zero, 2) for short-term
calculations, the maximum plume height is limited to the mixing
height. Horizontal Mind Field. For long-term calculations, th«
model utilizes the following: climatological approach, 16 Hind
1308
-------
Accession No. 14504000928 (cont)
directions, 6 Mind speed classes, no variation in Hind speed with
height, constant uniform (steady-state) wind assumed, and the user
mast specify the wind speeds representative of each class (these
are not internally defined). For short-term calculations,
specifically to predict the second highest 24-hour concentration
expected in one year, a Class F stability and a 2.5 it/sec, wind
speed with user-defined direction are assumed. These conditions
are assumed to exist for 25% of the 24-hour period, and an internal
adjustment is made for this. In stable conditions, in complex
terrain, concentrations for receptors located above the point of
impingement are obtained by linear interpolation between the value
obtained at the point of impingement and a value of zero at a
height of 400 meters above that point. The value at the point of
impingement is taken to be equal to thevalue 10 meters below the
plume centerline. For receptors located below the point of
Impingement, the effective plume height is equal to the height of
the plume above the receptor elevation or 10 meters, whichever is
larger. The plume is assumed to remain at a constant elevation
following the initial rise. In neutral or unstable conditions, in
complex terrain, the plume is assumed to remain at a constant
height above the topography, following the intial rise. The model
assumes that there is no variation of wind speed with height, and
that there is a constant, uniform (steady-state) wind. Vertical
Hind Speed. In stable conditions, this is assumed to be equal to
zero. In neutral and unstable conditions, the vertical wind speed
is assumed such that the plume remains at a fixed height above the
terrain. Horizontal Dispersion. VALLEY uses a climatological
approach, with sector averaging (narrow plume approximation) for
calculating the center values of each of the 16 sectors. The model
uses linear interpolation between centerlines, as does the Air
Quality Display Model (AQDM). Averaging time for VALLEY is one
month to one year for long-term calculations. Vertical Dispersion.
The model uses a semi-empirical/ Gaussian plume. In the urban
mode, the model assumes the following: five stability classes
(Turner, 1964); neutral stability split internally into 60% day and
40% night; dispersion coefficients from Pasquill (1961) and Gifford
(1961); neutral dispersion coefficients used for all neutral and
stable classes; no provision for variations in surface roughness;
and stable cases are never dealt with. In the rural mode, the model
assumes: six stability classes (Turner, 1964); dispersion
coefficients from Pasquill (1961) and Gifford (1961); neutral
stability split internally into 60% day and 40% night (has no
effect on dispersion coefficients); long term mode only; and no
adjustments are made for variation in surface roughness.
Chemistry/Reaction Mechanism. VALLEY uses exponential decay and a
user-input half-life. Physical Removal. The model uses exponential
decay and a user-input half-life. Background. VALLEY does not
treat this in any mode.
(IMP) Input to model: Input to the model includes: point and area
residual discharges and stack parameters; meteorological data; and
ambient air concentration measurements.
(OUT) Output of model: Output from the model in the long-term mode
1309
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Accession No. 14504000928 (cont)
includes long-tera arithmetic means and a source contribution list
for each receptor. Output for the short-tern node includes the
second highest 24-hour concentration and a source contribution list
for each receptor.
(APR) Applications of nodel: The source program for this dispersion
•odel is available as part of UNANAP (Version 4) PB 81 164 600 for
$840 from Computer Products/ NTIS, Springfield, VA 22161.
TECHNICAL CONTACT: D. Bruce Turner U.S. Environmental Protection
Agency Hail Drop 80, EPA Environmental Applications Branch Research
Triangle Park, NC 27711 FTS 629-4564 COm 919/541-4564
(HDW) Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 13K
(LNG) Computational system requirements - Language(s) used: Fortran V
(ATP) Air Models - Type of model: Gaussian dispersion
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(THE) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: multiple point, less than or equal to 50
(AR) Area where sample was collected: level or gently rolling terrain.
1complex: rough terrain clo of water or in valley or street canyon.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - user manuals, documentation, etc.:
Burt, E., Valley Model User's Guide, Publication
No* EPA-450/2-77-018, Environmental Protection Agency,
Research Triangle Park, North Carolina 27711, September, 1977.
(CNM) Contact name(s): Turner,D.B.
(COR) Contact organization: U.S. EPA, Environmental Applications Branch
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Quality Planning and Standards.Monitoring and
Data Analysis Division.
1310
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Accession No. 14504000929
-------
Accession No. 14504000929 (cont)
are assumed to be equal to zero. Horizontal Hind Field. The aodel
uses user-supplied hourly wind direction (nearest 10 degrees),
internally aodified by the addition of a randoa integer value
betveen -4 degrees and +5 degrees. Hind speeds are corrected for
release height based on power las variations and exponents from
DeMarrais(6); different exponents are used for different stability
classes, and the reference height is equal to 10 aeters. A
constant, uniform (steady-state) wind is assuaed within each hour.
Vertical Hind Speed. This is assumed to be equal to zero.
Horizontal Dispersion. The Model assuaes a seal-
eapirical/Gaussian pluae. Seven stability classes are used:
Turner Class 7 is an extremely stable, elevated plume assuaed not
to touch the ground. Dispersion coefficients are froa Turner, and
no further adjustments are nade for variations in surface
roughness, transport, or averaging time. Vertical Dispersion. A
sewi-empiricaI/Gaussian plume is used, and the model utilizes seven
stability classes. Dispersion coefficients are from Turner, and no
further adjustments are made. Chemistry/Reaction Mechanism. This
Is not treated. Physical Removal. This is not treated. Background.
This Is not treated.
(IMP) Input to model: Meteorological data must be input to the model.
(DOT) Output of model: Output produced by the model includes highest
and second highest concentrations for the year at each receptor for
averaging times of 1, 3, and 24-hours, plus a user- selected
averaging time which may be 2, 4, 6, 8, or 12-hours. An annual
arithmetic average at each receptor is given, and the aodel
provides the highest 1-hour and 24-hour concentrations over the
receptor field for each day, and hourly concentrations for each
receptor on magnetic tape.
-------
Accession No. 14504000929 (cont)
1313
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Accession No. 14505000905
(DQ) Date of Questionaire: 12-02-82
CHAM) Kane of Data Base of Model: HUBan Exposure Program
(ACR) Acronym of Data Base or Model: HEP
{MED) Media/Subject of Data Base or Model: Air ;Toxic substances
fABS) Abstract/Overview of Data Base or Model: The Hunan Exposure
Program (HEP) is a digital conputer sinulation which calculates
population exposure to airborne pollutants enitted by point,
prototypical points and area sources, using the concentration
patterns of those pollutants. Additionally, the sinulation
deternines the dosage (an integrated concentration x population)
received by this exposed population. The purpose of the pro gran is
to estimate the national inpact of the enissions from sources on
the actual population. This program is not intended to certify a
source as neeting a standard. The original version of the nodel
was conpleted in March 1980 by Systens Applications, Incorporated
of San Rafael/ California with contributions fron Hydroscience,
Incorporated, Knoxville, Tennessee and Mininax Research
Corporation, Berkeley, California. The progran was re-structured
for use on the UNIVAC 1100 by OAQPS.
(CTC) CONTACTS: Dave Patrick or George Duggan U.S. EPA, Office of Air
Quali Planning and Standards, Strategies and Air Standards Division
Loc: Research Triangle Park Ph: (919) 541-5645 or 541-5620
Loc: North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-27-83
(CAP) Functional capabilities of nodel: The Hunan Exposure Progran
conputes the dosage received by an exposed population in the
vicinity (usually within 20 kn) of specific point sources enitting
an airborne pollutant. The nodel also provides neans for the
analysis of the combined effects of point, prototypical point, and
area sources and calculates the total dosage (M6/M3X PEOPLE)
produced by these sources. HEP consists of several prograns which
carry out the calculations. Pollutant concentrations are obtained
froB a Gaussian dispersion nodel which uses meteorological data
fron over 300 star-sites across the country. Population exposure
is determined using 1970 Census Bureau population distribution
estlnates adjusted by esitmated 1980 county growth factor. For
point source, total dosage is obtained with the aid of
interpolation algorithms to achieve a natch of pollutant
concentrations and population centroids. An ancillary progran,
STAR PICK, can be used to aid in selecting the star-site whose
meteorological conditions nost closely approximate those of the
location of the point source. A support progran, DTM-CALC, is
available to obtain the longitude and latitude of the source in
degrees-ninutes- seconds if the OTM coordinates are available. For
prototypical point sources, the country was divided into nine
regions. Based on enissions characteristics, photochemical
reactivity, and the star data of pre-selected stations, the
concentrations patterns fron modeled sources typical of those
existing in the nine regions were determined using the sane
dispersion nodeling techniques developed for point sources* The
average population density in the urbanized areas for the nine
1314
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Accession Ho. 14505000905 (cont)
regions was used to estimate the population exposed to different
concentrations. For each model source in each region, three
corresponding matrices were produced—one for the concentration
pattern, one for the exposed population and one for the dosage
estimates. The dosage Has estiaated by multiplying the exposed
population by the concentration to which it was exposed. For area
sources, chemical emissions Here estimated as national totals uhich
nere then distributed over cities Hith populations greater than
2500. Emissions from mobile sources were appor- tioned by the
number of motor vehicles. Emissions from home heating sources Here
distributed by the product of population and per capita heating
requirement. Emissions from other stationary area sources Here
distributed by population. A box model Has used to estimate the
average annual concentration in each city. These concentrations
Here multiplied by the estimated 1980 population of each city to
produce national dosage estimates.
(ASM) Basic assumptions of model: The Human Exposure Program assumes
that, for point sources, the concentrations of the airborne
pollutant can be described by a Gaussian dispersion model Hhich
uses averaged meteorological data for a one year period. The model
assumes also that the pollutant is emitted at a constant rate over
the entire year. Also, the density of the emissions is considered
to be the same as the local atmosphere. Human population is
assumed to be distributed uniformly over each BG/ED (Block Group/
Enumeration District) and population growth rates (required for
periodic updates) are considered uniform over an individual county.
The important feature of HEP is the interpolation algorithm - it is
also the most important assumption because it considers a
distribution of pollutant concentrations and a distribution of
population that are reasonably smooth in the vicinity of a point
source. The accuracy of the concentration to nhich each unit of
population is exposed is as important to the accuracy of the total
exposure as is the accuracy of the populations. Concentration
patterns are input to HEP as polar grids Hith the source at the
origin, the radial divisions (Hind directions) oriented along the
compass-points, and the circular divisions (radii) spaced closely
(o.l km) near the source and less closely farther away. Since the
population does not array itself neatly along these lines, a method
for interpolating betneen concentration points Has developed.
(INP) Input to model: Input to the model includes the geographical
location of the point source/ a Starsite whose meteorology is
similar to that of the source if desired (if not the nearest site
is chosen), and a description of the physical parameters of the
source. These are the so-called "stack parameters" which are the
emission rate, stack height, diameter and vertical cross section
area, effluent velocity and temperature/ and the type of stack,
i.e., vent or tall stack.
(OUT) Output of model: HEP provides intermediate output, which can be
suppressed, as well as "bottom-line" information about dosage which
is usually of primary interest. Intermediate output includes
pollutant concentrations around the point source and the
distribution of population exposed to the airborne pollutant.
1315
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Accession No. 14505000905 (cont)
Final output is the dosage (population x concentration) received by
the exposed population foe various concentration levels out to 20
km from the point source.
(APP) Applications of model: This model provides a means for the
estimation of the dosage received by the national population
exposed to an airborne pollutant emitted by a specific source
category. HEP calculates also the effect of multiple sources such
as those found in industrial areas. HEP is a neu program and
represents state-of-the art for exposure models.
(HMO Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 600 tracks permanent dat Printer 132 position
line printer
(LHG) Computational system requirements - Language(s) used: Automatic
scratch space depending on amount of data. Oses than 45K memory.
Fariable scratch space not available under ASCII FORTRAN
Fortran V
(OSK) computational system requirements: Operator Knowledge/Skills: Eng
ineering
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Kodel reviewed and approved by OAQPS? YES
(PHP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Chemical
removal processes are those in which pollutant rea
(THE) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20) and
limited area.
(AR) Area where sample was collected: simple: area with level or
gently rolling terrain.
(RMG) Distance traveled by pollutant from source: short range (less
than 60 km)
(REF) References - User manuals, documentation, etc.:
Human Exposure to Atmospheric Concentrations of
Selected Chemicals, Attachment B. EPA Contract Ho. 68-02-
3066, SAI No. EE-156 R, 5 March 1980.
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Quality Planning and Standards.Strategies and
Air Standards Division.
1316
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Accession No. 14505000906
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Coke Supply
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: A production cost model
that incorporates technical relationships and engineering cost
estimates is used with plant-specific information to compute
separate industry supply functions, with and without EPA regulatory
alternatives for specific emissions sources on a year-by-year basis
for furnace and foundry coke plants projected to be in existence
between 1980 and 1990. Both coke production costs and the costs
that plants will incur to meet existing environmental regulations
are computed in order to estimate the industry supply curve before
any new regulations are applied. Estimates of the costs of control
for the regulatory alternatives are then used to compute the
projected upward shift in that supply function. All costs are in
1979 dollars. Econometric estimates of the demand for coke are used
to get price and quantity adjustments.
(CTC) CONTACTS: Bob Short U.S. EPA Loc: Research Triangle Park Ph:
(919) 541-5610
Loc: North Carolina 27711
(STA) Data Base status: Operational/Ongoing
Disc storage 50 tracks 1330 ;Printer
(LNG) Computational system requirements - Language(s) used: Fortran I?
(REF) References - User manuals/ documentation/ etc.:
1) Economic Impact of NESHAP Regulations on Coke
Oven Batteries Research Triangle Institute
2) An Econometric Model of the U.S. Steel Industry Research
1317
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Accession No. 14505000906 (cont)
Triangle Institute
3) Technical Approach for a Coke Production Cost Model PedCo
Environaental, Inc., Cincinnati, Ohio
(CUM) Contact name(s): Bob Short
(COR) Contact organization: U.S. E.P.A. MD-12 Research Triangle Park
MC 27711
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Offlee of Quality Planning and Standards.Strategies and
Air Standards Division.
1318
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Accession No. 14505000907
(DQ) Date of Questionaire: 12-02-82
(NAM) Faroe of Data Base of Model: Fertilizer Supply
(ACR) Acronym of Data Base or Model: FERTSUPPLY
(MED) Media/Subject of Data Base or Model: Air ;Industry/economic
CABS) Abstract/Overview of Data Base or Model: The FERTSUPPLY model is
a quadratic programming model of the U.S. nitrogen fertilizer
industry, designed to assess the economic impact of New Source
Performance Standards on urea, ammonium nitrate and ammonia
production facilities. The model consists of a set of linear
programming (LP) models of production facilities to account for
supply, a transport model to account for distribution, and a
quadratic programming model to account for demand. The U.S. is
divided into 10 production/consumption regions to explain domestic
production and consumption activities and Imports are treated as
exogenous variables. The parameters of the LP production models
are developed from engineering cost data. The parameters of the
demand functions and the transport model are estimated
econonetrically.
(CTC) CONTACTS: Thomas Walton U.S. EPA, Office Air Quality Planning
and
Standards, Strategies and Air Standards Division
Loc: Research Triangle Park Ph: (919) 541-5610
Loc: North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-27-83
(CAP) Functional capabilities of model: The purpose of the model is to
provide long run conditional forecasts for costs of regional and
national consumption and production of major nitrogen fertilizers
and investment in new plants. The model provides data on an annual
basis and is specifically designed to assess the differential
impacts of alternative New Source Performance Standards.
(ASM) Basic assumptions of model:
1) Individual plants face Leontief production functions.
2) Regional demand functions can meaningfully be linearized over
the relevant ranges of feasible solution sets.
3) Transport costs are independent of the level of
interregional shipments and constant on a per unit basis.
4) The solution methodology is encapsulated in the Univac
Functional
Mathematical Programming System (FMPS) package.
(IMP) Input to model:
1) Unit production costs for each product for each plant
2) Plant capacities
3) Interregional shipping costs
4) Linear demand function parameters
(OUT) Output of model:
1) Plant product mix
2) Plant output by product
3) Regional output by product
4) U.S. output by product
5) Interregional trade flows
6) Total regional shipping costs
1319
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Accession No. 14505000907 (cont)
7) Total national production costs
8) Investment in new plant by region
9) Total investment in neu plants in the U.S.
10) Total costs of alternative new source performance standards
regulations, measured by changes in economic surplus All data are
presented in tabular form.
(APP) Applications of model: Model was being used to assess economic
impacts of new source performance standards regulatory alternatives
for urea and a»«onium nitrate facilities between 1981 and 1986.
(HD«) Computational system requirements - Hardware: Onivac 1110 ;Disc
storage 1 20 tracks ;Printer any model
(LUG) Computational system requirements - Language(s) used: Fortran
Functional Mathematical Programming System (FMPS)
(OSK) Computational system requirements: Operator Knouledge/Skills: Pro
granting
(ATP) Air Models - Type of model: Econometric/linear programming
(OAQ) Model reviewed and approved by OAQPS? YES
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Physical
(TME) saaple averaging time used: less than 24 hours
(SRC) Source of pollutant: limited point, limited time
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals/ documentation* etc.:
Report in progress.
CCNH) Contact name(s): Walton,?.
(COR) Contact organization: U.S. EPA, Office Air Quality Planning and
Standards, Strateg
-------
Accession No. 14605000007
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Mobile Source Air Pollution Emission
Model
-------
Accession Mo. 14605000007 (cont)
(HDW) Computational system requireaents - Hardware: Mainfraae IBM 360
or Unlvac ;Dlsc storage (or tape) 45/000 u Magnetic tape storage
(or disc) ^Printer 80 or 132 coluan BOdel
(LliG) Coaputational systea requireaents - Language(s) used: Fortran
(OSK) Computational systea requireaents: Operator Knowledge/Skills: Pro
graaaing ^Engineering
(REF) References - User Manuals, documentation, etc.:
1) Users Guide to Mobile II, EPA* 460/3-81-006,
Feb. 1981, HTIS fPB81205619, Ann Arbor, Michigan.
2) Coapilation of Air Pollutant Emission Factors: Hlvay Mobile
Sources, EPA f460/3-81-005, March 1981, MTIS tfPB 81238305, Ann
Arbor, Michigan.
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Mobile Sources.Eaission Control Technology
Division.
1322
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Accession No. 15302000107
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: Toxics Treatment-Hastewater/Solid
Waste
(ACR) Acronym of Data Base or Model: OCPSPMODEL
(MED) Media/Subject of Data Base or Model: Toxic substances /Mater
;Industry/economic
(ABS) Abstract/Overview of Data Base or Model: (This model is not
related to the ecosystem-it is a cost and treatment technology
performance model) The model has been designed to use input date
fron the model itself or input by the operator defining the
quantity and quality of waste water or solid waste to design and
cost treatment systems. The quality of the acceptable effluent can
be varied to accomodate local variations in treatment and control*
(CTC) CONTACTS: E. H. Forsht U.S. EPA, Effluent Guidelines Division
Loc: 401 M Street, SW. Room 935 E.T. Ph: (202) 382-7173
Loc: Washington/ D.C. 20460
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-08-83
(CAP) Functional capabilities of model: The model produces a treatment
plant design (waste water and solid waste) which achieved the
effluent quality targets. Operating and capital costs are given as
are the energy, land and chemical requirements for the treatment
system.
(ASM) Basic assumptions of model: The model relies on data derived
from the literature (physical constants such as vapor pressure,
log<10> P, etc.) and data gathered during the BAT studies for the
organic chemicals industry.
(INP) Input to model: The user has the option to input a raw uaste
water load or quantity of solid waste. Alternatively, he may
choose to study one or more of the 150 product/process which have
data in the system. Many options are available to modify labor
rate, materials usage, etc. in lieu of using the default valves in
the model.
(DOT) Output of model: The output of the model consists of a treatment
plant design and associated costs. The model predicts the effluent
quality of all waste water parameters on the list of 129 toxics and
PLOD, COL, TOC, TSS and ammonia. Cost data for capital and
operation are listed with the materials necessary for support of
the operation (chemicals such as alum, lime, etc., and energy).
-------
Accession Ho. 15302000107 (cont)
(REF) References - User Manuals, documentation/ etc.:
Docunentatlon Is now in progress.
(ROR) Responsible Organization: Office of water.Office of Hater
Regulations and Standards.Effluent Guidelines Division.
1324
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Accession Ho. 15603000003
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Waste Resources Allocation Program
(ACR) Acronym of Data Base or Model: WRAP
(MED) Media/Subject of Data Base or Model: Solid waste
(ABS) Abstract/Overview of Data Base or Model: WAP is a waste
resources allocation program which is coded in FORTRAN, this
Modeling program consists of a series of equations which consider
the sources of solid waste generation/ a set of sites, and
processes to be considered at those sites, as well as various site
and process capacity constraints. KRAP sorts out the various
allocation options specified by the user and indicates a preferred
allocation solution which is the minimum cost plan that meets all
the user-supplied constraints. Use of the model enables users to
study and analyze the costs and implications of all available
alternatives under consideration. WRAP has been used for decisions
regarding solid waste management in Massachusetts, in Illinois, and
in St. Louis, Missouri.
(CTC) CONTACTS: Frank McAllster O.S. EPA, Office of Solid Haste
Loc: 401 M Street, S.H. Ph: (202) 382-2223
Loc: Washington, D.C. 20460
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 12-28-82
(CAP) Functional capabilities of model: MRAP is an optimizing model
which selects, sizes, and locates solid waste processing and
disposal facilities. Costs for the solid waste systems are
determined by a specialized fixed charge linear programming
algorithm. There are two operational modes available: static and
dynamic. The dynamic operating mode allows for two to four
Planning periods. Planning periods are expressed in years, and, in
the dynamic mode, are consecutive over the total planning period*
The model consists of a series of equations which consider the
sources of solid waste generation, a set of sites, and processes to
be considered at those sites, as well as various site and process
capacity constraints. The processes can be transfer stations,
resource recovery processes (including the extraction of
recoverable resources to be marketed), secondary processes (which
receive the residue of primary processes as input) and various
disposal processes. KRAP further considers many transportation
route alternatives from sources of waste generation to sites, and
from sites to sites, with due allowance for site traffic
constraints.
(ASM) Basic assumptions of model: WRAP is a fixed-charge linear
programming model, using as the optimizer an algorithm developed by
Dr. Warren Walker of Cornell University in Ithaca, New York. The
fixed-charge capability of the model permits the representation of
economies of scale in process costs. Since the model is
cost-minimizing, it will seek out the lowest cost segment at any
level of tonnage. Thus the capability of treating cost in two
parameters (fixed and variable, or intercept and slope) permits the
model to represent economies of scale at any level of accuracy
desired. In the actual model applications, three segment
representations have been used for nearly all processes.
1325
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Accession No. 15603000003 (cont)
(IMP) Input to model: Program execution data is input from a
sequential data set, normally the card reader* There are eight
types of inputs to be prepared. Five of the input types are
required by every program. Three input types are optional. All
data for a particular input type is input sequentially. There is
no special ordering required within an input type. However, a
special ordering is required for the types of user-supplied inputs.
The required input sequence follows:
1. Control Records: four control record inputs are
possible. T«o records are always required and two records are
optional.
2. Source Identification Records: an identification
record for each original solid waste source must be supplied. Each
record must have a unique source identification code as well as the
record code.
3. Site identification Records: there must be one record
for each intermediate and ultimate site. All site records are
input in one group.
4. Process Identification Records: there are five types
of records possible for each unique process. Though the processes
need not be in a particular order, the records associated with each
process must be in a specific sequence.
5. Site Process Identification Records: there is one
record for each process at each site, and there may be a maximum of
125 records. These records do not need to be in any particular
order.
6. Transportation Activity Records: these records are
optional, but generally part of the input file. Each record must
have an activity type code which describes the transportation
links.
7. Truck constraint Identification Records: these
records are optional and are required only when the user's control
data indicates that sites are to be subject to truck constraints.
There must be one record for each truck constraint, and each record
may have a maximum of three site identification codes.
8. Starting Basis Records: these records are optional
and are not considered part of the problem identification records.
These records are input only when the user has indicated their
availability. The number of records is determined by the number of
rows (equations) in the matrix.
(OUT) Output of model: There are six types of output generated In the
HRAP program: (1) optional debugging variables and tables, (2)
error messages and codes, (3) input data reports, (4) punched
transportation and matrix decks, (5) intermediate phase solution
tables, and (6) final solution punchout and reports.
(APP) Applications of model: MRAP has been used in several locations
by decision-makers who are considering regional solid waste
management. In Massachusetts, the model was used to identify the
most efficient regional system design for that state's first
regional resource recovery system* WRAP was used in St. Louis,
Missouri, to determine the advantages of community participation in
a proposed regional solid waste management plan. In suburban
1326
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Accession No* 15603000003 (cont)
Chicago, HRAP was used to evaluate the economic feasibility of
various solid waste management and recovery options facing the
decision-makers.
(HOW) Computational system requirements - Hardware: Mainframe IBM 360
;Disc storage (or tape) 256,000 uords core Magnetic tape storage
(or disk) ^Printer 132 position line printer ; or tape/disk (input)
(LNG) Computational system requirements - Language(s) used: Fortran
-------
Accession No. 16301000102
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Strategic Environment Assessment
System
(ACR) Acronym of Data Base or Models SEAS
(MED) Pedia/Subject of Data Base or Model: Air ;Noise ;Radiation
iSolid waste ;Toxic substances ;Water Industry/economic
(ABS) Abstract/Overview of Data Base or Model: SEAS is a policy
sensitive emissions data base/ or alternatively a major policy
analysis model for the environmental/ energy/economics areas and
their interactions. SEAS is really large in terms of numbers of
variables. It is estimated that SEAS has over 100,000 variables.
As the scope and number of Federal regulatory activities have grown
in recent years, so has the need for Federal policy-makers to
anticipate what effects new regulations will have on the economy,
energy and water usage as well as the environment including land
use and/or abuse. Both the Environmental Protection Agency (EPA)
and the Dept. of Energy (DOE) have responded by developing a number
of comprehensive simulation models. The SEAS model is one of
these. As a computer tool, SEAS projects the magnitude and sources
of environmental impacts resulting from input assumptions
concerning the stringency and cost of environmental regulation,
future levels of energy supply, and economic activity. Such
projections can be developed on levels including the nation, EPA
Regions, State, or Air Quality Control (AQCR) Regions. SEAS is an
interactive computer model and associated data base, which
functions via a set of energy, economic, regional, and
environmental modules. From the Energy Demand Modules, an Energy
Retwork Simulator is fed with assumptions and energy demand
relationships; economic assumptions together with environmental
assumptions are fed into Economic Modules. In turn, the Energy
Network simulator and the Economic Modules feed into
Regionalization Modules. Then, the Regionalization Modules
together with the environmental assumptions are fed into the
Environmental Modules, which finally produce Environmental Effects
Expected Under the selected Scenario up through the year 2000, to
support long-range program planning, analysis, prepare
Environmental Impact Statements, etc.
(CTC) CONTACTS: John J. Coleman EPA Office of Research and
Development
Loc: Office of Environmental Engineering and Technology Ph:
(202) 426-9434
Loc: 401 M Street, SW, Washington, DC 20460
(STA) Data Base status: Operational/Ongoing
(CAP) Functional capabilities of model: SEAS usually projects air
pollutants, trace elements to the air, solid haste, and land and
water use. The system can also project certain data regarding
labor requirements and occupational health and safety needs. EPA
has used SEAS to identify the range of environmental futures likely
to result from alternative patterns of energy and economic
development. SEAS contains a series of comprehensive data bases,
including: environmental coefficients for industrial activities
(i.e., emission factors, land use, water use, occupational safety),
1328
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Accession No. 16301000102 (cont)
pollution control costs, energy investment costs/ regional
deployment patterns, economic factors, technological change,
materials substitution, consunption patterns. Eventually effects
will include damage, disability, deaths, and disease as well as
cost-effectiveness of mitigation measures.
(ASM) Basic assumptions of model: The SEAS logic is relatively simple.
Economic and energy modules simulate national activity levels for
over 500 SEAS sectors; the regionalization module disaggregates
these data to one of several possible geographic subdivisions? and
the environmental modules use data on emission coefficients,
control strategies, economic and energy activities as well as
eventual effects relationships, to calculate emissions, resource
requirements, effects, and control mitigation strategies versus
costs.
(IMP) Input to model: SEAS modules use an extensive data base
containing detailed environmental, energy-related, and economic
information; and, eventually, cause-effects relationships along
with mitigation and recovery indices. Every effort is made to
maintain current data through frequent updating and validating.
Many types of information are presented in a consistent manner yith
much of the information keyed to specific industrial activities.
As a result, the SSAS data base is now considered a resource in its
own right. The more than 50 files that comprise the SEAS data base
are based upon information from numerous government reports,
documents and communications Hith government labs, university
personnel, contractors, and trade associations. In addition,
indices of cause-effects (e.g., deaths, disabilities, damage, and
diseases from accidents, pollutants, etc.) associated with various
activities are planned to be included in the overall SEAS data base
system as it grows.
(OUT) Output of model: SEAS forecasts can be displayed in several
formats, includi graphic presentation designed to provide ready
visual reference to impacts and trends. Eventually, computerized
graphs of effects and emissions over regions and sectors of
interest will be used to pull together the data with management and
technology control measures against several policy postures.
(i.e., we plan to integrate computer graphics into the assessment
process, converting endless mazes of emissions, effects, sectors,
and regionalized sources and depositions into colorful charts,
graphs, and maps that will help administrators and managers to spot
trends and make mutually satisfactory decisions more quickly and
efficiently than before. Otherwise, masses of printouts piled
several feet high would offer more data indigestion than relief to
the problems SEAS can help to resolve as an effective and
efficient, as well as accurate and comprehensive, policy-sensitive
emissions data base and modeling system.
(APR) Applications of model: Several applications of SEAS exist and
are growing: The comprehensive Environmental Outlooks, yearly
to Congress, analyze national and r^ional environmental
of different economic/energy scenarios—a high growth and a
r?h scenarlS. ?he Ohio'River Basin Energy Study (ORBES) used
SEAS to obtain estimates of future trends in pollutant discharges
1329
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Accession No. 16301000102 (cont)
in the Ohio River Basin area, with emphasis on energy-related
industries. SEAS was used to analyze changes in pollutants
attributable to materials substitution such as aluminum and
plastics for steel in autoaoblle construction. The 5 year R&D plan
(Research Outlook) required by Congress and the Integrated
Technology Assessment studies of energy development within OEET are
developed each year. Additional applications include OSHA, Health,
Solid Waste, and Water Quality modeling* Future plans include
indoor air quality Studies, Acid Rain Mitigation studies, etc.
(HDV) Conputational system requireaents - Hardware: Calculator
^Mainframe IBM ;Disc storage Largest amount avail Magnetic tape
storage Varies by application ;Printer Any model
(LUG) Computational system requirements - Language(s) used: Fortran
Cobol
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gratmlng Engineering ;Policy analysis, physics, environm
(ATP) Air Models - Type of model: Gaussian dispersion / Numerical
dispersion; Numerical
(OAQ) fcodel reviewed and approved by QAQPS? NO
-------
Accession No. 16301000103
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Regional Episodic Grid Model
(ACR) Acronym of Data Base or Model: REGMOD
(MED) Kedia/Subject of Data Base or Model: Air
/S0<4» or fast and reversible (e.g.
NQ/NO<2>). REGMOD is appropriate for large-scale energy growth
studies. The model can be used in conjunction with subregional
'trajectory* and local "straightline Gaussian* models in
multiple-scale analyses. In this application, local-scale NAAQS
and PSD analyses can therefore incorporate realistic time-dependent
'background* concentrations/ as supplied by the regional scale
model.
(CTC) CONTACTS: Michael Kills Teknekron Research, Inc.
Loc: 69 Hickory Drive Waltham, Mass. 02154 Ph: (617) 890-6270
(STA) Data Base status: Operational/Ongoing
(CAP) Functional capabilities of model: REGMOD computes short-term
average pollutant concentrations and deposition patterns for a
coupled set of pollutants. The solution of the two-dimensional
advection-diffusion equation is carried out in a spatially and
temporally varying wind field using a Fast Fourier Transform (FFT)
technique which is both accurate and computationally efficient.
REGMOD includes first-order transformation of primary to secondary
pollutants and the wet and dry removal of both species.
(ASM) Basic assumptions of model: REGMOD does not explicitly account
for pollutant diffusion—rather/ diffusion is implicitly considered
by advection in a spatially and temporally varying wind field. The
model assumes that the windfield is two-dimensional/ and that
pollutants are uniformly mixed through a constant vertical depth.
(IMP) Input to model: Inputs to the model include: job specification/
dispersion and removal parameters/ time sequences of gridded wind
fields/ and gridded emissions inventory.
(OUT) Output of model: REGMOD produces gridded sequences of
concentration or deposition fields for each pollutant. An output
tape or disk file may be created for interface with post processing
packages which allow for 1) graphical display of concentration
fields/ and 2) concentration of output fields with those of
sub-regional or local-scale models.
(APP) Applications of model: REGMOD has been used by Teknekron
Research/ Inc. for a number of regional-scale energy growth
studies/ including . The Ohio River Basin Energy Study (ORBES) .
Regional Air quality Impact Assessment of Hood Burning for TVA .
Air Quality Benefits of the Increased Use of Solar Power . Analysis
of Coal Conversion Air Quality Impacts
(ROW) Computational system requirements - Hardware: Mainframe IBM
360/370, 3033 ;Disc storage for tape 2000 word time step if results
1331
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Accession No. 16301000103 (cont)
saved. ^Magnetic tape storage or disk jCard reader/punch a
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;Meteorology
(ATP) Air Models - Type of model: Numerical dispersion
(QAQ) Podel reviewed and approved by OAQPS? NO
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Combination
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20)
(AR) Area uhere sample was collected: level or gently rolling terrain.
(RHG) Distance traveled by pollutant from source: more than 100 km
(REF) References - User manuals, documentation, etc.:
Prahm, L.P. and 0. Christensec, 1976: Long Range
Transmission of Pollutants Simulated by a Two-Dimensional
PSeudospectral Dispersion Model, J. Appl. Meteor.16:
898-910.
Nievann, B.L., M.T. Mills, A.A. Hirata, and E.Y. Tong, 1980:
Air Quality Meteorology in the Ohio River Basin—Baseline and
Future Impacts, Teknekron Research, Inc., 270 pp.
(CUM) Contact name(s): Mills,M.
(COR) Contact organization: Teknekron Research, Inc.
(ROR) Responsible Organization: Office of Research and Development.
1332
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Accession No. 16301000104
(DQ) Date of Questionaire: 12-02-82
(NAM) Nane of Data Base of Model: Regional Climatological Disperson
Model
(ACR) Acronym of Data Base or Model: RCDM
(MED) fcedia/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The Regional Dispersion
Model (RCDM) is a steady-state regional-scale two-dimensional
dispersion model for predicting long-tern average (e.g. monthly or
yearly) concentrations from single or multiple point and area
sources at distances greater than 50 km. The no del is designed for
a coupled set of pollutants linked by a mechanism which is either
slow and Irreversible (e.g. S0<2>/S0<4», or fast and reversible
(e.g. NQ/NO<2». The long-term average concentration is based upon
a regional scale diffusivity and a resultant average wind vector
field. Because it is a steady state model/ RCDM enjoys a decided
cost-advantage over trajectory or grid models for long averaging
times and large source inventories. RCDM is therefore especially
useful for predicting the effects of energy growth on seasonal or
average annual air quality and air quality related values such as
pollutant dry and wet deposition.
(CTC) CONTACTS: Carl V. Benkley Teknekron Research/ Inc.
Loc: 69 Hickory Drive Ualtham, Mass. 02154 Ph: (617) 890-6270
(STA) Data Base status: Operational/Ongoing
(CAP) Functional capabilities of model: RCDM computes long-term
average pollutant concentrations or deposition patterns for a
coupled set of pollutants/ based on the analytical solution of the
steady-state two-dimensional advection-diffusion equation. The
model incorporates mesoscale diffusivity/ resultant wind vector/
wet and dry removal/ and either a linear decay mechanism or an
equilibrium mass coefficient. The model can handle either point or
area sources/ and any arbitrary rectangular coordinate system.
(ASM) Basic assumptions of model: RCDM assumes that the time averaging
of pollutant parcels can be represented by horizontal diffusion in
a two-dimensional steady-state wind field. It also assumes that a
single set of dispersion and removal parameters is appropriate for
an individual source, independent of distance or travel time.
(INP) Input to model: Inputs to the model include: job
specifications/ dispersion and removal parameters/ resultant wind
field, and emissions inventory. RCDM prints all input information.
(OUT) Output of model: RCDM produces a gridded field of time-averaged
concentration or deposition for each pollutant. An output tape or
disk file may be created for interface with a post-processing
package which allows for graphical display of output fields.
(APP) Applications of model: RCDM has been used by Teknekron Research/
Inc. to predict annual average S0<2> and S0<4> concentrations over
the eastern United States for the Ohio River Basin Energy Study
(ORBES)/ using the Sulfate Regional Experiment (SURE) emissions
inventory. The results have compared favorably for both pollutants
with SURE measured values.
(HDtf) Computational system requirements - Hardware: Mainframe IBM
360/370, 3033 ;Disc storage (or tape) 2000 wor if results saved)
;Magnetic tape storage or disk ^Printer 132 position line pri Card
1333
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Accession No. 16301000104 (cont)
reader/punch and tape/disk (input)
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) computational system requirements: Operator Knowledge/Skills: Pro
gramming ^Meteorology
(ATP) Air Models - Type of model: Numerical dispersion
COAQ) Model reviewed and approved by OAQPS? NO
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) process used to remove pollutant from atomosphere: Combination
(THE) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20)
CAR) Area uhere sample uas collected: level or gently rolling terrain.
(RUG) Distance traveled by pollutant from source: more than 100 km
(REF) References - User manuals, documentation, etc.:
Fay, James A., and Jacob T. Rosenzwelg, 1980:
An Analytical Diffusion Model of Long Distance Transport of
Air Pollutants, Atmospheric Environment 14, pp. 355-365.
Hi em arm, B.L., M.T. Mills, A. A. Hirata, and E.Y. long, 1980:
Air Quality Meteorology in the Ohio River Basin—Baseline and
Fugure Impacts, Teknekron Research, Inc., 270 pp.
(CNM) Contact name(s): Benkley,C.H.
(COR) Contact organization: Teknekron Research, Inc.
(ROR) Responsible Organization: Office of Research and Development.
1334
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Accession No. 16301000105
CDQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Interregional Coal Analysis Model
(ACR) Acronym of Data Base or Model: ICAM
{MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Over view of Data Base or Model: The ICAM is a large
scale simulation model designed to assist in coal development
planning and the analysis of alternative policies toward coal
development. The model uses a mathematical programming approach but
is constrained to replicate existing and announced coal mines,
power plants and transportation links. The model is run in
cooperation with the Coal Transportation Model which simulates rail
and barge transportation networks and generates transportation
costs for each link. The ICAM contains exterior data bases on coal
mining and transport and coal preparation and electric power plants
(see attached list).
(CTC) CONTACTS: John Green U.S. Dept. of Agriculture Resource
Economics Loc: Colorado State University Ft. Collins, Colorado Ph:
(303) 323-5251
(STA) Data Base status: Operational/Ongoing
(CAP) Functional capabilities of model: The coal energy systems of the
United States are described by a number of variables, each of which
is linked to the others through a set of linear inegualities. An
additional linear function of these variables, the objective
function, is then defined and optimized. Model limitations derive
specifically from at least three sources: input data, systems
structure, and appropriateness of the modeling methodology used.
Specific problems arising from available data can be divided into
two major parts: (1) the uncertain nature of some of the data,
particularly that dealing with new energy systems not yet
cofflnercially available, and (2) the problems of projecting historic
data, however good, to future years. An important aspect of
projecting cost data is the choice of appropriate rates of
escalation.
(ASM) Basic assumptions of model: The development of operational
policies or regulations using results of simulation analyses should
be done carefully. The linear relationships present within linear
programming models may cause dramatic shifts between regional
activity levels. This occurs because linear programming algorithms
set up ratios between coefficients. These ratios are constantly
compared and if, as demand is net, their relative magnitudes
switch, it may cause dramatic shifts in the levels of activities.
This problem can be clarified by performing sensitivity analyses.
Sensitivity analysis enables the analyst to define shift points and
to temper the description of impacts to prevent unwarranted
reliance on shifts caused by linearity assumptions.
(INP) Input to model: For baseline projections the model can be
operated with existing data on current and announced mines, plants,
etc. as input. In addition, the user can specify on input scenerio
deferring plants, using alternative coal sources, assuming
differing rates of electricity demand, etc.
(OUT) Output of model: Outputs can be detailed listings of coal
produced by coal producing area, coal carried by each transport
1335
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Accession No, 16301000105 (cont)
link, etc. or regional aggregates of these results.
(APP) Applications of model: The complete model has not been applied
yet. Applications should begin by January 1981.
(HOW) Computational system requirements - Hardware: Mainframe Onivac
1100 ;Disc storage or magnetic tape ;Magnet Printer any model
(LIG) Computational systea requirements - Language(s) used: Fortran
Cobol
(QSK) Computational systea requirements: Operator Knouledge/Skills: Sys
tens analysis or operations research
(REF) References - User Manuals/ documentation, etc.:
Western Energy: The Interregional Coal Analysis
Model/ OSDA Technical Bulletin No. 1627, EPA-600/7-79-139.
(CNM) Contact name{s): Green, J.
(COR) Contact organization: U.S. Dept. of Agriculture Resource
Economics Div.
(ROR) Responsible Organization: Office of Research and Development.
1336
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Accession No. 16301000107
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Utility Simulation Model
(ACR) Acronyan of Data Base or Model: USM
(MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Over view of Data Base or Model: The Utility Simulation
Model projects the nature and implication of investaent and
operating decisions made by electric utility firms in each state
from 1976 to beyond the year 2000, as these decisions are
influenced by energy and environmental policies, technology
choices, and economic conditions. This highly flexible model makes
it possible to investigate the impact of numerous alternative
policies while coherently and consistently accounting for many
technical, economic, energy, and environmental factors that
directly influence decisions made by utility companies.
(CTC) CONTACTS: Edward H. Reckon
Loc: E.H. Peckon and Associates, Inc., 5537 Hempstead Way,
Loc:Springfield, VA 22151 (703) 642-1120
(CAP) Functional capabilities of model: The USM consists of a number
of interconnected computer modules and data sets that simulate
decisions for system planning and operation, their impact on
utility finance and their environmental effects. The model is
driven by a set of exogenous scenerio elements that include
electricity, demand levels, financial market conditions, fuel
prices and availability, advanced technology employnent, and
environmental regulations. For each scenerio, the model calculates
the following by geographic region, for future years up to 2000 or
beyond. System characteristics: Fuel use by type, composition and
region of origin; electricity generated by type of unit; capital
requirements by source; plant and equipment requirements; releases
of air and water pollutants, and solid wastes. Financial statistics
for utility firms Average electricity prices.
(ASM) Basic assumptions of model: The Utility Simulation Model
operates under certain basic assumptions, each of which are
functionally modular so that any may be redefined by the user.
These assumptions include electricity demand growth rates for peak
and average growth, environmental regulations applicable to each
fossil generating unit, fuel prices and real cost escalation for
fuel and capital items, alternative capacity expansion plans, and
macro-economic conditions affecting utility finance.
(INP) Input to model: The data needs of the DSM are extensive. Each
nodule has its own data set, each of which can be modified to
accomodate new or more specific information. The various data sets
can be grouped into the following functional categories:
Generating Plant Data; Data on Primary Energy and Fuel Supply; Data
on Economic Factors; and environmental and regulatory data. Hi thin
these categories the data sets are further classified by source, as
empirical or modeling data. The modeling data typically undergo an
intermediate analysis before being specified as the part of the USN
database. Many sources are used for comparison and completeness
and the various data sets continually are refined and updated as
new source data become available.
(OUT) Output of model: Output from the utility simulation model may be
1337
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Accession Ho. 16301000107 (cont)
classified into two categories. That which is used for interactive
analytical purposes and that which is used to produce summaries.
Here, ue only summarize the latter. Planning Input (PINI/M). The
plan model input data are organized In a top-down fashion. First
of all are the national data required by the OSM. Second are the
required county data; third, the state data; and finally the unit
data. In general the national data are default data, and include
several snitches and other scenario controls. The user has the
ability to specify such parameters as nuclear deferral years,
siting Methodologies/ emission Halts for SIP, HSPS and RMSPS
units, specific Q&H cost data, stringent pollution controls, water
pollution control regulations, estimates for construction costs of
various generating facilities, characterization of fuels used,
assignments of fuel for any future year, a dispatch hierarchy (with
the ability to specify those generating technologies to be
dispatched on a least-cost basis), default State Implementation
Plans and construction cost spreads. Following the national data
are county data including siting Heights; each county is assigned a
weight on the basis of its relative ability to site a coal, oil,
nuclear or minemouth coal generating facility. State specific data
follow the county data; for each state, demand is first printed
including such variables as pumped-storage efficiency, energy loss
factor, the effective capacity factor (which is the capacity factor
of purchase power), and then peak energy demand over the entire
simulation. The next state data required and printed out by PIMI/M
are the initial composition of the system from Forms 1 and 1M.
Data from these forms (including initial operation and maintenance
expenses and initial values) should correspond to the unit-by-unit
data. The planning input shows unit-by-unit data for all existing
and and future generating technologies. For each unit, the data
base specifies the owner state and its reliability council; the
name of the unit; the unit number; the abbreviation of the
company's name and the FPC flag and fraction owned. The
unit-by-unit data base also shows the state and county of location,
the type of prime mover, the rated capacity of the unit, the
primary or alternate fuels used, the year the unit came online, the
condenser cooling type, the re-rate date, and the amount of rerate,
the conversion date, and the fuel with which the conversion will
occur, the FPC plant and unit ID numbers, and the piece number, if
the unit is a Jointly owned facility. For each fossil facility,
available Unit Data and Fuel Data are specified. Included in the
Dnit Data are the heat rate, if known, (otherwise default heat
rates are used based on the year the unit came on line), the SIP
S0<2> limit the unit is required to meet, and the unit's S0<2>
control device and efficiency. As future research generates more
Unit Data the other data fields will be used. Also for each unit
at least one fuel is specified. This fuel is characterized by its
heating value, its first year of use, its sulfur and ash content,
and its price. In the case of unit conversions a second fuel data
card in given and the data conversion is assigned in the proper
piice. Planning Summary (PSUMI/M). The planning summary is the
first report generated by plan. It shows results of PLAN
1338
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Accession No. 16301000107 (cont)
algorithms which calculated the system composition for each state
over the entire simulation period. Also shown are systen size,
systen need/ and peak demand. Included in this report are
analytical reports enabling analysis of capacity expansion and
dispatch routines. Finally the planning summary reports each steam
unit built by state; for each steam unit built, the listing shows
fuel type, size (in megawatts), the size of future "conjured*1
units, and their location. Location State Capacity Factors and
Generation Reports (LCAP). The plan model is run for the entire
simulation and the results are stored on magnetic tape. These
results can then be accessed by smaller post-processors. The first
such post-processor prints out the LCAP report. The LCAP report
takes the PLAN results which are generated on the basis of owner
state and allocated to the state of location. The LCAP report shows
capacity and generation by state over time by class of unit. The
Summary Resource and Residual Report (SUMR&R). The summary resource
and residual report aggregates emissions to air and land, and
resource consumption by state of location for any year of the
simulation and for any region; output is presented by year. On the
first page of every output the regions are defined. Under the
category "emissions," we show S0<2> emissions for coal and oil
units broken down into SIP, NSPS and RNSPS units. N0 emissions
are calculated for coal oil and gas units and particulate emissions
for coal and units, with the units again broken down into the
separate classes. If flue gas desulfurization devices were built
to meet emission limits, the sludge generated by these units is
calculated and reported. Also reported in SUMR&R are water
consumed due to cooling and scrubbing devices. Fuel Btu's are
calculated for coal, gas and nuclear steam units. Distillate is
calculated for peaking units: in the next table for SOMR&R, fuel
consumed is calculated from the fuel Btu table. Finally the report
shovs the number of Btu's used to transport ccal from the point of
origin to the point of use. Scrubbers Build Report (SCRADDI/M).
The scrubbers built report aggregates scrubbers by major
ownerstates. It shows, for every scrubber, the location of the
scrubber, size of the unit, "net capability," the on-line date of
the scrubber, the annual average of controlled S0<2> emissions and
pounds per million Btu, the on-line data of the unit, annual
average fraction of S0<2> scrubbed, the capital cost in millions in
1975 dollars, the fixed operating cost at a capacity factor of 1.0.
Finally the listing shows the scrubber type, and the annual average
emissions in pounds per million Btu's. The report may be summed
for any aggregation of regions defined by the user. The Capacity
Penalty Report (CAPPEN). The CAPPEN may be obtained for any year
or region. The first report, Megawatts Scrubbed by FGD Device
represents the amount of flue gas that is scrubbed relative to the
total unit size. The report shows FGD by "limestone", wet
limestine, magnesium, and dry scrubbing." When an FGD or
particulate device is installed, capacity penalties occur. These
are summarized in the capacity penalties report. The actual
generating capacity of the unit is then reported at the bottom of
the capacity penalty report. Financial Report (FINI/M). Reports
1339
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Accession No. 16301000107 (cont)
•ay be obtained for any year in any state. Summary includes
operating results, including price of electricity in terns of
generation, revenues, costs and profits. A balance sheet includes
es assets, equities, liabilities. Other statistics such return on
rate base after taxes, types of financing, capitalization and
investment and pollution control equipment are also given. Sources
and uses of funds are summarized. The cost allowances in the set
price in a given year are shoiin. Finally the report calculates
levelized revenue requirements from the user specified start period
to the user's specified end period with a given discount rate.
MOTES The convention of using I/M indicates whether output is
disaggregated to private (Investor) and public (municipal)
utilities.
(HDH) computational system requirements - Hardware: Mainframe special
CDC system configuration jDisc storage 1 m Magnetic tape storage
1-8 ^Printer any model ;Card reader/punch
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
grarming ;Engineering ;Economics
(REF) References - User manuals, documentation, etc.:
Van Horn, Andrew J. et. al., "Review of New
Source Performance Standards for Coal Fired Utility
Boilers:" Phase 3 Final Report, Project Officer Lowell
Smith, Officer of R&D, Environmental Protection Agency,
EPA-600/7-79-215, December 1979.
Ohio River Basin Energy Study: Air Quality and Related
Impacts Volume III, "Selected Impacts of Electric
Utility Operations in the Ohio River Basin (1976-2000):
An Application of the Utility Simulation Model," by
Teknekron Research, inc., Berkeley, CA (Report No.
R-001-EPA-80); series edited by J. Stukel, University
of Illinois, subcontract under Prime Contract R805588.
(ROR) Responsible Organization: Office of Research and Development.
1340
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Accession No. 16301000108
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Coaltown lapact Assessment Model
(ACR) Acronym of Data Base or Model: COALTOWN
(MED) Media/Subject of Data Base or Model: Industry/econonic
;energy-socioeconoraic Impact
(ABS) Abstract/Overview of Data Base or Model: COALTQWN simulates
future employment, population, wage levels, migration, State and
local tax receipts, intergovernmental transfers, and local
government expenditures for counties in Montana, Wyoming, and North
Dakota. The model is designed to assess impacts by comparison of
results when one or more energy projects are included with baseline
results. The model has three parts — socioeconomic. State and
local government revenues, and local governnent expenditures. The
structure of COALTOWN is different from an economic base model
although modified economic base concepts are used. Stochastic
estimates of the major parameter of the model are used. A
multiplier Is not calculated by the model. Rather, predictions of
"ancillary* employment are made by use of equations. The model is
dynamic in that it uses lagged variables, and because
interrelationships among variables in the equations of the model
produce reverberations in years following an initial change.
Although the the coefficients in the equations of the model are
representative of Northern Plains counties, the application to a
specific county yields results which iiill be different from that of
counties with other background conditions. The model is designed
for near term prediction and assessment purposes. Principal uses
are: 1. Predict absolute levels of socioeconomic aggregates for
planning purposes, 2. Assess impacts on socioeconomic aggregates
for purposes of evaluation of a facility, and 3. Test the
sensitivity of socioeconomic and fiscal aggregates to key policy
measures.
(CTC) CONTACTS: Lloyd Bender D.S.D.A., Economic Development Division
Loc: Montana State University Ph: (406)585-4344
Loc: Bozeman, Montana
(STA) Data Base status: Operational/Ongoing
(CAP) Functional capabilities of model: The model has limitations and
shortcomings. First, it estimates only aggregate parameters
because predictive accuracy declines with the level of
disaggregation. Second, accurate results are very much dependent
on the accuracy of data supplied by users as as inputs. Third, no
capability nou exists to estimate the distribution of new people
among counties, and local governments within a county. Finally,
the level of aggregation to some extent prevents an analysis of the
distribution of Impacts among classes of residents in the area.
(ASM) Basic assumptions of model: The model assumes that relationships
can be calculated between aggregate socioeconomic indicators based
on historical information and that these estimated relationships
will be reasonably accurate predictors of the same relationships in
the near and medium term future.
(INP) Input to model: The user supplies two types of information: data
regarding the energy project itself, and background Information
related to the region where the development will take place. These
1341
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Accession Ho. 16301000108 (cont)
are labeled 'exogenous variables". Information about the project
itself includes the nunber of workers directly employed in
operating and constructing the proposed facility in each year; the
•egauatts of electricity generated or the tons of coal mined each
year, and optionally, the labor force participation rate of the
•igrant population.
COOT) Output of nodel: The COALTOWN output generates the follouing
information for each year of the simulation run: the number of
workers employed by primary industries, the nuaber of workers
employed in ancillary Jobs, the nunber of nonfarm proprietors
(owners of businesses and self-employed persons), total employment,
relative real wages in the service sector as a percent of the base
year. Migration, population, the employment/population ratio, and
number of school children. Summary statistics for state, county,
school, and town revenues are also given, along with estimates of
school and county spending. The detailed tax output breaks revenues
into the following categories: coal severance, gross proceeds,
taxes on electricity generation, other taxes generated by mines and
generators, taxes on people and businesses (for example, income,
liquor, cigarette, and auto registration taxes), and
intergovernmental flows. Information is also given regarding
revenue sources peculiar to each State, such as the Myoming sales
tax, the school foundation program, or trust funds*
(APP) Applications of model: The COALTOMN model has been operated to
respond to numerous requests for information from Federal agencies,
various components of state governments, universities, national
laboratories, congressional offices, etc. The information provided
has ranged from projections of local impacts from coal mines for
environmental impact study purposes to projections of impact of
increased synfuels development in multi-county regions.
(HOtf) Computational system requirements - Hardware: Mainframe
Honeywell ;Printer standard
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
grarming
(REF) References - User manuals, documentation, etc.:
Bender, Lloyd D., George S. Temple and Larry C.
Parcels. "An introduction to the COALTONS Impact Assessment
Model." Working Paper. Environmental Development Division,
U.S. Dept. of Agriculture, May I960.
(CHM) Contact name(s): Bender,L.
(COR) Contact organization: U.S.D.A., Economic Development Division
(RQR) Responsible Organization: Office of Research and Development.
1342
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Accession No. 16301000111
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Coal Transportation Model
(ACR) Acronym of Data Base or Model: CTM
(MED) yedia/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: The Coal Transportation
Model simulates existing rail and barge transportation networks in
the contiguous U.S. The node! can be operated independently but is
nornally used in conjunction with the Interregional Coal Analysis
Model (ICAM). Data bases maintained in support of the ICAM and
Transportation Model are briefly described on attached sheets.
(CTC) CONTACTS: Kenneth Ebeling North Dakota State University
Loc: Fargo, North Dakota Ph: (701)237-7285
(CAP) Functional capabilities of model: The model uses a linear
programming approach to generate a least cost transportation
pattern for any given combination of coal production and demand
with various user generated constraints.
(ASM) Basic assumptions of model: The node! uses the assumptions
associated with linear programming techniques and is limited to
existing rail and barge networks. The model may identify potential
overloads of existing capacity but does not simulate additions to
current rail/barge networks.
(INP) input to model: The user must specify the magnitudes and
locations of coal production and electric utility coal demand.
These can be the base cost existing capacity and announced plans in
the data base or modifications of this data to reflect alternative
sceneries.
(OUT) Output of model: Output includes transportation volume and cost
for each link of the rail/barge network.
(APP) Applications of model: The model is currently being used to
evaluate coal transportation needs for 1985 and to identify high
volume and excess capacity areas.
(HDfcf) Computational system requirements - Hardware: Mainframe IBM 370
;Disc storage less than one disk drive ;Ma Printer any model ;Card
reader/punch
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;Engineering ;economics
(REF) References - User manuals, documentation, etc.:
Ebeling, Kenneth A., and Dalsted, N.L., Assessment
of Costs of Various Interregional Energy Transportation
Systems, Final Report to be Published, North Dakota State
University, Fargo, N.D.
(CNM) Contact name(s): Ebeling,K.
(COR) Contact organization: North Dakota State University
(ROR) Responsible Organization: Office of Research and Development.
1343
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Accession No. 16301000112
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: AIRTEST
(ACR) Acronym of Data Base or Model: AIRTEST
(MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: The Air Test Model is a
preprocessor to the Utility Simulation Model/ which can also be
used as a stand alone Model* Using actual fuel and specified
generation for each power plant or generating unit, it calculates
for one year the controlled and uncontrolled emission of SQ<2>,
N0, and particulates. In addition, the aodel selects the least
levelized cost fuel and pollution control option to Beet unit
specific emissions standards.
(CTC) CONTACTS: Edward H. Reckon
Loc: E.H. Peckon and Associates, Inc., 5537 Hempstead Way
Loc: Springfield, VA 22151 Ph: (703) 642-1120
(STA) Data Base status: Operational/Ongoing
(CAP) Functional capabilities of model: The options to meet the
applicable S0<2>, N0, and particulate standards currently
include: actual 1979 for fuels burned in the generating unit, coal
Hashing on a coal specific basis, low sulfur coal options for each
unit, coal-blending to meet unit specific standards, wet and dry
F.D.G., E.S.P. *s, fabric filters, Ion excess air, staged
combustion, flue gas recirculation, limestone injection burners,
and oil hydrodesulfurizatlon. The Air Test Model passes each
unit's low cost and fuel characteristics on to the Utility
Simulation Model.
(ASM) Basic assumptions of model: Assumes minimization of levelized
cost of fuel and pollution control vs. the decision factor in
selection of fuel and technology.
(IMP) Input to model: Actual fuel and specified generation for each
power plant or generating unit to be considered.
(OUT) Output of model: Controlled and uncontrolled emissions to S0<2>,
N0 and particulates, pollution control option and cost and fuel
type and cost for each unit.
(APP) Applications of model: AIRTEST is currently being used in the
Acid Rain Mitigation Strategies research program.
(HDH) Computational system requirements - Hardware: Mainframe CDC 7600
and IBM ;Disc storage 200 tracks approxim Printer Any model line
printer
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming }Engineering
(REF) References - User manuals, documentation, etc.:
Carol Bowan, Don Clements, Michael Moffet, Andy
Van Born. AIRTEST USER'S GUIDE. Nov. 1980.
Teknekron Report Ho. (RM-060-DOE80)
(ROR) Responsible Organization: Office of Research and Development.
1344
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Accession Mo. 16302000104
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Premixed One-Dimensional Flame Code
(ACR) Acronym of Data Base or Model: PROF
(MED) Media/Subject of Data Base or Model: combustion
(ABS) Abstract/Overview of Data Base or Model: The PROF code can be
used to predict the detailed chemical kinetic combustion and/or
pollutant formation events which occur in a Hide variety of
experimental and practical combustion devices. Both steady, free
and confined premised flames, where gaseous diffusion is important/
can be treated by the code. Also, Hell-stirred reactor, plug-flou
reactor, and fixed mass time-evolution chemical kinetic problems,
where diffusion is not explicitly treated, can be modeled by the
code. The code Has completed in February 1978 by Acurex
Corporation/Energy & Environmental Division of Mountain View,
California. Previously called: Modeling Studies in Combustion
Aerodynamics/ Chemistry.
(CTC) CONTACTS: W. Steve Lanier U.S. EPA Industrial Environ.
Research L Loc: Research Triangle Park, North Carolina 27711
Ph: (919) 541-2432
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-28-83
(CAP) Functional capabilities of model: The PROF code uas developed to
accurately model the detailed combustion and pollutant formation
processes occurring in premixed one-dimensional flames. Previous
plug-flow models applied to premixed flame combustion and pollutant
formation processes did not incorporate axial diffusion in the
formulation. Since ignition processes require upstream diffusion,
these plug-flow models could not be directly applied to flames
without making some gross assumptions as to the upstream ignition
zone starting conditions. In addition, the accuracy of these
nondiffusive models is very poor in the flame zone, where diffusion
is important. Since the PROF code includes axial diffusion,
predictions of combustion and pollutant formation processes can be
achieved in the flame zone as well as downstream of this zone. The
accuracy of these predictions is dependent only on the adequacy of
elementary kinetic reaction and transport data. Thus, PROF
predictions, combined with experimental data, can provide valuable
insights into the complex chemical events taking place within as
well as downstream of the flame zone.
(ASM) Basic assumptions of model: The key program element in the PROF
code is a stable and reliable kinetic chemistry routine. This
routine can be applied to any chemical system for which kinetic
reaction data are available. To model flame and reactor-type
problems, appropriate drive routines are linked to the general
chemistry routine. The flame model includes axial gas phase
diffusion and is mathematically, a multivariable boundary value
problem. This problem requires a coupled grid solution procedure
for all variables. This grid problem is solved in PROF by using a
predictor-linearized corrector iterative matrix procedure. The
reactor type models do not have explicit diffusion terms. These
models are initial value problems solved by simple time or space
marching in the PROF code*
1345
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Accession No. 16302000104 (cont)
(IHP) Input to «odel: Input to the code include: type of solution to
be obtained (e.g. well-stirred reactor), names and number of
chemical species, thermochemical data for che»ical species,
cheaical reactions and associated forward rate constants, third
body efficiencies, initial aole fractions, temperature, pressure,
and flow rates.
(OUT) Output of model: The PROF code output gives complete summary
information or flame, Hell-stirred and plug-flow reactor and
time-evolution cheaical kinetic problems. If called for, it can
also provide information on intermediate iterations and chemistry
routine solutions. For each iteration during a flame solution the
code always prints out a line of output which gives the flame speed
parameter, its error, the maximum error in concentration and the
constraint (i.e. damping) applied to the corrector step correction
vector. In addition, all of the input data is output along with
the title of the run.
(APP) Applications of aodel: The PROF code has been used widely by
Acurex and the Environmental Protection Agency to predict the
pollutant formation that occur in a wide variety of experimental
and practical combustion devices. The code has been applied to a
variety of gas turbine, furnace and catalytic combustion, and
pollutant formation problems. The PROF code has also been used to
treat the reaction of a fixed mass of gas in time as the pressure
and temperature change. Chemical evolution inside Internal
combustion engines, combustion bombs and other time- dependent
combustion systems have been predicted by this option. Of course
the option assumes uniformly mixed and reacting mixtures within the
system. Therefore, applying this option to spatially nonuniform
systems represents only an approximate modeling of the system.
(ROW) Computational system requirements - Hardware: Mainframe Univac
1108, IBM 360 or COC 6600 ;Disc storage 153 instrument, and 31978
words decimal storage are needed for data. ; Magnetic tape storage
or disk ^Printer 132 line printer >Card reader/punch or t
(LUG) Computational system requirements - Language(s) used: Fortran
(REF) Feferences - User manuals, documentation, etc.:
Kendall, R. M. and J. T. Kelly, Premixed One-
Dimensional Flame (PROF) Code User's Manual,
EPA-600/7-78-172a, August 1978.
(CNM) Contact name(s): Lanier,W.S.
(COR) Contact organization: U.S. EPA Industrial Environ. Research Lab
(RQR) Responsible Organization: Office of Research and
Development.Office of Environmental Engineering and
Technology.Industrial Environmental Research Laboratory.
1346
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Accession No. 16302000114
(OQ) Date of Questionaire: 12-02-82
CHAM) Name of Data Base of Model: Cost Effectiveness Model for
Pollution Control at Coking Fac
(ACR) Acronym of Data Base or Model: NONE
(MED) Media/Subject of Data Base or Model: Industry/economic
(ABS) Abstract/Overview of Data Base or Model: The computer model,
developed for coking facilities, allows the user to deteraine the
optimum mix of pollution control devices will be determined to
provide the greatest reduction in pollutant emissions. The model
uill optimize on the whole population of coke batteries or any
sub-set that is specified.
(CTC) CONTACTS: Robert C. McCrillis Industrial Environmental Research
Labor Loc: RTF, NC 27711 Ph: (919)541-2733
(STA) Data Base status: Discontinued
(DP) Date of form completion: 01-28-83
(CAP) Functional capabilities of model: The computer program
calculates and displays: the associated cost for each emission
control: the total captial and annual!zed cost for the optimum mix
of controls; and the emission levels in pounds of pollutant per ton
of coal and tons of pollutant per year for each of the four
pollutant types, particulates, benzene-soluble organlcs, benzo(a)
pyrene, and benzene.
(ASM) Basic assumptions of model: The model considers 16 emission
sources, 64 control options, 4 air pollutants (particulates,
benzene- soluble organics, benzo(a)pyrene, and benzene), 59 plants,
and 26 batteries. The controls and their costs are those that were
current at the time the model was developed (august 1979). These
can be modified as new information and data become available.
(INP) Input to model: Input to the model includes: initial level of
control coke battery population to be considered, level of control
desired for a specific pollutant or either the annualized cost or
capital cost.
(GOT) Output of model: The results of this model are the calculation
of emissions and emissions control costs and the selection of a set
of controls that will meet a given emission restriction at the
lowest cost possible.
(APP) Applications of model: The model provides a means for developing
regulatory strategies for achieving the greatest control of air
pollutant emissions from coke batteries at the lowest cost.
(HDH) Computational system requirements - Hardware: Mainframe Univac
1110 ;Printer any standard model
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ?Engineering
(REF) References - User manuals, documentation, etc.:
William F. Kemner, PEDCO Environmental, Inc.,
Cost Effectiveness Model for Pollution Control at Coking
Facilities, EPA Report EPA-600/2-79-185, August 1979.
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Engineering and
Technology.industrial Environmental Research Laboratory.
1347
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Accession No. 16303000108
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Centralized Treatment of Industrial
Hasteuater
(ACR) Acronym of Data Base or Model: Hone
(MED) Media/Subject of Data Base or Model: Hater ; Industry/economic
(ABS) Abstract/Overview of Data Base or Model: The objective of the
Centralized Treatment model is to produce an optimal geographic
pattern of treatment facilities for industrial wastewater in a
metropolitan area. An optimal pattern is one whose annual costs of
transporting and treating industrial Hasteuater is minimal.
Treatment facilities may be located at wastewater-preducing
industrial plants or at one or more candidate sites for centralized
treatment. Both capital and operating costs are considered. The
fundamental tradeoff resolved by the model is between the costs of
transportation and the economies of scale inherent in centralized
treatment. The model is formulated as a mixed integer program. It
is supported by a matrix generator and reports programs. The model
was developed by CSNTEC Corporation during 1979 and 1980 in
connection with an analysis of centralized treatment as an option
for meeting pretreatment regulations published by EPA in 1979.
Antecedents include a model for optimizing municipal sludge
handling and disposal systems developed by Yakir Hasit in his PhD
dissertation at Duke University in 1978, and It RAP, Haste Resource
Allocation Program, a model developed for EPA by Mitre Corporation
in 1977.
(CTC) CONTACTS: Howard Markham CENTEC Corporation
Loc: 11800 Sunrise Valley Drive Reston, Virginia 22091 Ph:
(703) 476-4000
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-24-83
(CAP) Functional capabilities of model: The model views the original
wastewater workload as 1, 2, or 3 streams emanating from each
industrial plant. The 3 stream types are chromium, cyanide, and
acid/ alkali. Each stream is characterized by a flow rate, the
concentrations of Cr+3, Cr+6, Cn, Zn, Fe, Ni, Cu, Cd, and Pb, and
through its plant or identification number, a geographic location.
Treatment processes considered are chrome reduction, cyanide
oxidation, neutralization/precipitation, flocculation,
clarification, thickening, and filtration. Each process may be
located at each industrial plant and at each candidate site for
central treatment* Each wasteuater source stream is required to
undergo full treatment in the sequence
neutralization-precipitation, flocculation, clarification,
thickening, and filtration. In addition, chroie and cyanide streams
must undergo chrome reduction and cyanide destruction,
respectively, before entering neutralization/precipitation.
