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                                 EPA 450/2-81-078
   A  Screening Procedure for the
Impacts  of Air Pollution Sources on
       Plants,  Soils, and Animals
                       by

                A.E. Smith and J.B. Levenson
                Argonne National Laboratory
                 9700 South Cass Avenue
                   Argonne, II 60439
              Contract No. EPA-IGA-79-D-X0764
                     Prepared for

           U.S. ENVIRONMENTAL PROTECTION AGENCY
            Office of Air Quality Planning and Standards
           Research Triangle Park, North Carolina 27711
                   December 12, 1980

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The guideline series of reports is being issued by the Office of Air Quality
Planning and Standards (OAQPS) to provide information to state and local
air pollution control agencies; for example, to provide guidance on the
acquisition and processing of air quality data and on the planning and
analysis requisite for the maintenance of air quality.  Reports published in
this series will be available - as supplies permit - from the Library Services
Office (MD-35), U.S. Environmental Protection Agency, Research Triangle
Park, North Carolina 27711; or, for a nominal fee, from the National
Technical Information Service,  5285 Port Royal Road, Springfield, Virginia
22161.
                   Publication No. EPA-450/2-81-078
                                    11

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                                   CONTENTS
ACKNOWLEDGMENTS  .............................  vi

1  INTRODUCTION  .............................    1

   1 . 1  Background ............................    1
   1 . 2  Scope  ..............................    1

2  OVERVIEW  ...............................    3

3  AIR QUALITY RELATED IMPACT DATA ....................    7

   3.1  General  .............................    7
   3.2  Natural  Vegetation and Crops ...................    8

        3.2.1  General ..........................    8
        3.2.2  Screening Concentrations for Ambient Exposures  ......  10
        3.2.3  Synergisms ........................  15
        3.2.4  Screening Concentrations for Soil and Plant
               Tissue Exposures  .....................  16

   3.3  Soils  ..............................  17
   3.4  Fauna  ..............................  22

4  TRACE ELEMENT AIR QUALITY DATA ....................  24

5  SCREENING PROCEDURE ..........................  25

   5.1  Methodology  ...........................  25

        5.1.1  Description ........................  25
        5.1.2  Estimating Maximum Concentrations .............  28
        5.1.3  Screening and Deposition .................  33

   5.2  Example  Screen and Significant Emission Rates  ..........  42

        5.2.1  Example Screen  ..... .  ................  42
        5.2.2  Significant Emission  Rates  ................  44

APPENDIX A:  ESTIMATES OF MAXIMUM GROUND LEVEL CONCENTRATIONS  ......  49

APPENDIX B:  POLLUTANT SENSITIVITIES OF PLANT SPECIES  ..........  59

APPENDIX C:  TRACE ELEMENT AIR QUALITY DATA ...............  71

APPENDIX D:  EFFECTS OF DEPOSITED PARTICULATE MATTER ........... 107

REFERENCES ................................ Ill
                                      111

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                                   TABLES
2.1  Regulated Pollutants .................. ......
2.2  Pollutants Screened .........................
3.1  Screening Concentrations for Exposure to Ambient
     Air Concentrations .........................
3.2  Screening Concentrations of Gaseous Pollutants Compared
     to Ambient Criteria .........................   ^
3.3  Synergisms of Gaseous Pollutants ..................   6
3.4  Screening Concentrations for Exposure of Vegetation to
     Pollutant Concentrations in Soil and Tissue .............  17
3.5  Range of Endogenous Soil Concentrations of Selected Elements ....  20
3.5  Plant: Soil Concentration Ratios ...................  22
3.6  Dietary Trace-Element Concentrations Toxic to Animals ........  23
5.1  Steps in Screening Procedure ....................  29
5.2  Pollutants and Averaging Times ...................  31
5.3  Ambient Screening Concentrations ..................  34
5.4  Solubilities of Endogenous Trace Elements ..............  38
5.5  Equivalent Exogenous Soil Screening Concentrations .........  40
5.6  Significant Emission Rates for Direct Acting Pollutants .......  46
5.7  Significant Emission Rates for Trace Elements ............  47
5.8  Summary of Representative Stacks ..................  43
A.I  Dispersion Coefficient Parameters and Maximum
     Concentration Coefficient ......................  53
A. 2  Averaging Time Conversion Factors ..................  56
B.I  Sulfur Dioxide Sensitivity of Crop Species . ............  61
B.2  Sulfur Dioxide Sensitivity of Natural Vegetation ..........  62
B.3  Ozcne Sensitivity of Crop Species ..................  65
B.4  Ozone Sensitivity of Natural Vegetation ...............  66
B.5  Nitrogen Dioxide Sensitivity of Crop Species ............  68
B.6  Nitrogen Dioxide Sensitivity of Natural Vegetation .........  69
C.I  Air Quality Data for Arsenic ....................  73
C.2  Air Quality Data for Cadmium ....................  75
C.3  Air Quality Data for Chromium ....................  80
C.4  Air Quality Data for Fluoride Ion ..................  84
C.5  Air Quality Data for Lead .......... . .......          85
C.6  Air Quality Data for Manganese ............                at

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                               TABLES (Cont'd)

C.7  Air Quality Data for Selenium	100
C.8  Air Quality Data for Vanadium	102
C.9  Air Quality Data for Zinc	104

                                   FIGURES

3.1  S02 Dose-Injury Curves for Plant Species 	  12
3.2  N02 Dose-Injury Curves for Plant Species 	  13
3.3  Concentrations of Some Trace Elements Toxic to Terrestrial Plants. .  18
3.4  Range of Endogenous Concentrations of Trace Elements 	  21
5.1  Pollutant Pathways  	  26
5.2  Flowchart of Screening Procedure 	  30

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                             ACKNOWLEDGMENTS

       The authors wish  to express  their  appreciation  to  K. Robeck  and
S. Zellmer  of the Energy  and  Environmental Systems  Division of Argonne
National  Laboratory  for their help  in  assembling the data on which  the
screening  concentrations were based  and  for helpful  discussions during  the
development of the screening procedure.
                                   VI

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                               1  INTRODUCTION

1.1  BACKGROUND
       Section  165  of Che  Clean  Air Act* requires  precons truce ion  review of
major  emitting  facilities  to  provide for the  prevention of  significant de-
terioration (PSD) and charges Federal Land Managers  (FLMs) with an affirmative
responsibility  to protect - the  air  quality  related  values of  Class  I areas.
Regulations? implementing  these provisions require:
       •  An analysis of the impairment to visibility, soils, and
          vegetation (52.21 (o)) and
       •  A notice  from the EPA Administrator to the appropriate FLM
          of any  permit application  from a source whose emissions
          would affect a Class I area  (52.21 (p)).
For  sources more  than  10 km  from any  Class I  areas,  exemptions  provide
that  no  analysis of  impairment  need be done if emission  increases  are below
specified limits.*   The  analysis should  address the impairment due to general
secondary growth  associated with the source and need  not  address the impacts
on  vegetation  having no  significant commercial or  recreational value.   For
impacts  in  Class I  areas, consultation  between EPA and the  FLM is  required.

1.2   SCOPE
       The  entire  subject of air  quality related  values and  impairment  to
these values is  currently under investigation.   For example,  although  some
values related  to  plants,  soils,   and  visibility  are  "air  quality  related
values," the term itself remains  to  be defined  in a  fashion appropriate to the
review of  PSD  permit applications and air quality reviews.   Much of the data
required to  relate  ambient concentrations of pollutants to impairment of these
values is  currently lacking.  However, the  requirements  of  52.21 (o)  and (p)
need  to  be  addressed  now  while  additional  investigations are  being  carried
out.
*The "de minimis" values are given in Sec. 52.21 (b)(23)(i) of the PSD
 regulations.2

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       The  information  and  screening  procedure  presented here provide interim
guidance:
       •  To aid in determining whether emissions are significant
          or whether there are significant air quality impacts under
          Sec. 52.21 (o) and
       •  To aid in flagging sources which should be brought to the
          attention of an FLM under Sec. 52.21 (p).
       Impacts  on  vegetation  and  soils  are  the  principal   areas  addressed
by  the  procedure  which  thus takes a  limited view  of  the possibly broad scope
of  air quality related values.  A selected review of impacts on fauna has also
been  included  and  the  odor potential  of  regulated pollutants  is  addressed.
       This procedure is intended  for  use by  air quality engineers and is not
a manual for the assessment of impacts on plants, soils,  and other air quality
related values such as would be suitable for an  ecologist.  A handbook provid-
ing for such detailed assessments  is  being  prepared for  the FLMs.  In keeping
with  the screening  approach,  the  procedure  provides conservative,  not defini-
tive  results.  However,  a source which passes  through  the screen without being
flagged for detailed analysis cannot  necessarily be considered safe.   Species
more  sensitive to particular pollutants than species  considered  in this study
probably exist.  Further research  may  indicate that averaging  times different
from  those used  here are  controlling.   When available, such information
could be easily included in the screening procedure by changing the screening
concentrations presented here.
       Based on  estimates  of typical  stack parameters,   significant  emission
levels  have been  estimated.    These   estimates  are not  intended  to  replace
source-specific screens, but  do  indicate  what  sizes of sources  appear  most
likely to cause significant impacts on plants  and soils.

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                                 2  OVERVIEW

       The  procedure  presented here  provides a  simple  method for  assessing
the potential  a source has  for  adversely affecting some air  quality  related
values.   In particular, the  potential  for impacts  on plants,  soils, and
animals  is assessed.  The  approach  taken is similar  to the "de  minimis"
approach  used  by  EPA in the  PSD regulations.3   in  the procedure  presented
here, the  minimum levels at which  adverse  effects have  been  reported in the
literature  are  used  as screening concentrations.   These screening concentra-
tions can be concentrations  of pollutants in  the  ambient air,  in  soils,  or  in
aerial  plant  tissues.  They  have been  developed by searching  the  review
literature; few original  sources have been  consulted.   The analyst applying
this  procedure  must  read the  material  in Sec.  3 which lists  these  screening
concentrations and provides background on them in order to  apply and  interpret-
them appropriately.
       Section  5  describes  a seven step process for screening a source.  The
procedure  begins  by  estimating  the maximum ambient concentrations caused'  by
the source  for the averaging times specified for the screening  concentrations.
For  some pollutants these  maxima are compared directly to the screening
values.   For other pollutants  (trace  elements) estimates of deposition in the
soil  and subsequent  uptake  by plants are  made  based  on  an  estimate  of the
maximum  annual  concentration.   The estimated concentrations of the  pollutant
in the soil and aerial  plant parts  are then compared to  appropriate  screening
concentrations.   Concentrations  in  excess of any of the screening concentra-
tions would indicate that  the source might  have  adverse  impacts on plants,
soils, or animals and that  the actions required by 40 CFR 52.21  (o) and (p)
need to be  taken.  For situations where modeling results  are not available for
the source, significant emission levels corresponding to  the various  screening
concentrations are developed in Sec. 5.2.   In these cases,  emissions  in excess
of the significance levels would trigger the additional actions.
       The  estimation of potential impacts on  plants, animals,  and  soils  is
extremely  difficult.    The  screening concentrations  provided here  are not
necessarily safe  levels  nor are  they levels  above which concentrations will
necessarily cause  harm  in a particular  situation.   Effects data for plants,
animals,  and  soils are  under  constant revision  and reevaluation.   There  is

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good deal of controversy among experts.   In  addition,  this  procedure is based
upon  a  simplistic view  of extremely  complex systems  in  which single  value
estimates are not possible  and  in which the number of  variables  is  extremely
large.   Many simplifying  assumptions  have  been involved  in developing  the
procedure and are discussed in Sec.  3.
       Ideally,  the screening procedure should address  the  impacts of  all  the
pollutants  currently regulated  under the  Clean Air  Act, but  as  shown  in
Table 2.1,  screening  concentrations were  found  for only  half the  regulated
pollutants.   Ozone and TSP  are  discussed  in Sec. 3.1.  Of  the  remaining sub-
stances  for  which  screening concentrations were  not found, methyl mereaptan,
dimethyl sulfide, dimethyl  disulfide,  carbon disulfide, and carbonyl  sulfide
are  regulated because of  their  odor potentials.  Odor  is an  air quality
related  value  and Sec.  52.21 (b)(23)(i)  of the PSD  regulations2 gives  "de
minimis" emission  levels for  reduced  sulfur  (RS)  and  total  reduced  sulfur

                      Table 2.1    Regulated Pollutants
                          Screening Concentrations
                  Available              Not  Available
                  CO                   TSPa
                  N02                  Asbestos
                  S02                  Sulfuric  Acid  Mist
                  03^                  Vinyl  chloride
                  Lead                 Methyl Mercaptanc
                  Mercury              Dimethyl  Sulfide0
                  Beryllium            Dimethyl  Disulfidec
                  Fluoride             Carbon Disulfide0
                  Hydrogen Sulfide     Carbonyl  Sulfidec
                  aFraction of TSP present as trace ele-
                   ments treated through deposition and
                   uptake by plants.
                  ^Screening concentration available  but
                   no simple procedure for estimating the
                   ozone impact of a single source  is
                   currently available.
                  cRegulated indirectly as constituents of
                   reduced sulfur or total reduced  sulfur.

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(TRS) based on odor.   RS  and TRS include these sulfur compounds.   Sources not
emitting more than these "de minimis" levels (10 t/yr for both RS  and TRS) are
not expected  to  have a significant  odor impact and hence should  not  require
any  additional  review  for  impacts  on  air quality  related  values.   If  the
10  t/yr  "de  minimis"  level is  exceeded,  the appropriate FLM might want  to
evaluate  the  potential for an odor  problem.   Whether  or  not these  sulfur-
containing compounds  might  adversely affect  plants,  soils,  or animals  could
not  be  determined.   Riere  was one  questionable  indication  that  methyl  mer-
captan might  be  toxic  to  plants  at concentrations near  150,000  ug/m3,  far
above likely  ambient concentrations.^  Information for asbestos, sulfuric acid
mist, and vinyl chloride  was not  available in the review literature  consulted
for this work.
       Pollutants which  can  be  screened by this  procedure  are listed  in
Table  2.2 according  to whether  they are  screened  for  potential effects  on
plants or on  animals and according to whether the potential effects are caused
directly by concentrations  of  the  pollutant in the  ambient air or  whether the
potential effect  is exerted indirectly  through the  soil  or the diet.  Absence
of  a pollutant  from  a particular column in  the  table  does not  necessarily
mean that impacts can not result  from  the pollutant acting  through the
corresponding pathway.   Such  absence simply  means  that  no data to provide a
suitable  screening concentration were found in the review literature  consulted.

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                Table 2.2.  Pollutants Screened
Potential Impacts on

Direct
Ambient
Impact
S02
°3
N02
CO
H2S
Ethyl ene
Fluoride







Plants
Indirect through Direct
Deposition and Ambient
Uptake Impact
Arsenic
Boron Beryllium
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead Lead
Manganese
Mercury
Nickel
Selenium
Vanadium
Zinc
Animals
Indirect through
Plants in
Diet
Arsenic

Cadmium

Cobalt
Copper
Fluoride
Lead
Manganese

Nickel
Selenium
Vanadium
Zinc
aThe other five sulfur-containing compounds are screened for
 odor impacts during the "de minimis" determinaion for RS and
 TRS.

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                     3  AIR QUALITY RELATED IMPACT DATA

       NOTE:  In  this  chapter  and throughout  this work,  a distinction is made
between  parts  per million  by  volume (ppmv)  and  parts per million  by weight
(ppmw).   The  former,  ppmv,  is the  unit more  familiar to  air quality analysts
and  is  used,  for  example,  to express  ambient concentrations  and  standards.
The  latter, ppmw, or an equivalent (mg/kg, ug/g)> is frequently  used  to
express  concentrations of elements  in  soils, plants,  and  animals.   The air
quality  analyst  should be aware of the difference, because  the units are not
equivalent.  The  unit  ppmv  is  normally  used only in expressing concentrations
of components of gaseous mixtures.

3.1   GENERAL
       Data  to  be used  in  screening  impacts on  three  air  quality  related
values (vegetation and crops, soils, and fauna) are discussed in this section.
Vegetation  and crops receive the  greatest  amount  of attention, reflecting the
availability of  data.   No  direct impacts on  soils are defined,  such impacts
being  screened  through the potential impacts on vegetation growing  in  soils
which have  become contaminated by the deposition of  air  pollutants.   Impacts
on  fauna are  also  addressed  indirectly  with effects being  related to  the
ingestion  of  plants  containing toxic elements  taken  up from pollutants
deposited on soils.  Thus, the information presented here  represents a prelim-
inary definition of air quality related values and impacts.
       Perhaps  as  important  as  the  areas  addressed are  several  areas  not
addressed in this  procedure.   These areas  are visibility, acid precipitation,
a screen for  TSP, and a  screen for ozone.   Consideration of visibility  as  an
air  quality related value  is  required  by  regulations  (40  CFR 52.21  (o)  and
(p)).  Addressing  visibility was  beyond  the scope of  this work.  However, EPA
has  prepared a  report  to Congress  on visibility**  and draft  regulations7 have
been published.
       No simple  procedure  is  currently available to deal with the  impact  of
a single source on acid precipitation.  Acid precipitation presents  a regional
problem  involving  long-range transport which makes  the  impact of  a  single-
source  difficult   to  isolate.    Various  adverse  effects on  vegetation  have
been noted  in  areas with  low  soil buffering  capacities  and subject  to  heavy

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annual  precipitation.    Such  areas  appear to  be most  susceptible.8,9,10,
Observed  effects  include  reduced  growth,  reduced  germination  of  seeds  and
pollen, accelerated leaching of nutrients, decrease in soil calcium and  other
bases,  and  reduced microbial  activity,  particularly that  of nitrifiers  and
nitrogen-fixers.   A  major EPA  initiative  to study acid precipitation is
currently underway.   Policy and  guidance  will  be formulated  as part of  this
initiative.
       Total suspended particulates  (TSP)  are  not  considered here.  No useable
information other than that used to develop the ambient  standards (NAAQS)  was
found in the review literature.   Thus,  EPA's current procedure  for TSP3 should
suffice for the review of  generic  TSP-  However,  the trace metals in TSP  may
have greater impacts on vegetation  and  soils than  the total amount of particu-
lates.   This  section  provides information related to  specific trace metals.
       No simple  models  are  currently available  to  estimate  the  impacts on
ozone  concentrations  of  emissions  of  volatile organic  compounds  (VOC)  from
a  single source.   EPA is currently developing  means  other than modeling
to  deal with  VOC  emissions  and  ozone.   It  appears  likely  that an emission
management approach will be  taken.   When this approach has been completed it
could probably be used  to review new sources for impacts  on air  quality
related  values.    Meanwhile,  the  minimum  reported  concentrations  at  which
vegetative damage occurs are presented  here  but no method for their use
is  given and  no  significance levels  for  VOC emissions  have  been developed.

3.2  NATURAL VEGETATION AND CROPS

3.2.1   General
        Two pathways by which  air pollutants can affect vegetation are consid-
ered here.  The first  is  the direct  exposure of  a  plant to a gaseous pollutant
in the ambient  air.  The second  involves  indirect exposure to trace elements
through deposition of the pollutant  in  the soil  and later uptake by the plant.
For each pathway certain qualifications and cautions should be kept in mind in
order  to avoid interpreting  the values  presented here  either  as absolutely
safe  levels for all plants or as levels which could never be exceeded without
damaging vegetation.  The following  discussions  are not intended  to be exhaus-
tive  and details  required by specialists are  not given.   The  intent  is to

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provide  the  air quality  analyst  with a  feeling  for  the difficulty of  esti-
mating  screening  concentrations for  plants and  the  complexity of making
detailed assessments  of impacts on vegetation.   References  8, 9, 12, and  13
may  be consulted for  additional  details  and  guidance  to  primary source
material.
       Effects  of  pollutants can be  classified  as acute  or chronic.   Acute
effects  result  from  short-term  (e.g.,  3-hr)  exposures  to  relatively high
concentrations.  Chronic effects result from exposures to lower concentrations
for  times  of  from months  to  several years.  Most of  the  effects  data for
plants  comes  from  experiments  conducted under  acute conditions  of  exposure
with  some  limited  information on chronic  exposures.   Thus,  the data may not
adequately reflect impacts which take years or decades to develop.
       The values presented here represent the ambient levels  at which visible
damage or growth retardation may occur or the observed minimum levels  at  which
injury and mortality to plants have been reported.   These numbers  are  general-
ly the lowest  values consistently reported in the literature  on plant  response
to  controlled  exposures  of  single  pollutants.    Both  field  and greenhouse
studies have been used  in developing the data. Experiments which  demonstrated
only physiological changes (e.g.,  a  change in respiration  rate)  without
associated  visible damage  or effects  on growth,  weight,  or  yield  were not
considered in  this compilation.
       The majority of  the studies were performed on crops  and  other economic-
ally important species; for lack of  sufficient data,  it is assumed here that
native  plant  species are  affected  at  similar concentrations.   In addition,
assessment of  the  data on crops is difficult because of the number of horti-
cultural varieties  available for many of the species tested.   In  the process
of  selecting  desirable  attributes in  different varieties, the  species'
original sensitivity  or resistance  to the element being tested may have been
inadvertently  altered, making general conclusions about  the sensitivity of the
species  as a whole difficult.
       Effects  from  simultaneous  exposure  to   two  or  more  pollutants  have
been  ignored in the majority of the  studies.  Exposure  to a  single pollutant
at a  time  is not  the  usual situation.  Particular  combinations and concentra-
tions of pollutants may act either synergistically or  antagonistically  under
certain  conditions.    Such  situations   are  seldom clearly  predictable  with

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                                      10

current information and the screening procedure presented here  does  not deal
with  them.   A  limited  discussion of synergisms  is  pesented in  Sec.  3.2.3.
       Each  species exhibits  a specific range  of  tolerance  which may be
higher, lower,  broader,  or narrower  than  another species'.   In  addition to
the variation  in  tolerance between species,  every individual of a  given
population has an intrinsic  tolerance  to environmental stress.  Therefore, the
population exhibits a  characteristic range of tolerance so that all members of
the population  would  not  necessarily  respond  to  pollutant levels  that  would
adversely affect some  members.
       Species  vary in the way they take up, metabolize,  eliminate,  and
accumulate elements.  Species also vary in  the  way they respond to different
elemental forms.   For example, As3+  is  generally  thought  to  be  more  toxic to
plants than As^+.  The values presented here do not make such distinctions nor
could they be made based  on the review literature.
       Finally, the response of species  and  individuals  depends  upon  a number
of  uncontrolled  variables.   Changes  in these  variables might alter  the
sensitivity  of  the plant.   These variables include:   age  (stage  of  develop-
ment), health  and  vigor,  season  of year,  temperature,  light  intensity,  soil
type,  moisture  content  of  soil,  pH  of soil, humidity,  wind speed,  and  the
presence of other elements.

3.2.2  Screening Concentrations for Ambient Exposures
       Table  3.1  presents  the suggested  screening values for  seven gaseous
pollutants.   These values represent the minimum concentrations at which
adverse growth effects or tissue  injury  in exposed vegetation were reported in
the  literature.   Data for some  other gases  could  not be included because the
critical  specification of  averaging time was missing.   Where  information was
available,  separate values  are given  for  sensitive,  intermediate,  and  resis-
tant plants.   Species belonging  to each of these  groupings  are given in
Appendix  B  for  S02,  NC>2,  and ozone.   Figure  3.1 displays  graphically  the
variation  in experimental  determinations  of the minimum  SC>2  concentration at
which  effects occur.  Figure 3.2  presents  a similar display for N02.  For both
pollutants  there is reasonable  but not perfect agreement between the graphical
data  and  Che  screening  concentrations  recommended  in  Table 3.1.   The  use
of the data from the table rather  than interpolation  from the curves is

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              Table 3.1  Screening Concentrations for Exposure to
                          Ambient Air  Concentrations^1*
Minimum Reported Level (ppmv)
Vegetation Sensitivity
Pollutant
S02
N02
COS
H2S
Ethylene1*
Fluorine
Beryl liumi
LeadJ
Averaging
Time
1 hr
3 hrs
1 yr
1 hr
4 hrs
8 hrs
4 hrs
8 hrs
1 mo
1 yr
1 wk
4 hrs
3-4 hrs
24 hrs
10 days
1 mo
3 mo
Sensitive**
.35(917)
.30(786)
.20(392)
.10(196)
.06(118)
2.0(3760)
2.0(3760)

1000
(1,800,000)
20.0-60.0
(28,000-84,000)





Intermediate
.80(2096)
.35(686)
.15(294)
.15(294)
5.0(9400)
4.0(7520)







Resistant
5.0(13100)
.55(1078)
.35(686)
.30(588)
9.0(16920)
8.0(15040)

10,000
(18,000,000)
400
(560,000)





Reference
14
16
17
18
18
18
19
19
f
20
21
22
24
25
26
27
28
•All values except beryllium and lead refer to effects  on vegetation.

^Minimum reported levels at which visible damage or growth effects  to vegetation may
 occur.
                                                    *
cValues in parentheses are ug/m3 at 20"C and 1 atm.
''These values should be used in the screening procedure unless  it  is known that only
 intermediate or resistant plants will be affected.
eThe values for 20Z injury are reported here, since they correspond closely with other
 values in the literature.

^Based on generalization of results of a number of studies.
8Reversible decreases in photosynthetic rate have been  shown  to occur at significantly
 lower levels but effects on growth have not been demonstrated.
DEthylene " ... is the only hydrocarbon that should have adverse effects on vegetation
 at ambient concentration of 1 ppm or less."  (Ref. 23).
        value to protect public health.   Very toxic  to  humans  and presumably to some
 animals also.
JNAAQS value to protect public health.

