VOLUME IJI
03/73-09-28
03/73-10-30
03/73-11-01
03/73-1 1-30
03/74-Ol-OOA




03/74-01-008


03/74-01-35



03/74-02-00A



03/74-Q2-QOB



03/74-02-35




03/74-03-00
OPPORTUNITY FOR PUBLIC COMMENT ON SIB PLAN REVISIONS  AND
  SUBMITTALS.  CPDD.  9/28/73,  PR DRAFT NOTICE*

GUIDELINES FOR INTERPRETATION OF AIR QUALITY STANDARDS
  (DRAFT) t  MDAD.   10/30/73.  OAQPS NO.  1 .2-008*   •<*<•-•« ----
EPA NEDS PROCEDURES - RESPONSIBILITIES AND PROCEDURES  FOR
  INTERNAL SEMIANNUAL REPORTS ACTIVITIES - REQUIRED  NEDS
  UPDATE PROCEDURES,  MDADt  11/1/73.  OAQPS NO*  l*2-
GUIDELINES FOR DETERMINING THE NEED FOR PLAN REVISIONS  TO
  THE CONTROL STRATEGY PORTION OF THE APPROVED STATE
  IMPLEMENTATION PLAN (DRAFT).  CPDD,  11/30/73.
  OAQPS NO. 1,2-011,                  <2ec,* .'•<-,,-..•    ..•  ,  /
                        .                           . ..    .
PROCEDURES FOR SCREENING,  VALIDATING  AND  REPORTING AIR  ^
  QUALITY DA'TA (DRAFT).   MDAD,   1/74,   OAQPS  NO*  1.2-013
  (SUPERSESSION OF OAQPS  1.2-Q06).                — -  -

GUIDANCE FOR  AIR  QUALITY  MONITORING  NETWORK  DESIGN AND  . ..   .
  INSTRUMENT  SITING.  MDAD.  .1/74.   OAQPS  NO.  1.2-012.

GUIDELINES FOR DESIGNATION  OF  AlR  QUALITY  MAINTENANCE AREAS.
  CPDD.  1/11/74,  OAQPS NO, j. 2-016.

GUIDELINES FOR THE EVALUATION  OF. AIR  QUALITY  TRENDS.   MDAD.
  2/74,  OAQPS NO. 1.2-014.

GUIDELINES FOR THE EVALUATION  OF .AIR  QUALITY  DATA.  MDAD.
  2/74.  OAyPS NO. 1.2-015.

DESIGNATION OF CRITERIA POLLUTANT ANALYTICAL  METHODS  AS
  ACCEPTABLE/NOT  ACCEPTABLE FOR PURPOSES OF DATA  ANALYSIS
  (DRAFT).  .MDAD.  2/8/74.  OAQPS NO. 1.2-018.

A  DESCRIPTION OF  THE ANALYTICAL TECHNIQUES AND  A5SOC I ATED
  SAROAD METHOD CODES USED  IN  STORING DATA IN THE  NATIONAL
  AEROMETRIC DATA BANK.  HDAD,  3/74.  OAQPS  NQ«  1*2-017.
                                                               <-•
                                                                     I t~

-------
                           ENVIRONMENTAL PROTECTION AGEIC
Reply to
 Anno/:  OAQPS, CPSS, SIB                                            Dale.-September 28,

 Subject:  Opportunity for Public Comment on SIB Plan Revisions and  Submittals

     TO:  Director,  Division of Air and Water Programs,  Regions  I - X
         Principal  Air Contacts, Regions I - X
                «
              Guidelines concerning the preparation of  Federal  Register notices
         for "Opportunity for Public Comment" were forwarded  to you under cover
         memorandum dated August 21, 1973.  We have received  numerous comments
         from the  Regional  Offices, OAWP,  and OEGC.  To the extent possible,
         we have addressed  these comments  in the  enclosed  revised guidelines.
         The major  changes  are as follows:

              1.   The notice will  appear  as a "Notice  of  Proposed Rulemaking"
              and  be signed by the Administrator.   Since it involves proposed
              rulemaking, the notice must  contain  a detailed  sjrrcnary of the issues
              in the state  plan submission (example attached) in order to reason-
              ably  assure that interested  parties  would be alerted.

              2.   It is estimated that ten to fifteen  working days will be
              required to process the Federal  Register  notice after it has
              been  received by OAWP from the Regional Office.

              The revised guidelines are to be implemented in future plan sub-
         mittals.   Also, see the attached  memorandum (attachment 3) from
         William Frick to myself which discusses  preparation  of the above
         mentioned  Federal  Register notices.   Any  comments concerning these guide-
         lines should bs addressed  to Ted  Creekmore or  Joe Sableski (919-688-8437)
         by October 12,  1973.
                                                                       ^v
                                             Morman G.  Edmisten, Chief
                                          Standards Implementation Branch
                                                 Control  Programs
                                               Development  Division
         Enclosure

         cc:  B. J. Steigerwald
             J. J. Schueneman
             D. K. Berry
             I. Auerbach
             R. Baum
             B. Frick
             R. Wilson

-------
               GUIDELINE FCR PU2LIC Cr;:::~iiT PRIC* TO  EPA
              APPROVAL OF STATE INPLEf'.ENTATION PLAN ACTIONS
Background
     The Environmental Protection Agency has been criticized for not
providing an opportunity for public convnent prior to  approval/disapproval
actions on state implementation plans and plan revisions.  This criticism
has been a major issue in three recent court decisions:
     1.   Appalachian Power Company, et al, vs. EPA,  477 F 2nd 495,
          (4th dr., 1973).
     2.   Duguesne Light Co.. et al. vs. EPA. 5 ERC 1473 (3rd Cir.,
          1973).
     3.   Buckeye Power Inc., et al. vs. EPA, Case Nfos. 72-1628, 1629.
          1632- (6th dr., June 28, 1973).
The Plaintiff in each case complained that EPA did net provide an opportunity
for review and comments of implementation plans as officially submitted by
the States in compliance with section 110 of the Clean Air Act, as amended
1n 1970.  They contend that implementation plans have been measurably
modified following the states' public hearings and EPA has acted on these
plans without opportunity of public review and comment on such modifications.
In response to the court decisions, EPA will provide  an opportunity for
public review and comment on plan submissions, revisions and supplements
Involving regulatory actions and other matters of suL-stantivc signific-:.nce
to the plan.  This opportunity fcr public review and  comment shall be extended
through publication in the Federal Register of pertinent information.  These
Federal Register notices will appear as proposed rule:naking. The attached
memorandum (attachment 3) from William Frick to Norm Edmisten discusses the
preparation of the proposed ru.lemaking Federal Register and gives the
rational behind the requirement that the package bo in the form of proposed
rulemaking.

-------
                                    2
Nptj fi cati en P.';gui roir;ents
     A Federal Rem'ster notice soliciting public ccrr/.-ents on proposed
plan  revisions rust be prepared for all  plan revisions and submittals
Involving regulatory actions and/or regulatory associated actions  such  as
compliance schedules, variance actions,  changes in attainment dates,
transportation controls and land use plans,  etc.  The Regional  Offices
should also consider public notices for other submittals and revisions
that  substantially impact on the attainment and maintenance of the
national ambient air quality standards,  such as emergency episode  proce-
dures, substantial changes in air quality moritoring, or other matters
which are likely to be controversial.  Substantive public consent  might
be received in such instances that would Influence EPA's approval/disapproval
decisions.

Procedures
     The procedure for processing plan revisions and supplements will remain
as described in the Guidelines Series OAQPS 1.2-005A, June 1, 1973,  except for
an additional action providing for public notification of plan availability
for review and coranent.  This additional notice is required effective
immediately.

P re 1 in'nary Plan Rev lev/
     Immediately after receipt of plans from a State, the Regional Office  shall
review such information and determine if the revision is acceptable for furthe
consideration.  If the plan contains obvious deficiencies, the Regional Office
will  attempt to negotiate with the State to correct these deficiencies.

-------
                                    3
Propnration of Fc:dcrn 1 Roqisjtcr_ Nqtjcc.:,
     Once the deficiencies have been corrected, or if no deficiencies are
noted, the. Regional Office shall be responsible for preparing, for the
Administrator's  signature, a Federal Register package  which announces
receipt'of the plan, gives notice of proposed ru1e,;i3king, provides for a
30-day public comment period,  identifies places where tiie plan can be
examined, and stipulates to whom comments should be addressed.  The Federal
Register package shall also include an action memorandum and the notice of
proposed rulemaking.  The notice will appear in the proposed rulemaking
section of the Federal Register (40 CFR 52).
     Because the notice is setting forth proposed rulemaking, it should con-
tain more information than would be contained if it were simply a notice of
opportunity to comment.  While  it is not necessary that the subniittal be
printed verbatim in the Federal Register, the notice should adequately
describe the content of the proposed revision so that interested parties can
determine the scope and impact  of the proposal, then if further detail is
desired, the plan  can be reviewed at the identified locations.  The content
will obviously vary greatly depending on the type of action that is being
proposed.  If the  action includes significant changes, the notice should identify
the purpose of the revision, the increase or decrease in emissions or ambient
concentrations that will be effected by the change, the regulations which
are being changed, and the impact on attainment of national standards.  Every
effort should be made to present this summary in clear, simple language which
can be easily understood.
     Since it is rulemaking, the notice should clearly indicate that fact.
Although there is  no essential  language which must ba used in the last line
of the heading which describes  the action cQiitnincd in the publication, it'
would be appropriate that the  heading state that it is a notice of proposed

-------
                                    4
rule-nakinn and then describe the nature of tho proposal, e.g., "Notice of
Proposed Ruleiuaking:  Proposed Revision to Arize-.-.;. Implementation Plan";
or "notice of Proposed Rulemaking:  Proposed Compliance Schedule for Certain
Sources in Alabama."
     Th"e Federal Register notice shall follow the general format describing
pertinent plan information similar to the attached example (Attachment 1).
Note the detailed description of the proposed plan, and the discussion of
the projected impact the proposed plan will have on the State implementation
plan.
     The Regional Office  shall  forward  the  notice  of  action
memorandum from  the Regional Administrator to the Administrator through CAMP
'Attention:  Ms. Cathy Thompson, Waterside Mall, Room 943-West Tower, 4th and il
Streets, S.W., Washington, D.C  . 20460).  The package shall include the original
Federal Register notice (double spaced with pages numbered at the bottom) and
ten copies.  Two of the copies shall contain the statement "Certified to be a
true copy of the original" typed at the bottom of the last page.  This is
necessary because the Administrator will sign three notices, the original and
two copies.

     Additional  copies of the Federal Register package shall be forwarded to:
     1.   Mr. Jean J. Schueneman, Director, Control Programs Development
     Division, Research Triangle Park, N. C. 27711 for inclusion in the
     official SIP files.
     2.   Ms. Rubye Mullins, Information Officer, Office of Public Affairs,
     EPA, Waterside Mall, Room 329C-Wost Tower, 4th and M Streets, S.W.,
     Washington, D. C. 20460 for public availability a^ headquarters.

-------
                                    5
     3.   Mr. Richard Wilson, Director, Division of Stationary Source
     Enforcement, Waterside Mall, 1125C-l!cst Tov/or, 4th and M Streets,  S.W.,
     Washington, D. C.  20460.
     4.   Cognizant State and local  air pollution control  agencies (State
       *
     and local agencies should not get copies of the action memorandum).

     Since these actions do not involve wide EPA interest and consideration,  it
is expected that they will appear in the Federal Register in 10 to 15 working
days after receipt by Ms. Thompson.   Ms. Thompson will  monitor progress of
Federal Register actions.  If you have any questions on the status of a
particular package, please call her at (202) 755-0472.
     In summary, the following information should be included in the Federal
Register notice:
     1.   An identification of the plan under consideration.
     2.   A detailed summary of the action or important aspects of the  plan.
     Describe any court orders requiring the revisions.
     3.   Identify places where the plan can be examined and periods of avail-
     ability for review.  As a minimum, this will include the offices of cogni-
     zant state and local air pollution control agencies, including State
     district offices; the EPA Regional Office, and the Freedom of Information
     Office in Washington, D. C.
     4.   Identify to whom comments shall  be submitted.

Public Advertisement
     The Regional Office will also arrange for a legal  notice to be published
in newspapers of general circulation throughout the area affected by the
proposed plan, which will contain a. summary of the information included in the

-------
                                    6

Federal Register notice.  This shall be published as soon as possible after

the Feclcraj^ Register notice has been published.  Care must be exercised in

preparing the legal notice to assure consistency with the Federal Register

with regard to period of comments, plan content, etc.
       *
Handling Public Coiirii'ents

     Receipt of any comments shall be promptly acknowledged (for an example,

see Attachment 2).  A copy of all comments and acknowledgments will be for-

warded to Ms. Rubye Mull ins, Mr. Jean Schueneman, and Mr. Richard Wilson at

the addresses given above.  The Regional Office will take substantive

comments into proper consideration as they impact on approval/disapproval

and proposal actions.   In preparing subsequent Federal Register packages,

these public comments must be addressed in the preamble to the regulations

on Federal Register notices and EPA's responsiveness noted.

-------
                              Attachir.r.-nt 1
                     ENVIRONMENTAL iro'iicnc;; ;,GLr;;cY
                            (40 CFR h.rt 52)
   APPROVAL AND PROMULGATION OF STATE IMPLEMENTATION PLANS - MARYLAND
       Notice of Proposed Run-making:  Proposed Plan to Achieve
                    Secondary Standards for Maryland
     On May 31, 1972 (37 F.R. 10342), pursuant to section 110 of the Clean
Air Act and 40 CFR Part 51, the Administrator granted an 18-month extension
for submission of a plan to attain and maintain the secondary standard for
sulfur oxides in the Metropolitan Baltimore Intrastate Region.   On July 31,
1973, the Governor of Maryland submitted the plan as required.
     The Administrator hereby issues this notice setting forth the Maryland
Plan for Implementation of the Secondary Standards for sulfur oxides in the Metro-
politan Baltimore Intrastate Region as proposed rulemaking, and advises the public
that comments may be submitted on whether the control strategy should ba
approved or disapproved as required by section 110 of the Clean Air Act.
Only comments received within 30 days from the publication of this notice
will be considered.  The Administrator's decision to approve or disapprove
the plan is based on whether it meets the requirements of section 110(a)(2)
(A)-(H) and EPA regulations in 40 CFR Part 51.
     The proposed plan does not alter or supplement the present Maryland
regulations for sulfur dioxide.  Rather, the plan is submitted to demonstrate
that implementation and enforcement of existing Maryland regulations in the
Metropolitan Baltimore Intrastate Region will be sufficient to achieve the
secondary standards for sulfur dioxide by 1975.  The control strategy developed
by Maryland in the original plan  (submitted January 28, 1972, hereafter referred
to as the original plan) to meet the secondary standards for sulfur oxides was
not approved because calculations in the plan regarding projected air quality

-------
for 197G indicated  that  the;  stccndjjy  standard.; ci.uld not bo met using
reasonably  available  technology. .  Thus,  an  IC-iront.h extension VMS grf.ntcc!.
     The Maryland proposal states  that certain cievsacprrsnts have token place
since the original  irplerr.entation  plan v.-cis  submit to;!', which elter projcctr/d
sulfur'oxide  air quality significantly.   These devc?T:pir.ents are given by
Maryland as follows:
     1.   A new data  base has  been formulated for  afr quality due to
     changes  in measurement  and  data reduction techniques.
     2.   More detailed  information has  been obtained on actual emission rates
     and dynamic effluent characteristics.
     3.   Considerable change  in fuel  burning sources and control plans are
     to be  expected due  to negotiations  with emitters that had not previously
     been dealt  with.
     4.   Improved  capability  in the computer used in the analysis.
     The results of this model effort  predict a maximum concentration of 35 ug/rn
annual average for  the Metropolitan Baltimore Intrestate Region.  Total
emissions of  sulfur oxides will  be reduced  from 180,250 tons/year for tht base
year of 1971  to 90,996 tons/year by 1975.
     Copies of the  Maryland  plan are available for public inspection during
normal business hours at the Office of EPA, Region III, Curtis Building,
Second Floor, 6th and Walnut Streets,  Philadelphia, Pennsylvania 19106, and in
the Office  of the Maryland State Department of Health and Mental Hygiene, CO!
N. Howard Street, Baltimore, Maryland  21201, and at "he Freedom  of Infcr.raticn
Center, EPA,  401 M  Street, S.W.  Washington, D.C.   20,'GO.

-------
                                     3
     Interested  persc^s  ruy  p^rU'dp''''0  in  this  rulf.r';!;inn  by  su!;rrl •'I inij  ',.T! !.;.•..• i:
con;:e:r,ts,  preferably  in  triplicate,  to the  Regional  Administrator,  Environ." vi.'i'ol
Protection Acency,  Region  III,  Curtis  Building,  Gth  and  K'alnut Streets, Phila-
delphia, Pennsylvania 1910C.  Relevant cerricnts  received within 30  day:, cf tin':.
notice will  te considered.   Receipt  of comments  will  be  ackncwl edged but  si^stsn-
tive responses to individual  consents  will  not be  provided.  Comments  received
will be  available during normal working  hours at the Region III office.   All
relevant iratter  presented shall be evaluated and the Agency will  inccrporate
in the rules adopted  a concise  general,  statement  of their  basis  and purpose.
Authority:   Section 110(a)  of the Clean  Air Act, as  amended, 42 U.S.C.  1857c-5(a)
Date
                                     Russell  Train,  Administrator
                                     Environmental Protection  Agency
          "Certified  to  be  a  true  cqpy  of  the  original"
        (THIS APPEARS-OM TWO  COPIES  OF  THE ORIGINAL  DOCUMENT)

-------
r ; •••  '••--  •!.•:• .--:i-.t
W ! . .-   . i .•«..  i i . •. . . ...  . .. ....<
/' ':   \.--f-r-
 a^r  Sir:
       Thin  i^  to  i. '.vri<.. •.'!>•. 'n;. 2  rcc-'irt
cor.t:.":i"i'ino. c.::.'r--:-r,i~  on  v.i'.rj |'/vcpo.;:d  :
dioxide;.   V'j  i-.r-c In  tiii  i;:--oc:Ch£  ;/f r;
the ::
                                                 ycur  1 ::-t •!>'::• of  onV-/ ;•:'":,
                                               ~;i::iops  co:-:. ••rr.ino •"•':'- -or; -en
                                               :::ii:b'i'ii:Cj  i,\]  t:w.  ccr' :::::•, •;;:.:
                                                \;!:e n-^cc^snry ch:.i'-^'i> for
       Ws  slnccraly r,;3pri:--:ric.tc your prfi/irL  af-tcMtlon in  st/!::i;\tt'!ny
                                              Sincerely VOLTS, •
                                               rrmari &.  EcV./i stan ^ Clv'-.vr
cc:    Rubye H'.jlVins
       Oe.ui 0.  ici.!:cii«nrin

-------
l
-------
EPA's reviov; can be  made  in  a  short lino,  the  Region  is
precluded  from  proposing  its detcrminat:ion  to ni'pi'ovo.
The Rccjjon  r.!iou.ld  do v;lMtcvcr  i;; nore  <::;.•>; is I:; lc;it  v/j. {.h
the time fr;.'.:.;C3 established  by k'110.

     Since  it is rulcnaking, the notice  should clearly  in-
dicate  that fact.  For  this  reason, we recoir.r^.end  that the
example used in the  transportation control  plans  not be
used here.  Although there is  no essential  language  which
must be used in the  last  line  of the heading  v.'hich  describes
the action  contained in the  publication,  we believe  it
would be appropriate that the  heading  state that  it  is
a notice of proposed rulemakirig and then describe the nature
of the  proposal, e.g.,  "Notice of Proposed  Rulenaking;  Pro-
posed Revision'to  Airzona Implementation Plan"; or  "Notice
of Proposed Rulemaking; Proposed Compliance Schedules for
Certain Sources in Alabama".

     Because the notice is setting forth proposed rulemaking
it should  contain  more  information than  would be  contained
if it were  simply  a  notice of  opportunity to  comment.   While
it is not  necessary  that  the submittal be printed verbatim
in the  Federal  Register,  the notice should  adequately de-
scribe  the  content of the proposed revision so that  in-
terested parties can determine the scope and  impact  of
the proposal, then if further  detail is  desired,  the plan
can be  renewed  at  the identified locations.   The  content
will obviously  vary  greatly  depending  on the  type of action
that is being proposed.   If  the action is substantial,  the
notice  should identify  the purpose for the  revision, the
increase or decrease in emissions or ambient  concentrations
that will be effected by  the change, the regulations which
are being  changed, and  the impact on attainment of  national
standards.  These, of course,  are only examples and  it  must
be left up  to the  judgment of  the Regional  office to deter-
mine the detail which will be  sufficient to properly make
all interested  parties  aware of the action  that is being
taken.