Overflows from the clarifier and thickener go to the sanitary
sewer. Sludge from the filtration unit goes to a landfill. When
wastewater is transported from one site to another, storage tanks
with attendant costs are required at each site. Capital and
operating costs for each treatment process reflect economies of
scale. In addition to wastewater treatment processes, the model
1348
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Accession No. 16303000108 (cont)
considers the economics of uasteuater reduction Measures applied In
the plant production processes to reduce the size of source
streams. The BOdel determines the optimal pattern of uasteuater
reduction, the optimal size of each treatment process at each plant
and central site, and transportation flows among sites. Plants and
central sites may perform full treatment, partial treatment or no
treatment. A typical problem size is 50-100 plants, 1-3 candidate
central sites, and 1-2 landfills. That translates to a typical
model size of 4000- 8000 constraint equations with 500-1500 integer
variables, about half of the latter for representing increasing
returns to scale as piecewise linear equations. For mixed integer
programs of this size, it is not feasible to run the solution
algorithm long enough to prove optimality, but experience indicates
that an optimal or near-optimal solution is obtained on the 2nd or
3rd integer-feasible solution when the search criteria are chosen
to support that objective.
(ASM) Basic assumptions of model: The treatment processes modeled are
assumed adequate to meet treatment regulations uhen properly
operated. The performance of clarifiers, thickeners and filtration
units is modeled in terms of fixed efficiencies of solids capture
and fixed ratios of solid to liquid weights in the underflow.
Process sizes include a 20% safety factor. Transportation cost is
assumed to be a function of payload and distance* It is further
assumed that liquid waste is moved in 5500-galIon tank trucks only,
filled to capacity. Dewatered sludge is assumed moved in trucks of
30-cubic yard capacity, fully loaded. Separate capital recovery
factors are used for in-plant and central facilities, to permit
inclusion of rate-of-return requirements on capital investments by
industrial plants. The capital costs of central facilities include
a component for site acquisition and construction. Every plant and
central site is assumed large enough to accommodate treatment
equipment of sizes chosen by the model.
(IMP) Input to model: The model requires four kinds of input:
Technological Data. Cost and performance characteristics of
treatment technologies and transportation. With the exception of
occasional adjustments to costs, which is provided for in the model
via appropriate standard cost indices, this is a reasonably stable
set of data that need not be developed anew for each model run*
Plant and source Stream Data: For a region, the identity and
location of each industrial plant whose wastewater requires
treatment, and the flow rate and chemical composition of the
chrome, cyanide, and acid/alkali waste streams at each plant*
Also, the number of production lines where wastewater reduction has
been applied and for which it is feasible. Central Site and
Landfill Data: Location of candidate sites for central treatment,
and location of landfills suitable for receiving filtercake
containing precipitated metals. Economic Factors: Interest rates,
equipment lifetime. Wholesale Price Index for Industrial Chemicals,
Chemical Engineering Plant Cost Index, Chemical Engineering
Manpower Cost Index, sewer fee, landfill fee*
(GOT) Output of model: Three principle output reports are produced:
plant Report, central facility report, and transportation report.
1349
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Accession No. 16303000108 (cont)
The plant and central facility reports show whether a flow
reduction or treatment process is present at a site, and, when it
is, its size, capital cost, and operating cost. Operating cost is
broken out into labor, utilities, and chemicals. When
transportation is used, the costs of storage are shown. The
transportation report shows the workloads and costs of transporting
liquid wastes from plants to central facilities, and transportation
among central facilities. The costs of transporting sludge from
plants to central facilities and to landfills is also shown.
Regional totals are reported by process and resource. Subsidiary
outputs include the standard linear programming report of the model
solution, and reports of intermediate factors generated during
input preparation.
(APP) Applications of model: The model was used by CENTEC Corporation
to analyze centralized treatment in the Milwaukee region. That
analysis was performed in the project under whose aegis the model
was developed.
(ROW) Computational system requirements - Hardware: Mainframe Univac
1110 Series ;Disc storage Short term: 100 million bytes ^Printer
any 132 character per line nodel
(LMG) Computational system requirements - Language(s) used: FMPS and
GAMfcA
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;Engineering mathematical programming
CtfTP) Hater Models - Type of model: Water quality
Regional treatment system design
(COM) Processes and constituents included in model: Toxic chemicals
}Quality processes
(CPL) Complexity level of model: steady state mass balance ;multi
dimensional
(REF) References - User manuals, documentation, etc.:
CENTEC Corporation, Centralized Treatment Model.
User's Manual, August 1980.
CENTEC Corporation, Centralized Haste Treatment Mixed Integer
Programming Model -- Milwaukee Results, July 1980
Takir Hasit, Optimization of Municipal Sludge Handling and
Disposal Systems, PhD Dissertation at Duke University,
Department of Civil Engineering, 1978.
CENTEC Corporation, Centralized Treatment of Metal Finishing
Hastes, September 1980
HRAP, A Model for Regional Solid Haste Management Planninng -
User's Guide, EPA/530/SH574, U.S. Environmental Protection
Agency, February 1977
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Engineering and
Technology.industrial Environmental Research Laboratory.
1350
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Accession No. 16304000926
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Urban Hasteuater Toxics Flow Model
(ACR) Acronym of Data Base or Model: TOXFLO
(MED) Media/Subject of Data Base or Model: Toxic substances JWater
}Industry/economic
(ABS) Abstract/Overvieu of Data Base or Model: The Urban Hasteuater
Toxics Flow Model provides statistical estimation of the generation
and fate of toxic pollutants entering into a given Municipal sewage
treatment system. It can also develop a least-cost strategy of
industrial pretreatment and municipal treatment to satisfy
applicable environmental criteria. Quantities computed by the
model include flow and concentration values from each controllable
industrial discharger, flow and concentration values from the
domestic/ commercial sector, quality of the influent, effluent, and
sludge from the municipal sewage treatment plant, receiving stream
water quality, and the total cost of the industrial/muni- cipal
control technology utilized. The model can aid in developing
industrial pretreatment programs by indicating which industrial
dischargers and toxic pollutants may be problematic under existing
levels of treatment, and what impact alternative industrial
pretreatraent/municipal treatment technologies may have in
controlling toxic pollutants. The program is run in time-sharing
•ode over an interactive terminal.
(CTC) CONTACTS: Lewis Rossman U.S. SPA Municipal Environmental
Research La Loc: 26 West St. Clair St., Cincinnati, OB 45268
Ph: (513) 684-7636
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-18-83
(CAP) Functional capabilities of model: The model computes an average,
standard deviation, and confidence limit for the long term mean
flows and concentrations of toxic pollutants at various points
within an industrial/municipal wastewater treatment system* The
total cost of the industrial pretreatment and municipal treatment
provided is also computed. The model can consider up to 20
industrial dischargers (or aggregated discharge categories), a
maximum of 5 alternative treatment options at each discharger, and
up to 50 pollutants. Environ- mental criteria considered by the
model include local or national pretreatment standards, municipal
discharge or receiving water quality criteria, and municipal sludge
quality criteria.
(ASM) Basic assumptions of model: The model assumes statistical
independence between all industrial discharges and between the
performance of the municipal treatment plant and the flow in the
receiving stream. Municipal treatment plant removal capabilities
may be described as a deterministic function of influent
concentration coupled to a random error term. Confidence intervals
on long term means are developed based on assuming log normal
probability distributions. Cost optimization of the
industrial/municipal level of treatment is based on average
estimates of the long term means.
(INP) Input to model: Input to the model consists of means and
standard deviations for the flow and concentration of each
1351
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Accession Ho. 16304000926 (coot)
pollutant of Interest discharged from each industrial source and
the domestic/commercial sector. A set of pollutant removal
functions and their standard errors is required for the municipal
treatment plant. If a cost optimization is not being made then the
type of control used by each industry and the Municipality mist
also be specified. Statistics of the receiving water flow,
specification of the environmental quality criteria, and the cost
of all individual treatment alternatives »ay also be needed. There
is a possibility that at some future date, an internal data base
will be added to the »odel so that the input can be reduced to
specifying industrial sub-category types, pretreatment
technologies, and environmental quality criteria*
(OUT) Output of model: Standard output from TOXFLO consists of a table
of estimate statistics of the long term mean flows and
concentrations of each toxic pollutant from each industrial source,
in the Influent, effluent, and sludge of the municipal plant, and
of the receiving water. Also, reported is the expected frequency
of violation of environmental criteria and the cost of the control
policy being utilized.
(APP) Applications of model: TOXFLO was developed to aid in the
planning of industrial pretreatment programs. It can also be used
to assist in the analysis of municipal treatment facility discharge
permit requirements. An illustrative application of the model has
been made to controlling heavy metals in Kokomo, Indiana.
-------
Accession No. 16304000927
(DQ) Date of Questionaire: 12-02-82
(NAM) Karoe of Data Base of Model: Storm Hater Management Model
(ACR) Acronym of Data Base or Model: SHMM
(MED) Media/Subject of Data Base or Model: Mater
(ABS) Abstract/Overview of Data Base or Model: The EPA Storm Hater
Management Model (SHMM) Is a comprehensive mathematical model
capable of simulating urban stormuater runoff and combined sever
overflows including the spatial and temporal quality and quantity
aspects of the precipitation/runoff (snowmelt) process, conveyance
system transport, control measures, and receiving water responses.
The model operates in a continuous mode for detailed planning and
receiving water analysis or in a single event mode for indepth
analysis. Two transport routines are available: One is based on a
kinematic wave formulation while the other is based on the complete
St. Venant equations (i.e., HRE Transport) to include effects of
backwater, flow reversal, surcharging, looped connections and
pressure flow. Two receiving water models are included in SHMM:
RECEIV and LEVEL III - RECEIVING. RECEIV is a dynamic model
applicable to streams, rivers, estuaries, marshes/swamps and lakes.
LEVEL III - RECEIVING is a simplified continuous model applicable
to streams or tidal rivers that provides dissolved oxygen frequency
information.
(CTC) CONTACTS: Tom Barnwell ERC, Athens, GA U.S. EPA Municipal
Environmental Research
Laboratory, CURRENT CONTACT: Tom Barnwell, ERC, Athens, Georgia*
Loc: 26 H. St. Clair St., Cincinnati, OH 45268 Ph: (513) 684-7635
(STA) Data Base status: Operationa/Ongoing
(DF) Date of form completion: 01-18-83
(CAP) Functional capabilities of model: (1) Single event or continuous
simulation, latter has unlimited number of time steps, former
usually limited to 150-200 but can be unlimited also, depending on
portions of model utilized, continuous version simulates only
surface runoff (including simple gutter/pipe routing) and
storage/treatment? (2) Precipitation: input at arbitrary time
intervals for single event simulation (typically 1-15 min.) and at
one-hour intervals for continuous simulation, for snownelt
simulation daily max-min temperatures required for continuous, time
step temperatures for single event; (3) output at time step
intervals (or multiples), daily, monthly, annual, and total
summaries for continuous simulation; (4) Time step arbitrary for
single event (typically 5 minutes) and one hour for continuous, HRE
transport model time step depends on stability criteria, may be as
small as a few seconds; (5) Small to large multiple catchments:
(a) surface: lumped simulation of overland flow with allowance for
up to 200 subcatchments and six input hyetographs, up to 200
gutter/ pipes may be simulated by one-dimensional routing, (b)
channel/ pipes: one-dimensional network, up to 159
conduit/noneonduit elements for original transport model, up to 239
conduits in HRE transport model, up to two in-line storage units in
original transport model, (c) catchment area may be disaggregated
and modeled sequentially for simulation of areas too large for
existing SWMM dimensions, (d) storage/treatment simulated
1353
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Accession No. 16304000927 (cont)
separately, receiving input from upstream routing, (e) output from
surface, channel/pipe, or storage/treatment simulation may serve as
new input for further simulation by the latter tuo modules.
(ASM) Basic assumptions of model: (1) Deterministic model; (2) surface
quantity: iterative solution of coupled continuity and Manning
equations, integrated form of Horton infiltration (infiltration
rate proportional to cumulative Infiltration, not time), or Green-
Amp t; (3) Surface gutter/pipe routing, nonlinear reservoir assuming
water surface parallel to invert; (4) Channel/pipes: (a) original
transport: implicit finite difference solution to modified
kinematic nave equation, (b) WRE transport: explicit finite
difference solution of complete St. Venant equations, stability may
require short tine step: (5) Storage/ sedimentation: modified
Puls method requires table look-up for calculation of outflow; (6)
Surface quality, quality routing and treatment: algebraic
equations, no iterations required once flows and conduit volumes
are known.
(IMP) input to model: (1) Historical or synthetic precipitation
record, uses National Heather Service precipitation tapes for
continuous simulation, monthly evaporation rates for snoumelt:
daily max-min (continuous) or time-step (single event)
temperatures, monthly wind speeds, melt coefficients and base melt
temperatures, snow redistribution fractions and areal depletion
curves (continuous only), other melt parameters; (2) Surface
quantity: area, imperviousness, slope, width, depression storage
and Manning's roughness for pervious and impervious areas,
infiltration parameters; (3) Channel/pipe quantity: linkages,
shape, slope, length. Manning's roughness, URE transport also
requires Invert and ground elevation, storage volumes at manholes
and other structures, geometric and hydraulic parameters for weirs,
pumps, orifices, storages, etc., infiltration rate; (4)
Storage/sedimentation quantity: geometry, hydraulic
characteristics of outflows; (5) Surface quality; land use, total
gutter length, catchbasin volume and initial residuals
concentrations, street sweeping interval, efficiency and
availability factor, dry days prior to initial precipitation,
user-supplied initial residuals surface loadings, exponential
washoff coefficient or parameters for pollutant rating curve,
linear or nonlinear surface accumulation rates; (6) Dry-weather
flow on basis of diurnal and daily quantity/quality variations;
population density, other demographic parameters; (7) No input data
required for channel/pipe quality routing; (8) Storage/ treatment:
parameters defining exponential removal as function of residence
time in storage/sedimentation, parameters for individual treatment
options, e.g., particle size distribution, maximum flow rates, size
of unit, chemical additions, optional dry-weather flow data when
using continuous simulation; (9) Storage/treataent costs: ERR
Index, unit costs of excavation, land, power, chlorine, polymers,
alum, interest rate and amortization period; (10) Data requirements
for individual modules much less than for run of whole model, large
reduction in data requirements possible by aggregating (lumping) of
subcatchments and channel/pipes, especially useful for continuous
1354
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Accession No. 16304000927 (cent)
simulation.
(OUT) Output of model: (1) Input data summary including precipitation;
(2) Hydrographs and pollutographs (concentrations and loads versus
time) at any point in systea on time step or longer basis/ no
stages or velocities printed; (3) WRE transport also outputs
elevation of hydraulic grade line/ (4) Surcharge volumes and
required flow capacity/ original transport model Mill resize
conduits to pass required flow (optional); (5) Removal in
storage/treatment units/ generated sludge quantities; (6) Summaries
of volumes and residuals loads for simulation period/ continuity
check/ initial and final pounds of solids in conduit elements; (7)
Daily (optional)/ monthly/ annual and total summaries for
continuous simulation/ plus ranking of 50 highest hourly
precipitation/ runoff and BOO values; (8) Line printer plots of
hyetographs/ hydrographs/ and pollutographs; (9) Costs of simulated
storage/treatment options.
(APP) Applications of model: SWMM has been widely used in planning and
design studies for urban stormwater and combined sever overflow
pollution control (e.g./ under Section 108/ 201, and 208 studies).
It is widely used for urban drainage and flooding analysis. Users
are primarily consulting engineers/ public agency engineers and
university researchers. Presently semi- annual meeting of the SWMM
User's Group are held in the U.S. and Canada. Individual modules
have been linked to HECSTORM/ QUAL-II model/ simplified receiving
uater models/ and others. Individual modules have been altered and
renamed by various groups.
(HDW) Computational system requirements - Hardware: Mainframe IBM
360/370 or Univac 1108 or CDC 6600 or AMDAHL 4 Disc, storage 90,000
words core storage plus 5 units to process ; Magnetic tape storage
or disc ;Printer 132 position line printer ; Card reader/punch for
tape or disc (input)
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming Engineering ;Engineer familiar with urban hydro
(WTP) Hater Models - Type of model: Water run-off
(EH?) Environment(s) to which model applies: Estuary ;Stream/river
;Wetlands ;Non-point Urban
(CON) Processes and constituents Included in model: Dissolved oxygen
;Eutrophication ;Erosion and sediment ;Toxl Salinity ;Hydrology
;Hydraulics ;Quality processes
(CPL) Complexity level of model: transient mass balance ;one
dimensional ;multl dimensional ;
(REF) References - User manuals/ documentation/ etc.:
Metcalf and Eddy/ Inc./ University of Florida,
and Water Resources Engineers, Inc./ "Storm Hater Management
Model, Volume I - Final Report," EPA Report 11024 FOC (NTIS
PB 203 289)/ Environmental Protection Agency/ Washington/ D.C.,
July 1971.
Huber, W.C./ Heaney, J.P./ Medina/ M.A., Peltz, M.A., Sheikh,
H. and Smith, G.F., "Storm Water Manageaent Model User's
Manual - version II/" EPA-670/2-75-017/ Environmental Protection
Agency/ Cincinnati/ Ohio, March 1975.
1355
-------
Accession Mo. 16304000927 (cont)
Heaney/ J.P*/ Huber, W.C., Sheikh/ H./ Medina/ M.A./ Doyle/
J.R./ Peltz/ H.A. and Darling/ J.E./ "Urban Stormuater
Management Modeling and Decision Making," EPA-670/2-75-022/
Cincinnati, Ohio/ May 1975.
Medina/ M.A./ "Receiving Mater Quality Modeling for Urban
Stornuater Management: Level III/ "OSEPA Report
EPA-600/2-79-100, Environmental Protection Agency/ Cincinnati/
Ohio, August 1979.
Huber, W.C., Heaney/ J.P. and Mix/ S.J., "Storm Uater Managenent
Model User's Manual - Version III/** EPA Report, Environmental
Protection Agency, Cincinnati/ Ohio, Draft 1980.
(CMM) Contact naae(s): Ainon/D.
(COR) Contact organization: U.S. EPA Municipal Environmental Research
Laboratory
-------
Accession No. 16304000928
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: HATSPEC2
(ACR) Acronym of Data Base or Model: NATSPEC2
(MED) Media/Subject of Data Base or Model: Hater
(ABS) Abstract/Over view of Data Base or Model: HA1SPEC2 is a chemical
model for major element speciation of natural and drinking waters,
plus several additional constituents such as Sr, Ba, Fe, N0<3> and
H<2>S. HATSPEC2 is an expanded version of HATSPEC, developed by
T.M.L. Higley (ref. 1). The program takes analytical chemical data
and calculates aqueous speciation and solid saturation states, and
several indices of Hater corrosivity toward various kinds of
drinking water piping.
(CTC) CONTACTS: Herb Braxton O.S. EPA Municipal Environmental Research
Laboratory
Loc: 26 H St. Clair St., Cincinnati, OH 45268 Ph: (513) 684-7236
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-18-83
(CAP) Functional capabilities of model: The program considers the
effects of temperature and ionic strength on the formation of
complexes and ion pairs. The resulting values are used to
calculate the free ion activities, and these are used to calculate
some corrosion indices and saturation states of solids. The
accuracy of the program is dependent upon the accuracy of the
thermochemical data, the closeness of the system to equilibrium,
the accuracy of the species included in the model in describing the
real system, and the accuracy of the analytical data input. „
(ASM) Basic assumptions of model: The program assumes chemical
equilibrium, or a metastable state characterizable by operational
"equilibrium1* constants. Redox equilibrium is not assumed for
NO<3>/NH<4> system. The simultaneous equations are solved by a
continuing-fraction iteration technique. Temperature adjustment of
equilibrium constants are accomplished by either analytical
Polynomials or the Van't Hoff relation. The analytical data are
assumed to represent dissolved concentrations.
(INP) Input to model: HATSPEC2 accepts analytical chemical input as
mg/L (mg/L as CaCD<3> for alkalinity), rather than meq/L as in
WATSPEC. Program input also includes some calculation options if
some output is unnecessary, optional calculation of ionic strength
from TDS or SPC, temperature and a redox potential (or D.O.). The
program can be set to default to a particular pE.
(OUT) Output of model: The output includes aqueous speciation,
saturation indices for 43 solids, ion balance error, an
approximation of the buffer capacity of the water, the (chloride «•
sulfate)/ alkalinity ratio, the Aggressiveness Index, the
calculated pH of saturation for calcite and a fresh calcium
carbonate precipitate, the total inorganic carbonate concentration/
equilibrium C0<2> partial pressure, the calculated TDS, plus some
others.
(APP) Applications of model: This program has been used extensively by
the Drinking Hater Research Division, OS EPA to evaluate the
potential corrosivity of water supplies and to perform data
reduction for laboratory experiments.
1357
-------
Accession Ho. 16304000928 (cont)
(HDW) Computational systea requirements - Hardware: Mainframe IBM
370/168 ;Disc storage or tape - 5 tracks ;Magn Printer 132 position
line printer or terminal or direct terminal input ;Card reader/punch
(LUG) Computational system requirements - Language(s) used: ueter
chemistry knowledge and ability to enter data by card terminal
Fortran 61 compiler
<«TP) Mater Models - Type of model: Mater quality
Ground uater
drinking water
Environment(s) to which model applies: Estuary ;Lake
}Stream/river ^Marine
(COM) Processes and constituents included in model: Dissolved oxygen
;Eutrophication ;Toxic chemicals inorganics Salinity as
constituents ^Temperature ;Quality processes
(CPL) Complexity level of model: steady state mass balance /one
dimensional
(REF) references - User manuals/ documentation/ etc.:
T.M.L. Wigley/ WATSPEC: A Computer Program for
Determining the Equilibrium Speciation of Aqueous Solutions.
British Geomorphological Research Group Tech. Bull. Ho.
20(1977).
Michael R. Schock/ HAT SPEC 2 program and documentation/
unpublished/ Drinking Water Research Division/ OS EPA,
Cincinnati/ Ohio.
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Engineering and
Technology.Municipal Environmental Research Laboratory.
1358
-------
Accession No. 16304000929
/NH<4> system. The simultaneous equations are solved by a
continuing-fraction iteration technique. Temperature adjustment of
equilibrium constants are accomplished by either analytical
polynomial functions or by the Van't Hoff relation. The program is
of limited usefulness if the aqueous or solid species present in a
real system are not included in the model. Additionally, the
analytical data are presumed to represent dissolved concentrations*
(INP) Input to model: Input to the model includes: chemical
analytical data, (such as pH, Ca, Mg, titration alkalinity, Cl,
Pb), temperature, redox potential (or an estimator, such as D.O.),
options for calculations to be performed and thermochemical data
describing the reactions to be considered. Test data sets are
given in references 1 and 3. Thermochemical data and the ordering
of output species are contained in 4 external files that are called
by the program if operated as a load module, or that must follow
the program if run in-streanu
(OUT) Output of model: The output consists of the activities of the
1359
-------
Accession No. 16304000929 (cont)
aqueous species, the molarities of the aqueous species/ calculation
of ion balance error/ derivation of total inorganic carbonate
concentration from titration alkalinity
-------
Accession No. 16304000929 (cont)
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Engineering and
Technology.Municipal Environmental Research Laboratory.
1361
-------
Accession No. 16304000930
(DQ) Date of Questions!re: 12-02-82
(NAM) Name of Data Base of Model: REOEQL.DWRD
(ACR) Acronym of Data Base or Model: REDEQLDWRD
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/overview of Data Base or Model: A load aodule is
maintained/ along with a theraodynanic data deck/ of the
REDEQL.DWRD aqueous chemical equilibrium modeling program
originally developed by Ingle./ et al. at the Corvallis
Environmental Research Laboratory (refs. 1 and 2). This program can
calculate equilibrium aqueous speciation, saturation states of
solids and calculate dissolved and solid concentrations following
precipitation reactions. The prograa is useful for aquatic
toxicology studies/ titration experiment modeling (determination of
pH or complexation changes)/ water chemical evaluation for
corrosion control treatments and determination of solubility
controls on constituents in natural or drinking waters.
(CTC) CONTACTS: Herb Braxton U.S. EPA Municipal Environmental Res.
Lab.
Office of Vater Waste Management
Loc: 26 tf. St. Clair St., Cincinnati, Ohio 45268 Ph: 513-684-7236
(STA) Data Base status: Operational/Ongoing
(OF) Date of fora completion: 01-18-83
CCAP) Functional capabilities of model: The model can include up to 20
aetals and 30 ligands at any one time, many of which can be added
by the user. The model allows teaperature and ionic strength
corrections to equilibrium constants. The model allows the user to
impose solids in contact with the solution, to prohibit
precipitation of supersaturated solids, or to allow precipitation*
The prograa calculates aqueous and solid speciation, interaction
intensities and capacities, and can be used to calculate pH.
Several other options are noted In references 1 and 2. The
accuracy depends on the quality of the theraochemical data, the
accuracy of the species chosen to represent the real system, the
nearness to equilibrium, and the quality of the analytical data
input.
(ASM) Basic assumptions of model: The major assumption is that the
system in question is at equilibrium (or can be considered to be in
a metastable state that can be treated as equilibrium). Temperature
corrections to the equilibrium constants are done by the Van't Hoff
relation. Three solids and six complexes are allowed for each
aetal-ligand pair. Equilibrium constants can contain no aore than
one decimal place. Mathematical and computational limitations are
given in references 1 and 2. Charge balance is not required.
(IMP) Input to aodel: A program header card with Input and output
selections is included with each run. Ten cases can be considered
in each run. Concentrations of each aetal and ligand can be given
in "ag;/Ln or "- log (aolarity)." Cards are added to give carbon
dioxide partial pressure, redox reactions to consider, solids to
check saturation indices for, or for which to disallow
precipitation, etc. A test data set Is given In reference 2.
(OUT) Output of model: The aodel can output solid and aqueous
speciation in units of •* - log (aolarity)," and give a table
1362
-------
Accession No. 16304000930 (cont)
summarizing forms by percentage. Interaction capacities and
intensities can be given, and the ionic strength, saturation
indices for numerous solids, the pH, and several other parameters
can be calculated.
(APP) Applications of aodel: The model has been used extensively
Drinking Water Research Division, US EPA to determine water quality
adjustments to protect asbestos-cement, lead and galvanized pipe.
The program has been used to gain a comprehensive understanding of
the naturally-occurring chemical factors involved in preventing the
deterioration of asbestos-cement pipe, (see ref. 3)
(HDV) Computational system requirements - Hardware: Mainframe IBM
370/168 ;Disc storage 19 Tracks ;Magnetic tape Printer 132 position
line printer or terminal ;Card reader/punch
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Kno
nledge of water chemistry and ability to input data via
(WTP) fcater Models - Type of model: Mater quality
Ground water
drinking water
(EN?) Fnvironment(s) to which model applies: Estuary ;Lake
;Stream/river ;Marine
(COR) Processes and constituents included in model: Eutrophication
/Toxic chemicals inorganics, organic ligands Salinity as individual
constituents ^Temperature ;Quality processes
(CPL) Complexity level of model: steady state mass balance ;one
dimensional
(REF) References - User manuals, documentation, etc.:
Ingle, S.E. et al., A User's Guide for REOEQL.EPA,
A Computer Program for Chemical Equilibria in Aqueous Systems,
EPA-600/3-78-024 (1978).
Ingle, S.E. et al., REDEQL.EPAK Aqueous Chemical Equilibrium
Computer Program. Marine and Freshwater Ecology Branch,
Corvallis Environmental Research Laboratory, Corvallls, Oregon
(in press, 1980).
Schock, Michael R. and R. W. Buelow, the Behavior of Asbestos-
Ceient Pipe Under Various Mater Quality Conditions, A Progress
Report. Part 2 - Theoretical Considerations. Jour. ANNA,
(1961) in press.
Schock, Michael R. Computer Modeling of Solid Solubilities
as a Guide to Treatment Techniques. A paper given at the
seminar "Corrosion Control in Hater Distribution Systems,**
Cincinnati, Ohio, May 20-22, (1980).
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Engineering and
Technology.Municipal Environmental Research Laboratory.
1363
-------
Accession Ho. 16304000931
(DQ) Date of Questionaire: 12-02-82
(MAM) Nave of Data Base of Model: Hater Supply Simulation Model
(ACR) Acronym of Data Base or Model: HSSM
(MED) Hedia/Subject of Data Base or Model: Hater
UBS) Abstract/Overview of Data Base or Model: In Meeting the
requirements of the Safe Drinking Hater Act, VSSM can be used to
evaluate the trade-offs involved in aaking decisions concerning
water supply systems expansion, water production and facility
location. This model can be used by planners to study some of the
economic alternatives associated with regional water supply* It
incorporates a series of sub-models to describe the various aspects
of the economic/ demographic, and hydraulic systems that make up a
water utility. Extensive system hydraulic and cost data is needed
to use the model.
(CTC) CONTACTS: Robert M. Clark
Loc: DHRD/MERL/Cincinnati, Ohio (513) 684-7488
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-18-83
(CAP) Functional capabilities of model: This model can spatially model
the hydraulics and economies of a water supply system. The results
of the analysis is only as good as the data that is input to it.
(ASM) Basic assumptions of models Economies of scale exist such that
the unit cost of producing drinking water in smaller plants is
higher than for larger plants.
(IMP) Input to model: All hydraulic flows are needed based on a
diagram of the system. Construction costs are for piping and other
physical equipment needed for the system. Operation and
maintenance costs are for system use. Cost indices provide for the
effects of inflation.
(OUT) Output of model: The computer model is capable of producing
tabular and graphical output as well as diagrams of the operating
system.
(APP) Applications of model: Main use of model so far has been
Internally by the economic analysis section of DVRD, MERL, EPA in
Cincinnati, Ohio. After the completion of the model effort, it
will be made available to all who are Interested, such as
consultants, etc.
(HDH) Computational system requirements - Hardware: Mainframe-IBM 370
;Magnetic tape storage-none ;Prlnter-stand Card reader/punch
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ^Engineering
(HTP) Hater Models - Type of model: Drinking water
(EM?) Environment(s) to which model applies: Hydrolic analysis model
for drinking water networks
(CON) Processes and constituents included in model: Hydraulics
(CPL) Complexity level of model: Steady state mass balance
(REF) References - User manuals, documentation, etc.:
Rough drafts of documentation exist at present.
(RQR) Responsible Organization: Office of Research and
Development.Office of Environmental Engineering and
Technology.Municipal Environmental Research Laboratory.
1364
-------
Accession No. 16304000931 (cont)
1365
-------
Accession Mo. 16305000507
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: NAAQS Exposure Model
(ACR) Acronym of Data Base or Model: NEM
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: National Ambient Air
Quality Standards (NAAQ's) regulate six ubiquitous pollutants (CO,
NO, 03, SQ2, Pb and particulate natter) under Sections 108 and 109
of the Clean Air Act. The NAAQS Exposure Model (NEM) is a discrete
simulation model that can be used to estiaate both current hunan
exposure to each of these pollutants and exposure that would occur
were various alternative standards just aet. NEM develops
tiae-average exposure estimates in individual urban areas based
upon aabient air quality data, census information, huaan activity
data, and other user-supplied inforaation needed to approximately
describe day-to-day activities of residents. NEM is expensive to
run, if the number of age-occupation categories is large. In that
situation, costs to run the program increases approximately as the
square of the nuaber of exposure districts increases.
(CTC) CONTACTS: George Duggan Strategies and Air Standards Division,
OAQPS LQC: EPA, MD-12, Research Triangle Park, NC 27711 PH:
FTS 629-5611
(STA) Data Base status: Operational/Ongoing
(OF) Date of fora completion: 02-07-83
(CAP) Functional capabilities of aodel: NSM computes the following
exposure estimates for specified urban areas:! 1. Numbers of
people exposed to (specified averaging tiae) concentrations in a
year (for up to 20 user-specified concentration levels, which do
not need to have equal intervals). The specified averaging times
are presently 1, 3, 8, 24 hours and one year.jf 2. Nuaber of
person-occurances of exposures to specified averaging
concentrations in a year.f 3. Nuaber of people exposed to
(specified averaging time) aaxiaua concentrations in a year.f 4.
The same three iteas as aentioned above but for a specified
physiological index, such as CQHb levels in the blood.f The model
operates upon up to 13 age-occupation (A-0) groups, up to 9
exposure districts, up to 5 aicroenvironaents are indoor, so the
•odel can handle indoor sources of air pollution.
(ASM) Basic assuaptions of aodel: The aodel assuaes that an urban
area's population can be completely defined by the age-occupation,
etc. categories aentioned above. It also assuaes that their
•oveaents through tiae and space can be approximated by existing
huaan activity (or tiae budget) surveys and by origin-destination
inforaation obtained in 0. S. Census or in urban transport'Aation
planning surveys. The aodel also requires a complete set of
aabient air quality data at centroids of exposure districts (or in
"neighborhood types"), and that transforaation factors can be
developed froa a literature review to relate aabient air quality to
indoor pollutant concentrations. In addition, the aodel requires
"additive factors11 to account for indoor- generated and non-air
sources of the pollutant.
(IMP) Input to aodel: Needed inputs include: for each selected urban
area, a coaplete yearly set of hourly aabient air pollution
1366
-------
Accession No. 16305000507 (cont)
concentrations for each exposure district defined for the urban
area; age-occupation specific population estimates for each
district; hourly activity patterns for weekdays, Saturday, and
Sunday for each A-0 group; hourly microenvironnent assignments for
each A-0 group, with a corresponding activity level assignment;
tticroenvironment, transform factors; and additive factors to
represented indoor-generated and non- air sources. If a
physiological index model is used then NEM requires files of the
parameters/variables needed to completely define the equations used
to calculate the index number(s).
(OUT) Output of model: Outputs are tables and graphs depicting the
types of information noted in Item 2 above. Table headings, as
well as row and column headings are specified.
(APP) Applications of model: To date, NEM has been applied to CO, N02,
and particulate matter by the Ambient Standards Branch of the
Office of Air Quality Planning and Standards. The Office of
Research and Development and The Office of Mobile Sources have each
recently begun projects in which NEM will be applied.
(HOW) Computational system requirements - Hardware: Mainframe UKlVAC
1110 ; Magnetic Tape Storage None ; Disc Storage 100 Tracks ;
Printer
(LNG) Computational system requirements - Language(s) used: PL-1
(ATP) Air Models - Type of model: N/A, NEM is not a dispersion model
(OAQ) Model reviewed and approved by OAQPS? Yes
(PMP) Production method of primary pollutant in model: N/A
(MPk) Process used to remove pollutant from atomosphere: None (only
negligible removal)
(TME) Sample averaging time used: 24 Hours or less
(SRC) Source of pollutant: N/A, NEM is currently based on air quality
"concentrations data.
(AR) Area where sample was collected: N/A
(RUG) Distance traveled by pollutant from source: N/A
(REF) References - User manuals, documentation, etc.: Roy A. Paul.
User's Guide for NAAQS Exposure Model (NSM). Research Triangle
Park, N.C., U.S. Environmental Protection Agency/ 1981.
(CNM) Contact name(s): George Duggan
(COR) Contact organization: Strategies and Air Standards Division,
OAQPS
(ROR) Responsible Organization: Office of Air, Noise and
Radiation.Office of Quality Planning and Standards.Strategies and
Air Standards Division.
1367
-------
Accession No. 16402000121
(DQ) Date of Questionaire: 12-02-82
CHAN) Kane of Data Base of Model: LAGRANGIAN PHOTOCHEMICAL AIR QUALITY
SIMULATION MODEL
(ACR) Acronym of Data Base or Model: LPAQSM
(MED) Perila/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: LPAQSM Is designed to
predict the concentrations of ozone produced in an urban area by
•odeling the emissions, transport, and transformations in the
presence of ultraviolet radiation.
(CTC) CONTACTS: Jack Shreffler Environmental Sciences Research
Laboratory
Loc: Research Triangle Park Ph: (919)541-3659
(STA) Data Base status: Operational/Ongoing
(DP) Date of fora completion: 03-17-83
(CAP) Functional capabilities of model: The model is designed for
simulation between sunrise and sunset on a single day. It has five
levels of vertical resolution but describes only one area of an
urban domain at a particular time. Concentrations are output for
each 30 minutes along the trajectory.
(ASM) Basic assumptions of model: The model assumes a Lagrangian
parcel of air of dimensions typically 5x5 km by 1.5 tea high. The
parcel moves with wind/ entraining emissions which enter into the
photochemical reactions. Initial leading of pollutants is
specified, and the parcel has a rigid upper boundary and no lateral
diffusion.
(IMP) Input to model: 1. Emissions Inventory for hydrocarbons,
nitrogen oxide.
2. Surface network air quality and meteorological measure-
ments.
3. Upper air radiosonde data.
4. Solar radiation data.
The Regional Air Pollution Study (RAPS - St. Louis) data base is
being used with LPAQSM.
(OUT) Output of model: Output is in the form of computer printout*
Concentrations of ozone, carbon monoxide, sulfur dioxide,
hydrocarbons, and nitrogen oxides are supplied at 30 minute
intervals for 5 levels in the vertical.
(APP) Applications of model: The model builder. Environmental Research
and Technology, Inc., has tested the model against data in Los
Angeles as well as using it in environmental impact assessments.
EPA is testing the model against the RAPS data base.
(HDtf) Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 60,000 words ^Magnetic t Printer standard
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
-f gramming
(ATP) Air Models - Type of model: Numerical reactive
(OAQ) Model reviewed and approved by OAQPS? NO
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Chemical
(THE) Sample averaging time used: less than 24 hours
1368
-------
Accession No. 16402000121
-------
Accession No. 16402000122
(DQ) Date of Questionalre: 12-02-82
(HAM) Mane of Data Base of Model: LIVERMQRE REGIONAL AIR QUALITY MODEL
(ACR) Acronym of Data Base or Model: LIRAQ
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/OvervieH of Data Base or Model: LIRAQ is a single level
grid nodel designed to predict ozone concentration in an urban
area. The model simulates emissions transport and diffusion, and
photo- chemical reactions.
(CTC) CONTACTS: Jack shreffler Environmental Sciences Research
Laboratory Loc: Research Triangle Park Ph: (919)541-3659
Loc: NC, 27711
(STA) Data Base status: Operational/Ongoing
(DP) Date of fora completion: 03-17-83
(CAP) Functional capabilities of nodel: The nodel is designed
primarily for single day simulations. It has a single level in the
vertical although uses an analytic method to infer vertical
profiles. The grid is typically 20 elements in each axis.
Pollutant outputs represent 1-hour concentrations.
(ASM) Basic assumptions of model: The grid model can be set with
variable grid although a mesh of 5x5 km is recommended for
photochemistry because of storage problems. A wind processor
creates a divergence free Mind field over the region. Emissions
are added hourly.
(IMP) Input to model: The model requires an input data base including:
1. gridded emissions
2. a dense network giving meteorology and air quality
3. upper air Hinds
4. solar radiation data
The RAPS data base (St. Louis) is being used by EPA.
(OUT) Output of model: Primary output is by microfiche with a vide
variety of graphics. At each station a time series of predicted
pollutants is given. Also, for each hour of the simulation a
contour nap of each pollutant is produced. A verification package
•ill produce comparisons of predicted and observed valves including
correlations.
(APP) Applications of model: LIRAQ is being used by the Bay Area Air
Pollution Control District (San Francisco) for air guality
planning. The model is being tested by EPA on the RAPS data base-
WDM) Computational system requirements - Hardware: Mainframe CDC 7600
fDisc storage 1.5 million words ;Magnetic Printer standard
(LNC) Computational system requirements - Language(s) used: Fortran
Microfiche plotter
(ATP) Air Models - Type of model: Numerical reactive
(OAQ) Model reviewed and approved by OAQPS? NO
(PHP) Production method of primary pollutant in model: Secondary
(produced in atmosphere by chemical reactions)
(MPR) Process used to remove pollutant from atomosphere: Chemical
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: Multiple point and limited area
(AR) Area where sample Has collected: level or gently rolling terrain.
(RIG) Distance traveled by pollutant from source: 60-100 km
(RIP) References - User manuals, documentation, etc.:
1370
-------
Accession No. 16402000122 (cont)
Livernore Regional Air Quality Model (LIRAQ) -
Transfer to EPA.
OCRL - 52864, Laurence Livermore Laboratory, March 21/ 1980.
The EPA has United access through the Laurence Berkeley
Laboratory Computer system.
(see M9999 9999 04)
CROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1371
-------
Accession No. 16402000125
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Air Resources Laboratory Atmospheric
Transport and Diffusion
(ACR) Acronym of Data Base or Model: TRAJ
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The trajectory model
developed by Jerome Hefter is a computerized post-facto trajectory
model intended primarily for use in calculating transport/
diffusion/ and deposition of effluents on regional and continental
scales.
(CTC) CONTACTS: Dale Coventry U.S. EPA/ Environmental Sciences
Research
Laboratory/ Monitoring & Data Analysis
Loc: Research Triangle Park Ph: (919)541-3668
Loc: North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: In its present form 5-day
trajectories FORTRAN origin in North America 2) six-hour time
intervals and 3) forward and backward in time.
(ASM) Basic assumptions of model: The model moves the trajectory with
the average value of the winds in the layer selected/ either
surface or aloft.
(INP) Input to model: 1) Location of trajectory end-point 2) Starting
Date
3) Number of Days 4) Direction in Time 5) Map Boundaries
6) Met Data provided by Asheville sorted by Time and Stored on
Magnetic Tape.
(OUT) Output of model: Tables of trajectories points for every six
hours of each trajectory Tables of transport- layer depth every
three-hours for each trajectories Tables of maximum vertical
wind-shear in transport layer every three-hours each trajectories
Pricier - plots of trajectories - optional Optional - vertical
potential - temperature profiles for each STA Optional - Uooographs
for each STA Optional - Plotted concentration and deposition
accounts.
(APP) Applications of model: SOURCE IDENTIFICATION and SOURCE IMPACT
are two of this model's applications to date.
(HDU) Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 84 k ;Magnetic tape stor Printer any line
printer ;Card reader/punch
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: operator Knowledge/Skills: Pro
graining
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? NO
(MPR) Process used to remove pollutant from atomosphere: Negligible
removal
(TME) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: limited point (less than 10-20)
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: more than 100 km
1372
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Accession No. 16402000125 (cont)
(REF) References - User Manuals, docunentation, etc.:
NOAA TECHNICAL MEMORANDUM ERL ARL-81
(ARL-ATAD)
Jerone L. Hefter
(CUM) Contact name(s): Coventry,D.
(COR) Contact organization: U.S. EPA, Environmental Sciences Research
Laboratory, Monito
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Erivironaental Sciences Research Laboratory.
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Accession No. 16402000126
(DQ) Date of Questionaire: 12-02-82
(RAM) Name of Data Base of Model: Reactive Plume Model
(ACR) Acronym of Data Base or Model: RPM-II
(MED) Media/Subject of Data Base or Model: Air
(A8S) Abstract/Overview of Data Base or Model: The Reactive Plume
Model (RPM-II) is an air quality simulation nodal that provides a
tine history of pollutant concentrations within a chemically
reactive point source plume* Its purpose is to estimate the
concentration levels these species will attain within the plume
downwind of the source by simulating in the model the physical and
chemical processes responsible for the plume's evolution* These
include the emissions of primary pollutants from the source, their
transport and dispersion downwind, their chemical transformation
into secondary products, and the entrainment of background ambient
air into the plume* Simulated species of particular interest would
include NO, N0<2>, and 0<3>. RPM-II was developed and tested by
Systems Applications, Inc. (SAX) of San Rafael, California for the
Environmental Protection Agency.
(CTC) CONTACTS: Kenneth L. Schere Environmental Sciences Research
Laborat Loc: MD-80 Ph: (919) 541-3795
Loc: RTP, MC 27711
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: RPM-II simulates the reactive
system of N0- HC-0<3> species with the Carbon Bond-ll
generalized kinetic mechanism. This includes a set of 68 chemical
reactions with 35 separate species, including NO, N0<2>, 0<3>s six
classes of organics, PAN, CO, and other intermediate products. The
model is constructed within a Lagrangian framework. The plume
parcel is followed downwind from the source as it is advected by
the wind. The frame of reference moves with the parcel. The pluae
model is composed of a fixed number of cross-wind cells/ typically
from 2 to 10, that can expand as they move downwind. The rate of
horizontal dispersion is determined by Fickian diffusion
considerations. The rectangular cells comprising the plume are
considered well- mixed reactors. The model is applicable under
limited nixing atmospheric conditions and ground-level computed
concentrations are relevant only after the plume touch-down point
has been reached. While RPM-II is primarily designed for use as a
point source plume model/ an urban area plume may also be modeled
by considering the source area as a virtual upwind point source.
The model simulates the evolving concentrations using time steps of
less than a minute, but the model inputs and outputs are hourly
averages. Concentrations units are in parts per million. The
model's limitations include the requirement for valid ambient
concentration estimates of reactants along the plume trajectory,
and the specification of valid wind speeds and dispersion rates,
especially in complex terrain applications.
(ASM) Basic assumptions of model: The plume is assumed to advect
dowr.wind of the source according to the specified hour averaged
wind speed and direction. Fickian dispersion is assumed to govern
the diffusion between adjacent cells in the model and all cells are
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Accession No. 16402000126 (cont)
assumed to be well-mixed. The numercial solution of the set of
cfteraical reactions is by a modified version of the GEAR routine, a
Predictor - corrector method for stiff systems of differential
equations, it is implicity assumed that the Carbon Bond-II
mechanism is an accurate description of the chemical
transformations of NO-HC-0<3> in the real atmosphere.
(IMP) Input to model: Inputs to the model include: Hind speed and
dispersion rates as a function of time and downwind distance
respectively, average initial concentrations for all species and
the time- varying ambient concentrations (an option), hourly source
emission rates, and the time varying photolysis rates for the
photolysis chemical reactions. The reactions comprising the
chemical kinetic mechanism are also a set of inputs.
(OUT) Output of model: Outputs from RPM-II include: a printout of all
input data, a printout of the program control variables, a printout
of plume concentrations, plume widths, plume depths, wind speed,
and photolysis factors at various downwind distances, and printer
plots of average plume and ambient concentrations versus time.
Average concentrations are printed for each species within each
plume cell as well as average concentrations for the entire plume.
(APR) Applications of model: This model aids in the analysis of
reactive plumes from point sources. A limited data base from such
sources was collected as part of the Midwest Interstate Sulfur
Transport and Transformation (MISTT) project in and around St.
Louis in
1976. SAI analyzed this data base for use with the RPM-II and
applied the model to 10 test cases from it for the EPA. Despite
problems with the ambient HC measurements in the data base, model
results are encouraging.
(HDM) Computational system requirements - Hardware: Mainframe Univac
111C or equivalent ;Disc storage about 65,0 Printer any model
model
predictions using MISTT data. Proc. of Second Joint
Conference on Applications of Air Pollution Meteorology, New
Orleans, La. March 1980.
Liu, M.K., D.A. Stewart and P.M. Roth, 1978: An improved version
of the Reactive Plume Model (RPM-II). Paper presented at the
Ninth NATO/CCMS International Technical Meeting on Air Pollution
1375
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Accession No. 16402000126 (cont)
Modeling/ Toronto, Canada. August 1978.
Only draft documentation iron EPJl exists on the «odel at this ti«e.
(CUM) Contact na«e(s): Schere,K.L.
(COR) Contact organization: Environmental Sciences Research Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental processes and Effects
Research.Environmental Sciences Research Laboratory.
1376
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Accession No. 16402000127
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: SAI Airshed Model
(ACR) Acronym of Data Base or Model: SAIASP
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The SAI AIRSHED Model
Is a grid-type photochemical air quality simulation nodel. Its
primary purpose is to estimate the evolution of concentrations of
urban atmospheric smog-related pollutants/ including ozone* These
concentration estimates are based on simulating the physical and
chemical processes occurring in the ambient atmosphere that are
responsible for ozone production. These include the emissions of
organics and N0(x)/ chemical reactions of these precursors,
advection and dispersion among grid cells/ and transport of ozone
and its precursors into the model region from upwind areas. The
precursors include N0(2)/ NO/ and six classes of organics.
Typically a model simulation period is on the order of one day.
This model is guite complex and is rather input data-intensive.
Nevertheless/ it is useful for providing spatial and temporal
resolution of ozone concentration estimates based on a detailed
consideration of the underlying physical and chemical processes.
(CTC) CONTACTS: Kenneth L. Scherefcb-Environmental Sciences Research
Laborat Loc: MD-80 Ph: (919) 541-3795
Loc: RTF/ NC 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: The model considers emissions/
the atmospheric chemistry of ozone formation/ advection and
dispersion. The chemistry embedded in the model includes 71
reactions and 35 species including N0(2)/ NO/ six classes or
organics/ ozone/ PAH/ CO/ and several intermediate products.
Advection is simulated by estimating the transfer between
neighboring cells, and dispersion is estimated by using horizontal
and vertical diffusivity coefficients. Hind shear can also be
considered. The model considers these processes in each cell of a
three dimensional grid system. This grid system typically includes
four to six vertical layers of between 15 x 15 and 30 x 30 cells/
each cell being between two and ten kilometers square. The model
simulates the evolving concentrations using time steps of less than
a minute/ but the model inputs and outputs are hourly averages.
The principal limitations of the model are its complexity and the
substantial amount of data required.
(ASM) Basic assumptions of model: The SAI Airshed Model uses a finite
difference method to calculate the progression of pollutant
concentrations through a series of time steps. The model assumes
flat terrain in estimating concentrations/ although the influence
of the terrain on the wind field can be considered if the user is
able to do so. All emissions and all concentrations are assumed
uniformly mixed throughout each grid cell. It is assumed that
turbulent fluxes are linearly related to the gradients in the mean
concentrations so that eddy diffusivlties are used in the diffusion
calculations.
(INP) Input to model: The SAI Airshed Model requires various
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Accession Mo. 16402000127 (cont)
emissions, meteorological and air quality data for each grid cell
in the grid system. The emissions inventory must be gridded,
hourly, and must include 110(2), MO, and five classes of organics.
The meteorological and air quality input data are interpolated from
the values measured by a relatively dense monitoring network. The
meteorological data include yind speed, wind direction, nixing
height, atmospheric stability and photolysis rate constant and the
air quality data include concentrations of NOCx), organics, and
ozone at the beginning of the simulation and at the upwind
boundary. If an inert pollutant is being simulated, only data for
that pollutant is necessary.
(DOT) Output of model: The principal output of the model is a printed
array of concentrations at ground-level or any level aloft
throughout the grid for each hour for each major pollutant. This
array of concentrations is also put into disc storage in case the
user wishes to develop programs to analyze the data further. In
addition, the model provides the option of estimating
concentrations at specific sites by interpolating among the
concentrations in the surrounding grid cells.
(APP) Applications of model: The SAI Airshed Model has been used by
EPA and some state agencies to estimate the impact of emission
controls on urban ozone concentrations. The model is currently
undergoing evaluation and verification as part of the EPA Regional
Air Pollution Study (RAPS) model validation program. The urban
area modeled in this study is St. Louis, MO.
(HDIO computational system requirements - Hardware: Mainframe Univac
1110 or equivalent ?Disc storage about 70,0 Printer any model
(LUG) Computational system requirements - Language(s) used: Fortran
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Accession No. 16402000145
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Aerosol Transport Computer Model
(ACR) Acronym of Data Base or Model: AROSOL
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: AROSOL is a
three-dimensional K-theory model for the urban aerosol. AROSOL
computes particle size and composition distributions over a
three-dimensional grid covering a given urban area. The purpose of
the program is to establish the urban aerosol source-receptor
relationships and permit calculation of other quantities related to
the urban aerosol such as visibility, total mass concentration, or
hourly average respiratory dose of specific chemical species. The
complete model to permit these calculations is still under
development. Completed portions of the model have been used in
studies of gas transport using the St. Louis RAPS data base and in
modeling the super micrometric portion of the urban aerosol for
Maricopa County, Arizona; St. Louis, Missouri; and Buffalo, NeM
York.
(CTC) CONTACTS: Dr. Tate Tsang University of Texas at Austin
Loc: Chemical Engineering Dept. Ph: (512) 471-1328
Loc: Austin, Texas 78712
(STA) Data Base status: Operation/Ongoing
(DP) Date of form completion: 3-17-83
(CAP) Functional capabilities of model: AEROSOL will calculate time
variations in pollutant gas concentrations and aerosol size and
cocposition distributions in a three-dimensional grid covering a
given urban area. Since it is a K-theory model, it is expected
that it will describe well most atmospheric conditions except those
that are very stable or unstable.
(ASM) Basic assumptions of model: The model assumes that the urban
atmospheric concentrations of gases and aerosols can be calculated
froB a knowledge of their sources and the physical and chemical
processes intervening in the urban atmosphere. Atmospheric
dispersion is assumed to be described by the first order closure
assumption for turbulence—WK theory.1* The model solves the
resultant conservation equations for pollutant gases or the general
dynamic equation for the aerosol either by finite-difference
techniques or by orthogonal collocation on finite elements with
both options available.
(IMP) Input to model: Input to the model includes: numerical grid for
the urban area, hourly primary source inputs (point, line and
area). Hind field, stability conditions, and urban surface
roughness parameters. Calibration and verification of model
provided by comparisons to analytical solutions for single line
and area sources in numerical grid.
(DOT) Output of model: Output for pollutant gases is in form of
concentra- tions (Hg/m(3)) at the grid points in the
three-dimensional array, extending vertically up to the mixing
height. For the urban aerosol, output will include particle and
composition distributions at the grid points. These may be
presented in tables or as three-dimensional plots.
(HDW) Computational system requirements - Hardware: Mainframe CDC
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Accession No. 16402000145 (cont)
6600, 7600, CYBER ;Disc storage 220k ;*agnetic Printer line printer
jCaid reader/punch
CLHG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirenents: Operator Knowledge/Skills: Pro
graming ; Engineer ing
(ATP) Air Models - Type of model: Numerical reactive
(QAQ) Model reviewed and approved by OAQPS? NO
(PHP) Production nethod of primary pollutant in model: Primary
(emitted directly into atmosphere); Secondary
(MPR) Process used to remove pollutant from atomosphere: Combination
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Accession No. 16402000146
(OQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Simulation of Photochemical Smog
with Kinetic Mechanisms
(ACR) Acronym of Data Base or Model: CKIN ;CHEMK
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: Mechanisms that
describe the formation of photochemical smog are developed using a
computer modeling technique directed toward the simulation of data
collected in two snog chambers = an indoor chamber and a dual
outdoor chamber. Individual compounds for which specific
experiments were simulated and mechanisms developed include the
following: formaldehyde, acetaldehyde, ethylane, propylane,
butane/ and toluene. Experiments in both chambers were simulated
for all these compounds. The mechanisms reported describe the
decay of the premium organic compounds, formation and decay of
secondary organics/ conversion of nitrogen oxides, formation of
nitrates, and the appearance and decay of ozone. Special emphasis
is given to the chemistry of toluone. CHEMK is a fortran computer
program which, when given a predetermined kinetic mechanism,
computes the concentration of the various readants in time.
(CTC) CONTACTS: C.Z. Whitten Systems Applications, Inc.
Loc: 950 Northgate Dr. Ph: (415) 472-4011
Loc: San Rafael, CA 94903
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: This program incorporates the
Gear Integration Package of A. Hindmarsh of Lawrence Livermore
Laboratories (Livermore, California). This new version of CHEMK
can handle chemical kinetic mechanisms containing up to 89 species
and up to 200 reactions. The new version can also handle
photolysis rate constants and temperatures that very with time, and
reaction schemes with stoichiometric coefficients. Program requires
approximately 44k to load.
(ASM) Basic assumptions of model: Calculation of the time-dependent
concentration profiles of a number of reacting species in a complex
reaction mechanism is central to the science of chemical kinetics.
Such calculations allow this validation of kinetic schemes and
reaction rate constants through the comparison of predicted
concentrations with experimental data. Efficient computer programs
to integrate the system of ordinary differential equations (ODES)
associated with a kinetic mechanism, given a set of initial
conditions, have been developed. CHEMK relies on these advances.
(IMP) Input to model: Two separate sets of data are needed to execute
program: One set controls the computational part of the program,
and is necessary to establish the integration routine. The second
set controls the plotter output and provides the parameters
necessary to specify the output format. For details see Reference
f2.
(OUT) Output of model: Reactions are listed along with summary of
Initial conditions; reaction rate tables; line printer "plots" of
concentration versus time.
(APP) Applications of model: Tested within Atmospheric Chemistry &
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Accession No. 16402000146 (cont)
Physics Division, ESRL, EPA (Project Officer Harcia Dodge). No
known linkage to other models.
(HDH) Computational system requirements - Hardware: Calculator
/Mainframe any IBM or CDC with Fortran IV ;Printe Card reader/punch
reader required
(LHG) Computational system requirements - Language(s) used: Fortran IV
(QSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ^Chemistry
(ATP) Air Models - Type of model: Numerical reactive
(OAQ) Kodel reviewed and approved by OAQPS? YES
(PUP) Production method of primary pollutant in model: Secondary
(produced in atmosphere by chemical reactions)
(MPR) Process used to remove pollutant from atomosphere: Combination
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20)
(AR) Area where sample was collected: complex: rough terrain close to
body of water or in valley
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals/ documentation, etc.:
Modeling of Simulated Photochemical Smog
with Kinetic Mechanisms, Vol. 1, Final Report; EPA-600/3-
80-028a. February 1980
Modeling of Simulated Photochemical Smog with Kinetic
Mechanisms, Vol. 2, CHEMK: A Computer Modeling Scheme
for Chemical Kinetics; EPA-600/3-80-028b February 1980
(user manual)
(CNM) Contact name(s): Whitten,G.Z.
(COR) Contact organization: Systems Applications, Inc.
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
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Accession No. 16402000147
(DQ) Date of Questionaire: 12-02-82
(NAM) Karae of Data Base of Model: Photochemical Box Model
(ACR) Acronym of Data Base or Model: PBM
(MED) Kedia/Subject of Data Base or Model: Air
(A8S) Abstract/Overview of Data Base or Model: The Photochemical Box
Model (PBM) is a stationary single cell photochemical air quality
simulation model (PAQSM) designed to simulate the concentrations of
particular pollutant species within a well-mixed domain. Typically
the domain is centered on an urban area. The horizontal dimensions
of the cell are on the order of 20-30 km and are temporally
invsrient/ while the vertical dimension of the cell changes to
reflect the diurnally varying growth of the mixed layer above the
earth's surface. The principal species simulated by the PBM include
carbon monoxide, nitrogen monoxide and dioxide, ozone, and five
lumped-hydrocarbon classes: olefins/ paraffins/ aldehydes/
aroroatics/ and non-reactives. The processes of transport through
the domain/ entrainroent from aloft/ injection of source emissions
through the bottom of the cell/ and chemical transformations within
it are modeled. The PBM is quite simple in comparison to other
PAQSM's. It provides an hour-averaged measure of air quality taken
as a spatially integrated average over the volume of the cell for
each hour of simulation. Spatial resolution is not possible within
the model's structure.
(CTC) CONTACTS: Kenneth L. Schere#b-U.S. SPA Office of Research and
Develop Environmental Sciences Research Laboratory.
Loc; Research Triangle Park/ MD-80 Ph: (919) 541-3795
Loc: North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: The model considers emissions/
the atmospheric chemistry of ozone formation/ and advection. The
chemical kinetic mechanism within the PBM contains 24 species
participating in 36 reactions. The horizontal extent of the model
domain enables only a portion of an urban area to be modeled at a
time/ and hence an entire urban airshed connot be considered by the
PBM. Typically the domain encompasses the area where most of the
emissions sources are concentrated. The model domain is on the
order of 20 km x 20 ks x 1.5 km in dimension and is considered to
be a homogeneous volume of air. The meteoro logical situation of a
prevailing stagnating anti-cyclone might be most conducive to
application of the PBM.
(ASM) Basic assumptions of model: The PBM assumes a well-mixed model
domain at all times and a homogeneous pattern of emissions sources
across the bottom of the cell. The winds are assumed to fall into
one of two categories: (1) very light and directionally variable or
(2) above 2 m/s and directionally stable throughout the model
simulation period. The rates of change of the modeled
concentrations are described by a set of coupled ordinary
differential equations that are solved numerically through a method
developed by Gear.
(IMP) Input to model: The PBM requires various emissions/
meteorological/ and air quality data to be pre-processed before the
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Accession No. 16402000147 (cont)
nodel can be executed. The emissions inventory must have hourly
resolution and must include CO, N0(x), and five classes of organic
hydrocabons. The Meteorological and air quality data are averaged
over the available measurements. Some of the monitors should be
located outside of the model domain to give an indication of the
upwind boundary concentrations. The meteorological data include
wind speed, wind direction, mixing height, and photolysis rate
constants and the air quality data include concentrations of N0(x),
organics, and 0(3) at the beginning of the simulation and at the
upwind boundary.
(OUT) Output of model: The model provides a list of simulated
concentra tions for all species at ten-minute intervals during a
model simulation. The current mixing height, photolysis rate
constants, and Mind speed are also printed out. Also printer plots
of the time series of predicted and observed (if available)
concentrations are provided as well as a summary of hour-average
model predictions for principal species. The hour-average
predicted and observed concentrations from a given simulation may
be saved on disc storage at the user's discretion.
(APP) Applications of model: The Photochemical Box Model is an
evolving PAQSN being developed by the Modeling Sciences Section of
EPA's Meteorology Division. It has been used to model the air
quality for St. Louis, Mo., and Houston, Tx. The model is
currently undergoing evaluation and verification as part of the EPA
Regional Air Pollution Study (RAPS) model validation program.
(HOW) Computational system requirements - Hardware: Mainframe Onivac
1100 or equivalent ;Disc storage up to 25 t
(LN6) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ^Engineering ^atmospheric chemist and meteorolog
(ATP) Air Models - Type of model: Numerical reactive
(OAQ) Model reviewed and approved by OAQPS? NO
(PMP) Production method of primary pollutant in model: Secondary
(produced in atmosphere by chemical reactions)
(MPR) Process used to remove pollutant from atomosphere: Chemical
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: limited area sources, and multiple point
sources included.
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
Schere, K.L. and K.L. Demerjian, 1977.
A photochemical box model for urban air quality simulation
in Proceedings of the 4th Joint Conference on Sensing of
Environmental Pollutants, New Orleans, La., Nove. 1977,
pp. 427-433.
Demerjian, K.L. and K.L. Schere, 1979: Application of a
photochemical box model for 0(3) air quality in Houston,
Texas, in Proceedags of Ozone/Ox id ants: Interactions with
the Total Environment II, Houston, Texas, October 1979,
pp. 329-352.
(ROR) Responsible Organization: Office of Research and
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Accession No. 16402000147 (cont)
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1385
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Accession Mo. 16402000148
(DQ) Date of Questionaire: 12-02-82
(HAM) Kane of Data Base of Model: Point Source Models
(ACR) Acronym of Data Base or Model: PTMAX /PTDIS ;PTMTP
(MEO) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: These point source
models use Briggs plume rise methods and Pasquill-Gifford
dispersion nethods as given in EPA's AP-26, "Workbook of
Atnospheric Dispersion Estimates/* to estinate hourly
concentrations for stable pollutants. PTMAX is an interactive
program that performs an analysis of the Maxima short-term
concentrations from a single point source as a function of
stability and uind speed. The final plume height is used for each
computation. PTDIS is an interactive program that estimates
short-term concentrations directly dounuind of a point source at
distances specified by the user. The effect of limiting vertical
dispersion by a mixing height can be included and gradual plume
rise to the point of final rise is also considered. An option
allows the calculation of isopleth half-uidths for specific
concentrations at each dotmuind distance. PTMTP is an interactive
program that estimates for a number of arbitrarily located receptor
points at or above ground-level, the concentration from a number of
point sources. Plume rise is determined for each source. Dounuind
and crossuind distances are determined for each source- receptor
pair. Concentrations at a receptor from various sources are
assumed additive. Hourly meteorological data are used} both hourly
concentrations and averages over any averaging time from one to 24
hours can be obtained.
(CTC) CONTACTS: D. Bruce Turner D.S. EPA, Environmental Operations
Branch Loc: Mail Drop 80 Ph: (919) 541-4564
Loc: Research Triangle Park, North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: PTMAX estimates maximum
ground- level concentration and distance to maximum for
combinations of stability class and wind speed (internal to
program). PTDIS estimates the ground-level concentrations directly
dounuind of source for each dounuind distance specified (maximum
number of distances is equal to 50) for one set of specified
meteorological conditions. A table is produced with distance,
height of plume, and ground-level concentration given for each
distance. The program may reiterate for additional meteorological
conditions in the same run, or for additional source and
meteorology in the same run. PTMTP estimates concentrations at
arbitrary heights above ground for multiple sources at multiple
receptors for multiple hourly time periods. Input data is repeated
in tabular form. Total concentrations at each receptor and
concentration contribution from each source may be tabulated
hourly. Average concentrations (maximum 24 hours) are given for
each receptor. The concentration contribution from each source for
averaging time is optional.
(ASM) Basic assumptions of model: A. Source-Receptor Relationship.
For PTMAX all receptor locations are determined internally for a
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Accession No. 16402000148 (cont)
point of maximum. For PTOIS all receptors are considered directly
downwind of the plume. For PTMTP each source and receptor is
abritrarily located by coordinates In a kilometer grid scheme. B.
Emission Rate* A single constant eaission rate for each source is
assumed. C. Chemical Composition. The models treat chemical
composition as a single inert pollutant. D. Plume Behavior.
Gaussian spreading is both horizontal and vertical. Briggs (1969,
1971, 1972) plune rise formulas are used* Eddy reflection from the
ground in all three models is assumed/ and multiple eddy
reflections from the ground and nixing height are used in PTDIS and
PTMTP. If the plume height exceeds the mixing height, the
ground-level concentration is assumed to be zero. E. Horizontal
Hind Field. The wind speed is internal in PTMAX/ and it is
user-specified in PTDIS. The wind speed and direction are
user-specified in PTMTP. F. Vertical Wind Speed. This is assumed
to be equal to zero. G. Horizontal Dispersion. A Gaussian
horizontal plune shape is assumed. Dispersion parameters of
Pasguill- Gifford are dependent upon stability class. H. Vertical
Dispersion. A Gaussian plume shape is assumed. Dispersion
parameters of Pasquill-Gifford are dependent upon stability class.
I. Chemistry/Reaction Mechanism. This is not treated. J.
Physical Removal. This is not treated by the models. 1C.
Background. This is not treated by the models.
(OUT) Output of model: PTMAX: Output from the model is a
two-dimensional table giving maximum concentration/ distance to
maximum/ and height of final rise for each stability-wind speed
combination. OUTPUT: PTDIS: Output is ground level concentration
for a set of meteorological conditions. OUTPUT: PTMTP model
estimates output concentrations at various heights. INPUT: PTMAX
has the ability to run additional sources in the same run. PTDIS
can run additional meteorological or additional sources and
meteorology or other distances/ additional sources and meteorology
in the same run. PTMTP has optional output for hourly periods and
for concentration contribution from each source for averaging tine.
It can run for additional meteorology or additional receptors/ and
meteorology in the same run. This model/ which gives estimates for
a single point/ would not normally be calibrated or verified in
actual application/ but rather would be used for planning or design
purposes to find a "worst case" impact.
(APP) Applications of model: The source program for this dispersion
model is available as part of UNAMAP (Version 3)/ PB 277 193, for
$420 from Computer Products/ national Technical Information
Service, Springfield, VA 22161.
(HDV) Computational system requirements - Hardware: Mainframe Uni
1110 ;Disc storage 12K core memory
(LUG) Computational system requirements - Language(s) used: Fortran
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) process used to remove pollutant fro* atomosphere: Negligible
removal
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: limited point, multiple point/ and limited
1387
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Accession No. 16402000148 (cont)
area
CAR) Area where sample uas collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals/ documentation, etc.:
Turner, D.B., and Busse, A.D., Users*
Guides to the Interactive versions of Three Point Source
Dispersion Programs: PTMAX, PTDIS, and PTHTP,
Preliminary Draft, Meteorology Laboratory, U.S.
Environmental Protection Agency. Research Triangle Park,
NC 27711, 1973.
(CUM) Contact name(s): Turner,D.B.
(COR) Contact organization: U.S. EPA, Environmental Applications Branch
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1388
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Accession No. 16402000149
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Cliaatological Dispersion Models
(ACR) Acronym of Data Base or Model: COM ;CDMQC
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The Cliaatological
Dispersion Models (CDMQC/ COM) determine long-term (seasonal or
annual) quasi-stable pollutant concentrations at any ground level
receptor using average emission rates fron point and area sources
and a Joint frequency distribution of wind direction, yind speed/
and stability for the sane period. The User's Guide for the
Climatological Dispersion Model is available from the Environmental
Protection Agency as EPA-R4-73-024 and from MTIS (accession number
PB 227-346-AS). The Addendum To User's Guide For Climatological
Dispersion Model describing the enhancements available in the CDMQC
is available from EPA as EPA-45013-77-015 and from NTIS
(PB-274-040).
(CTC) CONTACTS: D. Bruce Turner U.S. EPA, Environmental Operations
Branch Loc: Research Triangle Park, Mail Drop 80 Ph: (919)
541-4564
Loc: North Carolina 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 3-17-83
(CAP) Functional capabilities of model: All input to the models
appears on output. Long-term concentrations corresponding to the
period of Joint frequency distribution of meteorological data
(usually seasonal or annual), assuming that the emission inventory
is valid for the same period, are produced for each receptor. The
two contributions to the concentration, those due to points and
those due to areas/ are output. Receptor locations are specified
by the user. An option is available to produce a pollutant
rose-contribution to the total concentration from each direction.