-------
                                     12
3.5


3.0


2.5|-
E
a
a
~ 2.0
O
2
9. 1-5
 en
O
« 1.0
0.5
            (a) SENSITIVE SPECIES
                DAMAGE  LIKELY
        INJURY OR
        DAMAGE
        POSSIBLE
    INJURY
       I    I
                                          E
                                          O
                                          O
                                          CM
                                          O
                                          co 2
                                                               (b) INTERMEDIATE
                                                                  SPECIES
                                                                  DAMAGE LIKELY
                                                         INJURY OR DAMAGE
                                                              POSSIBLE
                                                    NO
                                                  INJURY

                                                    I    I
           23456
             EXPOSURE (hr)
                                                        23458
                                                          EXPOSURE (hr)
                    O
                    z
                    o
                    CM
                    g
                      10
                       9
                       3
                             (c) RESISTANT SPECIES
                                    INJURY OR DAMAGE
                                        POSSIBLE
                                  NO
                                INJURY


                             J	1	1	I    '    '
                                    3458
                                  EXPOSURE (hr)
                                                                    VALUES
                                                                    RECOMMENDED
                                                                    IN THIS
                                                                    PROCEDURE
            Fig.  3.1  S02 Dose-Injury Curves  for Plant Species
                      (From  Ref.  8 as adapted from Ref.  29)

-------
               1000 p
            ^   100
            I
            a
           •ai
            o
            o
            o
            N
            o
10
                0.1
                                             X-SCREENING
                                                CONCENTRATIONS
                                                USED IN THIS WORK
   -   METABOLIC
             AND
                 GROWTH
                     EFFECTS
FOLIAR LESIONS
                       I  I I Mill	I  I I I I 11 ll   I  t i I I I• ll   I I | | I | ill   i  I i | i t\
                  0.1
                     10       100
                     EXPOSURE (hr)
        1000     10000
              Fig. 3.2  N02 Dose-Injury Curves for Plant Species
                        (From Ref. 8)
recommended, since  Che  curves are based on attempts  to  fit  theoretical dose-
response  curves  to  experimental data whereas  the  tabulated  screening  concen-
trations are based directly on experimental results.
       Several points  are worth noting about  the  chosen  screening  concentra-
tions.   First,  the significant  variation  between the values  for  the  various
sensitivity groupings  should  be noted.   With  this  large  variation  it  appears
unlikely  that  use of any  values but those for  sensitive vegetation could be
justified  in  a  screening procedure, given the  large  number of species  for
which information is. not available.
       Second, the  tabulated  concentrations should be compared  to  NAAQS,  PSD
increments, and   likely  ambient concentrations.   Table 3.2  summarizes these
comparisons for  the cases  where they  can be made.   For pollutant/averaging
times not  tabulated, either no  corresponding  NAAQS or PSD increment exists or
it appears that  the screening  concentration  could be exceeded  under  certain
circumstances.    For  the  criteria  pollutants,  the NAAQS  appear  to  protect
against vegetative  damage except possibly for 3-hr and  annual S02 exposures.
For the 3-hr exposure,  the screening concentration exceeds  the applicable PSD

-------
                                      14
          Table  3.2   Screening  Concentrations of Gaseous Pollutants
                      Compared to  Ambient Criteria
Pollutant
S02


03
N02


CO
Averaging
Time
3 hr
1 yr

1 hr
4 hr
8 hr
1 yr
1 wk
Vegetation Sensitivity
Sensitive
< NAAQS3
> PSDb



> NAAQSf
-
—


c
Intermediate
> NAAQS3
> PSDb



> NAAQS f
c
c


—
Resistant
c
c



> NAAQSf
c
c


c
         aS02  3-hr  NAAQS  =  .SOppmv  (1300  ug/m3) .
         bS02  3-hr  PSD increments  (ug/m3)  »  25(Class  I),  512(Class
          II), 700(Class  III),  325(Class  I variance).   These values
          do not  include  background.
         cScreening concentration  unlikely to  be  reached  under ambient
          conditions.
         dS02  annual NAAQS  • .03 ppmv (80 ug/m3).
         eS02  annual PSD  increments (ug/m3)  «  2(Class  I), 20(Class
          II), 40(Class III),  20(Class I  variance).   These values do
          not  include background.
         f03 1-hr NAAQS = 0.12 ppmv (235  ug/m3).
         8N02  annual NAAQS  - O.OSppmv (100 ug/m3).
increments  and  for the  annual exposure,  it  exceeds  the  Class I  increment.
However,  the  screening  concentration  should  be compared  to  the  total  S02
concentration including background whereas the PSD increment  does not include
background.   Thus,  a  source  could cause an  S02 concentration less  than  the
increment  while  the  total  S02 concentration  (source  plus background)  could
exceed  the  screening, concentration.   With the  exception of  the  following it
appears  that  possible  adverse impacts  to  vegetation  resulting  from  direct
exposure  to ambient concentrations of criteria pollutants  are already covered
by existing programs for NAAQS attainment:
       •  S02 exposures at 1 hour, 3 hours, and 1 year,
       •  Ozone exposures at 4 and 8 hours,

-------
       •  N(>2 exposures of sensitive species at 4 and
          8 hours, and
       •  Long-term N(>2 exposures at 1 month and 1 year.
This  observation does  not  preclude  doing  a  review  for  impacts  on  plants,
particularly  where  the minimum values  at  which  effects  have been  reported
are close  to  being  exceeded.   It does,  however,  indicate  that the vegetative
impact review can be  done along with the review  for NAAQS or PSD increments.
Even  in cases  where   review for NAAQS  and PSD  increments  covers  exposures
to  plants, there may still be the necessity of dealing with  trace metal
exposures  through deposition in  the  soil  or  through concentration in  plant
tissues.

3.2.3  Synergisms
       Only a very  limited amount of information  was  available  in the review
literature  consulted  regarding  synergisms.    Three  indications of  synergism
were  found:
       •   S02 and N02,
       •   S(>2 and 03, and
       •   SC>2, 03, and N02-
Table  3.3 presents values which could  be  used  as  screening  concentrations
based  on  the most restrictive values  in  the references.   Where  averaging
times  allow  comparison,  the screening  concentrations  for single  pollutants
in  Table  3.1 are greater  than the screening  concentrations for mixed  pol-
lutants in Table  3.3.  Given the problems with the data discussed  in Sees.  3.1
and  3.2.1, this  comparison should not  be  interpreted  as clear  evidence  of
synergism.  An additional caution is also in order-  Mixtures  of gases  may act
synergistically  on some  species  and antagonistically  on others (see,  for
example,  Ref. IS).   Thus,  the  tabulated  values  should be used  to  indicate
situations  where the  FLMs  should  be  alerted  so  that  the  situation  may  be
evaluated by  them.  There  may be additional synergisms which  are  not noted in
Table 3.3 but  which could be  added to the table  and incorporated in  the
screening procedure at a later date.

-------
                                      16
                  Table 3.3  Synergisms of Gaseous Pollutants
                             (Plants)3
Pollutants
S02
N02
S02b
03
S02b
03
SO 2
03
N02
Cone en tr at ion s
(ppmv)
.05
.05
.30
.10
.05
.05
.14
.05
.10
Exposure
1 hr
1 hr
4 hr

6 hr/day
for 28
days
Reference
30
31
32

33
              aThe same criteria were used in selecting these
               values from Ref. 15 as were used in developing
               Table 3.1.
              bAntagonism, as well as synergism, has been
               reported for mixutes of SC>2 and 03 (Ref. 18).

3.2.4  Screening Concentrations for Soil and Plant Tissue Exposures
       Table  3.4  presents suggested  screening concentrations  for  trace ele-
ments found to adversely affect plants.  Two types of data are presented.  One
gives a concentration which when present in the soil has been found harmful to
plants.   The  other gives  a  concentration found to be  present  in the tissues
of  plants  which  had  been harmed.    In  considering  these  values,  it  should
be remembered  that most  elements  and  compounds are not deleterious until they
have been complexed in  the  soil  and  become suitable for uptake by plants.  In
addition,  many  soil  characteristics  such  as pH,  composition  (sand,  clay,
loam,  organic  matter, etc.),  moisture content, and  cation  exchange capacity
affect the  amount of  trace elements available  for  uptake.   In developing the
tabulated values,  only data taken with  the plants growing  in  soil  were con-
sidered.  Data developed  in  experiments  in which plants were grown in aqueous
nutrient solutions were  ignored.   Conditions of nutrient solution culture are
likely to  be  sufficiently different  from natural conditions  as to render the
results of the experiments misleading for the purposes of this work.
       As with the ambient screening concentrations for gases, a great deal of
variation  is   exhibited  by the  data  as  shown in  Fig.  3.3.   For comparison

-------
                   Table 3.4  Screening Concentrations for
                              Exposure of Vegetation to
                              Pollutant Concentrations in
                              Soil and Tissue
Minimum Reported Level

Pollutant
Arsenic
Boron
Cadmium
Chromium
Cobalt8
Copper
Fluoride3
Lead3
Manganese
Mercury
Nickel
Selenium3
Vanadium
Zinc
Pollutant Source
Soil Tissue
3 0.25
0.5 11
2.5 3
8.4 1
19
40 0.73
400 310
1000 126
2.5 400
455
500 60
13 100
2.5
300
(ppmw)

Reference
9
9
9
9,35
9
9
9
9
9,36
9
9
9,37
38
9
                 ^Tissue concentrations may affect animals
                  before affecting plants.  Compare to
                  toxic levels for animals in Table 3.7.
purposes, this  figure includes results  based on  experiments  in nutrient
solutions  and  also shows  the values chosen  for screening concentrations  in
this work.
       No standards or PSD  increments currently  apply  to  these  trace  elements
so no comparisons with other review criteria can be made.   It  should be noted,
however,  that  the heavy metals  listed  in  Table 3.4 are  emitted  as particles
and become TSP  in the atmosphere.  To  the  extent  that they contribute to  TSP
levels, the NAAQS and PSD increments would  apply to these  trace  elements.   The
connection between such ambient  levels and the screening concentrations  for
soils and tissues is discussed in Sec. 5.

3.3  SOILS
       In contrast  to the  amount of  published information on  the  effects  of
atmospheric pollutants on plants and animals,  very little  has  been reported on
their effects on  soils.   Research on trace elements in soils,  often  the  same

-------
   10000
    1000
O

cc
UJ
o
O
o
     100
10
     0.1
                         o
                         8
            •   o

        — x •   o
                         -» Value used In this work
                         • Plants grown in soils
                         O Plants grown in nutrient solution
                         x Growth medium unknown
                                                           S*Soll Concentration
                                                           T = Tissue Concentration
                                                            00°
                         •
                         o

                       • o
                                                                8     •
                                                                      i
                                                            0     • O
                                           •*-
                         •
                         •
                                                                         o

                                                                         o
                                                                                     o

                                                                                     o
                                                                                     o
                                                                -*•*
                                                                                                  o
                                                                                                  o
                                                 ••*-
          ST
          As
          S T
          Be
ST
 B
ST
Cd
                                  J 1
ST
Cr
                                        -LI-
ST
Co
                                         .LI-
ST
Cu
                               JJ_
ST
 F
                               JJ	U	M    II
ST
Pb
ST
Mn
ST
Hg
ST
Mo
                                                  -LI-
ST
Nl
                                                  JJ	LL
                                                        J_L
ST
Se
ST
 V
ST
Zn
                                                  TRACE ELEMENT
                                                                                                                             oo
        Fig.  3.3   Concentrations of Some Trace Elements Toxic  to Terrestrial Plants

-------
elements as  atmospheric  pollutants,  has  been directed to notable deficiencies
or excesses  that limit  agricultural  crop  production.  When the  amount  of an
atmospheric .pollutant  entering a  soil system  is  sufficiently small,  the
natural ecosystem can adapt to these small changes in much the  same way as the
ecosystem adapts to  the  natural  weathering  processes  that occur in all soils.
Cultural  practices  (e.g.,   liming,   fertilization,  use  of  insecticides  and
herbicides)  add  elements and modify  a soil  system more than  a  small amount of
deposited atmospheric  pollutant  can.  The secondary  effects of the pollutant
appear  to  impact  the  soil  system  more adversely than  the addition of  the
pollut-ant itself to the soil.   For  instance, damaging  or killing vegetative
cover  could  lead  to increased solar radiation,  increased soil temperatures,
and  moisture stress.  Increased  runoff  and erosion  add to the  problem.   The
indirect  action of  the  pollutant,  through  changes   to  the  stability of  the
system, thus may be more significant than  the direct  effects on soil inverte-
brates  and  soil microorganisms.     However, the  lack of long-term historical
data on both the type and amount of atmospheric pollutants as well as the lack
of  baseline data  on soils  has  made  difficult  the   task  of  determining  the
effect  of  pollutants on soils by monitoring  changes  associated  with exposure
to  pollutants.   A limited  number of  studies  have been carried out  on  trace
element contamination  of soils.39,40  plant and  animal  communities  appear  to
be  affected before  noticeable accumulations occur in  the  soils.   Thus,  the
approach used  here in which the  soil  acts  as an  intermediary  in the transfer
of deposited trace  elements to plants appears reasonable as a first attempt  at
identifying  the  air  quality related values associated with soils.
       When  viewing soils  in this way it is  important  to know the endogenous
or background concentrations of  elements already  in the  soil of interest,  for
these endogenous levels may be available for plant uptake. There is, however,
a  wide variation  in the normal  concentrations  of various trace  elements  as
shown  in  Table 3.5.8   if extremes  in the concentrations are  considered,  the
range of endogenous  concentrations becomes even larger (see Fig. 3.4) .43.   Both
references show relatively good agreement on the normal ranges.  The tabulated
values  also  provide "average concentrations" which can  be used  when specific
information about the  concentrations  of trace  elements in  the region  of
interest  is not available.  One  of the  difficulties with  screening  for
impacts on  plants  and soils becomes apparent when the  endogenous concentra-
tions in Table 3.5 are compared with the screening concentrations for soils  in

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20
Element
Arsenic
Beryllium
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanad ium
Zinc
Average Soil
Range Concentration
(ppmw) (ppmw)
0.1-40
1-40
2-100
0.01-7.0
5-3000
1-40
2-100
30-300
2-100
100-4000
0.01-4.0(7)
10-1000
0.01-80
20-500
10-300
6.0
6.0
10.0
0.06
100
8
20
200
10
850
-
40
0.5
100
50
  aBased on Ref. 8.
Table 3.4:   the screening values are     Table 3.5  Range of Endogenous  Soil
exceeded for some  part of the listed                £f en"a'ion8  °fa
                  f                                 Selected Elements9
range  for  nine  out of the  twelve
elements for which screening concen-
tration are given.  Fluorine, lead,
and  mercury  are  the  only  elements
whose screening values lie above the
corresponding  endogenous ranges.
The default average soil concentra-
tion exceeds  the  screening  concen-
tration  for  boron,  manganese,
vanadium, and chromium and,  for the
first  three  of  these  four,  the
entire  listed  normal  range  exceeds
the  screening value.   In  inter-
preting this indication,  it  must be
remembered  that  the  screening
concentration value represents
the  lowest  value  found  in  the
review literature  (see  Fig. 3.3)  and that  not all  plant species  are as
sensitive  as  the  one upon which  the value  is  based.   As  outlined  in Sec.
3.2.1,  there  are  many additional  reasons why there  is no inherent conflict
between  screening  concentrations  and endogenous  concentrations  above  these
values.    The  chief among  these  are probably the variation  in  sensitivity
between  individuals,  the  variation   in sensitivity between  species,  and  the
fraction of the  endogenous  concentration really available for  uptake by
plants.  It  should  be noted, however, that endogenous  concentrations of some
elements can make soils  toxic to some species.   Thus, certain tolerant plants
can act as indicator species  for the  element tolerated;  they will be among the
species  present in  soils where the endogenous concentrations of that element
exceed levels toxic  to more sensitive species.12
       The problem associated with  the amount of  an element in the  soil which
is  actually taken  up  into  plant  tissues can be handled  in  an  approximate
fashion  by using  a plant:soil  concentration  ratio.  Table  3.6  provides  two
sets of  concentration ratios (CR's).   One set is recommended for use in this
work;  the  other  is based  on nonstandard  methods using solution cultures

-------
<-N
a.
a
s^
Z ..-
o 10000
p
£ 1000
Jg
111
o
z too
o
o
_J
5 10
CO
i i
Z 0.1


- !



. 1

mv


1
1 I
i i
1 S
^
i

EXTREMES






R
-"
ti
\
\
j

f
i •;
1 I
T 1
1 1


f
*
^
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*•
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1
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pi NORMAL
P RANGE


i
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•
i
i
t
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a
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                                 ELEMENT
Fig. 3.4  Range of Endogenous Concentrations of Trace Elements

          (From Ref.  41)

-------
                                     22
but is given to  provide  some  feeling
for  the  large  uncertainties asso-
ciated with this  type  of work.   The
comparison set  of concentration
ratios could be  used in the screening
procedure presented  here  to   provide
very  conservative  estimates  of
potential  impacts.   Some elements
(boron  and cadmium)  tend  to  be
concentrated by  plants (ratios > 1),
that  is, concentrations  in  plant
tissues  exceed  those found  in the
soil  whereas  the  concentrations  of
most  of the  listed elements  tend
to  be less in  plant tissue  than
in  the  surrounding  soil .    In any
case, these CR's  represent ratios of
averages^ and thus  may give   results
Table 3.6.  Plant:  Soil Concentration
            Ratios
Element
Arsenic
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanadium
Zinc
Recommended
Value3
0.14
5.3
10.7
0.02
0.11
0.47
0.03
0.45
0.066
0.02-0.5
0.045
1.0
0.01
0.64
Comparat ive
Valueb
4.2
-
222
250
87
1000
2
3000
26
331
4
1
40
a8ased on Ref.  8.
^Based on Ref.  12.   Based  on non-
 standard methods  involving solution
 cultures.  See discussion in text.
quite different  from  the  true ratio
between plant  and  soil  concentrations  in a  particular  case.   However, they
appear  to be the best means available  for estimating .uptakes of  various
elements from the soil.
3.4  FAUNA
       The  screening  concentrations  presented here  are  based  on  data for
terrestrial vertebrates.   Data for aquatic species,  including fish,  were not
examined in the literature reviewed.  Also, effects on  aquatic and terrestrial
microorganisms  are  not  considered here.   Table  3.7  presents  the   screening
concentration values based on data summarized in Refs.  8  and 9.  The  tabulated
values represent  the  lowest dietary  concentrations  found to be  harmful.
Several  factors  limited the  usefulness  of the available data.   Some harmful
levels were given in terms of average concentrations in  the affected animals.
Unfortunately no equivalents  of the  plant :soil  CR's were available to go from
dietary  concentrations to concentrations per unit body weight.   In  addition,
all  the  data on ambient exposures  failed  to  give  averaging  times  thus ren-
dering it unuseable in  this screening procedure.  Even  for  the data upon which

-------
Table  3.7 is based, there  were no
indications as  to how  long  the
element needed to be  ingested in the
given  concentration  before  causing
the  harmful  effect.   Comparison of
the  screening  concentrations  for
animal effects (Table  3.7)  with the
values  for  plant  tissue concentra-
tions  (Table  3.4)  shows  that  the
values  for animals  generally exceed
those  for plant  tissue concentra-
tions.   However,  for cobalt, fluor-
ide,  lead,  and  selenium, it appears
that  plants  could accumulate concen-
trations  that would  be  toxic to
some  animals  before  the  plants
themselves were harmed.
 Table 3.7-   Dietary Trace-Element
             Concentrations Toxic
             to  Animals3
                      Dietary
Trace Element     Concentration (ppmw)
Arsenic''
Cadmium^
Cobalt
Copper''
Fluoride
Lead
Manganese''
Nickelb
Selenium
Vanad ium
Zinc
3
15
1-3
20-30
. 100-300
80-150
500-5000
1000
5-30
10-500
500-1000
aBased on Ref. 8.
^Tissue concentrations in plants may
 affect plants before affecting
 animals.  Compare to plant screening
 concentrations  in Table 3.4.
       For beryllium  and  lead,
data on ambient air exposures were available in terms of the NESHAP and NAAQS,
respectively (see Table 3.1).   These values  relate to human exposures.  With-
out other  indications  these same  levels  have  been assumed  to be potentially
hazardous to at least some  animals as well.

-------
                      4  TRACE ELEMENT AIR QUALITY DATA

       EPA's Storage and Retrieval of Aerometric Data (SAROAD) system was used
as a  data base to  develop air quality  information  for trace elements.   The
information was intended to serve primarily as an aid in estimating background
concentrations so minimum  concentrations were included.  A  secondary purpose
of the information was to identify locations where high concentrations already
exist.  For  this  purpose,  maximum concentrations were  included.   Compilation
of available  data for  all the  pollutants  discussed here with estimates
for  all  relevant averaging  times would  not  have been feasible  so  the  data
search was  limited  to trace elements  including  lead.   It was also  felt  that
more  complete  data  for  the gaseous  criteria pollutants  would  be  available
locally than could be found  in SAROAD.   On  the other hand, many  localities
probably  lack  estimates  of trace  element concentrations.   Since  only  annual
averages  are used  in screening  for  trace element  impacts,  the data  search
emphasized  annual  average  data.  Maximum and minimum  short-term  observations
have  been included in  the data compilations  for  informational purposes.
       In  order  to improve  coverage,  data for  1975-77 inclusive were  used.
Many  locations had  data  for only one of the  three  years.     As expected,  all
the data  were based on high volume sampler data with 24-hour averaging  times.
It was also  frequently the case that  insufficient data was  available to allow
the calculation of a valid annual average.  The available data is  presented in
Appendix C.  No data was found  for mercury, boron, cobalt,  copper,  and nickel.
The data  is  presented  by state and county for each  pollutant. As  can be seen
                                                                             •
from  the  tables,  the  spatial coverage  is  poor.   For counties with  data,  only
the minimum and maximum annual  averages from all reporting stations are  given.
With  multiple  stations,  it  is unlikely  that both values  come from  the  same
location.
       In order to  avoid possible  misinterpretation  of the data,  it should be
kept  in mind that SAROAD  routinely stores values below the  limit  of detect-
ability as one-half the minimum detectable limit.  In some cases,  this will be
the value  which  is listed as  the minimum observation.   These situations are
usually fairly  obvious,  since  the same  minimum  value  will  be recorded  at  a
large number of stations.

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                                     25

                           5   SCREENING PROCEDURE

5.1  METHODOLOGY

5.1.1  Description
       A simplified  view  of  the  pathways between  sources  and receptors  is
presented  in Fig.  5.1.   This  simple view is used  here  as  the basis  for
screening  a source for potential adverse impacts  on plants,  soils,  and
animals.  Emissions from the source are  assumed to disperse in the atmosphere
and  add  to  whatever local background concentrations  might exist  to  provide
an  estimate  of  the maximum  ambient  concentration for  the averaging  times
of  interest.  These ambient concentrations may act along  four different
pathways.   The  first  two  are routes  in which the ambient concentrations
affect  animals  or  plants directly  without  any  intervening  mechanisms.
In  the  third,  animals  can  ingest  substances  deposited on  plants  before  the
substances have  been washed  off by rain or blown  off onto the soil.   Such
ingestion is a critical pathway.   Appendix D provides  a referenced discussion
of  the  literature   related  to toxicity  resulting  from this pathway and  the
potential for harm  to  animals exists  whenever heavy metals are deposited  on
materials which  they ingest.  Some  start  on dealing with  this  issue was made
here  in  terms  of estimating the amount of deposited material but  a complete
methodology  was  not developed.   However,  reviewers  should be aware of  this
potentially  critical pathway and  the material  in  Appendix D  may be  useful
in  flagging  critical situations.   In  the  fourth,  a  certain  amount  of  the
dispersed material  is  deposited  on the  soil.   As  noted  in Sec. 3, only  the
deposition of trace elements  is considered here.  The deposited  trace elements
as  well  as any  endogenous concentration  of the element are then available  for
uptake by plants in  quantities which may be toxic  to the plants  themselves  or
to  animals which feed upon  the plants.
       It  is important to  realize  that  this  simplified  picture   leaves  out
many potentially  important  pathways  and  natural   processes.    For example,
there is no provision for  the  uptake  and concentration  of  substances  by
plants directly  from the air; all such  concentration is assumed  to be  through
the soil with  uptake  by plant  roots.   No account is taken  of  removal  of
deposited  substances from  the soil by  runoff,  leaching,  or erosion and  the

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Background
   Cone.
 Source
                              Direct
                            Exposure
              Deposition
               (Trace
               Elements)
Endogenous
   Cone.
       Participate
       Deposition
                                   Forage
                                    and
                                   Fodder
 Soil
Cone.
                                       Uptake by Roots
                   Fig. 5.1 Pollutant Pathways

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                                      27


subsequent deposition of such substances in bodies of water.  Also, no account

is taken of deposition directly from the air into water.  Finally, the effects

on animals of ingesting contaminated water have not been addressed.

       Screening for  a particular source is accomplished  in a series of

steps.  Steps 1  and  2  apply to airborne pollutants; steps 1 and 3-7 apply  for

trace metals where deposition must  be  taken into  account.  Step 8 provides an

alternative where modeling results  for the source are unavailable.

       1.  Estimate the maximum ambient concentration for averaging
           times appropriate to the screening concentrations for
           pollutants emitted by the source and including any
           background concentrations.

       2.  For exposures to airborne pollutants, check the maxima
           from  Step 1 against the  corresponding screening concentra-
           tions in Table 3.1 or against the corresponding NAAQS,
           NESHAP or PSD increments, whichever applicable standard
           is most restrictive.  In addition, the possibility of
           synergisms should be considered.

       3.  For trace metals, calculate the concentration deposited
           in the soil from the maximum annual average concentra-
           tion  assuming that all deposited material is soluable
           and available for uptake by plants.

       4.  Compare the increase in  concentration in the soil to
           the existing endogenous  concentration using the average
           values in Table 3.5 when local data is unavailable.
           (This provides a supportive indicator,  not a primary
           decision  parameter.)

        5.  Calculate the amount of  trace element potentially taken
           up by plants using the CR's in Table 3.6.

        6.  Compare the concentrations from Steps 3 and 5 with the
           corresponding screening  concentrations in Tables 3.4
           and 3.7.

        7.  Reevaluate  the results of the comparisons in Steps 4 and
           6 using estimated solubilities of elements in the soil to
           provide supportive indications, recognizing that actual
           solubilities may vary significantly from the estimated
           values.