     The Regions may wish to avoid giving the impression that
the proposal lias been reviewed by EPA  and that all  parts are
believed to be  approvi\ble by stating that the proposal  is
the States  submittal and  EPA is soliciting  comments  on  what
EPA's action  should be.

     A  final important  comment is that the  Federal  Register
package should  be  prepared for signature by the 7id:ninistiv.tor
rather  than the /issistant Administrator  for Air and  Water Pro-
grams.  Section 301  of  the Clean Air Act precludes  the  Ad--

-------
ministrator from delegating his authority to make .regulation::.
Since we are considering tie approval, of implementation
plans to be rul er.a): j M'J , this precludes the signinn of the
notice of proposed rulci:.aking by the Assistant 'ixi.v.inistrato::.
We are taking steps to minimize the internal reviev.' at
headquarters that would normally accompany substantive
rulemaking signed by  the Administrator.  In this type of
rulemaking the proposal does not include any substantive
EPA action.  Of course, if the region does propose what is in
fact EPA's determination, the proposal would have to folio1.-:
nor rial channels.  We  caution against reliance on the pro-
posals which were made in connection with transportation
controls.  Those proposals were made because the District
of Columbia Circuit Court of Appeals required that EPA take
comment on the transportation control strategies although
it did not say why this was required.  Because of the two
month deadline required by the Court order, the 21-day period
was established, with the concurrence of NRDC, as being
necessary to meeting  the Court deadline.  It was not in-
tended to supplant permanently the normal 30 day period.
Furthermore, at the time that those notices were prepared,
no Court had yet made the determination that the approval
of implementation plans was rulemaking and the notices were,
although published in the proposed rulemaking section,
drafted more like a notice of opportunity for comment in order
not to prejudice our  position in the other cases, which was
that this was not rulemaking.  The short description and
the preparation for signature by the Assistant Administrator
was also a function of a short time period involved.  Ac-
cordingly, these should not be used as an example of the
notices that are to be prepared from now on.

-------
GUIDELINE  SERIES
          OAQPS NO. 1-2008
               DRAFT
       GUIDELINES FOR INTERPRETATION
         OF AIR QUALITY STANDARDS
   US. ENVIRONMENTAL PROTECTION AGENCY
     Office of Air Quality Planning and Standards

      Research Triangle Park, North Carolina

-------
                  DRAFT

        GUIDELINES FOR INTERPRETATION

                     OF

            AIR QUALITY STANDARDS
    Monitoring and Data Analysis Division
Office of Air Quality Planning and Standards
       Environmental Protection Agency
              October 30, 1973                               <£

-------
                             INTRODUCTION

     This guideline document discusses a series of issues concerning
the interpretation of air quality data as it relates to the National
Ambient Air Quality Standards (NAAQS).  The issues presented deal
with points of interpretation that have frequently resulted in
requests for further clarification.  This document states each
issue with a recommendation and a discussion indicating our current
position.  It is hoped that this document will serve as a useful
step in the evolutionary development of a uniform and consistent
set of criteria for relating ambient air quality data to the NAAQS.

-------
     ISSUE 1:  GIVEN THAT THERE ARE A NUMBER OF MONITORING SITES
              "WITHIN AN AIR QUALITY CONTROL REGION (AQCR),  DOES
               EACH OF THESE SITES HAVE TO MEET THE NATIONAL AMBIENT
               AIR QUALITY STANDARDS (NAAQS)?  IN PARTICULAR, IF
               ONLY ONE OF THESE SITES EXCEEDS A STANDARD, DOES THAT
               MEAN THAT THE ENTIRE AQCR HAS VIOLATED THE STANDARD
               EVEN THOUGH ALL OTHER SITES MEET THE STANDARD?
RECOMMENDATION:  Each monitoring site within the AQCR must meet the
                 standard or the region is in violation of that
                 standard.
DISCUSSION:
The NAAQS's were defined to protect human health and
welfare.  The presence of one monitoring site within
an AQCR violating any given standard indicates that
receptors are being exposed to possibly harmful
pollutant concentrations.
Concentrations in excess of standard values at a
single monitoring station may result from the effect
of a small, nearby source which is insignificant
in terms of the total emission inventory, or the
station in violation may be so located that the
probability that individuals would be exposed for
prolonged periods is negligible.  Such circumstances
do not mitigate the. recommended interpretation of
the question raised by this issue since NAAQS are
generally interpreted as being set to protect health
and welfare regardless of the population density.
Although air quality improvement should be stressed
in areas of maximum concentrations and areas of highest
population exposure, the goal of ultimately achieving
standards should apply to all locales.  Data from
monitoring sites are the only available measure of
air quality and must be accepted at face value.
Attention is thus focused on the selection of
monitoring sites in terms of .the representativeness
of the air they sample.  The forthcoming guideline
document concerning the location of monitoring

-------
instruments should be consulted in evaluating
sites now in use.  Consideration should be given
to the relocation of monitoring stations if the
guideline criteria are not met.

-------
     ISSUE 2:  HOW SHOULD MEASURED AMBIENT AIR QUALITY LEVELS BE
               REPORTED FOR COMPARISON WITH THE NAAQS?  IS THE LEVEL
              .SPECIFIED BY THE STANDARD TO BE CONSIDERED EXACT,
               E.G., IS 75.0 pg/m3 THE PRIMARY ANNUAL NAAQS FOR
               TOTAL SUSPENDED PARTICULATE (TSP)?
RECOMMENDATION:
DISCUSSION:
Each measurement should be converted to ug/m  ; the
same number of significant figures shall .be
carried after the conversion as are available from
the original instrument reading or analysis technique.
Computed averages (arithmetic or geometric) will
carry one significant figure more than the number
set from which the average is derived.
An excursion will be deemed to occur if and only if,
the converted, rounded measurement is one unit
above the standard.

This procedure is the most direct, easily understood
technique for summarizing and evaluating air quality
data and will be easily understood in presentations
in which comparisons with air quality standards are
made.  In addition, Federal regulations are specific
with respect to the measure of air quality used
(e.g.: arithmetic mean, geometric mean) and the
standard to which it is compared.  The use of any
other rule is, in effect, an amendment to Federal
regulations.  Conventions concerning the use of
significant figures will be treated in greater detail
in the forthcoming Guidelines for the Evaluation of
Air Quality Data.   The feasibility of returning to
ppm by volume as the unit of expression for gaseous
pollutants is being examined.

-------
      ISSUE 3:  SHORT-TERM STANDARDS ARE SPECIFIED AS CONCENTRATIONS
                WHICH ARE NOT TO BE EXCEEDED MORE THAN ONCE PER YEAR.
                HOW IS THIS TO BE INTERPRETED WHEN ANALYZING DATA
                OBTAINED FROM MULTIPLE MONITORING SITES?
RECOMMENDATION:  Each site is allowed one excursion above the standard
                 per year.  If any site exceeds the standard more
                 than once per year, a violation has occurred.
DISCUSSION:
By examining each site separately, data processing
problems are lessened and, more importantly, regions
employing more than the required minimum number of
monitoring sites would not be unduly penalized.
For any level of air quality, the expected number
of excursions above the standard in an AQCR is
a direct function of the number of monitoring
sites in operation.  Hence, examining each site
separately tends to adjust for varying 'numbers
of sites among regions.

-------
      ISSUE 4:  WHAT PFJIIOD OF RECORD OF AIR QUALITY DATA IS
                NECESSARY TO nSTA!Jl.;:'U TIM: STATUS OF AN AQCU WITH
              •  RESPECT TO 'HIE NAAQS?
RECOMMENDATION:  Each AQCR should be treated as a separate case in
                 establishing its status with respect to the NAAQS.'
DISCUSSION:
Although each AQCR would be examined individually,
the gradual establishment of precedents would
eventually provide consistency.  This option would
consider differences in monitoring coverage,
meteorology, the type and mix of sources, and
unusual economic circumstances.  Case by case
treatment would allow greater flexibility in examining
borderline cases, such as annual averages which
fluctuate around the standard, or short-term excursions
above the air quality standards.  Use of this option
is illustrated by the following examples:  (1) SO-
concentrations during the heating season in a northern
AQCR are lower than the short-term standards.  If it
can be shown that the number of heating degree-days,
the industrial activity, and the dilution capacity
of the atmosphere favored the occurrence of high
SO- concentrations, then the status of the AQCR
with respect to the NAAQS would be evaluated
accordingly. (2) Eight-hour average CO concentrations
in an AQCR fluctuate about the standard.  The period
of record was unusually favorable for the dispersion
of pollutant =>.  Hence, a longer and more representative
period of record is required to evaluate the status
of this AQCR with respect to the NAAQS.
1  This issue should be considered in conjunction with Issue 10.

-------
        ISSUE 5:  THE NAAQS ARE DEFINED IN TERMS OF A YEAR, I.E.,
                  ANNUAL MF.AN CONCENTRATIONS AND SHORT-TERM
                  CONCENTRATIONS NOT TO BE EXCEEDED MOKE THAN 01ICE
                  PER YEAR.  WHAT IS MEANT BY THE TERM "YEAR" AND
                  HOW FREQUENTLY SHOULD AIR QUALITY SUMMARIES BE
                  PREPARED TO CONFORM TO THAT DEFINITION?
RECOMMENDATION:  The tern "year" means a calendar year and air quality
                 summaries should be prepared for that period.
DISCUSSION:
While pollutant exposures may overlap calendar years,
the use of a calendar year for air quality summaries
remains a simple and conventional practice.  Indeed,
inquiries concerning air quality are most frequently
expressed in terms of a calendar year.  The data do
not warrant quarterly evaluation of compliance or
non-compliance with NAAQS, nor would it be reasonable
to revise emission control requirements on a quarterly
basis.  Since all of EPA's summary files are structured
around the calendar year, redefinition of the term
"year" would necessitate revision of current data
handling procedures.

-------
                                                        DRAFT
     ISSUE 6:  THE NAAQS's FOR CO AND S02 INCLUDE EIGHT-HOUR AND
              THREE-HOUR AVERAGES, RESPECTIVELY.  FOR SUCH
              STANDARDS HOW IS THE TIME INTERVAL DEFINED?.

RECOMMENDATION:  Tine  is defined as discrete intervals beginning
                at midnight.  Thus, there are three such intervals
                for CO and eight for S0_.

DISCUSSION:      This  option keeps all of the data within one calendar
                day (and therefore year).  It is computationally easy
                to handle and minimizes the redundancy of overlapping
                time  periods.

-------
     ISSUE 7:   THE CHANCES OF DETECTING VIOLATIONS OF  24-HOUR MAXIMUM
                STANDARDS DEPEND CONSIDERABLY  UPON THE  FREQUENCY WITH
                WHICH THE AIR IS MONITORED.  IN VIEW OF THIS, HOW
                SHOULD DATA OBTAINED  FROM INTERMITTENT  MONITORING
                BE INTERPRETED?
RECOMMENDATION:   Partial annual coverage  is  sufficient  to show
                  compliance;  predictive equations  to calculate
                  expected maximum concentrations,  etc.  should not
                  be employed.

DISCUSSION:       Ideally, continuous  monitoring  of all  pollutants
                  would be conducted.   However, except for those
                  pollutants specified in  Federal regulations, EPA
                  does not currently require  continuous  monitoring.
                  Thus, one is left with either (a) predictive
                  equations employing  data from partial  annual
                .  coverage, or (b) the data collected through partial
                  annual coverage.  Since  the accuracy of predictive
                  equations is not well established, the remaining
                  alternative  is to judge  compliance on  the basis
                  of partial annual coverage; however, regions at
                  their option, could  sample  more frequently than
                  the required minimum. Partial  annual  coverage
                  schedules make detection of short-term violations
                  difficult.  The entries  in  the  following table are
                  the probabilities of choosing two or more days on
                  vhich excursions have occurred  for different numbers
                  of actual excursions above  the  standard and different
                  sampling frequencies. The  assumption  underlying
                  these probabilities  is that at  a  monitoring site
                  excursions above the standard occur randomly over
                  the days of  the year.

-------
                                                      i/KAf'T
         PROBABILITY OF SCLECTIIIC TV.'O OR MORE DAYS WHEN SITE
                        IS ABOVE ST/uNDARD
                        Sampling Frequency - Days per year

Actual no,
of excursions            61/365             122/365          183/365
2
4
6
8
10
12
14
16 '
18
20
22
24
26
.03
.13
.26
.40
.52
.62
.71
.78
.83
.87
.91
.93
.95
.11
•41
.65
.81
.90
.95
.97
.98
.99
.99
.99
.99
.99
.25
.69
.89
.96
.99
.99
.99
.99
.99
.99
.99
.99
.99
                              10

-------
                                                                     .   .4
     ISSUE 8:  HOW SHOULD PARTICULATE MATTER, CO AND OTTIER POLLUTANT
               CONCENTRATIONS RESULTING FROM SEVERE RECURRING DUST
               STORMS, FOREST FIRES, VOLCANIC ACTIVITY AND OTHER
               NATURAL SOURCES BE TAKEN INTO ACCOUNT IN DETERMINING
               COMPLIANCE WITH NAAQS?
RECOMMENDATION:  Regardless of the source, ambient pollutant concen-
                 trations exceeding a NAAQS constitute a violation.

DISCUSSION:      Ambient pollutant concentrations exceeding the
                 NAAQS and resulting from emissions from natural
                 sources constitute a violation.  However, such
                 violations should not be used as a basis for
                 developing or revising an existing, across-the-
                 board control strategy.
                                   11

-------
     ISSUE 9:  SHOULD ALL AVAILABLE AIR QUALITY DATA OR ONLY THOSE
               DERIVED FROM AIR QUALITY SURVEILLANCE SYSTEMS,
               AS SPECIFIED IN A STATE IMPLEMENTATION PLAN (SIP) ,
               BE USED TO DETERMINE COMPLIANCE WITH NAAQS?
RECOMMENDATION:  All available valid air quality data representative
                 of the exposure of receptors will be used to determine
                 compliance with NAAQS.  This includes data obtained
                 from the air quality surveillance system specified
                 in the applicable SIP, data obtained from the
                 National Air Surveillance Network (NASN), data
                 obtained by industry monitoring stations, data
                 obtained from monitoring stations installed and
                 operated by concerned citizens, etc.
DISCUSSION:
NAAQS have been established to protect the health
and welfare of the population.  If the NAAQS have
validity, the violation of a standard at any point
in the AQCR is significant.  Even though a station
is not part of the established surveillance network,
if acceptable methods, procedures, calibrations
and recordings have been used and can be verified,
and the station is located in accordance with applicable
criteria for representativeness, the data from that
station should be used for the determination of
compliance (or violations).
                                    12

-------
     ISSUE 10:  HOW SHOULD COMPLIANCE WITH THE NAAQS BY JULY
                1975 BE DETERMINED?
RECOMMENDATION:  Base the  >reliminary determination of compliance
                 on adherence to the implementation plan emission
                 reduction schedules.  Confirm compliance with
                 NAAQS by air quality surveillance during the
                 calendar year 1976.  However, non-compliance
                 with short term standards can be determined during
                 the last six months of 1975 if two concentrations
                 in excess of the standards occur.
DISCUSSION:
Implementation plans based on bringing many individual
or categories of sources into compliance with emission
regulations by July 1975 have been granted at least
conditional approval.  However, a twelve-month period
of air quality surveillance is required to determine
annual average air quality values.  Further, the
calendar year has been recommended as the time unit
for the calculation of annual average concentrations
(see Issue 5).  Obviously the calendar year of data
required to demonstrate that annual NAAQS have been
achieved by the control activities fully implemented
by July 1975 cannot begin before 1 January 1976.
Non-compliance with short period standards can be
determined in less than a calendar year by the
occurrence of two concentrations in excess of the
NAAQS.  Before an AQCR can be said to be in compliance
with short term NAAQS a full twelve-month period of
air quality surveillance records, encompassing all
four seasons, must be available for examination.

-------
ISSUE 11:   MAY MONITORING FOR CERTAIN POLLUTANTS BE RESTRICTED
           TO ONLY A PORTION OF  THE DAY?    FOR EXAMPLE,  IN THE
           CASE OF OXIDANT,  WHICH HAS A CLEAR DIURNAL  PATTERN,
           WOULD IT SUFFICE  TO MONITOR ONLY DURING THE HOURS  •;
           FROM 8 A.M.  TO 6  P.M. L.S.T.?
                                                                       A
RECOMMENDATION:
DISCUSSION:
            Partial daily monitoring of pollutants  subject  to
            short term NAAQS is not allowed.   All hours  of  the
            day must be monitored (except  perhaps for one hour
            missed during instrument calibration) and reported,
            and will be used in evaluating compliance.

            While specific pollutants show rather consistent
            diurnal patterns of concentration,  particularly
            when mean hourly values are considered,  the
            concentration patterns  are subject to modification
            with both seasonal and  short period changes  of
            meteorological conditions.   This  is most noticable
            when a region is subjected to  episode conditions.
            In addition,  the actual local  time of occurrence
            of periods of high concentrations will  vary  from
            AQCR to AQCR and perhaps from  monitoring station
            to monitoring station within an AQCR.   Extensive
            study of patterns and trends exhibited  by pollutant
            concentrations within each AQCR would be required
            to select the portion of the day  to be  monitored if
            partial monitoring were allowed.   Further, monitoring
            data for the full twenty-four  hour period will  help
            determine the extent and duration of episodes and
            contribute to the determination of the  need  for
            emergency control measures.
            It should be noted that automatic monitoring devices
            used to obtain sequential hourly  data are seldom
            amenable to shut-down and subsequent startup without
            a  warm-up and stabilization period.
1  Except nonmethane hydrocarbons where 6-9 A.M. is specified in
   the NAAQS.
                                  14

-------
y*
 i
 i
 i
 i
 i
 i
 !
 !
GUIDELINE   SERIES
           OAQPS NO.  1.2-009
                        EPA NEDS PROCEDURES
                 Responsibilities and Procedures for
                 Internal Semiannual Reports Activities
                   Required NEDS Update Procedures
              US. ENVIRONMENTAL PROTECTION AGENCY
                Office of Air Quality Planning and Standards

                  Research Triangle Park, North Carolina

-------
      Responsibilities  and Procedures  for Internal Semiannual
                        Reports  Activities
      These procedures outlined below are  applicable  for  the  first
semiannual report activities pertaining to the  emissions  reporting of
sources (or points) achieving a final compliance requirement  in  the
reporting period or since approval  of the  implementation  plan or
applicable portion thereof, plus those sources  which  were new or modi-
fied and whose operation uegan in the reporting period and those
which ceased operations during the  reporting period.

      A.  Sources Under State Jurisdiction

          1.  The Division of Stationary Source Enforcement (DSSE)
will generate a computer tape (from CDS) identifying  known sources
achieving a final compliance requirement in the reporting period
according to a state's compliance schedule.  Before sixty days prior
to the report date the tape will be forwarded to the  NADB for NEDS
processing.

          2.  From the information provided above the NADB will  cen-
erate computer printouts, original  and one copy, of the current NEDS
sources records effected.  Approximately forty-five days  prior to the
report date these source records will be forwarded to the Regional
NEDS contacts.

          3.  Upon receipt, the Regional NEDS contacts should distribute
these NECS records to the appropriate state air pollution control
agencies.

          4.  State air pollution control  agencies should update
(see required NEDS Update Procedure) the NEDS source records.
These, in turn, will become a part of the state's semiannual  progress
report, due the  last clay of the reporting period.

          5.  Upon receipt of the emission portion of a state's
report:                                                      v

              a.  i-f the report is a computer card deck or tape it  may
be forwarded directly to the NADB for NEDS editing and processing;

              5.  if the roport is NEDS fom:s , marked-up fiCDS com-
puter printouts or other, coding and keypunching is  required, after
which activity records should be forwarded to NADB for NEDS editing
and processing no later than forty-five days after the end of the
reporting period.

-------
           6.  All input which has undergone-editing routines will
be returned to the NEDS contacts along with indication as to whether
or not the editing and validation were successful.  The NEDS contacts
will then be requested to further vrilid.vle those data which passed
and to correct and resubmit those data which did not


      B.  Sources Undor_J:e_dcraJ_J_uTisdi_cticm

        1 .The Division of Stationary Source Enforcement will generate
a separate list for sources achieving final coivpli a nee that are
federally controlled.  Dependent upon volume, a tape tray be provided.
Before sixty days prior to the report date, the tape must be forwarded
to the MADB for NEDS processing.