(ASM) Basic assumptions of model:
CDMQC and CDM use an arbitrary location for each point source/ and
area sources are represented in uniform grid squares. Receptor
locations are arbitrary/ as are release heights for point and area
sources. Receptors are assumed to be at ground level. The model
assumes that there are no terrain differences between the source
and receptors. B. Emission Rate. A single rate is allowed for
each point and area source. For area sources/ area integrations
are done numerically/ one 22.5 degree sector at a time; sampling at
discrete points is defined by specific radial and angular intervals
on a polar grid centered on the receptor. C. Chemical Composition.
CDMQC and CDM treat one or two pollutants simultaneously. D. Plume
Behavior. Only Briggs (1971) neutral/ unstable formula is used by
the model. If the stack height plus the plume rise is greater than
the mixing height/ then the ground level concentrations are assumed
to be equal to zero. As an alternate to the Briggs formula/ the
input value of the plume rise times the wind speed for each point
source can be used. No plume rise is calculated for area sources*
CDMQC and CDM do not treat fumigation or downwash. E. Horizontal
Hind Field. The models use a climatoiogical approach/ and utilize
16 wind directions and 6 wind speed classes. The wind speed is
1369
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Accession No. 16402000149 (cont)
corrected for the release height based on the power law variation
exponents from DeMarrais (1959). A constant, uniform
(steady-state) wind is assumed. F. Vertical Hind Speed. This is
assumed to be equal to zero. 6. Horizontal Dispersion. The models
use a clima- tological approach, and assume a uniform distribution
within each of 16 sectors (narrow-plume approximation). Averaging
time for the models is one nonth to one year. H. Vertical
Dispersion. The aodels use a semi- empirical/Gaussian plume with
five stability classes as defined by Turner (1964). Neutral
stability is split into day/night cases on input, and dispersion
coefficients are taken from Turner (1970). The stability classes
for area sources is decreased by one category from the input values
(to account for urban effects). Neutral dispersion coefficients
are used for all neutral and stable classes. No provision is made
for variations in surface roughness. I. Chemistry/Reaction
Mechanism* The models use exponential decay, and a user-input
half-life. J. Physical Removal. The aodels utilize exponential
decay and a user-input half-life. The same rate constant is aluays
applied. K. Background. A single constant background value is
Input for each pollutant.
(IMP) Input to model: Point and area source data, as well as
meteorological data must be input to the model.
(DOT) Output of model: Output from the model includes: input data;
one month to one-year averaging time simulated (arithmetic mean
only); arbitrary averaging time by the Larsen (1969) procedure
(typically 1-24 hours) which assumes a lognormal concentration
distribution and a pouer law dependence of median and maxinua
concentrations on the averaging time; an arbitrary number and
location of receptors; an individual point and area source
culpability list for each receptor; and a point and area
concentration rose for each receptor.
(APP) Applications of model: The source programs for these dispersion
models are available as part of UNANAP (Version 3), Computer
Products, NTIS, Springvield, VA 22161.
(RDV) Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 49k
(Lie) Computational system requirements - Language(s) used: Fortran V
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? YES
(PMP) Production aethod of primary pollutant in aodel: Priaary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Negligible
removal ;Chemlcal
(THE) Sample averaging time used: aore than 24 hours
(SRC) Source of pollutant: multiple point (aore than 10-20)
(AR) Area where saaple was collected: level or gently rolling terrain.
(RHG) Distance traveled by pollutant from source: less than 60 km
(REP) References - User manuals, documentation, etc.:
Busse, A.D., and Zimmerman, J.R., User's
Guide for the Climatological Dispersion Model, U.S.
Environmental Protection Agency, Research Triangle Park/
Worth Carolina, Environmental Monitoring Series,
1390
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Accession No. 16402000149 (cont)
EPA-R4-73-024, 131 p. (MTIS accession number PB 227-346/AS,
$4.75 paper copy), 1973.
Brubaker, K.L.; Brown, P., and R.R, Cirillo, Addendum
to User's Guide for Cliraatological Dispersion Model,
U.S. Environmental Protection Agency, Research Triangle Park,
Horth Carolina, EPA-450/3-77-015, 134 p. (»TIS accession
number PB-274-040, $7.25 paper copy), 1977.
(CMM) Contact nane(s): Turner,D.B.
(COR) Contact organization: U.S. EPA, Environmental Operations Branch
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environaental Sciences Research Laboratory.
1391
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Accession No. 16402000150
(DQ) Date of Questionaire: 12-02-82
(NAM) Naffle of Data Base of Model: Gaussian Plume Multiple Source Air
Quality Algorithm
(ACR) Acronym of Data Base or Model: RAH
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: This short-term
Gaussian steady-state algorithm estimates concentrations of stable
pollutants from urban point and area sources* Hourly
meteorological data are used/ and hourly concentrations and
averages over a number of hours can be estimated. The Briggs plume
rise and the Pasquill-Gifford dispersion equations with dispersion
parameters thought to be valid for urban areas are used in the
model. Concentrations from area sources are determined using the
method of Hanna, that is, sources directly upwind are considered
representative of area source emissions affecting the receptor.
Special features include determination of receptor locations
downwind of significant sources and determination of locations of
uniformly spaced receptors to ensure good area coverage with a
minimum number of receptors.
(CTC) CONTACTS: D. Bruce Turner EPA-Environnental Sciences
Research Lab Loc: Mail Drop 80 Ph: (919) 541-4564
Loc: RTP, NC 27711
(STA) Data Base status: Operational/Ongoing
(DP) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: Concentrations are estimated
hourly and for a longer averaging time (less than 24 hours) for a
limit of 150 receptor locations (all at the same height above
ground) from no more that 250 point sources and 100 area sources.
(ASM) Basic assumptions of model: Source-Receptor Relationship. The
model assumes an arbitary location for point sources/ and the
receptors may be: 1) arbitrarily located/ 2) internally located
near individual source maxima/ or 3) on a program-generated
hexagonal grid to give good coverage to a user-specified portion of
the region of interest. Receptors are all assumed to be at the
same height above (or at) ground/ and a flat terrain assumed. The
model uses a unique stack height for each point source. The model
user may specify up to three effective release heights for area
sources/ each assumed appropriate for a 5 m/sec wind speed. The
value used for any given area source must be one of these three. A
unique separation for each source-receptor pair is used. Emission
Rate. The model assumes a unique constant emission rate for each
point and area source. Area source treatment encompasses: narrow
plume approximation; area source used as input (not subdivided into
uniform elements): arbitrary emission heights input by user; areas
must be squares (side length - integer multiples of basic unit);
effective emission height equals that appropriate for a 5 m/sec
wind; and the area source contributions are obtained by numerical
integration along upwind distance of narrou-plume approximation
formulae for contribution from area-sources with given effective
release heights. Chemical Composition. This is treated as a single
inert pollutant. Plume Behavior. The model uses Briggs(8),(9)/(10)
plune rise formulas and does not treat fumigations or downwash. If
1392
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Accession Ho. 16402000150 (cont)
the plume height exceeds the nixing height, the ground level
concentration is assuied to be zero. Horizontal Hind Field. The
model uses user-supplied hourly vind speeds and user-supplied
hourly wind directions (nearest 10 degrees, internally modified by
addition of a random integer value between -4 degrees and +5
degrees* Hind speeds are corrected for release height based on
power law variation, exponents from DeMarrais(6); different
exponents for different stability classes are used, and the
reference height is equal to 10 meters. A constant, uniform
(steady-state) wind is assumed within each hour. Vertical Hind
Speed. This is assumed to be equal to zero. Horizontal Dispersion.
The nodel uses a semi-empiricaI/ Gaussian plune, and hourly
stability class is determined internally by TurnerO) procedure
(six classes are used). Dispersion coefficients are from McClroy
and Pooler(4) (urban) or TurnerO) (rural). No further adjustments
are made for variations in surface roughness or transport tine.
Vertical Dispersion. A semi-empirical/Gaussian plume is used.
Hourly stability class is determined internally. Dispersion
coeffficients are from McElroy and Pooler(4) (urban) or Turner(7)
(rural). Ho further adjustments are made for variations in surface
roughness. Chemistry/Reaction Mechanism. The model assumes and
exponential decay with a user-input half life. Physical Removal.
Exponential decay and a user-input half-life are used. Background.
This is not treated.
(INP) Input to model: Meteorological data must be input to the model.
(OUT) Output of model: Output produced by the model includes: hourly
and average (up to 24 hours) concentrations at each receptor; a
limited individual source contribution list; and cumulative
frequency distribution based on 24-hour averages and up to one year
of data at a limited number of receptors.
(APP) Applications of model: The source program for this dispersion
model is available as part of UNAKAP (Version 3), PB 277 193, $420,
from Computer Products, MTIS,
(HDH) Computational system requirements - Hardware: Mainframe Univac
1110 ?Disc storage ;41K of core
(LUG) Computational system requirements - Language(s) used: Fortran
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Nodel reviewed and approved by OAQPS? YES
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) process used to remove pollutant from atomosphere: Negligible
removal
(THE) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20)
(AR) Area where sample was collected: level or gently rolling terrain.
(RUG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
Novak, J.H., and Turner, D.B., "An
Efficient Gaussian Plume Multiple-Source Air Quality
Algorithm," Journal of the Air Pollution Control
Association, 26 (6), 560-575, 1976.
(CNN) Contact narae(s): Turner,D.B.
1393
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Accession No. 16402000150 (cont)
(COR) Contact organization: EPA-Environaental Sciences Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development,Office of Environmental Processes and Effects
Research.Environnental Sciences Research Laboratory.
1394
-------
Accession No. 16402000151
(DQ) Date of Questionaire: 12-02-82
(MAM) Kane of Data Base of Model: EPA HIHAY MODEL
(ACR) Acronym of Data Base or Model: HIWAY
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: HIMAY is an interactive
program which computes the hourly concentrations of non-reactive
pollutants downwind of roadways. It is applicable for uniform wind
condictions and level terrain. Although best suited for at-grade
highways, it can also be applied to depressed highways (cut
sections). The "User's Guide for HIHAY: A Highway Air Pollution
Model," is available for EPA as EPA-650/4/74-008 and from HTIS
(accession number PB 239-944/AS).
(CTC) CONTACTS: D. Bruce Turner EPA-Environmental Sciences
Research Lab Loc: Mail Drop 80 Ph: (919) 541-4564
Loc: RTP, »C 27711
(STA) Data Base status: Operational/Ongoing
(DP) Date of for« completion: 02-17-83
(CAP) Functional capabilities of model: Hourly estimates of
concentrations for receptors off roadways are determined resulting
from a single at-grade or cut-section roadway segment. The user
specifies geometry and emissions of roadway segment, meteorological
conditions to be simulated, and receptor coordinates and height of
receptor above ground.
(ASM) Basic assumptions of model: Source-Receptor Relationship: The
model uses a horizontal finite line with multiple line sources (up
to 24 lines). These are straight lines, arbitrary in orientatation
and length. One road or highway segment is run at a time.
Receptors are arbitrarily located, downwind of the source, with a
unique source-receptor distance defined. Arbitrary receptor heights
and arbitrary release heights are used. In the cut section mode
receptors cannot be located in the cut, and emissions are treated
as coning from 10 equal uniform line sources at the top of the cut.
A flat terrain is assumed, and line sources are treated as a
sequence of point sources; the number is such that convergence to
within 2% is achieved. Emission Rate: A constant uniform emission
rate for each lane is assumed. Chemical Composition: This is not
applicable to the model. Plume Behavior: This is not treated.
Horizontal Hind Field. The user specifies arbitrary wind speed and
direction. No variation of wind speed and direction with height is
allowed, and a uniform, constant (steady-state) wind is assumed.
Vertical Hind Speed. This is assumed to be equal to zero.
Horizontal Dispersion. The model uses a seal-empirical/ Gaussian
plume, and the user specifies which of 6 stability classes to be
used: Turner (1964). Dispersion coefficients used are from Turner
(1969); for distances less than 100m, dispersion coefficients from
Zimmerman and Thompson (1975) are used. In the level grade mode,
the initial value of the dispersion coefficient is 3 meters. In
the cut section mode, the initial value of the dispersion
coefficient is approximated as a function of the wind speed. No
further adjustments to the dispersion coefficients are made.
Vertical Dispersion. The model uses a semi-empirical/ Gaussian
Plume in which the user specifies stability class. Dispersion
1395
-------
Accession No. 16402000151 (cont)
coefficients used are from Turner (1969); for distances less than
100m, dispersion coefficients from Zimmerman and Thompson (1975)
are used. In the level grade mode, the initial o is equal to
1.5 meters. In the cut section mode, the initial o is equal to
a function of the wind speed* Chenistry/Reaction Mechanism. This
is not treated. Physical Removal. This is not treated. Background.
This is not treated.
(IMP) input to model: Initial set-up and calibration needs are: (1)
in batch mode residual discharges for vehicular line sources are
input and in interactive mode residual discharges are either input
or they may be requested from program; (2) meteorological data:
wind speed, wind direction, stability class, mixing height; (3)
ambient air concentration measurements. For verification of the
model, meteorological data and ambient air concentrations are
needed.
(OUT) Output of model: Output from the model includes a printout of
the 1-hour average concentration at each receptor.
(APP) Applications of model: The source program for this dispersion
model is available as part of UNAMAP (Version 3), PB 277 193 for
$420 from Computer Products, NTIS, Springfield, VA 22161.
(RDM) Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 12K core
(LUG) Computational system requirements - Language(s) used: Fortran
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? YES
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Negligible
removal
(TME) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: limited point (less than 10-20)
(AR) Area where saaple was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
Zimmerman, J.R.: and Thompson, R.S., 1975:
User's Guide for HIHAY: A Highway Air Pollution Model.
U.S. Environmental Protection Agency, Research Triangle Park,
NC. Environmental Monitoring Series, EPA-650/4-74-008, 59 p.
(NTIS accession number PB 239-944/AS).
(CNM) contact name(s): Turner,D.B.
(COR) Contact organization: EPA-Environmental Sciences Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1396
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Accession No. 16402000152
(DQ) pate of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Air Pollution Research Advisory
Comirittee Model 1A
(ACR) Acronym of Data Base or Model: APRAC-1A
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: APRAC, Stanford
Research Institute's urban carbon monoxide model, computes hourly
averages for any urban location. The model requires an extensive
traffic inventory for the city of interest, and its requirements
and technical details are documented in User's Manual for the
APRAC-lA Urban Diffusion Model Computer Program which is available
from NTIS.
(CTC) CONTACTS: D. Bruce Turner EPA-Environmental Sciences
Research Lab Loc: Mail Drop-80 Ph: (919) 541-4564
Loc: RTP, NC 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: The computer program can be
used to make calculations of the following types: Synoptic model:
hourly concentrations as a function of time, for comparison and
verification with observed concentrations and for operational
application. Climatologicai model: the frequency distribution of
concentrations/ for statistical prediction of the frequency of
occurrence of specified high concentrations in connection with
planning activities. Grid-point model: concentrations at various
locations in a geographical grid, providing detailed horizontal
concentration patterns for operational or planning purposes.
Roadway link information is limited to 1200 sources.
(ASM) Basic assumptions of model:
Source-Receptor Relationship. The user specifies the set of
traffic links (line sources) by providing link endpoints, road
type, daily traffic volume. The traffic links nay have arbitrary
length and orientation. Off-link traffic is allocated to a 2 x 2
mi. grid. Link traffic emissions are aggregated into a receptor
oriented area source array. The boundaries of the area sources
actually treated are 1) arcs at radial distances from the receptor
which increase in geometric progression; 2) the sides of a 22.5
degree sector oriented upwind for distances greater than 1000 ra.;
and 3) the sides of a 45 degree sector oriented upwind for
distances less than 1000 ra. A similar area source array is
established for each receptor. Sources are assumed to be at ground
level, and up to ten receptors are allowed in the model. Receptors
are at ground level and their locations can be arbitrary. Four
internally defined receptor locations on each user- designated
street are used in a special street canyon sub-model. B. Emission
Rate. Daily traffic volume for each link and off-link grid square
is input and modified by various factors to produce hour-by-hour
emissions from each link. Link emissions are aggregated as
described above: sector area source contributions are obtained
analytically, off-link traffic emissions on a two mile grid square
are added into the sector area sources. In the street canyon
sub-model, a separate hourly emission rate is provided by the user
1397
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Accession No. 16402000152 (cont)
for the link in question. C. Plume Behavior. The model does not
treat plume rise/ and it does not treat fumigation or downwash
except in the street canyon sub-model. In the street canyon
sub-model, a helical circulation pattern is assumed. D. Horizontal
Mind Field. Input for the aodel is hourly wind speed and direction
in tens of degrees. No variation of Hind speed or direction with
height is allowed. A constant, uniform (steady-state) wind is
assumed within each hour. E. Vertical Wind Speed. This is assumed
to be equal to zero except in the street canyon sub-model, where a
helical circulation pattern is assumed. F. Horizontal Dispersion.
Section averaging has a uniform distribution uithin sectors. Each
section larger than 1 km. is divided into sectors of 22.5 degrees;
sections within 1 km. of size are divided into sectors of 45
degrees. 6. Vertical Dispersion. The model utilizes a semi-
empirical/Gaussian plume. There are six stability classes/ and
each stability class is determined internally from user-supplied
meteorological data (modified by Turner,
1964). Dispersion coefficients from McElroy and Pooles
(1968) have been modified using information in Leighton and Ditmar
(1953). Ho adjustments are made for variations in surface
roughness, and the downwind distance variation of o(z) is assumed
to ax(b) for purposes of doing analytic integration. In the street
canyon sub-model, an empirical function of wind speed and street
width and direction is used. H. Chemistry/Reaction Mechanism.
This is not treated I. Physical Removal. This is not treated. J.
Background. The box model used to estimate contributions from
upwind sources beyond 32 km. is based on wind speed/ mixing height,
and annual fuel consumption. In the street canyon sub-model,
contributions from other streets are included in the background.
(IHP) Input to model: Emission and meteorological information are
needed for the model. Emissions are a function of the hour of the
day and the day of the week, and meteorological parameters are
functions of the hour of the day.
(OUT) Output of model: Output from the model Includes hourly
concentration values at each receptor and frequency distribution
based on hourly values.
(APP) Applications of model: The source program for this dispersion
•odel is available as part of ONAMAP (Version 3), PB 277 193, for
$420 from Computer Products, NTIS, Springfield, VA
22161. it ,
(HDW) Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 32k of core memory
(LNG) Computational system requirements - Language(s) used: Fortran
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Vodel reviewed and approved by OAQPS? YES
(PMP) Production method of primary pollutant In model: Primary
(emitted directly into atmosphere)
(NPR) Process used to remove pollutant from atomosphere: negligible
removal
(TME) Sample averaging tine used: more than 24 hours
(SRC) Source of pollutant: limited area
(AR) Area where sample was collected: level or gently rolling terrain.
1398
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Accession Mo. 16402000152 (cent)
(RUG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals/ documentation, etc*:
User's Manual for the APRAC-1A Urban Diffusion
Model Computer Program, NTIS ACCESSION number PB 213-091
(8 $5.25 per paper copy, $2.25 for microfiche).
A Practical, Multipurpose Urban Diffusion Model for
Carbon Monoxide, NTIS Accession Number 196-003.
Field Study for Initial Evaluation of an Urban Diffusion
Model for Carbon Monoxide, NTIS Accession Number
PB 203-469.
Evaluation of the APRAC-1A Urban Diffusion Model for
Carbon Monoxide, NTIS Accession Number PB 210-813.
Dabbert, H.F., Luduig, F.L., and Johnson, H.8., Jr.,
"Validation and Applications of an Urban Diffusion Model
for Vehicular Pollutants", Atmos. Environ., 7, 603-618,
1973.
Johnson, W.B., Luduig, F.L., Dabbert, H.F., and Allen,
R.J., "An Urban Diffusion Simulation Model for Carbon
Monoxide", Journal of the Air Pollution Control
Association, 23, 6, pp. 490-498, 1973.
(CNM) Contact nane(s): Turner,D.B.
(COR) Contact organization: EPA-Environmental Sciences Research
Laboratory
(ROR) Responsible organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1399
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Accession No. 16402000153
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Point, Area, Line Source Algorithm
(ACR) Acronym of Data Base or Model: PAL
(NED) Media/Subject of Data Base or Model: Air
CABS) Abstract/Overview of Data Base or Model: The Point, Area, Line
Source Algorithm is a short-tern Gaussian steady state algorithm
that estimates concentrations of stable pollutants from point,
area, and line sources. Computations froa area sources include
effects of the edge of the source. Line source computations can
Include effects from a variable emission rate along the source.
The algorithm is not intended for application to entire urban
areas, but for smaller scale analysis of such sources as shopping
centers, airports, and single plants. Hourly concentrations are
estimated and average concentrations for 1 hour to 24 hours can be
obtained.
(CTC) CONTACTS: D. Bruce Turner EPA-Environmental Sciences
Research Lab Loc: Mail Drop 60 Ph: (919) 541-4564
Locs Research Triangle Park, NC 27711
(STA) Data Base status: Operational/Ongoing
(DP) Date of fora completion: 03-17-83
(CAP) Functional capabilities of model: Concentration estimates are
given for up to 99 receptor locations, and there are concentration
estimates for 6 different source types/ as many as 99 sources of
each type. The model provides concentration averages for 1 to 24
hours for each source type.
(ASM) Basic assumptions of model:
Arbitrary locations are given for each point, area and line source.
Area source sizes are specified by an X and Y dimension. A
horizontal finite line or curved path is utilized, as is a slant
finite line. Receptor location Is arbitrary. Release heights for
point, area and line sources are arbitrary, as are receptor
heights. A flat terrain is assumed, and the model provides a
unique separation for each source-receptor pair. B. Emission Rate.
Point sources use a single rate for each source. Area sources also
use a single rate for each source. Area integrations are done by
numerical integration in the upwind direction of the concentration
from an infinite crossuind line source corrected for finite length.
Horizontal finite line and curved path sources assume a constant
uniform emission rate for each line. Slant line and special path
sources assume a variable emission rate along line or path. C.
Chemical Composition. The model does not treat this. D. Plume
Behavior. The model uses Briggs (1969, 1971,
1972) neutral/unstable formulas. If stack height plus
plume rise is greater than the mixing height, ground level
concentrations are assumed te be equal to zero. No plume rise
calculation is performed for area or line sources, and the model
does not treat fumigation or dounvash. E. Horizontal Wind Field.
Arbitrary wind speed and direction is user-specified. Variation of
ulnd speed with height is optional, and a constant, uniform
(steady-state) Hind is assumed, f. Vertical Hind Speed. This is
assumed to be equal to zero. G. Horizontal Dispersion. This model
uses a semi- empirical/Gaussian plume. The user specifies which of
1400
-------
Accession Ho. 16402000153 (cont)
the six stability classes are to be used: Turner (1964).
Dispersion coefficients are from Turner (1969). For distances less
than 100m, dispersion coefficients for line sources are from
Zimmerman and Thompson (1975), The initial value of the dispersion
coefficient is specified by the user, and no further adjustments to
the dispersion coefficients are made. H. Chemistry/Reaction
Mechanism. This is not treated. I. Physical Removal. The model
does not treat this.
(IHP) Input to model: The user must specify the source types and
provide meteorological data*
(OOT) Output of model: Output from the model includes hourly and
average (up to 24 hour) concentrations at each receptor.
(APP) Applications of model: The source program for this dispersion
model is available as part of ONAMAP (Version 3), PB 277 193 for
$420 from Computer Products, NTIS, Springfield, VA 22161 22161
(HDV) Computational system requirements - Uarduare: Mainframe Dnivac
1110 ;Disc storage 51k approximately
(LIG) Computational system requirements - Language(s) used: Fortran
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? NO
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Negligible
removal
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: Limited and multiple point, limited area,
and limited time
(AR) Area where sample Has collected: level or gently rolling terrain.
(RIG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
Petersen, W.B., User's Guide for PAL, A
Gaussian Plume Algorithm for Point, Area, and Line Sources,
U.S. Environmental Protection Agency, Research Triangle
Park, North Carolina, Environmental Monitoring Series,
EPA-600/4-78-013, 1975.
Turner, D.B., and Petersen, W.B., A Gaussian Plume
Algorithm for Point, Area, and Line Sources, NATQ/CCMS
Sixth International Technical Meeting on Air Pollution
Modeling and Its Application, V 42: 185-228, 1975.
(CNM) Contact name(s): Turner,O.B.
(COR) Contact organization: EPA-Environmental Sciences Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1401
-------
Accession No. 16402000154
(OQ> Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: HIHAY-II
(ACR) Acronya of Data Base or Model: HIHAY-II
(MED) Media/Subject of Data Base or Model: Air
CABS) Abstract/Overview of Data Base or Model: HIWAY-2 is a batch and
interactive program which computes the hourly concentrations of
non-reactive pollutants downwind of roadways. It is applicable for
uniform wind conditions and level terrain. Although best suited
for at- grade highways, it can also be applied to depressed
highways (cut sections). The "User's Guide for HIHAY-2: A Highway
Air Pollution Model," is available for EPA as EPA-600-8-800-018 and
from NTIS as PB 80-227-576.
(CTC) CONTACTS: William Peterson EPA/Environmental Sciences
Research Lab Loc: Research Trinagle Park, Ph: (919) 541-4564
Loc: NC 27711
(STA) Data Base status: Operational/Ongoing
(OF) Date of fora completion: 03-17-83
(CAP) Functional capabilities of nodel: Hourly estiaates of
concentrations for receptors off roadways are determined resulting
from a single at-grade or cut-section roadway setaent. The user
specifies geoaetry and eaisslons of roadway segment, aeteorological
conditions to be siaulated, and receptor coordinates and height of
receptor above ground.
(ASM) Basic assuaptions of aodel: Source-Receptor Relationship: The
aodel uses a horizontal finite line with aultiple line sources (up
to 24 lines). These are straight lines, arbitrary in orientation
and length. Receptors are arbitrarily located, downwind of the
sources, with a unique source-receptor distance defined. Arbitrary
receptor heights and arbitrary release heights are used. In the
cut-section aode receptors cannot be located in the cut, and
emissions treated as coaing froa 10 equal uniform line sources at
the top of the cut. A flat terrain is assuaed, and line sources
are treated as a sequence of point sources; the number is such that
convergence to within 2% is achieved. Eaission Rate: A constant
uniform emission rate for each lane is assuaed. Chemical
Coaposition: This is not applicable to the aodel. Pluae Behavior:
This is not treated. Horizontal Hind Field: The user specifies
arbitrary wind speed and direction. No variation of wind speed and
direction with height is allowed, and a uniform, constant
(steady-state) wind Is assuaed. Vertical Hind Speed: This is -
assuaed to be equal to zero. Horizontal Dispersion: The aodel uses
a seai-eaplrical/ Gaussian pluae, and the user specifies which of 6
stability classes to be used. Turner (1964). For distances less
that 300 a empirically derived dispersion parameters are used, Rao
et al. (1980). In the level grade aode, the intial value of the
dispersion coefficient is twice the value for the initial vertical
dispersion coefficient. In the cut- section node, the initial
value of the dispersion coefficient is approximated as a function
of the wind speed. Vertical Dispersion: The aodel uses a
seai-eaplrical/ Gaussian pluae in which the user specifies
stability class. Dispersion coefficients used are froa Turner
(1969); for distances less than 300 a dispersion coefficients froa
1402
-------
Accession No. 16402000154 (cont)
Rao et al. (1980) are used. In the level grade mode, the initial
o is a function of the crossroad wind component with a maximum
value of 3.57 m and a minimum value of 1.5 n. In the cut section
•ode the initial dispersion parameter is a function of Hind speed.
I. Chemistry/Reaction Mechaniss. This is not treated. J. Physical
Removal. This is not treated. K. Background. This is not treated.
(IMP) Input to model: Initial set-up and calibration needs are (1) in
both batch and interactive node, discharges for vehicular line
sources are input into the program; (2) meteorological data: wind
speed, wind direction, stability class, mixing height; (3) anbient
air concentration measurements. For verification of the nodel,
Meteorological data and ambient air concentrations are needed.
(DOT) Output of nodel: Output fro* the nodel includes a printout of
the 1-hour average concentration at each receptor.
(APP) Applications of nodel: The source program for this dispersion
nodel is available as a part of UNANAP (Version 3), PB 277-193 for
$420 from Computer Products, NTIS, Springfield, VA
22161.
(HDH) Computational system requirements - Hardware: Mainframe Univac
1100 ;Disc storage 6K
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? YES
(PHP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(HPR) Process used to remove pollutant from atomosphere: Negligible
removal
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: Automotive
(AR) Area where sample was collected: level or gently colling terrain.
(RUG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
Petersen, V.B., 1980. user's Guide for
HIWAY-2: A Highway Air Pollution Nodel. U.S.
Environmental Protection Agency, Research Triangle Park,
MC., EPA-600/8-80-018, 70 p.
Rao, S.T. and M.T. Koonan, 1980: Suggestions for
Improvement of the EPA-HIHAY Model. JAPCA, 30, 6, pp
247-256.
(CHM) Contact narae(s): Peterson,H.
(COR) Contact organization: EPA/Environmental Sciences Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1403
-------
Accession No. 16402000155
(DQ) Date of Questionalre: 12-02-82
(MAN) Name of Data Base of Model: Multiple Point Gaussian Dispersion
Algorithm with Optional
(ACR) Acronym of Data Base or Model: MPTER
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: MPTER is a multiple
point-source Gaussian nodel with optional terrain adjustments.
MPTER estimates concentrations on an hour-by-hour basis for
relatively inert pollutants (i.e., sulfur dioxide and TSP). MPTER
uses Pasquill-Gifford dispersion parameters and Briggs plume rise
nethods to calculate the spreading and the rise of plumes. The
•odel is »ost applicable for source-receptor distances less than 10
kilometers and for locations with level or gently rolling terrain.
Terrain adjustnents are restricted to receptors whose elevation is
no higher than the lowest stack top. In addition to terrain
adjustments options are also available for wind profile exponents,
buoyancy induced dispersion, gradual plume rise, stack downuash,
and plume half-life.
(CTC) CONTACTS: Tom Pierce and Bruce Turner EPA Environmental
Sciences Re Laboratory
Loc: Davis Drive Ph: (919) 641-4564
Loc: RTP, MC 27711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: MPTER computes hour-by-hour
concentrations for relatively inert pollutants for each
source-receptor pair. MPTER can handle up to 250 point sources and
180 receptors. Model users have the option of specifying elevations
and location coordinates in either metric or English units. Hourly
met data can be read either off cards or off disk/tape. MPTER can
calculate concentrations for averaging periods of 1, 3, 8 and 24
hour for up to a year's data. Annual concentrations can also be
computed.
(ASM) Basic assumptions of model: NPTER is based upon Gaussian
dispersion theory using mean meteorology conditions on an
hour-by-hour basis. Dispersion coefficients used to calculate both
vertical and horizontal spreading are those of Pasquill and
Gifford. The rising plume is assumed to completely reflect off the
top of the nixing height in neutral and unstable conditions. The
plume rise is based on Briggs. MPTER can also optionally consider
stack downwash, buoyancy induced dispersion* and gradual plume
rise. MPTER can either utilize constant emission rates or hourly
emission rates for each point source. The emitted pollutants
should be relatively inert chemically since MPTER does not consider
complex physical removal or chemical reaction processes. Users can
approximate exponential decay of a pollutant by supplying a
half-life. Hind speeds are extrapolated to stack top using user
supplied wind profile exponents. The optional terrain adjustment
reduces the plume height relative to the ground. Additional
terrain adjustment factors can be entered which control the
proportion of terrain adjustment g according to stability
class.
1404
-------
Accession No. 16402000155 (coot)
(IMP) Input to model: Input for MPTER Includes: control data,
emission data, receptor information, and hourly met data. The
hourly met data can be read either off cards or fron a disk/tape
preprocessed from NCC surface/upper-air observations. Hourly
emission data can optionally be input from disk/tape.
(DOT) Output of model: The variety of MPTER options allow the user to
output to a printer or to write to tape information required for a
multitude of applications. Tape/disk files can be written
containing hourly concentrations for each receptor for each source,
hourly concentrations for each receptor for all sources,
concentrations for user specified averaging periods, and highest
five concentrations for each receptor for each averaging period.
MPTER allows even more flexibility on printed output. The range of
options include printout for the highest five concentrations for
each receptor to printout for hourly contributions from each source
at each receptor.
(APP) Applications of model: The frequent use of MPT2R is to assess
air quality from multiple point sources to compare with National
Aibient Air Quality Standards for SOC2) or TSP. MPTER can estimate
concentrations for a single source at one or more receptors for one
hour, or it can simulate concentrations on an hour-by-hour basis
for as many as 250 point sources at up to 1180 receptors for up to
a year. The types of multiple applications for which MPTER is
suited include stack design studies, combustion source permit
applications, regulatory variances evaluation, monitoring network
design, control strategy evaluation, coal conversion studies,
control technology evaluation, new source review, and prevention of
significant deterioration (within 10 km).
(HDH) Computational system requirements - Hardware: Mainframe IBM 360,
CDC 6600, or Univac 1100/82 ;Disc storage Magnetic tape storage or
disc ^Printer 132 position line printer ; Card reader/punch,and/or
tape/disc input
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;Air quality meteorology
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? YES
(HPR) Process used to remove pollutant from atomosphere: Negligible
removal
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20)
(AR) Area where sample was collected: level or gently rolling terrain.
(RUG) Distance traveled by pollutant from source: less than 60 km
(REP) References - User manuals, documentation, etc.:
Pierce, T.E. and Turner, O.B., 1980: User's
Guide for MPTER: A Multiple Point Gaussian Dispersion
Algorithm with Optional Terrain Adjustment. EPA-600/8-80-016,
U.S. Environmental Protection Agency, Research Triangle Park,
NC. 239pp.
O.S. Environmental Protection Agency, 1980: MPTER tape.
(Computer programs on tape containing programs, and PTPLU
screening model) NTIS PB 80-168156, National Technical
1405
-------
Accession No. 16402000155 (cent)
Information Service, Springfield, ?A.
(CUM) Contact nane(s): Turner,!.P.
(COR) Contact organization: EPA Environmental Sciences Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environaental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1406
-------
Accession No. 16402000156
(DQ) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: Point Source Gaussian Plume Model
(ACR) Acronym of Data Base or Model: PTPLU
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: PTPLU Is a point source
dispersion Gaussian screening model for estimating maximum surface
concentrations for 1-hour concentrations. PTPLU is based upon
Briggs plume rise methods and Pasquill-Gifford dispersion
coefficients as outlined in the Workbook of Atmospheric Dispersion
Estimates. PTPLU is an adaptation and improvement of PTMAX which
allows for wind profile exponents and other optional calculations
such as buoyancy induced dispersion, stack downwash, and gradual
plune rise. PTPLU produces an analysis of concentration as a
function of wind speed and stability class for both wind speeds
constant with height and wind speeds increasing with height. Use
of the extrapolated wind speeds and the options allows the model
user a more accurate selection of distances to maximum
concentration.
(CTC) CONTACTS: Tom Pierce EPA/Environmental Sciences Research
Laborato Loc: MD-80 Ph: (919) 541-4564
Loc: Research Triangle Park, NC 27711
(STA) Data Base status: Operational/Ongoing
(Dp) Date of form completion: 03-17-83
(CAP) Functional capabilities of model: PTPLU estimates the maximum
ground-level concentration and the distance to the maximum for both
wind speeds constant with height and wind speeds increasing with
height for each stability class. The user has the option of
selecting anemometer height, receptor height, wind profile
exponents, stack downwash, buoyancy induced dispersion, gradual
Plune rise, and mixing height. Output consists of 2 two-
dimensional tables listing maximum concentrations, distance to
maximum concentrations, and effective plume heights for a range of
surface wind speeds and extrapolated wind speeds in each stability
class.
(ASM) Basic assumptions of model: PTPLU calculates the source-
receptor distance to the point of maximum concentration for each
wind speed and stability class. Relatively inert pollutants are
modeled and emissions are assumed to be constant. The plume is
spread horizontally and vertically using P-G dispersion
coefficients. Briggs plume rise computations are employed with
options available for buoyancy induced dispersion, stack downwash,
and gradual plume rise. PTPLU does not allow for any depletion of
the plume by physical removal or chemical reactions. Eddy
reflection with the ground is assumed. If the effective plume
height is calculated to be below the mixing height in neutral and
unstable conditions, then multiple reflections of the plume between
the ground and the mixing height are computed. But if the
effective plume height is above the mixing height in neutral and
unstable conditions then no calculations are made for ground-level
concentrations. Mso, ground-level concentrations are not
calculated if the distance to maximum concentration extends beyond
100 kilometers from the source. Cautionary messages are printed
1407
-------
Accession No. 16402000156 (cont)
for plume heights greater than 200 meters and plume resident times
greater than that expected under normal atmospheric conditions*
(INP) Input to model: PTPLU is extremely convenient since only nominal
effort is needed to supply the necessary input. Four data cards
are needed for a single run, however/ additional separate point
sources can be analyzed by input of two data cards for every
source. Information required to run PTPLU includes selection of
options, anemometer height, wind profile exopnents, stack
parameters (emission rate, stack height, exit velocity, stack gas
temperature, and stack diameter), receptor height, and mixing
height.
(DOT) Output of model: PTPLU is a screening model and its output
results can be helpful in more detailed modeling. In particular,
the tables of concentration and distance to maximum concentration
can be examined for selection of receptor distances for use in
detailed models.
(APR) Applications of model: The source code of PTPLU is written in
ASCII Fortran. PTPLU calls six subroutines but on the DNIVAC
1100/82 PTPLU does not require any special software or facilities.
approximately 12K of core memory are needed for execution on the
UNIVAC 1100/82.
(RDM) Computational system requirements - Hardware: Mainframe Unlvac
1100/82, IBM 360, CDC 6600 ^Printer 132 cha
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;Air quality meteorology
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? YES
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Negligible
removal
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: limited point (less than 10-20)
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
The PTPLU source program is presently
avaialable on the MPTER tape from COMPUTER PRODUCTS,
NTIS, Springfield, Va 22161. Ask for PB80-168156; the
price is $420. The PTPLU program will also be available
on UNAMAP (Version 4) scheduled to arrive at NTIS in
December 1980. Preparation of a users guide is underway,
and the users guide should be available by October 1981.
(CUM) Contact name(s): Pierce,T.
(COR) Contact organization: EPA/Environmental Sciences Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1408
-------
Accession No. 16402000157
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Averaging Tine Model
(ACR) Acronym of Data Base or Model: AV6TIME
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: AVGTIME is a
mathematical model based on two characteristics that are often
demonstrated by air quality data: (1) air pollutant concentrations
tend to be lognormally distributed for all averaging tines and (2)
median (50 percentile) concentrations tend to be proportional to
averaging tine raised to an exponent and thus plot as a straight
line on logarithmic graph paper. Tvo percentile concentrations (at
the same or at different averaging tines) are read into the BOdel
and concentrations for the maxima or any percentiles can then be
calculated for any other averaging tines.
(CTC) CONTACTS: Ralph Larsen Environmental Sciences Research
Laboratory
Loc: MD-80 Research Triangle Park, Ph: (919) 541-4564
Loc: NC 27711
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 03-17-83
(CAP) Functional capabilities of nodel: The detailed characteristics
of the nodel are described by a dozen equations on pp. 51-52 in
Ref. 2. Tuo input concentrations are entered into the proper
equation to calculate two output parameters: the geometric nean
and standard geometric deviation for one averaging tine. The other
equations are then used to calculate these two output parameters,
the maxima, and the concentrations for any desired percentiles for
any other averaging tines.
(ASM) Basic assumptions of nodel: Analyses of air pollutant
concentration data suggest that urban concentrations often tend to
fit a general mathenatical model having the following three
characteristics: (1) Pollutant concentrations are lognormally
distributed for all averaging tines. (2) Median concentrations are
proportional to averaging time raised to an exponent. (3) Maxinun
concentrations are approximately inversely proportional to
averaging tine raised to an exponent. A 2- parameter averaging
tine nodel with the above three characteristics has been developed
(Refs. 1 and 2). Air pollutant concentrations measured near
isolated point sources often do not fit a 2-paraneter lognornal
distribution very well. Such data often do fit a 3-paraneter
lognormal distribution fairly well. A 3-parareeter averaging tine
nodel has therefore been developed to model such data (Ref. 3).
(IMP) Input to model: The user inputs any tuo air quality neasurenents
for the 2-paraneter model. These two input parameters might be the
concentrations exceeded 0.1% and 30% of the tine for 1 hr average
concentrations for instance. The two input concentrations can be
at the same or different averaging tines. The user inputs any
three air quality neasurenents into the 3-paraneter nodel, at
either the sane or at different averaging tines.
(OUT) Output of model: The equations mentioned under "Functional
Capabilities'* are used to calculate expected concentrations.
Expected highest and second highest concentrations for various
1409
-------
Accession No. 16402000157 (cont)
averaging tines {1, 3/ 8, and 24 hr, and 1 yr) can be easily
determined by using Table II in Ref. 3. The 3-parawetec averaging
tine model is sore difficult to use than is the 2-paraaeter Model.
Trial and error techniques can be used to calculate the third
paraneter (a constant that is added or subtracted from each of the
three input concentration measureaents) needed to fit the data to a
2-parameter iognormal distribution. Alternatively, a 500 card
FORTRAN job deck is available that will calculate expected maxima
and percent!le concentrations for several averaging times based on
three concentration neasurenents input to the Model. The job deck
is available on request froa the "Technical Contact" listed belou.
(APP) Applications of aodel: As the title of Ref. 2 implies, the
averaging tine nodel has been used to relate air quality
measurements to air quality standards to determine overall average
percent emission reductions neeed to achieve air quality standards.
The input air quality data can either be Measured or
dispersion-modeled. Air quality data for one averaging tine have
been used to calculate percentiles and expected maxima for other
averaging tines for Hhcih air quality standards have been written*
Air quality aeasurenents Might be available for 24 hr average
concentrations of sulfur dioxide for instance. The Model could be
used to calculate expected maximum concentrations for 3 hr averages
and these maxima could then be compared with the 3 hr sulfur
dioxide National Ambient Air Quality standard (MAAQS).
(HDtf) Conputational systea requirements - Hardware: Calculator
;Mainframe Dnivac or IBM
(LNC) Computational systea requirements - Language(s) used: Fortran
(QSK) Conputational systeM requirements: Operator Knowledge/Skills: Mod
el is usually used manually.
(OAQ) Model reviewed and approved by OAQPS? YES
(PMP) Production method of priMary pollutant in Model: PriMary
(emitted directly into atnosphere)
-------
Accession No. 16402000157 (cont)
(ROR) Responsible Organization: Office of Research and
Development.Off ice of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1411
-------
Accession No. 16404000136
-------
Accession No. 16404000106 (cont)
(404) 546-3148
(CAP) Functional capabilities of model: The set of unit process models
used to compute the kinetics of toxicants is the central core of
EXAMS. These unit models are all "second-order" models/, in other
words/ each process equation includes a direct statement of the
interactions between the chemistry of a toxicant and the
environmental forces that shape its behavior in aquatic systems.
Most of the process equations are based on standard theoretical
constructs or accepted empirical relationships. For example/ the
light intensity in the water column of the system is computed using
the Beer-Lambert law/ and temperature corrections for rate
constants are computed using Arrhenius functions. lonization of
organic acids and bases/ and sorptlon of the toxicant with
sediments and biota/ are treated as thermodynamic properties or
(local) equilibria that constrain the operation of the kinetic
processes. For example/ an organic base in the water column may
occur in a number of molecular species (as dissolved ions/ sorbed
with sediments/ etc.)/ but only the uncharged/ dissolved species
can be volatilized across the air-water interface. EXAMS allows
for the simultaneous treatment of up to 15 molecular species of a
toxicant. These include the parent uncharged molecule/ and singly
or doubly charged cations and anions/ each of which can occur in a
dissolved/ sediment-sorbed/ or biosorbed form. The model computes
the fraction of the total concentration of toxicant that is present
in each of the 15 molecular structures (the "distribution
coefficients/" ALPHA). These values enter the kinetic equations as
multipliers on the rate constants. The model thus completely
accounts for differences in reactivity that depend on the molecular
form of the toxicant. EXAMS makes no intrinsic assumptions about
the relative transformation reactivities of the 15 molecular
species. These assumptions are under direct user control through
the way the user structures the chemical input data. EXAMS computes
the kinetics of transformations due to direct photolysis/
hydrolysis/ biotransformation/ and oxidation reactions. The input
chemical data for hydrolytic/ biological/ and oxidative reactions
can be entered either as single valued/ second-order rate
constants/ or as pairs of values defining the rate constant as a
function of the environmental temperature specified for each
compartment. EXAMS includes two algorithms for computing the rate
of photolytic transformation of a toxicant. These algorithms were
structured to accommodate the two more common kinds of laboratory
data and chemical parameters available to describe photolysis
reactions. The simpler of the algorithms (subroutine PHQTOl)
requires only an average first-order rate constant (KDP€)
applicable to near-surface waters under cloudless conditions at a
specified reference latitude (RFLATG). In order to give the user
control of reactivity assumptions/ KDPG is coupled to user-supplied
(normally unit-valued) reaction quantum yields (QOANTG) for each
molecular species of the toxicant. The more complex algorithm
(subroutine PHOT02) computes photolysis rates directly from the
absorption spectra (molar extinction coefficients/ ABSG) of the
compound and its ions/ measured values of the reaction quantum
1413
-------
Accession No. 16404000106 (cont)
yields, and the environmental concentrations of competing light
absorbers (chlorophyll, suspended sediments, dissolved organic
carbon, and water itself). The total rate of hydrolytic
transformation of a toxicant is computed by EXAMS as the sum of
three contributing processes. Each of these processes can be
entered via simple rate constants, or as Arrhenius functions of
temperature. The rate of specific acid catalyzed reactions is
computed from the pH of each sector of the ecosystem, and specific
base catalysis is computed from the environmental pOH data. The
rate data for neutral hydrolysis of the compound is entered as a
set of pseudo-first- order rate coefficients (or Arrhenius
functions) for reaction of the 15 (potential) toxicant species with
the water molecule. EXAMS allous the user to compute biodegradation
of the toxicant in the water column, and in the bottom sediments,
of the system as entirely separate functions. Both models are
second-order equations that relate the rate of biodegration to the
size of the bacterial population actively degrading the compound.
The second-order rate constants (KBACHG for the water column,
KBACSG for benthic sediments) can be entered either as single-
valued constants or as functions of temperature. When a non-zero
value is entered for the Q-10 of a biodegradation (parameters
QTBAhG and QTBASG respectively), KBAC is interpreted as the rate
constant at 20 degrees C., and the biotransformation rate in each
sector of the ecosystem is adjusted for the local temperature
(BICTMG). Oxidation reactions are computed from the chemical input
data and the total environmental concentrations of reactive
oxidizing species (alkylperoxy and alkoxyl radicals, etc) specified
by the user. The chemical data can again be entered either as
simple second-order rate constants, or as Arrhenius functions.
Internal transport, and export, of a toxicant occur in EXAMS via
advective and dispersive movement of dissolved, sediment- sorbed,
and biosorbed materials, and by volatilization losses at the
air-water interface. EXAMS provides a set of vectors (JFRADG,
etc.) that allows the user to specify the location and strength of
both advective and dispersive transport pathways. Advection of
water through the system is then computed from the water balance,
using hydrologic data (rainfall, evaporation rates, streamflows,
groundwater seepages, etc.) supplied as part of the definition of
each environment. Dispersive interchanges within the system, and
across system boundaries, are computed from the characteristic
length (CHARLG), cross-sectional area (XSTDRG), and dispersion
coefficient (DSPG) specified for each active exchange pathway.
EXAMS can compute transport of a toxicant via whole-sediment
bedloads, suspended sediment wash-loads, ground-water infiltration,
transport through the thermocline of a lake, losses in effluent
streams, etc. Volatilization losses are computed using a Whitman
model. This computation treats the total resistance to transport
across the air-water interface as the sum of resistances in the
liquid and vapor phases Immediately adjacent to the interface.
External loadings of a toxicant can enter the ecosystem via point
sources (STRLDG), non-point sources (NPSLOG), dry fallout or aerial
drift (DRFLDG), atmospheric wash-out (PCPLDG), and via ground-water
1414
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Accession Ho. 16404000106 (cont)
seepage (IFLLDG) entering the system. Any type of load can be
entered for any system compartment, but the program will not
implement a loading that is inconsistent with the system
definition. For example, the program Hill automatically cancel a
PCPLD entered for the hypolimnion or benthic sediaents of a lake
ecosystem. When this type of corrective action is executed, the
change is reported to the user via an error message.
(ASM) Basic assumptions of model: EXAMS has been designed to evaluate
the consequences of long term, time-averaged toxicant loadings that
ultimately result in trace-level contamination of aquatic systems.
SXAHS generates a steady-state, average floy field for the
ecosystem. The model thus cannot evaluate the transient
concentrated EECs that arise, for example, from spills of toxic
chevicals. This limitation derives from tyo factors: First, a
steady flow field is not always appropriate for evaluating the
spread and decay of a major pulse (spill) input. Second, the
assumption of trace-level EECs, which can be violated by spills,
has been used to design the process equations used in EXAMS. The
following assumptions were used to build the model: A first-order
evaluation can be executed independently of the toxicant's actual
effects on the system. In other words, the toxicant does not
itself radically change the environmental variables that drive its
transformations. Thus, for example, an organic acid or base is
assumed not to change the pH of the system, the toxicant is assumed
not to itself absorb a significant fraction of the light entering
the system, and bacterial populations do not grow {or decline)
simply due to the presence of the chemical. EXAMS uses linear
sorption isotherms, and second-order (rather than
Michaelis-Menten-Monod) expressions for biolysis. This approach is
knovn to be valid for low concentrations of pollutants? its
validity at high concentrations is less certain. EXAMS controls its
computational range to ensure that this assumption is not grossly
violated. The program will not report EECs for loadings that
result in aqueous-phase toxicant residuals greater than 50% of the
aqueous solubility of the compound. This restraint incidentally
allows the model to ignore precipitation of the toxicant from
solution, and precludes inputs of solid particles of the chemical.
Sorption is treated as a thermodynaaic or constitutive property of
each compartment in the system, that is, sorption/desorption
kinetics are assumed to be rapid compared to other processes. The
adequacy of this assumption is partially controlled by properties
of the toxicant and system being evaluated. Extensively sorbed
chemicals tend to be sorbed and desorbed more slowly than weakly
sorbed compounds; desorption half- lives may approach 10 days for
the most extensively bound toxicants. Experience with the model
has indicated, however, that strongly sorbed chemicals tend to be
captured by benthic sediments, where their release to the water
column is controlled by benthic exchange processes. This
phenomenon overwhelms any accentuation of the speed of processes in
the water column that may be caused by the assumption of local
equilibrium. Steady-state solutions are obtained via Gaussian
elimination or sequential cascade. Transient decay solutions are
1415
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Accession No. 16404000106 (cont)
obtained via the method of lines, using a Runge-Kutta 4th-5th order
and a Gear stiff equation numerical integrator.
(IMP) Input to nodeI: Input parameters include: A set of pollutant
loading rates on each sector of the ecosystem. Toxicant molecular
weight, solubility, and ionization constants. Sediment- and bio-
sorption parameters: Kp, Koc or Row, biomasses, benthic Hater
contents and bulk densities, suspended sediment concentrations,
sediment organic carbon, ion exchange capacities. Volatilization
parameters: Henry's Law constant or vapor pressure data,
Hindspeeds, reaeration rates. Photolysis parameters: quantum
yields, absorption spectra, surface scalar irradiance, cloudiness,
scattering parameters, suspended sediments, chlorophyll, dissolved
organic carbon. Hydrolysis: 2nd-order rate constants or Arrhenlus
functions for the relevant molecular species, pH, pOH,
temperatures. Oxidation: rate constants, temperature, oxidant
concentrations. Biotransformation: rate constants, temperature,
total and active bacterial population densities. Parameters
defining strength and direction of advective and dispersive
transport pathways. System geometry and hydrology: volumes, areas,
depths, rainfall, evaporation rates, entering stream and
non-point-source flows and sediment loads, ground water flows.
Although EXAMS allows for the entry of extensive environmental
data, the model can be run with a much reduced data set when the
chemistry of a toxicant of interest precludes some of the
transformation processes. For example, pH and pQH data can be
omitted in the case of neutral organics that are not subject to
acid or alkaline hydrolysis reactions. An environmental "Canonical
Data Base1* is under development by EPA for eventual linkage to
EXAPS.
(OUT) Output of model: The 17 output tables include an echo of the
input data, and tabulations giving the exposure, fate, and
persistence of the toxicant. The program prints a summary report
of the results obtained. Printer-plots of longitudinal and
vertical concentration profiles can be invoked by the interactive
user.
(APP) Applications of aodel: EXAMS can be used to assess the fate,
exposure, and persistence of organic chemicals in aquatic
ecosystems in which the loadings can be time-averaged and residuals
are at trace levels. The model has been used by EPA to evaluate
the behavior of relatively field-persistent herbicides. EXAMS has
beer successfully used to model volatilization of organics in
specific field situations, and for a general assessment of the
behavior of phthalate esters in aquatic systems. EXAMS has been
implemented by a number of manufacturing firms for environmental
evaluations of newly synthesized Materials and has been used in an
academic setting for both teaching and research. EXAMS has been
linked to a "multi-media" model under development by A. 0. Little,
Inc.
(HDN) Computational system requirements - Hardware: Mainframe IBM 370,
CDC CYBER, POP 11, HP 3000 ;Dlsc storage: 2.5k/ENV ;Printer 80
position line printer
(LNG) Computational system requirements - Language(s) used: Fortran
1416
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Accession Ho. 16404000106 (cont)
(OSfO Computational system requirements: Operator Knowledge/Skills: bas
ic ecology/chemistry
(HTP) fcater Models - Type of model: Water quality
(ENV) Environraent(s) to which model applies: Sstuary ;Lake
jStream/river ;«ietlands
(CON) Processes and constituents included in model: Erosion and
sediment ;Toxic chemicals ^Temperature ;Biologic Hydrology
(CPL) Complexity level of model: steady state aass balance ;transient
mass balance ;one dimen multi dimensional ^Simplified
(RSF) References - User manuals, documentation, etc.:
Burns, L.A., D.M. Cline, and R. R. Lassiter. 1982. Exposure
Analysis Modeling
System (EXAMS): User Manual and System Documentation.
a.S. Environmental Protection Agency/ Athens, GA.# SPA -
600/3-82-023.# Baughraan, G.L. and L.A. Burns. 1980. Transport and
Transformation of Chemicals: A Perspective.# In: Handbook of
Environmental Chemistry. Vol.2, Part A.# 0. Hutzinger (Ed.) New
York, Springer-Verlag. pp. 1-17.$ Lassiter, R.R., G.L. Baughman,
and L.A. Burns. 1978. Fate
of toxic organic substances in the aquatic environment.
pp. 219-246 In: S.E. Jorgensen (ed.) State-of-the-Art in
Ecological Modelling. Proceedings of the Conference on
Ecological Modelling, Copenhagen, Denmark, 28 August - 2
September 1978. International Society for Ecological Modeling,
Copenhagen.
Volfe, N.L., L.A. Burns, and H.C. Steen. 1980. Use of linear
free energy relationships and an evaluative model to assess
the fate and transport of phthalate esters in the aquatic
environment. Chemosphere, 9:393-402.
(CNM) Contact name(s): Burns,L.A.
(COR) Contact organization: U.S. EPA (404) 546-3148
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1417
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Accession Mo. 16404000111
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Hydrological Simulation
Program-Fortran
(ACR) Acronym of Data Base or Model: HSPF
{MED) Media/Subject of Data Base or Model: Toxic substances ;Water;
BOO, DO, nutrients
(ABS) Abstract/Overview of Data Base or Model: HSPF is a comprehensive
package for sinulation of watershed hydrology and water quality
developed for the U.S. Environmental Protection Agency (EPA).
Simply put, the simulation model uses such information as the tine
history of rainfall, temperature, and solar radiation; such
characteristics of the land surface as land use patterns and soil
types; and agricultural practices to simulate the processes that
occur in a watershed. The result of this sinulation is a tine
history of the quantity and quality of the runoff. Flow rate,
sediment load, and nutrient and pesticide concentrations are
predicted. The model then takes these results and information about
the stream channels in the watershed and simulates the processes
that occur in these streams. This part of the simulation produces
a time history of water quantity and quality at any point in the
watershed—the inflow to a lake, for example. HSPF includes a data
management system to process the large amounts of input data for
the simulations and equally large amounts of simulation output.
Computer routines are provided to statistically analyze the data
for ease of presentation and interpretation. HSPF can be applied
to a wide range of water resource problems. The key attribute that
makes it applicable to such a wide variety of problems is its
ability to simulate the continuous behavior of time-varying
physical processes that occur in surface runoff and in receiving
waters and provide statistical summaries of the results.
(CTC) CONTACTS: Thomas 0. Barnuell EPA Athens Environmental Research
Labor Loc: Center for Water Quality Modeling, College Station Road,
Athens, GA,
30613 Ph: (404) 546-3585 or (404) 546-3175
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: HSPF is built on a systematic
framework in which a variety of process modules can fit. The
system consists of a set of modules arranged in a hierarchical
structure that permits the continuous sinulation of a comprehensive
range of hydrologic and water quality processes. HSPF currently
contains three application modules—PERLMD, IHPLHD, and RCHRES—and
five utility modules—COPY, PLTGEII, DISPLY, DURASL, and GENER.
Each of these nodules is briefly discussed below.
(ASM) Basic assumptions of model: In a model as comprehensive as HSPF,
it is difficult to list all the assumptions made in its
development. The watershed hydrologic algorithms generally follow
the assumptions made in the Stanford Watershed Model. The
agricultural chemical algorithms w«re derived from the ARM model
and the "simple** land surface washoff algorithms are from the NPS
model. Both ARM and UPS are described elsewhere in this catalogue*
Stream routing uses the kinematic wave approximation and the water
1418
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Accession No. 16404000111 (cont)
quality algorithms use first order kinetics except in the plankton
algorithms, yhere Monod growth kinetics are incorporated. Module
PERLNO simulates a pervious land segment with homogeneous
hydrologic and climatic characteristics. The simulation of snow
accumulation and melt is based on an energy balance approach. Hater
movement is modeled along three flow paths—overland flow,
interflow and groundwater flow—in the Banner of the Stanford
Watershed Model. Erosion processes include sediment detachment by
rainfall splash and man's influence and transport by overland 1
Scour in rills and gullies is also considered. Water quality
constituents may be simulated in the fashion of the NPS model using
simple relationships with sediment and Hater yield or by using the
detailed algorithms for pesticides and nutrients as in the ARM
model. Module IMPLND is designed to simulate impervious land
segments where little or no infiltration occurs. Algorithms are
similar to PERLND except that no water movement occurs by interflow
or groundwater flow. Solids are simulated using accumulation and
removal relationships in the manner of urban models such as SWHM
and STORM. Water quality constituents are simulated using
empirical relationships with solids and water yield. Module RCHRES
simulates the processes that occur in a single reach of an open
channel or a completely mixed lake. Hydraulic behavior is modeled
using the kinematic wave assumption. The outflow of an element may
be distributed across several targets that might represent normal
outflows, diversions, and multiple gates on a reservoir.
Temperature is simulated using a heat balance approach. Sediments
may be simulated as two components--washioad and sandload. Power
relationships to flow predict transport capacity and scour and
deposition of the sandload is modeled. Sediment transport may also
be modeled using the Tolby or Toffaleti equations for sand
transport and the Krone and Partheniades equations for the cohesive
sediments. Conservative and nonconservative constituents are
simulated in a manner that allows maximum user flexibility. Th-
following processes can be considered in simulating a
nonconservative constituent such as a toxic organic chemical
advection; decay by hydrolysis, oxidation, photolysis,
volatilization., or biodegradation; production of daughter products;
and adsorption/desorption on sediments. The primary dissolved
oxygen and biochemical oxygen demand balances are simulated in the
traditional manner, with provisions for decay, settling, benthal
sources, reaeration, etc. The primary nitrogen balance is modeled
as sequential reactions from ammonia through nitrate.
Oenitrification is also considered. Both nitrogen and pher.
are considered in modeling three types of plankton— phytopi
zooplankton, and attached algae. Dissolved oxygen is considered in
modeling plankton and the nitrogen cycle. Hydrogen ion activity
(PtO is calculated considering carbon dioxide, total inorganic
carbon, and alkalinity. HSPF's utility modules are designed to give
the user maximum flexibility in managing simulation input and
output. COPY is used to manipulate time series. The user can
change the form of the time series during the COPY operation. A
5-minute rainfall record may be aggregated to an hourly time
1419
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Accession No. 16404000111 (cont)
interval, for example* The PLTGEN module creates a specially
formatted sequential file for later access by a stand-alone plot
program. DISPLY takes a time series and summarizes the data in a
neatly formatted table. Aggregation of the basic data is also
possible. DORANL performs a duration and excursion analysis on a
tine series and computes soae elementary statistics. It can answer
questions like: "How often does dissolved oxygen stay below 4 mg/1
for 4 consecutive hours?" It can also perform a lethality
analysis. The GENSR nodule is used to transfora a tine series (A)
to produce a new series (C) or to combine two time series (A+B) to
create a new one (C). For example, this module is useful if one
«ants to compute the aass outflow of a constituent from the flow
and concentration.
(IMP) Input to model: Data requirements to run HSPF can be quite
extensive and depend on the state variables selected for
simulation. Tables 1 and 2 (attached) list the time series and
parameter inputs possible for HSPF. As a minimum, precipitation
and evapotranspiration records are required for simulations. Many
parameters can be defaulted but defaults are not provided for the
more sensitive, site-specific parameters.
(DOT) Output of model: System output can be obtained at several
levels, from a detailed printout of system state variables and
parameter values at every time step to yearly summaries. Printout
formats compatible with output interval are provided. An Interface
file for plotters is provided and a stand-alone program for CALCOMP
plotters is available.
(CSR) Computational System Requirements: HSPF requires a Fortran
compiler that supports direct access I/O. Twelve (12) external
files are required. The system requires 128K bytes of instruction
and data storage on virtual memory machines, or about 2SOK with
extensive overlaying on overlay-type machines. The system was
developed on a Hewlett-Packard 3000 minicomputer and has been used
on IBM 370 series computes. It has also been installed on DEC/VAX,
PRIfE and HARRIS minicomputers/as well as Burroughs CDC, and ONIVAC
mainframes. Because of its comprehensive nature, HSPF requires
individuals with several different backgrounds to implement it. As
a minimum, an implementation team should consist of a systems
programmer, a hydrologist, and a water quality expert. Manpower
requirements for data preparation and output interpretation will
vary with the system being modeled but are likely to be extensive.
(APP) Applications of model: Although HSPF is a relatively new
product/ having been publically released by EPA in April 1980, it
has undergone some testing through applications to inhouse projects
by the developer (Hydrocomp, Inc.). It has also been used in
projects sponsored by EPA. Some of these applications are
described below. In a 208 study, a prototype of the HSPF system was
applied to the Occoquan River Basin by the Northern Virginia
Planning District Commission. The Occoquan Basin Computer Model
consists of 15 sub-basins (39 mi(2) average) linked by a network
consisting of 12 stream channels and 3 reservoirs and was based on
a linkage of the NFS model and HSP. Considerable effort went into
date collection to calibrate the runoff and stream quality models,
1420
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Accession No. 16404000111 (cont)
resulting in one of the better general nonpoint source data bases.
The model was used to project long-tern receiving water quality
impacts of existing and future (year 2005) land use patterns and to
compare the benefits of alternataive "best management practice"
(BMP) levels. The HSPF software was tested largely using the
simulations of the Qccoguan basin as a reference. One of the early
applications of HSPF was in a hydropower study for the Doninlean
Republic. Hydropower is a major source of electricity in this
developing country/ which is experiencing an 11% annual increase in
demand. Twenty potential hydropower sites were identified and 10
potential network configurations were hypothesized. The analysis
procedure consisted of the generation of 99 years of synthetic
hourly precipitation, calculation of land surface runoff, and
calculation of natural streamflow at 21 sites. Power generation
was simulated by routing the streamflou through the 10 different
hydropower configurations. The tine series for depth of flow
(head) and flow rate were then analyzed using the GEHCR module to
estimate the most efficient configuration. Another water resources
study using HSPF has been conducted in the Clinton River Basin,
Michigan. The purpose of the study was to evaluate a proposed
Corps of Engineers floodway, estimate the impact of developing wet
lands, investigate better lake operating procedures/ and simulate
the effect of retention ponds. The basin is located north of
Detroit and lies in Macomb and Oakland counties. It is largely
urban in the south and agricultural in the north. The HSPF network
consisted of four land segments for each of nine rain gages and 128
channel reaches in six sub-basins. The model was calibrated on a
ten year record (1965-1975). Simulated annual peak flows were then
compared with 14 USGS stream gages for the period 1927-1975. The
longer time period was then used to evaluate water resource
management options. EPA has applied, through a contractor, HSPF
merged with the Chemical Migration and Risk Assessment (CMRA)
methodology to demonstrate its application as a planning tool for
the evaluation of agricultural BMP's. This demonstration is being
done at two scales—the 20<2>«i(2) Four Mile Creek watershed in
east central Iowa and the 1200 mi(2) Iowa River Basin above
Coralville Reservoir. The small scale demonstration serves as a
calibration site for scale-up to the larger basin. A BMP
implementation scenario has been investigated relative to its
impact on water quality. Schemes aimed at receiving water quality
targets for pesticides/ phosphorus, and nitrates were simulated.
HSPF has been used by the State of Nebraska to investigate the
effect of groundwater pumping for agriculture in the Big Blue
Basin. The University of Nebraska has used the system as a data
management tool for the Dee Creek Research Watershed. A project
sponsored through the University of North Dakota used HSPF to
Investigate the effect on wildlife habitat of proposed lake
drainage in the basin of the Red River of the North. The current
(July 1981) release of HSPF is designated Version 7. Another
release is anticipated in late 1983.
(HDW) Computational system requirements - Hardware: Mainframe
IBM/HP3000/PR!M£/HARRIS/Burroughs/UNlVAC CDC/DEC VAX >Disc Storage
1421
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Accession Ho. 16404000111 (cont)
12 files ^Printer any codel ;Card reader/punch
(LNG) Cosputational systea requirements - Language(s) used: FORTRAN
(OSK) Computational system requireaents: Operator Knowledge/Skills: Pro
graining /Engineering
(WTP) Water Models - Type of model: Hater quality
Hater run-off
(ENV) Cnvironaent(s) to which Model applies: Lake ;Stream/river
;Non-point Urban and non-urban
CCON) Processes and constituents included in model: Dissolved oxygen
?Eutrophication ;Srosion and sediment y Toxic Chemicals ;Salinity
^Temperature ;Hydrology ;Quality processes
(CPL) Complexity level of model: transient mass balance ;one
dimensional
(REF) References - User manuals, documentation, etc.:
J. C. Imhoff, J. L. Kittle, A. S. Donigian, R. C. Johanson, 1981
Users 'Manual For Hydrological Simulation Program - FORTRAN (HSPF)
Release 7.0. Draft Report, Environmental Research Laboratory,
Athens, GA., 30613& Donigian, A.S., Jr., J.L. Baker, D.A. Haith,
and M.F. Walter. 1980. HSPF Parameter Adjustments to Evaluate the
Effects of Agricultural Best Management Practices. Draft Report.
U.S. Environmental Protection Agency, Athens, GA. 306131 Donigian,
A.S., Jr., J.C. Imhoff, and B.R. Bicknell. 1981. Modeling Water
Quality and the Effects of Agricultural Best Management Practices
in Four Mile Creek, Iowa. U.S. Environ mental Protection Agency,
Athens, GA.f Hydrocomp, Inc. 1980. Analysis of Power Generating
Configurations in the Rio Yaque del Norte Watershed. Mountain
Viet, CA.f Imhoff, J.C., B.R. Bicknell, and A.S. Donigian, Jr.
1981. Preliminary Application of HSPF to the Iowa River Basin to
Model Water Quality and the Effects of Agricultural Best Management
Practices. U.S. Environmental Protection Agency, Athens, GA.#
Donigian, A.S., J.C. Imhoff, B.R. Bicknell, J.L. Kittle, Guide to
the Application of the Hydrological Simulation Program - FORTRAN
(HSPF) 1982 Draft Report, Environmental Research Laboratory,
Athens, GA. 30613$ Gilbert, D.P. Development of State Water Quality
Management Plan for the State of Nebraska 1982. Water Resources
Center, University of Nebraska - Lincoln, Nebraska 68583f Johanson,
R. C., J. C. Imhoff, and H. H. Davis.ft 1980. User's Manual for the
Hydrologic Simulation program-
Fortran (HSPF). EPA 600/9>80-015. Environmental Research
Laboratory, Athens, GA 30613.