        8.   If modeling  results are  unavailable, the significance
            levels  for  emissions developed in Sec. 5,2 may be used
            to  screen the source.
 The discussion  in Sec. 5.2  also  provides an  example  of  the  application of
 the screening  procedure.     This  example  develops  the  significant emission

 levels for one  of the trace elements from an  estimate  of a source's maximum

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annual average  concentration.   Table  5.1  summarizes  these steps and  indexes
them to the relevant sections, tables, and  equations  in  the  text.   Figure  5.2
provides  a  flowchart  of  the  screening  procedure showing  the  more  commonly
used tables and equations.

5.1.2  Estimating Maximum Concentrations  (Step 1)
       To estimate  the maximum concentration, the maximum air quality  impact
of  the  new source  must be estimated  and  added  to an appropriate  background
c one entrat ion.

       5.1.2.1  Air Quality Modeling
       The  first step in  the  screening  procedure  for air  quality  related
values  is  to  estimate the maximum ambient concentrations of pollutants
emitted from the new source for appropriate averaging  times.  Table 5.2 gives
the correspondence between pollutants and the averaging times  to be  considered
for  each.   Two cases need to be considered.   The  first arises when the
required  source-specific  concentration estimates  are available and  the second
arises when they are not.

       Concentration Estimates Available.     When source-specific   estimates
made  by an approved model are  available they  should  be used directly in
making the  calculations and  comparisons  called for in  Steps 2-7 of  Table 5.1.
Such  a situation would be ideal but  such estimates may frequently be unavail-
able, particularly during early discussions of a  permit application.

       Concentration Estimates Unavailable.   When  source-specific   estimates
of  concentrations are  unavailable  or when they are lacking for some critical
averaging times, there are two courses of action:
       •  Use of a screening technique for air quality impacts
          if the emission rates and stack parameters  are
          available or
       •  Use of the significance levels  for emissions  presented
          in Sec. 5.2.
       If stack parameters are available, some simple  techniques of  dispersion
modeling can be used  to screen the  source  for its air quality impact, remem-
bering  that only a screen  and  not a definitive demonstration  is  required.
Reference 42 provides  such techniques  developed  by EPA  for use in  new source

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                            Table  5.1  Steps in Screening Procedure
Step
1

2
3
4
5

6
7
8
Description
Estimate ambient maxima
• Modeling
• Background
Screen for direct exposure
Calculate deposited concentration
of trace elements8
Calculate percentage increases
over endogenous concentrations^
Calculate tissue concentrations
in plants
Screen for potential adverse
impacts of trace elements
Consider effects of trace element
solubility''
Apply significance emission levels0
Applicable
Text
Section Tables Equation

5.1.2
5.1.2, Appendix C C
5.1.3 3.1
5.1.3
5.1.3

5.1.3
5.1.3 3.4
5.1.3 3.4
5.2 5

.1-C.10
,3.3,5.3
5.1
3.5 5.4

3.6 5.5
,3.7,5.5
,3.7,5.4 5.7,5.8
.6,5.7
aReviewers may want to review the information in Appendix D to assess the potential for
 harm to animals from directly ingesting deposited materials.
bSupportive indication only, not primary decision parameter.
cUsed only when source-specific modeling results are not available.
                                                                                                        ro
                                                                                                        vo

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                                                    — Uiln Flw

                                                    	TIMMH InrinrnllM
                                                       ili In B»» Rifw »
                                                    3t»l In PraeMurt-Sii TtiU S. I.
Fig.  5.2  Flowchart  of Screening  Procedure

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                         Table 5.2  Pollutants and Averaging  Times
Pollutant
S02
N02
CO
H2S
Ethylene
Fluoride
Be
Pb
Trace Elements'*
Required Averaging Times
1 hr 3 hr 4 hr 8 hr 24 hr 1 wk 10 days 1 mo 3 mo 1 yr
X X Xa Xb
XX X Xb
Xa Xa X
Xa X
X X
Xa X
xa
xb xc
xe
aFor comparison with criteria not necessarily related to impacts on plants,  animals,
 or soils (NAAQS, NESHAP's, PSD increments).
bApplies to both impacts on plants, animals, soils and other criteria.
cAlso included in trace element analysis.
dTrace elements:  As, B, Cd, Cr, Co, Cu, F (as fluoride), Pb, Mn, Hg, Ni, Se, V, Zn.
eRequired for use in estimating amount of deposition.

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review.   These  methods  were used  to develop  EPA's  significance levels  for
emissions42 published as part of the proposed PSD regulations.^3,44
       As an  alternative, the  procedure  used in Ref.  45 to estimate air
quality impacts can be used  as presented in Appendix  A.  Some expansion
of  the original procedure was required  to  cover the  range of averaging
times  needed  for this  screening  procedure.   The equations presented in
Appendix A  are suitable for hand  calculation  or the development  of a simple
computer code.    The  significance  levels presented in Sec.  5.2 are  based on
this procedure.

       5.1.2.2  Background Concentrations
       The  estimation  of background concentrations is one of the perennially
difficult problems  of air  quality analysis.   Development  of new approaches
was beyond  the scope of  this  work.  The  analyst  should  consult  Ref. 46 for
guidance on this  subject.  No attempt was made here to  develop  information for
the gaseous criteria  pollutants.   For  these  gases,  it was  felt that  local
records would  be likely to provide more timely  and complete information.  In
addition, the  sheer  volume of data available precluded its  inclusion in this
procedure.  No attempt was made to develop background  estimates for other than
annual averaging  times.
       For  the 14 trace  elements  (including lead), EPA's  SAROAD files were
searched as described in Sec. 4.  No information was found  for mercury, boron,
cobalt, copper,  and  nickel.  The tables in  Appendix C summarize  the informa-
tion found  by  state  and county.  To estimate a  background value,  the concen-
trations  in the  county  of  interest  or nearby  counties  should   be  used and
the minimum geometric mean  picked.   This  minimum can then be added to the
estimated «q?«imi^i» annual concentration from the source  being  screened.  Values
of  the minimum  geometric  mean  from other  areas  should be compared  with the
value  chosen.   It is  possible  that some of the tabulated minima may be too
high to represent background levels because  the  monitor providing the data is
impacted by a large  source and thus is  not representative  of general  back-
g round c ond i t ion s.
       It will not  be possible  to  estimate background levels by this method
for many  locations.    In  such  a  situation,  the minimum  geometric  mean may

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                                       33

be  selected  from among  those  tabulated  in Appendix  C  and  used  in a sensitivity
analysis  to determine  if  the  addition of  a background level  is likely  to
raise  the  predicted concentration  above  the  screening concentration.    If
it  does,  then  a determination  of background  will  be  necessary  to  allow  a
clear  determination of  the source's potential  to  cause  adverse  impacts  due
to  trace element deposition.

5.1.3  Screening and Deposition  (Steps  2-7)

       Screening for Direct Impacts (Step 2).    This  screen  applies  to  the
pollutants listed in Table 3.1  for which data was available on  direct  impacts
of  airborne  concentrations on plants and animals:   SC>2,  N02,  CO,  t^S,  ethyl-
ene,  flourides,  Be, and  Fb.   After the maximum concentrations both with  and
without background have been calculated, screening  is simple.  The  appropriate
maxima are  compared to  the values given in  Table  5.3.   Values in excess of
the  screening  concentrations  indicate that  additional  detailed  review is
required and that the appropriate  FLM  should be notified.  The  possibility of
synergisms  should  also  be checked  at  this  point.   Consideration should be
given to the synergisms listed in Table 3.3 but no screen on the values  listed
there is recommended here.  Rather, the information could be used to alert the
appropriate  FLM to  the  possibility  of  a  problem  arising from  synergisms.
       Also included in Table 5.3 are the values used in  reviewing  new sources
under other criteria.  The value expected to be controlling for  each pollutant
has been circled in the table under the following assumptions:
       •  No background,
       •  Long averaging  times result in lower concentrations
          than short averaging times, and
       •  For short averaging times, the concentration is
          proportional to averaging time raised to the power
          -0.17.
This observation is made  only to give some feeling for what might be expected.
It  is  possible, for  example,  for  a  new S02  source  in  a Class III  area to
be  controlled  by the 700 ug/m3 PSD increment  and  still need  to  do a  review
for  plant,   soil,  and  animal  impacts  if  3-hour background  levels  are high
enough to make the predicted ambient concentration likely to exceed 786  ug/m3.
Completion  of  Step  2  would  complete   the screening  for  direct  impacts from
airborne pollutants.

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                                       Table 5.3  Ambient  Screening Concentrations
                                                              Aabient Concentration
                  	Pollutant and Averaging Ti«e*	
Screening         	^?	  	M°2	 	     CO	   H2S    Ethylene   fluoride  Beryl1in*  Lead
Criterion           1324A48MA1       8         W        4      3    24      240        M      3M
AQRV
  Screening                                               	                                          	     	      		
  Concentration11   917   786    -  18  3.760*  3760b  564 C^fi)   -       -    l.SOO.OOO1* 28,000*   47(772)   Qj^)    CfiD  CLi-
NAAQSc.d            -   1.300  365  80                    (loo)40,000
PSD Increment                  	
  ie.f              _     25  C_O 2-----
  II*. f             -512   91  20-----
  Ilie.f            -    700  182  40     -----
  Variance6.8        -325   91  20-----
NESHAPf>h           --_____._
Note:  Circled  value* expected to be controlling;  «ee  text.
aNumeral8:  hour*
   W:  1 week
   M:  1 Month
   A:  Annual
'•Ambient concentration* thi* high are unlikely.
C40 CFR 50.
dBaaed on maxiaua  impact of aource plu* background.
eRef. 1.
fBased on oaxinua  impact of source alone.
^Includes the  aource together with all other source*.
h40 CFR 61.

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                                      35

       Calculating Deposited Soil Concentrations  (Step  3). Deposition  of  trace
elements is  a long-term process  extending  over the  lifetime  of the  source.
The simple procedure used here depends upon an estimate of  the maximum annual
average concentration from  the source as  corrected by  the addition of  a
background concentration if known.   Reviewers may also  want  to review  Appendix
D at  this  point  to  assess the  potential  for harm to  animals  from direct
ingestion of  deposited  heavy  metals  (see  Sec 5.1.1).   The  following  equation
can be used to estimate the maximum concentration in the  soil:
       DC(ppmw) = 21.5 (N/d)X                                            (5.1)
where:
       DC = deposited concentration (ppmw),
        N = expected lifetime of source (yr),
        d = depth of soil through which deposited material
            is distributed (cm),  and
         X =» maximum annual average ambient concentration  from
            the source (ug/m^).
The value generally recommended  for d  is 3 cm.8,9,12   Some  work*-3 has assumed
20  cm for  d,  but the more  conservative value of 3  should  be adopted  for use
in  this screening procedure  unless  site-specific data indicate that  greater
penetrations  of  deposited  substances  are  more  representative of local condi-
tions.   It should also be noted  that an estimate  of  the source's  lifetime must
be  made in  order to use Eq.  5.1.   In the  absence  of  contrary indications,  a
value of N  s 40 years  should provide  a reasonable  and generally conservative
estimate of  source lifetimes  based  on  lifetimes equal  to twice  the time
allowed  by  the  Internal   Revenue  Service  for  equipment   depreciation.^, 47
If  the source is  tied  to  a resource,  the estimated  resource lifetime  might be
used  instead  of  40  years.   For  example, a mine-mouth  power  plant might have  a
lifetime of  N = 100 years  based on  the life expectancy  of the mine  or a gas
plant might have  a  lifetime N =  15 years, the  expected useful  life of the gas
field.
        Equation  5.1  is simply  derived.   Consider  a  volume of  soil  1 m2 in
area  and d cm deep at the location of the  source's annual maximum.  The weight
of material deposited on this area of 1 m2 can  be calculated as:

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      /Weight   \   /Ambient      \    /Deposition^    ,.   2^   IT-   \      t* «\
      ^Deposited) " (concentration)  * ^Velocity J  * (1  m } X (Tme)'     (5'2)
The weight of the soil in the volume of interest is
       /Weight \ m /Volume
       \of soil/   ^of soil
       /Weight \ m /Volume \   /Bulk Density\
                          l/   \  of soil   j
                                                                         (5.3)

Then  the ratio  of the weight deposited to the weight of the  soil can be
used  to  find the  concentration of  the  deposited material by  weight in  the
soil.   Soil  densities  range  from  1-2 gm/cm3 and  a value of  1.47 g/cm3 is
assumed here  as  a  good average value. 12   if an  average value  of 1 cm/sec is
assumed  for  the deposition  velocity, Eqs.  5.2  and  5.3 can be  combined to
give
       DC - (Weight deposited) /(Weight of soil)
                                    1 m
          - 21.5 (N/d) X   |

          •  21.5 (N/d) X(ppmw)
where  conversion factors  have  been used  as appropriate  to  give  consistent
units.   This result  is simply Eq.  5.1.    The  principal  assumptions in  this
derivation are:
       •  Deposition velocity of 1 cm/sec,
       •  Average bulk density of soil » 1.47 gm/cm3,
       •  Uniform distribution of deposited material throughout
          the soil volume, and
       •  All deposited material is retained by the soil,  that
          is, no leaching, surface runoff,  or erosion.

       Calculate Increase over Endogenous  Soil Concentration (Step 4).      The
purpose  of  this  simple  calculation  is to provide a  supportive  indication

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                                      37
for the primary screen  for  deposition to be carried out  in  Step 6.  As  sug-
gested in Ref. 13, an increase over the  endogenous concentration of more  than
10% over  the  lifetime  of the  source  could be taken as  a possible cause  for
concern.   The percentage increase  is simply calculated  from
       (% Increase) - [DC(ppmw) x  100)]/[Endogenous
                      Concentration (ppmw)]                              (5.4)
where the deposited concentration (DC) was calculated  in  Step 3.   The average
endogenous concentrations  from Table  3.5  can  be used but data  for the  area
of  interest  is preferable  given  the  wide range  in  natural concentrations.
       It  is  not  recommended at this  time that  a  source be flagged   for
further actions based solely on the results of this calculation.   The results
of  the  screens in Step 6 are appropriate  for  that  purpose.   However, an
indicated increase of more than 10% in this step would increase  the assurance
with  which  a  finding   that  additional  action was  necessary could  be  made.

       Calculate  Potential  Concentrations  in Plant Tissue (Step 5).      Once
the  deposited  concentration  in the soil has been calculated using Eq.  5.1,
straightforward application  of the plant:soil concentration, ratios in  Table
3.6  can  be  used  to  estimate  the  concentration in  aerial plant  parts (tissue
concentration)
       [Tissue concentration (ppmw)] *
       [Deposited concentration (ppmw)]  x [Concentration  ratio]
or
       TC (ppmw) » DC (ppmw)  x CR                                        (5.5)
using TC for  tissue concentration   and  other symbols  introduced  earlier.
Equation  5.5 requires an additional conservative  assumption:
       •  All the deposited material  is soluable  and
          available for uptake by  plants.
This assumption  is almost  always  violated  in  practice.   Table  5.4  gives
the  solubilities  of  some trace elements  based on extraction  of these elements
from  endogenous concentrations in the soil.13  of course, the solubilities of
exogenous deposited elements could differ markedly from these values as could
the  solubilities  of endogenous concentrations  in different  soils.   The solu-
bility of a  trace element  in  the  soil depends upon many  factors.   Among these

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                    Table 5.4  Solubilities of Endogenous
                               Trace Elements*>b
Element
Arsenic
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanadium
Zinc
Solubility
«)c
9
—
40
0.004
0.4
0.1
—
—
37
0.8
0.1
21
—
8
Emission Rate
Increase Factor^
11
—
2.5
25,000
250
1,000
—
—
2.7
120
1,000
4.8
—
12
               aBased on Ref. 13.
               bUsed in Step 7.
               C0nly soluable fraction would be  available
                for uptake by plants.
               dUsed when Step 8 is required.

are chemical  form,  temperature,  presence of other elements,  selective uptake
by plants, soil pH, and soil moisture  content.   The composition of the soil is
also  an important determinant  of solubility, especially  the presence of
organic matter and  clays  which can bind trace elements.   The point is that a
significant  portion of  the exogenous  concentration  may be  unavailable  for
uptake by plants, making Eq. 5.5 a conservative  estimator.

       Screen  for Potential Adverse  Impacts  from  Trace Elements (Step 6).
At  this point the  screen for adverse  impacts  from the  deposition  of trace
elements  is  straightforward.   The process  is similar to that used in Step 2,
that  is,  the comparison  of  calculated  concentrations  to tabulated screening
concentrations.   In this  step,  however, three comparisons  need  to  be made:

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                                      39

       1.   The deposited concentration (DC) is compared to
           the soil screening concentration in Table 3.4,
       2.   The tissue concentration (TC) is compared to the
           tissue screening concentration in Table 3.4, and
       3.   The tissue concentration (TC) is compared to the
           dietary screening concentration for animals in
           Table 3.7.
A calculated concentration in excess of any one of the three screening concen-
trations is an indication  that a more  detailed evaluation may be required for
the new source and/or that the FIM should be notified, since there are indica-
tions  of  potential adverse  impacts  to plant,  soils,  or  animals.   In making
these  three comparisons,  the  following additional assumptions have  been
made:
       •  All deposited forms of an element have the same  toxicity,
       •  The feeding or grazing range of animals is limited to the
          area exposed to the estimated maximum annual concentration,
          and
       •  Most importantly, it is the exogenous incremental burden
          which should be compared with the screening concentration
          values, not the burden which would result from both the
          exogenous and endogenous concentrations.
This last  assumption is critical  and  follows the procedure used  in Refs.  12
and  13.   The  assumption  is  implicit  in Eq. 5.5  where  only  the deposited
concentration  (DC)  is  used to calculate the  tissue  concentration  (TC) and  in
the three screens as defined above.
       The three screens can be compared to see which is the most restrictive.
The screening value for concentrations in aerial plant tissues and for concen-
trations toxic to  animals  can be converted  into  equivalent soil concentration
values  by  use of  the  plantrsoil  concentration  ratios.    The dietary concen-
tration potentially toxic  to animals can be thought of as  the concentration  in
aerial  plant  parts that may be  toxic  to animals.   Thus, Eq. 5.5 can be re-
arranged  to  give  the  equivalent  deposited concentration  (EDC)  corresponding
to a particular screening  tissue concentration (STC):
       EDC (ppmw) = STC (ppmw)/CR                                        (5.6)
where  the  STC is  either  the  plant tissue  screening  concentration from Table
3.4  or the animal  screening concentration  from  Table 3.7.  in  fact,  Eq. 5.6
provides an alternative approach to the screening procedure that is equivalent

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to the  one  presented here.   Table  5.5 gives the equivalent deposited concen-
trations  (EDCs)  for  the  trace elements.   Based on  the  CR's  and assumptions
used here,  animals appear  to be the  critical  receptor  for cobalt,  lead, and
                                                          «
selenium  while  tissue  concentrations  in plants  appear to  be  critical for
arsenic,  cadmium,  copper,  and  zinc.   For the  remaining  seven elements, the
soil concentration appears to be critical.   As long as the screening concen-
trations  and  concentration ratios given here are  used,  Table  5.5 can be used
to  reduce the  number of  comparisons required  for  a  screen.    For example,
cadmium sources  need only be screened  against  the single screening  value for
plant tissue  concentrations,  since this screening  concentration is shown  to be
controlling in the table.
                     Table 5.5  Equivalent Exogenous Soil
                                Screening Concentrations
Trace
Element
Arsenic
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanadium
Zinc
Equivalent
Soil*
3
0.5*
2.5
8.4d
-
40
400d
1000
2.5d
455d
SOQd
13
2.5d
-
Deposited Concentration (ppmw)
Plant
Tissue^
1.8d
2.1
0.28d
50
170
1.6d
10,300
280
6,100
-
1,300
100
-
470d
Animals0
21
-
1.4
-
9.1d
43
3,300
180d
7,600
-
22,000
5d
1,000
780
            aSame as soil value  in Table 3.4.
            bEDC * (STC for plants from Table 3.4)/CR.
            CEDC « (STC for animals  from Table 3.7)/CR.
            dContro11ing value.

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                                      41

       Since acute  fluoride  poisoning in various  species of cattle  has been
well documated,48 it  is  surprising that animals do not  appear  to be critical
for  fluorides.   This may  be due  to the omission of the  critical  pollutant
pathway involving  ingestion  by animals  of materials  deposited on  plants
prior to these materials being washed off or blown off the plants and carried
into the soil.  The same indication could be given of course, if the screening
concentration value  for the effects  of soil  fluorides  on  plants were based
upon a  very  sensitive species.   Further detailed  investigation and  more data
would  be required  to determine  whether the  latter  explanation is true  or
whether there is a deficiency in the procedure outlined here.  In either case,
the  fluoride example  serves to  illustrate  the  potential  problems  involved
in screening for impacts on air quality related values.

       Consider Effects of Solubilities  (Step 7).    The  assumption  that  all
deposited material is soluable and  available  for uptake  by plants is unlikely
ever  to be  met  in practice.   If  a  screen  indicates that a  further  action
is needed on a source because its emissions  will cause a  trace element screen-
ing  concentration  to be exceeded, an  attempt may  be  made to look  at  the
possible effect  of  reduced solubility on  that indication by considering  the
solubility of the deposited material.   This  additional  consideration  should
only  be used as  a  supportive  indicator; it  can  only increase  confidence  in
the  decision to  take further  action; it  can never  reverse such a  decision
based  on the  screens in  Step  6.   That is,  the  conservative  assumption  of
100%  solubility  should be used  in  making  the decision for  further  action  on
the  source.
        If  the solubility  of a  particular   trace  element  is  SZ, the  amount
actually available for uptake (AA) by plants is
      /Amount    \
      I  available )=» DC x (S/100)
      \for uptake/
or
        AA =  DC x (S/100).                                                (5<7)
This  value  for AA should  be  compared  with  the soil  screening  concentrations
in  Table 3.4.  An equation  similar  to Eq.  5.5 can now be  written  reflecting

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the assumption  that only  the  fraction AA of  the  deposited concentration is
available for uptake.
       TCcorr. - AA x CR - DC x (S/100) x  CR  -  TC x  (S/100)              (5.8)
where TCcorr> stands for the tissue concentration corrected  for the solubility
of the deposited material.   The new values of TCcorr% could be compared with
the screening concentrations for plant  tissues  and animals given in Tables 3.4
and 3.7,  respectively.

5.2  EXAMPLE SCREEN AND SIGNIFICANT EMISSION  RATES
       Section 5.2.1  illustrates the use  of Steps 1-7  of  the screening
procedure  through  application to  a  source of nitrogen dioxide  and  arsenic.
Whenever  source-specific  estimates  of maximum concentrations  are  available
or can be generated. Steps 1-7 should be used.  Step 8 provides an alternative
screening procedure  based on  the  concept of  significant  emission  rates
(SER).   Section 5.2.2 illustrates  the derivation  of the SER for arsenic from
the  results  for the  example source and  describes  the  use of  the SER's  for
screening.   Use  of  the  SER's  precludes  any  consideration of  the  emission
characteristics  cf the source  other  than emission rate.   Local  conditions
including background also cannot be  taken  into account.   Application  of Steps
1-7 is the preferred procedure.

5.2.1  Example  Screen
       The example  source is assumed  to have  a plume release height  of 30 m
(physical  stack plus plurae  rise).    It is  assumed  that  the  source  is  subject
to  PSD  review  and  Chat it  is  desired to screen the source  for  arsenic  and
nitrogen dioxide  among  other pollutants.   An  emission  rate  of 1  T/yr of
arsenic  is  assumed for this  example  and  estimates  of maximum concentrations
of N02 are  available for  4-hour and 8-hour averaging times.  Following Table
5.1  or  Fig. 5.2,  the  first step  in  the  procedure  is to  estimate  maximum
concentrations  for  the times listed in Table  5.2.   For arsenic,  these esti-
mates  need to  be  made.  Using the simple  modeling procedure outlined in
Appendix A, the maximufa annual  average  ground  level concentration is  found to
be  X =  0.1051  ug/m^.  Other  appropriate  models  or techniques  could  also be
used.   If an  insignificant background  is assumed for the  example,  this
result completes Step  1 of  the  screening  procedure  for arsenic.   For  N02, the

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                                      43

available results  show maximum ground  level concentrations  (including  back-
ground) of  X^. = 51  ug/m3 and Xg  » 45  ug/m  for  averaging times of 4  and 8
hours, respectively.  (A little foresight will show that estimates need  not be
made for 1 mo and 1 yr.)  These results complete Step 1.
       Then in Step 2 of the screening procedure,  these maximum concentrations
for  N(>2 would  be   compared  to the  appropriate  screening  concentrations  in
Table  3.1 or  Table  5.3.   For  N02,  the screening concentration at both 4 and 8
hours  is  3760  ug/m3.   The  estimated maxima  are  for below  this value.   No
calculation need be  done  for  the  one month  and annual averaging times,  since
the modeled 4- and 8-hour maxima are already below the corresponding  screening
concentrations.  There would thus  be no indication that a more detailed  review
would  be required for NC>2 impacts  on plants, soils,  and animals.
        Since  the screen also involves  a  trace element,  the  next step  is
Step  3.   If a 10-year  lifetime (N="10)  is assumed  and the recommended value  of
3  cm is used  for the depth of soil  throughout which  the  deposited arsenic  is
mixed,  Eq.  5.1 gives
        DC - 21.5 (N/d)X
          * 21.5 (10/3) x (.1051)  3 7.53 ppmw as the concentration
            of arsenic in the soil.
Following with Step 4 and Eq.  5.4,
        [% Increase] = 7.53 x 100/6 - 126%
where  6.0  ppmw  has been used  as the  average endogenous  soil  concentration
of arsenic  from Table 3.5.   Thus,  there is a supportive indication  that  the
source should receive further review if Step 6 shows the potential for adverse
impacts because  the  source may increase  concentrations  of arsenic in the soil
by more than  10%.   In Step 5, the plant tissue concentration  would  be  calcu-
lated  from  Eq. 5.5:
        TC - DC x CR - 7.53 x 0.14 - 1.05 ppmw.
Next the screening comparisons  are made  in Step 6.  The DC  ("7.53  ppmw)
exceeds the  soil  screening  concentration of 3 ppmw for arsenic  given  in
Table  3.4.  Similarly, the TC (1.05 ppmw) exceeds  the tissue screening concen-
tration of  0.25 ppmw given in Table 3.4.   The TC does  not  exceed the animal-
related screening concentration of 3  ppmw given in  Table  3.7.   There are thus

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two  indications  that this  source might  adversely affect plants and that
further actions need to be taken.
       To look  at  the possible effect of arsenic  solubility on  these  indica-
tions, the calculations in Step 7 can be done.  For arsenic,  Table 5.4  gives  a
solubility of 9Z  to account for the  limited  solubility  of arsenic compounds.
Equations 5.7 and 5.8 give AA - 7.53 x .09 • 0.68 ppmw and TCcorr * 1-05  x  .09
• 0.0945 ppmw.  AA does  not  exceed the soil screening concentration of 3 ppmw
and TCcOrr does not  exceed  the  tissue screening concentrations  for plants  and
animals, 0.25 ppmw and 3 ppmw, respectively.   Thus,  no  supportive indication
has  been  found  but  the  original  indication that  additional detailed  work is
required on the source is not  altered and  it is known that solubility  effects
might be important.