          2.  Fron the information provided above  the NAD!'; will gen-
erate computer pri-iiouts., original and one copy, of the current NEDS
sources record:.- cficctec.  Approximately forty-five days prior to
the report date source records will be forwarded to the Regional
NEDS contacts.
i
          3.  Upon receipt, NEDS contacts trust r-ako c'pprnnri otc dis-
tribution to responsible Regional Office personnel rmriitoring
Federally controlled sources.

          4.  Dependent upon normal operating procedures, emission
records should be updated and returned to t!ic NEDS contact.
(Proposed procedures for use of APER fc-nrs in conjunction with
seir.i annual repc.rting are being drafted and will be forwarded for
review at a later date).

          5.  Upon receipt of this report:

              a.  if the report is a computer c,::r.d deck or tape, it
tray be forwarded directly to the MAD I1, for NEDS editing and processing;

              b.  if the report is NEDS fonts, irarked~up NLDS com-
puter printouts or other, coding and keypunching is required^ after
which activity records should be forwarded to NADD for NEDS editing
and processing no later than forty-five days after the end of the
reporting period.

          6.  All input which has undergone editing routines will be
returned to the NEDS contacts along with indication as to whether or
not the editing and validation were successful.  The NEDS contacts
will then be requested to further validate those data which passed
and to correct and resubmit those data which did not.

-------
    C •   !''£w_ 9JLJ1°A'LD' .9 cLSoy rccs  and Sources  Ceasj IKJ  Operation

        Sources  falling  into  the  above  categories  should  follow  the
some routing as  those covered  in  Section  A.  There will,  however,
be no Ni.DS point S(.n;rce  listing  from which  to  begin.   The specific:
instructions belov/will  apply:

        1 •  ''    n1   fd soJrcRs beginning  oerations  durinn  the
                                 ..
jep_ortino_p_enpd should be entered  into  NEDS  following  established
standardized procedures as deliniated  in  the  Publication  APTD-1135,
''Guide for Compiling a Coi-.prdKrisi ve Emission Inventory."   NECS
forms thus completed should be  keypunched  before  submission to NADB
for editing and processing.
            .i0."'1".^^  f o_r_ wh_i ch  yp___            __      _
given but at v/hich operation has not begun should  be  reported
ecf.orcina to the nrr-edures defined in  C-l above,  with  the  followinn
EXCEPTION:

            Card 4, spaces 66-70 should be completed  with a  "6",  a
new cede added to N!"D5> to define new non-operating sources.

        The emission estimate calculated automatically  by NEDS will
be zer.Oj until so;iie future date when the plant starts operation and
the estimation method code is change! appropriately.

        3.  Sources coasino oporations_  durinn tiie  reportinc  period
should not Lc deleted fror.; ili.ic .   Instead, a code  "7" should be
utilized on Care! f[ , spaces 6G-70 of tiic h'EDS form  using the  chancje
procedures derinee in "Required Update  Procedures  for NEDS." The
code "7" will cause an automatic calculation of  emissions ar zero.

-------
PILL o-!'• i M.'  ON FHIUAY AUGUST 17, is>;3  .    •                     •

                                       NATIONAL    EMISSION    DATA    SYSTEM

                                                 POINT    SOURCE    LISTING

STATF. (3?):  \f.W  .••t;XICO       A.1CRI014): FoUH CORNERS  (4 S12-COLO-N. M. -u7 AH)                     CITY!
COUNTY : 1'JOO) :  SAN JUAN CO                     PLANT IP!  0003  POINT ID:  Cb
  -'fi-iOiMrS^:  PLATEAU INC
   SOVA! CQ'-TACT:   •
                                 SIC (3911):  PETROLEUM./!^ INIXG
        SCCd-CJ-OOh-03) :  EXTCOM3  UOILER    -INDUSTRIAL /      -MATU-->AL GAS
  GKNFwr-L  If-F.'iHMATIllN
  O-»«9<>4}oi>« oa^* atif>i>«oo«


FUEL SULF'.i-1 CONTFN'T:  0.01  S

   FUEL  As-i CONTENT:  oo.c  ^

  FUEL HEAT CON-TENT:     890
HAND CALCULATED ErtISSlG.->fciI>VATES
PAP.T1CULATE : \ 0 l^:NS/Yrt
SOX: \ /Tr.\s/Yr<
M(!X: ^^V" TO.'iS/Yw
( ~^~^\^ CO: | 0 TO.'-.S/YR
\t.-.! ss i CN >k: -^ T i ON ^T^C.DS
\f-ARS. EMISSION FACTOR ( AP-4i; 0" PENDING)
\ .SOX iXF^MtSSIOM F ACTOH1 A^-42 f!R PENDING)
\NOX ti'M^SluN F iCTOW ( A°--"•; NLi I-'G )
^ CO EMISSION FACTOHtAP-^? OH PENDING)
CiTION | COriT-vfiL.
^coo<» j trFICIt^CIES
"ENT ! PART: .CG.C %
1
WENT 1
MtNT I SOX: 00.0 %
!
WENT |
M£i\iT I fjOX; 00.0 '-(,
1
M5!NT |
WENT 1 HC: 00.0 *
!
KENT I CO: 00.0 i
t Q ? f " P ' ^ I '• j H A T r '•>
( AMN'JAL OPtrlATIMG KATE: ;
1
! fiOU-'L'f MftXM L'tlSioN ^ATt:
1
. 1 iOlLi.V OESir,,\ Ci.:3i.CITY:
LI-ION B7U/«lLL10:,' CUjiC FEET tsU«.\ED
ALLOWABLE EMISSIONS
PAWTICULATF:: TOXS/YR
sox: o TONS/YR
HC: TOMS/YM
CO: TONS/YR
COMPUTED CALCULATED Ef-.IL-SICNS
PART: <1 TONS/YS
sov: 
-------
                     Required NEDS Update Procedures

     Periodic updating will be necessary to Insure that the data 1n the
National Emission Data System are current and as correct as possible,
Any new information or change will be submitted by the State Agencies
at least as often as che semiannual report.  After the information is
coded and submitted by the State through the Regional Offices for editing
and validation, the information will be reviewed and included in NEDS by
National Air Data Branch (formerly National Source Inventory Section)
personnel.
     The three processes included in the update procedure are:  DELETION,
CHANGE, and ADDITION.   The DELETION procedure is utilized to delete any
plant, point within a plant, or process within a plant which is invalid
on the data bank.  The CHANGE procedure is utilized to change any data
field in an existing record on the data bank.  The ADDITION procedure is
utilized to add a new point, plant, or process to the data bank.  A more
complete explanation on each procedure including the exact coding follows.
     If the DELETES, CHANGES, and ADDITIONS are coded correctly, the three
types of coding do not need to be separated as they can be handled during
the same computer run.  The procedures are performed on any given plant,
point, or SCC in the following order:  DELETE, CHANGE, and ADD.  A DELETION
and ADDITION of the same card or cards within a point will be done on the
same run.  A DELETION and CHANGE of the same card cannot be handled on the
same run.  However, CHANGE and ADDITION of the same card cannot be handled
on the same run as this would result in duplicate cards.

-------
     The update procedure which 1s  performed  1s determined by the entry 1n
column 78 on each card.  If a D 1s  coded  and  punched  1n column 78, the
DELETE procedure will  be activated; 1f a  C  1s coded,  the CHANGE procedure
will be activated; and 1f an A 1s coded,  the  ADDITION procedure will be
activated.  For these  reasons, the  correct  action code (D, C, or A) must be
coded in column 78.

-------
                           DELETION PROCEDURE

The DELETION procedure 1s utilized to:
1.  DELETE any plant, point within a plant, or process within a  point which
has incorrect identification.  If a plant was initially located  in  the wrong
state, AQCR, or county, the identification would be incorrect.  Also, if  a
point or process was incorrectly coded, the identification would be incorrect.
2.  DELETE an incorrect SCC by deleting a card 6 and re-add the  correct card  6
in the same computer run.
3.  DELETE an incorrect data field when the field should be blank.   If the
incorrect data field is on cards 2-5, card 2 would be deleted and the complete
point (cards 2-6) re-added with'the incorrect data field left blank.   If  the
Incorrect data field is on card 6, card 6 would be deleted and re-added with
the incorrect data field left blank.
4.  DELETE a point or points when a change is made in the field  for Points
With Common Stack (card 2, columns 56-59).  After the point or points are
deleted, with a card 2 deletion, they must be re-added with all  cards (2-6).
     The DELETION Procedure is set up so that only a card 1, 2,  or  6 is
deleted.  The deletion of a card 1 removes the complete plant from  the
master file, the deletion of a card 2 removes that specific point from the
master file, and the deletion of a card 6 removes that specific  process from
the master file.
     Use the following specific procedures and a blank NEDS Form (OMB No.
158-R009S) to DELETE any information from the master file:
1.  To DELETE an entire plant, complete the identification columns  (1-13)
for that specific plant and enter a D in columns 78 for card 1.

-------
2.  To DELETE a specific point,  complete the Identification columns 0-15)
for that specific point and enter D 1n  column 78 for card 2.
3.  To DELETE a specific process, complete the Identification columns
(1-15 and 18-25) for that specific process and enter D In column 78 for
card 6.
4.  Mark the card on which the DELETE occurs with an asterisk (*) in the
margin of the form so only that  card will be keypunched.

CAREFULLY NOTE:
      Care must be exercised to  insure  that only the desired plants, points,
or SCC's are deleted.  Once the  DELETE  has been completed, retrieval of
lost data would be impossible.   To make sure that the correct identification
1s used, a current NEDS Point Source Printout should be used to double
check the identification.
                                                    •
      Figure 1 is an example of  a possible point source forms in NEDS.
Figure 2 is a point source form  with columns 1-15 and 78-80 completed
for card 2.  This coded card would DELETE the point from the master file.

-------
                            CHANGE PROCEDURE

The CHANGE procedure 1s utilized to:
1.  CHANGE any data fields, except Points With Common Stack,  which were
blank or incorrect on the NEDS point source.
2.  CHANGE any data field, except Points with common stack, which has
changed as a result of a process change, a design change,  or  an  operating
rate change.
     The CHANGE procedure 1s set up so that any data field on cards  1-6
can be changed.  Only the data field which is to be changed should be
coded to reduce both coding errors and keypunch errors.  The  changes
must be consistent with all coding procedures as presented in Chapter 4
of "Guide for Compiling a Comprehensive Emission Inventory,"  APTD-1135.
     Use the following specific procedures and a blank NEDS Form to
CHANGE any data field in a point source record on this master file:
1.  Complete only the card on which the CHANGE is coded.
2.  Code only the complete data field which contains the CHANGE  using coding
procedures as presented in APTD-1135.
3.  Complete columns 1-13 for card 1, columns 1-15 and 56-59  for cards 2,
columns 1-15 for cards 3-5, and columns 1-15 and .18-25 for card  6 with the
Identification as taken from the NEDS Point Source Printout.
4.  Change the action code in column 78 from an A to a C or if column 78 is
blank, enter a C.
5.  Mark the card on which the CHANGE occurs with an asterisk (*) in the
margin of the form so only that card will be keypunched.
CAREFULLY MOTE:
                                       /
     Care must be exercised to Insure that only the desired data field is

-------
changed and that the correct point source Identification  has  been  used.



     Card 4 of Flpure 10-2 aives an example of a  change  in  NO  emissions.
                                                             n


The change is coded by completing the point source identification



(columns 1-15), completing the emission estimate  for NO   (145 T/Y),  and
                                                      "


placing a C for CHANGE in column 78.

-------
                           ADDITION PROCEDURE

     The ADDITION procedure 1s used to add new plants, pofnts within
existing plants, or processes within a given point.  The standard NEDS
point source form and the coding procedures as presented In Chapter 4
of "Guide for Compiling a Comprehensive Emission Inventory," APTD-1135
will be used.
     The only problem which could result from ADDITION of new points 1s
a duplicate record.  A current point source listing should be used to
obtain the identification for plants currently in NEDS.  New plant Identi-
fication numbers will be assigned by the NEDS contact 1n each EPA
Regional Office.

-------
•'= i  Co--.!>•
1T|TJT]FT7
i _ * TT . : _ TZ
     i on ijo
                 AQCS
                  8 !
                        Plant 10
                       Qiojo
                                                              NATIONAL EMISSIONS DATA SYSTEM (JiEDS)
                                                               ENVIRONMENTAL PROTECTION AGENCY
                                                                     OFFICE: OF AIR PROGRAMS
                                                                           Figure 1
                                                                                                                            POINT SOURCE
                                                                                                                              npu
                                                        ns ol Pcrscn
                                                                                             FOKV, A?rr;.\;o
                                                                                             O.V3Nc. H'-.OSSS'
                                                         Establishment Ha:?* jr.d A^rf ss
i  •      1 „-,
L_  City  	  Zgre.KscsrdI                                     Estabiis.'-.men'. Ha.?? a.-.d f.ititss 		             j         Conlacl-
j:4fl7risTl7|'-?'[!9|2ol2j 'zl23[>'J?S]26!27T2^9[30|31J32r33l3'i!33 Sel?, _3^33|JOi4l!<:;ra3[-'.''.[T5]i:6'<7U'al45!5CJS1J62:!i"ijC-^?;'' ••r-L^!.:" :"'!\fJ5l!C2;35S4ioy 6\lG7
IZklol oh io'iVm'jr oYNTfi'silFiQiuh IblA IRIYI  Tg'iTrol~i sTs'ipT Tsi'ft  IciHT'ifaOuFjloT' .["2'.5 ;.-i i""' • •: ~t7I i i'AtiTlTT"

L
Coniacl • Personal ',o
^•Sl!C2;5^54l
*:Tp1irAti
ci-j 6\| G7
i IT!
G3j6Cl7G>71
M U |R I
72

73.'7«
!»

rrr-
                               UTM COORDINATES     '
                        !PP   Hcrizc;Ua! I   Vetlical
 ra:r.l  j  jrcrri!          I  !PP   Hcrizc;Ua!     Vetlical             ,       i          j                 j PL;>; K?it/-:J  j   ,.: rr   i
 _!? J  t-'-lii    5!:___'!"'"-iS_	i;^	ia^	    Heij^!(Jl)  j Dia- ;!:j JT;.^ (-Q    Flnw Pdt; ;.:;3,f.;-,  jljj^o sl^.-iLi  |_Vi::-V  _?	^^—^^—^
 ^SJ  jlR:i:]iIl&!2:lp[5fe!li:£5py]2S:23]i|?^
I^JD  |7! i|313:2 jl 17/101512 l6j.8|3nil|oTir I  13 1 fii  13 5 I   j?fQ  1 Q| TTzi  SFo 10 P Fl  ! Tot  JO n  I 0! oli TlH  I   II
        F.occ::  !06eTUbr
                          Pt:ru;y  JSeconda.-y
                           Part.  |  Psn.  | SQ?   I  SO?

       I?'li'_i~.r'i5 feltiLolcrfe''! 6|i) jpToLo76 T ohSjl.
                                               Second3(>
 CONTROL
   Piisocy
     BO,
                                                      3:i3c[32
                                                      jOlo.
                                                            Sccasdjrv
                                                              NOZ
          38139! 40
                                                                                                       ESTIMATED CONTROL Er FICIE.'tCY (4)
                        Pn.TJry  Secondary i  pi i.Tury I Secondary        ill!
                         HC     KC      CO  I  CO     P;rl.  j   S07      HO-     !IC   j   CO
                       4i[«!";""; ^J^i^^~C^1-^^[s7^"!s^^^!i7 :'-^'33'--.s'£iM? igslcTfj'^^
                       ollol ololfiMlpjp.Jo"I'CLQI'lO'„ lot'T'Ioi~T"rbl "!~l"ol":r~I'
                                                                                                                                                 2i73!7^[75 •:  .'7!7of/9
                                                                                     c£
                                                                                     so
               % ANNUAL TKRL'PUT

        S'ear ot
             Dcc-
             Fe!)
             215
                Kay

                  2ir-
               .	?
                       Aug
                       215.
                            Nov
                                  OPERATING
                                          yi
                                        .?9T30
                                                                          EMISSION ESTIMATES (tcrs/y
                                                 Parlicuiate
                                             31!
rrrrre
     NOS 	        HC                CO   	
    M^tPjH i^T^siisGr^i.w ^'^F^^plFE.!-
    i  n tern  I  I  I T  i fihi  I  I  i i  I   n
                                                                                ESTiaMIOH
                                                                               f Kw|
                                                                               ^'s!I'-'oL'r
                                                                               3    nh l
                                                                                                                                                S Space
                                                                                                                                                 Heal
                                         ALLOWABLE EMISSIONS (tons/year)
                 Parliculale  	   	   s°2__
              !ri9J20j2TJ22J2j 24 25J26J27 23 2Sl30J3
                                                       «0,
                                               32|33J34i3s]3'6T37
                                               rn  M
          38
                                                                       HC
                                                              3_9]loUf}42 Iip!*ijt5.
            i°i!2illli?il3L*2i
            JLLLJ-d
                                           CO
                                   46'47!48[43}50l5l]52
                                   "n  rrn~
                                               53
                                                 COMPLIANCE
                                                 SCHEDULE
                                                 Yt;r  V.onUi
                                                      56157
                                                                                                               COK^IANCE STATUS
                                 UPDATE]
                               Yejr Jf:'oslh
                              SfllbSICOiSi
                               .LLZ
                       Day
                       32]l3
                                                                                                                                        CONTROL REGULATION    I
                                                                                                                                     Regl
                        5S[66 167
                          ED
                                                                                                                                               Reg 2
                                                                                       59
                                                                                         TtJ
                                                                                            71
                     SCC
             IS
                19
                  20
                    21
                       22
                         23
                            24
                             IV
                              25
                                '6
                                     Fiiel)process/
                                     Solid Waste
                                    Operating Rate
                                   27
                                        29
                                             31132
                                                5
Rlaximum Design
                                                  33
34|35
                                                      RM
                                                       36
                                                           37 38 133
                                                           .5.
                      Sullui
                    Conten!_^
                         «
                         J}
                                                                          Content 1,
                                                                           ^iriili
  Heat Co.-tc.il
_iOJ £TU/r.cc_
46747'|4aT4"";50
                          Jfi
                                                                            Li_'
                                                                              i_

                                                                                  i Jo
                                                                                 	I
        IE
                                                                                         1'
                                                                                                                    Cc-nsn!;
                                                                                              51|5
Isfsl
"b1!^
i9T6o!G1162,'63164
                                                                                                                     i~r
                                                                             65l66l07
                                                                                    68 69
                                                                                           71
                                                                                              72
                                                                                                                                                              I =
                                                                                                                                                     R^JL  i  U
                                   73'74[7si:T'.'7i;3
                                                                                                                                                                       ei
                                                                                                                79
                                                                                                                                                  72
                                                                                                73
                                                                                                                                                       74
                                                              II
                                                             J<
                                                       ~^~^-~ • ,i.rT"
75•'.--: '/;;3
                                                                                                      -rtr
                                                                                                                                                                      cd
                                                                                                                                                                      30
                                                                                                                                                                 AjP
                                                                                                                  6,

-------
SU!-
1
\f
2
^
CS-Tity
3
0
< Is
1
0
6
0
AOCR
7
2
819
OjO
Plant ID
Njnlar
10J11J12J13
o io b h'
                                       NATIONAL EMISSION'S DATA SYSTEM (X£DS)
                                       ENVIRONMENTAL PROTECTiOM AGENCY
                                            OFFICE OF AIR PROGRAMS
                                                 Figure 2
                                                                                        PCiWTSOURCE
                                                                                         Ir.put Form
                                                                                                 FOaM A?? .•..'.• .
                                                                                                 ov.sivo. v:: ••
                                                                                                 Date	
                                                                      Co.r.;!c!irj Form .
   Hi?
IVifislieli? iT! 151?:o[?1 B2T2l!? U. j _
                                                      4^8 45U6J47J-:3
                                                                                                |;i J72
                                                                                                    73 74|7c •
     Boiler C:5i"
                                     CONTROL EQL'!P,V£NT
tv'53fcl I C.i?ici^y    pii-;r/  Sicontoy | Piir.-.a;; jScccr.ijfy j Primary ! Sccaniaiy p;ima:y IScccrrirjryi prl.Ti.-,;)'jSecsr-':.'/!
 ecii '5"'    Fj;!    Fai1' l-S0---;°2    :i0*    °s    HC    iiC    CO    CO  j  P;;i.
                                                                    ESTIMATED CUfiTROL ErrlCIEKCY (%>
     rl^~b'iflfnzr^]d^ H-r j^j^^^p}3-^
           % ANNUALTKRUPOT
pn r'j'rri'n'T'J  i j i  \  i \  IT  i i
                    HO?..V:'.L
                   OPERATING
                     >D I
                                                                                             CO
                                                                                                                      cd
K:cr.:.Jlrcb! Mo/ A'J|>
                        -yt
               ..
         JTT i "LI r r r r i
                                               EMISSION ESTIMATES (Sans/year)
                              Parliculalc
                                     ____ _
                          ~3"i Ffz"' 3.j! 3 :;3T3s\
                •
                                                         oiibi 1:1'j Ti"I r jTtrt'. ri I'lTI  I i"i~j":
                                                                                           CONTROL RLCULATJCNS
                                                                                     L
                                                          CO     |«|V.-jr ito^.j V-.-jV -!:,| ::y ^   R?P 1