Barnwell, T. 0. and R. C. Johanson. 1980. "HSPF: A
Comprehensive Package for Simulation of Watershed Hydrology
and Water Quality.** Presented at: Nonpoint Pollution
Control: Tools and Techniques for the Future, Gettysburg,
PA, June 1980.
Grimsrud, G. P., D. D. Franz, R. C. Johanson, N. H. Crawford.
1980. Executive Summary for the Hydrologic Simulation
Program—Fortran (HSPF). In Press. Environmental Research
Laboratory, Athens, GA 30613.
Anderson, E. A. 1968. "Development and Testing of Sno« Pack
Energy Balance Equations*** Water Resources Research,
4(l):l9-37.
1422
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Accession No. 16404000111 (cont)
Crawford, N. H. and A. S. Donigian, Jr. 1973. Pesticide
Transport and Runoff Model for Agricultural Lands. EPA-
600/2-74-013. Environmental Research Laboratory, Athens, GA
30613.
Crawford, N. H. and R. K. Lindsey. 1966. Digital Simulation
in Hydrology: Stanford Watershed Model If. Stanford Univ.
Tech. Rep. No. 39, Stanford Univ., Palo Alto, CA.
Donigian, A. s., Jr., D. C. Beyerlain, H. H. Davis, Jr.,
and N. H. Crawford. 1977. Agricultural Runoff Management
(ARM) Model Version II: Refinement and Testing. EPA-
600/3-77-098. Environmental Research Laboratory, Athens, GA
30613.
Donigian, A. S., Jr. and N. H. Crawford. 1976. Modeling
Pesticides and Nutrients on Agricultural Lands. SPA-
600/2-76-043. Environmental Research Laboratory, Athens, GA
30613
Donigian, A. S., Jr. and N. H. Crawford. 1976. Modeling
Nonpoint Pollution From The Land Surface. EPA-600/3-76-083.
Environmental Research Laboratory, Athens, GA 30613.
Donigian, A. S., Jr. and N. H. Crawford. 1977. Simulation of
Nutrient Loadings in Surface Runoff with the NPS Model.
EPA-600/3-77-065. Environmental Research Laboratory, Athens,
GA 30613.
Donigian, A. S., Jr. and N. H. Crawford. 1979. Cser's Manual
for the Nonpoint Source (NPS) Model. Unpublished Report.
Environmental Research Laboratory, Athens, GA 30613.
Donigian, A. S., Jr. and H. H. Davis. 1978. User's Manual
for Agricultural Runoff Management (ARM) Model. EPA-
600/3-78-080. Environmental Research Laboratory, Athens, GA
30613. August 1973.
Hydrocomp, Inc. 1969. Bydrocomp Simulation Programming:
Operations Manual, 2nd Edition, Hydrocomp/ Inc., Palo Alto,
CA.
Leytham, K. M. and R. C. Johanson. 1979. Watershed Erosion
and Sediment Transport Model. EPA-600/3-79-028. Environmental
Research Laboratory, Athens, GA 30613.
Negev, M. 1967. A Sediment Model on a Digital Computer.
Stanford Univ. Tech. Rep. No. 76, Stanford Univ., Palo Alto,
CA, 1967.
TABLE 1
INPUTS FOR HYDROLOGY AMD HYDRAULICS
SECTIONS OF HSPF
TIMF SERIES INPUTS
air temperature(l)
precipitation
dewpoint temperature(l)
wind movement(l)
solar radiation(l)
potential evapotranspiration
channel inflows not simulated
channel diversions
surface lateral inflow to
1423
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Accession Ho. 16404000111 (cont)
land segment(2)
Interflow lateral inflow to
land segment(2)
groundwater lateral inflow
to land segaent(2)
(l)Needed only if snow
nodule is used/ or for
water quality nodules*
(2)These inputs are optional.
If entire watershed is
modeled, these can usually
be assumed to be zero*
CONSTANT PARAMETER INPUTS
Interception storage (maximum value)
Noninal upper zone soil moisture storage
Nominal lower zone soil mositure storage
Infiltration index
Interflow index
Areal cover of deep-rooted vegetation
Seepage to deep (or inactive) groundwater
Evaporation from groundwater within reach of
vegetation
Length of overland flow (feet)
Overland flow slope
Manning's "NM for overland flow (constant or
monthly)
Daily interflow recession rate
Dally groundwater recession variable rate
Exponent of the infiltration curve equation
Actual upper zone soil mositure storage at
start
Actual lower zone soil moisture storage
Groundwater storage volume
Groundwater slope parameter
Surface detention storage
Interflow detention storage
Interception storage volume
Convection-condensation melt parameter
Snow correction factor
Elevation difference in thousands of feet
Index density of new snow
Forest cover index
Dally ground melt
Hater content of snow at saturation
(fraction)
Hater equivalent of snow-pack for complete
areal coverage
Channel geometry
Stage discharge relationships
Channel slope
Ratio of max and mean velocities in channels
Retention (interception) storage capacity of
1424
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Accession No. 16404000111 (cont)
impervious surface (constant or monthly)
TABLE 2
INPUTS TO HATER QUALITY
SECTIONS OF HSPF
LAND SEDIMENT
Supporting management practice factor - constant
Soil Detachment coefficient and exponent - constants
Rate of soil re-attachment - constant
Land surface cover - constant or monthly
Sediment influx from atmosphere - constant or monthly
Detached sediment washoff coefficient and exponent - constant
Matrix soil scour coefficient and exponent - constant
Lateral input of sediment to segment surface - time series
(optional)
SOIL TEMPERATURE
Slope and intercept of land surface temp to air temp
equation - constants
Smoothing factors in temperature calculations - constants
Air temperature - time series
DISSOLVED GAS IN LAND HATERS
Ground elevation - constant
Interflow and Groundwater concentration of DO - constant or
monthly
Interflow and Groundwater concentration of C0<2> - constant
or monthly
QUALITY CONSTITUENTS ASSOCIATED WITH SEDIMENT
Hashoff potency factor (each constituent) - constant or
monthly
Scour potency factor (each constituent) - constant or monthly
QUALITY CONSTITUENTS IN INTERFLOW AND GROUNDWATER
Concentration of const, in Interflow - constant or monthly
Concentration of const, in Groundwater - constant or monthly
AGFICHEMICAL QUALITY CONSTITUENTS
Solute leaching factors (each soil layer) - constant
Soil layer depths (each of four layers) - constant
Soil bulk densities for each layer - constant
Temperature correction parameter for pesticide decay - constant
Pesticide solubility - constant
Pesticide adsorption - desorption parameters - constant
Pesticide degradation rates (each layer) - constant
Nitrogen plant uptake rates (each layer) - constant or monthly
Fraction of plant uptake from N0<3> and NH<4> - constant
Temperature correction coefficients for various nitrogen
reactions - constant
Ammonium desorption rate (each layer) - constant
Ammonium adsorption rate (each layer) - constant
Nitrate immobilization rate (each layer) - constant
Organic N amraonification rate (each layer) - constant
Denitrification rate (each layer) - constant
Nitrification rate (each layer) - constant
Ammonium immobilization rate (each layer) - constant
Max. solubility of ammonium - constant
1425
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Accession No. 16404000111 (cont)
Nitrogen adsorption-desorption parameters (each layer) -
constant
phosphorus plant uptake rates (each layer) - constant or
Monthly
Temperature correction coefficients for various phosphorus
reactions - constant
phosphate desorption parameters (each layer) - constant
Phosphate adsorption parameters (each layer) - constant
Phosphate immobilization rate (each layer) - constant
Organic P mineralization (each layer) - constant
Max. solubility of phosphate (each layer) - constant
IMPERVIOUS LAND WATER QUALITY
Solids washoff coefficient and exponent - constant
Rate of solids placement on surface * constant or monthly
Rate of solids removal on surface - constant or monthly
Ground elevation - constant
Air temperature to surface water temp, recession constants -
constant or monthly
Sediment borne pollutant uashoff potency factor (each const.) -
constant or monthly
Overland flow borne pollutant accumulation rate (each const.) -
constant or monthly
Overland flow borne pollutant max. storage (each const.) -
constant or monthly
Surface runoff removal rate (each const.) - constant or monthly
Lateral input of sediment to segment surface - time series
(optional)
REACH AMD RESERVOIR HATER QUALITY
Solar radiation correction factor - constant
Longwave radiation coefficient - constant
Conduction convection heat transport coefficient - constant
Evaporation coefficient - constant
tfashload material sinking rate - constant
Sandload suspension coefficient and exponent - constants
Sediment density and stream bed porosity-constant. Critical
bed shear stress for scour and deposition-constant. Hydrolysis/
oxidation/ photolysis/ volatilization/ biogradation/ and
adsorption/desorption parameters-constant.
BOD benthic release characteristics and rates - constants
BOD decay rate and temperature correction - constants
BOD settling rate - constant
Allowable level of DO supers at.ur at ion - constant
Benthai oxygen demand rate - constant
Benthai release of BOD - constant
Reaeration characteristics and coefficients - constants
Content of carbon/ oxygen/ nitrogen and phosphorus in biomass -
constants
Nitrogen and phosphorus benthic release rates - constants
Oxidation rates of ammonia and nitrite - constants
Chlorophyll "*" content of biomass - constant
Fraction of algae and zooplankton biomass - constant
Light extinction coefficients - constants
1426
-------
Accession No. 16404000111 (cont)
Maximal algal groth rate - constant
Constants for light, nitrogen and phosphorus limited growth -
constants
Temperature thresholds for algal growth retardation - constants
Algal respiration rate - constant
High and low algal death rate - constant
Phytoplankton death rate due to anaerobic conditions - constant
Lower thresholds of nitrogen and phosphorus concentrations
below which high algal death occurs - constants
Advective characteristics of plankton - constants
Threshold of chlorophyll "A" concentration above which high
algal death occurs - constant
Phytoplankton settling rate - constant
Dead refractory organics settling rate - constant
Maximum zooplankton ingestion rate - constant
Zooplankton filtering rate - constant
Zooplankton respiration rate - constant
Natural Zooplankton death rate - constant
Increment of Zooplankton death rate due to anaerobic conditions -
constant
Average weight of zooplank ton organism - constant
Maximum benthie algae density
Ratios of benthic algal to Phytoplankton respiration and
growth rates - constant
C0<2> invasion rate at water surface - constant
Benthal release of C0<2> - constant
Meteorological time series listed in Inputs for hydrology -
tine series
inflow concentrations of all simulated constituents - tine series
(CNN) Contact name(s): Barnwell,T.O.
(COR) Contact organization: EPA Athens Environmental Research
Laboratory 30613 Ph: (4
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1427
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Accession No. 16404000114
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Simplified Stream Model
(ACR) Acronym of Data Base or Model: SSM
(MED) Fedia/Subject of Data Base or Model: Hater
UBS) Abstract/Overview of Data Base or Model: The Simplified Stream
Model is a one-dimensional, steady state water quality node! for
the evaluation of conservatives, singular non-conservatives with
first order decay, and coupled BOD-DO deficits in streams, rivers,
and shallow non-stratified lakes. It was developed by
Hydroscience, inc. for the EPA as a "first cut" planning tool to
achieve estimates of ambient DO downstream from point sources. SSN
requires no computer equipnent except for an electric hand
calculator which is used to compute logs and exponentials.
(CTC) CONTACTS: Robert B. Ambrose U.S. EPA, ORD Environmental
Research La Loc: College Station Rd., Athens, GA 30605 Ph: (404)
546-3546
(STA) Cata Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: SSM is capable of simulating
the physical processes of dilution, advection, reaeration, and
temperature effects in streams, rivers, and shallow non- stratified
lakes. Uncoupled chemical reactions can be represented, as well as
coupled BOD-DO deficit reactions. Constituents that can be
represented by the model include BOD, DO, unspecified
conservatives, and un-coupled non-conservatives with first order
decay. The model handles only point source residual inputs, and
its simplified nature restricts its usage when complicated
prototype systems or complex water quality problems are involved.
No bio-chemical processes are represented directly, although first
order decay for coliform bacteria may be possible. SSM has a high
estimated sensitivity to residual loading rates and stream
velocities, and a moderate estimated sensitivity to decay
coefficients and total streamflow.
(ASM) Basic assumptions of model: The model considers only
longitudinal variations and handles only point source residual
inputs, it assumes a constant stream velocity for each reach, and
assumes first order decay rates for quality constituents.
(IHP) input to model: For initial set-up/calibration needs, the
following input data are required: Met river flow Flow velocity
Depth Distance from point source discharges Constituent
concentration, temperature, and background DO deficit for all
stream inflows Loading rate for ultimate oxygen demand
Deoxygenation coefficients Constituent concentrations throughout
the modeled area are required for model verification.
(OUT) Output of model: Output from the model (through hand
calculation) includes constituent concentrations and DO deficits.
(CSR) Computational System Requirements: The model is uncoded and
requires no computer equipment except for an electronic hand
calculator which is used to compute logs and exponentials. Data
preparation and model set-up may require 1-2 man-weeks, and actual
computation time may take from several man-hours to several
man-days, depending on the complexity of the application and the
1428
-------
Accession No. 16404000114 (cont)
mathematical skill of the personnel involved* For manpower needs
an engineer (junior level) or engineering aid with a mathematical
orientation is required. Ho programming experience is necessary.
(APP) Applications of model: SSM can be applied to rivers, streams,
and shallow/ non-stratified lakes for the evaluation of
conservatives, non-conservatives with first-order decay, and
coupled BOD-DO deficits. TECHNICAL CONTACT: Robert B. Ambrose U.S.
Environmental Protection Agency Environmental Research Laboratory
College Station Road Athens, Georgia 30605 FTS 250-3546 COM
404/546-3546
(HDH) Coaputational system requireaents - Hardware: Calculator
(OSK) Coaputational system requirements: Operator Knowledge/Skills: Eng
ineering
(WTP) Vater Models - Type of model: Hater quality
(ENV) Environment(s) to which model applies: Stream/river
(CON) Processes and constituents included in model: Dissolved oxygen,
biochemical oxygen demand >Salinity, conse
(CPL) Complexity level of model: steady state mass balance ;Simplified
(REF) References - User manuals, documentation, etc.:
Hydroscience, Inc. "Simplified Mathematical
Modeling of Hater Quality." Report to Office of Hater
Programs/ U.S. Environmental Protection Agency, Washington,
D.C. (U.S. Government Printing Office No. 1971-444-367/392),
1971.
Hydroscience, Inc. "Addendum to Simplified Mathematical
Modeling of Water Quality." Report to Office of Water
Programs, U.S. Environmental Protection Agency, Washington,
D.C. (U.S. Government Printing Office No. 1972-484-486/291),
1972.
(CNM) Contact name(s): Ambrose,R.B.
(COR) Contact organization: U.S. EPA, ORD Environmental Research Lab
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1429
-------
Accession No. 16404000115
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Simplified Estuary Model
(ACR) Acronym of Data Base or Model: SEM
(MED) Media/Subject of Data Base or Model: Water
CABS) Abstract/Overview of Data Base or Model: The Simplified Estuary
Model (SEM) is a one-dimensional, steady state water quality model
for the evaluation of uncoupled chemical reactions and BOD-DO
deficits in tidal streams and rivers, and non-stratified estuaries.
Constituents that can be modeled include BOD, DO, unspecified
conservatives, and uncoupled non- conservatives with first order
decay (i.e. sone nutrients). SEM Has developed by Hydroscience,
Inc. For the EPA as a "first cut" uater quality planning tool to
achieve estimates of ambient DO concentrations in estuaries
downstream from point source residual inputs. The Bodel requires
no computer equipment except for a hand calculator which is used to
coapute logs and exponentials.
(CTC) CONTACTS: Robert B. Ambrose U.S. EPA, Environnental Research
Labora Loc: College Station Road, Athens, GA 30605 Ph: (404)
546-3546
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: SEN is a far-field, one-
dimensional (horizontal plane) model that considers only
longitudinal variations and handles only point source resi- dual
inputs. The model can be applied to tidal streams and rivers, and
to non-stratified estuaries. Physical processes that can be
represented include advection, longitudinal dispersion, dilution,
reaeration, and temperature effects. The model can simulate
uncoupled chemical reactions and coupled BOD-DO deficit reactions,
and It can represent the following constituents: BOD, DO,
unspecified conservatives, and uncoupled non-conservatives with
first order decay. No biochemical processes are represented
directly, although the modeling of first order decay for coliform
bacteria is possible. The simplified nature of SEM restricts its
usage when complicated prototype systems or complex water quality
problems are involved. SEM has a moderate estimated sensitivity to
residual inputs, stream flow and velocity, and decay coefficients.
(ASM) Basic assumptions of model: The model considers only
longitudinal variations and handles only point source residual
inputs. It assumes a constant velocity for each reach, and assumes
first-order decay rates for quality constituents.
(IMP) Input to model: The following input data are required for
initial setup/calibration of the model: Net river flow exclusive of
tidal effects Flow velocities Average depths Distance from point
source discharges Dispersion coefficients Cross-sectional area
Constituent concentration, temperature and background DO for all
stream inflows Loading rate for ultimate oxygen demand
Deoxygenation coefficients Reaeration coefficients Salinities at
the seaward boundary Constituent concentrations throughout the
modeled area are needed for verification of the model.
(OUT) Output of model: Output from the model (through hand
calculation) includes constituent concentrations, maximum DO
1430
-------
Accession Mo, 16404000115 (cont)
deficit, and minimurn DO concentrations.
(CSR) Computational System Requirements: SEM is encoded and requires
no computer equipment except for a hand calculator which is used to
compute logs and exponentials. Data preparation and model setput
(including moel familiarization) requires 1-2 man-weeks/ and the
actual computation time nay take from several man-hours to several
nan-days depending on the complexity of the application and the
mathematical skill of the personnel involved. Manpower-needs
require an engineer (junior level) or engineering aid with a
mathematical orientation. No programming experience is necessary.
(APP) Applications of model: SEM has been used for various
applications. TECHNICAL CONTACT: Robert B. Aabrose U.S.
Environmental Protection Agency Environmental Research Laboratory
College Station Road Athens, Georgia 30605 FTS 250-3546 COM
404/546-3546
(HDW) Computational system requirements - Hardware: Calculator
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(WTP) tlater Models - Type of model: Mater quality
(EMV) Environment(s) to which model applies: Estuary
(CON) Processes and constituents included in model: Dissolved oxygen,
biochemical oxygen demand ;Salinity, conse
(CPL) Complexity level of model: steady state mass balance ;one
dimensional ;Simplified
(REF) References - User manuals, documentation, etc.:
Hydroscience, Inc. "Simplified Mathematical
Modeling of Water Quality." Report to Office of Water
Programs, U.S. Environmental Protection Agency,
Washington D.C. (U.S. Government Printing Office No.
1971-44-367/392), 1971.
Hydroscience, Inc. "Addendum to Simplified Mathematical
Modeling of water Quality." Report to Office of Water
Programs, U.S. Environmental Protection Agency, Washington,
D.C. (U.S. Government Printing Office No. 1972-484-486/
291), 1972.
(CUM) Contact name(s): Ambrose,R.B.
(COR) Contact organization: U.S. EPA, Environmental Research Laboratory
(ROR) Fesponsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1431
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Accession No. 16404000116
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: Agricultural Runoff Model (Version
ID
(ACR) A crony* of Data Base or Model: ARM II
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: The Agricultural Runoff
Management Model - Version II (ARM II) is a continous simulation
model that estimates the movement and degradation of pollutants on
agricultural land surfaces. The model can be used to study
pollutants including pesticides, nutrients, and sediments. ARM II
is an improved version of ARM I and the Pesticide Transport and
Runoff (PTR) Model published in 1973. All of these models build
upon the Stanford Watershed Model. The ARM II model has been tested
on agricultural plots at Vatkinsville, Georgia, and is currently
being tested at other sites throughout the United States. The
model is recommended for use to estimate pollutant loads from
agricultural fields. Applications include basin planning and
evaluation of pesticides being considered for registra- tion. ARM
II vas developed by Hydrocomp, incorporated, for the U.S.
Environmental Protection Agency*
(CTC) CONTACTS: Lee A. Mulkey U.S. EPA/ Office Research and
Development,
Environmental Research Laboratory/ Athens
Loc: College Station Road, Athens/ GA. 30605 Ph: (404) 546-3581
(STA) Data Base statust Operational/Ongoing
(DP) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: ARM II can be used to study
the impact of various land use practices on pollutant loading to
streams in agricultural areas. It can also be used to evaluate
loadings of pesticides based on the physio-chemical properties of
pesticides/ recommended application rates and topographical/ soil/
and meteorological properties of an area in uhich the pesticides
are to be used. For the best results/ land areas simulated should
not be larger then 2 mi(2). Channel processes affect timing of
loadings for areas larger than this. Consequently, for areas
larger than 2 mi(2), it Is recommended that ARM II be used with a
compatible channel routing model to insure accurate representation
of significant transport processes. The model outputs include a
continuous recording of the following parameters: Volume flow rate
of surface runoff. Volume flow rate of interflow. Volume flow rate
of base flow. Volume of water contained in interception storage.
Volume of water In upper zone soils. Volume of water in lower zone
soil, volume of water in active groundwater storage. Rate of
evapotranspiration water from land surface. Soil surface
temperature, Upper zone soil temperature, Mass of pesticide on the
watershed. Mass loading of pesticide, Concentration of dissolved
pesticide in runoff, Concentration of adsorbed pesticide in runoff,
Amount of pesticide degraded and volatilized. Amount of organic
nitrogen in the soil. Amount of dissolved ammonia in the soil,
Amount of adsorbed ammonia in the soil. Amount of dissolved nitrite
plus intrate in the soil. Amount of nitrogen incorporated into
plant material. Load of organic nitrogen in runoff. Load of
1432
-------
Accession No. 16404000116 (cont)
adsorbed ammonia in runoff, Load of dissolved ammonia in runoff.
Load of nitrite plus nitrate in runoff, Concentration of dissolved
inorganic phosphorus in soil, Concentration of adsorbed inorganic
phosphorus in soil. Concentration of organic phosphorus in soil,
and Amount of phosphorus incorporated into plant material. AHR II
is composed of six subroutines: MAIN, LANDS, SEDT, ADSRB, DFGRAD,
and NUTRNT. MAIN calls and executes the other subroutines and
establishes input and output files. LANDS performs the moisture
balance in the soil and generates runoff* SEDT generates and
transports sediment loads. ADSRB partitions pesticides between
adsorbed and dissolved phases. DEGRAD degrades pesticides
contained on the soil surface. NCJTRST transforms nutrients to
various forms and also establishes the equilibrium between adsorbed
and dissolved phases. The model is capable of simulating changes
in any parameter on 5- and 15-minute intervals. Several output
formats can be selected to display results on 5-ninute, 15-minute,
hourly, daily, or monthly intervals. Simulations can be run for
any number of years desired.
-------
Accession No* 16404000116 (cont)
transformations. Nitrogen and phosphorus parameters that define
reaction rates and nutrient storage. Chloride storage parameter.
(OUT) Output of model: Outputs produced by the model include an echo
of the input data set, the concentration on pestides and nutrients
in the soil and runoff, and loads of nutrients, pesticides, and
sediaent in runoff. Nutrient concentrations are reported in terms
of the various foras present in the cycle. For both pesticides and
nutrients, concentrations and loads for dissolved and suspended
materials are reported separately. Some selection in available as
to the frequency of printout. Monthly and yearly summaries for
loads are also provided.
(CSR) Computational System Requirements: On the IBM 370/168, using the
FORTRAN H compiler, the progran requires approximately 360K bytes
(90,000 words) of storage for compilation of the largest
subroutine. Program execution requires up to 230K bytes (57,500
words) of storage depending on the model operation selected. Thus,
a computer with relatively large storage capability is usually
needed for use of the ARM model. However, Version II of the ARM
model has been adapted and run on a Hewlett-Packard 3000 Series II
computer, which is substantially smaller than the IBM machines.
Thus, the model can be used on relatively small computers; the
effort and model changes needed to adapt the ARM model to other
computers will depend on the specific computer installation. The
A?M model requires no special external storage devices (tape, disc,
etc.) other than the standard card reader input and line printer
output However, the model includes an option to output simulated
runoff and sediment values to an external storage device as
unformatted FORTRAN records.
(APP) Applications of model: ARM II has been used by the U.S.
Environmental Protection Agency to evaluate potential runoff of a
pesticde fro* agricultural lands. Application of ARM includes
evaluation of best management practices for agricultural lands in
relation to basin planning. It can also be used to evaluate
pesticide loading in relation to registration of pesticides.
TECHNICAL CONTACT: Lee A. Mulkey Environmental Research Laboratory
U.S. Environmental Protection Agency College Station Road Athens,
Georgia 30605 FTS 250-3581 COM 404/546-3581
(HDW) Computational system requirements - Hardware: Mainframe IBM
370/168 or Hewlett-Packard HP 3000 Series II j Card reader/punch
(LNG) Computational system requirements - Language(s) used: Fortran
(KTP) Kater Models - Type of model: Hater run-off
C^NV) Environment(s) to which model applies: Non-point non-urban
-------
Accession Mo. 16404000116 (cont)
and Nutrients on Agricultural Lands." Environmental Research
Laboratory/ U.S. Environmental Protection Agency, Athens.
Georgia, EPA-600/2-76-043, 1976.
Doniglan, A. S., Jr., D. C. Beyerleln, H. H. Davis, Jr.,
and N. H. Crawford. "Agricultural Runoff Management (ARM)
Model - Version 11, Refinement and Testing.*1 Environaental
Research Laboratory, U.S. Environmental Protection Agency,
Athens, Georgia, EPA-600/3-77-098, 1977.
Donigian, A. S. Jr., and H. H. Davis, Jr. "Agricultural
Runoff Management (ARM) Model User's Manual: Versions I
and II." Environaental Research Laboratory, U.S. Environmental
Protection Agency, Athens, Georgia, EPA-600/3-78-080, 1978.
CCNM) Contact narae(s): Mulkey,L.A.
(COR) Contact organization: U.S. EPA, Office Research and Development,
Environmental Res
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmentai Research Laboratory.
1435
-------
Accession No. 16404000117
i'Di,-; Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Nonpolnt Source Pollutant Loading
Model
(ACR) Acronym of Data Base or Model: UPS
(MED) Media/Subject of Data Base or Model: Water
(A8S) Abstract/Overview of Data Base or Model: The Nonpoint Source
Pollutant Loading (NPS) Model is a continuous simulation model
which estimates the movement of pollutants on land surfaces. The
•odel can be used to study pollutants that are conserved or which
degrade slowly. The NPS model is one of a series, including the
Agricultural Runoff Management Model (ARM) and the Pesticide
Transport and Runoff Model (PTR), which are based on the Stanford
Watershed Model. The nodel was initially tested on three
predominantly urban sites and has been used in relation to planning
required under Section 208 of Public Law 92-500. The model is
recommended for use to estimate nonpoint source pollutant loads in
urban and rural areas* Applications are primarily waste allocation
in relation to basin planning. NPS was developed by Hydrocomp,
Incorporated, for the U.S. Environmental Protection Agency.
(CTC) CONTACTS: Lee A, Mulkey U.S.EPA, Office Research and
Development,
Environmental Research Laboratory-Athens
Loc: College Station Road, Athens, GA 30605 Ph: (404)546-3581
(STA) Data Base status: Operational/Ongoing
CDF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: NPS can be used to study the
impact of various land management strategies on pollutant loading
to streams in a planning area. For best results, land areas
simulated should not be larger than 2 square a lies. Since channel
processes affect timing of loadings for areas larger than 2 square
miles; it is recommended that NPS be used with a compatible channel
routing model to insure accurate representation of significant
transport processes for areas of application larger than 2 square
miles. The model outputs include a continuous recording of the
following parameters: Runoff flow rate. Runoff temperature.
Dissolved oxygen concentration of runoff. Amount of pollutant load
in a given time interval for up to five pollutants. Concentration
of up to five pollutants in runoff. Amount of sediment load in a
given tine interval. Concentration of sediment in runoff. NPS is
composed of three major components: MAIN, LANDS, and QOAL. MAIN
calls and executes the two major subroutines in the program and
establishes input and output files. LANDS performs the moisture
balance and generates runoff. QUAL executes erosion calculations
generating sediment loads and sediment concentration in runoff. - It
also calculates pollutant loads and concentrations by relating
these parameters to sediment load and concentration. The node! is
capable of simulating changes in any parameter on 15-minute or
hourly intervals. Several output formats can be selected to display
15-mlnute, hourly, daily, or monthly intervals. Simulations can be
run for any number of years desired.
(ASM) Basic assumptions of model: Both water and pollutant transport
descriptions are based on the principle of conservation of mass.
1436
-------
Accession No. 16404000117 (cont)
The overall model is based on the Stanford Watershed Model. Water
transported out of the watershed Is assumed to be drawn from every
portion of the watershed. Consequently, water and chemical
constituents in runoff cannot be identified with any particular
location within the watershed. The water balance calculations
assumes that there are five water storage zones, namely,
interception storage, upper zone storage, lower zone storage,
active ground-water storage, and inactive ground-water storage.
During a storm event, rainfall is partitioned between these
storages and also exported from the watershed by overland flow,
interflow and baseflow. Between storm events, export continues
along with transfers between compartments. In addition/ water is
lost by evapotranspiration. Snow accumulation and melt is also
nodeled. The rates of water export and intercompartnent transfers
are governed by empirical equations which contain constants
requiring calibration for each application of the model. Where
possible, guidance has been provided to show reasonable parameter
estimates in various parts of the country. Calibration requires
simultaneous rainfall and runoff records. Sediment loss from
pervious are modeled in identical fashion as the ARM Version I
model. Two processes are described: detachment of fines and
transport of fines. For impervious surfaces, sediment particulate
accumulates and is removed according to impirical equations during
dry weather periods. During storms, transport of sediment particles
are defined by the same relationship as for sediment fines from
pervious surfaces. Conservative constituent transport is assumed to
move at a rate proportional to the rate of movement of sediment.
(IHP) Input to model: Input parameter list include the following: A
set of control parameter values that defines frequency of printing
of output, dates of simulation and whether snowmelt calculations
are to be performed. A set of hydrology parameter values that
specify the noninal capacity of the storage zone and specific rates
of hater transport between zones and the rates of export of water
by runoff and evapotranspiration. A set of parameter values that
define show pack characteristics. A set of paraneter values that
define sediment transport characteristics. A set of parameters that
defines land use characteristics and for impervious surfaces,
sediment accumulation, and removal rates during dry weather
periods. Precipitation date for period of simulation.
(OUT) Output of model: Outputs commonly displayed are hydrographs for
each storm as well as base flow projected for dry weather periods,
sediment loads and concentrations as a function of time, pollutant
loads and concentrations as a function of time, dissolved oxygen
concentration and temperature as a function of tine. An echo of
the input data set is also printed along with stora, monthly, and
annual summaries of the output data sets.
(CSR) Computational System Requirements: As abstracted from the report
documenting the NFS model, system resource requirements are as
follows. The NFS Model is written in the IBM FORTRAN IV language.
The "handy minimal language** concept was adopted to the extent
possible to produce a reasonably compatible computer code for at
least the following computer systems: IBM 360, UNIVAC 1108, CDC
1437
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Accession Ho. 16404000117 (cont)
6000, and Honeywell Series 32. However, at the present tine, model
operation has been limited to the IBM systems. The NFS model
operates most efficiently in a two-step procedure* The first step
involves the compilation of the program and the storage of the
compiled version on disk or Magnetic tape. In the second step, the
complied model is provided the necessary input data and is
executed. Thus, the model can operate a number of types of
different input data with a single compilation.
(APP) Applications of model: NPS has been applied to small urban
watersheds in Durham, North Carolina; Madison, Wisconsin; and
Seattle, Washington. It is also being used in conjunction with
implementation of several 208 plans, including the plan being
developed by the Northern Virginia Planning Commission. TECHNICAL
CONTACT: Lee A. Mulkey Environmental Research Laboratory U.S.
Environmental Protection Agency College station Road Athens,
Georgia 30605 FTS 250-3581 COM 404/546-3581
(HOH) Computational system requirements - Hardware: Mainframe IBM 360
Univac 1108, CDC 6000 and/or Honeywell, Se II
(LNG) Computational system requirements - Language(s) used: Fortran
(HTP) hater Models - Type of model: Hater run-off
(EN?) Environment(s) to which model applies: Non-point urban and
nonurban
(CON) Processes and constituents included in model: Dissolved oxygen
;Eutrophication ;Erosion and sediment ;Hydr
(CPL) Complexity level of model: transient mass balance ;»ulti
dimensional
(REF) References - User manuals, documentation, etc.:
Donlgian, A. S., Jr., and N. U. Crawford.
"Modeling Pesticides and Nutrients and Agricultural Lands."
U.S. Environmental Protection Agency, Environmental Research
Laboratory, Athens, Georgia, EPA-600/2-76-043, 317 p., 1976.
Donigian, A. S., Jr., and N. H. Crawford, "Modeling Nonpoint
Pollution from the Land Surface," 0. S. Environmental
Protection Agency, Environmental Research Laboratory, Athens,
Georgia, EPA-600/3-76-083, 280 p., 1976.
(CNN) Contact name(s): Mulkey,L.A.
(COR) Contact organization: U.S.EPA, Office Research and Development,
Environmental Rese
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1438
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Accession No. 16404000118
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Multi-Segment Comprehensive Lake
Ecosystem Analyzer for Envi Resources
(ACR) Acronym of Data Base or Model: MS.CLEANER
(MED) Media/Subject of Data Base or Model: Hater
(ABS) Abstract/Overview of Data Base or Model: The Multi-Segment
Comprehensive Lake Ecosystem Analyzer for Environmental Resources
(MS.CLEANER) is one of the more biologically realistic aquatic
ecosystem models. Because of the attention to general process-level
constructs, the model is appropriate for application to diverse
types of lakes and reservoirs and is capable of addressing many
environmental problems. The model represents over 30 man-years of
development by a multidisciplinary team. The precursor, CLEANER,
was formulated by 25 investigators from several institutions under
the aegis of the International Biological Program, Eastern
Deciduous Forest Biome. The model is structured to simulate up to
20 biotic and 20 abiotic state-variables in each of 10 spatial
segments simultaneously. Current development includes adaptation
to coastal environments and coupling to a model for bioaccumulation
of toxic substances. MS.CLEANER was developed by Dr. Richard A.
Park of the Center for Ecological Modeling, Rensselaer Polytechnic
Institute, Troy, New York, for the U.S. Environmental Protection
Agency.
(CTC) CONTACTS: Thomas 0. Barnyell U.S. EPA, Office Research and
Developme Environmental Research Lab-Athens
Loc: college Station Road, Athens, Georgia 30605 Phs (404)
546-5175
(STA) Data Base status: Discontinued
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: MS.CLEANER is an ecological
model capable of addressing environmental problems such as nutrient
enrichment, thermal pollution, siltation, impoundment, and fish
renoval. The model can simulate a variety of biotic variables,
including four types of phytoplankton (two Mith internal storage of
nitrogen and phophorous); up to four types of submerged aquatic
vegetation (macrophytes); five types of zooplankton; tuo or more
types of fish with as many as four life stages* tno kinds of
bottem-diielling animals (zoobenthos); and three groups of
ecovposers (bacteria and fungi). An equal number of abiotic
variables can be simulated, including seven types of dissolved
organic matter; four types of particulate organic matter; five
types of inorganic nutrients in the water column and sediments; and
four compartments for dissolved oxygen and inorganic carbon. This
potential complexity is seldom fully utilized, however. Normal
applications require a subset of perhaps 20 state-variables. The
model has been run with as fey as two dynamic state-variables.
Several external variables and all the biotic state variables can
be used as loadings. External variables include water temperature,
temperature and discharge rate of inflowing water, wind speed,
light, dissolved inorganic nitrogen, orthophosphate, dissolved
silica, dissolved organic material, and particulate organic
material. As a user-oriented model, MS.CLEANER features a machine-
1439
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Accession No. 16404000118 (cont)
independent name list editor that enables the user to list and Make
changes in parameter values while running the model; to plot
state-variables concentrations, rates for various processes/ and
loadings to the model; and to transform the state- variable values
into "environmental perception" characteristics such as turbidity/
fish catch/ or concentrations of noxious algae. Multiple segments
can be simulated/ each having different physical-chemical and
biotic characteristics. Movement of materials across the
boundaries of the segments is specified by a linking language* The
movement can either be intersegmental or be treated as a loss from
the system/ as specified by the user. The loadings of nutrients/
temperature/ and light can be perturbed using the editing
capability of MS.CLEARNER to set at the perturbation parameters.
The perturbations can be either additive or multiplicative/ and
either constant or as a pulse of user-specified duration and
timing. An algorithm has been developed to facilitate analysis of
the sensitivity of MS.CLEANER to changes in values of parameters
and driving variables. Using a random number generator/ values
with a normal or uniform distribution are used to vary loadings or
parameters within a specified range. The simulation is repeated a
given number of times with different perturbations/ and the results
are summarized. The parameters are perturbed at the beginning of
each simulation; the loadings are perturbed at each step. The model
is coded in FORTRAN IV and is virtually machine independent.
(ASM) Basic assumptions of model: The realism of MS.CLEANER is
achieved by disaggregation of state-variables and by use of
detailed process equations. Adaptive constructs are used for light
and temperature response in phytoplankton. These constructs have
permitted application to a wide range of lakes without changing
parameters. Onlike most ecosystem models/ MS.CLEANER can treat
phytoplankton growth as a function of stored nutrients. This
uncoupling of growth and external nutrient concentrations has
resulted in more realistic simulations with avoidance of the time
lags between modeled and observed phytoplankton peaks that are a
persistent problem with many models. Likewise/ process-level
realism in simulating zooplankton has been achieved by recognizing
variations in modes of food consumptions. In some zooplankton the
rate of consumption is independent of the concentration of food; in
others a minimum food level is necessary before feeding will occur.
The rate of consumption follows saturation kinetics. In order to
use MS.CLEANER in studying bioaccumulation of toxic substances/ the
fish compartments have been disaggregated to represent age classes.
At the time of promotion/ all/ or some fraction/ of the fish in.one
age class is transferred to the next age class at a rate that
follows a normal distribution. The shedding of gonadal products
(and associated pesticides) by adults Is handled in the same
manner. By modeling decomposers explicitly/ more realistic
simulations of decomposition have been obtained. This is
particularly important In representing the differential degradation
of different types of organic material (including oil spills)/ the
cycling of nutrients/ and—through the production of microbial
biomass—formulation of a high-quality food source for detritus
1440
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Accession No. 16404000118 (cont)
feeding animals. Phosphorus, silicon/ carbon and soluble inorganic
nitrogen are the only nutrients that can be limiting. The
temperature, nutrient/ and biomass are considered to be uniformly
distributed in a segment.
(INP) Input to model: The data required to calibrate and use the model
fall into several categories: Driving Variables - a tine-series of
data for the period of the simulation (which nay be from a few days
to years)/ including water temperature/ incident radiation/
loadings of dissolved and particulates/ organic matter/ biomass,
and nutrients. Site Constants - average water depth and light
extinction coefficient. Initial Conditions - for all variables.
Parameter Values - a default set of values for the extensive
parameter list may be used or values that are known nay be input.
Calibration Data - observed values for some state variables are
necessary to fine-tune the model. Pertubations and Sensitivity
Analysis - sensitivity to changes in parameters and driving
variables may be examined using a built-in algorithm. All of the
input data and parameter values used can be output as well as the
state variables simulated. A plotting routine is available.
(CSR) Computational System Requirements: MS.CLEANER requires
approximately 250K bytes of core/ which may be reduced to about
145K bytes using an overlay structure. Ten files are required for
operation of the program/ plus an additional number of files equal
to the number of segments being simulated (up to 10 segments).
Execution times depend on the complexity and length of the
simulation.
(App) Applications of model: The model has been calibrated and
verified with data froi a number of lakes of diverse types. It was
originally applied to Lake George/ Hew York. Subsequent versions
have been calibrated for Lock Leven, Scotland; Slapy Reservoir/
Czechoslovakia; Balaton Lake/ Hungary; Lakes d'Endine and Mergozzo,
Italy; Lake Esrum/ Denmark; Lake Paijanne/ Finland; and DeGray
Reservoir/ Arkansas. A version that incorporates all the latest
improvements/ including storage of internal nutrients in
phytoplankton/ has been calibrated for subalpine Ovre Heimdalsvatn/
Norway/ and verified with data from Vorderer Finstertaler See/
Austria/ without changing parameter values. With only minor
changes/ it gives reasonable results for Lake Mergozzo/ a
mesotrophic/ stratified lake. TECHNICAL CONTACT: Mr. Thomas 0.
Barnwell/ Jr. Environmental Research Laboratory 0.S. Environaental
Protection Agency College Station Road Athens/ Georgia 30605 FTS
250-3175 COM 404/546-5175 Dr. Richard A. Park Center for Ecologic
Modeling Renssselaer Polytechnic Institute Troy/ Sew York 12181
COM 518/270-6494 , f „„,„„„
(HOW) Computational system requirements - Hardware: Mainframe IBM/CDC
;Disc storage ten files ;Printer Any model
(LNG) computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
g ramming Engineering ; Bio logy/ecology
(WTP) Water Models - Type of model: Hater quality
(ENV) Environment(s) to which model applies: Lake
(CON) Processes and constituents included in model: Dissolved oxygen
1441
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Accession Mo. 16404000118 (cont)
;Eutrophication ;Temperature ;Hydraulics ;Q
(CPL) Complexity level of model: transient mass balance ;multi
dimensional
(REF) References - User manuals, documentation, etc.:
Bloomfield, J. A., R. A. Park, D. Scavia, and
D. S. Zahorcak, "Aquatic Modeling in the Eastern Deciduous
Forest Biome, U.S. International Biological Program." In:
Middlebrooks, E. J., D, H. Falkenborg, and T. E. Maloney
(Editors), Modeling the Eutrophication Process, Utah State
University, Logan, Utah, pp. 139-158, 1973.
Clesceri, L. S., R. A. Park, and J. A. Bloomfield. "General
Model of Microbial Growth and Decomposition in Aquatic
Ecosystems." Appl. Environ. Microbiol., 33<5):1047-1058,
1977.
deCaprarils. P., R. A. Park, R. Haimes, J. Albanese,
C. Collins, C. Desormeau, T. Groden, D. Leung, and B. Youngberg.
"Utility of the Complex Ecosystem Model MS.CLEANER" In:
Proceedings of the International Conference on Cybernetics and
Society, pp. 87-89, 1977,
Desormeau, C. J. "Mathematical Modeling of Phytoplankton
Kinetics with Applications to Two Alpine Lakes." Report #4,
Center for Ecological Modeling, Rensselaer Polytechnic
Institute, Troy, New York, 21 pp., 1978.
Groden, T. H. "Modeling Temperature and Light Adaptation of
Phytoplankton." Report $2, Center for Ecological Model,
Rensselaer Polytechnic Institute, Troy, New York, 17 pp.,
1977.
Leung, D. K. "Modeling the Bioaccumulation of Pesticides in
Fish." Report #5, Center for Ecological Model, Rensselaer
Polytechnic Institute, Troy, Neu York, 18 pp., 1978.
Leung, D. K., R. A. Park, C. J. Desormeau, and J. Albanese.
"MS.CLEANER: An Overview." in: Proceedings of Plttsburg
Modeling and Simulation Conference, Pittsburg, Pennsylvania,
1978.
Park, R. A. "Theoretical Implications of Models of Aquatic
Systems." Presented at AAAS, Biological Sciences Meeting,
New York, Neu York 1975.
Park, R. A. "A Model for Simulating Lake Ecosystems." Report
f3. Center for Ecological Modeling, Rensselaer Polytechnic
Institute, Troy, New York, 19 pp., 1978.
Park, R. A. "Predicting the impact of Man on Lake Ecosystems."
(Abstract) in: Biro, P. (Editor), Human Effects on Life In
Fresh Water, Hungarian Academy of Sciences, Tihany, Hungary,
1977.
Park, R. A., R. V. CTHeil, J. A. Bloomfield, H. H. Shugart, R.
S. Booth, R. A. Goldstein, J. B. Han kin, J. F. Roonce, 0.
Scavia, M. S. Adams, L. S. Clesceri, E. M. Colon, E. H.
Dettaann, J. Hoopes, D. D. Huff, S. Katz, J. F. Kitchell,
R. C. Kohberger, E. J. LaRom, D. C. McNaught, J. Peterson,
J. Titus, P. R. Heller, J. H. Wilkinson, and C. S. Zahorcak.
"A Generalized Model for Simulating Lake Ecosystems."
Simulation, 23 (2): 33-50, 1974.
1442
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Accession No. 16404000118 (cont)
Park, R. A., D. Scavia, and H. L. Clesceri. "CLEANER, the Lake
George Model." In: Russell, C. S. (Editor), Ecological
Modeling of a Resource Management Framework. Resources for the
Future, Inc., Washington, D. C. pp. 49-82, 1975.
Park, R* A. T. W. Groden, and C. J. Desormeau. "Modifications
to the Model CLEANER Requiring Further Research." In:
Scavia, D. and A. Robertson (Editors), Perspectives on Aquatic
Ecosystem Modeling, Ann Arbor Science Publishers, Inc., 1978.
Park, R. A., C. D. Collins, D. K. Leung, C. V. Boylen, J.
Albanese, P. deCaprariis, and H. Forstner. "The Aquatic
Ecosystem Model MS.CLEANER." Center for Ecologic Modeling,
Rensselaer Polytechnic Institute, Troy, Heu York, 1978.
Scavia, D., C. W. Boylen, R. B. Sheldon, and R. A. Park.
"The Formulation of a Generalized Model for Simulating Aquatic
Macrophyte Production." Fresh Water Institute Report |75-6,
Rensselaer Polytechnic Institute, Troy, Neu York, 1975.
Scavia, D. and R. A. Park. "Documentation of Selected Contructs
and Parameter Values in the Aquatic Model CLEANER." Ecol.
Mod., 2(1): 33-58, 1976.
Youngberg, R. A. "Application of the Aquatic Model CLEANER to
a Stratified Reservoir System." Report fl, Center for
Ecological Modeling, Rensselaer Polytechnic Institute, Troy, Neu
York, 22 pp., 1977.
(CNM) Contact name(s): Barnuell,T.Q.
(COR) Contact organization: U.S. EPA, Office Research and Development,
Environmental Res
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1443
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Accession No. 16404000119
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Explore-I
(ACR) Acronym of Data Base or Model: EXPLORE-I
(MED) Vedia/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: EXPLQRE-I is a
comprehensive mathematical water quality model to be used in river
basin planning and water resource studies. This generalized river
basin water quality model can predict the hydrodynamics and water
quality dynamics for rivers and those well nixed estuaries where
dispersion is negligible. The EXPLQRE-I model is an extended and
modified version of the Storm Hater Management Model, receiving
water component, which was developed for studies of DO/BOD
dynamics. The model is capable of simulating a number of hydraulic
regimes in either a dynamic or steady state mode, and it has been
set up, calibrated, and verified on a portion of the Willamette
River Basin, consitlng of major tributaries. EXPLORE-I was
developed by Battelle-Northwest Laboratories for the EPA.
(CTC) CONTACTS: Robert B. Ambrose, Jr. EPA, Athens Environmental
Research Center for Quality Modeling
Loc: College Station Road, Athens, Georgia 30613 Ph: (404)
546-3546
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: EXPLORE-I can be used to study
the effects of various flow conditions, waste discharge and/or
treatment schemes on the water quality levels in the river basin.
EXPLORE-I is capable of simulating a number of hydraulic regimes in
either a dynamic or steady state mode. These are: 1) streams and
rivers, 2) shallow lakes, and
3) estuaries or tidally influenced rivers. In addition,
the behavior of the following water quality parameters can be
studied: Carbonaceous Biochemical Demand (BOD) Nitrogenous BOD
Benthlc BOD Total Organic Carbon {TOO Ref-t-actory Organic Carbon
Sedimentary Phosphorous Soluble Phosphorous Organic Phosphorous
Ammonia Nitrogen Nitrite Nitrogen Nitrate Nitrogen Organic Nitrogen
Toxic Compunds (dissolved only) Phytoplankton Zooplankton Dissolved
Oxygen EXPLORE-I is composed of a river basin program which is
capable of modeling one-dimensional open channel flow in streams
and rivers, and the predominant lateral and longitudinal flow in
shallow lakes and estuaries. The program consists of a hydraulic
code which calculates the required water velocities, depths, and
flows, and a quality code which evaluates the quality parameter
reactions and routes the constituents through the system. The .
model is capable of simulating diurnal or long-term periods, and it
can handle constant and/or time-varying point or diffuse sources.
(ASM) Basic assumptions of model: The overall model formulation is
partitioned into two basic modules which can be operated
sequentially* a hydrodynamics module and a mass transport and water
quality submodels nodule. The hydrodynamics nodule is formulated
on conservation of mass and momentum principles. The mass
transport and water quality submodels module is formulated from the
expressions for specie continuity, i.e., mass balance of a
1444
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Accession No. 16404000119 (cont)
particular constituent or specie. For any biotic or abiotic
substance the general mass transfer expression is the sum of the
individual forms of mass transfers. Diffusion is assumed to be
negligible, and mass transfer is partitioned into simple transport
and water quality kinetics.
(INP) Input to model: Junction and channel data are required for the
hydrodynamics module. Junction input data include: The average
water surface elevation for the junction point The water surface
area associated with the junction point Any significant inflows to
the junction point from small streams, tributaries/ or other
sources Any significant outflows fron the junction point The
average elevation of the bottom of the river or estuary for the
junction point The cartesian coordinates of the junction point
(necessary only if the effect of wind stress on channel flow is
being calculated) Required input channel data include: Channel
length Channel width Average elevation of the channel bottom
Manning coefficient for the channel Initial velocity in the channel
Input for the water quality program include: upstream node
specification, reach boundaries, source node specification, BOD
constants, benthic BOD constants, TOC constants, toxic constants,
DO production by phytoplankton, DO production by benthic plants,
reaeration constants, phosphorous constants, nitrogen constants,
algae constants, number of constant sources, constant source
values, time-varying source values, reach temperatures, constant
upstream node concentrations, and time-varying upstream node
concentrations.
(OUT) Output of model: Output produced by the model includes an echo
of the input data and BOD and loading rates for each of the
constituents modeled.
(APP) Applications of model: EXPLORE-I has been used by the
Environmental Protection Agency for studies of hydrodynamics of the
Willamette River Sasin, and it has been tested in the Detroit
Reservoir. Application of EXPLORE-I is relatively inexpensive, and
it can be efficiently used to sound and economical solutions to
complex water pollution problems in many different types of water
systems including estuaries and bays, streams and river networks,
lakes and reservoirs, and combinations of these. TECHNICAL CONTACT:
Robert B. Ambrose, Jr. EPA, AERL, Center for fcater Quality College
Station Road Athens, Georgia 30613
(HDH) Computational system requirements - Hardware: Mainframe IBM 370
and Univac 1100 jDisc storage 44K word on Printer any type
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gratnming ;Engineering ;Environmental engineer with enviro
(WTP) Hater Models - Type of model: Hater quality
(ENV) Environment(s) to which model applies: Estuary ;Lake
;Stream/river
(CON) Processes and constituents included in model: Dissolved oxygen
;Eutrophication ;Salinity ^Temperature ;8io Hydraulics ;Quality
processes
(CPL) Complexity level of model: transient mass balance ;momentum
balance /one dimensional
1445
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Accession No. 16404000119 (cont)
(REF) References - User aanuals, docuaentation, etc.:
Thackston, E. L. and P. A. Krenke. "Reaeration
Predictions in Natural Streaas." ASCE, Proc. Journal of
the Sanitary Engineering Division, Vol. 95, No. SAI, Paper
6407, pp. 65-94, February 1969.
Feigner, K. D. and H. S. Harris. "Docuaentation Report:
FWQA Dynamic Estuary Model." U.S. Departaent of the Interior,
Federal Water Quality Administration, July 1970.
Callaway, R. J., K. V. Byraa and G. R. Ditsuorth. "Mathematical
Model of the Columbia River froa the Pacific Ocean to Bonneville
Dan - Part I." Federal Water Pollution Control Adainistration,
Pacific Northuest Water Laboratory, pp. 155, November 1969.
Netcalf S, Eddy, Inc. "Stora Hater Management Model." Vol.
1-4. Palo Alto, California; University of Florida, Gainesville,
Florida; and water Resources Engineers, Inc. fcalnut Creek,
California.
(CNM) Contact narae(s): Ambrose,R.B.
(COR) Contact organization: EPA, Athens Environmental Research Lab,
Center for Quality M
(ROR) Responsible Organization: Office of Research and
Developaent.Office of Envlronaental Processes and Effects
Research.Environmental Research Laboratory.
1446
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Accession No. 16404000120
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Dynamic Estuary Model
(ACR) Acronym of Data Base or Model: DEM
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: The DSM is a "real
time" link-node model that simulates the unsteady tidal floii and
dispersive characteristics of an estuary. The model can be applied
to estuaries in which vertical stratification is either absent or
limited to relatively small areas. It can accommodate both
conservative and non- conservative constituents. Constituents
which have been modeled include salinity, tracer dye, dissolved
solids, DO, BOD, total nitrogen, temperature, organic nitrogen,
ammonia, nitrite, nitrate, phosphates, chlorophyll a, and coliforn
bacteria. Given the necessary kinetics and rates, the model could
also treat parameters such as pesticides, heavy metals, and organic
compounds. The DEM is often linked to the Tidal Temperature Model
(TTP) for heat budgets. Ecological processes such as algal
dynamics, nutrient transport, sediment oxygen demand, coliform
die-off, and first order kinetics have been expressed in the model.
Higher order kinetics are available on some versions.
(CTC) CONTACTS: Robert B. Ambrose EPA Athens Environmental Research
Labor Loc: College Station Road, Athens, GA 30613 Ph: (404) 546-3546
(STA) Data Base status: Operational/Ongoing
(DF) Date of forra completion: 01-25-83
(CAP) Functional capabilities of model: The DEM represents the
predominant lateral and longitudinal tidal flow pattern, basic
transport processes (advection and dispersion), and the accretion
or depletion of pollutants within an estuary (provided that
vertical stratification is either absent or insignificant). The
estuary is represented by a network of channels (or links) and
junctions (or nodes). A channel is viewed as a flow conduit with a
length, width, tine varying depth, time varying velocity, time
varying cross-sectional area, and frictional resistance associated
with it. A junction acts as a well-mixed receptable for mass and
volume. It is described by a constant surface area, time varying
head, and time varying volume. The DEM is composed of two separate,
but interrelated components. The first component is a hydraulic
model which uses a step- forward explicit finite difference scheme
to solve the equations of motion and continuity for channels and
junctions, respectively. The result is a "dynamic steady-state"
solution of the hydrodynamic behavior of the estuary applicable to
a specific set of flow inputs and boundary tidal conditions. Some
versions allow varying flow inputs and boundary tidal conditions,
resulting in a fully dynamic hydrodynamic solution. The second
component, a quality model/ is closely tied to the hydraulic model.
The quality model and the hydraulic model are referenced to the
sane network of channels and junctions. The tidally fluctuating
velocities, flows, and heads predicted by the hydraulic model are
stored on tape or disk and are the basis of the hydraulic inputs to
the quality program. Constituents in the quality program are
subject to the processes of advection, dispersion (including both
eddy diffusion and dispersion due to density currents), biological
1447
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Accession No. 16404000120 (cent)
and/or chemical decay, transfer between water and the atmosphere,
and transfer betveen water and the bottom sediments. A mass
balance for each constituent is performed at each junction for each
time step. The quality model predicts the dynamic (ti«e varying)
constituent concentrations in each junction which result fro* a
specified set of boundary conditions, inflows, waste discharges,
and diversions. It is important that the tine and space scales
used in the DEM approximate as nearly as possible the physical,
tidal, and climatic characteristics of the estuary. Special
attention should be paid to the correspondence of model network
features with existing sampling stations and wastewater inputs. The
OEM is sensitive to (l) the time step in the hydraulic program
(stability reasons), (2) net flows, (3) residuals loading rates,
(4) frictional resistance coefficient, (5) initial conditions if
"real time" solutions are desired, and (6) the specified reaction
kinetics and rates. The Dynamic Estuary Model has been run for
networks with as many as 1300 channels and 840 junctions. Some
versions have modeled up to 15 constituents.
(ASM) Basic assumptions of model: The model assumes that vertical
stratification is either absent or limited to relatively small
areas. It does not handle wind stress or tidal flats exposed at
low tide. Other hydrodynamlc processes assumed negligible include
longitudinal density gradients, Coriolis acceleration, and bottom
slope. The instantaneous mixing of residuals discharge throughout
junctions is also assumed.
(IMP) Input to model: The DEM requires a large input data base on
disk, tape, and/or cards. Parameters which need to be specified
include headwater and tributary flows, wastewater flows and
loadings, water withdrawals, seaward tidal conditions, channel and
junction geometry, bottom roughness of each channel, constituent
concentrations at boundaries, and decay rates for non- conservative
constituents. Physical data pertaining to channels and junctions
can be obtained from navigational charts since direct measurements
are seldom available.
(OUT) Output of model: The model is capable of producing a wide
variety of outputs. Output options available are: (1) maximum and
minimum flows, heads, and velocities, as well as net flows, over a
tidal cycle for the model network, (2) maxiaui, aininum, and
average constituent concentrations for each junction over a
complete tidal cycle (or other specified averaging interval), (3)
"slack water" and "snapshot1* tables of constituent concentrations
at desired time intervals throughout the simulation, and (4)
line-printer plots of both spatial and temporal concentration
profiles.
(CSR) Computational System Requirements: The DEM is written in FORTRAN
IV. The hydraulic component of the model requires 2 files, either
on disk or tape. For a network of 129 junctions and 131 channels,
the hydraulic program can be run on a digital computer with 130K of
main storage. THe cost of a 50 hour (4 tidal cycles) hydraulic
simulation on an IBM 370/168 is approximately $40. The quality
component of DEM requires from 4 to 7 files, depending of the
output options desired. A quality program with 6 constituents can
1448
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Accession No. 16404000120 (cent)
be run on a digital computer with 200K to 400K of main storage.
The cost of a 1000 hour (80 tidal cycles) quality simulation for 6
constituents and 129 junctions can range from $40 to $75. The DEM
requires 5 to 20 aianweeks of effort for data preparation and output
interpretation, one programmer, and one environmental engineer with
experience in water quality modeling.
(APP) Applications of model: The Dynamic Estuary Model has been used
by the EPA for the Pearl Harbor Water Quality Model development
project. It was originally developed by the Hater Resources
Engineers for the Division of Water Supply and Pollution Control of
the Public Health Service/- and it has been used by the Federal
Hater Pollution Control Administration (FWPCA) and by the State of
California. THe DFM was used by the Federal k'ater Quality
Administration (FWQA) for water studies of the San Francisco and
San Diego Bay estuaries, and by the EPA for water quality studies
of the Delaware and Potomac estuaries. There have been other users
and applications of this model.
(HOW) Computational system requirements - Hardware: Mainframe IBM
370/168 ;Disc storage 130K and 6 constituents main storage
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
grarcming ;Engineering Experience in water quality modeli
(KTP) Water Models - Type of model: Water quality
(ENV) Environment s) to which model applies: Estuary
(CON) Processes and constituents included in model: Dissolved oxygen
;Eutrophication ;Salinity ^Temperature jBio Hydraulics
(CPL) Complexity level of model: transient mass balance ;momentum
balance ;one dimensional
(RSF) References - User manuals, documentation, etc.:
California Mater Resources Control Board. "Final
report - San Francisco Bay - Delta Hater Quality Control
Program." Preliminary Abridged edition, 1969.
Feigner, K.D. and H-S. Karris. "Documentation Report, FWQA
Dynamic Estuary Model." Report to U.S. Department of the
Interior, Federal Water Quality Administration, 1970.
Finnemore, E.J., G.P. Grimsrud, and H.J. Owen. "Evaluation of
Water Quality Models: A Management Guide for Planners.11
Report to Enviornmental Protection Agency, office of Research
and Development, Washington, D.C., 1976.
Genet, L.A., D,J. Smith, and £.B. Sonnen. "Computer Program
Doucmentation for the Dynamic Estuary Model." Report by Water
Resources Engineers, Inc., Walnut Creek, California, to U.S.
Environmental Protection Agency, Systems Development Branch,
Washington, D.C., 1974.
Water Resources engineers, Inc. "A Hydraulic Water Quality
Model of Suisun and San Pablo Bays." Report to U.S. Department
of the Interior, Federal Water Pollution Control Administration,
Southwest Region.
Water Resources Engineers, Inc. "A Water Quality Model of the
Sacramento - San Joaquin Delta." Report by WRE to U.S. Public
Health Service, Region IX, 1965.
Water Resources Engineers, Inc. "Computer Program Documentation
1449
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Accession No. 16404000120 (cont)
for the Dynamic Estuary Model." Report by HRE to Florida
Department of Pollution Control, Tallahassee, Florida, 1974.
Mater Resources Engineers, Inc. "Validation and Sensitivity
Analyses of Stream and Estuary Models Applied to Pearl Harbor,
Hauaii." Report by WRE, Walnut Creek, California, to U.S.
Environmental Protection Agency, Systeas Development Branch,
Washington, D.C., 1974.
(CUM) Contact naveCs): Aabrose,R.B.
(COR) Contact organization: EPA Athens Environmental Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1450
-------
Accession No. 16404000121
(DQ) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: Receiving Water Model
(ACR) Acronym of Data Base or Model: RECEIV-II
(MED) Vedia/Subject of Data Base or Model: Water
(ABS) Abstract/Over view of Data Base or Model: RECEIV-II is a two
dimensional receiving water model for streams, rivers, estuaries/
lakes, and reservoirs. The model represents the physical processes
of advection/ dispersion, and dilution, and it can simulate flows,
tidal movements, and water surface changes in a link-node network.
Coupled and non-coupled chemical reactions can be simulated, and
dissolved oxygen, BOD, coliforms/ nutrients, salinity, conservative
constituents, chlorophyll a, and non-conservative constituents with
first order decay can be modeled. RECEIV-II is a modification of
the receiving water module of the Storm Water Management Model
(SWMM) developed by Hater Resources Engineers/ Metcalf and Eddy,
and the University of Florida.
(CTC) CONTACTS: USEPA, ORD, ERL/Athens
Loc: College Station Road, Athens, GA 30613 Ph: (404) 546-3585
(STA) Tata Base status: Operational/Ongoing
(DP) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: The RECEIV-II model can be
applied to streams, rivers, estuaries, lakes,/ and reservoirs.
Dynamic conditions are represented, and an option is available for
steady state conditions. The model is two dimensional and permits
UP to 225 channels and up to 100 Junctions in a link- node network.
RECEIV-II can simulate estuarine flats at Ion tide by varying
cross-sectional area, and it can handle multiple tidal inlets,
upstream dams, and unsteady inflows such as residual discharges/
storm runoff, and tides. The physical processes of advection,
dispersion, and dilution are represented. Chemical processes
represented include coupled and uncoupled reactions/ DO/ BOD/
coliforras/ nutrients, salinity, conservative constituents/
chlorophyll a, 5iH<3>, N0<2>, and non-conservative constituents with
first order decay. The model does not consider stratified systems/
but it does consider ocean tide exchange at a single input point.
RECEIV-II lacks the ability to simulate temperature, but it does
consider wind stress and direct rainfall inputs. The model is
sensitive to quality time step size and decay coefficients.
Lateral and vertical velocity variation within the channels can be
broken-up laterally for a two dimensional effect.
(ASM) Basic assumptions of aodel: The model is based on deterministic
assumptions and uses a finite difference method as a solution
technique. RECEIV-II assumes instantaneous mixing throughout each
junction/ and it uses a two dimensional channel network to simulate
two dimensional flow and transport.
(IMP) Input to model: Input to the model for Initial setup and
calibration includes: constant headwater inflow rates; flow rate
for each inflow (discharge, tributary, etc.) or withdrawal; tidal
cycles and heights at the seaward boundary; widths and depths of
each channel; initial flow velocities and water surface elevations
throughout the system; initial constituent concentrations
throughout the system; residual loading rates from discharges/
1451
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Accession Ho. 16404000121 (cent)
tributaries/ and headwaters; tidal exchange coefficient;
Meteorological data (yind speed, rainfall, and daily solar
radiation); and first order decay rates for constituents. Input for
verification of the model includes: net flow and velocities for
each channel; data record of constituent concentration throughout
the modeled system; and salinity data to establish concentration
Inputs at the seaward boundary.
(OUf) Output of nodel: The aodel produces a tabular printout of:
maximum, minimum, and net flows for each tidal cycle; maximum,
minimum, and average constituent concentrations in each channel at
specified time intervals; and depth at each junction at specified
time intervals. Hydrodynamic output (especially channel
velocities) can be written onto magnetic tape or disk.
(CSR) Computational System Requirements: RECEIV-II is coded in FORTRAN
IV (G), and can be run on a digital computer with 400K bytes of
core storage, FORTRAN IV (G) compiler, and two magnetic tapes or
disks. Application of the hydrodynamic module costs between
$15-$100 per run, and application of the quality module ranges from
$10-$50 per simulation run. The actual expenses of using RECEIV-II
is dependent upon the extent of discretization, time step size, and
length of simulation. Depending on the model complexity, 1-5
man-months are needed for model set-up and data preparation.
Several manhours are necessary for output analysis. Manpower
requirements include one computer programmer and one hydraulics
engineer with a basic programming background*
(APP) Applications of model: RECEIV-II can be linked to the
terrestrial load routing module of the Storm iiater Management Model
(SV.KM), or it can be utilized by itself to simulate dynamic
conditions. RECEIV-II has been used by the U.S. Army Corps of
Engineers, and it is currently being utilized by the EPA in Regions
III and IV. TECHNICAL CONTACT: Center for Water Quality Modeling
Environmental Research Laboratory USEPA College Station Road
Athens, GA 3Q613 FTS:250-3585 COM:404/546-3585
(ROW) Computational system requirements - Hardware: Mainframe any
digital computer with 400K bytes of memory ;Ma -„„.«.«
CLMG) Computational system requirements - Language(s) used: FORTH**
(WTP) hater Models - Type of model: Water quality
(ENV) Environment(s) to which model applies: Estuary ;Lake
(COM) Processes and constituents included in model: Dissolved oxygen
JEutrophication ;Salinity ;Biological effec Hydrology
(CPL) Complexity level of model: steady state mass balance ;transient
mass balance ;multi dim
(REF) References - User manuals, documentation, etc.:
Metcalf and Eddy, Inc., University of Florida,
and Water Resources Engineeers, Inc., Storm Water Management
Model, Volumes 1-4, Report to U.S. Environmental Protection
Agency, Washington, D.C., 1971 (EPA Report No. 11024DOC).
"Stormwater Management Model User's Guide, Version II",
for the U.S. Environmental Protection Agency - Report No.
5PA-670/2-75-017, March 1975.
(CNM) Contact name(s):
1452
-------
Accession No. 16404000121 (cont)
16404000121 202 OSEPA, ORD, ERL/Athens
(ROR) Responsible Organization: Office of Rese"c^Jnpffects
Development.Office of Environmental Processes and Effects
Research.Environaental Research Laboratory.
1453
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Accession No. 16404000122
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Stream Quality Model
(ACR) Acronym of Data Base or Model: QUAL-II
(MED) Media/Subject of Data Base or Model: Mater
(ABS) Abstract/Overview of Data Base or Model: QUAL-II Is designed to
simulate the dispersion and advection of conservative and reacting
constituents in branching stream systems and rivers. Constituents
modeled included conservative minerals, temperature, BOD,
chlorophyll a, phosphorus, NH<3>, nitrate, nitrite, DO, coliform
bacteria, radioactive material, and an arbitrary nonconservative
material. It also considers nutrient cycles and algal growth. The
program simulates the dynamic behavior of these constituents by
numerical integration of the one-dimensional form of the advection-
dispersion transport equation. Any branching stream system can be
simulated.
(CTC) CONTACTS: Thomas 0. Barnuell EPA Athens Environmental Research
Labor Loc: Center for Hater Quality Modeling College Station Road,
Athens, GA
30613 Ph: (404)546-3585
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: QUAL-II nay be implemented at
several levels of sophistication-from a simple streeter-Phelps
BOD/DO model to a dynamic eutrophication/temperature simulation.
QUAL-II represents the stream simulated through the use of reaches,
a reach defined as a stretch of the stream yith uniform hydraulic
characteristics. Each reach is divided into computational
elements. A maximum of 75 reaches, each uith up to 20
computational elements uith no more than 500 in the system, can be
accommodated in the standard version of the program. In addition,
there can be a total of 15 headwater elements, 15 junction
elements, and 90 input and uithdraual elements. These limitations
are arbitrary and can easily be changed by a competent programmer.
All input is in relation to each reach, and the hydraulics
equations are solved by incorporating advection and dispersion
through a finite difference implicit solution technique. The
results on the quality constituents are obtained by numerical
integration of the one-dimensional form of the advection-dispersion
mass transport equation for each constituent. The model proceeds
to solve the relevant equations of each constituent until a steady
state equilibrium is achieved. QUAL-II is written in a modular
fashion so as to facilitate the incorporation of additional
processes.