5.2.2  Significant Emission Rates

       Basic Levels.   This  subsection discusses the  development  of a signifi-
cant emission rate  (SER)  for arsenic  based  on the generic source discussed*in
Sec. 5.2.1 with a release height of 30 m and an expected  lifetime of 10 years.
An SER is defined  as the minimum emission  rate which would cause the source's
impact to just equal the screening concentration.  That is,
       /Sign ificantX
       I emission    I * [(Screening concentrationVCConcentration  from source)]
       \rate       /
                       x (Source's emission rate).
For arsenic in soils and the example source,
       SER(Soils) -  [3/7.53] x (1 T/yr) - 0.40 T/yr.
Arsenic emissions  from this source  in excess of 0.40 T/yr might  be expected
to cause a soil  concentration in excess  of  the screening concentration.
Similarly, significant emission rates  based on plant  tissues (TC » 1.05  ppmw)
and animal ingest ion (TC * 3 ppmw) can also be calculated:
       SER(Tissue)  »  [0.25/1.05] x (1 T/yr) - 0.24 T/yr  and
       SER(Animals) -  [3/1.05]  x (1 T/yr) =2.8 T/yr-
Such significant emission rates were calculated assuming  a 30 m  release height
as in Ref. 43,  a  10-year source lifetime,  and the air quality model presented

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                                      45

in Appendix  A.   For  pollutants  acting along  the  direct pathways,  Table  5.6
presents the  significant  emission rates.    Table  5.7 presents  such  rates  for
trace elements.   When  no modeling results  or stack  parameters  such  as  are
required  by  simple air  quality  screening  procedures are available,  the
source's emission  rates can be  compared  directly  with  those  given  in these
two tables.   As  already noted  in the discussion of  Table  5.3,  other criteria
may be  controlling particularly when  background  is  considered.   Still,  the
significant  emission  rates  presented  in Table  5.6  can.be used to screen  for
potential adverse  impacts  to plants,  animals,  and soils.  Other  criteria  may
apply to different stages of the  new source  review process.   When  applying  the
significant  emission  rates  in Table  5.7,  only  the smallest  value need  be
considered for each pollutant.   The values  based on exceeding  ten percent of
the average  endogenous soil concentration  should again only be used as suppor-
tive indicators;  the primary decision  is based upon exceeding the  values based
on the criteria for soils, plant  tissues,  and animals.
       The values tabulated  in  Table 5.7  assume  a source lifetime  of  10
years.   Significant  emission  rates for  other lifetimes  for  trace  elements
acting through the deposition pathway  are  easily calculated:
      /Significant^                 .
      /emission    \   /Tabulated     \
      Irate  for    I = I significant  I  x (10/N).                         (5.9)
      \ N year      /   Remission rate/
      \lifetime  /
Thus, for example, if the  lifetime  of  the arsenic  source in  the above example
had  been  40   years  instead  of  10  years,  the associated significant  emission
rate  based  on  the plant tissue  screening  concentration  would have been
changed from 0.24 T/yr to
       (0.24) x (10/40)  = 0.06  T/yr.

       Solubility.    As  in  Step  7,  additional  supportive  indications can  be
sought  by  considering  the  effects of  solubility.    A corrected significant
emission rate can be found from
      /Significant  \
      /emission      \   /Significant    \    /Emission rate  \
      I rate  corrected/ = (emission rate 1  x  I increase factor)            (5.10)
      \for solubility/   \frora  Table 5.7/    \from  Table  5.4/

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                    Table 5.6   Significant Emission Rates for Direct Acting Pollutants8
Significant Eviction Rate (T/yr)
Screening
Criterion
AQRV
Screening
Concentration
NAAQS
PSD Increment I
II
III
Variance
NESHAP

S02
1 3
160 170
290
5.3
110
150
69
-


24
_
110
1.5
28
55
28
-
Pollutant and Averaging Ti
NO] 00
A 4 8 M A 1 8 W
171 840 950 3,200 950 - - 760,000
760 - 950 7.000 2,500
19 _ - - _ -
190
380
190
______
M-
H2> Bthylene Fluoride Beryl HUB Lead
4 3 24 240 M 3M
6,400 10.0 0.36 0.23 0.057 11
- - - - - 11
_ _ _ _ _ _
_
_ _ _ _ _ _
_
- - - - 0.057
•Based on 30 o release height and  no background.

"Nuoerals: hours
   W:  1 week
   M:  I month
   A:  Annual

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                                      47
           Table 5.7  Significant Emission Rates for Trace Elements3


Significant
Emission
Rate (T/yr)
Criterion

Trace
Element
Arsenic
Boron
Cadmium
Chromium
Cobalt
Copper
Fluoride
Lead
Manganese
Mercury
Nickel
Selenium
Vanad ium
Zinc

Soils
.40
.067
.33
1.1
-
5.3
53C
130d
.33
6 ic
67C
1.7
.33
-

Plant
Tissue
.24
.28
.037
6.7
23C
.21
1400C
37d
810C
-
17 Oc
13C
-
63C

Animals
2.8
-
.19
-
1.2
5.7
440C
24d
1000C
-
3000C
.67
130C
100C
10% of
Endogenous Soil
Concentration*9
.08
.13
.00080
1.3
.11
.27
2.7
.13
llc
-
.53
.0067
1.3
.67
           aBased on a 30 m release height,  no  background, and  a
            source lifetime of 10 years.   For a lifetime of N years,
            divide the tabulated values by (N/10).
           bFor use as a supportive indicator only; based on a  10%
            increase over the average  values in Table  3.5.

           cExceeds the significant emission level  for TSP of 10
            T/yr established for PSD (Ref.  3).

           ^Exceeds the significant emission level  for lead of  1
            T/yr established for PSD (Ref.  3).


These emission  rate  increase factors  are simply (100/S),  the  reciprocals of
the solubilities in percent.
       Other  Stacks.  Even though  the stack  parameters  may not  be known
exactly, it may be  known  that  the  stack  is  hot or  cold.    Table  5.8 gives

stack  parameters  for four  stacks  which might  be  useful if  they are  closer
to the source's expected  stack parameters than the 30 m release height  assumed

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              Table 5.8.  Summary of Representative Stacks
Stack Parameters
Stack
30 m release
10 m cold
10 m hot
30 m cold
30 m hot
Height
(m)
30
10
10
30
30
Temperature
CK)
293
350
550
350
550
Flow
(m3/sec)
0
4
4
4
4
Emission Rate
Increase Factor
1.00
0.96
4.07
3.43
8.93
in Tables 5.6  and 5.7.   The volume flow  rate of  4  m3/sec is  felt to be
conservative for major sources unless a large number of  stacks  are  used.  Also
given in the table are emission rate increase factors for each  model stack.  A
particular factor would be used  to adjust the tabulated  significant emission
rates  in Tables  5.6 and  5.7 to  correspond more  closely to concentrations
expected from the proposed source:
      /Significant \    /Significant \
      I emission rate)   [ emission rate!    /Qnission rate \
      I corrected    I "(from Tables  I  x I increase factor]              (5.11)
      \for stack   /    \5.6 or 5.7  /    \from Table 5.8/

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        APPENDIX A

   Estimates of Maximum
Ground Level Concentrations

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                                 APPENDIX A
              ESTIMATES OF MAXIMUM GROUND-LEVEL CONCENTRATIONS

       This appendix  develops the procedure used to estimate maximum  ground-
level concentrations (mglc's) from a single source for averaging times  ranging
from one hour to one year.  The developments presented here follow the  presen-
tation in Ref. 45 which can be consulted for additional details.   The procedure
is useful for  screening  because the  calculations  can be done by hand  or
implemented in  a simple computer  program.   The procedure accounts  for  stack
parameters, plume rise, and meteorological conditions.

A.I  SHORT-TERM ESTIMATES
       The  familiar  Gaussian plume model  is  the basis for  estimating  short-
term ground level concentrations.49  According to this model the plume  center-
line concentration is given by
                                            \2
       *<*>
-1/2
(A.I)
where:
       x     * Downwind distance from source (m),
       X(x)  » Ground-level centerline concentration at x
       Q     - Source emission rate (g/sec),
       u     " Wind speed (m/sec),
       cjy(x) - Horizontal dispersion coefficient (m)
       oz(x) - Vertical dispersion coefficient (m), and
       H     * Effective stack height (m) • ha * Ah «
               (Physical stack height) + (Plume rise).

       To  derive  an analytic expression for the mglc,  the  following commonly
used representatives of the two dispersion coefficients are used:
       oy(s) - ax"                                                       (A.2)
and
        crz(x) • ex
                 .d                                                       (A.3)

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                                      52

       The parameters  a,  b,  c, and d depend upon atmospheric  stability class
and, for oz, the downwind distance x.  The following expressions  for  the esti-
mated mglc  (Xm)  and the  corresponding downwind distance x^ may  be derived.
            AQ x 106    1
       Xm	™	X Til                                                (A.4)
                       n
and
             »        •
             / O\      1 /OJ
       ^.  (|i)l_   1/2d                                                (A.5)

where:
        a - (b+d)/(2d)                                                    (A.6)
and
             2a-l
       A = •£-£—  (2a)a exp (-a)                                          (A.7)

Values for a, b, c, d, and A are presented in Table A.I.
       Both Xm  and 3% depend  on stability class and wind speed.   To estimate
these  quantities,  the plume rise  must  be estimated because  both depend upon
the  effective stack height H.   Plume  rise can be estimated using the formulas
of Briggs .52,53
Se tt ing

         F - sf^-^V                                                      (A.8)

where:
       g = Acceleration  of gravity (9.8 m/sec^).
       T » Exit gas temperature (°K),
       Ta = Ambient  temperature (°K), and
       V = Exist  gas  flow rate at temperature T (m^/sec),
it can be shown  that
       Ah(n/u) = C/u  for  neutral/unstable conditions                      (A.9)
and
       Ah(s)   = D/ul'3 for stable conditions.                           (A.10)

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           Table A.I  Dispersion Coefficient Parameters and Maximum Concentration Coefficient
Atmospheric
Stability
Corresponding
Pasquill-Gifford
Stability Class
      a*
      b*
    c**,+
      At
 Moderately Unstable

         B
       0.351
       0.867
0.139, 0.0494, 0.0494
0.947, 1.114, 1.114
0.335, 0.188, 0.188
      Neutral

         D
       0.150
       0.889
0.0856, 0.259, 0.737
0.865, 0.687, 0.564
0.396, 0.955, 3.85
 Moderately Stable

 E-F (intermediate)
       0.0853
       0.894
0.0682, 0.227, 1.437
0.814, 0.618, 0.401
0.468, 1.21, 34.7
 ^Estimated from Fig. 3.2,  Ref. 49.
**Taken  from Table  5, Ref.  51.
 *The  first numbers given for each stability are appropriate at distances between 100 and 500 m, the
   second numbers at distances between 500 and 5000 m, and the third numbers at distances greater than
   5000 m.

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                                      54

Assuming  an  ambient  temperature  of  293*K (20*C)  and  an  ambient  potential
temperature lapse rate  (36/3z) of 0.5"K/100 m, representative of moderately
stable conditions,


       C = 21.4F0-75 m2/sec for F<55 m4/sec3,                            (A.12)
       C = 38.7F0-6  m2/sec for F>55 mVsec3,  and                        (A.13)
       D =• 47.2F1/3  m*/3 sec'1^.                                        (A.14)
       A wind  speed  corresponding  to  the  mglc can now be found.  For neutral
and unstable conditions,
             , . ,    b C                                                /»  i e\
       Uworstln/uJ  * -T r—,                                              VA.uy
                     d hs
with  a corresponding mglc
                     AQ x 1Q6 . __ 1   .   (b/d)b/d
                                Ch
Xworst(n/u) = ^T-^ ' —^r '         —  '                 (A'16)
 For stable conditions
             , .   AQ x 1Q6 .  q(b-2d)/3d
       v    _(s) « —^	   	ryr	. .,.                         (A.17)
       *worst         IT       ,1/3.    _Nl+b/d
                              (u  h  + D;
                                    S
 Equation  A.17  has no  maximum unless  b/d is greater  than  2.   Operationally,
 this difficulty is solved by  setting u =• 2 m/sec  for  the stable case in which
 case Eqs. A.10 and A.17 become
       Ah(s) - 0.794 D                                            '     (A.18)
 and
             , N   AQ x 106 .  2/3d
       w^'-h—   a.26VD)^/d-                        <*•»>

       Equations  A.15,  A.16,  and A.19 are  the basic equations  used  to cal-
 culate the  short-term  mglc.   The calculations  need to be done separately for
 unstable, neutral, and stable conditions and the  maximum  value  selected for
 the mglc.   In  addition,  for each  stability class,  the calculations need to be
 done  for  three  ranges  of downwind distance because of the dependence of c, d,
 and A  on  x  (see Table  A.I).   The  value chosen  for each stability class is the

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maximum  self-consistent value, that  is,  the maximum  of the values for which
the calculated  x^ falls within the range of downwind  distances over which the
particular c, d,  and A  values  apply.
       In  implementing  this  procedure,  high worst-case  wind speeds  are
occasionally  found which  are  unlikely to  persist  for periods  of time on the
order of hours  to one day.  On the other hand,  low worst-case wind speeds are
found which  are  small  enough to render  the  Gaussian plume formulation inap-
plicable.  To  avoid both extremes and still retain a  conservative estimate of
the mglc,  limits  are placed on the worst-case wind speed  for neutral/unstable
conditions such that 0.8 jC u,, £ 30 m/sec.
       Estimates  made in  this  way are appropriate  for averaging times of one
hour.   For averaging times  out to  about 24 hours,  the one-hour estimates can
be  multiplied  by  an  appropriate conversion  factor  from Table A.2.   These
factors  represent a power law dependence  of  concentration  on  averaging time
with an  exponent  of -0.17:
       X(t) -  X(l)t-0.17.                                               (A.20)
       For averaging times between 24 hours and about one month, a recognized
simple procedure  for estimating the concentration from a. single source at one
averaging  time given the  concentration at another averaging  time  appears to
be  lacking.  Larsen54 has  developed a  method which  can be  used in multi-source
applications.   For  averaging  times  less than one  month,  he  finds  that for a
year's data
           r(t)  -  X-.-U hr)t4                                           (A.21)
 where  q depends  upon the  geometric  standard deviation  of  the concentration
 values.   The form of  Eq.  A.21 with q -  -0.17  is exactly the same as that of
 Eq.  A.20.   On the basis  of this equivalence of mathematical form, the use of
 Eq.  A.20 was  extended  beyond 24 hours  to  estimate conversion  factors  for 4 and
 10 days as  shown  in  Table  A.2.

 A.2  LONG-TERM ESTIMATES
       Expected  monthly  and  annual  mglc's  from a  single   source  are  based
 upon the "sector-averaged" form of Eq. A.l:49>55

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                                       56
                Table A.2   Averaging  Time Conversion Factors
Averaging
Time (hrs)
1
3
4
8
24
96 (4 da)
240 (10 da)
aBased on Ref. 49.
bSee discussion in text.
x(l) -/2N1/2 fQ x 106 /
v/ u]
where:


       n » the number of sectors into which the entire  360"

           range of wind directions is divided and

       f » the fraction of the time during which the wind

           direction lies in the sector of interest.


Using the same parameterization as above (Eq. A.3),


          =, BfQ x 1Q6
       rt_-       « Q
        Tq       ^ n
              uh


where:


         8 - (l-i-d)/2d


and
        B - •=•
                   _
                  2ir
                     c28'1 (2B)6 exp (-6).
                                                                         (A. 22)
                                                                         (A.23)
                                                                         (A. 24)
(A.25)
To estimate  Che  expected  long-term mglc, values  of c and d for neutral  atmo-

spheric stability and distances between  500 and 5000 m are  used and  the  plume

rise is calculated using Eq. A.9.   With these assumptions,

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        B - 0.256 and
        B - 1.23.
Examination of  annual wind  roses in Ref.  56  indicated  that the maximum  ex-
pected wind direction in a single 22.5*  sector  (n-16) is  about  27%  (f-0.27).
For monthly wind  roses,  this maximum persistence is  about 45Z  (f"0.45).
The wind speed u used for both the annual and monthly calculations  is  u  •  4.4
m/sec, corresponding  to  the nationwide annual mean  wind speed based upon  the
speeds  listed  with  the   annual  wind roses.   For  these  conditions  Eq. A.23
gives
         ,  v   0.0157 Q  x  1Q6  ,        .   . ,                         ,.
       v (yr) •       .  ...      for annual mglc s                        CA.
                      H
and
       v  (mo) » "-"*»* Q »  1()6 for monthly mglc's.                      (A.27)
        ^DL            Z • 4O

-------
58

-------
               APPENDIX B




Pollutant Sensitivities of Plant Species

-------
60

-------
    Table B.I.  Sulfur Dioxide Sensitivity of Crop Species3
                          Sensitivity
         Sensitive
                 Intermediate
              Resistant
Alfalfa
Apple
Barley
Bean, field
     , lima
Beet, sugar
     , table
Blackberry
Blueberry
Broccoli
Brussels Sprouts
Cabbage
Carrot
Celery
Chard, Swiss
Cherry, sour
       , sweet
Clover
Clover, sweet
Cucumber
Currant, red
Eggplant
Endive
Gooseberry
Grapes
Kale
Leek
Lettuce
Oats
Okra
Onion
Parsley
Parsnip
Pea
Peach
Pear
Pepper
Plum, prune
Potato, Irish
Potato, sweet
Pumpkin
Radish
Raspberry
Rye
Safflower
Soybean
Spinach
Squash
Tobacco
Turnip
Wheat
Cotton
Corn
Sorghum
Cantaloupe
Citrus spp.
 Compiled  from data in Ref.  16.

-------
                           62
       Table  B.2.   Sulfur  Dioxide Sensitivity of
                   Natural Vegetation3
     Common Name
    Scientific Name
                     Sensitive
 Alder, mountain
 Aspen, large-toothed
       , trembling
 Ash,  red  (green)
     ,  white
 Birch, gray
       , western paper
       , white (paper)
       , yellow
 Blueberry, lowbush
 Cherry, bitter
 Fir,  subalpine
 Grasses-bentgrass
        -bluegrass
        -desert grass
        -Ky. bluegrass
        -orchard grass
        -red fescue
 Hazel, beaked
       , California
 Hemlock, mountain
 Larch, western
 Maple, Manitoba
       , Rocky Mt.
 Mulberry, Texas
 Pine, eastern white
     , jack
     , red
     , Virginia
Rockspirea, creambush
Serviceberry.  low
            ,  Saskatoon
            ,  Utah
Sumac, staghorn
Tulip tree
Willow, black
 Alnua tenuifolia
 Populua grandidentata
 Populus tremit aides
 Fraxinua pennsylvanica
 Fraxinua amerioana
 Betula populifolia
 Betula papyrifera commitata
 Betula papyrifera
 Betula alleghenienaia
 Vacoinium anguatifolium
 Prunua emarginata
 Abies laaiooarpa
 Agrostis paluatria
 Poo. ormua
 Orysopsia hymenoidea
 Poo, pratenaia
 Doctylia glomerata
 Featuoa rubra
 Corylue aornuta
 Corylua aornuta  oalifornioa
 Tauga mertenaia
 Larix oooidentalia
 Acer  negundo interiua
 Acer  globrwn
 Morua miarophylla
 Pinue strobile
 Pinue bankeiana
 Pinua reainoaa
 Pinua virginiona
 Holodiscus discolor
Amelanohier stolonifera
Amelanohier alnifolia
Amelanohier utaheneia
Shua  typhina
Liriodendron tulipifera
Salix nigra

-------
               Table B.2.  (Cont'd)
   Common Name
   Scientific Name
                   Intermediate
Basswood
Birch, water
Boxelder
Chokecherry
Cottonwood, black
           , eastern
           , narrowleaf
Dogwood, red osier
Elm, American
Fir, bias an
    , Douglas
    , grand
Grape, wild
Hemlock, western
Mahogany, mountain
Maple, Douglas
      , red
Mountain-ash, western
Oak, white
Pine,  lodgepole
     ,  ponderosa
     ,  shortleaf
     ,  western white
Poplar,  balsam
Sagebrush, big
Snowberry, mountain
          ,  Columbia
Sprue e,  EngeImann
       ,  white
Witch  hazel
Tilia amerioana
Betula occidental-is
Acer negundo
Prunua virginiona
Populua triohooarpa
Populua delta-idea
Populua onguatifolia
Cornus stolonifera
Ulmue americana
Abies baleamea
Paeudoteuga menziesii
Ab-iea grondis
Vitia rn.po.ria
Teuga heterophylla
CercocarpUB montanua
Acer gldbrum douglasii
Acer rubrum
Sorbue acopulina
Quercua alba
Pinua cantorta
PinuB ponderosa
Pinua echinota
Pinua monticola
Populua balaomifera
Artemisia  tridentata
Symphoricarpoe oreophilus
Symphoriaarpoe rivularie
Pieea engelmamii
Picea, glauca
Hamamelis  virginiana
                      Resistant
 Black gum
 Buck-brush
 Buffalo-berry
 Ceanothus, reds tern
 Cedar, western red
      , white(arborvitae)
 Dogwood, flowering
 Fir, silver
    , white
 Hawthorn, black
 Nyssa sylvatica
 Ceanothus velutinue
 Shepherdia canadensis
 CeanothuB sanguineua
 Thuja plicata
 Thuja occidentalis
 CornuB florida
 Abies oanabiliB
 Abies consolor
 Crataegus douglasii

-------
                             64
                   Table B.2.  (Cont'd)
       Common Name
    Scientific Name
                    Resistant (cont'd)
    Grape, Oregon
    Grasses-blue grama
           -needle grass
           -western wheatgrass
    Juniper, common
           , Rocky Mt.
           , Utah
           , Western
    Kinnikinnick
    Locust, black
    Mahogany, curl-leaf mt.
    Maple, mountain
          , silver
          , sugar
    Oak,  gambel
       ,  live
       ,  northern red
       ,  pin
    Pine, limber
        , pinyon
    Poplar, Carolina
    Sourwood
    Spruce, blue
    Squawbush
    Sumac, smooth
    Sycamore, American
    Willow, shrubby
    Yew,  Pacific
Odostemon aquifolium
Bouteloua gracilis
Stipa sonata
Agrapyron smithii
Juniperus communis
Juniperus saopulorum
JuniperuB osteosperma
Juniperus occidental-is
Arctostaphyloe uva-ursi
Robinia pseudoacacia
Cercoaarpus ledifolius
Acer apicatian
Acer saccharinum
Acer eaccharwn
Quercus gambelii,
Queraus Virginians,
Quercus rubra
Queraus palustris
Pinus flexilis
Pinus edulis
PopuluB canadeneis
Oxydendron arboreum
Picea pungens
Shus trilobata
Ehus glabra
Platanus ocoidentalis
Salix trietis
Taxus brevifolia
aCompiled from lists in Refs.  9 and  16.

-------
Table B.3.  Ozone Sensitivity of Crop Species3
Sensitivity
Sensitive
Alfalfab
bean, pinto
, White
Broccoli
Clove rb
Corn, sweet
Oatsb
Radishc
Saffloverc
Soybean5
Spinachb
Tobacco
Tomatob
Intermediate
Bean, bush
, lima
Beet, table
Cabbage
Chard, swissd
Clover, white sweet
Corn, field
Cucumber d
Potato, Irish
Sorghum
Squash, summer


Resistant
Cotton
Lettuce
Onion








Compiled  from data  in Ref. 18.
bSome cultivars  intermediate or resistant.
cSome cultivars  intermediate.
dSome cultivars  resistant.