      Jl
      1!4[^'
       i
          sec

           IM

                     Fuel^'roccss,
                     Solid W;i!c
                      rjIing Rate
     Rale	'anii	
33J24J35iJGi37"r38 !39tj»T4l!42
                              --
                                                      A:!i I  !io:! Ccr.Icr.;  j            •           '            (?!?!
                                                    Cc.i!?.'.l_".|  1C.£ OT'!/:.cc  i  _         _   Cc-.^'i:  _  ^^_^__^ _  J^}^'i_  _
                                                    fe3T^
                                                    LjJl:LCLLlJ-:_:IL.LiJX^^
                                                    4-i-i-LLi J._i4j...Lr.L.i i - CI-Li_i_4_L J±m.q±L
                                                    -4JJJ.-|_p-J_u. -U- 44^-Qlu3irTT J±ni
                                                    MTl4:kH-+m-rf]H-f4i+LH-i fffRm-
EPA (DUR) 220
   3/72

-------
GUIDELINE  SERIES
           OAQPS NO.   1.2-011
              DRAFT
    GUIDELINES FOR DETERMINING THE NEED FOR
    PLAN REVISIONS TO THE CONTROL  STRATEGY
         PORTION OF THE APPROVED
         STATE IMPLEMENTATION PLAN
                                            3OC
   US. ENVIRONMENTAL PROTECTION AGENCY
     Office of Air Quality Planning and Standards

       Research Triangle Park, North Carolina

-------
           OAQPS  1.2-011

GUIDELINES FOR DETERMINING THE NEED FOR

PLAN REVISIONS TO THE CONTROL  STRATEGY

         PORTION OF THE APPROVED

       STATE IMPLEMENTATION PLAN
                 DRAFT
                                 Analysis  and Reports  Section
                               Standards  Implementation  Branch
                             Control  Programs Development  Division
                                   Office of Air Quality
                                  .Planning and Standards
                                      November 30,  1973

-------
                      TABLE  OF CONTENTS

  I.   Introduction	1
 II.   Responsibilities in Implementing Plan  Revisions.  ...   3
III.   Procedures  for Determining  Whether  a SIP/Control
      Strategy Needs to be Revised  	   5
      A.   Identification of  Problem Air Quality  Control
          Regions	5
      B.   Evaluation of Data 	   7
      C.   Analysis of Control  Strategy 	 10
      D.   Reporting of Results	13
 IV.   Procedures  for Requiring Plan Revisions. . v	 14
      A.   Plan Revision Documentation.	14
      B.   Notification and Concurrence 	 15
      C.   Notification of State	15
      D.   Plan Submittal	17

-------
I.   Introduction
        Section 110(a)(2)(H)  of the Clean Air Act,  as  amended requires  that
    State Implementation Plans (SIP's) "provide for  revision,  after public
    hearings,  of such plan (1) from time to time as may be necessary to take
    account of revisions of such national primary or secondary ambient  air
    quality standard or (2) the availability of improved or more  expeditious
    methods of achieving such primary or secondary  standard;  or (3)  whenever
    the Administrator finds on the basis of information available to him
    that the plan is substantially inadequate to achieve the  national ambient
    air quality primary or secondary standard which it implements."
        While  the Act specifically identifies three (3) reasons why  SIP's can
    and must be revised, this guideline deals mainly with plan revisions to
    the control strategy portion of the SI? which are  deemed  necessary  on the
    basis of information available to the Agency which indicates  the approved
    SIP/control strategy is inadequate to attain the national  standard  it
    implements.  While the reasons for requesting a revision  may  be  different,
    the administrativa procedures for requesting a  revision under each  of the
    three cases is the same.
        EPA must exercise good judgement in determining whether the  control
    strategy portion of an approved SIP is inadequate  to achieve  national
    standards  on a timely basis.  It should be the  Agency's policy to request
    such plan  revisions only  where they are clearly necessary.  Frequent
    revisions,  particularly where they affect emission control requirements,
    are undesirable in that they confront source owners with  a "moving  target."
    In an attempt to assist in identifying those Regions that may need  plan
    revision,  the Standards Implementation Branch (SIB) of the Control  Programs

-------
                              2
Development Division, Office of Air Quality Planning and Standards,  has
developed a PLAN REVISION MANAGEMENT SYSTEM (PRMS)  which compares  actual
measured air quality levels, submitted by States  as part of their  quarterly
reports, with projected emission reductions required by the adopted  emission
limitations contained in the approved SIP.   The system is capable  of moni-
toring the progress in each AQCR and when ambient air quality  levels do not
follow the anticipated reductions,  the region  will  be flagged  as a "potential
problem region."  Further investigation by  regional personnel  will be necessary
prior to the determination of whether a plan revision is needed.

     The majority of the information that will be needed to formulate the
  decision as to whether the control strategy is  inadequate to achieve
  the national standards will be obtained from the quarterly and semiannual
  reports (40 CFR 51.7, Report, August 3, 1973).   Of course, other informa-
  tion such as the Quarterly Trends Report, daily contacts with State and
  local agencies, compliance information (see enclosure 1), etc.,  should
  also be used in the determination.  Air quality data will be the key
  indicator of a "potential problem region," as measured air quality will
  be the real   indicator of attainment of the NAAQS.  However, emission
  data, enforcement and compliance information, etc. must be reviewed to
  determine the adequacy of the control strategy to attain the national
  standard  in relation to the measured air quality levels.   \
                                                                j
      This guideline sets forth (1) the procedures  for determining when
  a revision to the control strategy portion of the SIP is necessary (2)
  the procedures for notifying the State that a plan revision is  necessary
  and (3) the responsibilities of headquarters and regional personnel in

-------
                              3
    implementing the:e procedures.
II.  Responsibilities in Implementing Plan  Revisions
         In cases where revisions  to the control  strategy  are  necessary
    because new information indicates that the approved  control  strategy
    is inadequate to attain the  national  standards,  the  Regional Office
    will  be primarily responsible  to review available  information  and
    recommend any action, if appropriate,  to call  for  a  plan  revision.
    Recently, in response to a request by  the Assistant  Administrator
    for OAWP, the Administrator  delegated  his authority  to request a plan
    revision to the Regional Administrators'through  EPA  Order  1270.5 (see
    enclosure).  In cases where  the requested revision would significantly
    affect emission control regulations,  or the enforcement thereof,
    Regional Administrators should obtain  the concurrence  of  the Deputy
    Assistant Administrator for  Air Quality Planning and Standards and the
    Deputy Assistant Administrator for General  Enforcement prior to request-
    ing that the State make the  revisions.   Further, where the requested
    revision would have significant national  policy  implications or would
    establish a significant precedent (the first time  a  substantial type
    of action is taken anywhere),  the above Deputy Assistant Administrators'
    concurrences should be requested.   Insofar as  other  revisions  are concerned,
    Regional Administrators should  simply  notify the above Deputy  Assistant
    Administrators of requests trade.
        OAWP/OAQPS will  provide overall assistance  to the Regions  in this
    area.  A  Plan  Revision  Management  System is  in  operation which  will provide
    a  review of the  air quality  data  received from each  State  and  local agency
    and identify  those  Regions where  it  appears  adequate progress  is not
    being  made  in  attaining the  air quality standards  as provided  in the

-------
implementation of the SIP.  In addition, OAQPS wi.ll publish the Quarterly
Trend Reports, Quarterly Air Quality Summary Statistics and the Annual
National Emission Report.  These reports will serve to assist the
Regional Offices; as the Regional Offices will have the primary responsi-
bility for determining whether a plan revision is needed.
     Once tne plan revision has been submitted by the State, the Regional
Offices (as outlined in the September 14, 1972, Sansom/Quarles memo of
understanding, as revised in 1.2-005 (revised) of the OAQPS Guideline
Series) are further responsible to review, to recommend approval/dis-
approval and promulgation and to prepare the Federal Register package
associated with any measures which have been determined to be necessary
to assure that the national standards will be achieved.
     Headquarters (OAWP/OAQPS and OEGC/DSSE) will provide technical and
policy assistance to assure national uniformity on various issues insofar
as appropriate.  Headquarters will also have the responsibility to review
and to concur or nonconcur with the recommended action for each revision.
     The Agency responsibilities are somewhat different in those cases
where plan revisions are necessary to take account of new or revised
national standards.  In this case, OAWP has the primary responsibility
of preparing and publishing in the federal Register (1) the new or
revised national standards and (2) specific guidelines en what actions
States need to take to develop, adopt and submit an approvable plan to
implement the new or revised standard.   In general, all States will be
required to subnit a plan for a new national standard or will be required
to revise their existing SIP's to consider a revised national standard.
After OAWP has published guidelines for the dc-velopmont of approved SIP's,

-------
     the Regional Offices are then responsible to assist States  in the
     development of SIP's etc.
          In situations where the SIP regulations (40 CFR Part 51) are
     modified in such a way as to affect the control  strategy requirements
     (such as the recent action in relation to maintenance of standards
     (40 CFR 51.12, June 18, 1973) and the  pending action in relation  to
     tall  stacks) OAWP and Regional  Office responsibilities are  identical
     to those described for a new or revised standard.
III.  Procedures for Determining Whether a SIP./Control Strategy Meeds  to  Be
     Revised
     A.  Identification of problem air quality control  regions
          It is difficult to develop comprehensive guidance on exactly
     how to detemine whether a control strategy will need to be revised.
     While there may be a few situations where it is  obvious that a plan
     revision is necessary, in general it will be a difficult task to
     determine that a plan is inadequate to attain the  standards prior  to
     the established attainment date.  The problem is to determine whether
     AQCR's are progressing satisfactorily in relation  to the emission  limi-
     tations contained within the SIP.  To this end,  a  Plan Revision  Manage-
     ment  System (PRMS) was developed to track the progress being made  by
     States in implementing their SIP.  PR/MS provides a means for effectively
     combining information contained in SAROAD (air quality) NEDS (source
     emissions), and CDS (enforcement and compliance  information) to  compare
     measured progress against expected progress.
          This system is designed to monitor the progress of actual air
     quality levels, obtained from the quarterly reports, in relation to the
     anticipated air quality reductions which should  occur as a  result  of

-------
                              6
 compliance with approved emission limitations.  If the difference between
 the observed  and projected air quality levels exceed certain specified
 limits, then  the site is "flagged" as a "potential problem."  A number of
 flagging  levels or tolerance limits are incorporated in the system to
 indicate  that the site either has acceptable progress or is having a minor,
 major or  significant problem toward attainment of the NAAQS.  The tolerance
 limits were developed through the application of statistical quality control
 techniques which allow for the many variables associated with measured air
 quality concentrations. (See Figure 1)
    Once  a "potential problem region" is identified, OAQPS will notify
 the appropriate Regional Office.  This will be done on a semiannual  basis.
 The Regional Office will be responsible for investigation and further assess-
 ment of the problem.  The Regional Office should also report their findings
 to OAQPS  indicating the action they have taken or plan to take.
  .  While the PRMS will provide a mechanism to identify "potential problem
 regions"  from an analytical point of view, the Regional  Offices should be
 more intimately aware of the status of Regions within their States.   Thus,
 the Regional Offices may be aware of other AQCR's not currently being
 analyzed  by the PRMS which should be reviewed to determine if the plan is
 adequate  to attain the NAAQS by the specified data for attainment.
    Currently, there are 17 AQCR's contained in the PRMS.  An additional
 50 Regions will  be included in the system by January 1974.  The additional
 50 Regions that were selected for analysis were based on recommendations of
 the Regional Offices as to those AQCR's which should be reviewed to  insure
 that adequate progress is  being made toward attainment of the standards.
By mid-1974, 50 more AQCR's are scheduled to be included in the PRMS.   Thus,
by July 1974,  117 Regions  will  be analyzed.   The Regional Offices should

-------
                        Figure  1
                PLAN REVISION  MANAGEMENT SYSTEM
                      Particulate  Matter
Emissions
(1000 tons/year)       150

                      100

                       50
                       1970   1971    1972    1973    1974   1975   1976   1977
Air quality
(yg/m3)
150

100

 50

  0
                                                       Tolerance limits
                                                             Projected air
                                                                quality
                       1970   1971    1972    1973    1974   1975   1976   1977
                                           Calendar Year

                     "Measured air quality
Step
#1  Calculation of emission reduction (NEDS, Emission  Regulations)
#2  Review of compliance dates (SIP,  CDS,  Emission  Regulations)
#3  Projection of air quality
#4  Establishment of tolerance limits or boundaries
#5  Measured air quality trend (SAROAPN

-------
indicate to OAQPS those AQCR's that they believe should be reviewed to
determine the possible need for plan revisions.
     It is understood that air quality levels throughout an AQCR are
highly variable and that each monitoring site within the region must
have levels at or below the national standards by the specified date
for attainment to be in compliance with the Act.  The PRMS analyzes all
monitoring sites within SAROAD for the particular AQCR in question to
determine if adequate progress is being made.  Thus, the system is capable
of defining the problem on a much smaller scale than the entire AQCR.
While most of the'region may be showing adequate progress, a few sites,
located in areas of maximum concentration, may be deviating from the
desired air quality levels.  Review of these sites will allow the Agency
to take a much closer look at the real problem areas.  Because the R.O.
may only be required to review a very few problem sites, more effort can
be placed upon those areas within an AQCR which appear to-.be having the
most difficulty 'in attaining the standards.  It is believed'at ^his time
that it will  not be necessary in most cases to require a major plan
revision for an entire AQCR.  The revision or additional action can be
tailored to a minimum number of sources to give the maximum amount of
benefit toward attainment of the standards.  Thus, a review to determine
the adequacy of the progress for a region should be done on a site by site
basis.
B.  Evaluation of Data
     The review of problem monitoring sites should include three basic
items.   Is the data valid?  What were the meteorological conditions during
the reporting period?  Is the control strategy for the region adequate to
correct the problem at this site?

-------
                              8
     The validity of the air quality data is  the  major item  in  the
review of potential problem sites.   Monitoring  and  Data Analysis  Division,
OAQPS is preparing several  guidelines  to assist  in the validation of air
quality data.  (See enclosure #3)
     While EPA should generally be  confident  of the validity of the  air
quality data submitted by State and local agencies, it is  also  necessary
to review the validity of specifid  data especially  those data which  indi-
cate the need for plan revision.  The Regional  Office  should refer to the
guidelines mentioned above for the  specific items that must  be  reviewed
to verify the data.  However, basically these steps should include:
     a.  Discussion with the State  or local agency  to  verify their
         confidence in the submitted data.
     b.  Determination that the State or local  agency  laboratory  or
         quality control procedures are adequate.
     c.  Determination that the sampling instrument that was used to
         measure the data was calibrated and  operating properly.
     d.  Review the strip chart or  other record of  the measurement to
         verify the reported values.
     e.  Determine if the sampling  method by  which  the data  were  measured
         is reliable and in accordance  with the specified  reference method
         or equivalent.
     f.  In certain cases, it may be  necessary  to visit the  monitoring site
         to determine its representativeness.   Does it meet  EPA criteria
         for location of ambient monitors?  Are surrounding  structures or
         buildings causing unusual  air  flow patterns near  the sampler?  Is
         the sampler influenced by  emissions  from the  chimney or  incinerator
         of the building on which the sampler is  located,  or is the sampler

-------
         on a building surrounded by a heavily used unpaved parking lot?
         In summary, is the data collected by the site representative of
         air quality levels and should the data collected at the site-  be
         used as a basis for developing a control strategy?
     The last item in data validation is very important.   All  problem
sites should be reviewed in detail. . It is suggested that each problem
site be visited to determine its representativeness and to see what local
sources, if any, may be causing the major impact upon a particular receptor.
     If after a review of the above items it is determined that the air
quality values are valid then a review of the meteorological  conditions
should be conducted.  If the frequency and duration of inversions and
stagnations were unusually high, air quality could be higher than normal.
Unusually warm or cold weather will result in a change in fuel  use which
may increase ambient levels above normal.  Snow or ice storms  may be  assoc-
iated with excessive sanding or salting of streets,  and thus  increase
particulate matter concentrations.   Long periods  of dry weather may also
.increase the parti cul ate matter concentrations.  .
     The review of air quality data should also attempt to identify if
high concentrations were caused by unusual, events, such as local  construc-
tion or demolition activity, fires or perhaps control  equipment malfunction
or shut-down which could temporarily cause abnormally high ambient concen-
trations.   Data collected during abnormal situations should not be used
as a basis for requiring plan revisions.  If data are determined to be
"abnormal" or invalids  or that they represent unusual  circumstances,  such
data should be reported so that the SAROAD data bank users are properly
notified of these conditions.

-------
                               10
     After the air quality data has been validated and the  unusual  meteor-
ological conditions have been investigated,  the Regional  Offices  should
make an attempt to obtain the very latest air quality concentrations  for
the site in question.   Because of the lag in processing the air quality
 data from quarterly reports, the SAROAD system may be as much as two
 to four quarters behind the current air quality levels;  therefore, the
 Regional  Offices are  encouraged to obtain the very latest  data possible
 for the sites in question and submit this data to the PRMS so that an
 updated analysis can  be performed to assure that we have the latest  data
 possible upon which to base the analysis for determining adequate  progress.
 The PRMS system has been developed with the capability to  temporarily
 accept selected data  independent of the SAROAD system so that the  best and
 most up-to-date information is available for the Regional  Office review.
 Attempts should be made by the Regional Offices to see that data from
 those monitoring sites with potential  problems receive the highest priority
 by attempting to have the data from those sites reduced and submitted to
 SAROAD as quickly as  possible.
 C.  Analysis  of  Control  Strategy
    With  the  addition  of the  latest  air quality data,  a comparison of the
 trends  in  air quality  levels  at the  site  in question, with the air quality
 trends  noted  at  other  sites within the  Region  (State,  city or other area
where comparable  results  should exist)  should be made.  If the increase  or
 decrease is significantly different  than at the other sites, it would appear
 that a  localized  problem  exists.
    For the purposes of this guideline, let us assume that the site in
question is out-of-line with other ambient monitors in a region.   In  this

-------
                              11
case, it is recommended that a review of the  emission  data  and  compliance
status of sources within the immediate vicinity  of the site in  question
(say within a 1  to 3 mile radius—particulate matter and  sulfur dioxide
only, CO and oxidant would require much large area)  be made.  Points to
consider include:
    a.  Are some sources presently uncontrolled?   If so,  are  there
        control  regulations  with which these  sources must ultimately
        comply?   If not, do  these sources impact  sufficiently on  the
        site to  warrant a recommendation for  a plan  revision  to require
        further  emission limitations  on these sources?
     b.   If the  sources reviewed in (a)  have  applicable regulations that
        they must adhere to  at some later date,  is the anticipated erris-
        sion reduction  adequate to reduce ambient levels  to below the
        standard?
     c.   Do the  sources reviewed in (a)  have  applicable emission  limita-
         tions they must presently comply with?   Are the  sources  in
         compliance with the regulations?  If so, will  additional emission
         reductions be  needed to provide for  the  attainment of  the national
         standard?  If  the sources are not in compliance  with the emission
         limitation, is the  source on a compliance schedule?  Should EPA/
         State enforcement action be  initiated against the  source?
     d.   Have the sources in the vicinity of  the  site  in  question increased
         significantly?  Is  a plan revision necessary  to  compensate for
         increases in emissions?  What action is  needed in  relation to
         assuring that  the State adequately considers  ambient standards
         prior to their providing approval  to construct new sources?