(ASM) Basic assumptions of model: QUAL-II assumes first order kinetics
and it utilizes a simplified nutrient-algae cycle uith Monod
kinetics. Only constant inflows and point source discharges are
considered, and each computational element is considered completely
mixed. The model does not consider variations in depth or uithin
stream cross-section.
(IMP) Input to model: QUAL-II requires an input data base in
card-image form. Aside from the printed report, no additional
requirements are imposed. The data required is varied and includes
1454
-------
Accession No. 16404000122 (cont)
evaporation coefficients, oxygen uptake per unit of nitrogen and
unit of algae, algal growth rates, nitrogen and phosphorus half
saturation constants, and reaction rate constants. Further input
required is the identification of the computational elements and
their hydraulic characteristics, and intial conditions of the
system.
(DOT) Output of Model: The printed output includes a complete history
of every quality parameter and temperature at each computational
element. The hydraulic information provided includes flow, velocity
and depth of each reach, as well as at the head of the system.
Water quality information provided includes the concentration of
each quality component, temperature, and reaction rates at each
computational element in the system.
(APP) Applications of model: QUAL-II can be used to simulate the
dispersionary and flow characteristics of conservative and
non-conservative constituents in branching stream systems and
rivers. It is a modification of QOAL-I yhich was used by the WRE
to simulate the Upper Mississippi River Basin, and it has found
many other applications. In fact, QOAL-II is probably the most
widely used and thoroughly tested water quality model in the United
States.
(HDW) Computational system requirements - Hardware: Mainfraie Any
digital computer with 45,000 words of memory c POP 11 ^Printer any
model
(LNG) Computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering ;Knowledge of water quality modeling
(WTP) fcater Models - Type of model: Hater quality
(ENV) Environment(s) to which model applies: Estuary ;Lake
;Stream/river
(CON) Processes and constituents included in model: Dissolved oxygen
;Eutrophication ;3alinity ;Teoiperature ;Hyd Quality processes
(CPL) Complexity level of model: steady state mass balance /one
dimensional
(REF) References - user manuals, documentation, etc.:
Roesner, L.A., P.R. Giguere, and D.E. Evenson.
Computer Program Documentation for the Stream Quality Model
QUAL-II, prepared for the Southeast Michigan Council of
Governments by Water Resources Engineers, Inc., 710 South
Broadway, Walnut Creek, CA 94596.
(CNM) Contact name(s): Barnwell,T.Q.
(COR) Contact organization: EPA Athens Environmental Research
Laboratory 30613 Ph: (4
(ROR) Fesponsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1455
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Accession No. 16404000123
(DQ) Date of Questlonaire: 12-02-82
(NAM) Same of Data Base of Model: Stormwater Management Model
(ACR) Acronym of Data Base or Model: SHMM
(MED) Kedia/Subject of Data Base or Model: Hater
(ABS) Abstract/Overview of Data Base or Model: The SHMM is a large
FORTRAN program which Models in a comprehensive manner the complete
urban rainfall/runoff cycle, including flow overland and in the
sewerage system, in-line and off-line storage, treatment (including
costs) of storm water flows, and which includes a receiving water
module to assess water quality impacts. Program outputs consist of
tables, hydrographs and "pollutegraphs," which can be displayed at
points within the system as well as in the receiving waters. The
SHMM has had limited application to non-urban areas as well. The
original SHMM was designed for single event simulation, producing
detailed (i.e., short time increment) hydrographs and pollutographs
for individual storm events. This capability remains, and the
model has been modified so that it may run for an unlimited number
of time steps, i.e., continuously. In this mode it may be used In
a planning context, that is, for an overall assessment of urban
runoff problems and estimates of the effectiveness and costs of
abatement procedures. Tradeoffs among various control options,
e.g., storage, treatment and street sweeping, may be evaluated.
Complex interactions between the meterorology, e.g., precipitation
patterns/ and the hydrology of an area may be simulated without
resorting to average values or very simplified methods. In this
manner, critical events from the long period of simulation may be
selected for detailed analysis. In addition, return periods for
intensity, duration and volume (mass) of runoff (pollutant loads)
may be assigned on the basis of the simulated record instead of
equating them (unjustifiably) to the same statistics of rainfall
record. In this manner, the critical events chosen for study may
be substituted for hypothetical "design storms," the latter often
being synthesized from intensity-duration- frequency curves on the
basis of questionable statistical assumptions. S*MM is run
continuously using only the Runoff and Storage/Treatment blocks.
Routing in TRANSPORT, EXTRAN or RECEIVE is avoided and is
unnecessary for the planning purposes to which the model is
applied. (However, there is no limitation on the number of time
steps for either EXTRAN or RECEIVE). A receiving water model that
will couple with either continuous SMMM or STORM has been developed
and documented.
(CTC) CONTACTS: Tom aarnwell EPA Athens Environmental Research
Laboratory Loc: College Station Road Athens, GA 30613 Ph: (404)
546-3175
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: The SWMM consists of 7 blocks
of subroutines. They are: Executive Block. Assigns logical units
(disk/tape/drum), determines the block or sequence of blocks to be
executed, and, or on call, produces graphs of selected results on
the line printer. Thus, this Block does no computation as such,
while each of the other six blocks are set up to carry through a
1456
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Accession No. 16404000123 (cont)
major step in the quantity and quality computations. All access to
the computational blocks and transfers between them pass through
subroutine MAIN of the Executive Block. Transfers are accomplished
on offline devices (disk/tape/drum) which may be saved for multiple
trials or permanent record. Combine block. Allows manipulation of
data sets (files stored on offline devices) in order to aggregate
results of previous runs for input into subsequent blocks. In this
manner, large complex drainage systems may be partitioned for
simulation in smaller segments. Runoff Block. Computes the storm
water runoff and its associated pollution loadings for a given
storm for each subcatchment and stores the results in the form of
hydrographs and pollutographs at the inlets to the main seuer
system. Overland flow simulation is accomplished by a nonlinear
reservoir routing method using Manning's equation and the
continuity equation. Overland flow does not begin until depression
storages are full. Infiltration on pervious areas is computed by
Green-Ampt or Horton's exponential function, and is subtracted from
water depth existing on the subcatchment. Gutter flows are treated
as a succession of steady-state flows, with routing accomplished
using Manning's equation and the continuity equation. To use this
block the user must input the rainfall hydrograph and a
discretization of the drainage basin into sub-basins of constant
land form characteristics. The location and characteristics of the
gutters and pipes also have to be described. In addition, the user
must input street cleaning frequency and catchbasin data as well as
the land use and other features of the different areas of the
basin. Transport Block. Routes flow through the seuer system.
Prestorm conditions in the sewers are set up by computing
dry-weather flow and infiltration and distributing them throughout
the conveyance system. The Transport Block then routes the storm
runoff (as determined by the RUNOFF Block), the dry weather flow
(DWF), and the water that has infiltrated into the system through
the main sewer pipes, and through a naximum of two optional
"internal*1 storage tanks. The routing scheme is based the kenematic
wave formulation assuming cascade of conducts. When a pipe is
flowing full and inflow exceeds outflow, the excess (surcharge) is
stored at the upstream manhole. The flows are routed to a maximum
of five outlet points. This block requires that the sewer system
be discretized into pipe segments of constant size, slope, and type
Joined by either manhole, control structures such as flow dividers,
or "internal" storage tanks* An "internal" storage tank is
described by its size, shape, outlet device, and unit cost. The
outlet device can be either a pump specified to go on or off at a
specified tank depth, a weir, or an orifice. The outlet device is
used to specify the operation policy of the storage tank. The DWF
quality and quantity entering the sewer system are calculated by
inputting to the model such parameters as daily and hourly
pollution correction factors, land use population of the subareas,
and average market value of the dwellings in a subarea. If more
exact data is available such as average BOD of flows, this can be
used in place of some of the other data. Infiltration is calculated
by estimates of base dry weather infiltration and groundwater and
1457
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Accession No. 16404000123 (cont)
rainwater infiltration, and such parameters as average Joint
distance. The use of sub- routines calculating CHF quality and
quantity and infiltration is optional. EXTRAN Block. This block,
which is an alternative to the TRARSPORT block, provides the user
the capability to model sever systems with extensive surcharging,
backwater, flow reversal, looped sewers and a variety of flow
control devices. EXTRAN performs the same basic functions as the
TRANSPORT block; however, there are two aajor differences: EXTRAN
uses a link-node conceptual representation of the transport system,
totally unlike the TRANSPORT block. EXTRAN includes the inertlal
terns of the Navier-Stokes equations in the solution, whereas
TRANSPORT is based on a kinematic wave assumption. Like TRANSPORT,
EXTRAN sets up pre-storm conditions by computing DNF and
infiltration and distributing then throughout the conveyance
systens. It then performs flow routing only, picking up the runoff
results, and producing combined flow hydrographs for the total
drainage basin and at selected interaediate points. EXTRAN nay
also be used strictly for stornwater routing with neither DHF nor
infiltration. The two programs are approximately the same length.
The order of operations in both cases is similar, although the
software itself is quite different. (EXTRAN is not a direct
derivative of the original TRANSPORT Block). Storage/Treatment
block. Simulates the changes in the hydrographs and pollutographs
of the sewage as sewage flows through a wastewater treatment
facility. A storage/Treatment device is simulated as a
series-parallel network of units, each with optional storage
routing. Each unit consists of arbitrary user-supplied removal
equations (e.g. removal as exponential function of residence tine
and/or use of sedimentation theory - coupled with particle size
specific gravity distribution for constituents. RECEIVE Block.
Takes output from runoff, TRANSPORT, EXTRAN or STORAGE/TREATMENT
and conputes the impact of the discharges upon the quality of the
receiving water. The receiving body of water is discretized by the
user to consist of a network of nodes connected by channels. An
option in the program allows two parallel channels to be used
between junctions, to aid in sinulating receiving bodies such as
narshes. Each channel is of constant surface and cross-sectional
area. Boundary conditions can be specified as a weir (outfall fron
a lake) or some tidal condition.
(IMP) Input to model: SHMM requires a large amount of input data, as
described above. Typically, the collection and preparation of
input data can consume 50% or more of modeling project resources.
The various blocks of SHMM will accept input data in card-inage '
forn, or fron disk or tape drives, particularly when output from
one block is input to the next. The SHMM is designed as a
"deterministic" model, in that if all input parameters are
accurate, the physics of the processes are simulated sufficiently
well to produce accurate results without calibration. This concept
may fail in practice because the input data or the numerical
nethods nay not be accurate enough for nost real applications.
Furthermore, many computational procedures within the Model are
abased upon limited data themselves. As a result it Is essential
1458
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Accession No. 16404000123 (cont)
that some local verification/ calibration data be available at
specific application sites to lend credibility to the predictions
of any urban runoff model. These data are usually in the fora of
measured flows and concentrations at outfalls or combined sever
overflow locations. Note the quality measurements without
accompanying flows are of little value. The SWMM has sufficient
parameters that may be "adjusted," particularly in the Runoff
Block, such that calibrating the Model against measured data is
usually readily accomplished.
(OUT) Output of model: SWMM output is in the torn of tables and
various graphs of rainfall intensity/ flow and pollutant
concentrations or loads. Output can be provided for selected
points within the system, as well as in the receiving waters. As
implied above, successful use of the SWMM requires careful
evaluation and interpretation of model results.
(APP) Applications of model: The SHMM is perhaps the World's most
widely used hydrologic model, having been extensively applied in
the U.S., Canada and 18 other foreign countries to such problems
as: Analysis and design of storm and combined sewer overflow
pollution abatement facilities. Drainage design (urban areas,
subdivisions, airports). Analysis of storage/treatment
alternatives. Evaluating the effects of changes in population and
land use. Design of sytems to relieve surcharging and/or basement
flooding. Analysis of sewer system performance. An active SHMM
Users Group meets semi-annually, and publishes meeting proceedings
which document a wide variety of applications. SWMM is a complex
model both computationally and theoretically, and a successful user
must have a thorough knowledge of hydraulics, hydrology, and water
pollution, together with some experience in water quality modeling*
(HDH) Computational system requirements - Hardware: Mainframe IBM 370
(minimum 360 K bytes of memory or other computer with adequate core
and Fortran IV) has been run on IBM 370, UNI VAC 1108, CDC 6800,
Amdahl 470 ;Disc storage Variable ^Magnetic tape storage Variable ;
Printer any printer with 133 columns ;Card reader/punch
(LNG) Computational system requirements - Language(s) used: FORTRAN -
the program is approximately 25,000 statements long
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;Engineering
(HTP) Mater Models - Type of model: Hater quality
Hater run-off
(ENV) Environment(s) to which model applies: Estuary >Lake
;Stream/river jNon-point Urban (Limited non-ur
(CON) Processes and constituents included in model: Dissolved oxygen
;Erosion and sediment ^Hydrology ^Hydraulic Quality processes
(CPL) Complexity level of model: transient mass balance ;momentum
balance ;multi dimensional
(REF) References - User manuals, documentation, etc.:
Huber, K.C., J.P. Heaney, S.J. Nix, R.E. Dickinson, D.J. Polmann,
Storm Hater Management Model Users Manual Version III, Nov 1981,
Draft Report, Municipal Environmental Research Laboratory,
Cincinnati, OH 45268$ L.A. Roesner, R.P. Shubinski, J.A. Aldrich.
Storm Hater Management Model User's Manual Version III Addendum I
1459
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Accession No. 16404000123 (cont)
EXTRAN. November 1981. Draft report. Muncipal Environmental
Research Laboratory, Cincinnati, OH 452681 Hetealf and Eddy, Inc.,
University of Florida,^ Hater Resources Engineers, Inc., "Storm
Hater Management Model,
Vol. I Final Report," Report 110 24 DOC 07/71, (NTIS PB 203 289),
Environmental Protection Agency, Washington, D.C., July 1971.
Huber, U.C., et al., "Storm Hater Management Model User's
Manual, Version II," EPA-670/2-75-017, Environmental Protection
Agency, Cincinnati, Ohio, March 1975.
Medina, M.A. Jr., "Level III: Receiving Hater Quality Modeling
for Urban Stormuater Management," EPA 600/2-79-100, Environmental
Protection Agency, Washington, D.C., August 1979.
Torno, H.C. (Editor), "Proceedings, Storauater Management Model
(SHMM) Users Group Meeting, January 10-11, 1980," EPA
600/9-80-017, Environmental Protection Agency, Washington, D.C.,
March 1980.
NOTE: Version III of the SHMM, with appropriate documentation,
available thru University of Florida or EPA
(CUM) Contact name(s): Barn«ell,T.
(COR) Contact organization: EPA Athens Environmental Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1460
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Accession Mo. 16404000124
-------
Accession No. 16404000124 (cont)
concentrations, organic pollutants eutrophic status, and
hypclinnion DO deficit; and estuary concentrations of BOD, DO,
total N, total P, and conservative pollutants by reach*
Calculations are done by hand calculator and can be arranged to the
user's convenience.
(APP) Applications of nodel: The methodology has been applied and
tested on the Sandusky River Basin and four Chesapeake Bay
sub-basins: the Patuxent, Chester, Hare* and Occoquan. This work
was done by the Midwest Research Institute and Tetra Tech on a
grant from EPA. The methodology is linked to the Midwest Research
Institute loading functions.
(HDtf) Computational systerr requirements - Hardware: Calculator
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(KTP) hater Models - Type of model: Water quality
Hater run-off
(ENV) Environment(s) to which model applies: Estuary ;Lake
;Stream/river ;Non-point Urban and non-urban
(COM) Processes and constituents included in model: Dissolved oxygen
;Eutrophication ;Erosion and sediment ;Sali Temperature
(CPL) Complexity level of model: steady state mass balance ;one
dimensional ;Simplified
(REF) Peferences - User manuals, documentation, etc.:
H. B. Mills, et.al. Mater Quality Assessment: A Screening
Methodology for Toxic and Conventional Pollutants/ Parts 1, 2, and
3. Sept. 1982, EPA6001 6-82-004a,b,c. Environmental Research
Laboratory, Athens, GA 30613* hater Quality Assessment: A
Screening Method Fort Methodology for Nondesignated 208 Areas, EPA
600/9-77-023, August 1977.
Available from MTIS (PB277161/AS for $29).
(CNM) Contact name(s): Ambrose/R.B.
(COR) Contact organization: EPA Athens Environmental Research
Laboratory
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1462
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Accession No. 16404000125
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Cornell Nutrient Simulation
(ACR) Acronym of Data Base or Model: CNS
(MED) fcedia/Subject of Data Base or Model: Water ^Agricultural
Non-Point Source Pollution
(ABS) Abstract/Overview of Data Base or Model: The CHS model is a
continuous simulation model. It has been developed to predict
losses of nitrogen and phosphorus in cropland runoff and
percolation water. These losses are modelled as a function of crop
selection and management, soil type, weather, and fertility
(including fertilizers, waste applications, and crop residues).
The model differs from other models which attempt to sinulate
cropland nitrogen and phosphorus loss in that it requires no
calibration. Rather, it is based on familiar models which have
themselves been calibrated for different geographic and management
factors: the U.S. SCS Curve Number equation for runoff and the
Universal Soil Loss equation for erosion. Snow accumulation and
snowmelt are also modelled.
(CTC) CONTACTS: Douglas A. Haith Cornell University
Loc: Ithaca, KTf 14853 Ph: (607) 256-2173
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: The model operates on a daily
hydrologic balance and a monthly nutrient balance. It is a
field-scale model which predicts edge-of-field losses of runoff
water and sediwent, organic and inorganic nitrogen, and fixed and
soluble phosphorus. Mass balances for fixed phosphorus and organic
nitrogen are kept for a surface layer of 10 c«. Mass balances for
soluble nitrogen and phosphorus are kept for this surface layer and
a 20 cm depth below that. Lateral movement of water and nutrients
in this 30 cm depth is not aodelled.
(ASM) Basic assumptions of nodel: Potential evapotranspiration is
modelled by Hamon's formula, and actual evapotranspiration is a
function of the level of soil water estimated from the previous
day, crop canopy development, and potential evapotranspiration.
Actual evapotranspiration is extracted from the surface layer first
and then from the lower level, and is subtracted before runoff is
computed. Precipitation accumulates as snoy «hen daily average
temperature is below freezing and snowmelt is estimated as the
minimum of: the present reservoir of snow or a degree day factor
multiplied by daily average temperature. Percolation from each
zone is equal to the account of excess water over field capacity in
each zone. This assumes that drainage is unrestricted and
completed within one day. The USLE factors of P (support
practice), LS (length-slope), and K (soil erodibility) remain
constant. The C (crop) factor varies over time and the R (storm
erosivity) factor is uniquely simulated for each storm. Input to
the inorganic nitrogen reservoir includes fertilizers and
mineralized organic nitrogen. Output Includes runoff, percolation
and crop uptake. Input to the organic nitrogen reservoir includes
crop residues and manure organic nitrogen. An equilibrium between
fixed and soluble phosphorus is maintained and is a function of
1463
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Accession Mo. 16404000125 (cont)
soil water and clay content of the soil. Fertilizer phosphorus
represents the only input to the soluble reservoir and output
include runoff, percolation, and crop uptake. Crop uptake of
nutrients follovs a sigmoldal uptake curve.
(IMP) Input to model: Meteorological input includes daily temperature,
precipitation, and storm duration. Model input parameters include:
soil physical parameters, OSLE factors K,LS,C, and P, SCS runoff
curve numbers, initial levels of nutrients, total seasonal crop
uptake of nutrient, fertilizer schedules. Manure organic II
schedules, and crop residue organic N schedules. The model can be
verified with actual field data including monthly runoff, soil
loss, nitrogen and phosphorus in runoff, and nitrogen and
phosphorus associated with the sediment.
COOT) Output of model: Monthly model output includes reservoir levels
of organic and inorganic nutrients, runoff, soil loss, and losses
of nutrients in uater and sediment. Annual totals and annual
averages of runoff, soil loss, and nutrient losses are also
included. , ,.,„*.
(APP) Applications of models The availability of meteorological data
as nell as minimal computer requirements for time and space make
the model yell suited for long-term simulations. Tyenty-five year
simulations in three US locations allowed for an evaluation of
several "Best Management Practices" (BMPs) in a recent EPA Report,
"Effectiveness of Soil and Water Conservation Practices for
Pollution Control." CHS was applied nationwide in a study by
Resources for the Future (soon to be available from HTIS). In this
application loadings yere estimated individually for the major
crops in all but 13 of the 156 major land resource areas (MLRA1 in
the OS with those excluded having negligible land area under
cultivation. For this study, ten years of meteorological data yere
stochastically generated for each MLRA.
(HDIO Computational system requirements - Hardware: Mainframe FDF
11/70, IBM 370, etc. ;Disc storage 200 blocks Printer Line Printer
(LMG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ; Engineering
(MTP) Water Models - Type of model: Mater run-off
(EM?) Environment(s) to yhich model applies: Non-point Non-urban
(COM) Processes and constituents included in model: Erosion and
sediment ; Temperature ;Blologlcal effects ;Hydro ,«*«.<•
(CPL) Complexity level of model: steady state mass balance Simplified
(REF) References - Oser manuals, documentation, etc.:
Tubbs, L. J. and D. A. Halth, 1977, "Simulation of
Nutrient Losses From Cropland" for presentation at the 1977
Winter Meetings, ASAE paper No. 77-2502, Chicago, Illinois.
. Loehr (eds.), 1979, "Effectiveness of
soil and Hater Conservation Practices for Pollution Control."
EPA-600/3-79-106. Chapter 6 and Appendix A.
DRAFT. Cianessi, L. P. and H. M. Peskin, 1980, "*/™1»c«<>J*
for Analyzing National Water Pollution Control Policy: Water
Quality Impacts and Costs of Cropland Sediment Control."
1464
-------
Accession No. 16404000125 (cont)
No. 16, 20 p.
(CNM) Contact name(s): Haith,D.A.
: Cornell
Research.Environmental Research Laboratory.
1465
-------
Accession No. 16404000126
(DQ) Date of Questions!re: 12-02-82
(MAM) Name of Data Base of Model: Dissolved Oxygen Sag Model
(ACR) Acronym of Data Base or Model: DOSAG-I
(MED) Kedia/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: DCSAG-I is a
mathematical model developed to predict the steady state dissolved
oxygen concentrations in streams and canals resulting from a
specified set of streaaflow, wasteload, and temperature conditions.
The model Hill determine the streaaflow required to maintain a
specified dissolved oxygen goal and will search the system for
available storage to achieve the goal. The model can be used to
estimate mean monthly dissolved oxygen levels over a full year.
Both carbonaceous and nitrogenous oxygen demands are included, and
up to five degrees of treatment for both can be specified. It is
one of two programs that the Texas Mater Quality Development Board
and the EPA has for use in stream quality simulation studies. The
other program, QUAL-II, Has designed to be used as a non-steady
complement to DOSAG-I. However, the QOAL-II model has been
modified to also include a steady-state solution and it has largely
replaced DOSAG-I.
(CTC) CONTACTS: Tom Barnwell US EPA, Environmental Research Lab,
Center f Quality Modeling
Loc: College Station Rd., Athens, GA 30605 Ph: (404) 546-3175
(STA) Data Base status: Operational/Ongoing
(DF) Date of fora completion: 01-25-83
(CAP) Functional capabilities of model: The purpose of this model is
to calculate the biochemical oxygen demand and the minimum
dissolved oxygen concentration in a particular stream system. If
desired, the minimum dissolved oxygen concentration in the stream
system may be checked against a prespecified target level dissolved
oxygen concentration. If the minimum dissolved oxygen level is
beloH the target dissolved oxygen level, the program Hill compute
the required amount of floH augmentation to bring the dissolved
oxygen level up to the target level in the entire system. The
program is designed to be run for varying climatic and hydrologic
conditions during a twelve month period. Thus, it is possible to
enter up to twelve different temperatures and corresponding
discharges to each of the headwaters ulthin the stream system being
modeled. The DOSAG-I model is a one-dimensional, horizontal plane
model for streams, rivers, manmade canals and other water
conveyance systems. Large impoundments such as reservoirs cannot
be considered by this program. A list of restrictions follows:
Maximum of 10 headwater stretches Maximum of 20 junctions Maximum
of 50 reaches Maximum of 20 stretches Maximum of twelve months of
routing for temperature and headwater flows; a minimum of one month
must be used Maximum of four dissolved oxygen targets. A minimum
of one dissolved oxygen target must be specified. This dissolved
oxygen target may be entered as a negative number If no flow
augmentation is desired. Maximum of five degrees of treatment for
both carbonaceous and nitrogenous wastes; a minimum of one degree
of treatment may be specified. If the user does not wish for the
degree of treatment calculations to be used in the modeling
1466
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Accession No. 16404000126 (cont)
process, a number less than one should be entered as the treatment
factor for both types of wastes. DOSAG-I has a high sensitivity for
residual loads and velocities, and a moderate estimated sensitivity
for flow and decay coefficients.
(ASM) Basic assumptions of model: The model assumes constant stream
velocity throughout each reach and assumes first order decay only.
The Streeter-Phelps equation is used to calculate dissolved oxygen
concentration, and the computation of atmospheric reaeration is
based on the Fickian Ian of diffusion. A Lagrangian solution
technique is used to solve the dissolved oxygen equations.
(INP) Input to model: The following are required for input and
calibration needs: Reach length Mean velocity Mean discharge Mean
depth (per reach) Average reach temperature Residuals discharge
inflows Withdrawals and groundwater inflows Residuals inputs (as
BOD) Dissolved oxygen concentration in each reach For verification
of the model, streamflows, stream velocity, and observed
constituent concentrations throughout the modeled area are required*
(OUT) Output of model: Output from the model consists of a tabular
printout of the concentration of dissolved oxygen for each reach,
BOD (carbonaceous and nitrogenous) at the start and end of each
reach, an echo of all input data, and a final summary.
(APP) Applications of model: DOSAG-I was developed by Water Resources
Engineers, Inc. and the Texas Water Development Board. The model
has been used by the Texas Water Development Board for use in the
San Antonio River Basin, and it has been used for a variety of
applications by the EPA. TECHNICAL CONTACT: Tom Barnwell Center for
Water Quality Modeling U.S. Environmental Protection Agency
Environmental Research Laboratory College Station Road Athens, GA
3605 FTS 250-3175 COM 404/546-3175
(HDW) Computational system requirements - Hardware: Mainframe Can be
used on many different models jDisc storage Printer Any model ;Card
reader/punch
(LNG) Computational system requirements - Language(s) used: FORTRAN I?
(OSK) Computational system requirements: Operator Knowledge/Skills: Jun
ior engineer familiar with water quality modeling
CWTP) hater Models - Type of model: Water quality
(EH?) Environnent(s) to which model applies: Stream/river
(CON) Processes and constituents included in model: Dissolved oxygen
(CPL) Complexity level of model: steady state mass balance ;one
dimensional
(REF) References - Oser manuals, documentation, etc.:
Texas Water Development Board. "DOSAG-I - Simulation
of Water Quality in Streams and Canals: Program Documentation
and User's Manual." Report by TWDB Systems Engineering
Division, Austin, Texas, 1972.
Finnemore, E.J., Grimsrud, G.P., and Owen, H.J. Evaluation
of Water Quality Models: A Management Guide for Planners,
prepared for the Environmental Protection Agency, Office of
Research and Development, Washington, D.C., under Contract
No. 68-01-2641, July 1976.
(CNM) Contact name(s): Barnwell,T.
1467
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Accession No. 16404000126 (cont)
(COR) Contact organization: US EPA, Environmental Research Lab, Center
for Water Quality
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1468
-------
Accession No. 16404000127
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data Base of Model: Level Ill-Receiving Water Quality
Modeling for Urban Stormwa ment
(ACR) Acronym of Data Base or Model: NONE
(MED) Media/Subject of Data Base or Model: Mater
(ABS) A bs tract/ Over view of Data Base or Model: Level Ill-Receiving is
a simplified continuous receiving water quality model that can be
used as a planning guide to permit preliminary screening of area
wide wastewater treatment strategies. The model Has designed to
interface with hourly continuous urban catchment hydrologic
simulation models such as STORM or SWMM. A large number of urban
pollution control alternatives can be simulated and evaluated In
terns of their impact on receiving water quality. Evaluation is
accomplished by evaluating either classical dissolved oxygen sag
curves or cumulative frequency curves of dissolved oxygen
concentration. The model computes a minimum inter event time to
define statistically independent storm events.
(CTC) CONTACTS: Dr. Miguel A. Medina Department of Civil
Engineering Du University
Loc: Durham, NC 27706 Ph: (919)684-2434
(STA) Lata Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: Level Ill-Receiving can
accommodate a large number of inflow combinations of receiving
water flow* dry-weather flow, and wet-weather flow. Oxygen
concentration is considered the key to the quality of natural water
bodies, although it is certainly not the only viable water J"alijv
indicator. Urban runoff quantity and quality must be computed with
a model like STORM or SWMM. Receiving water effects are computed
using a simplified modeling approach. Advective and dispersive
transport is modeled. The dissolved oxygen balance includes
carbonaceous BOD and reaeration. Nitrogeneous oxygen demand is
to
to
)Basc assumptions of model: Assumptions typical of models
limited to interim planning are made, Including: Temporal
steady-state conditions prevail, i.e., all ^^V^-sLc
inputs (other than stormwater inputs) are constant with respect
times Natural system parameters (such as flow, velocity, depth,
SeoxygenaUoi and reaeration rates, and longitudinal dispersion)
a?e spatially constant throughout each time step? All waste inflows
occufat one point; The effects of various Jf uraj *^?gical
processes (algal photosynthesis and respiration, benthal
stabilization) are incorporated into a background quality reflected
by an upltream "o. deficit. Any benthic buildup is incorporated
in the BOD decay rate; Waste treatment facilities operate at
constant efficiency, independent of hydraulic and organic loadings,
and
rh
II consols the autocorrelation analysis of ^'j^* U^SX.?
Card group III contains input data common to both the wet-weather
1469
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Accession No. 16404000127 (cont)
and dry-weather flow models. Card group IV contains the Met-weather
flow aodel input, and card group V is specific to the dry-weather
flow aodel.
(OUT) Output of model: Program output consists of tables and plots
describing system response, including correlogrants of tine series,
frequency histograms or cumulative frequency curves of D.O.
concentrations, and tables of D.O. concentrations at specified
locations.
(APP) Applications of model: Level-Ill Receiving may be applied to the
surface drainage of most urban catchments. There is no limitation
to the size of catchment or number of storn events modeled (other
than computer time and costs). Data requirements are connon to
engineering analysis of nonpoints source problems and complete
instructions on data preparation are provided. Field measurements
are necessary to calibrate model parameters and verify predicted
values. The methodology is not applicable to systems requiring
multi-dimensional transient analysis. Complex water quality
conditions such as eutrophication, non-linear kinetic interactions,
sedimentation, and sediment exchange are not represented. TECHNICAL
CONTACT: Pr. Miguel A. Medina Oept. of Civil Engineering Duke
University Durham, NC 27706 (919)684-2434
(HDH) Computational system requirements - Hardware: Mainframe IBM
370/165 and AMDAHL 470-V6/II ;Disc storage 100
(LNG) Computational system requirements - Language(s) used: FORTRAN
(WTP) hater Models - Type of model: Hater quality
(ENV) Fnvironment(s) to which model applies: Stream/river
(CON) Processes and constituents included in model: Dissolved oxygen
(CPL) Complexity level of model: steady state mass balance
(REF) References - User manuals, documentation, etc.:
Medina, M. A., Jr. 1979. Level III: Receiving
Water Quality Modeling for Urban Stormuater Management.
EPA-600/2-79-100. D.S. Environmental Protection Agency,
Cincinnati, OH 45268.
(CNM) Contact na«e(s): Medina,M.A.
(COR) Contact organization: Department of Civil Engineering Duke
University
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1470
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Accession No. 16404000128
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Water Quality for River-Reservoir
Systems
(ACR) Acronym of Data Base or Model: HQRRS
(MED) ?edia/Subject of Data Base or Model: Water
(ABS) Abstract/overview of Data Base or Model: WGRSS was developed and
is supported by the U.S. Army Corps of Engineers" Hydrologic
Engineering Center. The WQRRS model (HEC, 1978a) consists of three
separate but integrable nodules: the reservoir module, the stream
hydraulic module/ and the stream quality module. The three computer
programs may be integrated for complete river basin water quality
analysis through automatic storage of results. An output tape may
be generated for input to a separate plotting and statistical
program called the Statistical and Graphical Analysis of Stream
Mater Quality Data (HEC, 1978b). The system is based on a
comprehensive lake ecological simulation program originally
developed by Chen and Orlob (1972 and a river simulation model
developed by Norton (1972). The original river routines only
simulated steady hydraulic conditions so the capability to
dynamically route streamflou using either the St. Venant equations,
Kinematic Wave, Muskingum, or Modified Puls method «as added.
Subsequent updating of the system added the capability to analyze
branched and looped stream systems and added additional water
quality and biological constituents (King, 1976; Smith, 1978). A
separate program for statistical and graphical analyses of stream
water quality data is available (HEC, 1978b).
(CTC) CONTACTS: R, G. Willey Hydrologic Engineering Center
Loc: 609 Second St. Ph: (916)440-3292
Loc: Davis, CA 95616
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: The methodology in the
reservoir section is applicable to aerobic impoundments that can be
represented as one-dimensional systems with horizontal isotherms.
The stream hydraulic module includes six hydraulic computation
options capable of handling hydraulic behavior within both the
"gradually varied" steady and unsteady flow regimes. The stream
quality module simulates transport of quality parameters in aerobic
streams. Physical processes modeled in WQRRS include advection,
diffusion, dilution, and the heat budget. Temperature effects on
water density and various kinetic parameters are considered. State
variables include 18 highly interconnected physical, chemical and
biological parameters: BOD, organic detritus, organic sediment,
coliform, total carbon, phosphate, ammonia, nitrites, nitrate, DO
pH, total alkalinity, total dissolved solids, carbon dioxide, two
algae species, zooplankton, fish, and benthic animals. The river
module also includes aquatic insects, benthic algae, suspended
solids and inorganic sediment.
(ASM) Basic assumptions of model:
one-dimensional vertical plane; and stream segments as a
one-dimensional horizontal plane.
(INP) Input to model: (1) Initial setup/calibration needs: (a) flow
1471
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Accession So. 16404000128 (cent)
rate for all lake and stream inflows/ (b) lake and stream
hydrogeonetric data, (c) lake outflow elevations and locations, (d)
latitude and longitude of prototype systems, (e) Secchi disc depth
for light extinction, (f) concentrations of quality constituents,
biological parameters, and temperatures in all lake inflows and
river segments throughout the simulation period, (g) initial
conditions of quality constituents, biological parameters, and
temperatures in each lake layer and river segment, (W all kinetic
parameters, including growth rates, decay rates, respiration rates,
settling velocities, mortality rates, and other chemical-ecologic
reaction rates, (i) temperature stability coefficients, (j)
meteorological data-air temperature (wet and dry bulb), atmospheric
pressure, wind speed, sky cover; (2) Verification needs: (a)
conditions of quality constituents, biological parameters, and
temperatures during the simulation period (vertical profile for
lakes, horizontal profile for river segments), (b) constituent
concentrations, biological parameters, and temperatures at the lake
outflow for specified time periods, (c) time history of lake water
surface elevations during simulation.
(OUT) Output of model: (1) Output Information: (a) time history of
quality constituents, temperatures, and biological parameters in
each lake layer and river segment, (b) time history of quality
constituents, temperatures, biological parameters in lake outflows,
(c) all input values specified; (2) Output format: (a) tabular
printout, (b) reservoir outflows to river system may be recorded on
cards or magnetic tape.
(APR) Applications of model: Model acquisition:
-------
Accession No. 16404000128 (cont)
Water Resources Research/ U.S. Dept. of Interior/ Washington/
D.C.
2. King/ I. P. 1976. Flow Routing for Branched River
Systems/ prepared for Hydrologic Engineering Center/
U.S. Army Corps of Engineers/ Davis/ CA 95616.
3. Norton, W. R. 1972. An Assessment of Hater Quality in
the Lower American River: Past/ Present/ and Future/
County of Sacramento/ Dept. of Public Works/ Sacramento, CA
95616.
4. HEC. 1978a. Water Quality for River Reservoir
Systems/ Hydrologic Engineering Center/ U.S. Array Corps of
Engineers/ Davis/ CA 95616.
5. HEC. 1978b. Statistical and Graphical Analyses of
Stream Water Quality Data/ Hydrologic Engineering Center/
U.S. Army Corps of Engineers/ Davis, CA 95616.
6. Smith/ D. J. 1978. Revised Water Quality for River-
Reservoir Systems Model/ prepared for Hydrologic
Engineering Center/ D.S. Army corps of Engineers, Davis/ CA
95616.
7. Willey, R. G. And D. Huff. 1978. Chattahoochee River
Water Quality Analysis, Hydrologic Engineering Center, U.S.
Army Corps of Engineers, Davis, CA 95616.
8. Willey, R. G., J. Abbott, and M. Gee. 1977. Oconee
River Water Quality and Sediment Analysis, Hydrologic
Engineering Center, U.S. Army Corps of Engineers, Davis, CA
95616.
(CNM) Contact name(s): Willey/R.G.
(COR) Contact organization: Hydrologic Engineering Center
-------
Accession No. 16404000129
(DQ) Date of Questionaire: 12-02-82
(•AM) Kane of Data Base of Model: Receiving Mater Quality Model
(ACR) Acronym of Data Base or Model: RHQM
(NED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: The Receiving Hater
Quality Model (RHQM) was developed by Resource Analysis/ Inc. for
the U.S. Amy Corps of Engineers' Hydrologic Engineering Center to
interface with STORM (Storage Treatment Overflow Runoff Model).
RHQM (HEC, 1979), when linked with the time history of storm and
dry-weather flows generated by STORM, provides the capability to
predict the impact of land surface runoff on stream water quality.
(CTC) CONTACTS: R.G. Willey Corps of Engineers, Hydrologic
Engineering C Loc: 609 Second St. Ph: (916) 440-3292
Loc: Davis, CA 95616
(STA) Data Base status: Operational/Ongoing
(DF) Date of fora completion: 01-25-83
(CAP) Functional capabilities of model: RHQM simulates the
one-dimensional transport and transformation of six water quality
parameters (temperature, DQ, carbonaceous BOD, nitrogeneous BOD,
orthophosphate, conforms) in freshwater stream networks.
(ASM) Basic assumptions of model: RHQM simulates time-varying
hydraulic and nater quality conditions by utilizing the law of mass
conservation for water and pollutant volumes. Stream routing uses
the kinematic wave assumption. Hater quality parameters are
modeled using first order kinetics.
(IMP) Input to model: RHQM input is on cards and tape files. Input
consists of, for each stream reach: Stream reach and segmentation,
simulation controls, I/O controls, percentile curve limits and
location, atmospheric temperature input, monthly stream equilibrium
temperature, monthly heat transfer rate coefficients, reaction rate
coefficients, reaction rate termperature modification bases, gauged
baseflow information, stream hydraulics information, boundary
conditions, tributary flows, point sources, nonpoint sources,
volumetric sources and sinks, STORM runoff and dry weather flow,
combined sewer overflows, storage releases and treated outflow, and
initial conditions.
(DOT) Output of model: RHQH offers a wide range of statistical output
to both summarize and provide "snapshots'* of simulated instream
conditions. Long term average, maximum, and miniBUM pollutant
concentrations, temperatures, and flows are tabulated and frequency
(percentile) curves can be computed. In addition, parameter
profiles can be printed for any day or "pollutagraphs" for chosen
locations.
-------
Accession No. 16404000129 (cont)
(LUG) Computational system requirements - Language(s) used: FORTRAN
(WTP) Hater Models - Type of model: Mater quality
(EOT) Environment(s) to which model applies: Stream/river
-------
Accession No. 16404000130
(DQ) Date of Questionaire: 12-02-82
CMAH) Kane of Data Base of Model: Air, Land, Mater Analysis System
(ACR) Acronym of Data Base or Model: ALHAS
(MED) Media/Subject of Data Base or Model: Air ;Toxic substances
;Hater ;0ther-surface runoff
(ABS) Abstract/Overview of Data Base or Model: ALHAS can siaulate the
effects on surface water quality of multimedia toxicant releases to
the environment. This mathematical model integrates the single
media models DIDOT, an air model, EXAMS a water quality model, and
NFS, a runoff nodel. It is most suitable for persistent organic
chemicals which tend to adsorb to particulate matter.
(CTC) CONTACTS: Dr. Kenneth F. Hedden
Loc: C.S. EPA/ERL-Athens, Georgia 30613, (404) 546-3310
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: ALMAS is designed to assist In
the assess ment of water quality problems associated with toxic
chemicals released to the atmosphere. The combined effect on
surface water quality of toxic releases to several media; including
air, non- point source, direct discharge, and grounduater may also
be eval uated. Analysis of groundwater-impacts is limited since
the user must know the rate and quality of groundwater recharge to
the surface water body. The model will be useful in determining
the most effective strategies for controlling water quality effects
of toxic chemicals regardless of the ultimate source, and will be
useful in evaluating the potential impacts of new chemicals enter-
ing commerce.
(ASM) Basic assumptions of model: The basic flow of the model is from
air to land surface to surface water body, with the direct transfer
from air to surface water body also accounted for. Atmospheric
point sources (smokestacks) and area sources (arising from
transportation, land use, residential heating, etc.) can be
simulated. Vet deposition, caused by the scavenging of air- borne
contaminants by precipitation, is simulated as well as dry
deposition resulting from such processes as gravitational settling,
lipaction, or dissolution of gases. Gaseous and particulate
contaminants are treated uniformly by the model, consistent with
recent findings that many toxic organic con- taminants which exist
as gases at atnospheric pressure and temperature nonetheless will
behave as participates with respect to deposition processes, since
the fraction of the airborne mass which is adsorbed to ambient
aerosols is primarily responsible for atmospheric deposition.
The aodel is designed to be applicable at a wide range of
spatial scales ranging from that of a calibrated NFS watershed
(litited to about 5 k«(2)) up to a major river basin covering
10(4)ka(2).
ALHAS is a time-dependent model whose fundamental time
step is one hour. DiDOT and NPSDEP respond at that time scale
while EXAMS interfaces with those two models after temporal
averaging over a user-determined number of days. The time
dependence of DiDOT is different mathematically from that exhibited
by KPSDEP and EXAMS. DiDOT uses a standard air dis- persion
1476
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Accession No. 16404000130 (cont)
approach which assumes that steady state conditions exist for each
hourly time step.
DiDOT can handle two contaminants in a single run. In
order to interface with NPSDEP/ one of these contaminants must be
total suspended particulates (TSP)/ while the other one may be any
toxic pollutant, either vapor and partially vapor and partially
adsorbed to ambient aerosol. DiDOT does not explicitly account for
the particle size distribution of particulate contaminant/ so the
deposition parameters should represent the mass weighted average of
the distribution of the parameters.
DiDQT's usage of meteorological and source characteristics
data is consistent with standard procedures used in most
EPA-supported air quality models, this feature makes the model
easy to use for those familiar with standard air modeling
procedures. DiDOT is also consistent with standard air modeling
procedures in its use of Gaussian dispersion algorithms/ Briggs
plume rise formula, ASVE dispersion parameters, and stability
classes based on wind speed and solar radiation. Its method for
accounting for limited mixing under an inversion lid/ is also
consistent with standard approaches.
Where DIDOT diverges from standard air quality models is in
its deposition algorithms. The dispersion algorithms utilized in
DiDOT represent a synthesis and application of current research and
mathematical analysis of the deposition process. In order to
describe the dry deposition process from point sources/ DiDOT
applies the vigorous analytical solution derived by Ermak which
accounts for both gravitational settling and surface depletion.
(IMP) Input to model: ALWAS requires inputs which may be separated
into six basic categories:
Meteorological data: each sub-model of ALWAS requires
meteorological data of different kinds. Both DiDOT and
NPSDEP require hourly meteorological data in formats com-
patible with standard reporting formats of the National
Weather Service.
Pollutant Source data: DiDOT and EXAMS require data
characterizing sources of the pollutant to the environment.
DiDOT treats three kinds of pollutant sources: point sources/
traditional area sources/ and distant city-sized area sources.
Pollutant fate properties: chemical specific inputs are
required primarily by DiDOT and SXAMS. DiDOT uses the settling
velocity/ deposition velocity/ scavenging ratio/ and atmos-
pheric degradation half-life. These/ in turn/ may be esti-
mated from knowledge of particle size/ Henry's law constant/
vapor pressure/ and molecular weight/ or other fundamental
properties. EXAMS requires similar inputs/ solubility in
water/ octanol/water partition coefficient/ rates of
hydrolysis/ photolysis/ and oxidation.
Calibration data for NPSDEP: NPSDEP requires calibra-
tion data — time series of water flow and quality at the
discharge point of an upland watershed.
Characteristics of the physical environment: NPSDEP
requires as input various physical features of the watershed
1477
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Accession So. 16404000130 (cent)
area-length of overland flow path, slopes, elevation, land
use characteristics, portions of watershed which are pervious
and impervious, soil characteristics, etc.
EXAMS relies extensively on a user-specified description
of the water body.
Interfacing data: within this category are the geo-
metrical relationships between the DiDQT receptor locations
(points at which deposition rates are calculated), NPSOEP
catchments/ and EXAMS cells.
(GOT) Gutput of model: The fundamental ALMAS outputs are the surface
water quality outputs presented by EXAMS. Ihese include the total
contaminant concentrations, as a function of time, in each EXAMS
cell, and the partitioning of that total contaminant among various
ionic, dissolved, sediment adsorbed, and biosorbed forms. DiDOT
also presents summary air quality outputs including long-term
average concentrations over the watershed and the extreme hourly
and daily average concentration. NPSDEP provides flow, sediment
transport, and toxicant loading outputs at monthly and annual
intervals, as well as short term output for major storms.
CAPP) Applications of model: Presently (1/83) the model has only been
used on the Third Fork Creek Watershed (M.C.) for sensitivity
analysis.
(HOW) Computational system requirements - Hardware: Mainframe POP
11/70 and IBM 370 ;Disc storage 64K
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? NO
-------
Accession No. 16404000130 (cont)
1479
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Accession No. 16404000131
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Chemical Migration and Risk
Assessment Methodology
(ACR) Acronym of Data Base or Model: CMRA
(MED) Media/Subject of Data Base or Model: Toxic substances ;Water
(ABS) Abstract/Overview of Data Base or Model: The CMRA Methodology
predicts the occurrence and duration of toxic contaninants in
stream systems. At the sane time, it predicts the probability of
acute and chronic damages to aquatic biota* The methodology
consists of the following components: 1) overload contaminant
transport modeling; 2) in- stream contaminant transport modeling;
3) statistical analysis of instream contaminant concentrations;
and, 4) probabilistic risk assessment.
CMRA is composed of three simulation models and one statis-
tical package: The Agricultural Runoff Management (ARM) Model
(Donigian and Crawford, 1976), the hydrodynamic component of
EXPLORE (Baca, et al., 1973), the sediment-contaminant model
SERATRA (Onishi, et al., 1979; Onishi and Wise, 1979, a,b), and the
statistical program FRANCO (Olsen and Wise, 1979; Onishi, et al.,
1979).
(CTC) CONTACTS: Robert 8. Ambrose, Jr.
USEPA/ERL/Athens, GA 30613 (404) 546-3546
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: ARM model predicts runoff and
sediment and contaminant loadings at the edge of a stream. ARM
provides continuous simulation of contaminant loading by modeling
hydro- logic response of watersheds, soil erosion, contaminant
adsorp- tion and removal, and contaminant degradation.
Instream chemical migration and fate are simulated by the
hydrodynamic, water-quality model, EXPLORE and the sediment-con-
taminant transport model, SERATRA. EXPLORE is a one-dimensional,
general water-quality model which provides discharge and depth data
to SERATRA. SERATRA is a finite element model uhich pre- diets
time-varying longitudinal and vertical distributions of sediments
and contaminants. The model consists of the follow- ing three
submodels coupled to describe sediment-contaminant interaction and
migration: o sediment transport o dissolved contaminant transport o
particulate contaminant (contaminants adsorbed by sediment)
transport.
The sediment transport submodel simulates transport, deposition,
and scouring for each size fraction (or sediment type) of both
cohesive and noncohesive sediments. The transport of particulate
contaminants is also simulated for those associated with each
sediment size fraction. The contaminant submodels include the
mechanisms of: 1) advection and dispersion of dissolved and par-
ticulate contaninants, 2) chemical and biological degradation,
3) adsorption/desorption, and 4} deposition and scouring of par-
ticulate contaminants. SERATRA also computes changes in river bed
conditions for sediment and contaminants.
The computer program, FRANCO, provides statistical sum-
marization of time-varying contaminant concentrations and is the
1480
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Accession No. 16404000131 (cont)
link between simulated instream contaminant concentrations and risk
assessment. It provides the frequency of occurrence and duration
of specified contaminant concentrations in receiv- ing waters.
Outputs include the number of tines and the percent of ti«e a given
concentration-duration level is exceeded/ and the concentration
levels involved.
Risk is typically determined by multiplying the pro-
bability of an event by the consequential effects. FRANCO pro-
vides a measure of the probability. The consequential effects are
expressed in terns of lethality and sublethality by using a medial
lethal concentration (LC50) and MATC (maximum accept- able toxicant
concentration). The LC50 with its associated duration is defined
as a concentration at which level 50% of an aquatic species Hill be
killed. This represents an acute impact. The MATC range is
located between the highest concen- tration showing no detectable
harmful effects and the lowest values displaying some observable
effect. Hence, MATC describes the effect-no effect boundary for
chronic toxicity.
By selecting specific concentration duration levels to natch
LCSOs and the MATC value, FRANCO provides a probabilistic risk
assessment. FRANCO displays consequence zones of lethality,
possible lethality, sublethality, and no-effect with the assoc-
iated probabilities.
(ASM) Basic assumptions of model: The three simulation models are
based on mass balance considerations. ARM and EXPLORE are
described elsewhere in this inventory. SERATRA is a finite-element
sediment-con- tatninant model that solves net first-order chemical
degradation and linear partitioning along with an unsteady sediment
balance that calculates local erosion and deposition.
(IMP) Input to model: Required input for ARM includes meteorological
data, physical and chemical properties of a contaminant,
contaminant application rates and practices, and watershed
characteristics.
Required input for EXPLORE and SERATRA includes channel and
sediment characteristics and adsorption/desorption properties of
the contaminants. Because the current toxicological data base is
not sufficiently advanced to fully utilize the par- ticulate
contaminant concentrations, only the cross-sectionally averaged,
dissolved pesticide concentrations are further analyzed for risk
assessment. However, the capability is there to include
particuiate contaminants adsorbed by suspended and bed sediments
which may be important under actual field cir- cumstances,
especially for assessment of a long-term aquatic i»- pact.
FRANCO typically uses six concentration-duration pairs to
define a piecewise concentration-duration curve to provide the
number of times, duration, and frequency a given concentra-
tion-duration curve is exceeded. Because of the lack of avail-
able toxicological data, the risk assessment is presently limited
to the direct effects of the dissolved form of the chemical.
Ingestion as a secondary route is not addressed, nor are indirect
effects such as bioconcentration of biomagnification.
(OUT) Output of model: Outputs for ARM and EXPLORE are described
1481
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Accession No. 16404000131 (cont)
elsewhere in this inventory. SERATRA produces tables of sediaent
and chemical concentrations for specified model segments over tine.
(APP) Applications of model: Battelle NM has applied the CMRA
Methodology to a portion of the Four Nile Creek Watershed, Four
Mile and Wolf Creeks in central Iowa. The toxic contaminant
selected for the test yas the pre-emergence herbicide/ alachlor/ a
widely used pesticide in the area. Alachlor Is a phenylaniline
with a moderate solubility and a snail capacity for adsorption to
sediment. Pesticide migration-fate modeling was performed for a
three year duration between June 1971 and May 1974.
(HDW) Computational system requirements - Hardware: Mainframe IBM, DEC
POP 11-70 ^Magnetic tape storage-varies w Printer-standard 132 line
printer
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering
(HTP) Hater Models - Type of model: Water quality
Water run-off
(CNf) Environment(s) to which model applies: Stream/river
;Non-point:non-urban
(CON) Processes and constituents included in model: Erosion and
sediment ;Toxic chemicals ^Biological effects ;H Hydraulics
(CPL) Complexity level of model: Transient mass balance ;Momentum
balance ;Multi dimensional
(REF) References - user manuals/ documentation/ etc.:
Baca, R. G./ W.W. Maddel, C.R. Cole/ A. Brandstetter/
and D.B. Cearlock. 1973. EXPLQRE-I: A River Basin Hater
Quality Model, prepared for the U.S. Environmental Protection
Agency by Battelle/ Pacific Northwest Laboratories/ Richland/ MA.
Donigian/ A.S. and N.H. Crawford. 1976. Modeling
Pesticides and Nutrients on Agricultural Lands. EPA-600/2-76-043.
O.S. Environmental Protection Agency/ Washington/ D.C.
Olsen/ A.R. and S.E. Wise. 1979. Frequency Analysis
of Pesticide Concentrations for Risk Assessment. Prepared for
the O.S. Environmental Protection Agency by Battelle/ Pacific
Northwest Laboratories/ Richland/ WA.
Onishl/ ¥./ and S.E. Wise. 1979a. "Finite Element
Model for Sediment and Toxic Contaminant Transport in Streams."
Proceedings of Conservation and Utilization of hater and Energy
Resources. Hydraulics and Energy Divisions/ ASCE/ San Francisco/
CA./ pp. 144-150.
Onishi, Y. and S.E. Wise. 19795. Mathematical
Model, SERATRA/ for Sediment and Contaminant Transport in
Rivers and its Application to Pesticide Transport in Four Nile
and Wolf Creeks in Iowa. Prepared for the U.S. Environmental
Protection Agency by Battelle/ Pacific Northwest Laboratories,
Richland, WA.
Onishi, ¥., S.M. Brown/ A.R. Olsen, M.A. Park-
hurst, S.E. Wise, and W.H. Walters. 1979. Methodology for
Overland and Instream Migration and Risk Assessment of Pesti-
cides. Prepared for the U.s. Environmental Protection Agency
by Battelle, Pacific Northwest Laboratories, Richland/ WA.
1482
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Accession No. 16404000131 (cont)
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1483
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Accession No. 16405000105
(DQ) Date of Questionaire: 12-02-82
(NAM) Fane of Data Base of Model: Formal Name = International Ground
Hater Modeling Center (IGWMC)
(ACR) Acronym of Data Base or Model: None
(MED) ftedia/Subject of Data Base or Model: Hater
(ABS) Abstract/overview of Data Base or Model: The purpose of the
Clearinghouse is to make available, to the ground water community,
a description and location of over 500 of the world's ground water
models. Specifically, model descriptions include: (1) aquifer
conditions included in model/ (2) fluid conditions included in
model, (3) model processes, (4) input data of model requirements,
(5) basic technique for BOdel, (6) geometry of model, (7) equation
solving technique, (8) error criteria, (9) computer specifications
for model, (lO)model program code information, (ll)references.
Model contributors include numerous universities, the Department of
the Interior, the (I.S. Geological Survey, the U.S. Corps of
Engineers, state and local agencies, private businesses (esp.
Battelle Pacific NH labs), as well as a number of foreign countries.
(CTC) CONTACTS: Director, IGWMC, Holcomb Research Institute, Butler
University Loc: Indianapolis, Indiana Ph: (317)283-9555
(STA) Data Base status: Operational/Ongoing
(DP) Date of form completion: 01-27-83
(CAP) Functional capabilities of model: Users can search the library
of Kodels according to the following model type and obtain a
listing of those which would best fit their needs: Prediction
(flow, mass transport, heat transport, deformation); Management;
Identification; and Data Manipulation.
(ASM) Basic assumptions of model: The user will be able to describe
needs in terms of goals, available monetary resources,
sophistication of needed results.
(IMP) Input to model: The users will supply general information
concerning the ne model type, aquifer extent and thickness, flow
characteristics, and data availability.
(OUT) Output of model: Library will provide listing of model type,
model developer of documentation, availability and past
utilization, and special features.
(APP) Applications of model: The clearinghouse has been used by water
rescurce planners, reasearchers, and field investigators of ground
water. NH: Contamination Sites Directon OFC: Holcomb Research
Institute, Butler University AD: Indianapolis, Indiana PH:
(317)283-9421
(HDV) Computational system requirements - Hardware: Mainframe
VAX11/78030 ;Disc storage 200 cylinders (15000000 Printer
(LNG) Computational system requirements - Language(s) used: Cobol
(HTP) Hater Models - Type of model: Ground water
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1484
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Accession No. 16405000114
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Feedlot Runoff Model Kansas State
University
(ACR) Acronym of Data Base or Model: FROMKSU
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: A continuous
simulation, digital computer, hydrologic model of feedlot runoff
generation and disposal has been developed by Kansas State
University for SPA. The purpose of the model is to establish
guidelines and design parameters for feedlot runoff control
facilities uhich uill meet the requirements of the Federal Hater
Pollution Control Act Amend- merits of 1972. The model continuously
monitors the water bud- get of a feedlot-storage pond-irrigation
disposal area control system using historic rainfall and
temperature data. It uses only readily available climate/ soil/
and crop data so that it can be applied to all major livestock
producing areas of the United States. The model is expected to be
useful in evaluating applications for "permits" to discharge and
for planning agencies in "Best Management Practices" for feedlots.
A user manual is included with program printout/ input data
requirements, and an example of a 25-year simulation.
(CTC) CONTACTS: Jerome J. Zovne
Loc: Kansas State University/ Manhattan/ Kansas (913) 532-5580
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-27-83
(CAP) Functional capabilities of model: FROMKSU is a continuous
simulation digi- tal computer program written in "Ten Statement"
Fortran for simplicity and compatibility with most machines having
Fortran capability. The model uses historical daily precipitations
and temperatures to evaluate the design of a particular feedlot at
a particular location. This version of FROMKSU reads the required
precipitation and temperature data from tapes provided by the
National Weather Service Climatic Center in Asheville/ North
Carolina. A magnetic tape drive is required in order to use this
program. Minor alterations would be necessary in order to read
this data from other sources.
(ASM) Basic assumptions of model: The model is based on the assumption
that run- off/ evaporation/ evapotranspiration/ irrigation
disposal, scheduling/ and storage pond size can be expressed by
mathe- matical equations uhich simulate on a continuous basis the
actual field condition. The model accounts for snoumelt on the lot
and disposal areas differently due to surface conditions, it con-
siders frozen ground and crop water use for disposal timing.
(IMP) Input to model: The model uses information that can be obtained
from exist- ing records and maps/ plus the design of the feedlot.
dim a- tological needs are included - maximum and minimum daily
temperature/ daily precipitation/ relative humidity/ percent
sunshine, wind speed/ intensity of solar radiation and coefficients
for the panman equa- tion. The size of the feedlot is necessary
along with the volume and design of the retention pond system/ also
the pumping rate/ size of disposal area, soil type cropping pattern
are needed. Several assumptions must be made about operation of the
148S
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Accession No. 16405000114 (cont)
disposal side of the system, requiring professional agricultural
Judgement.
-------
Accession No. 16405000115
(DQ) Date of Questionaire: 12-02-82
(NAM) Sane of Data Base of Model: Prediction of Mineral Quality of
Irrigation Return Flow
-------
Accession No. 16405000115 (cont)
cheeical pro- parties of the soil profile; and a hydrologic balance
of inflows and outflows of each node*
(OUT) Output of model: The model provides statistical information on
the quantity and quality of irrigation return flows within each
node. This includes surface return flow and the percolation
vertically through the soil profile. This information is then used
to deter- mine the impact of irrigation practices on the quality of
sur- face and ground water resources.
(APP) Applications of model: The model allows us to better define and
understand the relationship between irrigated agriculture and the
salt load- ing of streams. When applied to an irrigated region of
river basin/ it will help to answer such questions as: (1) What
effect would improved water-use efficiency have on irrigation
return flow water quality? (2) Would a change to a higher
efficiency increase or decrease salt loading? (3) Hhat Influence
would development of new irrigation projects have on the salt load
of surface and ground waters? (4) ¥hat effect would canal lining
have on salinity? and (5) What is the effect of drainage systems on
surface water salinity? Such questions involve many com- plexities
and cannot be answered easily.
(HDM) Computational system requirements - Hardware: Mainframe IBM 360,
CDC 6400, DEC 20 ;Disc storage (or tape) Magnetic tape storage (or
disc) ;Printer 1200 baud printer ;Card reader/punch o
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gravmlng ;Engineering
(WTP) toater Models - Type of model: Mater quality
(ENV) Environment(s) to which model applies: Stream/river ;Non-point-
irrigated agriculture, non-urban
(CON) Processes and constituents included in model: Eutrophication
^Salinity ^Hydrology
(CPL) Complexity level of model: Steady state mass balance ;Multi
dimensional
(REF) References - User manuals, documentation, etc.:
Hornsby, A.G. 1973. Prediction Modeling for Sali-
nity Control in Irrigation Return Flows. EPA-R2-73-168, EPA, Ada,
Oklahoma.
taalker, tf.R. 1976. Assessment of Irrigation Return
Flow Models. EPA-600/2-76-219, EPA, RSKERL, Ada, Oklahoma.
U.S. Bureau of Reclamation. 1977. Prediction of
Mineral Quality of Irrigation Return Flow: Volume 1-Summary Report
and Verification, Volume 2-Vernal Field Study, Volume 3-Simula-
tion Model of Conjunctive Use and Water Quality for a River
Basin, Volume 4-Data Analysis Utility Programs, Volume 5-Detailed
Return Flow Salinity and Nutrient Simulation Model, EPA-600/2-77-
179 a-e* EPA, RSKERL, Ada, Oklahoma.
(ROR) Responsible Organization: Office of Research and
Development.office of Environmental Processes and Effects
Research.Robert G. Kerr Environmental Research Laboratory.
1488
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Accession No. 16405000116
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Cattle Feedlot Runoff Reservoir
Design Evaluation Simulatio
(ACR) Acronym of Data Base or Model: NONE
(MED) Vedia/Subject of Data Base or Model: Mater
(A8S) Abstract/overview of Data Base or Model: The Cattle Feedlot
Runoff Reservoir Design Evaluation Simulation and Economic
Evaluation Models were develo- ped by Oregon State University for
EPA. These models can be used as one or the economic portion can
be used separately. The models were developed to design systems
that would match structures to proposed management techniques,
regional climatic data and economic considerations. The first/ the
sufficient design pro- gram, is a simulation model which sizes
feedlot runoff retention ponds based upon previous climatic data
and management dewater- ing policies. In addition to minimum pond
volume, the sufficient design model lists average number of yearly
pumpings for each simulated management alternative at a selected
pumping rate. The economic portion with a budget generator,
determines cost of open feedlot runoff control systems. The models
were tested at seven selected locations in the United States to
determine the effects of five pumping rates and seven management
deuatering alternatives on minimum storage volumes required to
prevent dis- charges as defined by EPA Effluent Guidelines.
Stations were selected from each major climatic region in the U.S.
and repre- sented a broad spectrum of precipitation patterns.
(CTC) CONTACTS: J. Ronald Miner
Loc: Oregon State University, Corvallis, Oregon (503) 425-2041
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-27-83
(CAP) Functional capabilities of model: These models are continuous
simulation in nature written in Fortran IV for simplicity and
compatibility with most machines. The models use historical daily
precipita- tions and temperatures to design runoff control systems
for a particular feedlot at a particular location, this data is
read from tapes provided by the National iieather Service Climatic
Center in Asheville, North Carolina. The models use seven sets of
management alternatives for design and two disposal policies for
economic evaluation of the designs.
(ASM) Basic assumptions of model: The design model portion assumes
that runoff and snowmelt runoff can be expressed by a mathematical
equation along with the designs of the pond. The system assumes
that all runoff in excess of the design storm (25 year - 24 hour
event) can be discharged. The disposal area is sized via the
manage- ment options selected and the nitrogen content of the
runoff water. The economic portion uses two options: 1) nutrient
util- ization, and 2) strict waste disposal. It accounts for all
cost based on 1977 dollars, but can be updated as necessary.
(INP) Input to model: The models require climatological data for the
site, selection of pumping rate, selection of a management policy,
physical data regarding the feedlot and disposal area and economic
coefficients. . **••*»•
(OUT) Output of model: The models provide a printed output listing
1489
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Accession No. 16405000116 (cont)
retention pond size and pumping days required for each management
option and at different pumping rates and the econonic portion pro-
vides the cost per head capacity for each option.
(APP) Applications of model: These models are designed to be used by
consul- tants, agricultural service agencies and planning or
regulatory groups to assist the producer in selecting the most
economical system to meet the zero discharge standard.
(HDH) Computational system requirements - Hardware: Mainframe-CPC
Cyber 7-IBM 360 ;Disc storage-250K jHagnetic t Printer-132 position
line printer ;Card reader/punch or tape/disc (input)
(LUG) Computational system requirements - Language(s) used: Fortran IV
<«fP) Water Models - Type of model: Hater run-off
(EH?) Environment(s) to which model applies: Lake ;Stream/river
;Non-point Feedlot runoff, irrigation dis non-urban
(CON) Processes and constituents included in model: Hydrology
(CPL) Complexity level of model: Steady state mass balance ;Multi
dimensional
(REF) References - User manuals, documentation/ etc.:
Miner, J.R., R. B. Hensink, and R.M. McDowell. 1979.
Design and Cost of Feedlot Runoff Control Facilities. EPA
600/2-79-707.
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Robert G. Kerr Environmental Research Laboratory.
1490
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Accession No. 16406000109
CDQ) Date of Questionaire: 12-02-82
CHAM) Name of Data Base of Model: tidal Temperature Model
(ACR) Acronym of Data Base or Model: TTM
(MED) Media/Subject of Data Base or Model: Hater
(ABS) Abstract/overview of Data Base or Model: The Tidal Temperature
Model (TTM) is a derivative of the Dynamic Estuary Model (DEM) that
can simulate the heat budget and dispersional characteristics of
streams, well-mixed shallow impoundments, estuaries, and coastal
waters. The model can accomodate constituents which nay be
conservative or non-conservative, have coupled or non-coupled
reactions, and which undergo first order decay. The TTM was
developed by the EPA Pacific Northwest Laboratory and has been
applied to the Columbia River below the Bonneville Dan.
CCTC) CONTACTS: Richard J. Callauay U.S. EPA, Corvallis Environmental
Resea Laboratory
Loc: 200 S.tf. 35th Street Ph: (503) 757-4703
Loc: Corvallis, OR 97330
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: The TTM represents the one
dimensional tidal and net river flow, transport processes of
advection and diffusion, the heat budget and the dilution of up to
four constituents within an estuary, stream, bell-mixed shallow
impoundment, or coastal waters. Coupled BQD-DO reactions may be
modeled, as well as up to four constituents which may be
conservative or non-conservative, have coupled or non-coupled
reactions, and undergo first order decay. The model can simulate
systems with up to 300 channels and as many as 300 junctions. The
TTV primarily links hydrodynamic and temperature/heat budget
components, but additional water quality constituents may be
possible. A standard heat budget approach and a thermal equilibrium
approach are used to figure temperatures.
(ASM) Basic assumptions of model: The TTM assumes that all inflows or
withdrawals are constant, and it utilizes a simplified form of
evaporation. One dimensional channels are used to represent two
dimensional flows and transports. The model neglects wind stress
and disregards lateral and vertical variation in channel
cross-sectional area with tidal elevation change. It handles
constant residual input rates which can be put in variable form,
and it cannot simulate tidal flats that go dry.
(INP) Input to model: The Tidal Temperature Model allows for a large
input data base, written in card-image form. Parameters which can
be specified include headwater flows, tributary flows, groundwater
flows, water withdrawals, seaward tides, channel depths and widths,
bottom roughness, constituents in freshwater inflows and at seaward
boundaries, constituent concentrations throughout the modeled area,
the quality and quantity of point-source residuals discharges, net
solar radiation, and wet and dry bulb temperatures.
(OUT) Output of model: Output formats include tabular printouts and
velocities written by the hydrodynamic module. Output information
provided by the model includes summarized data (maximum and minimum
values) for tidal cycles, flows, velocities, water elevation,
1491
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Accession No. 16406000109 (cont)
constituent concentrations at each junction, channel velocities,
junction depths, and constituents at user specified periods*
(APP) Applications of model: The Tidal Temperature Model has been used
by the EPA Pacific Northuest Mater Laboratory and has been applied
to the Columbia River belou the Bonneville Dan. The model has also
beet> used by the EPA in Massachusetts, South Carolina, Florida,
Oregon, and Washington. TECHNICAL CONTACT: Melvin O. Hinson, Jr.
Quality of the Environment Division Resources for the Future 1755
Massachusetts Avenue NW Washington, DC 20036 COM 703/462-4400
Richard J. Callauay U.S. EnvironMental Protection Agency Corvallis
Environmental Research Laboratory 200 S.U. 35th Street Corvallis,
Oregon 97330 FTS 420-4703 COM 503/757-4703
(HDK) Computational system requirements - Hardware: Mainframe any
digital computer ;Disc storage 50,000 words ma
(LNG) Computational system requirements - Language(s) used: Fortran I?