-------
                          66
Table B.4.  Ozone Sensitivity of Natural Vegetation3
    Common Name                   Scientific Name

                      Sensitive

 Aspen, trembling              Populus tremuloides
 Ash,  red(green)               Fraxinus pennsylvaniaa
    ,  white                    Fraxinus ameriaana
 Cottonwood,  black             Populue triohocarpa
 Grasses-bent grass            Agrostis palustris
        -blue grass            Poa armua
        -brome grass           Bromus teetonun
 Oak,  gambel                    Queroue gambelii
    ,  white                    Queraus alba
 Pine   Coulter                 Pinus  aoulteri
       eastern white           Pinus  etrobus
       jack                    Pinus  banksiana
       Jeffrey                 Pinus  jeffreyi
       loblolly                Pinus  taeda
       Monterey                Pinus  radiata
       ponderosa               Pinus  ponderosa
       Virginia                Pinus  virginiana
 Serviceberry,  Saskatoon        Amelanchier  alnifolia
 Sycamore,  American            Platanus oaoidentalis
 Tulip tree '                    Liriodendron tulipifera

                    Intermediate

 Boxelder                       Acer negundo
 Cedar,  incense                Libooedrus deourrens
 Grasses-Ky. bluegrass          Poa pratensis
        -perennial  rye          Lolium perenne
        -red  fescue             Festuoa  rubsa
 Oak,  black                     Querous  velutina
    .  pin                       Quercus  palustris
    ,  scarlet                   Onerous  coecinea
 Pine   lodgepole                Pinus aontorta
       pitch                    Pinus rigida
       shortleaf                Pinus echinata
       slash                    Pinus elliottii
       sugar                    Pinus Icanbertiana
       Torrey                   Pinus torreyana
                               Cerais aanadensis
 Sweetgum                       Liquidambar styraaiflua

-------
                     Table B.4.   (Cont'd)
      Common  Name
   Scientific Name
                       Resistant

   Basswood
   Birch,  white (papet)
   Black gum
   Cedar,  white (arboxvitae)
   Dogwood,  f1owe r ing
   Fir, balsalm
       , Douglas
       , white
   Grasses-orchard grass
   Hemlock
   Juniper,  western
   Locust, black
   Maple,  red
         ,  sugar
   Oak, mossy-cup
       , northern red
       ,  shingle
   Pine,  digger,
        ,  red
   Redwood
    Sequoia
    Spruce, black
           , blue
           , white
   Walnut, black
Tilia americana
Betula papyrifera
Nyssa sylvatica
Thuja occidentalis
Cornus florida
Abies balsamea
Pseudotsuga mensiesii
Abies concolor
Dactylis glomerata
Tsuga eanadensis
Juniperus occidental-is
Robinia pseudoaoaeia
Acer rub-man
Acer saccharum
Quercus macrocarpa
Quercus rubra
Quercus imbricaria
Pinus sabiniana
Pinus resinosa
Sequoia sempervirens
Sequoiadendron giganteum
Picea mariana
Picea pungens
Picea glaucaa
Juglans nigra
aCompiled from lists in Refs. 18 and 57.

-------
                          68
       Table B.5.  Nitrogen Dioxide Sensitivity of
                   Crop Species3
Sensitivity
Sens it ive
Alfalfa
Barley
Bean, pinto
Broccoli
Carrot
Clover, crimson
, red
Leek
Lettuce
Luc erne
Mustard, white
Oats
Parsley
Peas
Radish
Rhubarb
Tobacco''
Intermediate
Bean, bush
Celery
Citrus spp.
Corn, sweet
Cotton
Endive
Potato, Irish
Rye
Strawberry, pine
Tomato
Wheat






Resistant
Asparagus
Cabbage,
>

red
white
Corn, field
Cucumber
Kale
Kohlrabi
Onion
Sorghum





















acompiled from lists in Refs. 19, 20, and 58.

bSome cultivars intermediate or resistant.

-------
        Table B.6.  Nitrogen Dioxide Sensitivity of
                    Natural Vegetation3

       Common Name                   Scientific Name

                         Sensitive

    Grasses-Viper's grass         Seorzonera hiepaniaa

                       Intermediate

    Fir, common silver            Abies pectinate
       , white                    Abies alba
    Grasses-bluegrass             Poa arauia
    Spruce, blue                  Pieea pungene
           , white                 Picea glauea

                         Resistant

    Grasses-Ky. bluegrass         Poa prateneie

Compiled from tables in Refs. 20 and 58.

-------
70

-------
          APPENDIX C




Trace Element Air Quality Data

-------
72

-------
                                     TABLE   C-1.   AIR QUALITY DATA FOR ARSENIC
HINIHUH IUS/H3I
STATE
HO


TX





































COUNTY
BUCHANAN
CLAY
JEFFERSON
BEE
BEXAR
BOUIE
BRA20RIA
BRAZOS
BR0184
CALIIOUN
CAIIEROtl
CHAMBERS
DALLAS
DEMTOH
ECTOR
ELLIS
EL PASO
6ALVESTON
GRAY
GRAYSON
HALE
HARRIS
HAYS
HIDALGO
HOUARD
JEFF DAVIS
• JEFFERSON
LUDDOCK
HCLEIUIAM
HCMULLEH
NATAGORDA
MAVERICK
NIOLAIID
HOJIT601IERY
HOORE
IIACOGDOCHES
HUECES
ORANGE
POTTER
SAN PATRICIO
SCURRY

0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
DBS
0100
0100
0100
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
0200
ARITH
HE AM
6EO
MEAN
MAXIMUM IU6/M3I
DBS
ARITH
MEAN
GEO
MEAN
o.oioo
0.0100
0.0200
0.0200
0.0200A
0.0300A
0.0200
0.0300A
0.0300A 0.0200
0.0300A 0.1100
0.0300 0.0500
0.0300 A 0.0700
0.0200A
0.0300A
0.0300
0.0300A
0.0300A
0.0300A
0.0300
0.0300A
fl.OSOfl
0.0200
0.0200
...
0.0200
...
0.0200A
...
0.0200
0.0200A
...
...
...
0.0200
...
0.0200
0.0200A
...
0.0200
0.0300 0.3000
...
0.0300
...
0.0300 A
...
0.0200
0.0300A

...
...
0.0300
...
0.0300
0.0300A
...
0.0300
.0200
.0600
.0500
.0600
.1000
.6600
.4000
.0200
.0600
.0200
.1300
.0700
.1000
.0200
.0200
.0500
0.0300
--_
0.0200
_._
0.0200A
...
0.0700
0.0200A

-•..
...
0.0300
--_
0.0300
0.0200A

0.0200
0.0700
0.0300

0.0300

0.0300A

0.0500
0.0300A

...
---
0.0300

0.0300
0.0300 A

0.0300

0.0200
0.0200
...
0.0200A
0.0200A
I
1.0200
0.0300A 0.0200
0.0300A 0.0300
0.0200

0.0200A
0.0200A

...
0.0300A
0.0300A

0.0200
0.0200
0.0200
0.0200A
0.0300 0.2000
0.0300A 0.0200
0.0300
0.0200A
0.0200
0.0300
0.0300A

0.0200
0.0200
A INDICATES ONLY ONE STATION REPORTING

-------
TABLE  C-1.  AIR QUALITY DATA FOR ARSENIC
MINIMUM (UG/M3)

STATE COUNTY
SHITH
T ARRANT
TAYLOR
TITUS
TOM GREEN
TRAVIS
VAL VERDE
VICTORIA
WALKER
MEBB
IUCMITA
WISE

OBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
ARITH
MEAN
0.0300A
...
0.0300A
0.0200A
—
0.0200

...
...
—
—
—
GEO
MEAN
0.0300 A
— _
0.0300 A
0.0300A
...
0.0300
...
...
...
...
...
—
MAXIMUM (UG/M3)

OBS
0.0700
0.1200
O.OSOO
0.0500
0.0500
0.0700
0.0200
0.0500
0.0200
0.0200
0.0200
0.0600
ARITH
MEAN
0.0300A

0.0300A
0.0200A

0.0300
.—
...
—


—
GEO
MEAN
0.0300A

0.0300A
0.0300A
—
0.0300
...
—
—
—
—
—

-------
                                    TABLE  C-2.  AIR QUALITY DATA FOR CADMIUM
MINIMUM (U6/M3)
STATE
A2





CO

ID
IN



















m








COUNTY
APACHE
COCOIIINO
HARICOPA
HOIIAVE
HAVAJO
PIMA
LA PLATA
HONTEZUHA
SHOSHONE
ALLEN
BARTHOLOHEH
CLARK
DUCOIS
ELKMART
GRANT
HOWARD
JASPER
JEFFERSON
KMOX
LAKE
LA PORTE
MARION
HOKUOE
ST. JOSEPH
• STEUDEN
TIPPECANOE
VAHDERBURGH
VIGO
HAYNE
BELTRAtll
BIG STOIIE
BLUE EARTH
CARLTON
CLAY
CROH UIN6
DAKOTA
600DHUE
HENNEPIN
OBS
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0001
0.0100
0.0009
0.0002
0.0010
0.0009
0.0006
0.0010
0.0012
0.0001
0.0003
0.0019
0.0002
0.0012
0.0012
0.0009
0.0004
0.0006
0.0010
0.0005
0.002?
0.0005
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
ARITH
HE AN
0.0001
0.0001
0.0003
0.0001
0.0002A
0.0006
0.0001A
0.0001 A
0.0095
...
...
—
...
...
___

...
...
.._
...
...
...
...

— -
...
...
— -
—
...
—
...
...
...

...
___
—
CEO
MEAN
0.0001
0.0001
0.0001
0.0001
0.0001A
0.0001
0.0001A
0.0001 A
0.0054
...
...
...
.__
...
...
...
...
...
...

...
...
...

...
...
...
...
—
...
...
...
-_.
...
...
...
...
—
HAXIIKJM IU6/N3)
OBS
0.0100
0.0100
0.0700
0.0001
0.0100
3.0000
0.0100
0.0001
3.6800
0.0360
0.0016
0.0083
0.0024
O.OC42
0.0095
0.0143
0.0007
0.0011
0.0162
0.0031
0.0207
0.0217
0.0050
0.0019
0.0048
0.0012
0.0056
0.0075
0.0057
0.0020
0.0010
0.0020
0.0020
0.0020
0.0020
0.0090
0.0060
0.0090
ARITH
MEAN
0.0002
0.0003
0.0040
0.0001
0.0002A
0.0037
0.0002A
O.OG01A
0.4592
...
...
...
---
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
—
...
...
...
...
...
...
...
...
—
6EO
MEAN
0.0001
0.0001
0.0004
0.0001
0.0001A
0.0002
0.0001 A
0.0001 A
1.5670
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
—
	
...
...
...
...
...
...
...
...
A INDICATES ONLY ONE STATION REPORTING

-------
                                     TABLE  C-2.  AIR QUALITY DATA FOR CADMIUM
STATE
















HO






















MT
NH
COUNTY
ITASCA
KAHDIVOHI
KOOCIIICHING
LYON
MCLEOD
MILLE LACS
MOIIER
NOBLES
OLMSTED
OTTERTAIL
POLK
ST. LOUIS
SCOTT
STEARNS
WASHINGTON
HIIIOHA
ADAIR
AUDRAIN
BOONE
BUCHANAN
BUTLER
CALLAItAY
CAHOEN
CAPE GIRARDEAU
CLAY
COLE
JASPER
> JEFFERSON
LIVINGSTON
MARION
HEN MADRID
NODAIIAY
PETTIS
PIIELPS
PLATTE
ST. CHARLES
STE. GENEVIEVE
SCOTT
VERNON
DEER LODGE
RIO ARRIBA

DBS
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0016
0.0007
0.0016
0.0003
0.0012
0.0003
0.0020
0.0016
0.0012
0.0024
0.0027
0.0010
0.0012
0.0003
0.0010
o.oooa
0.0011
0.0010
o.ooso
0.0031
0.0010
0.0015
0.0100
0.0001
MINIMUM IU6/M3)
ARITH GEO
KEAII MEAN
	 . ...
...
... ...
... ...
— - ...
... ...
... ...
... _—
...
— ...
... ...
... ___
... ...
— - ...
... ...
— _ _—
... _—
...
... —
—
— . ...
... ...
... ...
...
--- ...
-— ...
... ...
— ...
— ...
... ...

... ...
... ...
... ...
— - ...
...
... ...
... ...
...
—
0.0001 0.0001
MAXIMUM (UG/H3I
CDS
0.0010
0.0020
0.0110
0.0040
0.0010
0.0010
0.0020
0.0020
0.0450
0.0020
0.0050
0.0030
O.OG20
0.01SO
0.0040
0.0020
0.0042
O.OOS3
0.0140
0.0440
0.0062
0.0055
0.0046
0.0050
0.0150
0.0066
0.0079
1.4350
0.0052
0.0050
0.0045
0.0052
0.0125
0.0053
0.0109
O.OOSO
0.0030
0.0074
0.0041
0.0500
0.0100
ARITH
HE AN
. 	
—
—

—
—
...
—


...
...
—
—
—
—
...
—
—

—


—
—
—
—
—

...



...
	

—
—
—
...
0.0002
GEO
MEAN
...
...

...
—

...
...
...
...
...

	
-__

—
...
...
	
...

	

	
	 	
...
	
...
...
. 	
. 	
. 	
...
...
...
...
	 	
	 	
—

0.0001
A INDICATES ONLY ONE STATION REPORTING

-------
                                    TABLE  C-2.  AIR QUALITY DATA FOR CADMIUM
STATE

OK
SC
TN































TX



COUNTY
SAN JUAN
OKLAHOMA
CHARLESTON
ANDERSON
BEDFORD
BLOUIT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUMBERLAND
DYER
GIBSON
6REEME
HAMQLEN
HENRY
HUMPHREYS
LINCOLN
MCIIIKII
MADISON
MARION
HAU8Y
MONTGOMERY
OBION
POLK
> PUTNAM
ROAHE
ROBERTSON
RUTHERFORD
SULLIVAN
SUMMER
HARREH
WASHINGTON
WILLIAMSON
WILSON
BEE
BEXAR
BOS1IE
BRAZORIE

OBS
0.0001
0.0001
0.0020
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
.0010
.0010
.0010
.0010
.0040
.0010
.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0300
0.0300
0.0300
0.0300
MINIMUM IUG/M3)
ARITH
MEAN
0.0002 0
0.0008 0
—
...
...
...
...
...
...
...
—
—
...
...
...
...
...
...
...
...
...
...
...
...
...
...
— _
...
---
...
...
...
...
...
...
...
0.0300A 0
0.0300A 0
0.0300 0
MAXIMUM IUS/H3)
6EO
MEAN
.0001
.0006
—
...
...
...
...
...
...
...
...

...
...
—
...
...
...
...
...
...

...
...
...
...
...
—
-—
...
...
— .
...
...
—
...
.0300A
.0300A
.0300
OBS
0.2000
5.0000
0.0020
0.0030
0.0010
0.0040
0.0010
0.0040
0.0010
0.0050
0.0020
0.0030
0.0070
0.0010
0.0090
0.0030
0.0040
0.0010
0.0040
0.0030
0.0030
0.0030
0.0100
0.0030
0.0370
0.0010
0.0090
0.0050
0.0010
O.OOjO
0.0020
0.0010
0.0010
0.0010-
0.0010
0.0300
0.0300
0.0300
0.0300
ARITH
MEAN
0.0002
0.2739
—
...
...
...
...
...

...
...
...
...

...
...

...
...
...
— .
...
...
...
...
...
...
...
...
...
...
...
...
...
—
«M
0.0300A
0.0300A
0.0300
6EO
MEAN
0.0001
0.0012
	
...
—
...
...
...
—
...
...
...
...
...
— .
...
...
_-_
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
—
	
0.0300A
0.0300A
0.0300
A INDICATES ONLY ONE STATION REPORTING

-------
                                     TABLE  C-2.  AIR QUALITY DATA FOR CADHIUft
MINIMUM IU6/H3I
STATE COUITY
BRAZOS
BROHN
CALHOUH
CAIIEROII
CHAIIBERS
DALLAS
OENTOH
ECTOS
ELLIS
EL PASO
6ALVESTON
GRAY
6RAYSON
HALE
HARRIS
HAYS
HIDALGO
IIOIIARD
JEFF DAVIS
JEFFERSON
LU6BOCK
MCLEMIAH
HCIIULLEN
MATAGOROA
HAVERICK
MIDLAND
MONTGOMERY
MOORE
. NACOGDOCHES
KUEHCES
ORAM6E
POTTER
SAN PATRICIO
SCURRY
SMITH
TARRANT
TAYLOR
TITUS
TOM GREEN
TRAVIS
VAL VERDE
VICTORIA
HALKER
DBS
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0001
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
ARITII
MEAN
0.0300A
.._
_..
0.0300
._.
0.0300
...
0.0300A
—
0.0300
0.0300A

— -
—
0.0300
—
0.0300
0.0300A

0.0300A

.._
—
—
0.0300A
0.0300A
...

...
0.0300
0.0300A
—
...

0.0300A
__.
0.0300A
0.0300A

0.0300
...

—
GEO
MEAN
0.0300A

...
0.0300
...
0.0300
...
0.0300A
—
0.0300
0.0300A
—
...
...
0.0300
...
0.0300
0.0300 A
...
0.0300A
—
...
...

0.0300A
0.0300A

.._
___
0.0300
0.0300A
...


0.0300 A
...
0.0300A
0.0300A
___
0.0300

—
—
MAXIMUM (UG/lll)
OBS
0.0300
0.0300
0.0300
0.0300
0.0300
0.1000
0.0300
0.0300
0.0300
0.1000
0.1000
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.2000
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
0.0300
ARITH
MEAN
0.0300A
	
	
0.0300
...
0.0300

0.0300A
—
0.0300
0.0300A
—
...
—
0.0300
—
0.0300
0.0300A
—
0.0300A
—
—
—

0.0300A
0.0300A
—
—

0.0300
0.0300A
...
...
...
0.0300A

0.0300A
0.0300 A

0.0300


—
GEO
MEAN
0.0300A
	
	
0.0300
...
0.0300

0.0300A

0.0300
0.0300A



0.0300
—
0.0300
0.0300A

0.0300A




0.0300A
0.0300A

	
—
0.0300
0.0300A

	 .

0.0300A

0.0300A
0.0300 A

0.0300

-_-
	
                                                                                                                                         00
A INDICATES ONLY ONE STATION REPORTIM6

-------
TAOLE  C-2.  AIR QUALITY DATA FOR CADMIUM





        MINIMUM IUG/M3)                    MAXIMUM  (UG/M3)
STATE



UT




COUNTY
MEBB
WICHITA
WISE
EMERY
6ARFIELO
KAHE
SAN JUAN
WASHINGTON
DBS
a. 0300
0.0300
0.0300
0.0001
0.0001
0.0001
0.0001
0.0001
ARITII
MEAN
...
_._
—
__•
0.0001
0.0002A
0.0001
0.0001
6EO
MEAN
...
...
...
...
0.0001
0.0001A
0.0001
0.0001
003
0.0300
0.0300
0.0300
0.0001
0.0200
0.0100
0.0100
0.0100
ARITH
MEAN
...
...
...
...
0.0003
0.0002A
0.0020
0.0002
6EO
MEAN
...

...
...
0.0001
0.0001A
0.0001
0.0001
                                                                                                 VO

-------
                                     TABLE  C-3.  AIR QUALITY DATA FOR CHROMIUM
MINIMUM (U6/H3»
STATE
AZ




CO

HO






















IN





NM

COUNTY
APACHE
COCOMINO
IIARICOPA
MOIIAVE
NAVAJO
LA PLATA
KOMTEZUHA
ADAIR
AUDRAIN
BOOIIE
BUCHANAN
BUTLER
CALLAUAY
CAMDEH
CAPE 6IRARDEAU
CLAY
COLE
JASPER
JEFFERSON
LIVINGSTON
MARION
NEII MADRID
MODAIIAY
PETTIS
PHELPS
• PLATTE
ST. CHARLES
STE. GENEVIEVE
SCOTT
VERHOII
ALLEN
BARTHOLOMEW
ELKHART
LAKE
MOttROE
VANOERBURGH
RIO ARRIBA
SAN JUAN
OB3
0.0010
0.0010
0.0010
o.ooto
0.0010
0.0010
0.0010
0.0060
0.0060
0.0040
0.0060
0.0050
0.0050
0.0040
0.0060
0.0070
0.0060
0.0070
0.0030
0.0040
0.0060
0.0050
0.0060
0.0070
0.0050
0.0050
0.0050
0.0090
0.0050
0.0070
0.0050
0.0010
0.0020
0.0060
0.0050
0.0040
0.0010
0.0010
AIUTII
MEAN
0.0020
0.0020
—
0.0010
0.0030A
0.0020 A
0.0030A


—
—
...
...
...
...
...
...
—

-_.
...

_—
...
...
...


...
—
...
...
...
...
...
—
0.0020 A
0.0020
GEO
MEAN
0.0010
0.0010
—
0.0010
0.0010A
0.0010A
0.0010A
...
...
—

--_
...
...
_-_
...
...
...
...
...
...
...
...
...
...
...
_..
.__
...
—
...
...
...
...
...
—
0.0010A
0.0010
MAXIMUM (UG/M3)
DBS
0.0500
0.0700
0.0010
0.0300
0.0500
0.0500
0.0400
0.09SO
0.0920
0.0170
0.0860
0.0130
0.0670
0.0310
0.0180
0.0600
0.0640
0.0150
0.0640
0.0£80
0.0670
0.2370
0.0610
0.0110
0.0840
0.0620
0.0080
0.0090
0.0760
0.0130
0.0270
0.0140
0.0090
0.0160
0.0110
0.0100
0.0500
0.0500
ARITH
MEAN
0.0030
0.0050

0.0040
0.0030A
0.00'iOA
0.0030A
...

—
—




...

—


—
—
—
_—
	


	
...
—
«...
-«
...
....
- — .
...
0.0030A
0.0030
GEO
MEAN
0.0010
0.0020

0.0020
0.0010A
0.0020A
0.0010A
- — —
	
	
	
-_..

— ..

...
...
--.
	

-.-
...
—..
...
_._
...
-_-
— -
...
	
...
...
...
___
.>_<•
—
0.0010A
0.0010
                                                                                                                                        oo
                                                                                                                                        o
A INDICATES ONLY ONE STATION REPORTING

-------
                                    TABLE  C-3.  AIR QUALITY DATA FOR CHROMIUM
MINIMUM (U6/M3)
STATE
SC
TH































TX






COUNTY
CHARLESTON
ANDERSON
BEDFORD
BLOUHT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUCERLAND
DYER
GIBSON
GREENE
HAHBLEN
HENRY
HUMPHREYS
LINCOLN
NCHINN
MADISON
MARION
HAURY
MONTGOMERY
OBION
POLK
PUTNAM
ROANE
ROBERTSON
- RUTHERFORD
SULLIVAN
SUKIIER
MARREH
MASHItlGTOH
WILLIAMSON
HILSOH
BEE
BEXAR
BOMIE
BRAZORIA
BRAZOS
BROtiH
CALHOUH
ARITII
ODS MEAN
0.1530
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0050
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
6EO
MEAN

...
...
...
...
...
...
—
— -
...
...

...
...

...
...
...
...
...
...
...
...
...
...
...
...

...
...
— .
...
—
...
...
...
...
...
...
—
MAXIMUM (US/113)
ODS
0.1530
99.0000
.0050
.0050
.0050
.0050
.0010
.0050
0.0090
0.0050
0.0050
0.0010
0.0050
0.0050
0.0050
0.0010
0.0050
0.0050
0.0050
0.0050
0.0090
0.0050
0.0050
0.0020
0.0050
0.0050
0.0050
0.0050
0.0050
0.0050
0.0010
0.0010
0.0050
0.0200
0.0900
0.0900
0.0300
0.0200
0.0200
0.0200
ARITH
MEAN
...
...
...

...
...
...
...
...
...
...
...
...
...

...
...

...
...
—
...
...
...
...
...
...
...
...
...
...
...
—
....
...
...
...
...
...
...
6EO
HEAH
—
...
...
...
...
...
...
...
...
...
...

...
...

...
...
...
...
— _
— _
...
...
...
...
...
...
...
...
...
...
...
—

...
...
— —
.— ••
.— .
...
                                                                                                                                        03
A irUICATES DULY 0>IE STATION REPORTINS

-------
                                     TABLE  C-3.  AIR QUALITY DATA FOR CHROMIUM

STATE COUNTY
CAMERON
CHAMBERS
DALLAS
DENTON
ECTOR
ELLIS
EL PASO
GALVESTON
GRAY
6RAYSQM
HALE
HARRIS
HAYS
HIDALGO
HOWARD
JEFF DAVIS
JEFFERSON
LUCBOCK
MCLEKNAN
KCHULLEN
HATAGORDA
MAVERICK
MIOLAIID
MONTGOMERY
MOORE
NAGOOOCHES
NUEIICES
ORANGE
• POTTER
SAN PATRICIO
SCURRY
SMITH
T ARRANT
TAYLOR
TAYLOR
TON GREEN
TRAVIS
VAL VERDE
VICTORIA
WALKER
tIEDQ
WICHITA
WISE
MINIMUM (U3/M3I
ARITII GEO
DBS MEAN MEAN
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0010
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200

023
0.2400
0.0200
O.CBOO
0.0200
0.0500
0.0200
0.1'iOO
0.1000
0.0200
0.0200
0.0200
0.5600
0.0200
0.0200
0.0500
0.0500
0.0700
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0230
0.0200
0.3100
0.0200
o.oaoo
0.0700
0.0200
0.0700
0.0700
0.0700
0.0200
0.0200
0.0700
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
MAXIMUM (UG/M3)
ARITH GEO
MEAM MEAN

... ...
... ...
— ...
.__ -__
...
...

...
—
.__ —
...
—
...
...
._. ...

—
... ...
...
-._
— ...
... ...
—

—
...
___
— ...
— ...
— ...
... 	
	
. — 	
— . ._.
... . 	
	 . __.
	 . 	
	 	 .