-------
                              12
     Sometime during the investigation of potential  problems  there  should
be a review of the technique originally utilized for the AQCR to  correlate
the reduction in emissions with those in air quality levels.   Such  an
analysis was suggested in (a) and (b) above.   There  are a number  of approaches
available, each providing various degrees of accuracy which  can provide  a
relationship betv/een emission reductions and resultant ambient air  quality.
The selection of the appropriate method for determining this  relationship
depends upon the Regional Office resources available to address the problem.
Basically, these methods include:
    a.   Simple Rollback or proportional  model  which  assumed  that  as emis-
        sions are reduced or "rolled back" by one percent there is  a
        corresponding one percent reduction in ambient levels.  This is  a
        gross method of estimating the degree of emission reduction
        necessary to meet air quality goals and is by no means absolute.
        Most States used this method to develop their original SIP's
        because it is relatively simple and does provide a gross  estimate
        of the degree of a problem in a Region.   The method  is deficient in-
        that it does not consider meteorology, spatial  distribution of
        sources, nor the height of emission release; three important factors
        which influence ground level  concentrations.  It is  recommended  that
        in determining the need for a plan revision  that a more detailed
        approach be utilized in defining the relationship between emission
        reductions and air quality.
   b.    Modified Rollback procedures  have been recently developed by the
        Monitoring and Data Analysis  Division, OAQPS.   These  procedures
        provide a more sophisticated approach to the relationship of
        emissions to air quality.  This  procedure considers  meteorology,

-------
                              13
       spatial  distribution of sources, and the  height of emission
       release.   The  modified rollback provides a more accurate definition
       of  the  problem but also requires mere rofined omission data arid
       more nranpov/er.   The procedure is applicable to an urban area
       (city center)  problems.
   c.  Diffusion  Modelin? is the preferred predictive tool  available in
       relating .emission  to air quality duta.   A number of diffusion
       mc'-iels  (Air  Quality Display ifod^l, AQDM, and t!,ie Implementation
       Planning Program,  IPP) are available for defining urban situa-
       tions on an  annual basis.  Point source modsIs are also available
       for single source  short-term (1  hr and 24 hr)  situations.   Diffusion
       modeling requires  detailed emission, air quality and meteorological
       data to mathematically simulate the: emission/air quality relation-
       ship for a given region,   Voile there are certain limitations which
       restrict the use of diffusion nodals (lack of data} severe topo-   .. •
       ^ I':;[••:!! C  Vc i' I •:* i. i 'j\\'i ; •.. «..'w . / *  '.::<: ..'.; 1.1 ,'•.> U C.'»-:,';-• jj ;Xi V i--J'-.' >.i:'o IK..}!, i:\i'.\ , •••
       able approach  to predict resuVLir.g ch'ibient levels caused by the
       application of emission  "h'mitatioiis  0,1  emission sources.  Enclosure
       #4 provides a list  of  those  diffusion models which are  readily
       available to the Regional  Office through  the Tirr.e Sharing Option
       (TSO) computer facility.
D.  Reporting of Results
    The Regional Office will  be  notified 30 days  after the semiannual
report is due (February 15, August  15) of  those  potential problems and
should report on the status of their  investigation within 30 days  prior  to
the date due for the next  semiannual  report.   It  should be noted that the
above investigation of  potential  problem sites may require more than just
one semiannual  reporting  period  to  complete the  investigation.

-------
                                   14
         Thus, the results reported to OAQPS for inclusion  into  the  Adminis-
     trators SIP Status Report may include several  different recommended
     actions.  These include:
         1.  Data determined to be invalid—work proceeding to  correct  and
             validate data.
         2.  Unusual meteorological  conditions  existed at the time and  more
             recent data indicated adequate progress.
         3.  No action, minor problem identified and resolved.
         4.  No action, new  projected air quality curve should  be developed
             to better define the trend in estimated air quality.
         5.  No action, pending further study—inconclusive or marginal
             analysis, too early to determine if problem exists.
         6.  More effective  implementation of new source review  procedures
             to restrict growth in certain areas is  needed.
         7.  EPA/State enforcement action is necessary
         8.  Plan revision is  needed.
         Procedures on how to  require a plan revision  for those  cases where
     the need has been identified are described in  Section  IV.

IV.   Procedures for Requi ring  PI an Reyi sions  .
         If a revision to  the  control  strategy  is determined to  be needed, the
     following actions are necessary:
         A.  Plan Revision Documentation
             The Regional  Office should document the reason why  the  plan
         revision is necessary, providing as much detail  as  possible on the
         discovery analysis  performed to determine  the need for  the  revision
         and identify, if  possible,  what source(s)  or  source categories should

-------
                              15
    be considered under the plan revision.  While it is hoped that
   , the approved SIP will be adequate to attain the national standard
    on a region-wide basis, it is highly likely that portions of some
    AQCR's ("subregions") will need further controls to achieve the
    standards.  Therefore, it is proper and necessary to identify those
    sources which may need to be considered when developing the plan
    revision.  This analysis should be discussed with the State and local
    agencies involved.
B.  Notification and Concurrence
       Where the requested revision would significantly affect emission
    control regulations, or the enforcement thereof, the Regional  Offices
    should obtain the concurrence of the Deputy Assistant Administrator
    for Air Quality Planning and Standards and the Deputy Assistant
    Administrator for General Enforcement prior to officially requesting
    a plan revision by the State.  Further, where the requested revision
    should have significant national policy implications or would establish
    a significant precedent, the above Deputy Assistant Administrators'
    concurrence should be sought.  In so far as other revisions are concerned,
    the Regions should simply notify the above Deputy Assistant Administrators
    of plan revision requests that have been made.
C.  Notification of State
         The Regional Offices should confer with the State and/or local
    agencies involved and advise them of the need for a revision.   The
    Regional  Administrator should officially notify the State (Governor)
    that a. revision is necessary*.  The notice should identify the following:
         (1)   Why the plan revision is necessary
*Thc issue of whether this should be done by letter or Federal  Register
notice will  be discussed in a separate memo rand urn.                    -

-------
                     16
(2)   What appears to be necessary to correct  the  deficiency
     i.e., what sources appear to cause the need  for further
     controls
(3)   What other portions of the SIP  must be revised  as  a
     consequence of the control  strategy revision.   These may
     include:
     (i)   Section 51.11 Legal   authority-- especially if
     transportation controls are deemed necessary
     (ii) Section 51.15 Compliance schedules  must be provided
     if new control  regulations  are  adopted.   The negotiated
     schedules  must be submitted at  the time  of submittal of
     new regulations.   However,  if the  regulation is immediately
     effective, then the schedules can  be submitted  as  a plan
     revision itself.
     (iii)  Section 51.17  Air Quality  Surveillance  —  The
     increase of ambient levels  may  indicate  a more  widespread
     problem than anticipated.   More ambient  sampling may be
     needed to  define  the extent of  the. problem and  monitor
     progress.
     (iv)  Section 51.21   Intergovernmental cooperation -- This
     section may need  to be revised  if  the State  delegates new
     responsibility to other State or local agencies to carry out
     portions of the plan.
   (v)   Section 51.20  Resources  -  New control  regulations may
   require additional  resources  for  enforcement purposes.  Such
   information  should  be  reported  with  the plan revision.

-------
                              17
            (vi)   Section  51.10  General  requirements - The control regula-
            tions  submitted  as part of the plan revision may indicate the
            need for a change in the date of attainment of the national
            standard.  Plan  revisions designed to attain the primary
            standard which require more stringenet controls than that
           which  is reasonably available, and which are more restrictive
            than the original SIP may justify the need for an extension  of
            up to  two years  (section 51.30).   One year postponements,
           40 CFR 51.32 (revised June 19, 1973)  may also be utilized.   It
           should also be noted that plans to attain the national secondary
           standard must do so within a "reasonable time."
      (4)  The time period  for submission of the revision to the Agency
            (Section 51.6(b), Revision) states that 'the plan shall be
            revised within 60 days following notification by the Adminis-
           trator, or by such later date prescribed by the Administrator
           after  consultation with the State."  Since a control strategy
           will  need to be developed and a compliance schedule determined
           and then have the regulations subjected to a public hearing
           and be adopted, it appears that four to six months  and perhaps
           longer will  be needed in most cases to revise the control strategy
           portion of the plan.
      (5)  The plan revision must be submitted in accordance with the pro-
           visions of 40 CFR 51.4, Public hearings and 51.6, Revisions.
D.  Plan Submittal
    Once the plan revision is submitted by the State,  the Agency procedures
outlined in the Sansom/Quarles memo of understanding of September 14.  1972,
as revised by OAQPS No.  1.2-005A, of the Guideline Series govern the review
and approval process.   Because of a recent court decision, however,  the

-------
                              18
Agency must now publish, in the Federal Register, the fact that a new
or revised SIP has been subm'tted to the Agency and that the public has
30 days to comment on the new plan.  These procedures will apply also
to all regulatory plan revisions.

-------
                   OUTLINE OF  RESPONSIBILITY
                              Air Quality
                               Data From/
                                States  /
                              Regional
                               Of fi ces
                                                        ther
                                                       AQCR's
                   RO
                Notified
                   of
                 Problem
Adequate
Progress
No Action
Within
Normal
Limits
                                                               iRO Review For i
                                                               [Potential     j
                                                               Problem
                                 Validate
                                   air
                                   uali
aag/   p
                           Data
                          Revised
                                                        Report  to
                                                        OAQPS Results
                                                        for Report to
                                                        Administrator
                                            RO
                                         nvastigate
                                          nd resolve

-------
Enclosure #1

-------
                              Enclosure #1



          Additional  Technical Publications to Assist in Regional  Office


                Investigation of the Need for Plan Revisions




1.  AP 78:  Guide for Air Pollution Episode  Avoidance


2.  AP 98:  Air Quality Surveillance Networks
                                     i

3.  APTD 0736:  Field Operators Guide for Automatic Air Monitoring  Equipment


4.  APTD 1085:  Air Quality Data Handling System Users  Manual


5.  APTD 1347:  Guidelines for Technical  Services of a  State Air  Pollution


                Control Agency


6.  EPA-RA-73-028c:  Guidelines for Development of a Quality Assurance


                     Program - Photochemical Oxidants


7.  EPA-RA-73-028c:  Guidelines for Development of a Quality Assurance


                     Program - Carbon Monoxide

                                      4

8.  EPA-RA-73-028c:  Guidelines for Development of a Quality Assurance


                     Program - Suspended  Particulate Matter

-------
MDAD

  NADB Reports

    a.  NEDS
        SAROAD
           quarterly reports
    b.  Quarterly summary ststisties air quality data
    c.  National Emission Report (Annual)
    d.  Site file directory - air quality monitoring (annual)
    e.  ISO/direct request using standard computer program
MRB

  a.
  b.
Trends Report (Quarterly)
Special analysis reports (quarterly)
  Reporting high measurement regions
DSSE  - (CDS/KAPINS)

  a.  Semiannual questionnaire used to update CDS
  b.  Region by region statistical output - data"summary by city/county/
        region/state, etc. (percent in compliance, etc.)
  c.  Source ID report - Basic Source Data
  d. ' Future schedule summary
  e.  Geographic locations
  f.  Action summary report
  g.  Status summary report
  h.  Source action summary
  j.  Overdue action report
GAD'

  Must be some reporting but '.-liable to identify specific items
SIB
  a.  Guidelines for dcmer ^.i.-j the need for a plan revision
  b.  RTI manual for P.I'iS analysis
  C.  Protocol for submitting new data and results of PRMS to R.O.

-------
Enclosure #2

-------
ENVIRONMENTAL
[PROTECTION               ORDER
AGENCY
               I
1270.5
                                                             October 15, 1973
                 DELEGATIONS OF AUTHORITY - AIR AND WATER PROGRAMS
                   DELEGATION OF AUTHORITY TO REQUEST STATES TO
                         REVISE STATE IMPLEMENTATION FLANS
 1.   PURPOSE.  This Order  delegates to the Regional Administrators  the
 authority to request States  to revise State Implementation Plans under
 Section 110(a)(2)(H)(ii)  of  the Clean Air Act.

 2.   BACKGROUND.   Section  110(a)(2)(H)(ii) of the Clean Air Act provides
 for  the revision of State Implementation Plans  (SIP's)•"whenever the
 Administrator finds on the basis of information available to him that the
 plan is substantially inadequate to achieve the national ambient air
 quality primary or secondary standard which it  implements."  In view of
 the  emphases on utilizing regional offices in supervising the SIP's, a
 delegation of authority to the Regional Administrators uo request  the
 revisions is in order.

 3.   DELEGATION.   The Regional Administrators are delegated authority to
 perform the responsibilities indicated above within their respective
 regions.

 4.   LIMITATIONS.

     a.  Revisions will be requested only when such  revisions are clearly
 necessary.
              •»
     b.  Where the requested  revision would affect emission control
 regulations significantly, or the enforcement thereof, Regional Admin-
 istrators should obtain the  concurrence of the  Assistant Administrator
 for  Air and Water Programs and the Assistant Administrator for Enforce-
 ment and General Counsel.

     c.  Where the requested  revision would have significant national
 policy implications or would establish a significant precedent, the
 concurrence of the aforesaid Assistant Administrators is required.
Dist:  Directives Distribution                                        initiated by: AF

-------
                                                              1270.5
                                                          October 15,  1973
    d.  Insofar as other revisions are concerned, Regional Administrators
should simply notify the two Assistant Administrators of requests made.
    e.  This authority may not be redeles
                                      Russell E.  Train
                                       Administrator

-------
Enclosure #3

-------
                                                                 Enclosure #3

              Guidelines on Ambient Trend Monitoring
              Monitoring and Data Analysis Division

1.  General guidelines for Regional Office monitoring programs
    PURPOSE:  General summary of existing ambient trend monitoring
              guidelines
2.  Guidelines for validation of Air Quality Data
    PURPOSE:  Steps to insure valid data
3.  Guidelines on interpretation of Air Quality Data as it relates  to NAAQS.
    PURPOSE:  Answer questions on how NAAQS and Air Quality is  related
4.  Guidelines for network design and instrument siting
    PURPOSE:  Network design and instrument siting criteria
5.  Guidelines for selection of air monitoring instruments.
    PURPOSE:  Selection of instruments
6.  Guidelines for evaluation of air quality trends
    PURPOSE:  Trend evaluation
7.  Guidelines for the evaluation of air quality data
    PURPOSE:  Evaluation methodology
8.  Guidelines for complex source monitoring
9.  Evaluation of SIP monitoring requirements

-------
Enclosure #4

-------
                                             Enclosure #
CATALOG OF PROGRAMS as of OG/01/73

APRAC - A short-term Urban Diffusion Model that calculates the
        automotive contribution to Carbon Monoxide.  The model
        was developed by Stanford Research Institute (SRI).
        A 120 page manual is available on the model.
HIWA'.Y -
PTMAX -
PTD/S
PTMTP


READT
A model that calculates a pollutant concentration
in the vicinity of a roadway.  The model is
self-documenting.

An interactive program which performs nn analysis of
the maximum, short-term concentration from a point
source as a function of stability and wind speed.

An interactive program which computes short-term
concentrations downwind from a point source at
distances specified by the user.

An interactive program which computes, at multiple
receptors, short term concentrations resulting from
multiple point sources.

-------
GUIDELINE  SERIES
          OAQPS NO.  T.2-01 a
      PROCEDURES FOR SCREENING, VALIDATING



       AND REPORTING AIR QUALITY DATA
  US. ENVIRONMENTAL PROTECTION AGENCY
    Office of Air Quality Planning and Standards





      Research Triangle Park, North Carolina

-------
SUBJECT:
FROM:
TO:
       UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
      Office of Air Quality Planning and Standards
      Research Triangle Park, North Carolina  27711

A Description of the Analytical Techniques   DATE:  g 5 FE13
and Associated SAROAD Method Codes used in
Storing Data in the National Aerometric Data
Bank

Robert E. Neligan, Director ft"' & • ^'£
Monitoring and Data "Analysis Division

Surveillance and Analysis Division Directors
Region I-X
Environmental Protection Agency

    Enclosed is a draft copy of a document relating
SAROAD Method codes with analytical techniques.   This
has" been prepared cooperatively with the Quality  Assurance
and Environmental Monitoring Laboratory of the NERC-RTP.

    The basic purpose of the compilation is to bring
uniformity in reporting data to'the NADB.  There  are
a number of disturbing reports -^that air quality data
are being submitted to the bank' under the wrong code
numbers.  The consequences of ..this, if it is widespread,
are serious.  The Regional Offices must take the  lead
in minimizing this problem.

    It is important to read the Introduction to the
compilation, and especially the last two paragraphs,
because it gives the boundaries within which the  work
was carried out.  If you have comments, corrections, or can
help fill in the few blanks, please send them to
Mr. William Cox  (919/688-8312) by April 15, so that we
can incorporate them into a version for distribution
to State and local agencies through the Regional  Offices.

Enclosure

cc:  L.' Bockh
     B. Steigerwald
     J. Schueneman
     J. Padgett
     D. Goodwin
     D. Shearer
     T. Hauser
     S. Hochheiser
     F. Burmann
     J. Akland
     H. Slater
     J. Hammerle
     G. Morgan
     SAROAD Contacts
EPA Form 1320-6 (Rev. 6-72)

-------
            Gi.iIDQ.iNE SERIES

                OACjPS 110.  1.2-013
 j  PROCEDURES  FOR  SCREENING, VALIDATING  j

      AND  REPORTING AIR  QUALITY  DATA
   U.S.  Environmental  Protection Agency
Office  of Air Quality  Planning & Standards
  Research Triangle Park, North Carolina

-------
PROCEDURES FOR  SORECJKiG,  VALIDATING



      AND RF.r01fn.t-i3 AIR QUALITY DATA
             J a n u a r y 1 9 7 4

-------
                            TABLE OF COIITEIITS
                                                              Page
PREFACE

1.  I INTRODUCTION

2.  CURRENT A;;D Pl.AK.'lEii IV'.TA i'LOH PROCDUi'lLS

    2.1  Current  Dato  Flow System
    2.2  Current  Dei.a  Fid Hi no
    2.3  Cuyrerri;  Data  Vn 1 idation 5'cr-een
    2.4  Current  Flsq^lng  Teciii'kjiiK? for SIP Progress
    2,b  Plcnn^u  t.'ata  Flow System
3.
CURRENT AN!) PLANNED  REGIONAL OFFICE AIR QUALITY
DATA RESPONSIBILITIES

3.1  Current- Areas of  F'esponsiM] Ity
3.2  Future Areas of responsibility
 4

 4
 7
 9
12
14

17
                                                              17
                                                              34
REFERENCES
                                                          36

-------
                           LIST OF FIGURES
FIGURE                                                        Page
1.  Current  Air  Quality Data Flow System                      5
2.  f/.irrerrc  r'irKiging Technique For SIP Progress              13
3   }'•• r.n*.i  *<>•  (juality Data Flew System                     16
4.  ')•::•••.  Vi.-^ i -icf'ticn Flow Chart for Specific  Data  Values    ?6
5.  Ty •••.••.•'!  SO,.  Annual  Pattern                               31
6.  Typical  SO,  Annual  Pattern With Constant Baseline        31
    Drift      *•
1.  Typical  S0?  Annual  Pattern With Abrupt Baseline         31
    Change
8.  Typical  SO,,  Annual  Pattern With Seasonal'Abnormality    31
9.  Influence  of Nearby Source on SO^ Annual Pattern         31

-------
 AIR  QUALITY MONITORING AND  RELATED R'WKTS OF THE  OFFICE

          OF AIR QUALITY PLAI.'h'Ii-G AND STANDARDS*
The national Air Vcnitoz1;'-/.^ 'Si'ocy-on:  A Status F'cpoi-t on Tfc^-h-
in Air  Quality and Etriit;sic,:.^


G U4.d a n c e. S t/u. 
-------
                          PREFACE

    The i'oni tori ng and Data Analysis  Division  of the Office of
Air '••)•."';:.>' /".i-nlng and  Staridards  has  prepared  this report
en-:i~i'Ki i!;Y.'.'.': ••'>'„! res for  Screening,  Validating and  Reporting
Air f i:;5] . ;." io'-:" for use  by  the  Regional  Offices of tivs En-
vi re.; •:,:..(', .Yotecti on Agency.  The  purpose  of the  report is to
provide guidance information  on current data validation tech-
niques that, should' be follov/ed  as  part  of  the  procedure for ill-
putting air quality c! a t a  i n t o t h e  N a t i o n a 1  A e r o ;n e t r i c D a t a E.' a n k .
The Primary audience for  this report  is the  administrative and
management personnel in the Regional  Office  whose need is limited
to a general overview of  the  system  rather then  detailed in-
formation concerning specific elements.  The NEDS/SARQAD contact
personnel  will continue to  receive  specific  detailed information
directly from the National  Air  Data  Branch>  MDAD.  Adherence to
the guidance presented in  the report  will, hopefully, ensure
mutually compatible ambient air quality data for all States and
Regions and should also facilitate  data evaluation  and inter-
pretation.  Further, any  risks  involved in policy decisions concern-
ing National Ambient Air  Quality  Standards should be minimized.
This report is intended to  update  and expand upon the previously
issued Interim Guidance Report  on  "Evaluation  of Suspect Air
Quality Data. "

-------
1.   INTRODUCTION
    The purpose of this Guideline.,  the  third9  a series to be issued
by the Monitoring and Dat? An?'lysis Division  (ilDAD) of the Office of
Air Quality Planning and Sv.oridc;rds, is to provide tha Regional Offices
of EPA with fuidance on data  validation  techniques thai  should
be followed as part of the procedure for inputting r.ir quality data into
the National  Aerornetric  Data Bank."   Information  and  sur-i'l^tionc  zn
presented  for  both  the current and  planned computer system concern ire-
            Data Flow
         .  Data Editing
         ..  Data Verification
         .  Data Correction Procedures
         .  Statistical  Flc.yging Techniques
In conjunction with this Guideline, the MDAD  is also developing sophisticated
data edit, validation and quality  control   programs which should
help smooth  the transition between  current and  planned  Regional
Office air quality  data  responsibilities.
 This  document supercedes a previously issued  interim report
 entitled  "Evaluation  of Suspect  Air Quality Dita"  OAQPS # 1.2-005
 issued  in  August  1973.