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Accession No. 16406000110
(DQ) Date of Questionaire: 12-02-82
(NAM) Rarae of Data Base of Model: M.I.T. Transient Mater Quality
Network Model
CACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: The M.I.T. Transient
Water Quality Network Model is a one-dimensional, real-time/
nitrogen cycle model which can be used for nitrogen-limited,
aerobic estuarine systems. The BOdel solves one-dimensional
continuity and momentum equations to generate the temporal and
spatial variations in the tidal discharges and elevations. This
information is used in the solution of the conservation of mass
equations for the water quality variables, which include salinity,
temperature, carbonaceous BOD, nitrogen cycle variables, DO, and
fecal coliform. The model combines the work of many investigators
and has undergone a great deal of modification. It uas originally
developed at the Ralph M. Parsons Laboratory for Water Resources
and Hydrodynamics at the Massachusetts Institute of Technology, and
its broadest application has been the St. Lawrence River and
Estuary. The model is intended to be used in engineering decisions
regarding the degree of eutrophication due to distributed and point
source loadings in estuaries.
(CTC) CONTACTS: Richard J. Callaway U.S. EPA, Corvallis Environmental
Resea Laboratory
Loc: 200 S.K. 35th Street Ph: (503) 757-4703
Loc: Corvallis, OR 20036
(STA) Data Base status: Operational/Ongoing
(DF) Date of fora completion: 01-25-83
(CAP) Functional capabilities of model: The model was developed for
aerobic estuarine ecosystems and includes seven storage variables
and twelve transformations of nitrogen between those variables.
The storage variables include:
1) *(1), Amwonia-N, 2) S(2), Nitrite-N, 3) N(3),
Nitrate-N, 4) N(4), Phytoplankton-N, 5) N(5), Zooplankton-N, 6)
»(6), Particulate Organic-N, and 7) N(7), Dissolved Organic-K. The
transformations include:
1) nitrification, 2) uptake of inorganic nitrogen by
phytoplankton, 3) grazing of herbivores, 4) avmonia regeneration in
living cells, 5) release of organic matter from living cells, 6)
natural death of living organisms, and 7) amraouification of organic
nitrogen. The user can specify a branching and or looping network
of channels called reaches where each reach can be of variable
cross-section along its longitudinal axis. Storage volumes are
provided for along the reach and any number of concentrated or
distributed water quality loadings can be specified along each
reach. The flow regime can be that of an estuarine system with an
unsteady tidal elevation driving the circulation at the ocean
boundaries in combination with the upstream flow. For subcritical
flow, three possible boundary conditions can be specified, and
these are: 1) the Discharge Qf
2) the surface elevation Z, and 3) a relationship between
Z and Q. The node! can simulate control structures within the
1493
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Accession Mo. 16406000110 (cont)
network itself instead of only at the boundaries, and the user is
permitted to specify a boundary condition at the upstream side of
the control structure. Three possible boundary conditions
(concentration, dispersion flux, and total flux) and a special
ocean boundary procedure are provided.
(ASM) Basic assumptions of model: The M.I.T. Transient Water Quality
Network Model defines the geometry of the water body along a
particular reach by interpolation between the cross-sectional data
submitted by the user. The model pays strict adherence to the IB ass
conservation principle as applied to the element nitrogen, and Its
ecosystem model is coupled with a real-tine hydrodynaaic transport
system as opposed to a tidal-average or slack-tide approximation.
The structure of the model was formulated such that the level of
complexity would not be too complex to the point of diminishing
returns, nor too simplified to the point where rate-governing
parameters must be determined by curve fitting the available field
data. Carbonaceous BOD is handled as a first order decaying
substance in the classical manner.
(IMP) Input to model: Input data is divided into nine groups. Card
Group A includes information regarding solution options. Here it is
stipulated which solutions (hydraulic and water quality) will be
executed and which water quality parameters will be modeled. Time
parameters stipulating the duration of the run and the time step of
integration, and the network topology (identification and sequence
of reaches) is also provided. Card Group B provides the geometric
information (i.e./ the physical properties of the channel), and the
computational mesh spacing and initial conditions required for the
hydraulic solution. This group is repeated for each reach as given
in Group A. Card Group C provides values of rate coefficients for
those water quality parameters being modeled. The coefficients may
be specified for the entire network or may be specified for each
individual reach. If the user does not wish to specify values, the
program will automatically use default values. In this card group,
the computational mesh spacing for water quality calculations and
initial conditions for water quality parameters are also specified.
Card Group D describes the location, magnitude and quality of any
lateral inflows being considered. Lateral inflows are considered
for both the hydraulic and water quality solutions. Card Group E
describes the same information for any injections (e.g. sewage
treatment plant or waste heat discharge) of water quality
parameters, injections are considered only in the water quality
solution. For hydraulic purposes they are considered passive, that
is, they have no effect on the flow field in the receiving water.
Card Group F stipulates the hydraulic boundary conditions to be
applied at each node. Card Group G allows the user to selectively
view output from the hydraulic solution. Card Group H stipulates
the water quality boundary conditions to be applied at each node in
the network, and Card Group I allows the user to selectively view
output for the water quality solution. The sequence of the input
cards is important to note. Certain card groups (D,E,F,G,H,I) for
particular cases must be repeated several times corresponding to
the number of periods for which the solution is executed.
1494
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Accession No. 16406000110 (cent)
COOT) Output of model: The large volume of numerical information
generated by the computer is conveniently represented in graphical
fore, A plotting program is available for use on an incremental
druff plotter. The output for the hydraulic solution can be
requested in two forms:
1) a hydrograph which displays the parameters at a given
mesh point as a function of time, and 2) a hydraulic profile which
displays the parameters at a given time as a function of distance.
The hydraulic parameters displayed are surface elevation/ depth/
discharge/ and velocity. Output for the water quality solution
also may be displayed in two forms: 1} water quality graphs/ i.e./
parameters as a function of time/ and 2) water quality profiles/
i.e./ parameters as a function of distance* Special features
permit the user to plot several variables on the same frame and
also to plot user-supplied data points as special symbols.
CAPP) Applications of model: The model has had a number of
applications/ the broadest application being to the St. Lawrence
River and Estuary/ a study sponsored by the Canadian Departments of
the Environment and Transport and Quebec Service de Protection de
1'Environment and Ministers des Richesses Naturelles. Thatcher/
Pearson and Mayor-Mora have described the application to both
riverine and estuarine portions of the St. Lawrence River from
Cornwall to Montmagny/ a distance of 275 miles. The need for a
published user's manual was recognized by the National
Environmental Research Center/ U.S. EPA/ Corvallis/ Oregon/ and
their support has enabled documentation of the model at this stage
of its development. The EPA has used the model for test purposes.
(HDW) computational system requirements - Hardware: Mainframe Any
model ;Disc storage 256K for compilation; 226K for plotting program-
-------
Accession No. 16406000110 (cont)
in Unsteady Flows," Technical Report Ho. 175, R.M. Parsons
Laboratory for Hater Resources and Hydrodynamics,
Department of Civil Engineering, M.I.T., November 1973,
Harleman, D.R.F. and Thatcher, M.L., "Longitudinal
Dispersion and Unsteady Salinity Intrusion in Estuaries,"
La Houille Blanche/Mo. 1/2 - 1974.
Henderson, P.M. Open Channel Flow, MacMillan Co.
N.Y., 1966.
Larsen, P.A., "Hydraulic Roughness of Ice Covers,"
JHD, ASCE 99, HYI, January 1973.
Najarian, T.O. and Harleaan, D.R.F., "A Real Time
Model of Nitrogen-Cycle Dynamics in an Estuarine System,"
Technical Report No. 204, R.M. Parsons Laboratory for
Hater Resources and Hydrodynamics, Department of Civil
Engineering, M-I.T./ July, 1975.
Surveyor, Nenniger & Chenevert, Inc. and Carrier,
Trottier, Aubin, "Hydrodynamlc and Hater Quality
Simulation Model: Cornuall-Montmagny Section/" Report
to Department of Environment, Canada, March 1973.
Surveyer, Nenniger & Chenevert, Inc., and Carrier,
Trottier, Aubin; (In French) "Hydrodynaaic and Mater
Quality Simulation Model: Cornwall-Montmagy Section,**
Report to Service de Protection de 1'Environment Quebec,
March 1974.
Thatcher, M.L. and Harleman, D.R.F., "Mathematical
Model for the Prediction of Unsteady Salinity Intrusion
in Estuaries,*1 Technical Report No. 144, R.M. Parsons
Laboratory for Hater Resources and Hydrodynamics,
Department of Civil Engineering, M.I.T., February 1972.
Thatcher, M.L., Pearson, H.H., and Mayor-Mora, R.E.^
"Application of a Dynamic Network Model to Hydraulic and
Hater Quality Studies of the St. Lawrence River," 2nd
Annual Symposium of the Waterways, Harbours and Coastal
Engineering Division, ASCE, San Francisco, September 1975.
Harleman, D.R.F., Dailey, J.E., and Thatcher, M.L.,
Hajari an, T.O., Brocard/ D.N., and R.I. Ferrara, "User's
Manual for the M.I.T. Transient Hater Quality Network
Model," Report for U.S. Environmental Protection Agency,
Office of Research and Development, Corvallis Environmental
Research Laboratory, Corvallis, Oregon. U.S. EPA
Publication EPA-600/3-77-010, January 1977.
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1496
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Accession No. 16406000111
(DQ) Date of Questionaire: 12-02-82
(HAH) Same of Data Base of Model: Enhanced Hydrodynamical-Numerical
Model for Near Shore Proce
(ACR) fccronym of Data Base or Model: HN
(HED) Pedia/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: The Hansen type
multilayer Hydrodynamical- Numerical (HN) model described by Bauer
has been used successfully to study the dynamics of numerous
coastal areas. The optimized version of the HN model combines the
vertically integrated single layer HN model originally developed by
Professor H. Hansen, University of Hamburg/ Germany/ and the
multilayer multiple-open boundary HN model proposed by Hansen and
developed by Dr. T. Laevastu.
(CTC) CONTACTS: Richard J. Callauay U.S. EPA/ Corvallis Research Lab/
Marin Freshwater Ecology Branch
Loc: 200 Southwest 35th St. Ph: (503) 757-4703
Loc: Corvallis/ Oregon 97330
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: The enhanced HN model
simulates near-shore currents and exchange processes. Enhancements
to the multilayer Hansen type Hydrodynamical- Numerical model
include: non-linear tern extension to facilitate small-mesh
studies of the near-shore/ including river dynamics; layer
disappearance extension to enable appropriate procedures in tidal
flat and marshy regions/ as well as some dotm/upuelling cases;
thermal advection enhancement for treatment of thermal pollution
cases by method of moments coupled with heat budget procedures for
dynamic plume development experiments; and Monte Carlo diffusion
enhancement to deal with dispersion via statistical methods and
comparison to the method of moments experiments.
(ASM) Basic assumptions of model: The Hydrodynamical-Numerical model
is an explicit numerical difference scheme based on leap- frog
integration of the two dimensional Eulerian form of the
hydrodynamical eguations through time to obtain a dynamical
boundary-value solution of tidal order. Advection is simulated by
the method of moments/ a quasi-Lagrangian method which maintains
information on the zeroth/ first and second order moments of the
concentration in each cell of the grid mesh. In order to introduce
the random element for utilization of Monte Carlo methods/ the
total velocity for a particular fluid particle is assumed to be
composed of a Bean flow velocity component and a turbulent flux
velocity component. The HN model provides the mean flow velocity
and the Monte Carlo scheme provides the turbulent flux velocity.
Dispersion is thus modeled by simulating the diffusion process
stochastically within the background fluid in motion. The
Pedersen-Prahm thermal advection scheme has been chosen since it is
a conservative scheme without the pseudo-diffusion of Eulerian
difference methods. In order to model the heat budget effects on
the thermal discharge as it is transported by the currents
throughout the region/ the Laevastu thermal techniques were
selected.
1497
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Accession No. 16406000111 (cont)
(IMP) Input to model: Input to the HN BOdel include grid and mesh
size; system geometry, bathymetry, and boundaries; average
latitude; Coriolis factor/ tidal data; wind values; outfall sources
and sinks; storm surge/ and river inflow. Control cards and
library directives are necessary for the selection of subroutines*
(OUT) Output of Model: Output provided by the model include computer
printouts of the input variables and contour plots.
CAPP) Applications of model: The enhanced HN model has been applied by
the EPA to Prudhoe Bay/ and a section of the coastal area of the
Beaufort Sea/ Alaska/ and the San Onofre outfall in California.
The model can be used to evaluate the advection and dispersion of
constituents in near shore coastal waters.
(HDW) Computational system requirements - Hardware: Mainframe CDC 3300
and CDC 6500 ;Printer
(OSK) Computational systev requirements: Operator Knowledge/Skills: exp
erience In environmental modeling and an understanding o
(HTP) Water Models - Type of model: Water quality
(ENV) Fnvironment(s) to which model applies: Stream/river ;Metlands
(COR) processes and constituents included in model: Temperature
;Hydraulics
(CPL) Complexity level of model: Simplified
(RET) References - User manuals, documentation/ etc.:
Bauer, R.A. and Stroud, A.D. Enhanced
Hydrodynamical-Nuaerical Model for Near shore Processes.
In Press. Prepared by Compass Systems/ Inc./ San Diego/
California, for Corvallis Environmental Research
Laboratory, Office of Research and Development/ U.S.
Environmental Protection Agency/ Corvallis/ Oregon.
EPA Contract 68-03-2225.
Bauer/ R.A. Description of the Optimized DPRP Multi-
Layer Hydrodynamical-Ruaerical Model. EN7PREDRSCHFAC
Tech. Paper No. 15-74, Environmental Prediction Research
Facility, Monterey/ California/ 1974.
Hansen/ V. Hydrodynamical Methods Applied to Oceanographic
Problems. In: Proceedings of the Symposium on
Matheaatical-Hydrodynamical Methods of Physical
Oceanography, institute Fur Meereskunde der Onlversitat
Hamburg/ Hamburg, Vest Germany, 1962. pp. 25-34.
Laevastu, T. and P. Stevens. Applications of Numerical-
Hydrodynamical Models In Ocean Analysis/Forecasting.
FNWC Tech. Note Ho. 51, Fleet Numerical Weather Central,
Monterey, California, 1969.
Laevastu/ T. and K. Rabe. A Description of The EPRF
Hydrodynamical Models in Ocean Analysis/Forecasting.
FNWC Tech. Note No. 51, Fleet Numerical Weather Central/
Monterey/ California/ 1969.
Laevastu, T. A Vertically Integrated Hydrodynamical-
Numerical Model (W. Hansen Type), Model Description and
Operating/Running Instructions. Part 1 of a series of
four reports. ENVPREDRSCHFAC Technical Note No. 2-74,
Environmental Prediction Research Facility, Monterey,
California/ 1974.
1498
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Accession No. 16406000111 (cent)
Laevastu, T. A Multilayer Hydrodynamical-Nuraerical
Model (W. Hansen type), Model Description and Operation/
Running Instructions. Part 2 of a series of four
reports. ENVPREDRSCHFAC Technical Mote No. 2-74,
Environmental Prediction Research Facility, Monterey,
California, 1974.
Laevastu, T. in collaboration with M. Clancy and A.
Strcud. Computation of Tides, Currents, and Dispersal
of Pollutants in Lower Bay and Approaches to Neu York
with Fine and Medium Grid size Hydrodynaraical-Nuiaerical
Models. Part 3 of a series of four reports.
ENVPREDRSCHFAC Technical Note No. 3-74, Environmental
Prediction Research Facility, Monterey, California,
1974.
Laevastu, T. and R. Callauay in collaboration with A.
Stroud and M. Clancy. Computation of Tides, Currents
and Dispersal of Pollutants in Neu York Bight from Block
Island to Atlantic City with Large Grid Size, Single
and Two Layer Hydrodynamical-Nunerical Models. Part
4 of a series of four reports. ENVPREDRSCHFAC Technical
Note No. 4-74, Environmental Prediction Research Facility,
Monterey, California, 1974.
Laevastu, T. and G.D. Hamilton. Computations of
Real-Time Currents Off Southern California With Multilayer
Hydrodynamical-Numerical Models with Several Open
Boundaries. ENVPRSDRSCHFAC Technical Paper No. 10-74.
Pedersen, L.B. and L.P. Prahm. A Method for Numerical
Solution of the Advection Equation eC/et=V.VC,
Meteorological institute of Denmark, as submitted
to TELLUS, August, 1973.
Laevastu, T. and J.M. Harding. "Numerical Analysis and
Forecasting of Surface Air Temperature and Hater Vapor
pressure." Journal of Geophysical Research, 79(30):
4478-4480, 1974,
Stroud, A.D. and Bauer, R.A. User Guide for the
Enhanced Hydrodynamical-Nuraerical Model. In Press.
Prepared by Compass Systems, Inc., San Diego, California,
for Corvallis Environmental Research Laboratory, Office
of Research and Development, U.S. Environmental Protection
Agency, Corvallis, Oregon, under EPA Contract
No. 68-03-2225.
Young, Chen-Shyong. Thermal Discharges into the Coastal
Haters of Southern California. Southern California
Coastal Water Research Project (SCCV.RP), Los Angeles,
California, 1971.
Maier-Reimer, E. Numerical Treatment of Horizontal
Diffusion and Transport Phenomena in Marine Basins of
Large Size, Institut fur Meereskunde der Universitat
Hamburg, Hamburg, West Germany, as presented at IAMPA/IAPSQ
Assembly, Melbourne, Australia, January, 1974.
Thompson, R. Numerical Calculation of Turbulent
Diffusion. Quart, J.R. Met. Soc. 97(411):93-98,
1499
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Accession No. 16406000111 (cont)
1971.
CROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1500
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Accession No. 16406000112
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Aqueous Chemical Equilibrium Model
(ACR) Acronym of Data Base or Model: REDEQLEPAK
(MED) Kedia/Subject of Data Base or Model: Hater
(ABS) Abstract/Overview of Data Base or Model: The chemical
equilibrium model (RBDEQL.EPAK) computes aqueous equilibria for up
to 20 metals and 30 ligands in a system. The metals and ligands
are selected from a list of 35 metals and 59 ligands for which
thermodynamic data for complexes and solids have been stored in a
data file. The equilibria vhich the program considers include
conplexation, precipitation, oxidation-reduction, and pH-dependent
phenomena. A user's guide for this computer program was published
by EPA in February 1978 and a modified version of the program was
published in May 1980. The later version includes temperature
corrections for equilibrium constants and activity coefficients,
calculation of degree of saturation for selected solids, and
theoretical attainment of an electrically neutral solution for a
more realistic system. An adsorption model (surface complexation)
is also included in the later version.
(CTC) CONTACTS: Don Schults
Loc: EPA, Marine Science Center, Newport, Oregon 97365
(503) 867-4039
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: The REDECL.EPAK program is
designed to compute chemical equilibria involving solids,
complexes, oxi-dation- reduction and mixed solids in an aqueous
system. The inputs for the program are the total concentrations of
metals and ligands in the system, including quantities in solids
and gas phases if these are allowed to interact yith the aqueous
system. Computation is based on thermodynamic data contained in
the data file. Two major limitations exist with the model: (1) the
program is for equilibrium; kinetics of dissolution, precipitation
and oxidation-reduction are not considered and (2) the program is
no better than the analytical and thermodynamic data that is used.
(ASM) Basic assumptions of model: The program assumes the system is at
chemical equilibrium at the specific conditions established by the
data input. Kinetics are not considered in determining
equilibrium. It's assumed that the system is strictly chemical and
there is no biological component which will influence the chemistry.
(IMP) Input to model: Input to the program includes: total
concentration of metal and ligands in the system, including
quantities in solid and gas phases if these are allowed to interact
with the aqueous system, the pH and the oxidation-reduction
potential of the systei. Up to 10 cases of different total
concentrations for a set of metals and ligands can be treated by
the program in one run.
(OUT) Output of model: The output of the program are the speciation of
the metals and ligands and their concentration in various forms and
combinations. The first page of output is the input thermodynamic
data corrected to the ionic strength and temperature used. The
second page describes the input data read into the computer. The
1501
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Accession Ho. 16406000112 (cont)
next page is the case progress giving the total and free
concentration of all species and the total amount of solids and
mixed solids in one liter of solution. The concentration of all
metal species and associated ligands and the concentration of
complexes is reported. The percent distribution of metal and
ligand species is also reported.
(APP) Applications of model: This computer program calculates the
chemical equilibrium for metals and ligands in an aquatic system.
The program has been used to determine Cu complexing capacity of
natural waters, calculate metal speciation in soil/water systems/
account for the fate of trace raetals in ocean discharge, assess the
sorption and leaching of heavy netals in groundwater and relate
species of Cu to toxicity. The program has been used by EPA,
universities, industrial and consulting firms.
CHDfc) Computational system requirements - Hardware: Mainframe-IBM
360/370 ;Disc storage-4000 blocks (80 column b Printer-132 position
line printer ;Card reader/punch
CLNG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements: Operator Knowledge/Skills: Oth
er-Physical sciences
(HTP) fcater Models - Type of model: Hater quality
-------
Accession No. 16407000102
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Mater Quality Modeling System for
the Great Lakes
(ACR) Acronym of Data Base or Model: WQMSGL
(MSD) Media/Subject of Data Base or Model: Toxic substances ;Water
CABS) Abstract/Overview of Data Base or Model: The Hater Quality
Modeling System for the Great Lakes consists of three subsystems
which when applied together allow the user to develop/ calibrate
and verify water quality models for aquatic systems. Although the
system was developed to serve EPA's research mandates for the Great
Lakes, it has general applicability to any water system/ (i.e.;
rivers/ estuaries/ snail lakes, and coastal). Also/ the system can
be applied to most any water quality problem, constituent/ or their
interactions.
(CTC) CONTACTS: William L. Richardson O.S. EPA/ Office of Research
and
Development/ Environaental Research Lab/ Duluth, MH
Loc: 9311 Groh Rd., Grosse lie/ Michigan 48138 Ph: (313) 226-7811
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-28-83
(CAP) Functional capabilities of model: WASP - The kinetic
(biochemical structures) of the model is written by the user or he
can apply any number of kinetic subroutines that have been
developed by previous users. The transport characteristics of the
water system to be modeled are assumed to be known or determined by
current meter studies or hydrodynamic models* Another method of
determining transport is to use WASP to trace a conservative
substance through the system and adjust the transport parameters
until the calculated concentration matches the measured. HASP then
numerically integrates the system mass balance equations in space
and time and calculates tine variable concentrations of the
substances in each spacial segment. A table of available kinetic
subroutines/ authors, capabilities/ applications/ and references
follow. EPA/ LLRS continues to support research to refine and
verify these models and to incorporate new substances and processes
as they are needed. DASA - DASA consists of a small, working data
base inputed directly or obtained frora STQRET retrievals and
maintained on a DEC-PDP-11/45. A series of sub-programs are
available which access the parameters under study and compute
means/ standard deviations/ standard errors/ etc. for input to MVP
or for graphical display subroutines available in HASP. HVP - MVP
is used to make statistical comparisons between calculated
concentrations and those measured. It is used during calibration
to provide an efficient means to determine the difference between
results of two or more "runs" which have been made varying one of
the model coefficients. Finally/ it can be used to judge the
accuracy of the model compared to the data and to compare results
of two or more models.
(ASM) Basic assumptions of model: HASP - Transport structure is known
or can be determined by tracing a conservative substance. Hater
system can be divided into large/ spacial compartments which can be
assumed to be completely nixed. Time scale of the problem is on
1503
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Accession No. 16407000102 (cent)
the order of weeks to seasons up to decades (although smaller time
scales could be considered). DASA - It is assumed that data are
available through a research or surveillance program over the
period of time corresponding to the scale of the problem and
recorded by geographical locations (station, depth), time (Year/
month, day, hour), and collected and analyzed according to
prescribed quality control program. MVP - It is assumed that enough
data exists to statistically characterize the model state variables
in »any of the water segments over the time scale of the problem.
-------
Accession No. 16407000102 (cont)
Connolly. 1980. Mathematical Models of Mater Quality in Large
Lakes. EPA Ecological Research Series. In press. Cons Simple
subroutine for tracing a conservative or 1st order reacting
substance in a system. Applied to Saginau Bay.
(HDfcO Computational system requirements - Hardware: Mainframe DEC-PDF
11/45 IBM 370/168 ?Disc storage 2000 block Printer
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;Engineering ^Limnology, biochemistry
(HTP) Hater Models - Type of model: Water quality
(ENV) Environment(s) to uhich model applies: Estuary jLake
;Stream/river /Marine
(CON) Processes and constituents included in model: Dissolved oxygen
;Eutrophication /Toxic chemicals ;Salinity Teaperature ;Quality
processes
(CPL) Complexity level of model: transient mass balance ;one
dimensional ;aulti dimensional
(REF) References - User manuals, documentation/ etc.:
DiToro, D.M., James J. Fitzpatrick, and R.V. Thomann.
Hater Quality Analysis Simulation Program (HASP) and Model
Verification Program (MVP) Documentation. Hydroscience/ Inc.
In preparation.
Richardson, tf.L. and K. McGunagle. Data Analysis and Storage
(DASA) User Manual* EPA, Large Lakes Research Station.
In preparation.
(CNM) Contact natae(s): Richardson,*.L.
(COR) Contact organization: D.S. EPA, Office of Research and
Development, Environmental
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1505
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Accession No. 16407000105
(DQ) Date of Questionaire: 12-02-82
(MAM) Nam* of Data Base of Model: Spatially Segmented Phytoplankton
Model
(ACR) Acronym of Data Base or Model: 5SEG
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: The model describes
phytoplankton growth as a function of systen hydrology, phosphorus,
nitrogen, silicon, light, and temperature. Phytoplankton biomass
is partitioned into five functional groups: diatoms, greens,
non-N<2>- fixing blue-greens, N<2>-fixing blue-greens, and
"others". An internal nutrient pool kinetics mechanism is included
to describe phytoplankton nutrient uptake and growth. Zooplankton
are included, and are partitioned into two functional groups:
herbivorous and carnivorous. Compartments are included for total
concentrations of phosphorus, nitrogen, and silicon in the
sediments. Sediment-water interactions for these nutrients are
described using a wind-driven resuspension mechanism. The model is
spatially-segmented in the horizontal.
(CTC) CONTACTS: Victor J. Biernan EPA Office of Research and
Development
Loc: Environmental Research Lab-Karragansett, South Ferry Rd.,
Narragansett, RI 02882S Ph: (401) 789-1071
(STA) Data Base status: Operational/ongoing
(DF) Date of form completion: 02-11-83
(CAP) Functional capabilities of model: The model includes 28 state
variables for each spatial segment. Op to five horizontal spatial
segirents can be included. The model is not segmented in the
vertical. Values for advective flows and dispersions, nutrient
loads, light, temperature, and boundary conditions must be
specified externally. The model is typically run for a one year
simulation, although both larger and shorter simulations can be
conducted. Results of a T-test analysis between model output and
field data for Saginaw Bay, Lake Huron, indicated that the model
described the field data to an accuracy of approximately 85 percent.
(ASM) Basic assumptions of model: The model is based on the principle
of mass balance for each of the 28 constituents in each segment.
The model is coded in FORTRAN and consists of a series of ordinary,
non-linear, simultaneous differential equations. An Adams- Moulton
predictor-corrector technique is used to solve the equations
numerically. Typical time steps used are 30 minutes for the
nutrient equations and 3 hours for the phytoplankton equations.
(IMP) Input to model: To run the model, values for advective flows and
dispersions, nutrient loads, light, temperature, and boundary
conditions must be specified as input. To calibrate the model,
segment averages of individual sampling station concentrations are
needed for each state variable for the time period of interest.
(DOT) Output of nodel: The model can produce line printer output
consisting of all values for state variables and values for
individual component terms in each differential equation. This can
be clone at daily or five-day intervals. The model also can produce
a summary data file on a disk which contains values for all state
variables at five-day intervals. This file can be used off-line to
1506
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Accession No. 16407000105 (cont)
produce graphical output. A graphics program is available with the
/.on A for Producln9 overlay plots of model output and field data.
(APP) Applications of model: The model has been calibrated to two
extensive sets of field data for Saginaw Bay, Lake Huron,, acquired
during 1974 and 1975. The calibrated model was used to generate a
series of phosphorus load reduction simulations. Results of these
simulations are being compared to the outcome of a follow- up field
survey conducted on Saginaw Bay in 1980.
(HDW) Computational system requirements - Hardware: Mainframe Univac
1110, POP 11/45, or PDF 11/70 > Disc storage 64K words ; Printer
132 column model
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering ;operator oust have applications experience with
simulation models; scientific programming.
(WTP) Water Models - Type of model: Mater quality
(EN7) Fnvironraent(s) to which model applies: Estuary ;Lake ;Embayment
(CON) Processes and constituents included in model: Eutrophication
;Temperature ;Biological effects ;Hydrology ;
(CPL) Complexity level of model: transient mass balance ;multi
dimensional
(REF) References - User manuals, documentation, etc.:
There does not exist a User's Manual at this time.
The development and calibration of a single segment version of
the model, including all equations and coefficients appears
in:
Bier man, V.J., Jr., Dolan, D.M., Stoermer, E.F., Gannon, J.E.
and Smith, V.E. 1980. The development and calibration of a
spatially simplified multi-class phytoplankton node! for
Saginaw Bay, Lake Huron. Great Lakes Environmental Planning Study,
Contribution No.33, Great Lakes Basin Commission, Ann Arbor, Mich.fl
Results of phosphorus load reduction simulations with the
spatially segmented version appear in:
Bierman, V.J., Jr. and Golan, D.M. 1980. Responses of Saginaw
Bay, Lake Huron, to reductions in phosphorus loadings from the
Saginaw River. Report prepared for the International Joint
Commission. Bierman, V.J. and Dolan, D.M. 1981, Modeling The
phytoplankton- nutrient dynamics in Saginaw Bay, Lake Huron. J.
Great Lakes Res., Vol.7, pp.409-439.
(CNM) Contact name(s): 3ierman,V.J.
(COR) Contact organization: EPA Office of Research and Development Ph:
(401) 789-1071
(AOR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1507
-------
Accession Ho. 16407000106
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Tine-dependent, Three-dimensional,
Variable-density Hydrodyn
(ACR) Acronyn of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Hater
CABS) Abstract/Overview of Data Base or Model: The tile-dependent,
three-dimensional, variable-density hydrodynamic model Has
developed to describe the motion in thermal discharges, harbors,
bays, lake basins, entire lakes, estuaries. Marine coastal areas,
etc. The model calculates velocities and temperature (salinity,
also, if required) as a coupled set of time-dependent, non-linear
partial differential equations. The results of the model can be
used as input to a transport model (described separately). The
model has various versions (user specified) such that the
calculations can be performed with the Hater surface treated as a
rigid-lid or as a free-surface, and with the bottom boundary
condition specified either as no-slip or slip.
(CTC) CONTACTS: Dr. John F. Paul EPA Office of Research and
Development
Loc: Environmental Research Laboratory-Narragansett, South Ferry
Rd.,f Narragansett, RI 028821 Ph: (401) 789-1071
(CAP) Functional capabilities of model: The model is fully
time-dependent and three-dimensional. The spatial resolution is up
to the discretion of the modeler and the time step restrictions are
dependent on the individual application. The Coriolis, pressure
and vertical diffusion terms in the equations are calculated
implicitly in time, so no time step stability restriction applies
to them. The other terms are calculated explicitly. The momentum
and energy (and salinity) equations are coupled. Various
combinations of boundary conditions can be used at the discretion
of the modeler. Conservation-preserving finite- difference
techniques are used.
(ASM) Basic assumptions of model: The equations are derived from the
time- dependent, three-dimensional equations for conservation of.
mass, momentum, energy and salinity. The principal assumptions
are:
1) hydrostatic pressure variation; 2) rigid-lid or linearized
free-surface approximation; 3) eddy coefficients to account for
turbulent diffusion effects. The program for the model is modular
in form so the last condition can be modified to account for
various turbulence modeling schemes. The solution procedure is a
modification of the simplified marker and cell technique.
(INP) Input to model: Input to the model includes: complete
specification of geometry and grid layout, topography and forcing
functions. The latter includes Hind (constant or spatial and
temporal varying), infions/outflows and heat specification at water
surface. The initial conditions can be quiescent conditions, some
user specified form, or results from a previous calculation.
(OUT) Output of model: The basic output of the program Is a printed
record of velocities, temperature, salinity and pressure, as
desired. If results are stored (disc or tape), separate programs
are available to produce graphic output on either Tektronix,
1508
-------
Accession No. 16407000106 (cont)
Versatee, or Calcomp equipment. The plots available include tine
series of variables, and horizontal and vertical section plots of
the variables.
(APP) Applications of model: The model has been applied to the
following: Lake Huron; Lake Erie; separate basins of Lake Erie;
area of Lake Erie for proposed jetport; Cleveland harbor; vicinity
of Ponroe, Michigan for proposed dredged spoil sites; Saginau Bay;
numerous thermal discharges in Great Lakes and Baltic Sea; Sea of
Azov; Lake Baikal; Santa Barbara Channel; and Haukegan Harbor.
Organizations that have used the model or results of the model
include Corps of Engineers, Swedish Meteorological and Hydrological
Institute, Argonne National Laboratory, Rudjer Boskovic Institute
(Jugoslavia), Hydrometeorological Institute (USSR), Ohio State
University, University of Arizona, NASA, NOAA, University of
California,Institute for Electrical Investigation(Mexico), and U.S.
EPA. The output of the model can be used directly in a separate
transport model.
(HDW) Computational system requirements - Hardware: Mainframe Cray,
IBM 370/4300, Univac 1100, Vax 11/780 ;Disc Disc storage: 0-50 M
bytes ;Magnetic tape storage 0-2 units to process ; Printer high
speed line printer ;card reader/punch if disc input not used
(LNG) Computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Wor
king Knowledge of scientific computer programming and hydrod
(WTP) hater Models - Type of model: Water quality
Thermal, hydrodynaaic transport
(EN?) Environment(s) to which model applies: Estuary ;Lake ;Marine
(CON) Processes and constituents included in model: Salinity
;Temperature ;Hydrology ;Hydraulics
(CPL) Complexity level of model: multi dimensional, tine-dependent
(REF) References - User manuals, documentation, etc.:
Lick, W.J., J. Paul, and y.p. sheng. 1976. The
dispersion of contaminants in the near-shore region. In:
Modeling biochemical processes in aquatic ecosystems (R.P.
Canale, ed.) Ann Arbor Science Publishers, Inc. pp. 93-112.
Paul, J.F. 1976. Modeling the hydrodynaaic effects of large
man-made modifications to lakes. Proc. of the EPA Conf. on
Environmental Modeling and Simulation (H.R. Ott, ed.).
EPft-600/9-76-016, pp. 171-175.
Paul, J.F. and W.J. Lick. 1973a. A numerical mode' for a
three-dimensional, variable-density jet. Report Nc:•* FTAS/TR-
73-92, School of Engineering, C.W.R.U., Cleveland, >
-------
Accession No. 16407000106 (cont)
complete field (W.E. Dunn, A.J. Policastro and R.A. Paddock),
A»L/hR-75-3, pp. 484-511.
Paul, J.F. and M.J. Lick. 1976. Application of three-dimensional
hydrodynamic model to study effects of proposed
jetport island on thermocline structure in Lake Erie. Report
17-6 of Lake Erie International Jetport Model Feasibility
Investigation. U.S. Army Engineer Waterways Experimental
Station Contract Report H-75-1.
Paul, J.F. and W.J. Lick. 1979. An efficient, implicit method
for calculating time-dependent, free-surface, hydrodynanic flows.
Presented at the 22nd Conference on Great Lakes Research,
Rochester, New York.
Paul, J.F. and W.J. Lick. 1983. Numerical model for
three-dimensional, variable-density rigid-lid hydrodynamic flows:
Volume 1. Details of the numerical model. EPA research report in
press.
Paul, J.F., H.L. Richardson, A.8. Gorstko, and A.A. Natveyou.
1979. Results of a Joint USA/USSR hydrodynaraic and transport
modeling project. EPA-600/3-79-015.
Vasseur, B., L. Funkquist, and J.F. Paul. 1980. Verification
of a numerical model for thermal plumes. SMHI Hydrology and
Oceanography Report No. 24. Heinrich,J., Lick,M., and Paul,J. 1981.
Temperatures and currents in a stratified lake: a two-dimensional
analysis. J. Great Lakes Res., Vol. 7, pp 264-275. Jamaro,B.H«,
Lick,*,, Paul,J., and Milliff,R. 1982. Numerical modeling of the
currents on the continental shelf. Proc. Ocean Structural Dynamics
Symposium '82, Oregon State Oniv., Corvallis.
(CNM) Contact name(s): Paul,J.F.
(COR) Contact organization: EPA Office of Research and Development
Station, South Ferry Rd., Narragansett, RI 02882, Ph: (401)
789-1071
(ROR) Fesponsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1510
-------
Accession No. 16407000107
CDQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Time-dependent. Three-dimensional
Transport Model
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Water
CABS) Abstract/Over view of Data Base or Model: The time-dependent,
three-dimensional transport model was developed to calculate the
hydrodynaraic transport of conservative and non-conservative
substances in various water bodies. The model calculates the
ti*.e-dependent concentration of the desired substance. Input to
this model for velocities are results from the separately described
hydrodynamic model. Various user specified options permit
application to conservative substances such as chloride and
non-conservative substances such as suspended solids.
(CTC) CONTACTS: Dr. John F. Paul EPA Office of Research and
Development
Loc: Environmental Research Lab-Narragansett, South Ferry Rd.,
Narragansett, RI 02882 Ph: (401) 789-1071
(CAP) Functional capabilities of model: The model is fully
time-dependent and three-dimensional. The spatial resolution is up
to the discretion of the modeler but is usually the same as used in
the hydrodynaraic model. The tine step restrictions are dependent
on the particular application. The vertical diffusion term in the
equation is calculated implicitly in time so there is no time step
stability restriction for this term. The other terms in the
equations are treated explicitly. Various combinations of boundary
conditions can be used. For suspended solids calculations, flux at
the water-sedinent interface is parameterized by 2 coefficients
determined by laboratory experiments. Conservation-preserving
finite-difference techniques are used.
(ASM) Basic assumptions of nodel: The equations are derived from the
time-de- pendent, three-dimensional equation for conservation of
material. The main assumption is that eddy coefficients are used
to account for turbulent diffusion effects. The program for the
model is nodular in form so this condition can be changed to
incorporate various turbulence modeling schemes.
(INP) Input to model: Input to the model includes: complete
specification of geometry and grid layout (which can be obtained
from hydrodynamic model), topography and forcing. The latter
includes velocities (from hydrodynamic model), inputs/outputs and
other things such as wind, depending on what is being modeled. The
initial conditions can be user specified or from results of
previous calculation.
(OUT) Output of model: The basic output of the program is a printed
record of concentrations, as desired. If results are stored (disc
or tape), separate programs are available to produce graphic output
on either Tektronix or Calcomp equipment. The plots available
include time series of variables and horizontal and vertical
section plots of variables.
(APP) applications of model: The model has been applied to the
following: Lake Erie, entire basins of Lake Erie, Saginaw Bay, Sea
of Azov, Lake Baikal and Waukegan Harbor. Organizations that have
1511
-------
Accession Mo. 16407000107 (cont)
used the model include various federal agencies and universities in
this country and in Europe. TECHNICAL CONTACT: Dr. John F. Paul
ORD, ERL Narragansett, South Ferry Rd., Narragansett, RI 02B82 Ph:
(401) 789-1071
(HDV) Computational system requirements - Hardware: Mainframe Cray*
IBM 370/4300, Onivac 1100, Vax 11/780 ?Disc Disc storage:0-50 M
bytes ^Magnetic tape storage 0-2 units to process } Printer High
speed line printer ;Card reader/punch if disc input not used
(LRG) Computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Hor
king knowledge of scientific computer programming and hydrodynamic
modeling
(MTP) fcater Models - Type of model: Water quality
Sediment transport/resuspenslon
(ENV) Environment(s) to which model applies: Estuary ;Lake ;Marine
(COM) Processes and constituents included in model: Erosion and
sediment ;Toxic chemicals ^Temperature ;Hydrolog Hydraulics
(CPL) Complexity level of model: multi dimensional, timedependent
(REF) References - User manuals, documentation, etc.:
Lick, «. J., J. Paul, and Y. P. Sheng. 1976.
The dispersion of contaminants in the near-shore region.
In: Modeling biochemical processes in aquatic ecosystems,
(R.P. Canale, ed.) Ann Arbor Science Publishers, Inc.
pp. 93-112.
Paul, J. F. and R. L. Patterson. 1977. Hydrodynamic
simulation of movement of larval fishes in Western Lake
Erie and their vulnerability to power plant entrainment.
Proc. of the 1977 Winter Simulation Conf (H. J. Highland,
R. G. Sargent and J. H. Schmidt, ed.), VSC Executive
Committee, pp. 305-316.
Paul, J. F., ¥.. L. Richardson, A. B. Gorstko, and A. A.
Matveyev. 1979. Results of a Joint OSA/OSSR hydrodynamic
and transport modeling project. EPA-600/3-79-015. Heinrich, J.,
Lick, W., and Paul, J. 1981. Temperatures and currents in a
stratified lake: a two-dimensional analysis. J. Great Lakes res.,
Vol.7, PP.264-275. Jamart, B.M., Lick, W., Paul, J., and Hilliff,
R, 1982. Numerical Modeling of the currents on the continental
Shelf. Proc. Ocean structural Dynamics Symposium *82, Oregon State
Univ., Con"rvallis.
(CflM) Contact na*e(s): Paul,J.F.
(COR) Contact organization: EPA Office of Research and Development
ERL-Narragansett, South Ferry Rd., Narragansett, RI 02882 Phi
(401) 789-1071
(ROR) Responsible organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1512
-------
Accession No. 16502000101
(DQ) Date of Questionaire: 12-02-82
(NAM) Rame of Data Base of Model: Honlonlzing Radiation Models
-------
Accession No. 16502000101 (cont)
as the local SAR value at various defined locations within the
sphere, for a given incident frequency. Two additional programs
both employing ECOMP, have been developed: PLOT is a graphical
routine giving plots of local SAR against radial distance for
different aziauthal angles. ECOHX searches for the peak internal
SAR value over a given range of RF frequencies for a given sized
sphere. Convergence tests are employed in these programs in order
to ensure that there is rapid convergence of the infinite series
usec in the Bessel function expressions. Convergence is generally
obtained within 12-15 terns. Valid solutions are obtainable for
all combinations of sphere size and wave length including the
important resonant region where energy absorption reaches a peak.
The prolate spheriodal model is composed of homogeneous muscle-like
dielectric only and simulates large-scale objects such as humans or
primates. Solutions to the problem are based on the extended
boundary condition method (EBCM) which has been found to be the
most successful of the various methods available for dealing with
lossy prolate spheriod objects. However, for spheroids having high
eccentricity ratios equivalent to that of standard man (a/b = 6.3),
the method breaks down in the resonant frequency region owing to
problems of ill-conditioned matrices which the computer cannot
handle. The computer program, EBCQ, is written in FORTRAN and has
been run on a Control Data CYBER 70, Model 73 machine.
(ASM) Basic assumptions of model: The electromagnetic radiation is
assumed to be a simple plan wave, as exists in the far-field of an
antenna. The biological objects are of simple spherical or prolate
spheroid shape and are composed of dissipative dielectric materials
that are linear, homogeneous and isotropic. The heat transfer or
conduction aspects of the problem have not been considered.
(INP) Input to model: a. Inputs for sphere model.
1) Radius of core.
2) Number of outer layers and layer thicknesses.
3) Dielectric data (relative permittivity and conductivity)
of all tissue equivalent materials as a function of frequency.
4) Frequency or frequency range of incident wave.
5) Internal spherical co-ordinates, (r , 0 ,0) at which internal
fields are to be computed (or range of same).
6) Maximum allowable number of terms in series and tolerance
for convergence of series, b. Inputs for prolate spheroid model.
1) Major and minor axis values.
2) Dielectric data of muscle-equivalent material as a
function of frequency.
3) Frequency range of incident wave.
4) Orientation of major axis of spheriod with respect to
E-field vector.
5) Angle of incident wave with respect to major axis.
(OUT) Output of model: Outputs for both models are:
1) Absorption cross section and absorption efficiency
2) Total absorbed power.
3) Average SAR.
Outputs for sphere model only are:
1) Local internal E-field values (r , 0 ,0 components).
1514
-------
Accession No. 16502000101 (cont)
2) Local SAR or dose rate value.
(APP) Applications of model: These models provide insight into the
effect of nonionizing electro-magnetic energy in the RF-microwave
frequency, and allow researchers to predict approximately the
thermal load to which an animal is being subjected to during
experimental irradiation. These results can be extrapolated and
applied to humans. TECHNICAL CONTACT: Dr. Claude M. Weil
Experimental Biology Division (MD-74) Health Effects Research
Laboratory Environmental Protection Agency Research Triangle Park,
NC 27711 FTS 629-2617 COM: 919/541-2617
(HDW) Computational system requirements - Hardware: Mainframe Cyber 70
Model 73 jDisc storage 75-80 thousand uor
(LNG) Computational system requirements - Language(s) used: Fortran IV
or V
(OSK) Computational system requirements: Operator Knowledge/Skills: Sci
entific programming and electromagnetic theory
-------
Accession No. 16503000107
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: A Mathematical Model for
Fast-Screening Procedure for Testin Effects of Pollutants in Mammals
(ACR) Acronym of Data Base or Model: None
(MED) Media/Subject of Data Base or Model: Animals
(ABS) Abstract/Over view of Data Base or Model: The model offers an
"on-line" method for measuring the effect of pollutants on
respiratory efficiency in mammals, and it applies to any biological
system in Mhich the transport of matter is through yell- defined
compartments. Since C0<2> excretion from the lungs (a measure of
efficiency of respiratory function) has a well-defined distribution
with time/ it can be used for the prediction of effects by
pollutants entering the body system. In this particular case/ the
nodel was derived for the prediction of the effect of ingested
methylmercury (11) cloride on the excretion of (14)CO<2> from the
lungs. This method reduces the observation period from several
hours to only a few minutes. It is suggested that this model or a
similar one can be used for measuring the efficiency of other body
functions, provided that there exists a measurable parameter that
has a well-defined distribution with time.
(CTC) CONTACTS: Robert L. Miller EPA-Health Effects Research
Laboratory
Loc: 26 W, St. Clair Street, Cincinnati/ Ohio 45268 Ph:
513-684-7454
(STA) Data Base status: Discontinued
(DF) Date of form completion: 02-07-83
(CAP) Functional capabilities of model: The model is in the form of a
fourth order differential equation requiring a solution of eight
equations. Using mathematical methods of approximation/ the model
can be fitted precisely to a two-parameter model of the fora: R *
Bt exp (-8<2>t), where R is the rate of excretion of (14)CO<2>.
In this form/ only two measurements at the beginning of the
experiment are required in order to predict the effects of the
pollutants on respiratory function. The measure of effects is the
difference of cumulated <14)CO<2> excreted CR( + ) - function<0>(t) R
dt3 between the control animals and the exposed animals.
(ASM) Basic assumptions of model: It is assumed that a two-pool open
system exists (Shipley and Clark/ 1972) in which the blood pool is
the central coopartment while the second pool is a conglomerate of
peripherals such as the kidneys/ lungs/ and liver. Peripheral
pools can communicate only through the central compartment. If we
ignore the dead space in the respiratory tract/ then the lung can
be considered as composed of two classical compartments (Riley/
1965): the gas-exchange compartment/ and the anatomical dead space
in the alveoli. The model is based on the fact that the blood is
the vehicle by which the effect of an ingested toxicant/ such as
CH<3>HgCl, is super-imposed on all other peripherals/ thus
influencing the (14)CO<2> pattern. Each component is assumed to
follow first-order kinetics in that the (14)CO<2> loss rate is
taken to be proportional to the nunber of moles of the (14)CQ<2>
within a compartment. Actually/ excretion from the blood pool is
not linear (Piotrowski/ 1971). But/ as we assume/ when
1516
-------
Accession No. 16503000107 (cont)
steady-state kinetics apply the blood pool can also be treated as a
classical compartment. (Aris,
1966).
(INP) input to model: The model requires only two measurements of
(14)CO<2> from Gary vibrating reed electrometers in conjunction
with ionlzation chambers. Output of the model is the total
cumulative value of (14)C excreted and the percent of (14)C
excreted.
(CSR) Computational System Requirements: Solutions to the model can be
obtained on a digital DEC 10 computer/ but the model is simple
enough that it can be solved on any other computer system or
calculator.
(APP) Applications of model: The model has been used for a series of
experiments by the Health Effects Research Laboratory of the EPA*
and it can be used in biological investigations where there is a
need for a fast screening of pollutants (eg. heavy metals or
chemical compounds). The effects on respiratory efficiency or
cardiac output can be predicted in a short time/ thus saving time/
animals/ and personnel. This same approach can be developed for
any other body function with a well defined time distribution via a
contpartraental analysis. TECHNICAL CONTACT: Rumult Iltis and Robert
L. Wilier U.S. Environmental Protection Agency Health Effects
Research Laboratory 26 U. St. Clair Street Cincinnati/ OH 45268 FfS
684-7417 COM: 513/684-7417
(HDW) Computational system requirements - Hardware: Calculator
jMainframe DEC 10 or any other system
(LNG) computational system requirements - Language(s) used: User can
choose language
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
granming
(REF) References - User manuals/ documentation/ etc.:
Iltis/ R./ and Miller/ R. L. "A Fast-Screening
Procedure for Testing the Effects of Pollutants in Mammals."
Journal of Toxicology and Environmental Health. 3:683-689/ 1977.
Iltis/ R. "Mathematical Model for the Excretion of (14)CO<2>
During Radio Respirometric Studies." Proceedings of the
Conference of Environmental Modeling
Proceedings of the Conference on Environmental Modeling
and Simulation. U.S. EPA publication SPA 600/9-76-016/ July 1976.
Aris/ R. Compartmental Analysis and the Theory of Residence
Time Distribution in Intercellular Transport/ ed. K. B.
Warren, New York: Academic Press/ 1966.
Piotrowski/ J. The Application of Metabolic and Excretion
Kinetics to Problems of Industrial Technology. Washington,
D.C.: Department of Health/ Education/ and Welfare/ 1971.
Riley R. L. "Gas Exchange Transportation/" Physiology
and Biophysics, eds. T. C. Ruch and H. D. Patton.
London: Saunders/ 1965.
Shipley, R. A. and Clark, R. E. Tracer Methods for in
vivo Kinetics. New York: Academic Press, 1972.
(CNH) Contact name(s): Miller/R.L.
(COR) Contact organization: EPA-Health Effects Research Laboratory
1517
-------
Accession No. 1650300010? (cent)
(ROR) Responsible Organization: Office of Research and
Development.Office of Health Research.Toxicology & Microbiology
Division.
1518
-------
Accession No. 17301300001
(Dg) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: Multi30: A Computer Prograa For The
Risk Assessment Of Toxi
(ACR) Acronym of Data Base or Model: MULTI80G
(MED) Media/Subject of Data Base or Model: Toxic Substances
(ABS) Abstract/Overview of Data Base or Model: This program was
developed for the generation of low-dose carcinogenic risk
assessments of toxic substances based on the generalized multihit
and one-hit dose-response functions applied to animal response data
derived from lifetime feeding studies.
(CTC) CONTACTS: Gary F. Grindstaff, U.S. SPA, Office of Pesticides *
Toxic
Substances, Office of Toxic Substances, Health and Environmental
Review
Division
Loc: E617B Waterside Mall, (TS-796) 401 M. St, S.W., Washington,
D.C. 20460 Ph:
(202) 382-3459
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-23-82
(CAP) Functional capabilities of model: Limitations of the model:
There must be at least two positive (non-zero) dose levels. There
may be no more than 14 positive dose levels. The average run time
may vary for the same job by as much as +20%.
(ASM) Basic assumptions of model: The generalized multihit model is
equivalent to assuming a ganma tolerance dist However, it is
mathematically quite complex; thus, rather than list assumptions
here, individuals interested in the underlying assumptions are
referred to the Technical Contact for copies of theoretical papers
underlying the development of this model.
(INP) Input to model: The inputs to the model are: the number of
positive (non-zero) dose levels in the bioassay, magnitude of each
dose level; total numbers of animals on test at each dose level,
estimated environmental exposure levels and their number, "on-off"
switch for confidence limits, number of environmental exposure
levels as input, and total numbers of animals with tumor types of
interest at each dose level
(OUT) Output of model: The principal outputs of interest from the
model are: a chi-square goodnes-of-fit test, an maximum likelihood
estimate of the parameters of the generalized multihit and one-hit
models, point estimates and 90, 95, 97,5, 99, and 99.5 lower
confidence limits on "virtually safe dose" for risks from 1 in 10
to 1 in 100,000,000, point estimates and 90, 95, 97.5, 99 and 99.5
upper confidence limits on risks for each environmental exposure
level provided as input
(APP) Applications of model: The model, in conjunction with a variety
of other models, is used to estimate lifetime carcinogenic risks
associated with various levels of suspected human carcinogens. The
estimates are then included in risk assessments supporting
regulatory actions under Sections 4, 5 and 6 of the Toxic
Substances Control Act. TECHNICAL CONTACT: Gary F. Grindstaff
OTS/Health and Environmental Review Div. E617B Waterside Mall,
1519
-------
Accession Ho. 17301300001 (cont)
M St" S'W-' Washington, D.C. 20460 382-3459
nal syste« requirements - Hardware: Mainframe IBM
;Disc storage less than 300K bytes ;Pr
Computational system requirements - Language(s) used: Fortran G
}TDS0!fpu tat*onal system requirements: Operator Knowledge/Skills: MCC
-IBM Users Conventions, WYLBUR Editing
(REF) References - User manuals, documentation, etc.:
User Manual for Revised MOLTI80 Program is the program
documentation. Several theoretical papers, including
this documentation and method of access to the model at the
are available from the Technical Contact. All users must
,~. Vave a re9istered account on the EPA IBM System.
(CHM) Contact narae(s): Grindstaf f,G.F.
tCOR) contact organization: Office of Toxic Substances, Health and
Environmental Review Division (202) 382-3459
(ROR) Responsible Organizations Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Health and Environmental
Review Division.
1520
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Accession No. 17301300002
(DQ) Date of Questionaire: 12-02-82
(NAN) Kane of Data Base of Model: One-Hit Low-Dose Extrapolation Model
(ACR) Acronym of Data Base or Model: ONEHITMD
(MED) Media/Subject of Data Base or Model: Toxic Substances
(ABS) Abstract/Overview of Data Base or Model: This program computes
maximum likelihood estimates of the parameters of the one-hit
model. Abbott's connection is incorporated so that estimates of
increased risk may be generated. The parameters generated by the
model are used in the assessment of lifetime carcinogenic risks at
low environmental doses*
(CTC) CONTACTS: Gary F. Grindstaff, Office of Toxic Substances/
Health and Environmental Review Division
Loc: E617B Waterside Mall, (TS-796) 401 M St., S.H., Washington,
D.C. 20460 Ph:
(202) 382-3459
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-23-82
(CAP) Functional capabilities of model: The limitations of the model
are: The numbers of experimental doses must not exceed 10. The
numbers of dose levels must not exceed 20. Other limitations, if
any, are unknoyn.
(ASM) Basic assumptions of model: The theory of the one-hit model says
that there is some risk of cancer from even a slight exposure to a
carcinogen, and that the exponential probability law gives the
probability that a carcinogen at a given dosage will induce cancer
in a laboratory animal. The detailed, mathematical assumptions
underlying this model are provided in the program documentation,
available from the Technical Contact.
(INP) input to model: Inputs to the model include: number of
experimental groups (e.g. males, females), number of dose levels,
chi-square values for derived confidence Halts, dose levels,
titles of experimental groups, number of responders and number at
risk for each control and treated group in each experimental group.
(OUT) Output of model: The principal outputs of this model include:
lower confidence limits for dose at specified attributable risks
from 10(-1) to 10(-8) and louer confidence limits on the one-hit
parameter. These estimates are presented first for all dose groups
and then for successively smaller dose group combinations,
eliminating the highest dose on each iteration.
(APP) Applications of model: This model is used to estimate lifetime
carcinogenic risks associated with various suspected human
carcinogens. The model is only used, however, alth dichotomous
data from animal bioassays. The estimates of carcinogenic risk are
used in risk assessments supporting regulatory actions under
Sections 4, 5 and 6 of the Toxic Substances Control Act. TECHNICAL
CONTACT: Gary F. Grindstaff OPTS/OTS/HERD/EB. E617B Waterside
Mall,(TS-796) 401 M St., SW, Washington., D.C. 20460, 382-3459
(HDW) Computational system requirements - Hardware: Mainframe IBM
370/168 ;Disc storage less than 300K bytes ^Printer 132 position 1
(LNG) Computational system requirements - Language(s) used: Fortran G
(OSK) Computational system requirements: Operator Knowledge/Skills: NCC
-IBM User Conventions and WYLBUR Editing
1521
-------
Accession No. 17301300002 (cont)
(REF) References - User manuals, documentation/ etc.:
Crump, K«S. (1981)* An improved procedure for
lou-dose carcinogenic assessment for animal data. Journal
of Environmental pathology and Toxicology, (5(2):675-684.# Mantel,
N., Bohidar, N., Broun/ C«, Ciminera, J., and Tukey, J.
(1975). An improved Mantel-Bryan procedure for "safety" testing
of carcinogens. Cancer Research, 34: 865-872.
Hartley, H.O. and Sielken, R.L., Jr. (1978). Development of
statistical methodology for risk estimation. Final report.
National Center for Toxicological Research, Contract Mo.
222-77-2001, April, 1978.
Hartley, H.O. and Sielken, R.L. (1977). Estimation of "safe
dose" in carcinogenic experiments. Biometrics, 33:
1-30.
Rai, K. and Van Ryzin, J. (1980). MULTI80: A computer program
for risk assessment of toxic substances. Technical Report
No. N-1512-NIEHS, Rand Corporation, Santa Monica.
Van Ryzin, J. and Rai, K. (1980). The use of guantal response
data to make predictions. In: The Scientific Basis of Toxicity
Assessment. H. Hitachi (ed.) Elsevier/North Holland, Hen
York, 273-290.
Rai, K. and Van Ryzin, J. (1981). A generalized multihit dose-
response model for lou-dose extrapolation. Biometrics, 37:
341-352.
Keter, J. and Wasserman, W. (1974). Applied Linear Statistical
Models. Irwln, Inc.
Crump, K.S., Daffer, D.Z., and Hasterman, M.D. (1980). Low-dose
extrapolation utilizing time-to-occurrence cancer data.
In: Final Report, National Institute of Environmental Health
Sciences, Contract No. N01-ES-2133.
Daffer, D.Z., Cruap, K.C., and Hasterman/ M.C. (1980).
Asymptotic theory for analyzing dose-response survival data
with application to the low-dose extrapolation problem.
Mathematical Biosciences, 50 (3/4): 204-230.
Kreuski, D. and Van Ryzin, J. (1980). Dose response models
for quantal response toxicity data. Research supported by the
National Institute for Environmental Health Sciences under
grants 1R01-ES-02222 and 7R01-ES-02557.
The program documentation is available from the
Technical Contact. All users must have a registered account
on the EPA IBM System and be familiar with the basic system
conventions.
(CNM) contact name(s): Grindstaff,G.F.
(COR) Contact organization: Office of Toxic Substances, Health and
Environmental Review Division (202) 382-3
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.office of Toxic Substances.Health and Environmental
Review Division.
1522
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Accession No. 17301300003
corresponding to time t and additional risk, the expected
fraction of life-shortening by time t from dose d.
(APP) Applications of model: This model is used to estimate lifetime
carcinogenic risks associated with various suspected human
carcinogens. The model is only used, however, when time-to-
occurrence data are available from an animal bioassay. The
estimates of carcinogenic risk are used in risk assessments
supporting regulatory actions under Section 4, 5 and 6 of the Toxic
Substances Control Act. TECHNICAL CONTACT: Gary F. Grindstaff
1523
-------
Accession No. 17301300003 (cont)
OPTS/OTS/HERD/E8. (TS-796) E617B Waterside Mall, 401 H St., S.W.,
Washington, D,C. 20460 382-3459
(HDW) Computational system requireaents - Hardware: Mainframe IBM
370/168 ;Disc storage less than 300K bytes jPr
(LNG) Computational system requirements - Language(s) used: Fortran 6
(OSK) Computational system requirements: Operator Knowledge/Skills: NCC
-IBM user conventions and HYL8UR editing
-------
Accession No. 17301300004
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Mantel-Bryan Low-Dose Extrapolation
Model
(ACR) Acronym of Data Base or Model: MANTELAN
(MED) Media/Subject of Data Base or Model: Toxic Substances
(ABS) Abstract/Overview of Data Base or Model: This computer model is
an implementation of the technique for lou-dose extrapolation
developed by Mantel, Bohidar/ Brown, Ciminera/ and Tukey in a 1975
paper entitled/ "An Improved Mantel-Bryan Procedure for "Safety*
Testing of Carcinogens." (This paper is available from the
Technical Contact).
(CTC) CONTACTS: Gary E. Grindstaff Office of Pesticides and Toxic
Substanc Loc: E617B Waterside Hall (TS-796), 401 M St. S.H.,
Washington, DC 20460 Ph:
(202)382-3459
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 12-23-82
(CAP) Functional capabilities of model: The limitations of this model
are not well known - the documentation is somewhat sparse.
(ASM) Basic assumptions of model: The Mantel-Bryan model is a special
case of the well-known probit model. Mantel-Bryan/ however/
assumes a fixed presumed conservative slope. The methods used to
estimate parameters and to place confidence limits on dose are
explained fully in a number of theoretical background papers
available from the Technical Contact.
(INP) Input to model: Inputs to the model include: The assumed slope
of the dose-response curve (usually 1.0), number of experimental
groups (e.g. males/ females)/ number of dose levels/ number of
confidence limits/ chi-square values for desired confidence limits/
dose levels/ titles of experimental groups/ number of responders
and number at risk for each control and treated group in each
experimental group.
(OUT) Cutput of model: The principal outputs of this model include
lower confidence bounds for dose at specified attributable risks
from 10(-1) to 10(-8). These estimates are presented for all dose
groups first and then for successively smaller dose group
combinations/ eliminating the highest dose on each Iteration.
(APP) Applications of model: This model is used to estimate lifetime
carcinogenic risks associated with various suspected human
carcinogens. The model Is only used/ however/ with dichotomous
data from animal bioassays. The estimates of carcinogenic risk are
used in risk assessments supporting regulatory actions under
Sections 4/ 5 and 6 of the Toxic Substances Control Act. TECHNICAL
CONTACT: Gary F. Grindstaff OTS/HERD. E617B Waterside Mall
(TS-796)/ 401 M St./ S.W. Washington/ D.C. 20460 382-3459
(HDW) Computational system requirements - Hardware: Mainframe IBM
370/168 ;Disc storage less than 300K bytes ;Pr
(LNG) Computational system requirements - Language(s) used: Fortran G
(OSK) Computational system requirements: Operator Knowledge/Skills: NCC
-IBP user conventions and WYLBDR editing
(REF) References - User manuals/ documentation/ etc.:
The program documentation/ "Example of Input to
1525
-------
Accession No. 17301300004 (cent)
Run Mantel-Bryan Program" is available fro» the Technical
Contact. Copies of a number of theoretical papers are
also available froa the Technical Contact. All users must
have a registered account on the EPA IBM Systea and be
familiar with the basic system conventions.
(CNM) Contact name(s): Grindstaff,G.F.
tCOR) Contact organization: Office of Toxic Substances, Health and
Environmental Review Division {202)382-34
-------
Accession No. 17301300005
(DQ) Date of Questionaire: 12-02-82
(NAM) Kane of Data Base of Model: GLOBAL?9 A Fortran Program to
Extrapolate Dichotomous Anlnal Carcinogenicity Data to Lou Doses
CACR) Acronym of Data Base or Model: GLOBAL79
(MED) fcedia/Subject of Data Base or Model: Toxic Substances
(A8S) Abstract/Overview of Data Base or Model: GLOBAL79 is a program
to analyze dichotomous animal carcinogenicity data. It is assumed
that at each dose level/ animals have been exposed to a constant
dose rate of the agent under test and that sove positive responses
have occurred. The program calculates maximum likelihood estimates
of a multistage dose response function. The user may allow the
program to set the degree of the polynomial function to be one
fewer than the number of dose groups, or force the degree of the
polynomial/ or globally maximize the likelihood over polynomials of
arbitrary degree. A likelihood ratio test is then performed on the
polynomial's linear coefficient. Next, lower statistical
confidence limits on dose and upper statistical confidence limits
on risk are calculated for risk levels from 10-1 to 10-8 and for
other dose levels input by the user. Finally, if requested by the
user, the program will conduct a Monte-Carlo goodness-of-fit test
of the model to the experimental data.
(CTC) CONTACTS: Gary F. Grindstaff, Office of Toxic Substances,
Health and Environmental Review Division
Loc: E617B Waterside Mall (TS-796), 401 M St., S.U., Washington,
D.C. 20460 Ph: (202)
382-3459
(STA) Data Base status: Operational/Ongoing
(Dp) Date of form completion: 12-23-82
(CAP) Functional capabilities of model: Limitations of the model: the
number of dose levels must not exceed 19, the number of animals
must not exceed 2000, the number of environmental doses input by
the user must not exceed 50, the number of data sets that may be
analyzed in one run must not exceed 1000.
(ASM) Basic assumptions of model: This is a multistage model, the
parameters of which are estimated by the method of maximum
likelihood. However, the model is mathematically complex, thus
rather than list the assumptions and theory of this model here,
individuals interested in them are referred to the Technical
Contact for copies of theoretical papers underlying the development
of this model.
(IMP) Input to model: Inputs to the model include: the number of dose
levels, goodness of fit option, number of animals at risk at each
dose level, number of animals showing a positive response at each
dose level, magnitude of each dose level, model option (multistage,
forced stage, global optimization), degree of polynomial (for
forced stage option), and number and level of environmental doses
for which risks are to be computed.
(OUT) Cutput of model: The principal outputs of the model are: loner
statistical confidence limits for the doses producing extra risks
from 10(-1) to 10(-8) (virtually safe dose), upper confidence
limits on extra risk for maximum likelihood estimated doses (or
other doses which are input by the user) corresponding to increased
1527
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Accession No. 17301300005 (cont)
risks from 10(-1) to 10(-8).
(APP) Applications of model: This model is used to estimate lifetime
carcinogenic risks associated with various suspected hu»an
carcinogens. The model is only used, however, with dichotomous
data from animal bioassays. The estimates of carcinogenic risk are
used in risk assessments supporting regulatory actions under
Sections 4, 5 and 6 of the Toxic Substances Control Act. TECHNICAL
CONTACT: Gary F. Grindstaff QTS/HERD. E617B Waterside Mall
(TS-796), 401 M St., S.W. Washington, D.C. 20460 382-3459
(HDH) Computational system requirements - Hardware: Mainframe IBM
370/168 ;Disc storage less than 30OK bytes ;Pr
(LNG) Computational system requirements - Language(s) used: FORTRAN 6
(OSK) Computational system requirements: Operator Knowledge/Skills: NCC
-IBM User Conventions and HYL8UR editing
(REF) References - User manuals, documentation., etc.:
The program documentation Is:
GLOBAL79: A Fortran Program for Risk Assessment Using
Dichotomous Animal Carcinogenicity Data by Crump and Watson (1979).
Both this program documentation and a number of theoretical
papers are available from the Technical Contact. All users
must have a registered account on the EPA IBM System and be
familiar with the basic system conventions.
(CNM) Contact name(s): Grindstaff,G.F.
-------
Accession No. 17301300006
(DQ) Date of Questionaire: 12-02-82
(NAM) Kame of Data Base of Model: NRST: Statistical Methodology For
lexicological Research
(ACR) Acronym of Data Base or Model: HARTSIEL
(MED) fcedia/Subject of Data Base or Model: Toxic Substances
(ABS) Abstract/Over view of Data Base or Model: MRST is a program
designed to use both as a powerful research tool and a statistical
analyzer of experimental data from lexicological studies. The
program will provide a statistical analysis of real experimental
data. In addition, the program has the capability of simulating
experimental data. This capability is particularly useful in
evaluating the effectiveness of the risk estimation procedures and
also alternative experimental designs - especially with regard to a
design's number and spacing of dose levels as well as the number of
test animals assigned to each dose level.
(CTC) CONTACTS: Gary F. Grindstaff, Office of Toxic Substances,
Health and Environmental Review Division
Loc: E617B Waterside Mall (TS-796), 401 M St., S.W., Washington,
D.C. 20460 Ph: <202)# 382-3459
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 12-23-82
(CAP) Functional capabilities of model: The limitations of the model
are tied to the input specifications. Given the extent of the
required program input, interested users are referred to the
Technical Contact for the program documentation that will cover
these specifications in detail.
(ASM) Basic assumptions of model: The program is based, to some
extent, on the simulation of time-to-death of an experimental
anirral by a Weibull distribution. However, the theory underlying
this model is quite involved. Interested users are referred to the
Technical Contact for copies of the theoretical papers upon which
this model is based.