.__
	 . .._
— —
                                                                                                                                         CD
                                                                                                                                         ro
A INDICATES ONLY ONE STATION REPORTING

-------
                                      TABLE  C-3.  AIR QUALITY DATA FOR CHROMIUM


                                              MINIHUH (UO/H3I                     HAXII1UH IU6/H3I
                                                  ARITII       6EO                     ARITH       6EO
STATE   COUNTY                          DBS        HEAII       HEAH          DBS        MEAN       HEAH


 UT      EMERY                        0.0010      —        —          0.0300
         6ARFIELD                     0.0016     0.0020     1.0010        0.0500     0.0040     0.0010
         KANE                         0.0010     0.0030A    0.0010A       0.0300     0.0030A    0.0010A
         SAM JUAN                     0.0010     0.0010     0.0010        0.0400     0.0040     6.0020
         WASHINGTON                   0.0010     0.0020     0.0010        O.O'iOO     0.0030     0.0010
                                                                                                                                         00

-------
TABLE  C-4.   AIR QUALITY DATA FOR FLUORIDE  ION
MINIMUM (UG/M3)

STATE COUNTY
AZ HARICOPA
NO BARNES
BILLINGS
BOI1IIAN
BURLEIGH
CASS
DUNN
GRAND FORKS
GRANT
HETTINGER
HCKEHZIE
MCLEAN
MERCER
MORTON
MOUNTRAIL
OLIVER
RAMSEY
RICIILANO
SHERIDAN
STARK
STUTSHAM
HARD
UILLIAHS

DBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
ARITH
MEAN
0.0300
0.0200A
0.0200A
0.0200A
0.0300A
0.0200
0.0200
0.0200
0.0300A
0.0200
0.0200A
0.0200A
0.0200
0.0200
0.0200
0.0200
0.0200A
0.0200
0.0200
0.0200
0.0200
0.0200 A
0.0200
GEO
MEAN
0.0300
0.0300A
0.0300A
0.0300A
0.0300A
0.0300
0.0300
0.0300
0.0300A
0.0300
0.0300 A
0.0300A
0.0300
0.0300
0.0300
0.0300
0.0300A
0.0300
0.0300
0.0300
0.0300
0.0300 A
0.0300
MAXIMUM IUG/M3I

DBS
0.3700
0.0500
O.OSOO
0.0200
0.3500
0.0300
0.0200
0.1900
0.1200
0.0200
0.0200
0.1600
0.3000
0.0600
0.0200
0.1100
0.0200
0.0200
0.0200
0.0200
0.1400
0.0200
0.0200
ARITH
MEAN
0.0500
0.0200A
0.0300A
0.0200A
0.0400A
0.0300
0.0200
0.0300
0.0300A
0.0200
0.0200A
0.0200A
0.0600
0.0300
0.0200
0.0300
0.0200A
0.0200
0.0200
0.0200
0.0300
0.0200 A
0.0200
GEO
MEAN
0.0400
0.0300A
0.0300A
0.0300A
0.0300A
0.0300
0.0300
0.0300
0.0300 A
0.0300
0.0300A
0.0300A
0.0400
0.0300
0.0300
0.0300
0.0300 A
0.0300
0.0300
0.0300
0.0300
0.0300 A
0.0300
                                                                                                 co

-------
                                    TABLE  C-5.  AIR QUALITY DATA FOR LEAD
MINIMUM (UG/M3)
STATE
AL




AZ












AR



CA
















COUNTY
OBS
ETOHAII 0.1700
JEFFERSON
MADISON
MOBILE
MONTGOMERY
APACHE
COCHISE
COCOHUiO
GILA
GRAHAM
GREEHLEE
MARICOPA
HOIIAVE
NAVAJO
PIMA
PINAL
YAVAPAI
YUMA
CRITTENOEN
MILLER
MONTGOMERY
.2000
.2200
.3500
.2300
.0010
.0010
.0010
.0010
.1000
.0010
.0010
.0010
.0010
.0010
.1000
.0010
.1000
.3800
.2300
.0500
PULASKI 0.3000
ALAMEDA 1.4900
FRESNO 0.2900
> KERN 0.1960
LOS ANGELES 0.5200
MADERA 0.2150
MERCED 0.2110
MODOC 0.1860
MONTEREY 0.0450
NAPA 0.0600
ORANGE 0.4400
RIVERSIDE 0.0900
SACRAIIEMTO 0.2600
SAN BERNARDINO 0.4100
SAN DIE60 0.2500
SAN FRANCISCO 0.3400
SAN JOAQUIN 0.2830
SAN MATED 0.0100
ARITH
MEAN
0.5300A
0.9400A
0.6500A
...
...
0.0140
0.0190A
0.0120
...
...
...
0.5530
0.0130
0.0150
0.3600
...
...
...
...

...
0.9100A
0.7210
1.5100A
1.431QA
1.9100
...
...
-__
0.5020A
0.7290A
1.8000A
0.6120
0.6310
1.5600
0.9680
0.9000A
...
0.6580 A
CEO
MEAN
0.4400A
0.8400A
0.5500A
...
...
0.0010
0.0090A
0.0060
...
...
...
0.0220
0.0050
0.0070
0.3210
...
...
...
...
—
...
0.8390A
0.6110
1.1200A
1.0960A
1.6100
...
___
-__
0.4160A
0.5460A
1.4200A
0.5310
0.7900
1.4000
0.9900
0.8000A
«.
0.46 10A
MAXIMUM IU6/H3)
OBS
2.0600
4.2300
1.9600
2.9400
3.0900
0.2000
0.9300
0.6200
0.4000
0.4000
0.4000
9.3670
0.3000
0.3000
2. 1870
0.5000
0.2000
0.4000
2.8700
1.0500
0.1500
1.6300
6.1100
5.1300
5.5320
8.9400
2.0610
O.C700
0.1260
1.5120
4.0500
6.4900
4. 5 '.90
8.5000
4.5500
6.2600
6.9100
0.4630
4.2600
ARITH
MEAN
0.5300A
0.9400A
0.6500A
...
...
0.0320
0.0190A
0.0260
...
...
...
2.3240
0.0180
0.0150
1.0010
...
...
...
...
...
...
0.9100A
1.2150
1.5100A
1.4310A
2.5900

•._•.
___
0.5020A
0.7290A
.6000 A
.8390
.1000
.6550
.5930
.0290A

0.6560A
6EO
MEAN
0.4400A
0.8400A
0.5500A
...
—
0.0160
0.0090A
0.0130
...
...
... '
1.7560
0.0070
0.0070
0.8470

...
—
	
...
.--
0.8390A
0.8800
1.1200A
1.0960A
2.6500

...
...
.4 160 A
.5460A
.4200A
.6740
.5150
.4820
.1040
.8890A

0.4610A
                                                                                                                                       00
                                                                                                                                       in
A INDICATES ONLY ONE STATION REPORTING

-------
                                     TABLE  C-5.  AIR QUALITY DATA FOR LEAD
HIIIIHUH IUG/H3)
STATE

CO
CT
OE
DC
FL
GA
ID
IL
COUNTY
SANTA BARBARA
SANTA CLARA
SISKIYOU
SOLA! 10
SONOMA
TEHAHA
VENTURA
DENVER
LA PLATA
HONTEZUMA
FAIRFIELD
HARTFORD
NEH HAVEN
KENT
NEM CASTLE
HASHINGTON
DADE
OUVAL
HARDEE
HIGHLANDS
HILLSBOROUGH
PINELLAS
• CHATHAM
FULTON
HUSCOGEE
ADA
BAIINOCK
BUTTE
IIEZ PERCE
SIIOSIIOUE
COOK
LAKE
PEORIA
ROCK ISLAND
ST. CLAIR
OBS
0.0870
0.3100
0.0620
0.0300
0.0800
0.0670
0.1920
0.4000
0.0010
0.0
C.6300
0.5400
0.4600
0.0500
0.0700
0.4600
0.1000
0.3000
0.0400
0.0
0.1500
0.1100
0.1000
0.4100
0.1900
0.2SOO
0.1200
0.0
0.2000
0.0200
0.1500
0.1500
0.2800
0.1600
0.0300
ARITH
MEAN
1.1050A
1.6200
0.2600 A
0.4840
0.0170
0.0250 A
1.3020 A
I.0650A
1.1220
0.1600A
0.5300
—
0.3460
0.8900A
0.5590A
1.2000A
0.6100A
0.7800 A
0.5170
—
GEO
HEAN
0.7940A
0.8460
0.2050 A
0.3480
0.0060
0.0120A
1.2060A
0.9890A
1.0100
0.1300A
0.3900
—
0.2590
0.8000A
0.4600A
1.0700A
0.5500A
0.7000A
0.4390
—
MAXIMUM (UG/M3)
OBS
5.2470
8.5000
0.8430
1.3000
2.0000
0.3460
1.9370
3.6400
0.1700
0.1100
2.4600
2.2500
4.1900
0.5200
3.0700
3. 1800
6.9000
2.7200
0.5200
0.1100
2.5200
1.3100
1.3700
3.2800
2.9400
2.6200
1.0500
0.1300
1 .8300
82.0900
4.3SOO
1.9200
3.9000
1.9900
1.4400
ARITH
MEAN
1.1050A
1.4280
0.2600A
0.4840
0.0220
0.0250A
1.3020A
1.0650A
1.9160
0.1600 A
1.5000
—
2.0270
0.0390A
0.5590A
1.2000A
0.6140A
0.7800 A
15.7250
—
GEO
HEAN
0.7940A
1.11CO
0.2050 A
0.3480
0.0100
0.0 120 A
1.2060A
0.9S90A
1.7340
0.1300A
1.4200
—
1.7460
0.8000A
0.4600A
1.0700 A
0.4870 A
0.7000A
11.7850
—
                                                                                                                                        00
A INDICATES ONLY ONE STATION REPORTING

-------
                                    TABLE  C-S.  AIR QUALITY DATA FOR LEAD
STATE



IN






















IA







KS


KY

COUNTY
SANGAHON
MILL
MINNEBA60
ALLEN
BARTHOLOHEH
CLARK
DELAWARE
DUBOIS
ELKIIART
FLOYD
6RAIIT
HaiARD
JASPER
JEFFERSON
KNOX
LAKE
MINIMUM IU6/H3I
ARITH 6EO
OBS MEAN MEAN
. 1800
.3100
.2000
.2940
.1290
.3550
.3300
.1630
.2560
.4600
.1940
.1400
.0310
.1300
.2060
.1080
LA PORTE 0.2380
MARION 0.0560
MONROE 0.0400
PARKE
ST. JOSEPH
STEUDEN
TIPPECAHOE
VANOERBURGH
VI60
HAYNE
• BLACKHAIK
DELAIIARE
DUBUQUE
LEE
LIUM
POLK
POTTAHATAMIE
SCOTT
SEDGUICK
SHAIMEE
HYAIIOOTTE
.0600
.2350
.0440
.6810A
.4300A
.3370A
...
.4870A
.5080A
...
.4850A
.5150A
.1210A
.3770 A
.4990A
.5910
.4400A
.8300A
.7280A
...
.6000A
.1780A
.2220 0.5300A
.1720 0.5250A
.1930 0.5120A
.1960 0.5280
.6130A
.3660A
.1770A
...
.4440A
.4770A
—
.4420A
.45SOA
. 1070A
.3380A
.4620A
.4910
MAXIMUM IU6/M3I
OBS
.8300
.2100
.0500
.8200
.0460
.4040
.2900
.0780
.1020
.0600
.9970
.5120
.2720
.0410
.2810
.8700
.4160A 0.7700
.7070A 5.2550
.6360A
(
.5190A
1.8610
1.2800
1.3500
.1640A 0.3760
.4930A
.4670A 1
.4420A
.4600
1.0500
1.3620
1.5340
1.6340
.1700 0.4300A- 0.3900A 2.0100
ARITH
MEAN
...
...
...
0.6810A
0.4300A
1.3370A

0.4870A
0.5080A
...
0.4850A
0.5150A
0.1210A
0.3770A
0.4990A
0.7320
0.4400A
0.8300A
0.7230 A
...
0.6000A
0.1780A
0.5300A
0.5250A
0.5120A
0.6270
0.5S40A
GEO
MEAN
...
...
...
0.6130A
0.3660A
1.1770A
...
0.4440A
0.4770A
...
0.4420A
0.4580A
0.1070A
0.33SOA
0.4620A
0.6440
0.4160A
0.7070A
0.6360A
—
0.5190A
0.1640A
0.4930A
0.4670A
0.4420A
0.5840
0.5090A
.0520 — — 0.2800
.0200 — — 99.0000
.1100 — — 0.3200
.1500 0.5400A 0.4500A 1
1.8300
.3400 1.0070A 0.9030A 2.7500
0.5180A
1.0070A
0.4680A
0.9030A
.4500 — — 0.6500
.3000 — — 2.6700
.2000 — — 1
.1600 — — 1
1.1400
1.6400
.0900 0.5100 0.4600 3.0200
...
...
0.4280
...
...
0.3840
BOYD 0.1300 — — 3.8900
FAYETTE 0.2900 — — 3.5600
A INDICATES ONLY ONE STATION REPORTING

-------
                                      TABLE  C-5.  AIR QUALITY DATA FOR LEAD
HINIHUH IUB/H3)
STATE



LA



HE

HO

HA



HI




mi














,

COUNTY
JEFFERSON
KENTON
HARREH
CADOO PARRISH
EAST BATON ROUGE PARRISH
IBERVILLE PARRISH
ORLEANS PARRISH
CUII3ERLAI10
HANCOCK
BALTIIIORE (CITY)
CALVERT
CENTRAL HA. APCO
METROPOLITAN BOSTOtl APCO
PIONEER VALLEY APCO
SOUTHEASTERN HA. APCO
GENESEE
IIIGIIAH
KENT
SAGINAH
HAYHE
BELTRAHI
BIG STONE
• BLUE EARTH
CARLTOM
CLAY
CROW MING
DAKOTA
GOODHUE
HEHilEPIN
ITASCA
KAtiDIYOHI
KOOCHICIIIHG
LYOU
HCLEOD
HILLE LACS
HOMER
NOBLES
OBS
0.2700
0.3200
0.1900
0.2000
0.2SOO
0.0300
0.3900
0.1000
0.0
0.4400
0.0300
0.3000
0.4000
0.6500
0.1900
0.3800
0.2100
0.2700
0.1400
0.1800
0.0860
0.0060
0.2690
0.0530
0.0530
0.0130
0.0550
0.3130
0.1800
0.0220
0.1120
0.0320
0.1730
0.1130
0.3330
0.2190
0.0520
ARITII
HEAH
0.9760A
0.7100A
0.4800A
0.6720A
1.1500A
0.1300A
0.8000
0.4500 A
0.0600A
1.0700 A
0.1700A
0.8400A
...
...
—
...
_._
.--
0.4000 A
—
_._
— -

___
...
—
...
.-,
1.2700A
.-_
—
._.
...
...
...
...
...
GEO
MEAN
0.9400A
0.6300A
0.4100A
0.6100A
0.9000A
0.1100A
0.7700
0.4000A
0.0400 A
0.9SOOA
0.1400A
0.7400A
.__

—
...
...
...
0.3700A

...
...
._.
...
...
...
—
_—
0.9400A

...
...
...

...
	 .
—
MAXIMUM IUG/113)
ODS
3.JSOO
1.2200
1.1500
1.4400
4.2600
0.3300
1.6400
1.4700
0.3900
2.5000
0.3900
1.8600
1.3900
2.9000
1.1700
1.3400
1.7100
2.2500
0.9100
2.7100
0.1560
0.1130
0.75SO
0.2230
0.1150
0.2790
0.4750
1.2540
8.8100
0.1190
0.2040
0.4450
0.3670
0.3200
1.2220
0.3910
0.1720
ARITH
HEAH
1.1800 A
0.7100A
0.4&OOA
0.6720A
1.1500A
0.1300A
1.0300
0.4500A
0.0600A
1.0700 A
0.1700A
0.8400A

	
—
— — —

...
0.4 000 A
—
	
*-.
...
*— .
---
«._
---
_.--
1.2700A

— •__
_--
«.- —
_ — .
— __
•— -»
—
GEO
HEAH
0.8910A
0.6800A
0.4100A
0.6100A
0.9000A
0.1 100 A
0.9330
0.4000A
0.0400A
0.9800A
0.1400A
0.7400A

...
—
»«
...
...
0.3700A

...
»—
_*-
._•
...
...
....
...
0.9400A

...
...
...
...


...
                                                                                                                                         00
                                                                                                                                         CO
A INDICATES OIILY ONE STATION REPORTING

-------
                                     TABLE   C-5.   AIR QUALITY DATA FOR LEAD
MIMIHUH IUG/M3)
STATE









H3

KO
























NT


COUNTY
OLMSTEO
OTTERTAIL
POLK
RAMSEY
ST. LOUIS
SCOTT
STEARHS
WASHINGTON
HINOHA
HINDS
JACKSON
ST. LOUIS (CITYI
ADAIR
AUDRAIN
BQOIIE
BUCHANAN
BUTLER
CALLAIIAY
CAHOEN
CAPE 6IRARDEAU
CLAY
COLE
JACKSON
JASPER
JEFFERSON
LIVINGSTON
> IIARION
MEN MADRID
NODASIAY
PETTIS
PIIELPS
PLATTE
ST. CHARLES
STE GENEVIEVE
SCOTT
SHANNON
VERNON
6LACIER
JEFFERSON
LEIUS AW CLARK
ODS
0.2150
0.0840
0.0530
0.0720
0.0010
0.0320
0.0100
0.2180
0.1110
0. 1400
0.0020
0.2900
0.1200
0.1100
0.1100
0.0500
0.0190
0.1150
0.0100
0.0680
0.0010
0.0900
0.3500
0.1600
0.2340
0.0900
0.1700
0.1000
0.0460
0.1970
0.0690
0.0900
0.2400
0.1400
0.1400
0.0300
0.1490
0.0
0.0600
0.3300
ARITH
MEAN
...
_..
...
...
...

...
...
...
0.7500A
—
0.8900A

...
...

_..
...
...
...
...
...
...
...
...

—
...
...
— .
...
___
...
...

0.0790A
...
...
—
GEO
MEAN
...
...
...
...
...
...
...
...
...
0.6700A
—
0.8100A
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
— .
0.0710A
...
...
—
MAXIMUM (UG/M3)
DOS
2.3930
0.3140
0.1320
3.8600
2.3100
0.3430
1.1350
0.5610
0.5770
2.7600
0.4200
2.9200
0.5540
4.2300
2.9400
2.8100
4.0600
0.3920
0.7280
0.3100
2.1790
0.7300
1.3900
0.9600
37.5300
0.6120
1.0800
0.6360
0.3150
0.3500
0.2300
1.1420
0.6510
0.3700
2.1900
0.1900
0.3130
0.0600
10.9700
24.6200
ARITH
MEAN
...
...
...
...
...
...
...
...
—
0.7500A
—
0.8900A
...
...
...
...
— _
...
...
...
...
—
...
...
...
...
...
...
...
...
...
...
...
...
...
0.0790A



6EO
MEAN
w..
...
...
...
...
...
...
...
—
0.6700A
—
0.8100A
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...

...
— -
0.0710A


...
                                                                                                                                        00
                                                                                                                                        VO
A IIDICATES ONLY OtIE STATION REPORTING

-------
                                      TABLE  C-5.   AIR QUALITY DATA FOR  LEAD
MINIMUM (UG/M3)
STATE


MB


NV


NH

NJ







NH


NY
i







NC



COUNTY
POWDER RIVER
ROSEDUD
DOUGLAS
LANCASTER
THOMAS
CLARK
HASHOE
WHITE PINE
CODS
MERRIHACK
CAMDEN
ESSEX
GLOUCESTER
HUDSON
MERCER
MIDDLESEX
PASSAIC
UNION
BERNALILLO
RIO ARRIBA
SAN JUAN
ALBANY
ERIE
JEFFERSON
MOHROE
HEM YORK
NIAGARA
OMEIDA
OHOUDAGA
WESTCIIESTER
DARE
DURHAM
FORSYTH
GUILFORD
MECKLENBURG
OBS
0.0
0.0
0.2400
0.1200
0.0020
0.5300
0.3100
0.0
0.0020
0.2000
0.3100
0.2200
0.1300
0.2600
0.4000
0.4800
0.6100
0.6500
0.4800
0.0010
0.0010
0.1700
0.4300
0.0100
0.5700
0.2700
0.2300
0.4600
0.2700
0.4100
0.0200
0.3600
0.2900
0.3300
0.2300
ARITH
MEAN
...
...
...
0.3800A
—
...
— .
—
...
—
...
...
...
...
...

...
—
1.2700A
0.0130A
0.0130
...
—

...
...
...
...
...
—
...
...
0.8000
0.6900
GEO
MEAN
...

...
0.3400A
—
...
...
—
...
—
...
...
...

...
...
...
—
1.0600A
0.0040A
0.0060
...
--_
...
...
...
...
...
—
—
...
...
0.7400
0.5900
MAXIMUM IUG/M3)
OBS
0.0400
0.0300
1.9900
0.9500
0.0500
6.5200
5.2200
0.0400
0.1600
1.5300
2.5200
2.1100
1.1200
2.4900
4.4200
1.4400
3.0500
4.8600
4.3200
0.1600
0.1100
1.2700
1.3SOO
0.2600
1.2700
2.3700
0.7500
1.9000
2.7000
2.1400
0.2500
4.0300
2.2200
3.0600
3.8100
ARITH
MEAN
...
	
...
0.3800A

...

...
—
—
...
...
...
...
...
— -
...
— .
1.2700A
0.0140A
0.0230
...
...
...
._.
...
...
...
...
—
	
...
0.9230
0.7550
GEO
MEAN
...
	
...
0.3400A

...
	
—
—
...
...
...
...
...
...
...
...
—
1.0600A
0.0070A
0.0120
	
...
...
...
...
...
...
...
...

...
0.8300
0.6270
                                                                                                                                        MD
                                                                                                                                        o
MD      BURLEIGII                     0.3500


A INDICATES ONLY ONE STATION REPORTING
0.5700

-------
                                    TABLE  C-5.  AIR QUALITY DATA FOR LEAD
HINIHUH (U6/H3I
STATE
OH








OK


OR

PA






















RI
COUNTY
CUYAHOBA
FRAIKLIN
HAMILTON
JEFFERSON
LUCAS
HAIIOIUNu
MONTGOMERY
SCIOTO
SUMtT
CHEROKEE
OKLMIOHA
TULSA
CURRY
HULTNOHAH
ALLEGHENY
BEAVER
BERKS
BLAIR
BUCKS
CAIIBRIA
CHESTER
CLARION
DAUPHIN
ERIE
< INDIANA
LACKAllANNA
LANCASTER
LEHIGH
LUZERNE
LYCONING
NERCER
MONTGOMERY
NORTIIAHPTON
NORTHUMBERLAND
PHILADELPHIA
WESTMORELAND
YORK
PROVIDENCE
OBS
0.4300
0.2700
0.3600
0.1300
0.2600
0.2500
0.4300
0.1300
0.2800
0.0500
0.0100
0.0005
0.0020
0.0020
9.5200
0.5S60
0.2900
0.0010
0.1600
0.0020
0.1600
0.0300
0.2400
0.0200
0.1600
0.6500
0.1170
0.0700
0.2800
0.3230
0.2340
0.2530
0.16SO
0.2400
0.4600
0.1670
0.2900
0.3800
ARITH
MEAN

0.7900A
O.B200A
...
«_
0.6100
0.9800
0.4100
0.5700A
...
0.1810
0.5300A
0.0300A
0.8300A
...
...
0.8IOOA
-_.
...
_._
0.5100
...
1.0400
0.6000A
--..
2.0500A
.._
0.7900A
0.7900
...
...
...
...
0.6600A
1.2480
...
0.7200A
—
6EO
HE AN

0.7100A
0.7500A
...
...
0.5500
0.8600
0.3600
O.S500A
...
0.0650
0.4700A
0.0100A
G.6600A
_«»
._-
0.7400A
...
...
...
0.4700
...
0.9000
0.3000A
...
1.8500A

0.7100A
0.7200
...
...
...
...
0.6100A
1.1790
...
0.6600A
...
HAXINUH (UG/H3)
OSS
1.8700
2.3100
1.8000
1.4200
1.7200
1.4700
2.7500
1.0400
1.2000
0.2100
30.0000
1.4200
0.0700
4.2300
3.1100
2.8i)20
6.43SO
2.8250
2.2600
3.2430
1.3SOO
0.4400
2.6000
2.1630
0.9600
6.6100
2.7500
2.6600
2.6200
1.7820
1.5640
2.1700
1.4550
0.3300
2.7200
2.5S90
2.2630
2.0300
ARITH
HE AN
...
0.7900A
0.8200A
...
...
0.6100
0.9800
0.4100
0.5700A
..»
1.9120
0.5300A
0.0300A
0.8300A
...
._.
0.8100A
...
...

0.5670
-—
1.0400
0.6000A
...
2.0500A
_..
0.7900A
0.8270

...
...
_»
0.6600A
1.3200

0.7200A
...
GEO
MEAN

0.7100A
0.7500A
— .
...
0.5500
0.8600
0.3600
0.5500A
...
1.5170
0.4700A
0.0100A
0.6600A
...
...
0.7400A
...
...
...
0.4860
...
0.9000
0.3000A
...
1.8500 A

0.7100A
0.7820

.._"*
...
...
0.6100A
1.2100

0.6600A
...
A INDICATES ONLY ONE STATION REPORTING

-------
                                     TABLE  C-5.   AIR QUALITY DATA FOR LEAD

STATE

SC


SD

TN


































COUNTY
WASHINGTON
CHARLESTON
GREENVILLE
RICHLAIID
CUSTER
HINHEHAHA
ANDERSON
BEDFORD
BLOUIIT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUMBERLAND
DAVIDSON
DYER
GIBSON
GREEN
HAI1BLEH
HENRY
HUMPHREYS
KNOX
LIMCOLN
HCMIIitt
MADISON
> MARION
HAURY
MONTGOMERY
OBIOH
POLK
PUTNAH
ROANE
ROBERTSON
RUTHERFORD
SHELBY
SULLIVAN
SUMMER
HARKEH
UASHIN6TON
HILLIAM30N

CBS
0.0300
0.8450
0.3500
0.0500
0.0
0.0200
0.5800
0.2800
0.6500
0.2000
0.4500
0.5300
0.1600
0.0100
0.2500
0.1600
0.1400
0.4300
0.1300
0.0200
0.0300
0.3700
0.2300
0.1SOO
0.1300
0.1500
0.4000
0.2300
0.2400
0.3700
0.1700
0.3300
0.2300
0.2400
0.2500
0.2300
0.2100
0.2200
0.6300
0.2700
MINIMUM (UG/H3)
ARITII
MEAN
—
...
1.0500 0
—
...
—
...

...
...
...
...

0.0900A 0
—
—
...

—
...
—
...
—
...
...
...
—
...
...
...
—

...
...
...
...

...
...
—

GEO
MEAN
—
...
.8600
—
...
—
...
—
.—
...
---
...
._-
.0200 A

—
...
...
—

...
...