 Information presented  in this report, is als:   .'.ended to alert  the
 Regional  Offices of  thei"- incn-as 1 no respor.:.   'litics with respect
 to air  quality data  as  a result  of  the t:U.i. ......  ^pyrLding of  the
 EPA/RTP computer system.

-------
                             -2-
    This report will  serve on an interim basis until more explicit a;:d
detailed guidance is  developed by the Monitoring and Data Analysis.Di-
vision as a result of the expected interaction .with tha Regional  Offices
on air quality data handling techniques and  procedures.  For purposes
of definition  the  following terms are  listed  as they are used
in this report:
Data Screen  (Data  Check) (Screening)
    The comparing  of a piece of data  to  a  specified entity.
    The comparison may be  manual , (visual) or  automatic  (coin-
  .  puterized).   The entity maybe a code  or  location (edit)
    or a  value  (validation).
          f*
Data Edit'  (Edit Check) (Editor program)
    The comparing  of data  and its unique  identification to a
    set of  specifications  concerning  format.,  alphabetic and
    numeric requirements and coding requirements, etc., either
    manually or  automatically.
                «
Data Validation   (Validation Screen)
    The comparing  of data  values to a  set  of  predetermined
    criteria concerning minimum and maximum  l^vitts, deviation
    from  average values, percent change,  overti.,3 etc., either
    manually or  automatically.
Data Flag  (Flagging)
    Calling attention to and uniquely  identifying data for
    futher  action, the flagging iv;aybe  done r.<:>.nua 11 y or automatically
    •:.'  fiit.'ur  ;MI ed.i';, va~> ic^ti )n ;/  •; i. ,'i - .•  •;.• rug.'an;.  The action
    nr.y consist  of deletion, veri f icut iion , change etc.

-------
Data Anomaly  (Anomi>:. data i.'v.ybo
    identified  (flogncd) oiuior1  i-ianuiu "!y or autoiiiivri cf-'My l.;.y
    edit chsci's ;' vo'i i dr. fi on scri.r^rincj or ;..py other  flaoyin*;
    taciini (;<.;;:'.,
Data Verification
    The tots'!  process  involved  in  daterfiii rri iig v;htti!r::r ciai;;;
    is correct  or'not.  This process benins with the  1 abort i jfi as
    quality control practices  and  &ncoi;;poses the above iiienti cinc-d
    edit,  validation,  flaaging  processes to identify  potentially
    invalid data  and the steps  necessary to resolve the question
    of the data's validity.
   c Sin co  tiie  di sti net. i en between  Data Edit and  Data  V?. 1 idn.ti an
    is soinewhat arbitrary, we  have  chosen in this  M?-.:•>i;,?. 1 to pre-
    sent them  as  distinct entities:  edit connotatijuj forsaat
    and coding  characteristics  while validation  cennotofino
    actual data values.  It must be kept in mind,  however, that
    the two processes  may or may not be performed  in  the same
    step either manually or automatically.

-------
                                -4-
2.   CU:-'.RiIi-!T AND PLANNED DATA R.G1.-;  PROCEDURES
    This;  Section presents current  and plriiried flov: procedures for pro-
cessing air quality data.  Tht:3£ procedure Include data  editing .-creon-
ing and flagging l^chniques for SIP  progress evaluation.
    2.1   Currant Data Flow System
             The general fluv: of  eir quality data i'ro;r. the SUt::s
         through the; Regional  Offices to the Hatior.al  Aerornetric 0-itci
         Bank is presented in  Figure 1.  The steps in  the system arc
         as follows:
             a.  The State agency submits  air quality data to ths
         appropriate E'PA Regional  Office as part of the State Inip'lsinon-
         tstion Plan reporting procedures.  These reports v/hich are for-
         warded  on a quarterly basis contain the air  quality dsta and nev/
         site descriptions for the State's air monitoring stations.  The
         data may be sent in more  frequently than quarterly if cuj.nred,
         but must be submitted to  the Regional Office  in  SAROAD format
         on either coding forms, punched cards, or magnetic tape.  Data
         for all operational stations as described in  the SIP's, begin-
         ning with that used in plan preparation, must be submitted.  It
         is strongly encouraged  that  all reliable  data obtained
        by the State v/hich satisfies  the criteria established  for
        monitoring  network adequacy  be  submitted.
              b.    The NEDS/SAROAD  contact in  the  Regional  Office
        arranges  for keypunching  of  forms  if necessary and then
        transmits  the data to the  WDAD's National Air '_.-.t.o P.ronch

-------
                             AIR QUALITY DATA

                             '  FKOM'ST/Vlf-S
                                 REGIONAL OFFICE
      o
      LuJ
      a:
      C£
      o
      o
                            NATIONAL AIR DATA

                            •      BRANCH
      o




    NADB TR1TS TO           ;

:    CORRECT           "!	-.       DATA EDIT
j

i                      .      !



              DATA
              FAILED
            		:v    VALIDATION

                            j      SCREEN


                                DATA    ;  PASSED

i                      '      .
;   FLAGGING TECHNIQUE! :         DATA ENTERED

J      PROGRESS        :•: 	   Ih NATIONAL
i      '                      'AEROHUTRTC DATA    -
   FIGURE 1.   CURRENT AIR QUAL1V7  .OATA  FLOW  SYSTEM

-------
                     -6-
    c.   Air Quality data  submitted  f.o the National Air
Data Branch should have  the  fpl 1 o-vi \\<\ criarac lev] sties :
        i.  Data must  be  coded  in  SA!::/Aj fon:;ai:.
       ii.  Data value:':  less  than  the n.oni tori !';•>;; minimum
            detectable  sensitivity  should be reported «•>
            a "zero" value.   A  value equal  to half the
            minimum detectable  sensitivity  v/i'il be sub-
            stituted when  calculating summary statistics
            for con t i n u o u s  d a t a.
      iii.  It is desirable  that  the data be representativo
            of a consecutive  three-month period for which
            at least 75  percent  of  the data values are
            valid.  A  nondetectabl <•:•  measurement, i.e., a
            value belov/  the  minimum  detectable sensitivity
            (Limits of  Detection),  is considered valid.
            Summary statistics  are  not automatically  com-
            puted by the  M F) A D i f . g r e a t •:. r t h a n 5 0 percent.
            of the v a 1 i d  r,i e a s u r e m e n i s ; • r e b e 1 o w t he in i n 'i i n i,1 n;
            detectable  concentration.  'iov/ever, if the
            criteria are  not  met,  the rif. In  should still
            be submitted  particularly :   .'ivaluation  of
            maxiniuni value  standards,       ionconti nuous
            24-hour data  there  shoul;' ,.:;;• at least five data
            points in  tho  q;; ^ y-•:, e r,  ;:1 th at  least two  months

-------
                         -7-
                 be.ing v-e. ported and a miniHJui'.)  of  two  date  v;; "i uts
                 in the. IDonth with the  least number of  data
                 value reported.
            iv.  Data must represent an  interval  of one-hour1
                 or greater -- shorter  interval data  must  he
                 averaged over an hour.
             v.  Data must be representative of the condition.;  of
                 the site for.the period  of time  specified;
                 moc! i f i e a t ion of the en v i ronma n tin ivh i c h  thc
                 site is located ID List be  reported  to  the MDA.O
                 by the State and/or the  Regional  Office.
         cl.  Data are processed in the  National Aerometric Data
     Bank and the error messages generated are  provided to botfi
     the National Air Data Branch and the NEDS/SAROAD conte'ct,
         e.  Investigation and corroction of potential  errors
     is accomplished by the Regional Office in  conjunction with
     the States using procedures described later  in this docuifient
     Corrected data are submitted to the  National  Air Data Bank
     for file updating.
2.2  Current Data Editing
         The incoming air quality data,  in SAROAD format,  is
     subjected to various checks by the  National  Aeronictric  Data
     Bank's computer programs.  The data  will  fail  to pass the
     edit prog rains for the following reasons:
         a.  No existing site description.  Before any data  are
     accepted^ the s i i •" v i 1 e m u :•.• v c o i; t a i n the  inform (• t' o c  f r o i n

-------
                    -8-
the site identification form.  The program checks  the
12 digit sice code on the date, find if no corresponding
record is available in the site file, the dr.ta  arc  re-
jected.  Therefore, tiv.? site  i dent if ication must br.
entered before data fro;ii a new site can be accepted.
    b.  No existing description of sampling or  analytical
method.  The program outomatical ly rejects data if a
record of the method used to  generate the data  is  not
available.
    c.  No );)a tch on ihe po 11 utan t-me thoc!-• i nterva 1 -un i t
combinations for these codes.  Anything else will  re-
jected.  For example, there is no monthly interval
suspended particulate data using a hi-vol sampler  and
gra v i met r i c a n a lysis.
    d.  Any data field other  than "Agency" or "Interval"
which has been coded in alphabetic rather than  numeric
characters.
    e.  Data on the wrong form,: such 3;; drying  to  send  24-
hour data on the hourly data  form.
    f.  Incorrect start, hour.  For hour"'; date,  the start
hour must be 00 or 12.  For two-hour de'••• Virough  twelve-
hour data legitimate valua.? are givon vr   r.ie 36 of the
SAROAD Users Manual.  For twenty four I.our or greater
data, legitimate values are from 00 to 23.  Anything  else
i r. ?. i.i t orr ;i t i c a T! y re ;j s c i: 3d,

-------
                          -9-
         g.  Date  incorrect.   Data  are checked for m??ningful
     clays.  E x u MI pies  of  wean i n glen s d a y s are F e b r u a r y 3 0 or
     April 31.  Some  data  line!  to b'j rejected be causa the year
     was designated  as  1977.   Eventual 1y> the capability to
     flag data which  ha •••'«:?  a  dirte other than the current
     quarter w ill  be  ad c! e d ,   H o iv e v o r , this c c. p a b i 1 i t y w i 11
     be delayed until  all  back  date are incorporated in the
     system.
         h.  Imbedded  non-numeric characters in values.  There
     is a four digit  field  for  the  value.  For example!., values
     which have blanks  between  digits, such as tv;o zeros, a
     blank, and an eight  instead of three zeros and sn eight
     would be rejected.
         i.  Decimal  pi a c e  i n d i c a t o r n o t be t w e e n 0 a n. d 5 .  T! i ?
     data which are  currently  being generated all have fewer
     than five decimal  places.
2.3  Current Data  Validation  Screen
         Currently,  the  manual  procedure us ad by the MDAD in
     the indenti fi cation  of  potentially ano-r.r-.'lous data values
     depends, to a large  extent, on chance d jcovery by someone
     scanning a computer  printout of eithc-v   \\" data or summary
     statistics.   Automatic  procedures hav^   •• yet. been de-
     veloped for computer  r.opric;-. [•.ions .
         This process  of  d e ••': ft c fI r, u  -nrist. i vnao 1 o data volues
     'Mill h7: suppU.r :.c.d  i"/;c:,"  i,  .  •••• .•   •• • — •; i '•. transferred
     to the UnivoC computer  i ?•  \.irc'. <-r 1':'/'!•.  Potentially

-------
                   -10-
anoiiia'l ous  values  v/ill  be <;b.iecv.ivi.:'ly  idonti Tied as a step
in the addition  of all  new date?  to  the  file.   Both para-
metric find  non-p-:':rc:nistru; tests  cc'.fld  he  applied to •;;,•:
incoming data  aiui a li.sv.iuj] printed of  all  values tiia';
meet crii or  another cf  the test  cri t::-rio.  for  flaciginn.
Examples of  such  tests  aro rjivt-n  balov/.
N o u - p ?. r ajii s.t r i_c_ _t fi sts
       Values  that are  l.:vrc  suggesting soini
       abrupt  change in baseline  or a  transient inter-
       ference.
       Chebyschev type  tests, wherein  values  that are  more
       than  four  standard deviations  i-way from the me.an
       are  to  be  considered suspect.
Parametric  tests
    Efficient  use of these tests  depcrsc.;;  on  knowledge  of
the frequency  distribution of the  quci •  •'.<  being measured.
Example of  such  tests ar? presented i)e.:i.v/.   (The sensitivity
of these tests can be dc:';..?vrained  ynr-'iytically from the fre-
quency di s t r i b uti on),

-------
       Detection  of  any  values  thai: are larrer by so>;.c factor
       (e.g.,  1,5)  than  the  expected value of the assigned 99th
       pyre en tile  of tivj  di stri ijuti en under q'jestio1!.
       The f'incnno  that  ;:he  avurari of !' ;> H successive valuo;:.
                          r       ...,,'      '•*
       fo. I hi cutsicie t:.o  i.ji  •!•• .:uv;   i'tfii'ifcs wrier;: n ?. H o a1" are
                               /K"
       the riiasii  and  the  variancti of the distribution under cjuo.st.ioii.
Note:  The difference  between the  non-para^tric test and the  usva-
wetric test  is  that  in  the  former's the sssicined perccnti la •;;;  est'i-
jnnted from the  data,  whereas in  the letter it is theoretically  ob-
t a i n e. d .
    V a 1 i ci a t i o n  of  the  p o 11 LI t a n t  m e o ? LI r e m e n t s i n v o 1 v t:':, tec h ;i i c o. 'i
jurionjent  about  whet  constitutes  questionable data,, and is ex-
pected to  be applied systematically in the form of a set of  cri-
teria defining,  for  each  pollutant, what constitutes an unusual
      \
or anomalous value  or  art  abnormal  fluctuation.  Excursions out-
side of expected  bounds  should  be  flagged or tabulated but cannot
be automatically  rejected  or deleted.  They must be  brought  to
the attention  of  the contributing  agency for either  verification
or correction.
    Definitions  of  what  constitute unusual values or abnormal
fluctuations are  required  for each pollutant.  These criteria
should be  defined  by people  familiar with the characteristic be-
havior of  the  pollutants  and the instruments used to measure them.
Realistically,  these c r i t e r i a f o r  i d e n t i f y i n o quo:. t i o n a b 1 e v a 1 u o s

-------
     should be cp^n  to  rsvi/ion.   Or.c." developed, the:;. c c ;•• •; t :> r i a  (:,•.:.
     be readily  incorporated  as  a standard element in the  data  brink's
     editing and /or  v^ilidotlon  procedure::.
         7 he fo'i 1 ov; i !u;  list  i '! 1 ifi.tratc'3 Hie !:.y;..-;:.;i of cross  houf'iy
     value check? i'DAi)  is  cons iderii'Hj :
                          CO                         100 ppin
                          S02                          2 pr-ii
                  Ozone  (Total  Oxidant)               .7 ppm
                  T o t a 1  My d r o carbons                  10 p p in
              N o n - r^ •::! t h a n e  h y d r o c a r b o n s               Ji p p \'\\
                          N02                          2 ppra
                          NO                           3 ppni
                          NOV                          5 ppni
                            x.
       Total Suspended  Particul ate*               2000 g/m1*
2.4  Current Flagging  Techniques  for SIP Progress
         An implementation plan  reviev/ management system  to flag
     significant  departures  from  expected air quality, based  on emission
     projections  arid  SIP  regulations, has been 'developed  by the OAQPS.
     A flow chart for  this system, which incorporates parametric  and  nori-
     paranietric  techniques similar to those described in  Section  2,3  is
     presented in Figure  2.
         The system  projects  a  path from an air Monitoring  station's  cur-
     rent air quality  data levels to a point in time when  air quality
     standards are  to  be  achieved.  If at any time the actual  air quality
     data are significantly  different from that projected  by the  paths,
     that station is  flagged  as-  a ooten ::i '?. 1 problem.  This  to . iiTime  c-:n
           :i I

-------
                    i; AT 10HAL
                   AEROMETRIC
                     !:LAQGING  .
                •  TtOiiNIQUE FOR ' •
                       SIP
             l!0       ' PROGRESS'^, FLAG
    	  FLAG

£? ™0$?£SS-.          •            ADDITIONAL
I ISFAC !-./,-;. ,-..                  --DATA VALIDITY
           ;                          CHECK
NO ACTION
REQUIRED                               j
                     DATA      ,     QUERY TO
                     REVISION  "   REGIONAL OFFICF
          r,n         REAPPLY           DATA
          	 %  FLAGGING          VALID  '
          FLAG     X  TECK
                                        \

                                ", AQCR PROGRESS
                       FL/i\G 	.,' MOT SATISFACTORY
                                :  ALERT CONTROL     ••—	--JALERT REGIONAL
                                ;PROGRA?1 DEVELOPMENT       i-  .OFFICES.,'
                                  DIVISION, OAQPS          	 • -  -  '
                                                    	  'REEVALUATh SI;J
        FIGURE  2.   CERENT FLAGGING -r;...i.fl T QUE  FOR SIP PROGRESS

-------
                                    -14-.
     a1i>cr  be  used to identify  thy KG AQCR's  v.'hoso air quality  data v.'.-ul
     suqgost  a  h inner Priority Classification  than they are current'i.y
     as si ijiied .
c.. v  P1 a :i ned  0ata F i ow Sy s ton
           As  previous'!,'/ p;eii i ';-:'-C'c! ;,  it  ! ;•,  oxp •;:•<:•: •..' flic:;,  i !•-.:>  !>ai •:.:,,.- '
     Offices  v.'i i 1  ;..:':•;.. iiii-i: >;:•'}•(:  \"Q 5 p o i'i •'• ' :Vi 1 'i ty  v/'il.i'i respect  to  tiif:  v ?, i 1 ci :
     tion  of  air  quality data,   This vri'i'i  bo  sccowpl i ;;h'.':u  !;y  t!;.;1i' ta Ir
     a central  role in the  screening oi  sir C|i-,-''! i ty clirlM before it if;
     inputted  into the .National  Aeroinetric  Data Bank.  The  screening
     v.'i 11  involve  not only  editing the codinn for in at but also  the
     validation  of the measurements .  Figure  3  presents the  planned
     data  flow  system.
         During  the transition  period, of  shiftKiu in ore rv.-^ponsi hi 1 \ v.y
     to the Regional Offices,  it is anticipated }  at least  initially,
     that  the  MDAD v/ill do  minimal re veri fi cation of the data,   A'l?o,
     tlie flagging  technique  for  nieasuriii[:  SIP progress '-/I'll  still be
     employed  and  the National  Air Data  Branch  will assume  the  ulti-
     mate  responsibility of  entering the  "correct" SAROAD  data  into
     the National  Aerometric  Data Bank.

-------
                        -1 5 -
inputted  itito the National AerofnetrJc  Data  Dank.   The screening
Y.r!ri  invf.-lvo  not only oditincj the. coding  format but nUo the
v<:'; ;,.  . .on  of the measurements.  Pigure 3 presents the planned
•. \. '•':•.  • ,.>,'/ systtiiii.
      l-i-i-lng tiie transition period of shifting  hicre rnspo/uribil ity
1.0  the Regional  Offices, it n c.niicipatod,  at least initially,
that  the  MDAD will  do minimal ('^verification of tho data.  Also,
tii2 flagging  technique for nieasurina SIP  progress will still te
employed  and  the; Matior.a'I Air D>.tr< Brtnch will  assume tho ulti-
mate  responsibility of entering the "correct"  SAROAD data into
the Nations!  Aerowetrie Data Bank.