(INP) Input to model: The input requirements for this program are
quite large - too many to list here in detail. They include,
however, detailed information from the bioassay, such as individual
animal death times. Interested users are urged to obtain a copy of
the input specifications from the Technical Contact.
(DDT) Output of model: The outputs from this model are too numerous to
list here in any detail. In general, however, estimates of
increased risk and life-shortening are provided. Interested
individuals are urged to obtain a sample output listing from the
Technical contact.
(APP) Applications of model: This model is used in conjunction with a
variety of other models to estimate lifetime carcinogenic risks
associated with various level of suspected human carcinogens.
However, this model is used only when time-to-occurrence dose
response data are available. These estimates are then included in
risk assessments supporting regulatory actions under Sections 4, 5
and 6 of the Toxic Substances Control Act. TECHNICAL COHTACT: Gary
F. Grindstaff OPTS/OTS/HERD/EB. (TS-796.) E617B Waterside Mall, 401
M St., S.W., Washington, D.C. 20406, 382-34
(HDW) Computational system requirements - Hardware: Mainframe IBM
1529
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Accession No. 17301300006 (cont)
370/168 ;Disc storage less than 300K bytes ;Pr
(LNG) Computational system requirements - Language(s) used: Fortran C
(OSK) Computational systen requirements: Operator Knouledge/Skills: MCC
-IBM User conventions
(REF) References - User Manuals, documentation, etc.:
The 1978 program documentation entitled, "Development
of Statistical Methodology for Risk Estimation" by Hartley and
Sielken is available from the Technical Contact. Several
theoretical papers are also available. All users must have a
registered account on the EPA IBM System.
CCNH) Contact name(s): Grindstaff,€.F.
(COR) Contact organization: Office of Toxic Substances, Health and
Environmental Review Division (202) 382-3
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Health and Environmental
Review Division.
1530
-------
Accession No. 17301300007
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: RISK81: A Computer Program for Lou
Dose Extrapolation of Qu
(ACR) Acronym of Data Base or Model: DKREWSKI
(MED) Media/Subject of Data Base or Model: Toxic substances
(ABS) Abstract/Overview of Data Base or Model: This program was
developed for the generation of Ion-dose carcinogenic risk
assessments of toxic substances based on the probit model, logistic
regression (logit) model, Heilbull (extreme-value) model, and
gamma-multihit model. Any or all of these models are applied to
aninal response data derived from lifetime feeding studies.
(CTC) CONTACTS: Gary F. Grindstaff
Loc: USEPA/Office of Toxic Substances/Health and Environmental
Review Division/E617B Waterside Mall/401 M Street, S.W./Washington,
D.C., 20460/(202) 755-6841
(CAP) Functional capabilities of model: Limitations of the model are
twofold. No more than nine input environmental doses for each Job
run can be performed. The second drawback is that the average run
time may very for the same job by as much as +/- 50% depending upon
the options selected.
(ASM) Basic assumptions of model: There are four distinct models in
this program. Each of them are mathematicallly complex, thus,
rather than list assumptions here, individuals interested in the
underlying assumptions are referred to the technical contact for
copies of theoretical papers underlying the development of these
models.
(INP) input to model: The inputs to the models are: title of the data
set; number of dose levels; number of subjects responding at each
dose level; number of subjects tested at each dose level; optional
excess risks over background; optional significance levels for
one-sided lower confidence limit evaluation; environ- mental dose
levels for which added risk over background will be computed; and,
nine additional model electives.
(OUT) Output of model: The principal outputs of the interest from the
model are: estimates of the parameters for any of four models
chosen; point estimates and lower confidence limits on virtually
safe doses for a range of excess risks over background; and, point
estimates and upper confidence limits on added risk for selected
environmental doses.
(APP) Applications of model: The model, in conjunction with a variety
of other models, is used to estimate lifetime carcinogenic risks
assoc- iated with various levels of suspected human carcinogens.
The estimates are then included in risk assessments supporting
regulatory actions under Sections 4, 5, and 6 of the Toxic
Substances Control Act.
(HDH) Computational system requirements - Hardware: Mainframe IBM
370/168 ;Disc storage-less than 300K bytes ;Pr
(LNG) Computational system requirements - Language(s) used: Fortran G
(OSK) Computational system requirements: Operator Knowledge/Skills: Hyl
bur editing ;NCC-IBM User Conventions
(REF) References - User manuals, documentation, etc.:
"Dose Response Models for Quanta1 Response Toxicity
1531
-------
Accession Ho. 17301300007 (cont)
Data11 by John Van Ryzin and Daniel Kreuski, 1980 and "User
Instructions for RISK81: A Computer Program for Loir-Dose Extra-
polation of Quantal Response Toxicity Data, 1981, are the program
documentations. Method of access to the model at the MCC-IBM,
are available from the technical contact. All users must have a
registered account on the EPA IBM System.
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Health and Environmental
Review Division*
1532
-------
Accession No. 17301400906
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: Environmental Partitioning Model
(ACR) Acronym of Data Base or Model: ENPART
(MED) Media/Subject of Data Base or Model: Toxic substances
(ABS) Abstract/Over view of Data Base or Model: This generalized
partitioning model integrates information about a chemical's
production, use, and disposal Mith laboratory data describing its
physiochemical properties in order to provide Insight into the
dominant processes responsible for that substance's transport and
degradation in the environment. It is intended to be used in early
stages of chemical risk assessments to identify environmental media
through which exposure may occur, and to provide a guide for
further assessment by indicating the media with the highest
exposure potential. The methodology explicity treats transfer
between and transformation within environmental media and ranks
media as to their exposure potential, and transformation processes
as to the relative importance in controlling the level of exposure.
The analysis can also be applied in the design of a cost-effective
testing approach to yield data on interrelated transport and
transformation processes which when considered together, present a
clear picture of a substance's environmental fate.
(CTC) CONTACTS: William p. Mood Office of Toxic Substances
Exposure Eva Dlv.
LOG: 401 M St., S.V., Washington, DC 20460 Ph: (202) 426-0724
(STA) Data Base status: Operational/Ongoing
(DP) Date of form completion: 01-26-83
(CAP) Functional capabilities of model: The equilibrium partitioning
segnent of the model combines information on chemical releases and.
intermedia transport processes to determine the partitioning of the
chemical between air, water, soil, sediment, and biota. The dynamic
partitioning segment sums first-order degradation rates to yield
the overall transformation half-life for each medium. This is then
compared with the previously calculated intermedia transfer
half-life to determine if the chemical is degraded before it can be
transfered from the media to which it is released.
(ASM) Basic assumptions of model: The approach used in the equilibrium
partitioning analysis assumes that each media compartment is
homogeneously well mixed, and that all compartments are in
equilibrium. The dynamic partitioning portion of the model assumes
that inter-compartmental transfer is at steady state with
transformation processes such as photolysis, hydrolysis, oxidation,
and biodegradation. The concentration ratios are determined using
fugacity constants describing tendencies to transfer between
compartments which are valid for use at low environmental
concentrations.
(INP) Input to model: The equilibrium partitioning of the model
requires data on the substance's vapor pressure, water solubility,
soil and/or sediment adsorption coefficients, and the octanol/water
partition coefficient, or data for chemical surrogates. The
dynamic partitioning portion requires first order or pseudo first
order rate constants for major chemical transformation processes,
including ozone and hydroxyl radical oxidation, direct photolysis,
1533
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Accession Ho. 17301400906 (cont)
aqueous photolysis, hydrolysis In surface Hater and soil water, and
biodegradation in uater and soil.
(OUT) Output of nodel: The model provides ratios of chemical
concentrations between Media compartments, rather than absolute
concentrations. This allows media to be ranked in order of exposure
potential. The overall environmental persistence of the substance
is calculated based upon the degradation and intermedia transfer
rates.
(APP) Applications of nodel: The environmental partitioning model is
useful in the early stages of chemical risk assessment to identify
environmental media through which exposure may occur.
(HDM) Computational system requirements - Hardware: Mainframe TAX
11/760 ;Disc storage
(LNG) Computational system requirements - LanguageCs) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Bas
ic scientific
(REF) References - User manuals, documentation, etc.:
Chemical Fate Branch Modeling Team, "An Environmental
Partitioning Model (draft),** EPA Office of Toxic Substances,
July 1982.f Mackay, Donald, "Finding fugaclty feasible,
"Environmental
Science and Technology, Vol. 13, No. 10, October 1979, pp.
1218-1223.
(CNM) Contact name(s): Wood,U.P.
(COR) Contact organization: Office of Toxic Substances Exposure
Evaluation Div.
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Exposure Evaluation Division.
1534
-------
Accession No. 17301400907
(DQ) Date of Questionnaire: 12-02-82
(NAM) Name of Data Base of Model: Unified Transport Model - Toxics
(ACR) Acronym of Data Base or Model: UTM - TDX
(MED) Vedia/Subject Of Data Base or Model: Air jToxic substances ;Hater
(ABS) Abstract/Overview of Data Base or Model: The Unified Transport
Model is a multimedia no del which siaulates the movement of a
chemical through an inland watershed. The model calculates the
concentration of organic and inorganic chemicals in air* water*
soil, sediment and biota. The UTM consists of the Atmospheric
Transport Model (ATM) the Wisconsin Hydrologic Transport Model
(WHTM) the Terrestial Ecosystem Hydrology Model (TEHM) and a suite
of associated submodels. The model Has originally developed by Oak
Ridge National Laboratory to simulate trace element transport
through a forested ecosystem. The model was modified by Oak Ridge
in 1980 for the Environmental Protection Agency to incorporate the
transport and transforca- tion processes associated with organic
chemicals.
(CTC) CONTACTS: Davis Mauriello (TS-798) EPA Office Toxic
Substances Exposure Evaluation Division
Loc: 401 M St.* Washington* D.C. 20460 Ph: (202) 426-0724
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-26-83
(CAP) Functional capabilities of model: The model is applicable to
small watersheds consisting of up to 3 land segments and 7 reaches.
The concentration of the chemical in air is determined on a monthly
basis. Movement of the chemical through the terrestrial and
aquatic environment is simulated at 15 minute intervals. The
average monthly and annual concentrations can be calculated with an
accuracy of better than an order of magnitude. The hydrologic
submodel requires calibration.
(ASM) Basic assumptions of model: The chemical (organic or inorganic)
is assumed to be released from point* line or area sources into
air* deposited onto land and subsequently transported to ground
water and surface water. The ATM consists of a steady state
Gaussian algorithm. The terrestrial model is a simulation model.
The ecological submodels are mechanistic in character.
(IMP) Input to model: The input data includes monthly wind roses*
hourly precipitation, solar radiation* daily maximum and minimum
temperatures, soil characteristics* topographic information,
surface water characteristics, sediment characteristics, and the
physiochemical properties and transformation rates associated with
the chemical.
(OUT) Output of model: The output consists of plots and tables
summarizing the average monthly and annual chemical concentrations
in 8 wind sectors* in saturated and unsaturated soil layers* in
runoff* out of each reach* and in the stems, leaves, roots and
fruits of vegetation.
(APP) Applications of model: The model has been used by the
Environmental Sciences Division of Oak Ridge National Laboratory to
study the accumulation of trace metals in the soil and biota of two
forested ecosystems.
(HDW) Computational system requirements - Hardware: Mainframe IBM 370,
1535
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Accession No. 17301400907 (cont)
VAX 11/780 ;Disc storage 540K bytes on IB Printer any 132
characters per line model
(LNG) Computational system requirements - Language(s) used: Fortran IV
extended
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
g ramming
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? NO
(PHP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(HPR) Process used to remove pollutant from atomosphere: Combination
(THE) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: Combination of all sources
(AR) Area where sample was collected: level or gently rolling terrain*
(RNG) Distance traveled by pollutant from source: less than 60 km
(WTP) Water Models - Type of model: Hater run-off
(ENV) Environment(s) to uhich model applies: Stream/river
(CON) Processes and constituents included in model: Toxic chemicals
/Biological effects ;Hydrology
(CPL) complexity level of model: transient mass balance ;one
dimensional
(REP) References - User manuals/ documentation/ etc.:
Culkoiiski/ tf. M./ and Patterson/ M. R. 1976.
A Comprehensive Atmospheric Transport and Diffusion Model.
Oak Ridge national Laboratory Report ORML/NSF/EATC-17.
Patterson/ M. R./ at al. 1974. A User's Manual for the
Fortran IV Version of The Wisconsin Hydrologic Transport
Model. Oak Ridge National Laboratory Report QRNL/NSF/BATC-7.
Huff/ 0. D./ et al. 1977. TEHM: A Terrestrial Ecosystem
Hydrology Model. Oak Ridge National Laboratory Report QRN//
NSF/EATC-27.
(CSM) Contact name(s): Lefler/J.
(COR) Contact organization: EPA Office Toxic Substances Exposure
Evaluation Division
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Exposure Evaluation Division.
1536
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Accession No. 17301400908
(DQ) Date of Questionaire: 12-02-82
(NAM) Mane of Data Base of Model: Seasonal Soil Model
(ACR) Acronym of Data Base or Model: SESOIL
(MED) Media/Subject of Data Base or Model: Toxic substances ;Vater
(ABS) Abstract/Over view of Data Base or Model: The SESOIL model
describes the water transport, sediment transport/ pollutant
trarsport, and soil quality within a user specified soil column
extending between the ground surface and the lower part of the
saturated soil zone of a region. SESOIL is designated as seasonal
because it analytically estimates the pollutant distribution in the
soil column after a season (e.g., one year or six months) directly.
It does not estimate pollution distribution indirectly (i.e., by
summing up pollutant distribution estimates in the soil column
after each major storm event) as existing models in the literature
do. SESOIL is designed to simulate point or non- point pollutants
from major land use categories such as urban areas and is
sufficiently flexible to allow applications to various
climate-soil-vegetational conditions and pollutant types. The
analysis of SESOIL can consider time dependent pollutant inputs to
the soil column. The model simulates three major cycles: the
water cycle, taking into account rainfall, infiltration, surface
runoff, evapotranspiration, groundwater, and optionally snow
pack/melt, and vegetative interception; the sediment cycle, taking
into account sediment resuspension due to wind, and sediment
uashload from rainstorms; and the pollutant cycle which takes into
account volatilization, adsorption/desorption, degradation, and
biological transformation/uptake.
(CTC) CONTACTS: Annett Mold EPA Office Toxic Substances Exposure
Evaluation Div. Loc: 401 M St., S.W., Washington, D.C. 20460
Ph: (202) 426-0724
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-26-83
(CAP) Functional capabilities of model: The model calculates seasonal
pollutant concentration in soil water and water quantity in a soil
column, making it potentially useful in studying leaching from
waste disposal sites and pesticide or other toxic substances
movement on watersheds. Model accuracy has not yet been measured.
(ASM) Basic assumptions of model: The fundamental water balance
equation in the model sets infiltration equal to precipitation
minus surface runoff, which is in turn equal to net
evapotranspiration and groundwater recharge and loss. There is a
fundamental pollutant mass balance equation for both the upper
(unsaturated) and lower (saturated) soil zones, which can be solved
for dissolved and sorbed pollutant concentrations.
(INP) Input to model: In order to avoid difficulties in calibration,
SESCIL uses primarily theoretically derived subroutines based on
physical principles, there by limiting input data requirements.
Model parameters can be determined independently either from
laboratory experiments or from past field measurements. SESOIL
requires continuous (time dependent) inputs for various parameters
(e.g., rainfall, evapotranspiration) for a specific timestep. The
model accepts input from the atmospheric regime as well as from
1537
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Accession No. 17301400908 (cont)
point and non-point sources of pollutant discharges.
(OUT) Output of aodel: Separate concentration estimates for pollutants
are calculated for the upper and loner soil zones.
(APP) Applications of model: The SESQIL model has not yet been applied
and is still under development under the direction of the Exposure
Evaluation Division, EPA Office of Toxic Substances. A computerized
version is operational.
A version suitable for solving with a programmable
calculator is described in the reference. TECHNICAL COMTACT: Annett
Hold Exposure Evaluation Division
-------
Accession No. 17407000505
-d) Date of Questionaire: 12-02-82
(RAM) Name of Data Base of Model: TOX-SCRSEN
(ACR) Acronym of Data Base or Model: TOX-SCREEN
(MED) Media/Subject of Data Base or Model: Air; Toxic Substances;
Hater; Soil
(ABS) Abstract/Overview of Data Base or Model: TOX-SCREEN is a
multimedia screening-level model for assessing the potential fate
of chemicals released to the environment. It is intended to be used
in the early stages of chemical risk assessments to provide a means
of rapidly evaluating chemicals with respect to their human and
environmental exposure potential; by design, it is overpredictive
(conservative) in nature. Chemical concentrations in air, surface
water, and soil reflect both direct input to an or all of the media
fro*, a specified source(s), and subsequent interaction via
processes such as volatilization, atmospheric deposition, and
surface runoff. The user selects the types of water bodies (i.e.,
river, lake, estuary, ocean) to be considered in any given
simulation and specifies if the chemical is directly released to
air or water, and/or directly applied to soil.
(CTC) CONTACTS: Russell Kinerson USEPA/OTS/EED (TS-798) LOC: 401 M
St., S.H., Washington, D.C. 20460 PH: (202) 382-3929
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-07-83
(CAP) Functional capabilities of model: The multimedia nature of
TOX-SCREEN requires that physical/chemical processes which drive
trarsport of chemicals air-water, air-soil, and soil-water
interfaces be simulated. Such media interactions are handeled
explicitly in the model. The generic nature of the model
necessitated specification of the relative locations of media
interfaces. Contaminated soil areas are always adjacent to water
bodies. Hater bodies are assumed to intercept the plume
immediately downwind of the point of maximum concentration if an
atmospheric point source is present.
(ASM) Basic assumptions of model; Downwind, ground-level chemical
concentrations in the air are estimated for point sources and area
sources. The assumption of a constant wind direction throughout
the model time application period incorporates conservatism in the
overall estimate. An equation similar to the USEPA EXAMS model
equation is used to estimate monthly chemical mass in each reach of
river and in lakes. A steady-state Gaussion-type linear diffusion
model is used to estimate dispersion of chemicals discharged to
ocean constant waters. Dispersion in soil is handled by the Level3
SESOIL model.
(INP) Input to model: The data input includes monthly mean rules of
temperature, relative humidity, and cloud cover albedo,
evaportranspirations, storm duration, storm frequency,
precipitation, wind speed, soil properties, chemical
characteristics, descriptors for the simulated equative
environments, and the transformation rates associated with the
chemical.
(OUT) Cutput of model: The output consists of tables summarizing the
average monthly chemical concentrations in air, unsaturated soil
1539
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Accession No. 17407000505 (cont)
layers, in runoff, in each reach of the river, stream, or estuary,
and in the lakes and ocean.
(APP) Applications of model: The model has been used by the Office of
Toxic Substances to evaluate the upper levels of cheaical that
might be expected in each environment.
(HDU) Computational system requirements - Hardware: Mainframe VAX
11/780 ; PDP-10
(LUG) Computational system requirements - Language(s) used: FORTRAN
(ATP) Air Models - Type of model: Gaussian Dispersion
(OAQ) Model reviewed and approved by OAQPS? No
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into the atmosphere)
(NPR) Process used to remove pollutant from atomosphere: Chemical-physi
cal combination (with neither process dominant)
(THE) Sample averaging time used: More than 24 hours
(SRC) source of pollutant: Combination of 1-4, point or area sources
may be used
(AR) Area where sample was collected: Simple (area with level or
gently rolling terrain)
(HTP) Water Models - Type of model: Mater run-off/Loading
(ENV) Environment(s) to which model applies: Estuary; Lake;
Stream/River; Marine
(CON) Processes and constituents included in model: Erosion and
Sediment; Toxic Chemicals; Temperature; Hydrology
(CPL) Complexity level of model: Steady State Mass Balance;
One-Dimensional
(REF) References - User manuals, documentation, etc.: McDowell-Boyer
L.M., Hetrick, O.M., 1982. A Multimedia Screening-Level Model for
Assessing the Potential Fate of Chemical Released to the
Environment. ORNL/TM-8334. Oak Ridge National Laboratory; Oak
Ridge, TN TOX-SCREEN User's Guide - DRAFT
(CUM) Contact name(s): Russell Kinerson
(COR) Contact organization: USEPA/OTS/EED (TS-798)
(ROR) Responsible Organization: Office of Pesticides and Toxic
Substances.Office of Toxic Substances.Exposure Evaluation Division.
1540
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Accession No. 18313000510
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: Hydrologic Simulation on Solid Haste
Disposal Sites
(ACR) Acronym of Data Base or Model: HSSWDS
(MED) Media/Subject of Data Base or Model: Hazardous Waste
(ABS) Abstract/Over view of Data Base or Model: The Hydrologic
Simulation on Solid Waste Disposal Disposal Sites (HSSWDS) Model
was developed to help landfill designers and evaluators estimate
the amount of moisture percolation through different types of
landfill covers. This one-dimensional/ deterministic/
computer-based water budget model was developed and adapted froa
the U.S. Department of Agriculture CREAMS Hydrologic model and uses
the Soil Conservation Service curve number method for calculating
runoff. The model takes engineering, hydrologic/ and climatologic
input data in the form of rainfall/ average temperatures, average
solar radiation/ leaf area indices and characteristics of cover
materials/ and performs a sequential analysis to derive a water
budget including runoff/ percolation/ and evapotranspiratlon*
(CTC) CONTACTS: Douglas C. Ammon Solid & Hazardous Waste Research
Div/MERL LOG: 26 West St. Clair Street, Cincinnati, OH 45268
PH: (513) 684-7871
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-18-83
(CAP) Functional capabilities of model: The model's function is to
help landfill designers and permit officials estimate the amount of
moisture percolation through different types of landfill covers.
Being one-dimensional (in the vertical direction)/ the model does
not account for lateral inflow or drainage, the time step is one
day with simulation capabilities of up to 20 years. From minimal
input data the model will simulate daily/ monthly/ and annual
values for runoff/ percolation/ temperature/ soil-water/ and
evapotranspiration.
(ASM) Basic assumptions of model: The HSSWDS model is a deterministic/
one- dimensional model that develops a long-term water balance
based on historical or simulated daily rainfall records.
Infiltration of moisture through the soil surface is calculated
using the SCS curve number technique. The SCS curve number
technique relates runoff to soil type/ land use/ and management
practices and uses daily rainfall records. The actual rainfall
intensity/ duration/ and distribution are not cons*1ered. Average
daily temperatures/ average daily solar radiations and average
leaf area indices are used to estimate water loss >v evaporation or
transpiration using modified Penman method. The moc^l is not more
complex than a manual tabulation of moisture balance but HSSWDS
makes available a more complete data base and a state-of-the-art
system for obtaining an accurate water budget over a wide variety
of climatic, soil/ and vegetative conditions.
(INP) Input to model: The model is ordinarily used in the
conversational mode/ which enables the user to interact directly
with the program. Five year of climatical default data are on files
accessible to the user for over 104 locations. Logical values for
soil properties are provided as default values. The user specifies
1541
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Accession 80. 18313000510 (cont)
the design of the cover. If the user's overrides the default
values, the input requirement can become very intensive especially
for cliraatical data.
(OUT) Output of model: The model output are daily, monthly, and annual
values for runoff, percolation, temperature, soil-water, and
evapotranspiration for up to 20 years of simulation. Output is in
tabular form. In the conversational model the output is received
immediately through a terminal display.
(APP) Applications of model: The model is intended to assist permit
officials in evaluating the adequacy of a hazardous waste or
municipal solid waste landfill cover design. Landfill designer can
alsc apply the model to assist their engineering design efforts.
-------
Accession No. 18411000508
(DQ) Date of Questionaire: 12-02-82
(NAN) Name of Data Base of Model: Eastern North American Model of Air
Pollution
(ACR) Acronyra of Data Base or Model: ENAMAP-1
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The ENAMAP-1 model
(developed by SRI, International) is a one-layer long-range
transport model capable of estimating monthly, seasonal, and annual
concentrations and net and dry depositions of two
chemically-dependent pollutants across a 46 by 41 grid of eastern
North America (east of 105 degrees West longitude and in between 29
degrees and 54 degrees North latitude). In addition, the
individual contributions of emissions from x source regions on the
concentrations or depositions over y receptor regions are
determined. Puffs of both pollutants are released from 70-km grid
cells every 12 hours of simulation time. The puffs are advected
using 12-hourly wind fields which is generated by integrating and
grinding the observed rawinsonde uind between the surface and top
of the constant nixing height (1150 m in winter, 1300 m in
spring/suturnn, and 1450 n in summer). Diffusion is treated as being
Fickian (*tl/2) in the horizontal and instantaneous and uniform in
the vertical up to the mixing height. Dry deposition is a function
of land-use, season, and atmospheric stability. Wet deposition is
function of precipitation rate. A chemical transformation rtate of
1%/tr is assumed. Concentration and deposition across the 70-km
grid cells are determined at 3-hourly time steps.
(CTC) CONTACTS: Terry L. Clark ORD, ESRL, MD, AMB LOC: Research
Triangle Park, NC 27711 PH: (FTS) 629-3372
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-28-83
(CAP) Functional capabilities of model: In its present form, the model
should not be applied to time periods of less than a month, because
of the assumptions and limitations of the model (e.g., constant
mixing height, instantaneous and uniform mixing in the vertical,
and 12-hourly wind fields). Monthly, seasonal, and annual wet and
dry depositions (mg/m2 or kg/ha) and concentrations (ug/m3) of the
two pollutants are estimated for each of the 1886, 70-km grid
cells. Model results of monthly-averaged S02 and S04=
concentrations for a month in each season of 1975 through 1978 have
been compared with observations. Regional patterns determined by
the model compared quite favorably with the observed patterns. The
maximum estimated monthly concentrations across the domain for each
month were within 40% of the maximum observed monthly
concentrations.
(ASM) Basic assumptions of model: The model assumes 1) a constant
mixing height over the entire simulation month with a seasonal
variation of 1150 to 1450 mj 2) instantaneous and uniform mixing in
the vertical below the mixing height and no flux across the top of
the mixed layer; 3) a constant horizontal diffusion rate of 36
km2/hr; 4) a constant transformation rate of 1%/hr; 5) a constant
emission rate for each emission grid cell; and 6) a constant
precipitation rate over a period when precipitation was reported.
1543
-------
Accession Ho. 18411000508 (cont)
The dry deposition velocity of S02 ranges between 0.00 and 0.47
en/sec, while that of S04= ranges between 0.00 and 0.50 cm/sec.
Wet deposition of S02 and S04= (%/hr) are estimated by 0.28R and
0.07R, where R is the rate of liquid precipitation (sra/hr).
-------
Accession No. 18411000508 (cont)
Wolf, K. C. Nitz, and M. B. Johnson Atmospheric Science Center, SRI
International
(CNH) Contact narae(s): Terry L. Clark
(COR) Contact organization: ORD, ESPL, MD, AMB
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Sciences Research Laboratory.
1545
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Accession Ho. 18413000502
(DQ) Date of Questionaire: 12*02-82
(NAM) Name of Data Base of Model: Mater Quality Analysis Simulation
Program
(ACR) Acronym of Data Base or Model: HASP
(MED) Media/Subject of Data Base or Model: Hater
(ABS) Abstract/Overview of Data Base or Model: HASP is a generalized
modeling program for simulating the water quality of aquatic
systems* Based on the flexible conpartment modeling approach/ HASP
may be applied in one- two- , or three-dimensional configurations*
A variety of water quality problems can be addressed with the
selection of appropriate kinetic subroutines. Time-varying
transport processes/ including forcing and boundary processes/
advection/ dispersion/ and mass loading/ are represented in this
program. Water quality processes are represented in special
kinetic subroutines that are either chosen from a library or
written by the user. WASP is structured to permit easy
substitution of kinetic subroutines into the overall package to
form a particular model. User-defined constants/
spartially-variable parameters/ and time functions are input
through HASP to drive the kinetic subroutines. Problems simulated
with HASP include dissolved oxygen-BOD dynamics/ nutrients and
eutrophication/ bacterial pollution/ and toxic chemical transport
and fate.
(CTC) CONTACTS: Robert B. Ambrose/ Jr./ U.S. EPA/ Athens Env. Res.
Lab./ LOG: Athens/ GA 30613 Ph: (404) 546-3546
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 01-25-83
(CAP) Functional capabilities of model: HASP is a dynamic compartment
modeling program. Linked with various kinetic subroutines/ from 1
to 19 state variables have been simulated. Segments can be
configurated into one-/ two-/ or three-dimensional networks that
include the water coinin and bed. Concentrations are calculated
explicitely every time step for every segment. The time step
varies at the user's discretion/ generally between an hour and a
day. With the specification of appropriate driving functions and
parameters/ divrnal to seasonal variations can be simulated.
English units are used in the model/ but scale factors provided
allow all input data to be specified in SI (or other) units.
Accuracy is usually limited by scientific knowledge and precision
of input data/ and thus varies with application. HASP is
practically limited to those cases where the transport field can be
specified/ either from direct measurement or from other
hydrodynamic models.
(ASM) Basic assumptions of model: HASP is based on the conservation of
mass principle/ along with the following assumptions: all segments
are well mixed; the transport field can be adequately specified;
and the total derivative/ at a point can be solved as the sum of
the derivatives due to transport, mass addition/ and kinetic
processes. Reaction rates can vary over several orders of
magnitude/ from 0 to approximately 5 per day. An explicit/ finite
difference solution methodology is used.
(IHP) Input to model: To set up and run/ the following data are
1546
-------
Accession No. 18413000502 (cont)
needed: network divided into segments with length/ depth/ cross-
sectional area/ volume; dispersion coefficients; advective flows;
boundary concentrations; input loads; spatially-variable parameters
defined by the particular kinetic subroutine used; various
constants and time functions defined by the kinetic subroutine; and
initial concentration. To calibrate and verify the model/ the
above data are needed/ as well as measured concentrations
throughout the water body at different times.
(DOT) Cutput of model: Echo of input data. Table of output variables
at regular intervals. Time plot of output variables at selected
locations. Spatial plot of output variables at selected tines*
Statistical analysis and comparison with observed data using the
Model Verfication Program. Milwaukee River; and toxic substances
in the Hudson River and Great Lakes. The SPA Large Lakes Research
Station/ who funded the later development of HASP/ has applied it
to eutrophication problems in the Great Lakes and PCB problems in
saginaw Bay. The Athens Environmental Research Laboratory/ which
now supports WASP, has applied it to eutrophication problems in
subestuaries of Chesapeake Bay/ and has developed a compatible
toxic chemical kinetic subroutine based on EXAMS (see TOXIWASP). In
addition, linkage to the hydraulic file generated by the Storm
water Management Model (RECEIV block/ program SWFLOW) has been
accomplished.
(APP) Applications of model: Different versions of HASP have been
applied to many water resource management problms. Most of these
have been by the developers/ Hydroscience and Manhattan College:
eutrophication of San Francisco Bay/ the Great Lakes (Ontario/
Rochester Bay/ Erie/ Huron/ Saginaw Bay/ Michigan)/ the Potomac
Estuary, Chesapeake Bay/ and upper Mississippi; dissolved oxygen
budget of upper Delaware/ New York Harbor, and
(HDW) Computational system requirements - Hardware: Mainframe POP
11-70; IBM 370; Disc Storage 32K; Printer Standard
(LNG) Computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Con
puter Programming; Engineering
(WTP) hater Models - Type of model: Water Quality/Receiving Water
(ENV) Environment(s) to which model applies: Estuary; Lake;
Stream/River; Marine
(CON) Processes and constituents included in model: Dissolved Oxygen;
Eutrophication/Nutrients; Erosion and Sediment; Toxic Chemicals;
Salinity; Temperature; Quality Processes
(CPL) Complexity level of model: Transient Mass Balance;
Multi-Dimensional
(REF) References - User manuals/ documentation/ etc.: DiToro/ D. M./
J. J. Fitzpatrick, and R. V. Thoraann. 1982. Water Quality
Analysis Simulation Program (WASP) and Model Verification Program
(MVP) - Documentation. Hydroscience/ Inc./ Westwood/ NY/ for U.S.
Environmental Protection Agency/ Duluth/ MN/ Contract No.
68-01-3872.
(CNM) Contact naaie(s): Robert B. Ambrose/ Jr.
(COR) Contact organization: U.S. EPA/ Athens Env. Res. Lab.
(RQR) Responsible Organization: Office of Research and
1547
-------
Accession No. 18413000502 (cent)
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1548
-------
Accession No. 18413000503
(OQ) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: WASP Chemical Transport and Fate
Model
(ACR) Acronym of Data Base or Model: TOXIWASP
(MED) Media/Subject of Data Base or Model: Toxic Substances; Water
-------
Accession No. 18413000503 (cont)
variations in the chemical reaction rate. Accuracy is limited by
scientific knowledge and precision of input data, and varies with
application.
(ASM) Basic assumptions of lodel: TOXIhASP is based on the folloving
assumptions: all segments are well fixed; sorption is essentially
instantaneous within each segment (thus local equilibrium);
checical properties of the compound can be coupled uith pertinent
environmental characteristics to formulate a pseudo-first-order
rate for each of the degradation processes; and these process rates
combine linearly to form a total degradation rate for the chemical
in each segment. Reaction ratey can vary over several orders of
magnitude/ from 0 to approximately 5 per day. An explicit/ finite
difference solution methodology is used.
(IHP) Input to model: To set up and run, the following data are
needed: network divided into segments with length, depth,
cross-sectional area, volume; dispersion coefficients; advective
flow; boundary concentrations; input loads; spatially variable
environmental parameters, such as temperature, water velocity, wind
speed, bacterial concentrations, pH, pOH, light extinction
coefficients, concentration of oxidants, density and organic
content of sedimenty, setting velocity, sediment -water dispersion
rates, and target biomass concentration; various chemical
constants, including second-order rate constants for hydrolysis,
oxidation, and bacterial degradation, Henry's low constant or
measured volatilization rates, photolysis rate, and practition
coefficient; seasonal variability of various environmental
parameters, including temperature, wind speed, pH, pOU, and light
intensity; and finally, initial concentrations of chemical and
sediment. Not all of the data are needed for every application.
Measured degradation rates, for example, can be used instead of
•ost of the environmental parameters and chemical constants. To
calibrate and verify the model, the above data are needed, as well
as measured chemical and sediment concentrations throughout the
water body at different seasons.
(OUT) Cutput of model: Echo of input data. Table of output variables
at selected locations. Spatial plot of output variables at
selected times. Descriptive statistics and cumulative frequency
table of out put variables at selected location. Peak event table
of state variables when concentrations exceed specified level.
(APP) Applications of model: As of January 1963, TGXIHASP has been
applied by the authors to the upper Yazoo River, and successfully
tested against predictions by HSPF and EXAMS for three of its
canonical environments: pond, river, oligotrophic lake. The
following linkages are available: TQXIMASP can read nonpoint source
loading files generated by HSPF and SHRV; TOXIUASP can read and
interpolate flows in a reach between tow USGS gages; and TOXIHASP
can read the hydraulic file generated by the Stormwater Management
Model, (RECEIV block, program SWFLOH).
(HOtf) Computational system requirements - Hardware: Maniframe POP
11-70, IBM 370 ; Disc Storage 32K ; Printer Standard
(LUG) Computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
1550
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Accession No. 18413000503 (cont)
ineering
(MTP) Kater Models - Type of model: Mater
CEKV) Environment(s) to which aodel applies: Estuary ? Lake >
Stream/River } Marine
(COM) Processes and constituents included in model: Toxic Chemicals ;
Quality Processes
(CPL) Complexity level of model: Transient Mass Balance >
Multi-Dimensional
(RSF) References - User manuals, documentation, etc.: "Users Manual
for the Chemical Transport and Fate Model (TOXIWASP), Version 1,"
by Robert B. Ambrose, Jr., Sam I. Hill, and Lee A. MulJcey, U.S.
EPA, Athens, GA, sent to printer in January, 1983.# "Water Quality
Analysis Simulation Program (WASP) and Model Verification Program
(MVP) - Documentation," by D. M. Ditoro, J. J. Fitzpatrick, and R.
V. Thomann, Hydroscience, Inc, Vestuood, NJ, for U.S. TA, Duluth,
MN, sent to NTIS in September, 1982.
(CNM) Contact narae(s): Robert B. Ambrose, Jr.
(COR) Contact organization: U.S. EPA, Athens Environmental Res. Lab.
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1551
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Accession No. 18413000504
(OQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Metals Exposure Analysis Modeling
System
(ACR) Acronym of Data Base or Model: MEXAMS
(MED) Media/Subject of Data Base or Model: Toxic Substances ; Hater
(ABS) Abstract/Overview of Data Base or Model: MEXAMS, the Metals
Exposure Analysis Modeling System/ provides a capability for
assessing the impact of priority pollutant metals on aquatic
systems. It considers both the complex chemistry that affects the
behavior of netals and the transport pro cesses that affect their
migration and fate. This is accomplished by linking MINTEQ, a
geochemical model, with EXAMS, an aquatic exposure assessment
model.# MINTEQ is a therraodynamic equilibrium model that computes
aqueous speciation, adsorption and precipitation/dissolution of
solid phases. It has a Hell-documented thermodynamic data base that
currently contains equilibrium constants and other accessary data
for the following priority pollutant metals arsenic, cadmium,
copper/ lead/ nickel, silver and zinc. Data on other metals Mill
be added in the future. The model was developed by combining the
best features of two other existing geochemical models: MIMEQL and
HATFQ3.& EXAMS is an aquatic exposure assessment model designed
for the rapid evaluation of synthetic organic pollutants. Given
the characteristics of a pollutant and an aquatic system, EXAMS
computes steady-state pollutant concentrations (exposure), the
distribution of the pollutant in the system (fate), and the time
required for effective purification of the system (persistence).
Its linkage to MINTEQ required several modifications,# To
facilitate the use of HEXAMS, a user interactive program uas
developed. This program controls the operation of MINTEQ and
EXAPS, passes simulation results back-and-forth between the models,
and queries the user to obtain water quality data for input to
HINfEQ.tf As it is currently structured, MEXAMS can be used in a
number of ways. It can be used like EXAMS to perform rapid hazard
evaluations for priority pollutant metals. The system can also be
used to support the interpretation of metals bioassay data.
Finally, and perhaps most importantly, MEXAMS can be used as a
fraiteuork for defining what is and what is not known about the
behavior of priority pollutant metals in aquatic systems. This
framework will make it possible to identify the need for and guide
the performance of future research.
(STA) Data Base status: Operational/Ongoing
(OF) Date of form completion: 02-05-83
(CAP) Functional capabilities of model: MEXAMS is a steady-state
compartment raodd that calculates the distribution of a metal
throughout an aquatic system, including its aqueous speciation,
adsorption, and precipitation or dissolution. Segments can be
configured into one-, two-, or three- dimensional networks that
include surface and subsurface water and bed. MEXAMS calculates
aetel migration using the mass conservation principle. Speciation
Is calculated using an equilibrium constant approach wherein a
series of mass action expressions are solved subject to mass
balance constraints on each chemical component. Adsorption is
1552
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Accession No. 18413000504 (cent)
treated s being analogous to aqueous speciation, with six
algorithms available: an activity partition coefficient, an
"activity" Langmuir isotherm, an "activity" Frundlich isotherm, an
ion exchange activity ratio, the constant capacitance model, and
the triple layer model. Dissolution of solid metal or
precipitation to the solid phase Is calculated for equilibrium
conditions.£ The user of MEXAMS must be aware of its limitations.
First, simulations are United to those metals with measured
equilibrium constants an accessary data in the thermodynamic data
base: As, Cd, Cu, Pb, Ni, Ag, and Zn. Other metals nil! be added
as funds permit. Second, although MEXAMS contains default values
for fulvic and huaic acids its data base for organic complexation
is limited. For sites where this is important, local data should
be gathered and used. Third, although the kinetics of
precipitation/dissolution, extidation/ reduction, and adsorption
may be important, MEXAMS calculates equilibrium values only.
(ASM) Basic assumptions of nodel: MEXAMS is based on the following
assumptions: all segments are well mixed? environmental conditions
and loadings are at steady state; speciation, adsorption, and
precipitation/ dissolution reactions are at equilibrium, and can be
described by a set of mass action expressions.
(INP) Input to model: To set up and run MEXAMS, two data files are
needed: one for EXAMS and another for MINTEQ. EXAMS calculates the
distribution of a metal throughout the aquatic system based on the
following input data: loadings for each sector; system geometry and
hydrology, including volumes, areas, depths, rainfall, evaporation
rates, tributary and nonpoint source inflows and sediment loads,
and groundwater flows; advective flows; and dispersion
coefficients. MINTEQ calculates the speciation of a metal based on
two types of data:f 1) thermodynamic data and 2) water quality
data. The thermodynamic data are equilibrium constants, heats of
reaction and other basic information required to predict the
formation of each species or solid phase. The water quality data
are the physical and chemical properties of the water body being
analyzed. The user only has to generate the water quality data in
order to use MINTEQ. The thermodynamic data are contained in a
data base that accompanies the nodel. This data base is constantly
being updated and expanded as new or improved data become
available.# Presently, 55 chemical components can be considered
by MINTEQ. While accuracy is generally improved with more water
chemistry data, the user does not have to specify all components.
Many do not react with other components, or are present only in
very low concentrations. The following data are important: pH (most
important). Eh or pE (for elements affected by redox reactions such
as Fe, Mn, Cu, As, U, and V), temperature, ionic strenght
(optional, computed internally), major anions (most important are
carborate and sulfate), and major cations (most important are
calcium and magnesium). Other trace constituents may be important:
hydrogen sulfide, orthophosphorus, fluoride, iron and manganese,
aluminum, barium, and strontium.
(OUT) Output of model: MEXAMS provides the user with two sets of
simulation results: 1) details on metal speciation, sorption and
1553
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Accession Ho. 18413000504 (cont)
precipitation in each compartment and 2) exposure/ fate and
persistence predictions for the aquatic system. The first set of
results are provided by MINTEQ; the second set is provided by
EXAMS. The EXAMS users manual and documentation report provides a
detailed description of the EXAMS output. The only change is the
addition of the quantity of precipitated netal to the tables that
sunn arize model results. MINTEQ output is composed of € sections:
1. original sample description/ 2. thermodynaaic and accessory data
for species/ 3. initial charge balance information/ 4. convergence
pattern for first component/ 5. values for all specie types and a
percentage distribution of components/ and 6. the final charge
balance following aqueous speciation.
(APP) Applications of model: Although MINTEQ and EXAMS have been
tested on a number of problems/ the linked MEXAMS has undergone
internal testing only (as of spring/ 1983).
(HOW) Computational system requirements - Hardware: Disc Storage 32K
(LUG) Computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
Ineering
(VTP) Water Models - Type of model: Hater Quality/Receiving Hater
(ENV) Environment(s) to which model applies: Lake / Stream/River >
Wetlands
(CON) Processes and constituents included in model: Toxic Chemicals ;
Quality Processes
(CPL) Complexity level of model: Steady State Mass Balance ;
Multi-Dimensional
(REF) References - User manuals/ documentation/ etc.: Felmy/ A. R./
Broun/ S. M., Qnishi, ¥./ Argo/ R. S., Yabusaki/ S. B./ "MEXAMS *
The Metals Exposure Analysis Modeling System/* Battelle PNL/
Rlchland, HA/ for U.S. EPA, Athens/ GA, 1983, in press.t Felmy/ A.
R./ Jenne/ E. A./ Girvin/ D. C./ "MINTEQ - A Computer Program for
Calculating Aqueous Geochemical Equilibria/" Battelle PNL/
Rlchland/ HA/ for U.S. EPA/ Athens/ GA/ 1983, in press.
(CMM) Contact name(s): Robert B. Ambrose/ Jr.
(COR) Contact organization: U.S. EPA/ Athens Env. Res. Lab.
(ROR) Responsible Organization: Office of Research and
Development.Office of Environmental Processes and Effects
Research.Environmental Research Laboratory.
1554
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Accession No. 13417000506
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Water Analysis Assimilation for
Toxic Chemicals
(ACR) Acronym of Data Base or Model: MASTOX
(MED) Media/subject of Data Base or Model: Toxic Substances; Water
(ABS) Abstract/Overview of Data Base or Model: HASTQX is a
batch-oriented computer program which solves the mass balance
equations that define the fate of toxic chenicals in aquatic
systems. The model provides tiae variable solutions to these
questions and will eventually handle steady state solutions. The
•ass balance equation for a specified volume describes the mass
rate of change of the chemical due to the net effects of various
fluxes and transformations. The purposes of the modeling framework
are twofold: the first relates to the general hazard allocation
procedures. Such analyses may usually be accomplished by means of
the spatial steady state distributions. The second general purpose
relates to the time/variable aspects of the problem. Such analyses
apply to the effects of a short-term release of a toxicant/ such as
an accidental spill or a storm overflow discharge, in equally
important application in this regard is directed to the time
required to build up to steady state and, perhaps more
significantly, the time required to cleanse a system from existing
contamination.
(CTC) CONTACTS: John P. Connolly Manhattan College LOC: Bronx, NY
10471 PH: (212) 920-0780
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-14-82
(CAP) Functional capabilities of model: The framework is general in
nature. The "study" water system may be sectioned or segmented as
the user chooses. Transport is defined by dispersion coefficients
and flows that are specified in a series of fields that are
individually applied to either both the particulate and dissolved
chemical (e.g., hydrodynamic flow), the particulate chemical only
(e.g., res us pension), or the dissolved chemical only (e.g.,
interstitial water diffusion). The kinetic subroutine returns to
the main program that portion of the time derivative (dc/dt)
contributed by the transfer and reaction components* Changes say
be cade by adding desired terms. The variables that define a
specific kinetic process are transmitted to the kinetic subroutine
through a segment dependent array or parameters and an array of
constants. They may be altered by the user through respecfication
of the equivalence statements.
(ASM) Basic assumptions of model: The model assumes that an aquatic
ecosystem can be sectioned into a series of completely mixed
sections. The approach used is to approximate the spatial
derivatives that define the transport component of the mass balance
equation. The size of the completely mixed sections is controlled
by the time step constraints imposed by the stability limitations
of the numerical schemes and the extent of spatial resolution
desired.
(IMP) Input to model: Inputs to the model include: exchange
coefficients, segment volumes, flows, boundary conditions, forcing
1555
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Accession No. 18417000506 (cont)
functions/ sediment depth/ depth of sediment surface/ sediment
segment area/ pH of segment/ temperature of segnent/ concentration
of compound degrading bacteria/ rate constants for fate processes/
photolysis parameters/ and initial conditions.
(OUT) Output of model: Model provides toxicant concentration profiles
in time and space for estuaries/ streams and other aquatic systems.
It will give both disolved and particulate concentrations and
concentration with depth in sediment.
UPP) Applications of model: The model can be used to predict exposure
concentrations of toxic substances in estuaries/ rivers and other
aquatic systems for both water column and sediment. Future sub
routines will include steady state analysis/ food chain
bioaccumulation and a toxicity model. Kinetic subroutines have
beer developed to provide the user with the capability to alter the
transfer and reaction formulations or to add additional kinetic
processes.
(HDW) computational system requirements - Hardware: Mainframe PUP
1170; Disc Storage 25/000 Word Core Storage; Printer 132 Position
Line Printer »nn»n*u
(LNG) Computational system requirements - Language(s) used? FOKTKMI
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
(WTP) Water Models - Type of model: hater Quality/Receiving Water;
Exposure Assessment Model
(ENV) Environment
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Accession No. 19014000901
(DQ) Date of Questionaire: 12-02-82
-------
Accession No. 19014000901 (cont)
(COR) Contact organization: U.S, EPA Region I
(ROR) Responsible Organization: Region I.Adninistrative Services
Division.
1558
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Accession No. 19024000001
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Mater Quality Feedback Model
(ACR) Acronym of Data Base or Model: FEDBAK03
(MED) Bedia/Subject of Data Base or Model: Mater
(ABS) Abstract/Overview of Data Base or Model: FEDBAK03 is used to
compute the steady-state distribution of water quality variables
undergoing consecutive reactions with feedback and following first
order kinetics. The program has been developed in a general forn
but is specifically applicable to the reactions observed by
nitrogenous species and the associated dissolved oxygen uptake in
the natural environment. The basis for this nodel is the theory of
conservation of aass. The approach used to solve the equations is
a finite difference scheme developed by Thonann, which has been
shown to be a very effective tool in the field of water quality
management.
(CTC) CONTACTS: George A. liossa and Ton O'Hare U.S. EPA,
Information Systems Branch
Loc: 26 Federal Plaza, New York, NY 10278 Ph: (212) 264-9850
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion? 02-24-83
(CAP) Functional capabilities of BOdel: FEDBAK03 has been developed to
help predict water quality parameters which react under first order
kinetics and as a system of consecutive reactions, where any
parameter can react in a feedback fashion. The problem setting
assumes an aquatic environment in which steady-state conditions can
be applied. The Thomann solution of solving the general estuarine
advection/dispersion equation by replacing the derivatives with
finite-difference approximations is the approach followed in
FEDEAK03. Optionally, the program can also perform system
sensitivity analysis by varying the waste vector and re-multiplying
by (01) and/or changing the reaction rate constants for any
reactants and repeating several steps. A second option is the
comfutation of dissolved oxygen deficit and the corresponding
dissolved oxygen concentration by selecting the reaction schemes
producing the deficit and the associates tochioaetric coefficients.
As presently written, the program can accoaodate a multi-
dimensional system of up to 60 sections and each section can have a
maximum of six interfaces. The maximum number of reactants Is such
that when multiplied by the number of sections, it cannot exceed
120. This present limitation can easily be expanded.
(ASM) Basic assumptions of model: The model assumes steady-state
conditions in an aquatic environment. It is based on the theory of
conservation of mass and utilizes a finite difference scheme for
the solution of the general estuarine advection/dispersion
equation. Reactants are assumed to undergo consecutive reactions
with feedback and first order kinetics.
(IMP) Input to model: FEDBAK03 requires the input of the physical
characteristics of the system to be evaluated; namely, the
geometry, temperature, hydrologic characteristics, reaction
schemes, and corresponding reaction rates*
(OUT) Output of model: FEDBAK03 produces the calculation of BOD
dificit and nitrification.
1559
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Accession No. 19024000001 (cont)
(APP) Applications of model: FEOBAK03 can be used for the calculation
of BOD deficit and nitrification. TECHNICAL CONTACT: George A.
Nossa and Ton O'hare Environmental Systems Section Information
Systems Branch 2PM-IS U.S. Environmental Protection Agency 26
Federal Plaza New York, New York 10278 FTS 264-9850 COM
212/264-9850
-------
Accession No. 19024000002
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Estuarine Water Quality Model
(ACR) Acronym of Data Base or Model: ES001
(MED) Media/Subject of Data Base or Model: Hater
(ABS) Abstract/Over view of Data Base or Model: ES001 is a
steady-state, one-dimensional, estuarine water quality model uhich
simulates BOD and DQ variations. It was prepared by the EPA to
improve upon and document some water quality nodels developed for
the EPA by Hydroscience, Inc., and it is particularly useful for
the rapid evaluation of a number of varying estuary and uasteload
conditions. Based on the law of conservation of mass, the program
is designed to model the BOD-DO deficit system, but it is capable
of modeling analogous systems of sequential reactions of two
substances having first order kinetics, like that of a nitrogen
reaction with ammonia and nitrate. The model is assumed to be at
steady state and to be tidally averaged.
(CTC) CONTACTS: George A. Nossa and Tom O'Hare EPA, Environmental
Section Planning and Management
Loc: 26 Federal Plaza, New York, N.Y. 10278 Ph: (212) 264-9850
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-24-83
(CAP) Functional capabilities of model: The program segments the
system being modeled into sections within which the various
geonorphological, physical, and hydrological parameters of the
estuary are constant. For each segment the estuarine steady- state
advective-dispersive equation with constant coefficients is
defined, the junction points of the segments being boundary points
where these parameters can change. Several types of junctions are
allowed, including triple junctions, dams, etc., which in
combination allow the modeling of numerous types of configurations.
A maximum of 100 junctions and 50-100 sections can be accommodated.
Each section can have a length of up to 20 ffiles. Physical
processes that can be simulated include: dilution, advectlon,
longitudinal dispersion, temperature effects, and the processes of
first order decay and reaeration. The model handles riverine
estuaries well, especially when the net velocity is less than one
foot per second. The ES001 is sensitive to reaeration
coefficients, dispersion coefficients, net flow velocities, and
deoxygenation coefficients. A number of output options are
provided.
(ASM) Basic assumptions of model: SS001 handles only steady-state
flots and discharges, and it does not consider flow velocity or
quality variations with depth or within stream cross sections. The
model assumes only first order kinetics for BOD and DQ, and it
utilizes a matrix inversion technique for the solution of
simultaneous differential equations which are derived from the law
of conservation of mass.
(IHP) input to model: The ES001 requires a large amount of input data
in card-image form. Initial input/calibration needs include:
estuary cross-sectional data, segment length, water depth, net
flofc, reservoir outflows, estuary volume, tidal exchange
coefficient, dispersion coefficient, constituent concentration for
1561
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Accession No. 19024000002 (cent)
all system inflous, temperatures, benthic oxygen demand, algal
photosynthesis, respiration, and other rate coefficients, residual
Inputs from point sources, uniform waste input, salinities at
seavard boundaries, tidal exchange coefficients, and temperature
correction factors. Constituent concentrations throughout the
systea and observed salinity patterns are needed for verification.
(DOT) Cutput of model: Output information provided by the model
includes a tabular print-out of the input data, BOD concentration
and DO deficits at ten equidistant points per segment, and a number
of tatrices
-------
Accession No. 19024000002 (cont)
Contact name(s): Nossa,G.A.
-------
Accession No. 19024000003
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Outfall Plume Model
(ACR) Acronym of Data Base or Model: PLUME
(MED) Vedia/Subject of Data Base or Model: Nater
(ABS) Abstract/Overview of Data Base or Model: PLUME is a computer
program which can be used to evaluate coastal waters/ lakes/ or
estuaries under consideration as disposal sites. It is designed to
evaluate and/or predict the length of outfall needed to adequately
dilute a proposed discharge in order to provide compliance with
water quality standards. The model was developed by the U.S. EPA
Environmental Research Laboratory in Corvallis, Oregon/ and it has
been used by the San Juan Field Office of the U.S. EPA to aid in
the location and analysis of ocean outfalls.
CCTC) CONTACTS: George A. Nossa and Ton O'Hare (2PM-IS) EPA, Envi
Systems Section/ Information Systems Branch
Loc: 26 Federal Plaza, New York/ NY 10278 Ph: (212) 264-9850
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-24-83
(CAP) Functional capabilities of model: PLUME simulates the three
dinensional (two dimensions in the horizontal plane and one
dimension in the vertical plane) initial dilution of the effluent
pluie of residuals in lakes/ coastal waters/ and estuaries. Some
of the factors which can be evaluated by PLUME include the effects
of onshore currents/ tides/ density and salinity gradients/ ambient
surface and hypolianetic velocities/ the initial Jet velocity/ the
quantity of discharge/ the slope of the ocean bottom, and the rates
of coliform die-off in the vicinity of outfall locations. The
model simulates a stratified aquatic environment/ and up to 50
layers are permitted. PLUME is sensitive to discharged fluid
density and flow rate, and also to extent of stratification. The
model is also sensitive to the physical features of the outfall -
the diameter of openings, the number of ports, and the port depth.
(ASM) Basic assumptions of model: The model simulates the behavior of
a buoyant, round effluent plume being discharged into a non-
flowing water body where it considers the density differences
betbeen freshwater (with residuals) and saltwater masses. The model
does not simulate the transport of discharged residuals by
mechanisms other than mixing and dilution of fluids with different
densities, and it assumes no water flow other than the
plume-induced movement. A steady-state, stratified aquatic
environment is assumed.
(IffP) Input to models Input to the PLUME program should be in
card-image form. Initial setup/calibration needs include: (1)
water temperature profile (with depth), (2) salinity or density
profile (with depth), (3) effluent flow rate/ (4) effluent density,
and (5) the outfall features such as the port diameter/ number of
discharge points/ depth of discharge points, and the angle of the
discharge points to the horizontal plane. The initial constituent
concentration throughout the plume is needed for verification.
(OUT) Output of model: The model provides a tabular printout of the
following output information: (1) labeled input values, (2)
constituent dilution along the plume centerline, and (3) the depth
1564
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Accession No. 19024000003 (cont)
at which the plume stabilizes.
(CSR) Computational System Requirements: PLOMS is coded in FORTRAN IV
and requires a FORTRAN IV compiler. The program is compatible with
the IBM 370/155 and requires 10,000 words of core storage. Up to
one man-week is necessary for data preparation, and only one or two
man-hours for output interpretation. PLUME requires one computer
programmer or a hydraulics engineer with environmental modeling
experience.
(APP) Applications of model: Outfall plume was developed by the U.S.
EPA Environmental Research Laboratory in Corvallis, Oregon, and the
model has been used by the San Juan Field Office of the U.S. EPA to
aid in the location and analysis of ocean outfalls. PLUME has also
found other applications and other users. TECHNICAL CONTACT:#
Richard J. Callaway U.S. Environmental Protection Agency Corvail is
Environmental Research Laboratory 200 SW 35th Street Corvallis,
Oregon 97330 FTS 420-4703 COM 503/757-4703 George A. Nossa and To«
O'Hare Environmental Systems Section Information Systems Branch
2MP-IS 26 Federal Plaza New York, New York 10278 FTS 264-9850 COM
212/264-9850.
(HDW) Computational system requirements - Hardware: Mainframe IBM
370/155 ;Disc storage 10,000 words of core sto
(LNG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
graaming ;hydraulics engineer with environmental modeling
(HTP) Water Models - Typ« of model: Hater quality
(EBV) Fnvironraent(s) to which model applies: Estuary ;Lake jMarine
(CON) Processes and constituents Included In model: Salinity
;Te»perature ^Hydrology ;Quality processes
(CPL) Complexity level of model: steady state aass balance jmulti
dimensional
(REF) References - user manuals, documentation, etc.:
Bauvgartner, D.J. and D.S. Trent, "Ocean Outfall
Design: Part I, Literature Review and Theoretical Development."
Report by FWPCA, Mashington, D.C., 1970.
Baucgartner, D.J. and D.S. Trent, "User's Guide and
Documentation for Outfall Plume Model." Working Paper #80
by U.S. EPA Pacific Northwest Mater Laboratory, Corvallis,
Oregon, 1971,
Burchett, M.E., G. Tchobanglous, and A.J. Burdoln, "A practical
Approach to Submarine Outfall Calculations". Public Works.
5, 95, 1967.
Callaway, R.J., "Computer Program to Calculate ERF". EPA
Pacific Northwest Environmental Research Laboratory, Corvallis,
Oregon, 1973.
Guthrie, D.L., "Documentation for Outfall: A Computer Program
for the Calculation of Outfall Lengths Based upon Dilution
Requirements." U.S. Environmental Protection Agency, San
Juan Field Office, Santurce, Puerto Rico, 1975.
(CNM) Contact name(s): Nossa,G.A.
(COR) Contact organization: EPA, Environmental Systems Section,
Information Systems Bran
(ROR) Responsible Organization: Region II.Assistant Regional
1565
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Accession No. 19024000003 (cont)
Administrator for Policy,
1566
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Accession No. 19024000004
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Stream Network Simulation Program
(ACR) Acronym of Data Base or Model: SNSIM
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: SNSIM is a computer
program for the steady-state water quality simulation of a stream
network. Its basis is an expanded form of the Streeter-Phelps
equation, and it is designed to evaluate and/or predict the DO and
the carbonaceous and nitrogenous BOD profiles in a river or stream
where the effects of dispersion can be assumed to be insignificant.
This environmental model is ideal for the evaluation of various
water treatment schemes/ as its basic control variable is waste
input.
-------
Accession No. 19024000004 (cont)
A control variable which indicates if the stream depth, flow, and
velocity are to be computed by exponential correlation equations
nay also be used. The section length/ stream depth, stream
velocity, waste or effluent flow at the head of the section,
effluent COD, effluent NOD, effluent DO deficit, tributary flow at
the head of the section, and the ratio of ultimate to 5-day BOD are
needed* In addition, the tributary COD, tributary NOD, the
tributary DO deficit, water temperature, carbonaceous BOD
deoxygenation rate, carbonaceous BOD decay rate, nitrogenous BOD
decay rate, reaeration rate, algal oxygen rate, benthic oxygen
demand, the carbonaceous and nitrogenous bank loads, and the
altitude above sea level are required.
(OUT) Output of model: Reports produced by the SNSIM program include
the input parameters for each reach, as well as converted reaction
rates, section numbers, section names, distance downstream, CBOD,
NBQD, DO, flow, deficit components, and the total deficit for each
reach.
(CSR) Computational System Requirements: The SNSIM/1 is written in
FORTRAN IV for use on the IBM 370/155 in a 16K area of core
storage* It nay also be modified for compatibility with the IBM
1130 (SNSIN/2). At least one programmer or environmental engineer
with experience in water quality modeling are needed for the model.
(APP) Applications of model: SNSIN has been used for various
applications within the Environmental Protection Agency. TECHNICAL
CONTACT} George A. Nossa and Ton O'Hare U.S. Environmental
Protection Agency Environmental Systems Section Information Systems
Branch 2PM-IS Management Division 26 Federal Plaza New York/ NY
102*78 FTS 264-9850 COM 212/264-9850 Steven C. Chapra NOAA Great
Lakes Environmental Research Laboratory 2300 hashtenaw Avenue Ann
Arbor, Michigan 48104 FTS 378-2250 COM 313/668-2250
(HDit) Computational system requirements - Hardware: Mainframe IBM
370/155 ;Disc storage 16K core storage
(LNG) Computational system requirements - Language(s) used: FORTRAN IV
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming }Environmental engineer with water quality model experience
(HTP) Water Models - Type of model: Hater quality
Hater run-off
(EffV) environment
-------
Accession So. 19024000004 (cont)
1569
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Accession Ho. 19024000006
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Hater Quality Model
(ACR) Acronym of Data Base or Model: RAR03
(NEO) Media/Subject of Data Base or Model: Hater
(ABS) Abstract/Overview of Data Base or Model: HAR03 is a computer
program for the modeling of water quality parameters in
steady-state multi-dimensional natural aquatic systems* The
technique underlying the program is based on the Law of
Conservation of Mass, and the program can handle up to two
variables reacting in a feed forward fashion with first order
kinetics. The computer program from which HAR03 evolved was
developed by Hydroscience, Inc., for the Massachusetts Hater
Resources Commission. HAR03 utilizes a numerical solution
technique to a convective-diffusion equation for mass transport
including decay and source terms.
(CTC) CONTACTS: George A. Nossa and Tom O'Hare U.S. EPA,
Environmental Systems Section/ Information Sys. Branch
Loc: 26 Federal Plaza, Hew York, NY 10278 Ph: (212) 264-9850
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 02-24-83
(CAP) Functional capabilities of model: HAR03 is designed to model a
number of water quality parameters in a steady-state,
multi-dimensional natural aquatic system. The program has been
constructed with the BOD-DO deficit system in mind, but with minor
modifications the program may be used to model other variables
which are analogous to the BOD-DO deficit system such as chlorides,
coliform bacteria, polyphosphate-orthophosphate, etc. HAR03 is
capable of modeling conservative substances, single reactive
substances, coupled reactive substances, additive coupled
substances, estuarine coupled reactive substances, and estuarine
additive coupled systems. At present the program is limited to
simulating a system of up to 200 sections, where each section may
have up to six interfaces. A section may have only one interface
to act as a boundary.
(ASM) Basic assumptions of model: In an application of HAR03, it is
assumed that the variables and parameters inputted do not vary from
tidal cycle to tidal cycle. The reaction coefficients are assumed
to follow first order kinetics, and each individual segment of the
system is assumed to be completely mixed. An orthogonal system
segmentation for multi-dimensional systems is used.
(IMP) Input to model: HAR03 requires a large input data base in card
image form. JCL cards are required, as are cards to describe the
general system being modeled. The general system cards include
data for the interface parameters, the length, depth, temperature,
and volume of the system. These must be followed by specific
constituent cards which include data on: the number of boundaries,
boundary condition concentrations, photosynthetic rates, benthal
rates and loads, and other parameters for the constituents being
modeled. The geometric configuration for each section is also
required, as well as CBOD and NBOD removal rates, deoxygenatlon
rates and loads.
(OUT) Output of model: Output produced by the model includes:
1570
-------
Accession No. 19024000006 (cont)
printouts of the input system parameters, section temperatures,
volumes and depths, chloride boundary load, BOO rates and loads,
correction factors, deoxygenation and reaeration rates, and BOD-DO
deficits for each section in the system.
(CSR) Computational System Requirements: HAR03 has been designed for
an IBM System/370 computer, and it is written for a FORTRAN IV G or
H level compiler. The program requires approximately 184 K of
storage, but in order to save core storage for snail systems, HAR03
has been compiled in three versions* The first version handles a
system of up to 50 segments and is designated HAR50; similarly,
HAR100 and HAR200 can handle a maximum of 100 and 200 segments
correspondingly. The only difference between these versions is in
the size of the arrays defined in the programs. At least one
programmer and environmental engineer familiar with Hater quality
modeling are required to fulfill the resource requirements of the
model.
(APP) Applications of model: HAR03 has been used by the EPA for
various applications. TECHNICAL CONTACT: George A. Nossa and Tom
O'Hare U.S. Environmental Protection Agency Environmental Systems
Section Information Systems Branch 2PM-IS 26 Federal Plaza New
York, New York 10278 FTS 264-9850 COM 212/264-9850 Steven C.
Chapra NOAA Great Lakes Environmental Research Laboratory 2300
tfashtenaw Avenue Ann Arbor, Michigan 48104
(HDH) Computational system requirements - Hardware: Mainframe IBM 370
;Disc storage 184K
(LNG) Computational system requirements - Language(s) used: FORTRAN IV
G or H
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ;environmental engineer familiar with water qual modeling
(HTP) Hater Models - Type of model: Hater guality
(ENV) Environment(s) to which model applies: Estuary ;Lake
;Stream/river ;Marine
(CON) Processes and constituents included in model: Dissolved oxygen
;Eutrophication ;Salinity ^Temperature ;Hyd Quality processes
(CPL) Complexity level of model: steady state mass balance ;one
dimensional ;multi dimensiona
(REF) References - User manuals, documentation, etc.:
Chapra, S.C., and Moss a, G.A., Documentation for
HAR03: A Computer Program for the Modeling of Water Quality
Parameters in Steady State Multi-dimensional Natural Aquatic
Systems, U.S. Environmental Protection Agency, Region II,
26 Federal Plaza, New York, New York, October 1974.
(CNM) Contact naroe(s): Nossa,G.A.
(COR) Contact organization: U.S. EPA, Environmental Systems Section,
Information Sys. Br
(ROR) Responsible Organization: Region II.Assistant Regional
Administrator for Policy.
1571
-------
Accession No. 19036000101
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Receiving Hater Model
(ACR) Acronym of Data Base or Model: DIURNAL
(MED) Media/Subject of Data Base or Model: Hater
(ABS) Abstract/Overview of Data Base or Model: As stated in the
Instructions for Model Inventory, we have reviewed the information
contained in the abstract on DIURNAL which was published in the
1979 Environmental Modeling Catalogue. He have verified the
abstract and attach the verified copy to this page* Also/ question
#11 of the new EPA Form 3700-1A (8-80) is attached as requested.
DIUPNAL is a one-dimensional (horizational plane) receiving water
quality model. The model represents the physical processes of
advection and dilution and simulates receiving Hater quality
changes in dissolved oxygen. Coupled chemical reactions can be
simulated, and dissolved oxygen, CBQD and MOD can be modeled. The
primary function of DIURNAL is to predict the diurnal fluctuations
during periodic steady-state conditions. The model uas developed by
Hydroscience, Inc. of Hestwood, New Jersey.
(CTC) CONTACTS: Thomas Henry US EPA, Region 3 Hater Division
Loc: Curtis Bldg, 6th and Walnut Street Philadelphia, PA 19106 Ph:
(215)
597-8048
(CAP) Functional capabilities of model: The DIURNAL model can be
applied to streams and rivers under one-dimensional, steady-state
conditions. It allows a stream length to be analyzed with any
number of functional segments; the number being dependent only on
the frequency of instream characteristics changes, waste discharge
(or withdrawal) locations and accuracy desired. Each segment,
likewise, can be divided into any number of functional elements,
again dependent on desired accuracy. The following effects have not
been included in the solution; the time variation of flow, the time
variation of the temperature and wasterwater discharges and the
effect of dispersion. The sources and sinks of dissolved oxygen
considered in the model include reaeration, biochemical oxygen
demand, nitrogenous oxygen demand, benthic oxygen demand,
photosynthesis and respiration. The model is best used in
conjunction with a steady state water quality model to fix all
parameters except respiration and photosynthesis. DIURNAL would
then be used to determine these two parameters on a periodic
steady-state basis.