.—

.-t

...
...
...
...
...
...
...
___
...
...
...
...
	

OBS
0.6900
0.8450
3.4500
4.1500
0.0500
1.6200
1.3100
0.6400
1.5000
0.4900
0.8100
0.5300
1.6200
0.5000
2.4600
0.7700
0.4500
0.6500
2.7400
0.7100
0.2100
3.9000
0.2300
0.1200
2.3300
0.2200
2.4700
0.9200
0.5700
1.4200
0.7200
1.9000
0.4500
0.8200
5.5700
2.2900
0.4900
0.4200
0.6300
0.2700
MAXIMUM (UG/H3I
ARITH
MEAN
—
	
1.1320 0

	 	
—
...
...
...
—
...


0.0900A 0
_-_
...
...

—
...
—
—
...
...
—

—


...

...





...
...


GEO
MEAN
...
	
.9380
—
	 	
—
...
...
—
--.

—

.OSOOA
—


—


—


—


.__
...

	
	
--.
	 .
...
	

...
...
	 .
—
                                                                                                                                      to
A INDICATES ONLY ONE STATION REPORTING

-------
                                    TABLE  C-5.  AIR QUALITY DATA FOR LEAD
HINIHUH (UG/H3)
STATE COUNTY
NILSON
TX BEE
BEXAR
BOHIE
BRAZORIA
BRAZOS
BROCN
CALHOUM
CAMERON
CHAMBERS
DALLAS
OENTON
ECTOR
ELLIS
EL PASO
6ALVESTON
6RAY
GRAYSON
HALE
HARRIS
HAYS
HIDAL60
H01IARO
JEFF DAVIS
JEFFERSON
LUDDOCK
HCLEMIIAM
> HCHULLEH
HATAGORDA
MAVERICK
MIDLAND
HONTGOOERY
MOORE
NACOGOOCHES
NUECES
ORANGE
POTTER
SAN PATRICIO
SCURRY
SMITH
T ARRANT
TAYLOR
OBS
0.2500
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
.0200
.0200
.0200
.0200
.0200
.0200
. 0.0200
o.oo to
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0
0.1000
0.0200
0.0200
0.0200
0.0700
0.0200
0.0200
0.0200
0.0200
0.0200
0.0600
0.0010
0.0200
ARITH
MEAN
—
...
0.4400A
0.4200A
0.1400
0.3700A
...
...
0.0500
...
0.2300
...
0.4400A
~.
0.0900
0.4500A
-._
.__
—
0.1500
~.
0.0300
0.0700
...
0.1300
...
...
...
...
0.4900A
0.1200A
— -
...
...
0.3600
0.1100A
...
...
— _
0.5000A
0.6910A
0.1700A
GEO
MEAN
—
—
0.2800A
0.3300A
0.0900
0.3000A
...
...
0.0300
...
0.1700
...
0.3900A
...
0.0500
0.3800 A
...
...
...
0.0900
...
0.0300
0.0500
...
0.0600
...

...
...
0.3900A
0.0900A

...
...
0.2400
0.0700 A
...
...
...
0.3900 A
0.5340A
0.1300A
MAXIMUM IUG/N3I
ODS
0.2900
0.1300
4.3300
1.9500
0.7400
0.8700
1.8100
0.1300
1.2300
0.2000
8.0200
0.7200
1.0700
1.5000
4.0900
1.2000
0.1200
1.9900
0.1300
3.9100
1.2300
1.2500
0.0200
0.0200
0.9600
1.9600
0.7900
0.3300
0.2100
1.9000
0.6000
0.7000
0.1400
0.5600
17.3000
0.7200
1.4800
0.1100
0.2700
1.4000
3.8000
0.7400
ARITH
MEAN
—
...
0.4400A
0.4200A
0.1900
0.3700A

...
0.1700
...
2.9280
...
0.4400A
...
1.1100
0.4500A
...
...
...
0.8500
...
0.2800
0.0700

0.5200

...
...
...
0.4900A
0.1200A

....
.*.
0.6100
0.1100A

...
-p— •
0.5000A
0.8650A
0.1700A
GEO
MEAN
—
...
0.2800A
0.3300A
0.1200
0.3000A
...
...
0.1000
...
2.6310

0.3900A
...
1.0200
0.3800A
...
...
—
0.6700
...
0.2100
0.0500

0.5000

...
...
...
0.3900A
0.0900A

...
•..»
0.5300
0.0700A

••««•
...
0.3900A
0.8060A
0.1300A
                                                                                                                                      VO
A INDICATES ONLY ONE STATION REPORTING

-------
                                     TABLE  C-5.  AIR QUALITY DATA FOR LEAD
MINIHUH (UG/M3I
STATE









UT






VT

VA




HA


UV

HI






COUNTY
TITUS
TOH GREEN
TRAVIS
VAL VERDE
VICTORIA
HALKER
UEBB
WICHITA
HISE
EMERY
6ARFIELO
KANE
SALT LAKE
SAN JUAN
WASHINGTON
WEBER
CHITTENDEN
ORANGE
0000
FAIRFAX
PAGE
PITTSYLVANIA
HYTHE
KING
• PIERCE
SPOKANE
CABELL
KAHAIIHA
DANE
DOOR
DOUGLAS
EAU CLAIRE
KENOSIIA
MILWAUKEE
RACINE
OBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0010
0.0010
0.0010
0.3500
0.0010
0.0010
0.2300
0.0020
0.0500
0.1300
0.2100
0.0300
0.1800
0.0200
0.0700
0.1600
0.1800
0.2200
0.1200
0.1400
0.0
0.0300
0.1500
0.0800
0.3200
0.1300
ARITH
MEAN
0.1100 A
0.1000A
0.0400
_—
...
...
...
0.4600A
—
—
0.0150
0.0170A
—
0.0110
0.0190
—
0.6860

0.5200
.__
0.2400A
0.5700A
0.0900
1.4600 A
0.9500A
—
...
0.5200
0.6000A
..-
0.2300A

...
...
0.4200A
6EO
MEAN
0.0700A
0.0700A
0.0300
...
...
.-_
...
0.4000A
...
...
0.0070
o.ooaoA

0.0050
0.0070
	
0.4710
...
0.4400
...
0.1900A
0.4800 A
0.0300
1.3100A
0.8200 A
—
	 .
0.4400
0.5200 A
...
0.1900A
...
...
...
0.3500A
MAXIMUM IUS/H3)
DCS
0.5SOO
0.6500
2.6000
0.6000
0.8300
0.3300
0.7100
1.2100
0.6500
0.1600
0.1700
0.0900
4.9100
0.1400
0.2400
3.5500
1.2600
1.1800
3.7500
2.1100
0.8100
1.9300
0.1900
4.4800
2.1900
1.2900
2.2900
2.6900
1.3000
' 0.5500
1.0700
0.9800
1.0300
1.6100
1.4700
ARITH
HE AN
0.1100A
0.1000A
0.7300
-r-

...
.._
0.4600A

...
0.0170
0.0170A
...
0.0200
0.0300
—
0.7900
—
0.9700
...
0.2400A
0.5700 A
0.0900
1.4600A
0.9500A
—
...
0.6240
0.6000A
_._
0.2300A
...
...
...
0.4200A
GEO
MEAN
0.0700A
0.0700A
0.6400
...
...

...
0.4000A
—
...
0.0080
0.0030 A

0.0080
0.0160
—
0.7600
—
0.8600
___
0.1900A
0.4800 A
0.0800
1.3100A
0.8200A

...
0.7200
0.5200A

0.1900A

...
. 	
0.3500A
HY
LARAIIIE
0.1100
                                                                          0.6600
A INDICATES ONLY ONE STATION REPORTING

-------
                                      TABLE   C-S.   AIR  WJAUTV DATA FOR LEAD


                                              MINIMUM (UG/H3I                     MAXIMUM (U6/M3I
                                                  ARITH      6EO                    ARITH       GEO
STATE   COUNTY                          OBS        HEAN      HEAN         DOS        MEAN       IIEAH

         NATROHA                      H.OaOO      —         —          O.V.OO
         PARK                         0.0         —         —          0.0300
                                                                                                                                       \o

-------
                                     TABLE  C-6.  AIR QUALITY DATA FOR MANGANESE
MINIMUM (U6/II3)
STATE
AZ




CO

IN



















HO











COUNTY
APACHE
COCOHIHO
MARICOPA
HOIIAVE
NAVAJO
LA PLATA
HONTEZUHA '
ALLEN
BARTHOLOMEW
CLARK
OUBOIS
ELKIIART
GRANT
HOVIARO
JASPER
JEFFERSON
KHOX
LAKE
LA PORTE
MARION
MONROE
ST. JOSEPH
STEUBEN
TIPPECANOE
VAHDERBURGH
. VI60
UAYHE
AOAIR
AUDRAIN
BOOilE
BUCHANAN
BUTLER
CALLAIIAY
CAIIOEN
CAPE GIRARDEAU
CLAY
COLE
JASPER
JEFFERSON
OBS
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0170
0.0060
0.0230
0.0130
0.0120
0.0150
0.0250
0.0060
0.0070
O.OOSO
0.0060
0.0180
0.0040
0.0090
0.0150
0.0030
0.0130
0.0110
0.0160
0.0190
0.0260
0.0290
0.0210
0.0040
0.0190
0.0190
0.0130
0.0160
0.0300
0.0210
0.0330
0.0 1
-------
                                    TABLE  C-6.  AIR QUALITY DATA FOR MANGANESE
MINIMUM IUG/H3I
STATE











NH
SC
TH


























COUNTY
LIVINGSTON
MARION
NEU MADRID
HODAHAY
PETTIS
PHELPS
PLATTE
ST. CHARLES
STE. GEHEVIEVE
SCOTT
VERNON
RIO ARRIBA
CHARLESTON
ANDERSON
BEDFORD
BLOUNT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUMBERLAND
DYER
GIBSON
GREENE
HAMBLEN
< HENRY
HUMPREYS
LINCOLN
MCIIIIUI
MADISON
MARION
HAURY
MONTGOMERY
OBIOH
POLK
PUTNAM
ROAHE
ROBERTSON
RUTHERFORD
SULLIVAN

0
0

OBS
0310
.0190
.0190
ARITH
MEAN
6EO
MEAN
MAXIMUM IUG/M3)
ARITH
OBS MEAN
6EO
liEAN
0.8280
0.0690
0.2720
.0200
.0310
0.0710
0.0610
.0110 — — (
.0230
.0230
.0610
.0020

0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.0340
.0
.0170
.0320
.0160
.0310
.0100
.0200
.0200
.0030
.0040
.0060
.0060
.0280
.0160
.0060
.0120
.0360
.0190
.0160
.0270
.0310
.0080
.0160
.0370
.0060
.0610
.2500
.0100
.0060
1.0730
.
.
—
0.0960
0.1120
0.0610
0.3640
0.0820
0.0040A
0.0010A 0.0400 0.0040A
0.00 IDA
0.0170
...

...
...
...
...
...
...
...
...
...
...
...
— _
...
...
(
(
(
1
1
I
t
(
.« |
1
(
<
(
(
(
(
1.0420
1.0240
1.0450
1.1290
1.0340
1.0200
1.0330
1.0250
1.1260
1.0300
1.0340
1.0700
1.0260
).6960
1.0360
1.0190
_
-
-
-
_
-
.
_
_
_
_
.
.
_
_
_
—
_
_
_
_
_
_
„
..
_
.
_
_
_
—
—
— _
--
«
..
--
_-
__
..
__
_.
--
--
w_
_«
^—
__
0.0350
0.0290

(
1.0810
^
_
w
6 i 0410
0.1030

1
>.0«fl
_

_^
— — oioifio — —
— 0.9720 — 	
— — 0.0270 — 	
— — 0.0240 	 	
O!l670
                                                                                                                                        vo
A INDICATES OltLY ONE STATION REPORTING

-------
                                     TADLE  06.  AIR QUALITY DATA FOR MANGANESE

STATE COUNTY
SUtUIER
UARREN
UASHIN6TON
UILLIAHSON '
HILSON
TX BEE
BEXAR
BOS1IE
BRAZORIA
BRAZOS
BR013I
CALHOUI
CAMERON
CHAMBERS
DALLAS
DEHTOtt
ECTOR
ELLIS
EL PASO
GALVESTON
GRAY
GRAYSON
HALE
HALE
HAYS
HIDALGO
HOUARO
> JEFF DAVIS
JEFFESON
LUBBOCK
HCLEtlllAN
HCCULLEN
MATAGOROA
HAVERICK
MIDLAND
MONTGOMERY
MOORE
NACOGDOCHES
IAJECES
ORANGE
POTTER
SAN PATRICIO
MINIMUH (U6/H3)
ARITII GEO
DBS MEAN MEAN
0.0180
0.0070
0.4350
0.0370
0.0100
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0
0.0200
.0200
.0200
.0200 -—
. .0200
.0200
.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200

DBS
0.0250
0.0250
0.0350
0.0370
0.0230
0.0900
0.1400
0.1000
0.1600
0.0900
0.0700
0.0900
0.3100
0.1000
0.1900
0.0700
0.3100
O.OSOO
0.2000
0.1300
0.1500
0.0700
O.OSOO
1.1500
0.1100
0.1500
0.0900
0.1400
0.1400
0.1000
O.OSOO
0.0300
0.0200
0.0700
0.3700
0.1000
0.1600
0.0200
2.6600
0.2200-
0.1600
0.0200
MAXIMUM (UG/M3)
ARITH
MEAN
...
—
—
—
—
...

...
...
...
—
—

—
...
...
...
...
...
...
...
...
...
...
—
...
...


...

	
...
	 .
	
...
— -
— .
—
...
...
—

GEO
MEAN
...
...
...
...
—
...


...
...
—

...
...
...
...
—
...
...
...

...

	 .
...
—
—
	 .
...
	
...
. 	
	 .
...
...
	
. 	
. 	
...
...
...
—
                                                                                                                                       00
A INDICATES ONLY ONE STATION REPORTING

-------
TABLE  C-6.  AIR QUALITY DATA FOR MANGANESE
MINIMUM (UO/M3I

STATE COUNTY
SCURRY
SMITH
TARRAMT
TAYLOR
TITUS
TCH 6REEN
TRAVIS
VAL VERDE
VICTORIA
HALKER
HEEB
WICHITA
WISE
UT EHERY
6ARFIELD
KANE
SAN JUAN
WASHINGTON

OBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0
0.0
0.0
0.0
0.0
ARITH
MEAN
...
.--
...
...
...
...
...
...
...
...
...
...
...
...
0.0070
0.0050A
0.0040
0.0070
6EO
MEAN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
0.0020
0.00 IDA
0.0010
0.0030
MAXIMUM IUG/M3)

033
0.0600
0.0900
0.1000
0.0500
0.0700
0.1700
0.1000
0.0200
0.0700
0.0600
0.0600
0.0200
0.0600
0.0400
0.0500
0.0400
0.0300
0.0800
ARITH
MEAN
...
...
...
...
...
.._
...
...
...
___
___
...
—
...
0.0140
0.0050A
0.0100
0.0070
6EO
HE All
...
...
...
...
...
...
— _
...
...
...
...
___
—
...
0.0071
0.0010A
0.0030
0.0030
                                                                                                  NO
                                                                                                  VO

-------
                                     TABLE  C-7.  AIR QUALITY DATA FOR SELEHIUII
MINIMUM (UG/M3I
STATE COUNTY
TX BEE
BEXAR
BOHIE
BRAZORIA
BRAZOS
EROUM
CALHOUH
CAMERON
CHAMBERS
DALLAS
OENTOil
ECTOR
ELLIS
EL PASO
6ALVESTOH
GRAY
6RAYSOII
HALE
HARRIS
HAYS
HIDALGO
HOIIARD
JEFF DAVIS
JEFFERSOH
LUBBOCK
HCLEHHAN
MCHULLEII
• HATAGORDA
HAVERICK
MIOLAHF
MONTGOMERY
MOORE
NACOGOOCHES
MUECES
ORANGE
POTTER
SAII PATRICIO
SCURRY
SHITH
TARRAHT
TAYLOR
TITUS
OBS
0.0100
0.0100
0.1000
0.0100
0.0100
0.0100
0.0100
0.0100
o.otoo
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
o.otoo
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
o.otoo
o.otoo
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
0.0100
ARITH
MEAN

0.0100A
0.0100A
0.0100
0.0100A
— _ •

0.0100
	
0.0100

0.0100A*

0.0100

...

	
0.0100
...
0.0100
0.0100A
--_
0.0100A

_-_
«_
	
0.0100A
0.0 100 A

...

0.0100
0.0100A
.-.
.._

0.0100A
9.0000
0.0100A
0.0 100 A
GEO
MEAN

0.0200 A
0.0200A
0.0200
0.0200 A
.--
_--
0.0200
.—
0.0200
.--
0.0200A
.»
0.0200

—


0.0200
—
0.0200
0.0200 A
_--
0.0200 A
_--

...
.-.
0.0200A
0.0200 A
.--
...
.-_
0.0200
0.0200A
---
-.-_
_._
0.0200A
99.0000
0.2000A
0.0200A
MAXIMUM (UG/M3I
OBS
0.0100
0.0400
0.0300
0.0100
0.0100
0.0300
0.0100
0.0100
0.0300
0.0100
0.0600
0.0100
0.0400
0.0100
0.1300
0.0100
0.0300
0.0100
0.0300
0.0300
0.0100
0.0100
0.0100
o.otoo
0.0100
0.0400
0.0100
0.0100
0.0100
0.0100
0.0100
o.otoo
0.0100
0.0300
0.0100
0.0100
0.0100
0.0100
0.0300
0.0300
0.0100
0.0100
ARITH
MEAN

0.0100A
0.0100A
0.0100
0.0100A
»_
—
0.0100
	
0.0100
	
0.0100A
	
99.0000
--.-
-_-
—

0.0100
	
0.0100
0.0100A
	
0.0100A
—



0.0100A
0.0100A

—
-_-
0.0100
0.0100A

—

0.0100A
99.0000
0.0 100 A
0.0100A
GEO
MEAN
...
0.0200A
0.0200A
0.0200
0.0200 A
---

0.0200
---
0.0200

0.0200A
—
99.0000
—
_.-
—
_—
0.0200
_._
0.0200
0.0200A
__-
0.0200 A




0.0200A
0.0200A
—
—
—
0.0200
0.0200A
___
...
_—
0.0200A
99.0000
0.2000A
0.0200 A
                                                                                                                                        o
                                                                                                                                        o
A INDICATES DULY OHE STATION REPORTING

-------
TABLE  C-7.  AIR WMUTY DATA FOR  SELENIUM





        HIMUUH IU6/HJ)                    MAXIMUM IUG/II3)
STATE

COUNTY
TON 6REEN (
TRAVIS 1
VAL VEROE (
VICTORIA
UALKER
IIEBB
MICHITA
WISE
DBS
1.0100
1.0100
1.0100
.0100
.0100
.0100
.0100
.0100
ARITII
MEAN
0.0100
6EO
MEAN
0.0200
DBS
0.0100
0.0500
0.0100
0.0400
0.0100
0.0100
0.0300
0.0100
ARITH
HE AH
0.0200
6EO
ME AH
0.0200

-------
                                     TABLE  C-8.  AIR QUALITY DATA FOR VANADIUM

STATE
TN































TX









COUNTY
ANDERSON
BEDFORD
BLOUNT
BRADLEY
CAMPBELL
CARTER
COFFEE
CUMBERLAND
DYER
GIBSON
GREENE
HAHBLEH
HENRY
HUMPREYS
LINCOLN
HCMINN
MADISON
MARION
HAURY
MONTGOMERY
OBION
POLK
PUTNAM
ROANE
ROBERTSON
RUTHERFORD
SULLIVAN
• SUI1KER
HAKREN
IIASIIItiGTOH
HILL I AIISOII
UILAON
BEE
BEXAR
BOIIIE
BRAZORIA
BRAZOS
BROUN
CALHOUI
CAMERON
CHAtiOERS
MINIMUM (UG/M3I
ARITH 6EO
OBS MEAN MEAN
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200 — -/--
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
n.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010

OBS
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0200
0.0020
0.0010
0.0010
0.0020
0.0030
0.0040
0.0010
0.0020
0.0010
MAXIMUM (UG/lttl
ARITH GEO
MEAN MEAN
...
...
...



... ...
	 ...
	
... ...
...
___
...

	 ...
	 ...

-__
	

...
	

	 	
... 	
	
_—
	
... ...
... ...
... 	
	 	
... ...
...
... 	
... ...
— . -._
...
...
...
	 	
                                                                                                                                         o
                                                                                                                                         10
A INDICATES 0>1LY ONE STATION REPORTING

-------
TABLE  C-ft.  AIR SUAUITY DATA FOR VANADIUM
HIHINUH IUO/H3)
STATE COUNTY
DALLAS
DEHTOM
ECTOR
ELLIS
EL PASO
6ALVESTOH
GRAY
6RAYSOH
HALE
HARRIS
HAYS
HIDALGO
HOI1ARD
JEFF DAVIS
JEFFERSON
LUCBOCK
MCLENNAN
HHULLEN
HATAGORDA
MAVERICK
HIOLAHO
MONTGOMERY
WORE
NAC06DOCHES
NUECES
03AUGE
POTTER
SAN PATRICK
• SCURRY
SMITH
TARRANT
TAYLOR
TITUS
TON GREENE
TRAVIS
VAL VERDE
VICTORIA
MALKER
HEEB
WICHITA
HISE
OBS
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
ARITH
MEAN
...
...
.--
_..
...
...
...
...
...
...
...
...
_—
...
...
...
...
...

...

_-.
...
...

...
...
...

...
...
...
...
...
...
...
_--
.-.
...
	
—
6EO
HE AN
...
...
...

...
...
...
...
...
...
...
...
...
...
...
...
— _
—
...
...
...

...
	

...
-__
...

...
...
...
...
...
...
...
...
...
...
...
—
MAXIMUM IUS/H3I
OBS
0.0020
.0010
.0010
.0010
.0020'
.0070
.0010
.0020
.0010
.0030
.0010
0.0010
0.0020
0.0010
0.0230
0.0020
0.0020
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0010
0.0020
.0010
.0010
.0010
.0030
.0100
.0010
.0010
0.0010
0.0030
0.0010
0.0010
0.0010
0.0010
0.0010
0.0020
ARITH
HE AN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...

...
___
...
...
...
...
...
...
...
...
...
...
....
...
...
...
GEO
MEAN
...

...
...
...
...
...
...
--_
...
...
...
—
...
...
...

...

...
—
___
...
— _
—
...
_._
...
_—
...
...
...
...
...
...
...
...
...
...
...
...
                                                                                                 o
                                                                                                 LO

-------
                                     TABLE  C-9.  AIR QUALITY  DATA  FOR ZINC

STATE
AZ












10
IN



















SC
TX



COUNTY
APACHE
COCOHIHO
6ILA
GRAIIAII
GREEtlLEE
HARICOPA
MOIIAVE
HAVAJO
PIIIA
FINAL
SANTA CRUZ
YAVAPAI
YUIA
SIIOSHOHE
ALLEH
BARTHOLOMEH
CLARK
OUBOIS
ELKHART
6RANT
HOItARD
JASPER
JEFFERSON
KNOX
LAKE
> LA PORTE
MARIOti
KOtlROE
ST. JOSEPH
STEUBEN
TIPPECANOE
VAUDERBURGH
VI60
MAYHE
CHARLESTON
BEE
BEXAR
BOUIE
MINIMUM (UG/H3)
ARITII 6EO
DBS HEAH HEAH
0.0100
0.0200
0.0100
0.0200
0.0300
0.0001
0.0001
0.0100
0.0001
0.0300
0.1100
a. 0100
0.0200
0.0100
0.0550
0.04SO
0.0924
0.0478
0.0590
0.0772
0.2010
0.0543
0.0215
0.0410
0.0410
0.0634
0.1000
0.0430
0.0645
0.0602
0.0637
0.0520
0.1391
0.0736
0.3500
0.0
0.0 0.0200A 0.0100A
0.0 0.0500 A 0.0300A

DBS
0.2300
0.1500
0.1900
0.0900
0.2300
O.C410
0.1700
0.1400
0.3000
0.2200
0.1100
o.wao
0.1000
ft. 9000
0.1590
0.1140
0.6551
0.2774
O.Q7CO
0.2225
1.4440
0.136S
0.0976
0.0851
0.3990
0.1971
0.4960
0.0960
0.406S
0.2373
0.0995
0.1720
0.4640
0.3921
0.3500
0.0300
0.2100
0.7400
MAXIMUM (U6/M3I
ARITII GEO
MEAN IIEAH

...
—
—
...
... ...
... —
... —
—
...
—

— —
—
	 	 ...
—
_— —
— —
—
... ...
—
... ...
—
— ...
— —
—
...
...
— 	
—
— —

— 	
— —
—
-••• — ...
0.0200 A 0.0100A
Q.0500A 0.0300 A
A INDICATES OtILY ONE STATION REPORTING

-------
                                             HIHItlUH IU6/H3I
                                                                                  MAXIMUM (UG/M3I
STATE COUNTY
BRAZORIA
BRAZOS
BROUN
CALIIQUN
CAMERON
CHAMBERS
DALLAS
DENTON
ECTOR
ELLIS
EL PASO
6ALVESTON
6RAY
6RAYSON
HALE
HARRIS
HAYS
HIDALGO
HOIIARD
JEFF OAVIS
JEFFERSON
LU8BOCK
MCLEMMAN
HCIKJLLEII
HATA6CRDA
MAVERICK
HIDLAltD
MONTGOMERY
MOORE
NACOGOOCHES
NUECES
ORANGE
POTTER
, SAN PATRICIO
SCURRY
SMITH
TARRANT
TAYLOR
TITUS
TON 6REEN
TRAVIS
VAL VERDE 1
VICTORIA
DOS
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0100
.0
.0100
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0200
.0
.0300
.0
.