-------
           AIR QUALITY  DATA
             FROM STATES
£
                  EPA
           REGIONAL  OFFICE
I—
cc
o
                COMPUTE
                                            GlONAL OFFICE
                                               EDI1
                                                                   r_;
                                                                   UJ
                                                                   o
          REGIOFIAL OFFICE
          VALIDATION SCREKN
                               r .'i D '", ir r T rn: n T 0 f ' A !   n n I -" T r ',' T ''' T '•'
                                •••^-••- ' . .M_UI v.i!..,\L  u, ,j..i. i,a ...
                                          TPTT'Q TH  f r^1 n ITT
                                          IK1Li) TU  u-^--cl
         DATA
                     ••• PASSED
           NATIONAL AIR  DATA
                BRANCH
            DATA F.HTER!fD
          FLAGGING TECh'filQ'JES
            IN NATIONAL
           AEROMETRIC  BANK
FLAGGED    FLAGGING TECHNIQUES
               FOR SIP
";Tr;i'»F  3.   PLAfiNED AIR  QUALITY  L-.'-.TA  r:.0:' 'IVr.TE''

-------
                                 -17-
•3.   CURRENT MD PLANiitD Rfc-GlG^M. OFF ICE M\{ QUALITY  DMA Pr'-SPO^iHiLlTItS   '
     Th'r. S'..-c'. ..",'( preheats rGcn;'.-nendni:ions and  suggestions as to those
 iv.-.    ••':.. .:.•-     • i.:;i;:-.s  v'hich IT: R'';;u>i-.:''; OHi:.;.!;.  ciu.  ua^loy l.o valid;-,e
 n? :ii.';'' - G '..,..).  The  1-iC-ni Coring anc! Data Andi'lysis  Division re^iri >:<':::.
..tlii.1  •;(.":•   ;.' tr\o -r.re.as  of responsibility are beyond  tha cs.ptibility of Lome
 of  ti:£ Kou;.-.,ril Offices ut thU ti;y.a.  In the^a  c;;ses,  the; KDAl' will j.n-o--
V'tcle technical end other -issislc.r,cc on an as ne.nclcKl  basis In order th-rc
 the current and planned data flow system operate in  the rr,ost efficient
 and effective, manner possible.
     3.1   Current Areas  of Responsibility
               At this tiir.?,  there arc various tasks  which the Regional
          Offices can perform in the validation of  air quality data,   T'nsne
          include the following:
               A.   Preliminary Data Editing
                   The Regional  Office can make a visual  screening of the
          SAROAD sheets  before forwarding the data  to MDAD.   Ensuring that
          the site identification and descriptions, pollutant, sampling and
          analytical method,  interval, units and  decimal  point locations are
          properly filled  in  on  both the 24-hour  and  hourly SAROAD coding
          form will  greatly reduce the edit and resulting correspondence
          between  MDAD and  the Regional  Offices.  If  a particular agency
          shows a  history of  carelessness in correctly filling out their
          SAROAD sheets,  the  Regional  Office may v;ant to check these sheets
          for their "correctness"  as d" :.o" ssed in Section 2 rather than just

-------
                    -18-.
for their ccinpletensss .
     If the data  submitted t.o the Regional Office  frcir
the States are in  the  foy;:! of punched cards ,  the  iliv., i oncil
Office; can visually  inspect the batch to make sure  that
p e)-1 i rent col i:; ;i n s  are  pun c h e c! and c. 1 i g n e d c: o r r e c 1.1 y .  Th a
Regional Office  in ay  iitiri  it closiv ? b'le to r.ct nelly  |3r-ir, t.
out or list the  data  from  selected agencies befor:.  for-
warding the cards  to  MDAD.  If the: data ore sent  on  mag-
netic tape, thnrs  is  little the Regional Office can  c!o>
at present, but  forward  it on.
     B.  Interrogate  Data  Ban!', D?. I: a Requests and  Man'jal
         Excmi ii'-it i on
         The  flDAD  has  soir-c existing SAROAD outputs  which-"
the Regional  Office  may  find helpful in evaluating  their
air quality data.   The  Regional Office can request  out-
put from the  data  bank  and get quarterly and  yearly  fre-
quency distribution  lists  for each sr.inpling station.  The
output includes  the  site  description ;;1: the top of each
page and a frequency  distribution for each pollutant, year
or quarter-year.   The  number of obscr\iLionss minimum,
maximum, and  the  percentile values a :\.  M.itc/d for  each
pol 1 utant-quarter-year.   The ari tiit.'Gi,    Man, geometric
mean, and geometric  standard dcv i t.:. ;,,,; , .-.- yi/en  only for
those pollutant-quarter-years which i,:-et National  Aerometric
Data Bank criteria.
     The f rcqu';!i::^  :.-; •;, '•:;'•' !,•  .....  .  •;,• ai i .'ib i e on  a  na-
tional, EPA regional  and  s-trie bessis.  Other  options  in-

-------
                    -.19-
c'lude the ability  to  request  the distribution for I'uiitod
numbers of pollutants, years  or quarters.
          These  and other  outputs and remote h<;,fch .and
interactive access  methods  arc!  more fully defined arid a'is-
                                           o
cussed in the SARG',D  Terminal  User:* Manual', ord the r.ucii oridl
Office f!t"nS/SARO/'.i'  contact  should he: confa-jt."-.' for addi-
tional information,
          The Regional Office  will, in the futuriij bo a bit
to rnskc comparisons bat'./ecn ivcrsured air quality data snd
that v,'hi ch they ,, and/or  111e ? rato and local ao,-.• nc. i Gs }
intuitively feel is reasonable  for that geographical arec>
s t a t i o n a n d p o 11 u t a; 11..
      C.  Check  Anomalous  Dat;;
          Anomalous or questionable data values may arise;
from the data flow  system  as  a  result of the following pro-
cedures:  edit  checks, validation screen and the application
of the flagging  technique.   The Recional Office has the re-
sponsibility of  either accepting, reacting or modifying
the data value  or  average  in 'questio;,.   In this regard, the
Regional Office  has the  option  of rec;,.:luting that the origi-
nating agency determine  the validity c.  the data or provide
certain information and  doc ur,,:_ nttir. i o.-.     .hat they may make
the final determination.
          The procedure  ussd  to check out any specific data
value prior to  the  init':atioi:  of ?;,; .-.n.Mtial.y request to NAD8

-------
could  depend on:   the Reyioiial  Office1';1;  assesonorit of  t!.-~
C r I 0 "i!'--:i ; 'i !'• / ;•'. v'-v;--;  'i;: ''.;:.'••  '•,"  ;''' .  : ' '   ', \ i "i '•',y  . " • ' i I y   '. •
trol  profjvd!:], anc!  previous  u:-rf onnanco,   iiDAD suncast.s
that  ih.e  fol lov.'i hn  r-eque :•<•;.(.:  of  steps lc-  follow?.:!  in  or-Jar
to ci'iec !:  out •'./; ;••:'] o:.:s il'-ta  v.-'i'ic::,  oi-  ro :,posi l-r: :.\ or^jri,
Iri al'i  •;;••• i. •'.;•;, 11  si:c:!'id !.:•;'  r r.- c-cji, ~i:: cci  tlut  any A L; :• ft c y
which  alters, m^iii pu'i otes  or  transcribes  a  date. Volue  "in
any  way  Is potentially ccinpb'ic-  of i ntrof.'icri nc. en  error.
K;her)  a  data value  "is  •; Jf'::;;i i i cd (s  bc-'iricj  quest') •:••.-:'; ;'l u , "tiio
responsible Ag^R-y  ;nust dotcri;n;ic v/iset:•:(?)• or not  the d'.l:.
value  rnaintai ned  its  integrity  thi cugliout the A'j;.' ncy' s
data  a c q in s i t i o n  aiv.t  process 11,9 syste:.:.
          1 iiO c'-rrta  ohoj'lc! '..>:  trficeri  tin  i-^cih  '•..!:: ^'\?>\'.;'j
systoiy,  tha R t:: y i o r-;• 1  Offices..  Str;l'.e Ao,.-. f:cy  ctrrJ/or  loc?.'!
AfjCTivy  tu  its cvici'inal record'! ng f v.!het!v,-i% It bo a  value
from  a  c c iri p u t e r  r e a d o u t, paper  tape p r i n t e r , s t r i p c h a r i:,
or a  report from  the  chemist  in the laboratory.   The types
of errors  usually  found in  the  internal  check are:   typing,
key  punching, tabulating and  transposition,  mathematical  .
(such  as  addition,  multiplication and  transcribing).
Further  discussion  of these  errors  and  methods to  reduce
their  frequency  may  be found  in already  published  guide-
line  docurr.ents.  '^'5
          If no  errors have  been identified  in the  internal
check,  at  all agency  levels,  the  verification and  evaluation
process  should  "ontiuue '.own  two  similar  but s^.pftr.it.r-!  paths.

-------
':.'lnc!i path  is  cho;:nn  dop:;>';ds on v/hother the data  in
question is a  single  vai:..,  or a composite ?.ivov;.f;e.
         i..  Verifying  and  flvalua !.:irio Specific  Air
             0 je'l i ty  Dal.;~  Vi;'i ucs
             Instrument C: 1 i l:ri. l:i on ., Spoci fie; t.i on;;  SM<;
             Ope r <•;. t i o n s
             The  operation  r.nd ce'l ibration of  continiious
             instruments is  of the utmost importance; in
             the  p r o d u c t. i o i i  of v a 1 i d a i r q u a 1 i i. y  d <\ t a .   T h e
             instrument en lib rat ion should be  reviev/ori  for
             the  ti::ie period in question, l>oth  before (rind
             after  the  suspect data point.  It  should bo  rio-
             ter mined if the instrument we.s operating yrithin
             pre-deternri:•;!••'.!  porforiiiance specifications  i'ltch
             as  drift,  o p & r a t i n g t e m p e r a t u r e  f 1 u c t u a t i o 11 s >
             unattended operational periods,  etc.   Those
             performance specifications for automatic monitor
             are  defined and.published in the  Federal
             Register  and  summarized in various  guideline
             documents. ':   These specifications  are likely.,
             however, to be  superceded by those published in
             the  October 12, 1973 issue of the  Federal
             Register on proposed Equivalency  Regulations.
             Guidelines on  air quality control  practices  and
             error  traci'---  techniques are als-:  av::il cb'i s  ."*

-------
      - 2»'' -•

Before and After Readings
I f t h e i 11 * t r i! ni e n t g o ri e r a t i n y t h e cl a t s w a s
found to be "in control," the values  im-
mo d i a i; e 1 y f; o f o r e a n d ;-. f t e r should b G  c! e -
tcrminod .  Campari sons between the pc-'rcent
a n d / o r g r o s s d e v i a t i o n z co u'! d be 1,1 a d o .
1 d e a 11 y, i h i s  c! i f f c r o n c e  i n c o n c s ri t r s i: i o n
should bo determined through a statistical
analysis of historical data.  For example»
it may be determined that a difference of
0.05 pprn in SO-, concentration for successive
        o      t_
h o u r 1 y a v e r ages o c c u r s v e r y r a r r; 1 y (less  t h a M
one percent of the time).  The criteria for.."
what constitutes an excessive change  may.  also
be linked to the time of  day.  For example,
an hourly change of CO of .10 ppiri between  6 AM
and 7 AM may be common but would be suspect
if it occurred between 2  AH and 3 A?!."1'5
Other Instruments at the  Same Location
Observing the behavior of other instruments
at the same location would give the evaluator
a qualitative insight, into the possible  reasons
for the anomalous reading.  If all of the  in-
struments showed a general increase,  meteorolog-
ical factors' might be considered while a  drarr:s~.'

-------
      -23-
deviation over the same short period of time
may indicate an electrical problem or an sir
concli tiom'nf! malfunction.  On the other hand,
if t!i2 other instruments behaved normally, a
temporary inC 1 u<:•:nee of ?. si11y 1 e pc 11 utant or
single pollutant source may be suspected.
Similar Instruments at Adjacent Locations
Comparing the behavior of other instruments
in the vicinity which monitors the same
pollutant could further elucidate the
situation.  For example, if the adjacent in-
struments (upwind and downwind) exhibited
the same general trend, an area problem in
which the maximum effect was over the station
of interest, would be indicated.  However, if
the adjacent stations seemed to peak either
before or after the time the suspect value..
was recorded, the station may have been under
the influence of plume fumigation which wandered
according to wind direction influences.  Micro-
meteorological influences should -not be over--.
looked either.  The station may be under the
influence of subsidence effects from the urban
                                            7 P
heat island or upslope-downslope influences.  ''J
Meteoro'! o'j .'i i- i ,'onditions
No attempt  .*, explain an anomalous air quality

-------
      -24-
data point would be complete, without .-. con-
sideration of the meteorological conditions
present at the tiinn of the reading.  A passing
front end strong inversion, extended cnlii.s or
strong winds are conditions which have a grant.
impact on air quality. '   Influences of pre-
cipitation, temperature and season co'j'id be
included to interpret the reasonableness of the
d a t a a s we 11.
Time-Series Check
Investigating a time series plot of tho data
might reveal a repetitious pattern durii.g
similar time periods.  An extreme excursion
might thus be explained.  For example, the
instrument may be extremely temperature
sensitive and may be under the  influence of the
sun shining between buildings from 2 PM to 4 PM
each afternoon.  Similarly, for example, every
Thursday may be delivery day for an adjacent
supermarket where the delivery  trucks spent
the bulk of the day idling in the vicinity
of the sampler probe.
Physical Site Location
From time-to-time local air quality influences
may change find adversely affect a vivc-n air
monitoring sU.ti or,' s representativeness.  Ex-
amples of this might be an adjacent apartment

-------
               -25-                                    •

         house or supermarket changing from garbage
         haul-away to an incinerator.  Urhan renewal  •
         may also render'the location temporarily
         unrepresentative.   It may be beneficial for   ••"...
         each  Agency or Regional Office to maintain
         a map and photograph of each site showing in-
         fluencing site characteristics.  These could
         be updated on a periodic basis.  The site
         location, sampling probe material and con-
         figuration should also be within the bounds
         of those specified in published guidelines.
         Figure 4 presents a stepwise review and guide
         to the verification of specific data values.
         It should provide the Regional Offices -v/ith(  .
         an overall picture of the suggested processing
         of State and local air quality data.
ii.   Verifying and Evaluating Annual Air Quality Averages
         Summary Statistics                           •.,.
         If no calculation or recording errors have been
         found, those summary statistics which describe
         the average should be checked.  These may  in-.
         elude both geometric and arithmetic means,
         standard deviations, and the frequency dis-
         tribution in percent!les.   Both the standard
         deviation? ;(••:. t.1.3 magnitude of the difference
         between thi '.'..'Oiof.tric and the arithmetic means

-------
                         -26-
                              Tmoinalous D
                                  Dal: a
                              Identified
                                                  National Aero-  \
                                                  matic Data Bank /'
                 Error
                 Found
                Internal
                 Error

                 Corrected
                                     Error  not
                                     found
                                Contact
                                Regional
                                Office
 Reject
  data
Error
found
    Regional
     Office
    Internal
     Ch-cl:   .
         Error  not
         found.
Error
Corrected
                            Contact  State
                            and/or Local
                            Agency
Reject •
j
.data x .--•"<»••" -
Error
" Found
' State and
•-' 	 Local
;. Internal
Check
Error
Corrected
Reject
 data
Error
Found
  Instrument
- Calibration
 : Operation
 Specilieations
Error
Corrected
FIGURE 4.  DATA VERIFICATION FLO1?-; CHART FOR SPECIFIC
           DATA VALUES

-------
                   ._-..,_-.   .-.- ,-—,..•—.  .  -  J^ L\ (  _._ ^ ,'_,';.•. . . . , X

                   > - * -• i •-.	T ^       T

                   •"•'-"-'••••-'•-       f

                                                                                                 V

                                             O
                                                                i™,.
                                                            r l \.: -.-• •* - T~\



                                                - \ /    -j- \- v, -V o " .—. .- ^>
                                                       J. (  . . > .*. V^, _• . _ .._ i_>
                                        ,.  ,..-..• .._._,,.
                    — % •: r~\ — 1^1 ~ r -. - ~ r>
                    .i. t . J .1 L y . - -> 1J
                                      L.
                                                       V-r •»	v " /-* - r-\—T
                                                       1 j - ^ .L L j i A r. L
                O
CCLiRKEn
                                        ;*;_^j -'."vC'j'.^^O'o J L-.-'I-J
                                                                                              ;..'. .-v_ ,•- i') ,i V_/» »   t

                                                                                              s.             /
                                                                                                    \/
                                                      "TOWARD"" "
1X?»VA

                                                                                                                 C
                                                                      FIGURE 4.   continued

-------
       -28-
are wore sensitive to a few exi;rc>mely  high
v. ("i lues than to many moderately high  1 eve'is.
Ins p e c t i o n o f 111 o values cor r c s p o 11 d i n g t o  t h e
h i o! i o r p e r c c n t i 1 o s w o u 'id also s h o w t h e i n -
f li;?: nee of abnormal ly high values.   On the
a v e r n c; o , s t ?. n c! a r d d e v i n t. ions ci o not  cj e n e r a 1 'I y
ch;:.ncje much from yec-.r-to~year.
List I n ci i v i t! u :,i 1 Values
If the summary statistics indicate that the
mean was heavily influenced by a few high
values, or in the absence of summary statistics,
the individual data values which comprised the
average shou'U1 be listed.  From inspection of
this list, it can be determined if the average
was influenced by a relatively few large values
                                         i
or whether the bulk of the data appears to be
consistently  high.  If the former appears  to be
the situation, each individual data  value  should
be treated according to the guidelines for
specific air  quality data points presented above
In the latter case, proceed to the next step in
the verification of annual averages.
Physical Site Inspection
The physical  site location should be evaluated
in terms cf 1 •„«. i .^presontativensss of  the  pol-
lutant of ji-.i-ii-e^t, the averaging time of  in-

-------
      -29-
terest, the averaging time  of  interest  and  the
pollutant receptor.  The operation  of  tho  site
should bo'evaluated in terns of  sanip'i i ;ut
methodology, maintenance procedures,  cali-'
b r a t i o i i p r o c e d u r e s e n d qua! i t y c o n t r o 1  p r a c t i c A n
The actual sampling probe anc!  in'-jni f ol d  r.iater I 3 1 .-
configuration and  placement should  also be
evaluated.  Guidelines describing  i n  d c t ai1
these aspects'Of air quality monitoring have
been publ ished . ' '''''
Plot Data
Comparing a visual plot of  the current  data to
that of prior ears on a typical  annual  pattern
could further pinpoint reasons to  accept  or re-
ject the annual average in  question.   Note  that.
however9 some year-to-year  variation  is expected
Figure 5 presents  a typical  SOn  annual  pattern
based on expected  month"!-/ averages  (exaggerated
for purposes of illustration).   Figure  6  also
shows this same pattern with a constantly  in-
creasing baseline  drift.  A pattern of this
type suggests a contiruir   ionn-term failure
(change) in a cor,ipo,ie:v-': of  the instrument,
deterioration  in the supplies  being used  or a
s u b 11 e c h'. r. ' ? •'  *. 'i '.:• ~ ' v '•• '•" o n i?«. n t.   Figure  7
presents 1.:. -• •• •• •  "'• ;j:-.t,orn vnth  an  abrupt dis-
location of th:- '>n.-^ line.   This  may be iridicat.i

-------
      -30--
of a clu'nnc In  instruments,  method of analysis
procedures used  or  personnel.   It should not.
be arbitrarily  assuiied  that  any such r.iift
is wrong.  For  instance,  the analytical method
may have bjcn chnnfj^ci  to  tho standard re-
f e- r e n c e r o t h o A,  sources of i M L e r f e r c r; roc; in a y
have been t;'l ininatec!  or the  o porn tor:, n.-.y be
following i.he procedure correctly for tho first
time.  Figure 3  presents  a seasonal abnormality
in the expected  pattern.   It should be kept i ti
mind that a deviation  from the expected pattern
can be negative  as  we'll as positive.  Figure
9 demonstrates  hew  the  expected pattern can.t;.-:
smoothed (r.iasked)  by  a  nearby  source whose
emissions are fairly  constant  throughout the y.2r
"normal" and part  of  the  year  "masked" if there
are pronounced  seasonal wind direction chapes.
For those pollutants  S:K:'I as oxidants whose pcv.:;
                                             •r u i .
values occur during a  ? i;"! :• 1 e season a plot of
weekly or bi-weekly aver,? ^es through the period
of interest '/ould  provH:- vore information on
the cyclical pa'cterns  IDC  i. onthly averages.
C h e c!; P r i c r |j c. i a  f o *  "n c: i; u
Plotting at "iocst  feu;-  previous annual averages
along \ i (.!, l-.ii>':  cui'rfi;;;  y:?.r  and visually in-
spoct'i'•,;'.' (•(•.•:•••   ••  •  •:  gi-'e  the e valuator