(ASM) Fasic assumptions of model: The solution analysis is an
extension of the technique based on the continuity equation for
dissolved oxygen which includes the diurnal time-variable effect of
photosynthetic oxygen production. The analysis considers the
temporal as well as spatial distributions. The periodic extension
of the photosynthetic oxygen production is expressed as a Fourier
series.
(INP) Input to model: Input information is basically of three types;
initial conditions definition, individual segment characteristics
definition and discharger information. Initial conditions data
Include system description (number of sections, element length,
river mile at the head of the system) and quality description
1572
-------
Accession No. 19036000101 (cont)
(upstream BOD, upstream NBOD and Fourier coefficients of upstream
DO). The individual segment data include the following; section
length, velocity, temperature, reaeration rate, and decay rates
(carbonaceous and nitrogenous). Other information includes bottom
demand, hours of daylight, maximum photosynthetic rate,
respiration, time of sunrise, stream flow and segment elevation.
Discharger information includes, DO, flow, BOC and NOD. Segment
characteristics and discharger information is repeated for each
sequent modeled.
(GUT) Output of model: DIURNAL produces a tabular printout of section
parameters and dissolved oxygen response. The section parameters
include; length, velocity, temperature, flow, reaeration and decay
rates, benthic rates and photosynthesis and respiration rates. The
DO response table includes hourly dissolved oxygen values, for 24
hours, for the beginning and the end of the segment and any
intermediate point designated by the print interval.
(CSR) Computational System Requirements: DIURNAL is coded in FORTRAN
IV (G) and can be run on a digital computer uith a 40,000 word core
storage capability; FORTRAN IV (G) compiler. Application of the
model results !n minimal costs, in the range of $1 - $2 per run,
depending on the number of segments. Approximately 1-man week is
required for model setup and data preparation. Initial runs on a
companion model is necessary to establish appropriate velocities
and rates. Manpower requirements include one environmental
engineer uith a basic programming background.
(APP) Applications of model: DIURNAL can be used on any stream where
it is assumed that the primary cause of the diurnal variation of
the dissolved oxygen is the algal oxygen production. TECHNICAL
CONTACT: Thomas Henry (3W.A14) U.S. Environmental Protection Agency
Region III Curtis Building 6th and Walnut Street Philadelphia, PA
19106 FTS 597-8048 COM 215/597-8048
(HDW) Computational system requirements - Hardware: Mainframe any
digital computer ;0isc storage 40K core
(LNG) Computational system requirements - Language(s) used: Fortran IV
(G)
-------
Accession No. 19038000913
-------
Accession No. 19038000913 (cont)
referenced to the same network of channels and junctions. The
tidally fluctuating velocities/ flows/ and heads predicted by the
hydraulic model are stored on tape or disk and are the basis of the
hydraulic inputs to the quality program. Constit- uents in the
quality program are subject to the processes of advection,
dispersion (including both eddy diffusion and disper- sion due to
density currents)/ biological and/or chemical decay/ transfer
between water and the atmosphere/ and transfer between water and
the bottom sediments. A mass balance for each con- stituent is
performed at each junction for each time step. The quality model
predicts the dynamic (tine varying) constituent concentrations in
each junction which result from a specified set of boundary
conditions/ inflows/ waste discharges/ and diversions. It is
important that the time and space scales used in the DEM
approximate as nearly as possible the physical, tidal/ and climatic
characteristics of the estuary. Special attention should be paid
to the correspondence of model net- work features with existing
sampling stations and wastewater inputs.
The OEM is sensitive to (1) the time step in the hydraulic
program (stability reasons); (2) net flows; (3) residuals loading
rates; (4) frictional resistance coefficient; (5) initial condi-
tions if "real time" solutions are desired; and/ (6) the specified
reaction kinetics and rates.
The Dynamic Estuary Model has been run for networks with as
many as 1300 channels and 840 junctions. Some versions have
modeled up to 15 constitutents.
(ASM) Basic assumptions of model: The model assumes that vertical
stratification is either absent or limited to relatively small
areas/ and it does not handle wind stress or tidal flats exposed at
low tide. Other hydrodynamic processes assumed negligible include
longitudi- nal density gradients/ Coriolis acceleration/ and bottom
slope. The instantaneous mixing of residuals discharge throughout
June- tions is also assumed.
(IHP) Input to model: The DEM requires a large input data base on
disk/ tape/ and/or cards. Parameters which need to be specified
include headwater and tributary flows/ wastewater flows and
loadings/ water withdrawals/ seaward tidal conditions/ channel and
junction geometry/ bottom roughness of each channel/ constituent
concen- trations at boundaries/ dispersion coefficients and decay
rates for non-conservative constituents. Physical data pertaining
to channels and junctions can be obtained from navigational charts
since direct measure- ments are seldom available.
(OUT) Output of model: The model is capable of producing a wide
variety of out- puts. Output options available are: (1) maximum
and minimum flows/ heads/ and velocities, as well as net flows/
over a tidal cycle for the model network/ (2) maximum, minimum, and
average con- stituent concentrations for each junction over a
complete tidal cycle (or other specified averaging interval), <3)
"slack water" and "snapshot" tables of constituent concentrations
at desired time intervals throughout the simulation, and (4)
line-printer plots of both spatial and temporal concentration
profiles.
1575
-------
Accession No. 19038000913 (cont)
(APP) Applications of model: The Dynamic Estuary Model has been used
by the SPA for the Pearl Harbor Water Quality Model development
project. It Has originally developed by the Water Resources
Engineers for the Division of Water Supply and Pollution Control of
the Public Health Service, and it has been used by the Federal
Water Pol- lution Control Adninistration (FWPCA) and by the State
of Call- fornia. The DEM Mas used by the Federal Water Quality
Adainis- tration (FWQA) for water studies of the San Francisco and
San Diego Bay estuaries/ and by the EPA for uater quality studies
of the Delaware and Potomac estuaries. There have been other users
and applications of this aodel.
(HOW) Computational systea requireaents - Hardware: Mainfraae-IBM
370/168 ;Disc storage~130K to 400K ;Magnetic t
(LNG) Computational systea requireaents - Language(s) used: Fortran I?
(OSK) Coaputational system requireaents: Operator Knowledge/Skills: Pro
graaaing Environmental engineering with experience in w
-------
Accession No. 19038000913
-------
Accession No. 19046000005
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Georgia Dosag
(ACR) Acronym of Data Base or Model: GAOOSA6
(MED) Media/Subject of Data Base or Model: Hater
(ABS) Abstract/Overview of Data Base or Model: A dissolved oxygen
model based on the modified Streeter Phelps equation, with options
for incremental runoff/ an extra non-conservative variable/ a
converge to set Dissolved Oxygen routine/ and numerous waste
inputs. The model runs on a 9845 or 9831 Hewlett Packard mini
computer and is a user interactive program*
(CTC) CONTACTS: James Greenfield Hater Quality Standards
Loc: EPA-Region 4 Atlanta/ GA 30365 Ph: (404) 881-4793
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 12-23-82
(CAP) Functional capabilities of model: The model is a steady state/
one dimensional/ and one stretch model*
(ASM) Basic assumptions of model: The model is based on the modified
Streeter Phelps equation which predicts dissolved oxygen deficits
based on instream concentrations of carbonaceous and nitrogenous
BOD and their respective reaction rates and the reaeration
characteristics of the stream. Inputs are entered by modeler/
there are no default values.
(IMP) input to model: Haste treatment facility effluent flow,
carbonaceous biological oxygen demand/ nitrogenous biological
oxygen demand and Dissolved oxygen; Instream concentrations of
CBOE/ NBOD/ and D.O.; and stream velocity and flow measurements.
(OUT) Output of model: Dissolved oxygen concentrations along the
modeled stream segment/ the carbonaceous biological oxygen demand
and nitrogenous biological oxygen demand predicted concentrations/
and graphs of any of the variables in the model.
(APP) Applications of model: Used by the State of Georgia to set
effluent limits for the waste dischargers. TECHNICAL CONTACT: James
Greenfield Hater Quality Standards Region IV/ EPA/ Atlanta/ GA
30365 FTS 257-4793
(HDH) Computational system requirements - Hardware: Mainframe
Hewlett-Packard 9845 or 9831 jPrinter Thermal 80 c
(LUG) Computational system requirements - Language(s) used: Basic
(OSK) Computational system requirements: Operator Knowledge/Skills: Kno
iiledge of water modeling
(HTP) Hater Models - Type of model: Hater quality
(ENV) Environment(s) to which model applies: Stream/river
(CON) Processes and constituents Included in model: Dissolved oxygen
;Temperature ^Hydrology ^Hydraulics
(CPL) Complexity level of model: steady state mass balance ;one
dimensional
(REF) References - User manuals/ documentation/ etc.:
Georgia DOSAG USER Manual
(CNM) Contact name(s): Greenfield,J.
(COR) Contact organization: Hater Qullty standards
(ROR) Responsible Organization: Region IV.Hater Management Division.
1578
-------
Accession No. 19047000003
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Multi-Source CRSTER
(ACR) Acronym of Data Base or Model: CRSTER 2
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overvie* of Data Base or Model: This model is basically
the same as EPA's single source CRSTER.
(CTC) CONTACTS: Lewis H. Nagler EPA/NOAA-Air Management Branch
Loc: EPA Region 4 Atlanta/ GA 30365 Ph: (404) 881-4901
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-26-83
(CAP) Functional capabilities of model: While essentially the same in
function as CRSTER/ CRSTER 2 will allow separation of multiple
emission points.
(ASM) Basic assumptions of model: Same as CRSTER
(INP) Input to model: Differs from CRSTER in that distinct spacial
coordinates can be assigned to each point of emissions. Also/ this
model can handle an increased number of sources and receptors/ and
stack data can be input in English or metric units.
(OUT) Output of model: Basically/ the same as CRSTER/ but stack and
receptor coordinates can be output in a format for use by the
CALCOMP plotter.
(APP) Applications of model: Same as CRSTER/ except for added
flexibility of allowing emission source separation.
(HDU) Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 28K core
(LNG) Computational system requirements - Language(s) used; Fortran ¥
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? Note: OAQPS has reviewed
the model but has not yet approved
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atonosphere: Negligible
removal
(TME) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: multiple point (more than 10-20)
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals/ documentation/ etc.:
User Information for the Modified CRSTER Program
(EPA Information Cleaning-house Files)
Others: Same as for CRSTER.
(CNM) Contact name(s): Nagler/L.H.
(COR) Contact organization: EPA/NOAA-Air Facilities Branch
(ROR) Responsible Organization: Region I?.Air and Haste Management
Division.
1579
-------
Accession So. 19047000004
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Modified HIKAY Program
(ACR) Acronym of Data Base or Model: MODHIWAY
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: This model is basically
the sane as EPA's HITrfAY model.
(CTC) CONTACTS: Lewis H. Nagler EPA/NOAA-Air Management Branch
Loc: EPA Region 4, Atlanta, GA Ph: (404) 881-4901
(STA) Data Base status: Operational/Ongoing
(DF) Date of fora completion: 01-26-83
(CAP) Functional capabilities of model: SPA's HIWAY model was modified
to allow for calculations to be made for more than one roadway at a
time. This allows for computation of pollutant concentra- tions
due to intersecting roads (e.g./ intersections),
(ASK) Basic assumptions of nodel: Same as HIWAY
(IKP) Input to model: Differs from HIWAY to the extent that
coordinates for more than one roadway (and associated parameters)
can be used.
(OUT) Output of model: Outputs concentrations in parts per million
(ppm), milligrams per cubic meter (mg/m(3)), and micrograms per
cubic meter (ug/m(3)) as well as giving grid concentrations and
road segment end points in a format suitable for a graphic plotter.
(CSR) Computational Systea Requirements: Basically the same as HIHAY.
(APP) Applications of model: Same as HIWAY, but allows for additional
roadways and traffic. TECHNICAL CONTACT: Lewis H. Nagler EPA/NOAA -
Air Management Branch EPA - Region IV/ Atlanta, GA 404/881-4901
(HOB) Computational system requirements - Hardware: Mainframe Univac
1110 ;Disc storage 12K Core
(LUG) Computational system requirements - Languase(s) used: Fortran V
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) Model reviewed and approved by OAQPS? NO
(PMP) Production method of primary pollutant in «odel: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Negligible
removal
(TME) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: limited time
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
User Information for the Modified HItfAY Program
(EPA Information Clearinghouse files)
Others: Same as for HIWAY
(CUM) Contact name(s): Nagler,L.H.
(COR) Contact organization: EPA/NOAA-Air Facilities Branch
(ROR) Responsible Organization: Region I?.Air and Waste Management
Division.
1580
-------
Accession No. 19048000906
(DQ) Date of Questionaire: 12-02-82
(HAM) Same of Data Base of Model: Non-point Runoff Model for a Rural
Setting
-------
Accession No. 19048000906 (cont)
specified or as daily loadings*
(APP) Applications of model: EPARRB can be used in any wide area type
non- point assessment. TECHNICAL CONTACT: Howard A. True, Computer
System Analyst Ambient Monitoring Section Surveillance and Analysis
Division EPA Region IV College Station Road Athens, Georgia 30613
FTS 250-3139 COM 404/546-3139
(HDtf) Computational system requirements - Hardware: Mainframe any with
greater than 120K core IBM, CDC, 01IIVAC e Printer any 132
characters per line model ;any nodel
(LUG) Computational system requirements - Language(s) used: FORTRAN
-------
Accession Ho. 19048000907
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Non-point Runoff Model for a Single
Storm Event
(ACR) Acronym of Data Base or Model: EPAORA
-------
Accession No. 19048000907 (cont)
(HOW) Computational system requirements - Hardware: Mainfraie Any yith
greater than 120K core IBM, UlfI?AC CDC, e Printer Any 132
characters per line model ?any type or model
(LNG) Computational system requirements - Language(s) used: FORTRAN
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming Fortran * JCL/JES ^Engineering BS
(HTP) Mater Models - Type of model: Water run-off
(SNV) Environment(s) to yhich nodel applies: Lake jStream/river
jNon-point Urban
(CON) Processes and constituents included in model: Dissolved oxygen
?Eutrophication jErosion and sediment jToxi Hydrology ;aixing only
(CPL) Complexity level of model: Simplified
(REF) References - User manuals/ documentation/ etc.:
True, Howard A./ "Non-Point Assessment Processes",
April 1976/ Revised April 1977.
(CNM) Contact name(s): of,H.A.
(COR) Contact organization: Ambient Monitoring Section Surveillance (
Analysis Division
(ROR) Responsible Organization: Region I?.Environmental Services
Division.
1584
-------
Accession Mo. 19048000908
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Reporting and Projection Planning
Model-Point and Non-Point
(ACR) Acronym of Data Base or Model: EPATLC
(MED) Media/Subject of Data Base or Model: Water ;Point and Non-point
load manipulations
(A8S) Abstract/Overview of Data Base or Model: EPATLC is addressed as
Planning Model "C" of a three model group. This model will combine
point and non-point loads for reporting purposes and will also
perform projections by changing treatment levels for point sources
and land use percentages for non-point sources. The input to this
process which comes from NPDES permits for up to three types of
point sources (i.e. Municipal/ Industrial and any other) and output
from EPAURA "A" and EPARRB "BM process runs provide non-point
information for up to five land uses.
(CTC) CONTACTS: Howard A. True or any member of Ambient Monitoring
Sec/ Loc: EPA Region 4 College Station Road, Athens/ GA 30613 Ph:
FTS: 250-3113
(STA) Data Base status: Discontinued
(DF) Date of form completion: 12-07-82
(CAP) Functional capabilities of model: EPATLC was designed to provide
a composite report of pollutant loads from both point and non-point
sources for current conditions. The process has expanded to allow
charges in treatment rates for point sources and changes in land
use for non-point sources so that the modification of current
conditions provides for a projected report being made for some
future year. Each parameter of interest produces a separate
report. Three sets of loads are calculated if data ranges are
stated/ these loads are lowest/ highest and most probable. The
most probable load is developed by randomly sampling the values
between the input extremes. This report shows the relationship
between point and non- point loads and could indicate the
feasiblity of Advanced Waste Treatment effectivenss.
(ASM) Basic assumptions of model: This model is a technical assistance
process for simplified reporting and projecting waste and potential
non-point pollutant loads for an area and its component sub-areas.
The model assumes that required information is available and merely
requires manipulation according to changing criteria.
(INP) Input to model: The model input requires four cards of area data
for a particular parameter and an unlimited number of four card
land unit groups for this parameter. Multiple parameter groups can
be handled in a single machine run.
(OUT) Output of model: Output consists of a single point and non-point
conposite report for each sub-area and each parameter. A composite
poirt and non-point summary report is produced for each parameter.
-------
Accession No. 19048000908 (cont)
greater than 120* core IBM, ONI?AC, COC e Printer any 120 Character
model
(LNG) Computational system requirements - Language(s) used: FORTRAH
(OSK) Computational system requirements: Operator Knowledge/Skills: Exp
erience uith statistics and random number generators. ;Pr
Engineering BS
(WTP) Hater Models - Type of model: Hater run-off
(EH?) Environment(s) to which model applies: Lake ;Stream/river
; Non-point Drban and Non-urban
(CON) Processes and constituents included in model: Eutrophication
;srosion and sediment ;Quality processes
(CPL) complexity level of model: Simplified
(REF) References - User manuals, documentation, etc.:
True, Howard A., "Non-Point Assessment Processes",
April 1976, Revised April 1977.
(CUM) Contact nane(s): of,H.A.
(COR) Contact organization: Ambient Monitoring Sec, S&A Oiv.
(ROR) Responsible Organization: Region I?.Environmental Services
Division.
1586
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Accession No. 19051700001
-------
Accession No. 19051700001 (cont)
COSK) Computational system requirements: Operator Knowledge/Skills: Pro
granning ;Engineering
CWTP) Water Models - Type of model: Water quality
(ENV) Environment(s) to *hich model applies: Lake
(COR) Processes and constituents included in model: Cutrophication
;Temperature ;Biological effects ^Hydrology ;
(CPL) complexity level of model: transient mass balance ;multi
dimensional
(CNM) Contact name(s): Connolly,J.P.
(COR) . Contact organization: Manhattan College
-------
Accession No. 19058000903
(OQ) Date of Quest!onaire: 12-02-82
(NAM) Name of Data Base of Model: TEMSTAT
(ACR) Acronym of Data Base or Model: TEMSTAT
(MED) yedia/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: The computer program
TEMSTAT Is a river temperature simulation model developed for
assessing numerous thermal loading alternatives for the Vahoning
River (eastern border of Ohio flows through Warren and Youngstoun).
For the program the Edinger and Geyer temperature decay equations
were used with statistically varying inputs to compute the
statistical distribution of temperatures at designated points along
the river.
(CTC) CONTACTS: Donald Schregardus EPA, Region 5 Surveillance &
Analysis
Division/ Eastern District Office
Loc: 25089 Center Ridge Road, Westlake, OH 44145 Ph: (216) 835-5200
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-17-83
(CAP) Functional capabilities of model: The model uses a one
dimensional steady state tesperature calculation procedure
developed by Edinger and Geyer* Thermal loadings are input as a
mean and standard deviation. TEMSTAT uses a normal distribution
random number generator to determine specific inputs Cor each
calculation. Numerous repetitive stream calculations are made to
determine the distribution of temperature In the river.
(ASM) Basic assumptions of model: The lodel assumes heated water
discharged to the river decays exponentially to an equilibrium
temperature. Complete mixing of the effluent into the receiving
stream is assumed as well as a non stratified uniform temperature
distribution at each point in the river. Input loadings,
equillibrium temperatures, heat exchange, coefficients and stream
flows are assumed to be independent variables.
(INP) Input to model: TEMSTAT requires the mean and standard deviation
of thermal effluent loadings, flow duration data, stream surface
area and the mean and standard deviation of the equillibriuro
temperature (£), and heat exchange coefficient (K). E and K must
be calculated by a separate program requiring hourly meteorological
data (air temp, wind speed, relative humidity and cloud cover).
(OUT) Output of model: TEMSTAT outputs the statistical distribution of
stream temperatures at selected points in the river. Outputs
include maximum, minimum, mean and standard deviations of the
calculated temperatures. Also reported are the temperatures
exceeded 1,5, 10 and 20 percent of the time.
(APP) Applications of model: TEMSTAT was used to evaluate thermal
loading alternatives on the Mahoning River. With some modification
it has also used to compute temperatures in the lower Black River
(tributary of Lake Erie, West of Cleveland) Equillibrium
temperatures and heat exchange coefficients were determined for
both rivers using a model developed by US Army Corp of Engineers
and modified to fit program requirements. TECHNICAL CONTACT: Donald
Schregardus OS EPA, Region V S&A Division Eastern District Office
25089 Center Ridge Road, Westlake OH 44145 216/335-5200
1589
-------
Accession No. 19058000903 (cont)
-------
Accession No. 19058000904
-------
Accession No. 19058000904 (cont)
CHDIO Computational systen requirements - Hardware: Mainframe IBM 360
or Univac 1110 ;Disc storage Core - less t Printer medium or high
speed ;Card reader/punch
(LUG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational systea requirenents: Operator Knowledge/Skills: Eng
ineering
(VTP) Mater Models - Type of nodel: Hater quality
(ENV) Environment(s) to which model applies: Stream/river
(COM) Processes and constituents included in model: Dissolved oxygen
;Eutrophication ;Toxic chemicals cyanide ph Hydrology ;Quality
processes
-------
Accession No. 19097000101
-------
Accession No. 19097000101 (cont)
time of day and from one part of a city to another. If land use
categories are not specified, the model assumes that all central
business district area types correspond to the same locale type.
Core city areas are assumed to be commercial. Suburban streets are
assumed to be commercial if their average weekday traffic exceeds
10,000; otherwise the locale is taken to be residential. The
locale for areas that do not fit specified categories is taken to
be rural, or unclassified. A Gaussian-plume diffusion formulation
is used for diffusion calculations. The model uses an atmospheric
stability algorithm derived by Ludwig and Dabbert (1976) from the
basic method proposed by Pasquill (1961). Daytime stability
categories are based on iiind speed and the strength of the incoming
solar radiation.
-------
Accession No. 19097000101 (cont)
(REF) References - User manuals, documentation, etc.:
Heffter, J.L., and Taylor, A.D., A Regional-
Continental Scale Transport, Diffusion, and Deposition Model,
Part I: Trajectory Model, National Oceanic and Atmospheric
Administration Technical Memoranda, ERL ARL-50, pp. 1-16,
1975.
Johnson, W.B., W.F. Dabberdt, Luduig, F.L., and Allen, R.J.,
Field Study for Initial Evaluation of an Urban Diffusion
Model for Carbon Monoxide, Comprehensive Report CRC and
Environmental Protection Agency, Contract CAPA-3-68 (1-69),
1971.
Kircher, D.S. and Williams, M.E., Supplement No, 5 for
Compilation of Air Pollutant Emission Factors (AP-42),
Chapter 3 (second edition), U.S. Environmental Protection
Agency, Office of Air Quality Planning and Standards, (OAQPS),
1975.
Kunselman, R., McAdams, H.T., Do«ke, C.J., and Williams, M.,
Automobile Exhaust Emission Modal Analysis Model, EPA
Contract 68-01-0438, Calspan Corporation, Buffalo, New York,
1974.
Luduig, F.L., "Urban Air Temperatures and Their Relation to
Extra-Urban Meteorological Measurements,*1 Proceedings of the
Semiannual Meeting of the American Society of Heating,
Refrigeration, and Air Conditioning Engineers, (Survival
Shelter Problems, Part II) San Francisco, pp. 40-45,
January, 1970.
Ludwig, F.L., and Dabberdt, W.F., Evaluation of the APRAC-
1A Urban Diffusion Model for Carbon Dioxide, Final Report,
CRC and EPA Contract CAPA-3-68 (1-69), 1972.
Ludvig, F.L., and Dabberdt, W.F., "Comparison of Two
Atmospheric Stability Classification Schemes in an Urban
Application," Journal of Applied Meteorology, 15, 1172-
1176, 1976.
Luduig, F.L., Johnson, W.B., Moon, A.E., and Kancuso, R.L.,
A Practical, Multipurpose Urban Diffusion Model for Carbon
Monoxide. Final Report, Coordinating Research Council (CRC)
Contract CAPA-3-68 and National Air Pollution Control
Administration Contract CPA 22-69-64, 1970.
Ludvig, F.L., and Kealoha, J.H.S., Selecting Sites for Carbon
Monoxide Monitoring, Final Report, EPA Contract 68-02-1471,
Stanford Research Institute, Menlo Park, California, 1975.
Mancuso, R.L., and Ludwig, F.U, User's Manual for the
APRAC-1A Diffusion Model Computer Program, CRC and EPA,
Contract CAPA-3-68 (1-69), 1972.
Sagi, G., and Campbell, L., "Vehicle Delay at Signalized
Intersections," Traffic Engineering, 1969.
Sandys, R.C., Buder, P.A., and Dabberdt, W.F., ISMAP: A
Traffic/Emissions/Dispersion Model for Mobile Pollution
Sources, prepared for the California Business Properties
Association, Hawthorne, California, by the Stanford Research
Institution, Menlo Park, California, 1975.
D.S. Department of Transportation, Federal Highway
1595
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Accession Mo. 19097000101 (cont)
Administration, Orban Transportation Planning, General
Information, 1972.
tCMM) Contact naae(s): Larson,L.
U-S. EPA, Region 9, Air and
-------
Accession No. 19102000501
(DQ) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Chesapeake Bay Circulation Model
(ACR) Acronym of Data Base or Model: CBCM
-------
Accession No. 19102000501 (cent)
novel numerical modeling techniques embodied in CBCM have allowed
many time-consuming computations to be simplified at virtually no
loss of accuracy. Those processes which CBCM is not presently able
to simulate are:| - systems with a strong temperature-driven
density circulation^ - major storm and wind events^ - any
mass constiuents which interact and are not governed by first-order
decayt CBCM is an accurate, yet flexible and affordable, model of
the circulation of water in Chesapeake Bay. The latest advances in
numerical modeling have been used, combining the produce a split-
time/ space-staggered/ lumped-mass, finite-element numerical
solution scheme. New modeling techniques, such as the simulation
of deep sub merged trenches with quasi 2-B elements, have been
developed to meet the demands of simulating the complex Bay system
as simply as possible without sacrificing accuracy. The model
structure has been designed for easy operation. The CBCM code is
also very understandable and easy to modify, a feature important
when decision-making must be aided by subsequent modeling tasks to
simulate other parameters whose motion is governed by hydrodynamic
circulation.
(ASM) Basic assumptions of model: To develop a 3-0 aodel of Chesapeake
Bay which was both affordable in terras of computer costs and
accurate in terms of hydrodynamics and mass transport calculations,
a unique procedure was adopted. First, the model was designed to
handle river-bay and trench-bay connections using a linked 1-D to
2-F, layered model which produced accurate quasi 2-D and 3-D
representations. This provided an efficient means to model the
complex geometric features of the Bay. Second, numerical solution
techniques were developed to economically approximate the boverning
shallow water equations and conservation of mass equation. The
resulting solution techniques are actually the combination of four
or five different models or modeling approaches, selected to
develop a scheme with unusually good stability, accuracy and
economy features.# The Chesapeakke Bay Circulation Model (CBCM) is
comprised of two models, a hydrodynamic model and mass transport
model, weakly linked through an equation-of-state. The
hydrodynamic solution scheme is a linked quasi 2-D to 3-D/
fixed-layered, lumped-Bass, space- staggered, split-time finite
element technique with tide elevations calculated at modal points,
flow and velocities calculated at the raid-points of triangular
cells. The mass transport scheme is a linked quasi 2-D to 3-D,
fixed-layered, lumped-mass, space-staggered implicit finite-element
technique with concentrations calculated at nodal points. This
combination of solution schemes is very stable and accurate, as
well as very affordable in terms of computer costs due to the
removal of the matrix inversions normally associated with this type
of finite-element esturay model. Furthermore, the lumped- mass
approach eases the Courant condition on the hydrodynamic time step,
and allows a theoretically unlimited computation interval for mass
transport simulations, although a practical limit exists for the
resolution of results.
CIMP) Input to model: Bathymetry, Salinity, Tidal Elevations, Mind
Velocity Magnitude and Direction, Fresh Water Inflow, Atmospheric
1598
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Accession No. 19102000501 (cont)
Pressure/ Current Velocities/ Turbulence, Dispersion/ Friction
Coefficients/ Heat Source Temperatures/ Water Temperature
-------
Accession No. 19999999901
(DO) Date of Questionaire: 12-02-82
(MAM) Name of Data Base of Model: Texas Episodic Model Version 8
(ACR) Acronym of Data Base or Model: TEM8
(MED) Media/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The Texas Episodic
Model Version 8 (TEM-8) uses the steady state Gaussian plume
hypothesis in a relatively fast FORTRAN computer program designed
to predict ground level, short-tern concentrations of atmospheric
pollutants. The Briggs plume rise and the Pasquill-Gifford-Turner
dispersion equations are used in the «odel. Concentrations from
area sources are determined using the method developed by
Gifford-Hanna. An emissions inventory and a set of meteorological
conditions are input to the model by the user. The TEM was
developed by the Texas Air Control Board, Austin, Texas.
(CTC) CONTACTS: Keith Zimmermann Texas Air Control Board Technical
Services Division* Loc: 6330 Highway 290 East Austin, Texas 78773
Ph: (512) 451-5711
(STA) Data Base status: Operational/Ongoing
(DP) Date of form completion: 01-20-83
(CAP) Functional capabilities of model: Concentrations for one or two
pollutants nay be deterained for tine periods from 10 minutes to 24
hours. The model, as supplied, may analyze up to 300 individual
point sources and up to 50 area sources but these size limits are
easily expanded. Concentrations are calculated at up to 2500
locations in a user-defined rectilinear array of receptors. An
automatic grid feature in the program may be used to define a grid
that encompasses the point of maximum concentration. A variety of
input and output options are available to enhance the utility of
the model. Op to 24 sets of meteorological conditions may be input
to the model. Exponential decay of pollutant concentration may be
calculated as a user option.
(ASM) Basic assumptions of model: a. Emission Rate. The emission rate
is constant, b. Mind Speed. The pollutants are transported
downwind at an appropriate average wind speed. Hind speed is
adjusted to the physical stack height, c. Mind Shear. There is no
directional Hind shear in the vertical, d. Plume Behavior. The
pluve is infinite with no plume history. The pluae is reflected at
the earth's surface Mith no pollutant losses due to reaction or
deposition at the surface, e. Chemistry/Reaction Mechanism. The
pollutants are non- reactive gases or aerosols and remain suspended
in the air following the turbulent movement of the atmosphere.
There is an option to use exponential decay of pollutants
concentration based upon a user input half life. f. Horizontal and
Vertical Dispersion. Dispersion occurring in the downwind
direction is negligible compared to advection. The concentrations
in both the crosswind and the vertical directions are described by
the Gaussion distribution about the plume centerline. Dispersion
coefficients are from Pasquill- Gifford-Turner with no additional
adjustments being made for variations in surface roughness.
Horizontal coefficients (sigma-y) are assumed to represent
dispersion over a 10 minute averaging period and are increased for
longer averaging times to represent the greater horizontal plume
1600
-------
Accession No. 19999999901 (cont)
meander due to fluctuations in Hind direction.
(IMP) Input to model: A. Input to the TEM-8 is as follows: (1) Control
parameter cards specify the input and output options grid spacing
and orientation/ etc. (2) Scenario parameter (meteorological
conditions) cards. (3) area source inventory cards (4) point source
inventory cards B. Input options: (1) Point source inventory
parameters may be in metric or English units. (2) Point source
inventory may be read from cards or disk file.
{OUT) Output of model: TEM-8 output options are: (1) list of
coordinates and concentrations at each grid receptor (2) an array
map of grid coordinates and concentrations (3) for each receptor a
culpability list identifying the highest five major concentrations
contributors and respective contributions (4) a list of the point
of maximum concentration for each scenario <5) card punch output
for input to contour plotting programs
-------
Accession No* 19999999901 (cont)
CROR) Responsible Organization: Texas Air Control Board.
1602
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Accession No. 19999999902
(DQ) Date of Questionaire: 12-02-82
f?iS? ?aae of Data Base of Mo^ls Texas Climatological Model Version 2
(ACR) Acronym of Data Base or Model: TCM2
(MED) Media/Subject of Data Base or Model: Air
UBS) Abstract/Overview of Data Base or Model: The Texas
Climatological Model Version 2 (TCM-2) uses the steady-state
Gaussian plume hypothesis, is a relatively fast FORTRAN computer
program to predict ground level, long-tern concentrations of
atmospheric pollutants. The Briggs plume rise, the
Pasquill-Gifford-Turner dispersion equations, and sector averaging
are used in this model. Contributions from area sources are
determined by a modification of the method developed by
Gifford-Hanna. An emissions inventory and a set of meteorological
conditions are input to the model by the user. The TCH was
developed by the Texas Air Control Board, Austin, Texas.
(CTC) CONTACTS: Cyril Durrenbergent Texas Air Control Board,
Technical Services Division Section* Loc: 6330 Highway East,
Austin, Texas 78723 Ph: (512) 451-5711
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-20-83
(CAP) Functional capabilities of model: Concentrations for one or two
pollutants may be determined for long averaging times. Any number
of area and point sources may be analyzed. Concentrations are
calculated for up to 2500 locations in a user-defined rectilinear
array of receptors. Up to 5 sets of meteorological conditions in
the fora of a meteorlogical Joint frequency function and average
ambient temperature may be input to the model. Important user
options are exponential pollutant decay, choice of rising or final
plume rise, choice of urban or rural dispersion, and calibration
with observed concentrations. A variety of other input and output
options are available to enhance the utility of the model.
(ASM) Basic assumptions of model: A. The emission rate is constant for
each set of meteorological conditions. B. Wind Speed - The
pollutants are transported downwind at an appropriate average wind
speed. Wind speed is adjusted to physical stack height. C. Wind
Shear - There is no directional wind shear in the vertical. D.
Plunse Behavior - The plume is infinite with no plume history. The
plume is reflected at the earth's surface with no pollutant losses
due to reaction or deposition at the surface. E. Chemistry/Reaction
Mechanisms - The pollutants are non-reactive gases or aerosols and
remain suspended in the air following the turbulent movement of the
atmosphere. There is an option to use exponential decay of
pollutant concentration based upon a user input half life. F.
Horizontal and Vertical Dispersion - The concentration in the
vertical direction is described by a Gaussian distribution about
the plume centerline. Dispersion coefficients are from
Pasquill-Gifford-Turner with no additional adjustments being made
for variations in surface roughness. Horizontal dispersion is
described by sector averaging instead of by a Gaussian
distribution. A meteorological joint frequency function is used to
describe dispersion in the horizontal.
(I«P) Input to model: A. Input to the TCM-2 is as follows:
1603
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Accession No. 19999999902 (cont)
1* Control parameter cards specify the input and output
options, grid spacing and orientation, etc.
2. Calibration factor cards*
3. Meteorological joint frequency function value cards.
4. Area source inventory cards.
5. Point source inventory cards.
6. Monitoring data cards.
B. Input options (1) Point source inventory parameters may be in
•etric or English units. (2) Point source inventory may be read
from cards or disk file (3) Meteorological joint frequency function
nay be read from cards or disk file.
(OUT) Output of model: TCM-2 output options are: (1) list of
coordinates and concentration at each grid receptor (2) an array
nap of grid coordinates and concentration (3) for each receptor a
culpability list identifying the highest five major concentration
contributors and respective contributions (4) a list of the point
of maximum concentration for each scenario (5) card punch output
for input to contour plotting programs
(APP) Applications of model: Used by state air pollution control
agencies* meteorological consultants and industry for:
1. Stack parameter design studies.
2. ^valuation of the impact of new sources or source
modifications for permit application review.
3. Fuel conversion studies.
4. Monitoring network design.
5. Control technology evaluation.
6. Control strategy evaluation for SIP.
7. Prevention of significant deterioration.
(ROW) Computational system requirements - Hardware: Mainframe
Burroughs 6810/11 ;0isc storage 17K words ;Printer Card reader/punch
(LUG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Eng
ineering ;Meterology, Air Pollution
(ATP) Air Models - Type of model: Gaussian dispersion
(OAQ) yodel reviewed and approved by OAQPS? YES
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) Process used to remove pollutant from atomosphere: Combination
(THE) Sample averaging time used: more than 24 hours
(SRC) Source of pollutant: unlimited number of point and area sources;
5 sets of meteo
(AR) Area where sample was collected: level or gently rolling terrain.
(RNG) Distance traveled by pollutant from source: less than 60 km
(REF) References - User manuals, documentation, etc.:
Texas Air Control Board, "Users Guide to the Texas
Climatological Model**, Austin, Texas, August 1980. "Modifications
to the Texas Climatological Model", C. Ourrenberger, K. Zimmermann,
B. Broberg p53 Extended Abstracts, Fifth Symposium on Turbulence,
Diffusion, and Air Pollution, Atlanta, Ga., March, 1981. "A
Comparison Between Results from the TCM-2 and the CDM" C.
Durrenberger, B. Broberg, K« Zimmermann p279 Proceedings:
Speciality Conference on: Dispersion Modeling from Complex Sources,
1604
-------
Accession No- 19999999902 (cont)
St. Louis, April, 1981.
(CNM) Contact narae(s): Durrenberger,C.
(COR) Contact organization: Texas Air Control Board, Technical
Services Division
(ROR) Responsible Organization: Texas Air Control Board.
1605
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Accession Ho. 19999999903
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Storage, Treatment, Overflow, Runoff
Model
(ACR) Acronym of Data Base or Model: STORK
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: The Storage, Treatment,
Overflow/ Runoff Model (STORM) is a continuous simulation model
that provides an analysis of the quantity and quality of runoff
froo single (urban and/or nonurban) watersheds. STORM coaputes
loads and concentrations of six basic Hater quality parameters and
land surface erosion. The purpose of the program is to aid in the
sizing of storage and treatment facilities so that the quantity and
quality of storm water runoff and land surface erosion say be
controlled. The original version of the model was completed in
January 1973 by Water Resources Engineers, Inc. of Walnut Creek,
California, for the Hydrologic Engineering Center (HEC) and the
Environmental Protection Agency. Major additions since then
include the ability to compute (or specify) the quantity and
quality of dry weather flow. The program and its usage are
described in the current HEC Storm Users Manual dated August 1977.
(CTC) CONTACTS: Arlen Feldman U.S. Army Corps of Engineers,
Hydrologic, En Center
Loc: 609 Second St., Davis, CA 95616 Ph: (916) 440-2329
(STA) Data Base status: Opertional/Ongoing
(DF) Date of fora completion: 12-13-82
(CAP) Functional capabilities of model: STORM provides a means for
analysis of the quantity and quality of runoff from single (urban
and/or nonurban) watersheds. The purpose of this analysis is to
aid in the sizing of storage and treatment facilities so that the
quantity and quality of storm water runoff and land surface erosion
may be controlled. The model considers the interaction of seven
storm water elements (rainfall/snowaelt, runoff, dry weather flow,
pollutant accuBulaton and washoff, land surface erosion, treatment
rates, and detention reservoir storage). STORM computes land
surface erosion and loads and concentrations of six basic water
quality parameters (suspended and settleable solids, biochemical
oxygen demand, total nitrogen, orthophosphate, and total coliform
bacteria). The program is designed for period of record analysis
using continuous hourly precipitation data. It is a continuous
simulation model that may also be used for single events. The
aodel simulates runoff from single basins only; there is no river
or reservoir routing capability with which to connect the single
subbasin results. The HEC revised the input and output formats of
the program to conform to standardized methods and made program
modifications which include a Soil Conservation Service runoff
curve number technique, the use of hydrographs to define runoff,
pollutant accumulation in terms of pounds/acre/day, the ability to
compute or specify quantity and quality of dry weather flow,
specification of up to twenty land uses, and the choice of English
or Metric units.
(ASM) Basic assumptions of model: The model assumes that precipitation
cannot be considered without the system, and a design storm can not
1606
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Accession No. 19999999903 (cont)
be defined by itself/ but must be defined in the light of the
characteristics of the storm water facilities. The approach used
in the STORM jnodel recognizes not only the properties of storm
duration and intensity, but also storm spacing and the storage
capacity of the storm water system. In this approach/ rainfall
washes dust arid dirt and the associated pollutants off the
watershed. The resulting runoff is routed to the treatment-storage
facilities where runoff greater than the treatment rate is stored
for treatment at a later time. If storage is exceeded/ the
untreated excess is wasted through overflow directly into the
receiving waters. The magnitude and frequency of these overflows
are important in a storm water study/ so STORM provides statistical
information on washoff/ as well as overflows. The quantity/
quality/ and number of overflows are treated as functions of
hydrologic characteristics/ land use/ treatment rate/ and storage
capacity.
(INP) Input to models Input to the model include: job specifications/
hourly precipitation record/ daily temperature record/ land use
data including runoff parameters/ pollutant accumulation and
washoff data/ and land surface erosion data. The hourly
precipitation record and the daily temperature record are available
on magnetic tape from the National Weather Service/ Asheville/
North Carolina.
(OUT) Output of model: The two main types of output are statistical
information on the quantity and quality of washoff and overflow/
and pollutographs for selected individual events. The STORM
program produces four output reports: quantity analysis/ quality
analysis/ pollutograph analysis/ and land surface erosion analysis.
Input variables allow control of the level of printout which Bay be
summary only/ all events/ and/or detailed analysis of selected
events. The quantity and quality reports also include average
annual statistics of the rainf all/snowmelt; runoff; pollutant
washoff; and the quantity/ quality/ and frequency of overflows to
the receiving water. The land surface erosion report shows average
annual values for sediment production and delivery to the receiving
system.
(APP) Applications of model: This model provides a means for analysis
of the quantity and quality of runoff from sirgle (urban and/or
nonurban) watersheds. The purpose of this analysis is to aid in
the sizing of storage and treatment facilities so that the quantity
and quality of storm water runoff and land surface erosion may be
controlled. It does not contain any river or reservoir flow
routing. STORM has been widely used by the Hydrologic Engineering
Center of the U. S. Army Corps of Engineers and by the
Snviornraental Protection Agency. The model has been linked to
SMWM-RECEIVE. Medina/ Duke University/ has linked STORM to his
Simplified Continuous Receiving Hater Quality Model.
(HDtf) Computational system requirements - Hardware: Mainframe IBM 360,
CDC 6600/ or Univac 1108 ;0isc storage (o to process.) ;Magnetic
tape storage or disk ;Printer 132 position lire printer
(LNG) Computational system requirements - Language(s) used: Fortran
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
1607
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Accession No, 19999999903 (cont)
gramming ;Programming hydrologic and/or environmental
(WTP) fcater Models - Type of model: Water run-off
(ENV) Fnvironraent(s) to which model applies: Non-point Urban and
general nonurban
(CON) Processes and constituents included in model: Eutrophlcation
;Erosion and sediment ^Hydrology
-------
Accession No, 19999999903 (cont)
Engineers, Davis, California, August 1977.
Hydrologic Engineering Center "Pennypack Creek fcater Quality
Study" Special Projects Report #79-5, OS Array Corps of
Engineers, Davis California, November 1979. Medina, Miguel A., Jr.,
"Simplified Continous Receiving Water Quality! Model", Proceedings
of SWMM User Group Meeting, May 1978, Ottawa, Ontario, Canada
(CNM) Contact name(s): Feldnan,A.
(COR) Contact organization: O.s. Amy Corps of Engineers, Hydrologic,
Engineer Center
-------
Accession No* 19999999904
(DQ) Date of Questionaire: 12-02-82
(NAM) Nane of Data Base of Model: Livermore Regional Air Quality Model
and spatial variations of
terrain are treated.
(ASM) Basic assumptions of model: Both of the LIRAQ models are 2-D
horizontal models bounded on the top by a temporally and spatially
varying inversion "lid." Both models assume a logarithmic
concentration profile in the vertical based on a balance of fluxes
at the boundaries which can be different for each species. This
vertical profile is assumed to interact uith the power law wind
profile in determining horizontal transport. LIRAQ-2 does not
compensate for the effects of the vertical distribution of
pollutants in calculating transformation by chemical reactions.
LIRAQ-2 uses a chemical reaction mechanism of some complexity but
uses an approximate "lumping" schene in treating hydrocarbon
emissions and other reactive organic species. Although developed
uith the intention of maintaining the maximum fidelity to real
chemical data compatible uith the model, the chemical mechanism is,
in part, a simulation mechanism. The present version of LIRAQ-1
assumes no chemical interactions other than a deposition velocity
and/or exponential decay.
(IMP) Tnput to model: Inputs for the initial set-up and calibration of
the model include:
1) A file specifying the topographic elevation at every grid
point in the model domain, as uell as any map information (rivers
1610
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Accession No. 19999999904 (cont)
or shore outlines/ city or station locations) to be displayed on
the output.
2) Files specifying the emissions In each grid element at hourly
intervals.
3) Files giving data fields on aass consistent vertical
(through the inversion) and horizontal fluxes,/ inversion base
heights (i.e. mixing depths), atmospheric transaisslvity (based on
cloud extent)/ and horizontal and vertical eddy diffusivities.
these files are normally supplied by a meteorological data
processing code/ MASCON/ but could be provided by other processing
routines.
4) A file giving photodissociation rates as a function of solar
zenith angle for a clear sky (LIRAQ-2 only).
5) A file giving observed species concentrations at measuring
stations to be used for initializing the problem.
6) A file defining the particular problem to be run (i.e.
title/ start time/ stop tine/ species and locations for graphical
output, boundary conditions/ molecular weights and specific
emissions factors for various species).
(OUT) Output of model: Outputs provided by the model include the
following:
1) Voluminous printer files echoing all input and providing
species concentrations at the surface and averages for the mixed
layer at all grid locations at every edit interval.
2) A file containing concentrations for selected species at
selected locations as a function of tine*
3) A file containing information about the numerical integration
scheme.
4) Voluminous graphical output as described above (available from
post-processors).#
-------
Accession Ho. 19999999904 (cont)
(ATP) Air Models - Type of model: LIRAQ-1 (numerical dispersion) ;
LIRAQ-2 (numerical reactive)
(OAQ) Model reviewed and approved by OAQPS? NO
(PHP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere); Secondary
(THE) Sample averaging time used: less than 24 hours
(SRC) Source of pollutant: Model treats emission inventory that is
assessed hourly and is defined on a grid of \f 1* or 5 km.
(AR) Area where sample was collected: complex: rough terrain close to
body of water or in valley
(RNG) Distance traveled by pollutant from source: less than 60 ka
;LIRAQ-1 and LIRAQ-2 can treat from 1 to 100
(COM) Processes and constituents included in model: LIRAQ-1 ;LIRAQ-2
(REF) References - User manuals, documentation, etc.:
MacCracfcen, M.C., et al. "The Live more Regional
Air Quality Model: Concept and Development," J. Appl.
Meteorol., 17, 254-272, 1978.
MacCracken, M.C., et al.. User's Guide to the LIRAQ
Model: An Air Pollution Model for the San Francisco Bay Area,
Laurence Livermore Laboratory, Livermore, California, December
1975.
Duewer, U.H., et al. "The Livermore Regional Air Quality
Model: II. Verification and Sample Application in the San
Francisco Bay Area," J. Appl. Mateorol., 17, 273-311,
1978.
Duever, H.H., et al. "Livermore Regional Air Quality Model
(LIRAQ) Transfer to EPA" Laurence Livermore Laboratory Report
OCRL-52864, 1980 (available from NTIS). Also to be published
by EPA.
ABAC, et al "Application of Photochemical Models: Volume I:
The Use of Photochemical Models in Urban Ozone Studies"
EPA Report 450/4-79-025, 1979. Penner, J.E. and J.J. Walton, Air
Quality Model Update, Laurence Liveraore National Laboratory
report, UCID-19300, January 1982.
(ROR) Responsible Organization: Laurence Livermore Laboratory.
1612
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Accession No, 19999999905
(DQ) Date of Questionaire: 12-02-82
(HAM) Name of Data 3ase of Model: One-Dimensional Groundwater Mass
Transport Model
CACR) Acronym of Data Base or Model: GWMTMI
(MED) Media/Subject of Data Base or Model: Water
(ABS) Abstract/Overview of Data Base or Model: G&MTMl is a
deterministic/ one-dimensional/ unsteady-state/ analytical model
which simulates constituent concentrations in groundwater systems*
It is based on the convective-dispersive mass transport equation
modified for first order decay. The analytical solution is based
on £ semi- infinite medium with the following surface boundary
condition: C - Cexp (-ot); this allows the surface concentration
to be constant or exponentially varying (e.g./ through dilution
processes). It is typically applied in case of vertical
infiltration of uasteuaters. The soil may be saturated or
unsaturated (provided the moisture content is constant); the
vertical seepage velocity must be constant.
(CTC) CONTACTS: Prof. Robert W. Cleary Princeton Assoc.
Loc: P.O. Box 2010 Ph: (609) 924-4163
Loc: Princeton/ N.J. 08540
(STA) Tata Base status: Operational/Ongoing
(OF) Date of form completion: 01-17-83
(CAP) Functional capabilities of model: The program is user-oriented
requiring no previous FORTRAN experience. Its digital output is in
matrix form giving concentration versus distance at given times or
concentration versus time at given distances. It accounts for
advection/ dispersion and first order decay.
(ASM) Basic assumptions of model: The model assumes a homogeneous soil
and a constant seepage velocity. The constant seepage velocity
requirement is net under steady/ saturated conditions or steady/
constant moisture content/ unsaturated conditions.
(INP) Input to model: Data is inputted as FORTRAN statements. The
model requires only four pieces of data: the dispersion
coefficient/ the kinetic decay constant/ the seepage velocity and
the surface constant (if the surface concentration is not constant).
(OUT) Cutput of model: Concentrations are printed out at any number of
specified (read in as data cards) space and time positions. It is a
very simple model to operate.
(APP) Applications of model: The model was developed for the
Nassau-Suffolk Regional Planning Board (Lee Koppelraan/ Executive
Director) as part of a large 208 project. It was applied to
wastewater recharge basins where the depth to water was about 30
feet. It has been distributed widely through short courses dealing
with groundwater pollution and has found similar applications
throughout the country.
(HDH) Computational systea requireaents - Hardware: Mainframe IBM
360/91; also minicomputer using less than 100K Disc storage 100K
core storage
(LNG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements: Operator Knowledge/Skills: non
e/ 1/2 hour learning time
(WTP) V'ater Models - Type of model: Ground water
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Accession Mo. 19999999905 (cont)
(CPL) Complexity level of model: one dimensional
(REF) References - User manuals, documentation, etc.:
Cleary, R.M., Final 208 Report to the Nassau-
Suffolk Regional Planning Board, flauppauge, Ne« York,
December, 1977.
(CHM) Contact narae(s): Cleary,P.R.
(COR) Contact organization: Princeton Assoc.
(ROR) Responsible Organization: Princeton Associates.
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Accession No. 19999999906
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: Two-Diraensional Grounduater Mass
Transport Model
(ACR) Acronym of Data Base or Model: GHMTM2
(MED) Vedia/SubJect of Data Base or Model: Water
CABS) Abstract/overview of Data Base or Model: GKMTM2 is based on an
analytical solution to the unsteady-state, convective-dispersive
mass transport equation which describes the concentration
distribution in two-dimensional groundwater systems. The model
accounts for advection, dispersion in two dimensions, first order
decay and an exponentially decaying, Gaussian boundary condition.
The model can be used as an excellent test of available two-
dimensional, unsteady-state, numerical models; the degree of
numerical models; the degree of numerical dispersion and
oscillations for different numerical solution schemes can be easily
determined. In addition to exactly checking numerical models, this
Gaussian boundary condition model is a valuable tool, in itself,
for estimating the two- dimensional (areal or vertical
cross-section) concentration pattern doungradient from sanitary
landfills, wastevater lagoons or other groundwater pollution
sources.
(CTC) CONTACTS: Prof. Robert w. Cleary Princeton Assoc.
Loc: P.O. Box 2010 ph: (609) 924-4163
Loc: Princeton, New Jersey 08540
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-17-83
(CAP) Functional capabilities of model: The time-varying Gaussian
boundary condition is general allowing any variance, peak
concentration and center location. The exponential decay
multiplier may be used or onitted. The groundwater aquifer can be
any size.
(ASM) Basic assumptions of model: The model is applicable where there
is a uni-directional, constant seepage velocity and the dispersion
coefficients (longitudinal and lateral) are constants. This
presumes steady, horizontal flow in the homogeneous aquifer.
(IMP) Input to model: System parameters are inputted as FORTRAN
statements in the main program. Space and tine positions where
concentration predictions are desired are inputted as data cards.
The program is user-oriented requiring the punching of less than 10
cards for parametric information.
(APP) Applications of model: The model was developed for the
Nassau-Suffolk Regional Planning Board (Lee Koppleman, Executive
Director) as part of a large 208 project. It was applied to
simulate the two-dimensional chloride distribution doungradient
from the Babylon sanitary landfill. It was also used to check the
numerical accuracy of several solution schemes of two- dimensioanl,
numerical models of groundwater quality. It has been distributed
widely through short courses dealing with groundwater pollution and
has been used principally to simulate leachate plumes from
landfills and check the accuracy of two-dimensional, numerical
models.
(HOW) Computational system requirements - Hardware: Mainframe IBM
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Accession No. 19999999906 (cont)
360/91; also mini computer using less than 100 Disc storage 10OK
core storage.
(LUG) Computational system requirements - Language(s) used: Fortran IV
(OSK) Computational system requirements: Operator Knowledge/Skills: Non
e; learning tine 1/2 hour
(HTP) Water Models - Type of model: Ground water
(CPL) Complexity level of model: aulti dimensional
(REF) References - User manuals, documentation, etc.:
Cleary/ R.W., Final 208 Report to the Nassau-Suffolk
Regional Planning Board, Hauppauge, New York, December 1977.
(CUM) Contact naroe(s): Cleary,P.R.
(COR) Contact organization: Princeton Assoc.
(ROR) Responsible Organization: Princeton Associates.
1616
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Accession No. 19999999907
(DQ) Date of Questionaire: 12-02-82
(NAM) Name of Data Base of Model: National Residuals Discharge
Inventory
(ACR) Acronym of Data Base or Model: NRDI
(MED) Media/Subject of Data Base or Model: Water ;Industry/econoraic
(ABS) Abstract/Overview of Data Base or Model: The NRDI is a
quantitative assessment of residual generation and discharges
(total suspended solids, BOD, nitrogen, phosphorous, and nutrients;
and of residual reduction technology costs in each of 3,111
counties or county approximations in the contiguous U.S. Data for
industrial, municipal, urban runoff, and non-irrigated agriculture
sources are available for each county. However, the data are not
displayed at the county level, but rather are aggregated for
purposes of analysis by the Water Resources Council's 99 aggregated
sub-areas (ASAs), the 18 Water Resource Regions (WRRs) and by the
nation. The model was developed under the auspices of the National
Academy of Sciences, Washington, D.C. MM*
(CTC) CONTACTS: Ralph A. Luken U.S. EPA, Planning and Management ,
Office of Policy Analysis* Loc: 401 M Street, S.K. hashington, D.C.
20460 Ph: (202) 382-5490
(STA) Data Base status: Operational/Ongoing
(DF) Date of form completion: 01-21-83
(CAP) Functional capabilities of model: The NRDI is a series of
FORTRAN programs and data bases which provide estimates of cu"ent
and projected discharges of wastes (total suspended solids, BOD,
nitrogen and phosphorus) to surface waters, and Capital and
operation and maintenance costs of treatment facilities. The model
estimates pollutant discharges and costs by industrial or municipal
facility for approximately 40,000 point-source discharges, and by
cou^ti for urbln"storm runoff'and non-irrigated agriculture. These
detailed estimates are then aggregated as desired. Discharges and
costs are estimated for conditions of (1) no control, (2) controls
in place in 1973, (3) 1977 standards, and (4) 1983 standards. The
NRDI allows for an evaluation of policy alterna*ives *°,!?!„»?;"
application of residual reduction technologies to legislatively
defined (P L 92-500) point sources. These policies "fleet
alternatives where in a given ASA or WRR, achievement of the 1983
effluent limitations would not make a significant improvement in
t"al residual reactions and ambient water quality, and where a
given level of residual reduction could be achieved at a lower cost
without the uniform application of residual reduction technology to
point sources.
and discharge residuals, (2) a system for
increased industrial and population growth, J^) an index of
1617
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Accession No. 19999999907 (cont)
discharges, discharge and cost estimates are based on simulation of
specific end-of-pipe technologies for discharge reduction.
Discharge conditions in 1973 as veil as 1977 and 1983 standards are
estimated for specific industrial facilities or industry subgroups.
For municipal facilities, the 1974 EPA Heeds Survey is used. For
urban runoff, required treatment is estimated based on work done
for the National Commission on Water Quality; for non-irrigated
agriculture, information from the 1967 Conservation Needs Inventory
is used.
(IMP) Input to model: Major inputs to the NRDI include the EPA Needs
Survey, the Conservation Needs Inventory, County Business Patterns,
City-County Data Book, and Census data. A detailed industrial
source inventory was developed for the model. Thus, the model
contains information on identifiable point and areal source
residual generating activities which cover most uaterborne residual
generating activities. Information included about these
activities, where appropriate and available, are location of
activity, measures of production (physical output, employees, land
area, or population), type of production process, and current
residual reduction technologies being used.
(OUT) Output of model: Outputs are produced by county-aggregate unit,
and source category or subcategory. A variety of alternative
policies can be selected for solution in the NRDI. These policies
include both uniform and non-uniform abatement policies and can
simulate controls on areal as veil as point sources. The outputs
from each policy alternative are: residual generation, residual
discharge, abatement costs/ and residuals dilution index. The
basic policies used to date are discussed below:
1) No control - This policy estimates residuals discharge
if no control technology is used.
2) 1973 controls - This policy estimates discharge and
costs based on control technology in place in 1973.
3) BPT/ST - This policy estimates effects of the 1977
standards of the P L 92-500: Best Practicable Treatment for
industry and Secondary Treatment for municipalities.
4) BAT/BPVTT - This policy estimates the effects of the 1983
standards for industry and secondary treatment for municipalities
supplemented with tertiary facilities when requested in the EPA
Needs Survey.
5) BAT/BPWT* - This policy is identical to (3) for
industrial sources but includes filtration for all municipalities
not requesting treatment more stringent than secondary in the EPA
Needs Survey.
6) Non-irrigated agricultural control - Costs and residual
implications of implementing practices outlined in the 1967
Conservation Needs Inventory are included.
7) Urban stori control - Costs and residual implications
of one of five urban storm control strategies (combined, seperate
storm, and unsewered) is simulated.
8) Ocean discharges - Effects of discharge and costs for ocean
counties are excluded. This function is used to simulate lover
levels of treatment for ocean discharges based on using a specified
1618
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Accession No. 19999999907 (cont)
set of counties.
9) New source performance standards - In this policy,
residual discharges and costs for industrial growth are based on
new source performance standards {approximated by BAT).
10) Limited technology - Simulation of stringent effluent
limitation policies can be United to ASA with relatively bad water
quality.
11) Cost effective strategy - This policy used data on cost
per quantity of residuals removed to identify cost-effective
solutions in each ASA. Combinations of these policy components can
be combined in a single run if desired.
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Accession No. 19999999907
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Accession No. 19999999908
(DQ) Date of Questionaire: 12-02-82
(NAM) Kame of Data Base of Model: Regional Emissions Projection System
(ACR) Acronym of Data Base or Model: REPS
(MED) Kedia/Subject of Data Base or Model: Air
(ABS) Abstract/Overview of Data Base or Model: The REPS model is a
series of FORTRAN and PL/I programs which utilize data on existing
air pollution sources, projected energy use to projected emissions
(and proxy air quality measures) for five of the criteria
pollutants (all except oxidants and lead) for the 243 Air Quality
Control Regions (AQCR's) in the United States. The model Has
originally developed by the U.S. Environmental Protection Agency;
the revised model is available from the Energy Information
Administration of the U.S. Department of Energy.
(CTC) CONTACTS: William tteygandt U.S. Department of Energy
Loc: Washington/ DC 20461 Ph: (202) 633-8505
(STA) Data Base status: Discontinued
(DP) Date of form completion: 01-21-83
(CAP) Functional capabilities of model: REPS permits the examination
of projected emissions under changes in (1) environmental control
policy/ (2) projected energy use/ or (3) patterns of economic
growth. Ambient proxy measures of air quality are based on
emission density and population exposure. Outputs can be generated
in tabular form or map displays. Forecasts can be made for any
year from 1980-2000.
(ASM) Basic assumptions of model: The REPS model relies on the
National Emissions Data System (NEDS) for base year (1975) and
estimates of future emissions from present sources. A constant
annual retirement rate is applied to all AQCR's and fuel-burning
source categories. Regionallzation of expected growth is based on
the Department of Commerce OBERS projections/ the Energy
information Administration's fuel use projections/ and assumptions
concerning the expected patterns of fuel switching.
(INP) Input to model: Major inputs are the NEDS file/ OBERS
projections by AQCR and fuel use projections by Federal Region.
The user May also provide information on specific synthetic fuel
facilities and/or information on the desired environmental control
policy.
(OUT) Cutput of model: Projected regional residual emissions
(pollutant tons) in map or tabular form.
(APP) Applications of model: REPS results have been used for the
following:
1) The Department of Energy report/ 1985 Air Pollution
Emissions/ a study of the regional air emission impacts of the
National Energy Plan.
2) The environmental chapter in the Energy Information
Administrator's Annual Report to Congress/ 1978.
3) Environmental analysis of elements of the proposed National
Energy Supply Strategy under development by the Department of
Energy. TECHNICAL CONTACT: Milliam ileygandt U.S. Department of
Energy Washington/ D.C. 20461 FTS 633-8505 COM 202/633-8505
(HDH) Computational system requirements - Hardware: Mainframe IBM 370
;Disc storage 200K bytes
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Accession Ho. 19999999908 (cont)
(LUG) computational system requirements - Language(s) used: Fortran
PL/1
(OSK) Computational system requirements: Operator Knowledge/Skills: Pro
gravning ^Engineering
(ATP) Air Models - Type of model: Numerical reactive
(OAQ) Model reviewed and approved by OAQPS? NO
(PMP) Production method of primary pollutant in model: Primary
(emitted directly into atmosphere)
(MPR) process used to remove pollutant from atomosphere: Physical
(SRC) Source of pollutant: REPS is air emissions rather than air
quality model
(REF) References - User manuals, documentation, etc.:
Booz/ Allen/ and Hamilton. Regional Emission
Projection System—Systen Documentation. January 1977.
Energy Information Administration. 1977 Annual Report to
Congress. Volume II, April 1978.
Pechan, E.H. An Air Emissions Analysis of Energy Projections
for the Annual Report to Congress, in preparation.
Pechan, E.H. 1985 Air Pollution Emissions. Department of
Energy DOE/PE-0001, Government Printing Office, December 1977.
0. S. Environmental Protection Agency. AEROS Manual Series
Volume I: AEROS Overview. EPA-450/2-76-001, February 1976.
U.S. Environmental Protection Agency. AEROS Manual Series
Volume II: AEROS User's Manual. EPA-450/2-76-029,
December 1976.
U.S. Environmental Protection Agency. AEROS Manual Series
Volume V: AEROS Manual of Codes. EPA-450/2-76-005, April
1976.
U.S. Environmental Protection Agency. Compilation of Air
pollutant Emission Factors. Second Edition, AP-42, Parts A
and B, February 1976.
(CNM) Contact name(s): Heygandt,W.
(COR) Contact organization: U.S. Department of Energy
(ROR) Responsible Organization: U.S. Department of Energy.
1622
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Accession No. 19999999909
(DQ) Date of Questionalre: 12-02-82
(NAM) Name of Data Base of Model: Agricultrual Watershed Runoff Model
, grease, total
coliforras, fecal coliforras, NH<3>, organic nitrogen, nitrite and
nitrate, phosphate, orthophosphate, mercury, copper, zinc, lead,
chromium, cadmium, and arsenic. AGRUN is one module of a larger
set of compatible programs which include a runoff model (AGRUN), a
transport model, and a receiving model, and AGRUN has an interface
subroutine to connect it with the other two. This model uses the
Universal soil Loss Equation to compute the suspended solids source
loading rates, and it assumes that there is no decay of BOD or
conversion of nitrogen forms.
(C?C) CONTACTS: Dr. Larry Roesner Camp Dresser & McKee Inc.
Loc: 7630 Little River Turnpike Annandale, VA 22003 Ph: (703)
642-5500
(STA) Data Base status: Operational/ongoing
(DF) Date of form completion: 01-27-83
(CAP) Functional capabilities of model: The Agricultural Watershed
Runoff Model has the capability to simulate stora runoff
hydrographs and pollutographs for up to 22 hiater quality parameters
from agricultural watersheds. The watershed Bay be subdivided into
as many as 200 subareas, and up to two crop types from a list of
five say be specified for each subarea. Crop types include corn,
bears, pasture, oats, and hay. The tributary drainage system may be
subdivided into as many as 200 channels, and the system must be
dendritic in form, cross sections aay be triangular, trapezoidal,
or rectangular in shape. The user has the option of representing
infiltration by the Horton equation alone, in which case interflow
computations are neglected, or he may specify the additional data
which will be used to compute the contribution to interflow to
storm runoff. Computations of water quality can be made for up to
22 conservative constituents whose number is specified by the user.
Constituents modeled include: total suspended solids, non-
settleable suspended solids, TDS, BOD, COD, chlorides, S0<4>,
grease, total coliforms, fecal coliforms, NH<3>, organic nitrogen,
nitrite and nitrate, phosphate, orthophosphate, mercury, copper,
zinc, lead, chromium, cadmium, and arsenic. Only total suspended
solids, BOD, and fecal coliforns have been calibrated for this
model. AGRUN has been used to simulate the surface runoff
hydrograph for both urban and agricultural watersheds, and because
it assumes no decay of BOD or conversion of nitrogen forms, the
model should be considered for relatively short-term storm episodes
(ASM) Basic assumptions of model: The AGRUN model uses the Universal
1623
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Accession No. 19999999909 (cont)
Soil Loss Equation to compute the suspended solids source loading
rates, and Morton's equation to compute infiltration rates. An
iterative Newton-Raphson technique is the basis for the
determination of water depth and outflov rates. Velocity
computations are made on the basis that flow only occurs when the
soil Is above field capacity. The model assumes that there is no
decay of BOO and that there is no conversion of nitrogen foras.
(IMP) Input to model: The Agricultural Watershed Runoff Model requires
a large card-image input data base. Input data for the model fall
into seven categories, and there are: 1) input and program control
data/ 2) precipitation data/ 3} drainage channel specifications/ 4)
land use hydrogeoaetric data/ 5) watershed specifications/ 6) soil
characteristics/ and 7) output control information. For each
watershed subarea/ the surface area/ width/ and slope must be
specified. For each land use type specified for each subarea/ the
Manning n/ surface depression storage/ and Horton infiltration
coefficients must be entered as input data. Drainage channel
specifications must include the length/ invert slope/ and Manning
n/ plus the appropriate cross section data. If the user wishes to
specify the additional data which will be used to compute the
contribution of interflow to storm runoff/ rather than by
representing infiltration by the Horton equation alone/ the
following data are required for each subarea:
1) number of soil layers above the groundwater table/ 2)
depth of each soil layer/ 3) soil permeability coefficient/
4) soil field capacity/ 5} soil saturation level/ 6) present
field capacity available at the beginning of the storm/ and
7) constant baseflow from the watershed. Constituents must
be specified by the user.
(OUT) Output of model: Output produced by the model includes a
print-out of the input data/ rainfall hyetographs/ runoff
hyetographs/ and a variety of charts representing the
concentrations of the constituents. TECHNICAL CONTACT: Dr. Larry
Roesner Camp Dresser & McKee Inc. Little River Turnpike Annandale/
?A 22003 COM 703/642-5500
(HOW) Computational system requirements - Hardware: Mainframe Univac
1108 ;Disc storage 520k bytes ^Printer 120
(LMG) Computational system requirements - Language(s) used: Fortran
(QSK) Computational system requirements: Operator Knowledge/Skills: Pro
gramming ^Engineering
CHTP) Water Models - Type of model: Water quality
Water run-off
(EN?) Environment(s) to which model applies: Stream/river >Non-point
agricultural
(COR) Processes and constituents included in model: Erosion and
sediment ^Hydrology ;Hydraulics ;Quality process Eutrophication/
Nutrients
(CPL) Complexity level of model: transient mass balance ?one
dimensional
(REF) References - User manuals/ documentation/ etc.:
Roesner/ L.A./ Zison/ S.W./ Monser/ J.R./ and Lyons/
T.C./ Agricultural Watershed Runoff Model for the lowa-
1624
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Accession No. 19999999909 (cont)
Cedar River Basins, prepared for the Environmental Protection
Agency, Systems Development Branch/ Washington/ D.C., by
Hater Resources Engineers/ Inc./ under contract No. 68-01-0742/
November/ 1975.
(CNM) Contact nane(s): Roesner/L.
(COR) Contact organization: Camp Dresser & McKee Inc.
(ROR) Fesponsible Organization: Camp Dresser and McKee/ Inc..
.8. GOVERNMENT PRINTING OFFICE: 1983 381 082 "* 1 8
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