9.
1.
1.
1.
I.
1.0
1.0
1.0
1.0
1.0
ARITH
MEAN
0.0300
0.0400A
...
...
0.0100
...
0.0200
...
0.0600A
__.
0.0500
o.oaooA
...
...
---
0.0400
...
0.0100
0.0200A
...
0.0400A
...
...
~-
...
0.0500A
0.0400A
... •
...
...
0.0300
0.0400A
...
...
...
0.0400A
...
0.0300
0.0400A
...
0.0100
...
—
6EO
MEAN
0.0200
0.0300A
...
...
0.0100
...
0.0100
...
0.0400A
— _
0.0200
0.0700A
...
...
...
0.0200
...
0.0100
0.0100A
...
0.0200A
...
...
...
...
0.0300A
0.0200A
...
...
...
0.0200
0.0300A


...
0.0300A
...
0.0200
0.0200A
.__
0.0100
-._
—
DBS
0.5500
0.0900
0.4500
0.0600
0.4200
0.7400
0.2400
0.1000
0.1600
0.1400
2.3400
6.7000
0.0500
0.1600
0.0300
Z.OoOO
0.1000
0.2200
0.1700
0.1000
0.4300
0.3100
0.1200
0.1COO
0.0600
0.3600
0.1300
0.1000
0.0900
0.1000
28.6100
0.4700
0.1800
0.0400
0.1200
0.1700
1.5000
0. 1600
0.3SOO
1.1400
1.E300
0.0900
0.0700
ARITH
MEAN
0.0400
0.0400A
...
...
0.0400
...
0.0200
...
0.0600A
...
0.1500
0.0800A
_-.
—
...
0.1300
...
0.0200
0.0200A
_._
0.0400A
...

...
...
0.0500A
0.0400A
._.

...
2.5200
0.0400A
—
—
___
0.0400A
...
0.0300
0.0400A
~_
0.0500
...
—
GEO
MEAN
0.0300
0.0300A
...
—
0.0200

0.0200
...
0.0400A
...
0.0700
0.0700A
...
—
—
0.0800
...
0.0100
0.0 100 A
...
0.0200A
...

___ •

0.0300A
0.0200A

—
-__
1.1500
0.0300A
...
—
__.
0.0300A

0.0200
0.0200A
...
0.0400
...
—
A INDICATES OilLY ONE STATION REPORTING

-------
106

-------
              APPENDIX D




Effects of Deposited Particulate Matter

-------
108

-------
                                  APPENDIX D
                    EFFECTS OF DEPOSITED PARTICULARS MATTER

       Most  evidence  for particulate  toxicity  is  derived  from studies  of
domestic animals.   It is often not  clear  if  the  symptoms  of toxicity are  the
result of  ingestion,  inhalation, or both.   Only  those  studies  which clearly
indicated  ingestion of  dust-covered vegetation  are  summarized  here.   There
appears to be  a  definite relationship between deposition of fine particles of
arsenic, fluoride, lead, and copper  on vegetation; their ingestion by animals;
and chronic  or acute injury to animals.59,60   other metals which may also be
implicated are zinc and cadmium.  The surfaces of vegetation, especially those
covered with fine hairs  (stems,  leaf petioles, and blades),  provide a major
filtration  and  reaction  surface for metal-laden  particles of 1-5  um  and
less.61
       Fluorides  are  reported to cause  more  damage  to  domestic  animals than
any  other  air  pollutant.62    Dietary fluoride  is generally  accepted  as  the
major  source of  fluorosis in  animals.'   Fluorosis  has  been noted  in most
domestic livestock,  presumably resulting  from  particulate fluoride  deposited
on vegetation  and ingested by animals.63,64  por cattle, the most susceptible
domestic  animal,26,65,66  diets  containing concentrations exceeding  40 ppmw
fluoride may have  severe toxic effects.67   The  safe  range  for  soluble  and
insoluble fluorides has  been  specified at 30-50 ppmw and 60-100  ppmw, respec-
tively, for  cattle.68  Sheep and swine (70-100 ppmw), chickens (150-300 ppmw),
and  turkeys  (300-400 ppmw) are  less sensitive to dietary fluoride   levels.68
       Arsenic deposited on vegetation from smelting operations has been known
to  kill livestock  if  enough  was  ingested .62,69-72   ingestion  of arsenic-
contaminated  dust/soil  on forage presents the  greatest  dangers to grazing
animals.73  However, a wide range of toxicity for  arsenic compounds exists and
is correlated  to animal excretion rates.9  The reported biological  half-life
of arsenic compounds  ranges  from 30-60  hours.?4,75   Those compounds excreted
most rapidly tend to be least toxic.
       Lead  poisoning of cattle, horses, and other grazing animals as a result
of  ingestion of  contaminated forage  has been  reported  often.76-80   Fodder
contaminated  by   lead and  zinc by atmospheric  deposition  from  a foundry was
responsible  for  the death and slaughter of 140 cows.8*   Ingestion of surface

-------
                                     110

deposits of airborne  lead  on  forage,  especially adjacent to heavily traveled
highways,82 an
-------
                                     XXX
                                  REFERENCES
 1.   Clean Air Act (42 U.S.C. 1857 et seq.).

 2.   40 CFR 52.21 (o), (p), 45 FR 52675 (Aug. 7,  1980).

 3.   40 CFR 51 and 52, 45 FR 52676 (Aug. 7, 1980).

 4.   Bond, R.G., C.P. Straub, and R. Prober, (eds.) Handbook of Experimental
     Control,  Vol. 1:  Air Pollution, The Chemical Rubber Co.,  Cleveland, Ohio
     (1972) (as cited in Ref. 5).

 5.   Cleland,  J.G., and G.L. Kinsbury, Multimedia Environmental Goals for
     Environmental Assessment, Vols, I and n, U.S. EPA Report  No.  EPA-600/7-
     77-136a,  Research Triangle Park, N.C. (1977).

 6.   Protecting Visibility, An EPA Report to Congress, U.S.  EPA Report No.
     EPA 450/5-79-008, Research Triangle Park, N.C. (Oct. 1979).

 7.   40 CFR 51, Visibility Protection for Federal Class  I Areas,  45 FR 34762
     (May 22,  1980).

 8.   Lewis, B.C., P.C. Chu, R.M. Goldstein, F.C.  Kbrnegay, D.L. Mabes,
     L.F. Soholt, and W.S. Vinikour, A Biologist's Manual for the Evaluation
     of Impacts of Coal-Fir'ed Power Plants on Fish, Wildlife, and Their Habi-
     tats, U.S. Fish and Wildlife Service Publication No. FWS/OBS-78/75, Ann
     Arbor, Mich. (Aug, 1978).

 9.   Dvorak, A.J., B.G. Lewis, et al, Impacts of Coal-Fired Power Plants on
     Fish, Wildlike,  and Their Habitats, U.S. Fish and Wildlife Service Report
     No. FWS/OBS-78/29, Ann Arbor, Mich. (Mar. 1978).

10.   Webster,  C.C., The Effects of Air Pollution on Plants and  Soil, Agri-
     cultural  Research Council, London (1967).

11.   Katy, M., Sulfur Dioxide in the Atmosphre and Its Relation to  Plant
     Life, Indust. and Eng. Chem., 41:2450-2465 (1949).

12.   Dvorak, A.J. et al., The Environmental Effects of Using Coal for Gene-
     rating Electricity, U.S. Nuclear Regulatory Commission Report  No.
     NUREG-0252, Washington, D.C. (June 1977).

13.   Vaughan,  B.E., K.H. Abei, D.A. Cataldo, J.M. Hales, C.E.  Haue, L.A.
     Rancitelli, R.C. Routson, R.E. Wildung, and E.G. Wolf, Review  of
     Potential Impact on Health and Environmental Quality from  Metals Entering
     the Environment as a Result of Coal Utilization, Unnumbered  Batelle
     Energy Program Report, Pacific Northwest Laboratories,  Richland, Wash.
     (Aug. 1975).

14.   White, K.L., A.C. Hill, and J.H. Bennett, Synergistic Inhibition of
     Apparent  Photosynthesis Rate of Alfalfa by Combinations of Sulfur Dioxide
     and Nitrogen Dioxide, Environ. Sci. and Tech. 5:574-576 (1974) (as cited
     in Ref. 15).

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                                     112


15.   Zaragoza,  Larry, U.S. Environmental Protection Agency, personal communi-
     cation of tables attached to Environmental Impact Statement for Montana,
     Ambient Air Quality Standards Study (Aug. 1980).

16.   Ballou, S.W., P.M. Irving, M.H. Gabriel, and K.E. Robeck, Identifying
     the Potential for SO^-Induced Vegetation Damage in the Evaluation
     of Energy Policy Scenarios, Changing Energy Futures, Proceedings of
     the Second International Conference on Energy Use Management, R.A. Fazz-
     olare and C.B. Smith, eds., Pergamon Press, New York (1979).

17.   Materna, J., Criteria for Characterisation of Pollution Damages in
     Forests, Proc. Int. Clean Air Congr. 3rd, Dusseldorf, West Germany (1973)
     (as cited in Ref. 15).

18.   National Research Council, Ozone and Other Photochemical Oxidants,
     National Academy of Sciences, Washington, D.C. (1977).

19.   Heck, W.W., and D.T. Tingey, Nitrogen Dioxide:  Time-Concentration Model
     to Predict Acute foliar Injury, U.S. EPA Report No.  EPA 600/3-79-057,
     Research Triangle Park, N.C. (1979).

20.   Taylor, O.C. et aL, Oxides of Nitrogen,  in J.B. Mudd and T.T. Kozlowski,
     Responses of Plants to Air Pollutants, Academic Press, New York  (1975).

21.   National Research Council, Carbon Monoxide, National Academy of Sciences,
     Washington, D.C. (1977).

22.   Thompson,  C.R., and G. Katz, Effects of Continuous ffgS Fumigation on Crop
     and Forest Plants, Envt. Science and Tech. 12:550-553 (May 1978).

23.   National Air Pollution Control Administration, Air Quality Criteria for
     Hydrocarbons, U.S. Department of Commerce, Springfield, Va.  PB 190-489
     (1970).

24.   Stahl, Q.R., Preliminary Air Pollution Survey of Ethylene, U.S. EPA
     Report No. APTD 69-35, Research Triangle Park, N.C.  (1969) (as sited in
     Ref. 5).

25.   Jacobson,  J.S., and A.C. Hill (eds.),  Recognition of Air Pollution Injury
     to Vegetation:  A Pictorial Atlas, Air Pollution Control Administration,
     Agricultural Committee Informative Report No. 1, TR-70, Pittsburgh, Pa.
     (1970).

26.   National Research Council, Fluorides:   Medical and Biological Effects
     of Environmental Pollutants, Committee on Biological Effects of At-
     mospheric  Pollutants, National Academy of Sciences,  Washington, D.C.
     (1971).

27.   40 CFR 61, National Emission Standards for Hazardous Air Pollutants.

28.   40 CFR 50, National Primary and Secondary Ambient Air Quality Standards
     for Lead,  43 FR 46245 (Oct 5, 1978).

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  •   3£fec*a °f Sulfur Oxides in the Atmosphere on Vegetation:  Revised
     Chapter S for Air Quality Criteria for Sulfur Oxides, U.S. EPA Report
     No. EPA-R3-73-030, Research Triangle Park, N.C. (Sept. 1973).

30.   Bull, J.N., and T.A. Mansfield, Photosynthesis in Leaves Exposed to S02
     and N02, Nature, 250:443-444 (1974) (as cited in Ref. 15).

31.   Jennett, J.H., and A.C. Hill, Acute Inhibition of Apparent Photosynthesis
     by Phytotoxic Air Pollutants, Amer. Chem. Soc. Sympos., 3:115-127 (1974)
     (as cited in Ref. 15).

32.   Costonis, A.C., Injury to Eastern Vhite Pine by Sulfur Dioxide and Ozone
     Alone and in Mixtures, Europ. J. Forest Path, 5:50-55 (1973) (as cited
     in Ref. 15).

33.   Kress, L.W., and J.M. Skelly, The Interaction of 03, S02, and N02 and
     Its Effect on the Growth of Too Forest Tree Species, Cottrell Centennial
     Symposium, Air Pollution and Its Impact on Agriculture, pp. 128-152
     (1977) (as cited in Ref. 15).

34.   National Research Council, Chromium:  Medical and Biological Effects of
     Environmental Pollutants, Committee on Biological Effects of Atmospheric
     Pollutants, National Academy of Sciences, Washington, D.C. (1974).

35.   Desbaunes, P., and D. Ramaciotti, Etude Chimique de I'action sur la
     Vegetation d'un Effluent Gazeux Industrial Dontenant du Chrome Bexavalent,
     Pollut. Atmos. 1(7:224-226 (1968) (as cited in Ref. 34).

36.   National Research Council, Manganese:  Medical and Biological Effects of
     Environmental Pollutants, Committee on Biological Effects of Atmospheric
     Pollutants, National Academy of Sciences, Washington, D.C. (1973).

37.   Hurd-Karrer, A.M., Selenium Absorption by Plants and Their Resulting
     Toxicity to Animals.  Smithsonian Institution Annual Report  1934-35:289
     (as cited in Ref. 9).

38.   Preliminary Investigation of Effects of Boron, Indium, Nickel, Selenium,
     Tin, Vanadium, and Their Compounds, Vol. VI, Vanadium, U.S.  EPA Report
     No. EPA-560/2-75-005f (1975).

39.   Costeque, L.M., and T.C. Hutchinson, The Ecological Consequences of
     Soil Pollution by Metallic Rust from the Sudbury Smelters , Proc.
     Inst. Environ. Sci., 18th Annual Technical Meeting, New York (1972).

40.   Logerwerff, J.V., Heavy-Metal Contamination of Soils, Agr. Qual. Environ.
     pp. 343-364 (1966).

41.   Sillampaa, M., Trace Elements in Soils and Agriculture, United National
     Food and Agricultural Organization Report, Rome (1976).

42.   Budney, Lawrence J., Guidelines for Air Quality Maintenance Planning
     and Analysis Volume 10 (Revised):  Procedures for Evaluating Air
     Quality Impact of New Stationary Sources, U.S. EPA Report No. EPA-
     450/4-77-001, Research Triangle Park, N.C. (Oct. 1977).

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                                      114


43.  General Guidelines Used in Determining "de minimis" Air Quality Impacts
     for the Prevention of Significant Deterioration Regulations, Unnumbered
     U.S. EPA document, Research Triangle Park, N.C. (Aug. 27, 1979).

44.  40 CFR 51 and 52 in 44 FR 51,924 (Sept. 5, 1979).

45.  Monarch, M.R., R.R. Cirillo, B.H. Cho, G.A. Concaildi, A.E. Smith,
     E.P. Levine, and K.L. Brubaker, Priorities for New Source Performance
     Standards under the Clean Air Act Amendments of 1977, U.S. EPA Report
     No. EPA-450/3-78-019, Research Triangle Park, N.C. (April 1978).

46.  Guideline on Air Quality Models, U.S. EPA Report No. EPA-450/2-78-027,
     Office of Air Quality Planning and Standards Guideline No. 1.2-080,
     Research Triangle Park, N.C.  (April 1978).

47.  Depreciation, Guidelines and Rules, Revenue Procedure 62-21, U.S.
     Treasury Department, Internal Revenue Service Publication No. 456,
     Washington, D.C. (Revised Aug. 1964).

48.  Coffin, D.L. and H.E. Stokinger; Biological Effects of Air Pollutants,
     Air Pollution VII, A.C. Stern, ed., Academic Press, New York (1977).

49.  Turner, D.B., Workbook of Atmospheric Dispersion Estimates, U.S.
     EPA Report No. 999-AP-26, Research Triangle Park, N.C. (May 1970).

50.  Ragland, K.W., Worst-Case Ambient Concentrations from Point Sources
     Using the Gaussian Plume Model, Atmos. Env., 10:371-374 (1976).

51.  Busse, A.D., and J.R. Zimmerman, User's Guide for the Climatological
     Dispersion Model, Publication No. EPA-RA-73-024 (NTIS PB 227346), U.S.
     EPA, Research Triangle Park, N.C. (1973).

52.  Briggs, G.A., Chimney Plumes in Neutral and Stable Surroundings, Atmos.
     Env=, 0:507-510 (1972).

53.  Briggs, G.A., Plume Rise Predictions, Lectures on Air Pollution and
     Environmental Impact Analyses, D.A. Haugen, Workshop Coordinator, Ameri-
     can Meteorological Society. Boston, pp. 59-111  (1975).

54.  Larsen, R.I., A Mathematical Model for Relating Air Quality Standards,
     U.S. EPA Report No. AP-89, Research Triangle Park, N.C. (Nov. 1971).

55.  Slade, D.H., Meteorology and Atomic Energy, U.S. Atomic Energy Commis-
     sion, Office of Information Services  (NTIS TID 24190), Oak Ridge,
     Tenn. (1968).

56.  U.S. Department of Commerce, Climatic Atlas of the United States, U.S.
     Government Printing Office, Washington, D.C. (June 1968).

57.  Davis, D.D. and H.D. Gerhold, Selection of Trees for Tolerance of Air
     Pollutants, Better Trees for Metropolitan Landscapes:  Symposium Pro-
     ceedings, USDA Forest Service, General Technical Report No. NE-22 (1976),

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58.  National Research Council, Nitrogen Oxides, National Academy of Sciences,
     Washington, D.C. (1977).

59.  Daesler, H.G.,  Vegetationschaeden ala Falge der Luftwer schutsing, Wiss.
     Z. Tech. Univ., Dresden,  20:1171-1173 (1971).

60.  Manning, W.J.,  Bio-environmental Impact of Fine Paniculate Pollutants:
     A Summary Document and Critical Review, prepared for U.S. EPA, National
     Environmental Research Center, Corvallis, Ore. (Jan. 1975).

61.  Glass, N.R.,  Environmental Effects of Increased Coal Utilisation:
     Ecological Effects of Gaseous Emissions from Coal Combustion, U.S. EPA
     Report No. EPA  600/7-78-108, Washington, D.C. (June 1978).

62.  Li1lie, R.J., Air Pollutants Affecting the Performance of Domestic
     Animals - A Literature Review, USDA Agriculture Handbook No. 380,
     Washington, D.C. (1970).

63.  Phillips, P.H., D.A. Greenwood, C.S. Hobbs, and C.F. Huffman, The
     Fluorosis Problem in Livestock Production, NAS-NCR Publ. 381, National
     Academy of Sciences, Washington, D.C. (1955).

64.  Shupe, J.L., M.L. Miner,  L.E. Harris, and D.A. Greenwood, Relative
     Effects of Feeding Bay Atmospherically Contaminated by Fluoride
     Residue, Normal Say Plus  Calcium Fluoride and Normal Hay Plus Sodium   .
     Fluoride to Dairy Heifers, American Journal of Veterinary Research,
     23:777-797 (1962).

65.  Allaway, W.H.,  Agronomic  Controls over the Environmental Cycling of Trace
     Elements, Advances in Agronomy, 2(7:235-274 (1968).

66.  Suttie, J.W., J.R. Carlson, and C.C. Faltin, Effects of Alternating
     Periods of High- and Lou-Fluoride Ingestion in Dairy Cattle, J. of
     Dairy Science,  55:790-804 (1972).

67.  National Academy of Sciences, Effects of Fluorides in Animals,
     Washington, D.C. (1974).

68.  Phillips, P.H., et al., The Fluorosis Problem in Livestock Production,
     a Report of the Committee on Animal Nutrition, NAS-NRC Publ. No. 824
     (1960) (as cited in Ref.  9).

69.  Formad, R.J., The Effect  of Smelter Fumes upon the Livestock Industry
     in the Northwest, USDA Pathological Division, Bureau of Animal
     Industry Report 25:237-268 (1908).

70.  Swain, R.E., and W.D. Harkins, Papers on Smelter Smoke:  Arsenic in
     Vegetation Exposed to Smelter Smoke, J. American Chemical Society,
     30:915-928 (1908).

71.  Bischoff, 0., Poisioning  of Domestic Animals through Copper and Arsenic
     Containing Fly  Dust, Dent. Tierarztl. Wochschr-, 47:442-447 (1939).

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                                     116
72.  Phillips, P.H., The Effects of Air Pollutants on Farm Animals, Air
     Pollution Handbook, Maple Press, New York (1957).

73.  Berry, W.L., and A. Wallace, Trace Elements in the Environment:  Their
     Role and Potential Toxicity as Related to Fossil Fuels - A Preliminary
     Study, Univ. of California, Laboratory of Nuclear Medicine and Radiation
     Biology (1974).

74.  Frost, D.V., Arsenioals in Biology - Retrospect and Prospect, Federal
     Proceedings, 20:194-208 (1967).

75.  Sullivan, R.J., Air Pollution Aspects of Arsenic and Its Compounds,
     Litton Systems, Inc., Bethesda, Md.  (1969).

76.  Allcroft, R., Lead as a nutritional Hazard to Farm Livestock IV,
     Distribution of Lead in the Tissues of Bovines after Ingestion of
     Various Lead Compounds, J. Comp. Pathol. Exp. Ther., 0(7:190 (1950).

77.  Allcroft, F., Lead Poisoning in Cattle and Sheep, Vet. Rec., 05:583-590
     (1951).

78.  California Air Resources Board, A Joint Study of Pb Contamination
     Relative to Horse Deaths in the Area of Southern Solano County (Dec.
     1971) (as cited in Ref. 9).

79.  Hammond, P.B., and A.L. Aronson, Lead Poisoning in Cattle and Horses
     in the Vicinity of a Smelter, Annals of New York Academy of Science,
     111:595-611 (1964).

80.  Schmitt, N., G. Brown, E.L. Devlin,  A.A. Larsen, E.D.  McCausland, and
     J.M. Saville, Lead Poisoning in Horses, an Environmental Health Hazard,
     Archives of Environmental Health, 23:185-195 (1971).

81.  Vetter, H., Loads and Damage by Heavy Metals in the Vicinity of a Lead
     and Zinc Foundry in Lower Saxony, Staub Reinhaltung der Luft (English
     ed.), 34:11-12 (1974).

82.  Lagerweiff, J.V., Lead, Mercury and Cadmium as 'Environmental Contami-
     nants, Nicronutrients in Agriculture, J.J. Montvedt, P.M. Giordano,
     and W.L. Lindsay, eds., Agriculture Soil Science Society of America,
     Madison, Wise. (1972).

83.  Lisk, D.J., Trace Elements in Soils, Plants, and Animals, Advances in
     Agronomy, 24:267-325 (1972).

84.  Zimdahl, R.L., and J.H. Arvik, Lead in Soils and Plants:  A Literature
     Review, CRC Critical Reviews of Environmental Control, 3:213-224
     (1973).

85.  Bazell, R.J., Lead Poisoning:  Zoo Animals May be the First Victims,
     Science, 273(3992):130-131 (1971).

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86.  Scientific and Technical Assessment Report an Vanadium,  U.S.  EPA Report
     No. EPA-600/6-77-002, Research Triangle Park, N.C.  (1977).

87.  Ter Heege, J.H., Poisoning of Cattle by Ingestion of Fuel Oil Soot,
     Tijdschr. Diergeneesk, 55:1300-1304 (1964).

88.  Henneman, j., Frequent Occurrence of Stomach and Intestinal Diseases
     in Cattle Caused by Iron-Containing Flue Gases, wien. Tieraerztl.
     Monatsschr., 25:225-231 (1931).

89.  Shupe, J.L. , Levels of Toxiaity to Animals Provide Sound Basis for
     Fluoride Standards, Environmental Science and Technology, 3:721-726
     (1969).

90.  Newman, J.R., Effects of Industrial Air Pollution on Wildlife,
     Biological Conservation, 25:181-190 (1979).

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                            /»      TECHNICAL REPORT DATA
                            (Please read Instructions on the reverse before completing)
 EPA*450/1-81-078
                             2.
                                                           3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
A Screening Procedure for  the Impacts of A1r
Pollution  Sources on Plants,  Soils, and Animals
                                                                   'ATE
                                                           6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)	

 A.  E.  Smith and J. B. Levenson
                                                           B. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS

 Argonne National Laboratory
 9700 South Cass Avenue
 Argonne, IL  60439
                                                           10. PROGRAM ELEMENT NO.
                                                           11. CONTRACT/GRANT NO.

                                                           EPA-I6A-79-D-X0764
12. SPONSORING AGENCY NAME AND ADDRESS  . _   .   .
 Office of A1r Quality Planning and Standards
 U.S.  Environmental Protection Agency
 Research Triangle Park,  NC   27711
                                                                       JRT AND PERIOD COVERED
                                                           14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
        Section 165 of  the Clean A1r Act requires  preconstructlon review of major
   emitting facilities  to provide for the prevention  of significant deterioration (PSD)
   and charges Federal  Land Managers (FLMs) with an affirmative responsibility  to
   protect the air quality-related values of Class I  areas.  Regulations implementing
   these provisions require an analysis of the  impairment to visibility, soils, and
   vegetation (52.21(o)).

        The information and screening procedure presented here provide interim
   guidance:  (1) to  aid in determining whether emissions are significant  or
   whether there are  significant air quality Impacts  under Section 52.21(o),  and
   (2) to aid in flagging sources which should  be  brought to the attention of
   an FLM under Section 52.21(p).

        Impacts on vegetation and soils are the principal areas addressed  by  the
   procedure which thus takes a limited view of the possibly broad scope of air
   quality-related values.  A selected review of  impacts on fauna has also been
   included and the odor potential of regulated pollutants is addressed.   This
   procedure is Intended for use by air quality engineers and is not a manual for the
              nf Imacts on  lants, soils, and  other  air quality-related values such
17. as would be suitable  for an
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                  DESCRIPTORS
                                              b.lDENTIFIERS/OPEN ENDED TERMS
                                                                         c. COSATI Field/Group
                                                                                6F
18. DISTRIBUTION STATEMENT

   Release Unlimited
                                              19. SECURITY CLASS (This Report)
                                                    None
21. NO. OF PAGES
  117
                                              20. SECURITY CLASS (Thispage)
                                                                         22. PRICE
ERA Form 2220-1 (Rev. 4-77)   PREV.OUS ED.T.ON ,.
                                     OBSOLETE

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