-------



                                                 :: O.^ff^r I :r~.^ :'•:'':
                                                 ".::!:.. r^*1^' ;.,',X''-.:.'". r;:

                              -1 ::•:.:::
          :r:







 -?.-'ir:'--,'.'.'"; ••„•&.¥

                                                                                        "V   I.'Jl'.'" ™.!
                                   .is.-
                                                                               ^

 iz.vj :T-.* CVA'C'AM A '»" --«""!iur;r-ii."i
 -,...!	OJi-[l.iw.f.-'.aj.. .	!		I
                                                           "    '

  -. . • .
rf—mi-^t*M«T^T-»^
          I "".~ '. '." "'.
                                                i n 7-%^ V • O-'"'*'^'fTi
•T VIT i i-tv.'j-if.i;1*; :..":*'": t.:"":"./. ."iiv.:T7 .™".T;
;(.  -'O.w.*.>,.,.  :	, - --	- -1 -


""SEP    ii'cj    N'O'V	D j-:c™""	

-------
      -32-
a qufil i 'U ti ye insight into whether the currcr, v
annual average is a significant deviation fron
or an extension of the projected trend.
Compare v.'ith Surround ing Stations
3. f there ara enouoh surrounti \ \\g r; i tss  to do•-
vc'idp air quality isop'ieths of the area, the
c v a 1 LI a t o r c o u 1 d see ! i o w the arm u a 1 a v c r a g y i n
question fits in ivith the overall picture.  i:cr
instance, if the point in question was hiiov?;/
between the isopleth linos represent! no 80 anri
60, but the recorded value was 50* greater
than expected, i.e., 105, an abnormal i ty r:u-:y
be expected.
This comparative technique nay also be used in
a r e a s w here there a r c not enough s i t e s I; o c! i r e c t
plot air quality isopleths but where a pre-
dictive air quality model has been develop3d
and verified with a limited number of  actual
data values.  In these cases, for example, de-
viations of +_ 10055 could be suspect.
Heteorolcoy
The annual average should be interpreted in con-
junction with meteorological conditions for the
year in question.  For example, if the winter
of the yer :"  .  •vestion were the coldest in

-------
                   -33-
             50 years or the overall oegree days \vcro  BO;5;
             above the 20-yesr nonv!, an  increased  SOo  u v e r 3 [i :•
             would be expected.  Suspended participate-
             value? con ho greatly  affected by  wind  direc-
             tion and a disproportionate  wind rose  (atypical
             for t h e a r e a ) c o u 1 d h e 1 p  o x p lain u n u s u a 1  v <> 1 u f> r-
             Cornp ?.r ing t!u- appropriate meteorological  purfi-
             m e t e r s sue h a s r r, i n f a 11 ,  w i n d s p c e d ,  n u in b c;: r
             and length of inversion,  temperature  and  dnores
             days to their long-term averages,  i.e.,  20-
             or 50-year norms, bcfor>^  attempting to  change
             implementation plans is suggested.
     D.  Data Bank Update/Rep!ace/Delete  Procedures
         As Regional Office interaction  with the SAROAD dat-:
bank increases, there will be  an increasing need to  become
proficient with the procedures used  to update the  bank with
new data, correct existing data and  delete data  which  j'.-e
incorporated in the data bank  but hava been found  to  be  in
error.  There are then three types  of  transactions  which
can be processed by the SAROAD data  bonk:  update,  replace,
and delete.  In each case data in SA!K'\0  format  must  be  sub-
mitted on a separate tape or set of  ••• r  •;  ppd must  be  identi-
fied both on the tape and by an ucc.' ^s-.iny i ng Memorandum.

-------
                        -34-
              D.ocunientation of each of the transaction types,
     describing the processing which the data goes through and
     inchnting the''I imitations cf each type of transaction has
     ! -, ? •.  , f • :•- o v i d e d t o t h c R e g i a n a 1 Office b y M D A D (Slay tn a k G ; •' s
     :.:• .  •<>'•• June 6, 19/3).
              The Regional Office should use the previously
     discussed procedures to determine if identified suspect
     data should be uprlattd, corrected or deleted by in cans
     of these transactions.
3.2  Future  Areas or Responsibility
          Future areas of Regional Office responsibility vrith
     respect to air quality data include:
          A.  Qua!i ty Control
              Quality control practices in the operation of air
     monitoring instruments, laboratory analysis and data handling
     procedures is of the utmost importance in producing valid
     air quality data.  The Regional Offices should therefore
     encourage quality control programs at the State and local
     level.   To aid the Regional Offices in this effort, the
     Quality Assurance and Environmental Monitoring Laboratory,
     NERC/RTP,, has and is developing various manuals describing
     in detail, procedures to be followed during the course of
     sampling analysis and data handling for various pol-
     lutants?a>b»c'd

-------
                   -35
         The Control Programs Deve'lopniant  Division  has
developed a general guideline for  State  and  local quality
control programs entitled  "Quality Control  Practices  ii;
Processing Air Pollution Samples."0   This  guideline
should help the Regions! Office  establish  a  general  quality
control program at the  St.vte and local  level.
     B.  Edit and V a 1i dati o n C h c ck s
         W h e n M D A D d o v e 1 o p s t h e  d a t a  v a 1 i d a I i c n  p r c g r a n <>
and t u r i'i s both the e d i t o r  a n c! d a t a v a 1 i d n t ion  p r o g r a r.\':,
over to the Regional Office?., it is expected  that t!.>e
Regional Offices will assume the lead in initiating
edit and validation checks on the  incoming  data.  Hio.'i
                                         •.s           *J
quality data should then ba transmitted  to  the  National
Aerometric Data Bank via upgraded  remote access  computer
terminals.

-------
                       REFERENCES

1 .   .SA:':0/'.0 Users Hani! a'! > Office of Air Programs Publication
    No. APTD 0663, EPA, Research Triangle Park, N.C., July  1971.
2.   SAKOAD Terminal User'-s Manual, Office of Air Programs,
    Publication No. EPA-4CO/2-73-004, EPA, Research Triangle
    ?f\rk, N.C. , October 1973.
C.   II
     Field Operations Guide for Automatic Air Monitoring  Equip;.;0:; i. 5"
    Office of Air  Programs, Publication  No. APTD 0736,  EPA,  Research
    Triangle Park, N.C., November 1971.
4.   "Guidelines for Tec finical Services of a State Air Pollution
    Samples," Office of Air Programs, Publication No. APTD  1347,
    EPA. Research  Triangle Park, N.C., November 1972.
5.   "Quality Control Practices in Processing Air Follution  Sampl LS ,|:
    Office of Air  Programs, Publication  No. APTD 1132,  EPA,  Rese-ayc-h'
    Trieugle Park, M.C., March 1973.
6.   Federal Register, Vol. 35, No. 228,  November 25, 1971,  page  2>:40
-------
c
cl
Reference  Method  for  the; C-j,:''-, inuous  Koi'iilors of  Carlo;;
Monoxide  in  the A In:;:'sphere -
Reference.  i-iethoJ  for  the npU'rnri na Lion of Suspended
Particulates in i;"h:D Atmosj^iir re  (llinh V<;]ue Method}.
Reference  Method  for  Mefisurecent,  of  PJiotociic-.n^icnl  0>:'h!
Reference  Hethod  for  the DGlernn'natiG;) of Sulfur Dicxr
in the Ac.tT)Osphfi)-t!.

-------
                      GUIDANCE FOR
             AIR QUALITY MONITORING NETWORK
              DESIGN AND INSTRUMENT SITING '
                      January 1974
                  OAQPS Number 1.2-012
          Monitoring and Data Analysis Division
      Office of Air Quality Planning and Standards
                           and
Quality Assurance and Environmental Monitoring Laboratory
         National Environmental Research Center
         Research Triangle Park, North Carolina

-------
                      TABLE OF CONTENTS


PREFACE

1.  INTRODUCTION

2.  OBJECTIVE? OF REGIONAL MONITORING

3.  DESIGN OF AN AIR QUALITY MONITORING NETWORK

    3.1  Factors Influencing Network Design
         3.1.1  Source Receptor Relationships
         3.1.2  Meteorology
         3.1.3  Climatology
         3.1.4  Local Effects

    3.2  Size of Monitoring Networks
         3.2.1  Minimum Network (Existing Requirements)
         3.2.2  Additional Monitoring  (Suggested Guidance)

    3.3  Location of Monitoring ^Stations

    3.4  Sampling Frequency
         3.4.1  Recommended Frequencies - Urban Areas
         3.4.2  Recommendations for Isolated Point Sources

    3.5  Isolated Point Source Monitoring

4.  INSTRUMENT SITING

    4.1  General Considerations

    4.2  Specific Considerations

5.  REFERENCES

APPENDIX

    A.  Atmospheric Areas of the United States

    B.  Possible Procedures for Determining the Scope of
        Additional Monitoring

-------
APPENDIX, Continued

    C.  Screening Procedure for Determining the Necessity
        of Monitoring Isolated Ppint; Sources
                              ~*'j*'      ,'*'•'-!-
    D.  Computerized Atmospheric Diffusion Models Avail-*
        able from EPA

-------
                       LIST OF FIGURES
1.  Mean Daily Solar Radiation (Langleys) Annual.

2.  Estimated Distance from an Elevated Point Source to the
    Maximum Ground-Level Concentration.

3.  Schematic of Cross-Street Circulation in Street Canyon.

-------
                       LIST OF TABLES


1.  Minimum Number of Air Quality Monitoring Sites

2.  Distribution of Mechanical (Integrated) Sampling Stations

3.  Distribution of Automatic (Continuous) Sampling Stations

4.  Siting Guidelines for Areas of Estimated Maximum Pollutant
    Concentrations

-------
                           PREFACE

     The Monitoring and Data Analysis Division of the Office
of Air Quality Planning and Standards and the Quality Assur-
ance and Environmental Monitoring Laboratory of the National
Environmental Research Center, Research Triangle Park, have
prepared this report entitled "Guidance for Air Quality
Monitoring Network Design and Instrument Siting," for use
by the Regional Offices of the Environmental Protection
Agency and by State and local air pollution control agencies.
This report consolidates and updates information contained
in the previously issued air quality monitoring documents
listed below:
     1.  Guidelines:  Air Quality Surveillance Networks, AP-98,
         May 1971.
     2.  Guidelines for Technical Services of a State Air
         Pollution Control Agency - Appendix A, U.S. Environ-
         mental Protection Agency, APTD-1347, November 1972.
     3.  OAQPS Guideline Series 1.2-007, Air Quality Monitor-
         ing Interim Guidance, August 1973.
     Adherence to the guidance presented in this report will,
hopefully, lead to acquisition of more useable and mutually
compatible data by all States and Regions and will also facili-
tate evaluation of State air monitoring programs by the EPA
Regional Offices.  Further, risks involved in policy decisions
concerning National Ambient Air Quality Standards should be
minimized.

-------
1.  INTRODUCTION

     The primary purpose of this guideline is to provide the
Regional Offices of the Environmental Protection Agency (EPA)
and State and local air pollution agencies with updated gui-
dance on the principles and procedures involved in the design
of air quality monitoring networks with emphasis on the require-
ments of the State Implementation Plan (SIP) process.  The
August 14, 1971 Federal Register (40 CFR 51) provided regula-
tions regarding the minimum size of networks to be operated
by the States to monitor progress in achieving the National
Ambient Air Quality Standards  (NAAQS).  These regulations
specify minimum networks that vary in size according to regional
priority classification and population.  Full network implemen-
tation is required by mid-1974.'
                       123
     General guidelines ' '  have been issued which were
intended to provide a basic rationale for the development
and evaluation of air monitoring networks.  These earlier
guidelines were largely subjective but did provide the best
knowledge in existence at the time.  Much of the guidance pro-
vided by these earlier publications is repeated.  Areas where
updated or new guidance is presented include:  location of
samplers, instrument siting criteria, possible methods for
determining an adequate network size, and isolated point
source monitoring.
     The guidelines presented here can be used to assist
State and local agencies in setting up air quality monitoring
networks.  The development of an air quality monitoring net-
work includes determining the number and location of sampling
sites, selecting appropriate instrumentation, determining
frequency of sampling, and establishing instrument siting
criteria.  Experience and technical judgment are essential

-------
for determining the number and location of sampling sites
because mathematical models or other methods may not be
entirely reliable or, in some instances, may not be available.
     The development and implementation of a network must by
necessity involve a trade-off between what is considered
desirable from a strictly technical point of view and what
is feasible with the available resources.  An ideal network
will, in almost all instances, require more resources than
are available.  In light of this, the design discussed in
this guideline centers on the minimally required monitoring
network—a network less than ideal, yet capable of meeting
the major monitoring requirements.  The basic difference
between the minimally required monitoring network and the
ideal is that the minimal network has fewer and perhaps less
sophisticated instruments.  Designers of the network should
attempt to maximize the effectiveness of the minimally required
network through careful selection of sampling sites, scheduling
of variable sampling frequencies, and possible use of mechan-
ical (integrated)  as well as automatic (continuous)  samplers.
     This guideline does not cover specialized monitoring that
may be required concerning new issues such as indirect sources,
no significant deterioration, and supplementary control systems.
Information on air monitoring involving these issues and other
new issues will be provided separately either in the regula-
tions or in guidance issued at a later date.  Furthermore,
specific detailed guidance is being developed on an individual
pollutant basis covering the design and operation of the moni-
toring station network.   It should be recognized that air
monitoring networks are dynamic and, thus, should be flexible

-------
enough to allow for changing air pollution patterns as well
as the resolution of new issues.  Hence, network design is
not a one-time event.  An evaluation of a monitoring network
and how it meets the objectives of an air program should be
performed periodically.  Stations could be moved whenever the
needs of an agency change sufficiently enough to warrant the
move.  Some stations, however, should be designated as trend
sites and not be moved.  This will allow for analysis of long-
term air quality trends.

-------
2.  OBJECTIVES OF REGIONAL MONITORING

     Regional air quality monitoring networks are required as
part of the implementation plans currently in effect for sulfur
oxides, particulates, carbon monoxide, oxidants, and nitrogen
oxides.  Generally, monitoring networks for all of these pollu-
tants must be established in a region.  Although each pollutant
requires separate analysis, the collection of samples can be
generalized into two groups:  (1) a particulate network, which
is the source of information for suspended particulates, and
(2) a gas network, which consists of sampling devices for CO,
S02» NO?' non~met^ane hydrocarbons, and oxidants.  The need
for monitoring for each pollutant will depend on the amount of
pollution present within the region.  For example, whereas one
region may require extensive monitoring of, say, oxidants, the
relative absence of this pollutant in another region may pre-
clude such an extensive monitoring effort.
     Air quality monitoring within a region must provide infor-
mation to be use-d as a basis for the following actions:

     1.  Judging compliance with and/or progress made toward
meeting National Ambient Air Quality Standards.
     2.  Activating emergency control procedures intended to
prevent air pollution episodes.
     3.  Determining pollution patterns and trends throughout
a region including its nonurban areas.
     4.  Developing a data base for the assessment of health
and welfare effects, for land use and transportation planning,
for the study of pollutant interactions, for the evaluation
of abatement strategies and enforcement of control regulations,
and for validation of mathematical models.

-------
     It should be recognized that the overall goal of an air
quality monitoring network is the protection of human health
and welfare.  This report, however, stresses compliance with
SIP requirements because it is the regulatory process set up
to protect human health and welfare through the achievement
      I
of NAAQS.  While the two goals are generally compatible, there
are instances where the health and welfare aspect should pre-
vail.  For instance, where uncertainty exists between two
possible sampling locations, the one surrounded by a greater
density of population should be given preference

-------
3.  DESIGN OF AN AIR QUALITY MONITORING NETWORK

     In the design of an air quality monitoring network, know-
ledge of the factors influencing air quality and information
needed fo_r determining the number, location, and siting of
monitors is essential.  This section presents a discussion
of these factors and of possible methodologies that may be
used in the design of the network.

     3.1  Factors Influencing Network Design
     The design of a sampling network will depend mainly on
the magnitude and distribution of pollutant concentrations
within a defined area or region.  Pollutant concentrations
vary both in space and in time.  Variations occur as a result
of the interplay among various factors including source
strengths, emission characteristics,, meteorology, climatology,
topography, and urban effects as well as by chemical trans-
formations and natural removal processes.  Selection of the
number and location of sites for a network should properly
account for these factors.  Most of these factors are incor-
porated into dispersion models (see Appendix D)  which along
with past air quality measurements are used to estimate the
probable air quality isopleths throughout a region.  Isopleth
maps of ambient concentrations so derived are the best tools
for determining the number of stations needed, and for suggest-
ing station locations.  In the absence, of adequate or appropri-
ate models and/or past air quality data, techniques involving
some of the factors may be used to aid in network design.

-------
     The following discussion briefly describes the major
factors influencing air quality and how knowledge of these
factors may be used in designing an air quality network.

     3.1.1  Source-Receptor Relationships
     Source-receptor relationships are concerned v/ith source
strengths and emission characteristics and how they affect
pollutant concentrations at receptor sites.  This information
is utilized in dispersion modeling to indicate zones of con-
centration maxima, to locate monitoring sites, and to determine
the type and number of samplers.
     An emission inventory is a prime prerequisite for proper
design of a network.  In the absence of such an inventory,
information on distribution of major sources, population,
transportation networks, and present and projected land uses
can be quite useful.  This information along with available
data on meteorology, topography, and dispersion characteristics
will indicate the major features of pollutant distributions.
     For reactive pollutants such as oxidants which form in
the atmosphere from photochemical processes, the primary
factors affecting ambient concentrations are:
     . Concentration of reactive precursors
     . Intensity of solar radiation
     . Atmospheric stability
     . Low-level transport winds.
     Reactivities of photochemical pollutants can vary substan-
tially from place to place depending on the mix of photochemically

-------
                           8
active constituents in the air.  Solar radiation varies con-

siderably in different parts of the country as well as with

the season and time of day.  On sunny days when photochemical

processes are more prevalent, the atmosphere tends toward

instability.  Transport wind information along with some assump-

tion or measure of stability can be used in locating suspected

areas of concentration maxima.  The usual source of such meteoro-

logical information is airport weather observations.  Summaries

of daytime conditions are preferred for photochemical considera-

tions.


     3.1.2  Meteorology

     Major meteorological factors that influence pollutant

concentrations are:

     ». The Vertical Structure of Horizontal Wind and its
       Variability

       Winds transport and dilute pollutants between sources
       and receptors.  Variations of wind direction markedly
       influence concentrations at receptors.  Light winds
       generally tend to increase concentrations over wide
       areas.

     . Atmospheric Stability

       Pollutant dispersion is inhibited in stable air which
       accompanies temperature inversions and is enhanced by
       the instability caused by thermal and mechanical tur-
       bulence.

     . Mixing Heights

       This parameter is defined as the height above the
       surface through which vigorous mixing occurs.  Mixing
       height normally reaches a minimum in the early morning
       and a maximum in the afternoon.  Low afternoon mixing
       heights are often indicative of poor dispersion con-
       ditions.

-------
      . Solar Radiation
       Both the intensity and duration of solar radiation
       are important to the formation and buildup of photo-
       chemical pollutants.
     3.1.3  Climatology
     Dilution Climatology
     Dilution climatology is defined as-the combination of
meteorological conditions which affect the interchange and
dispersion of pollutants of relatively large areas.  Such
factors are the frequency, persistence, and height variation
of wind speed and direction of stable  (inversion) layers of
air and of mixing heights.  Collectively, an assessment of
these factors provides a measure of the dilution climatology
of an area.  Dilution climatology accounts for the effects
of large scale topographic features such as large bodies of
water and mountain ranges.  The relative recurrence of short-
term phenomena such as stagnation episodes is considered.
Small scale obstructions such as hills and buildings are
classified as localized influences and are not considered in
dilution climatology.
     Atmospheric areas possessing similar dilution climatolo-
gies have been defined on a geographic basis and include all
Air Quality Control Regions in the contiguous United States
(Appendix A).  Attached to Appendix A are interim definitions
for areas outside the contiguous U.S. for which AQCR's have
been designated.  Atmospheric areas are used in Appendix B
to derive relative numerical indicators of the possible need
for additional monitors in an adequate network.

-------
                           10
     Mean Solar Radiation
     The dilution climate of an area while important to the
accumulation of secondary pollutants once they form does not
influence their formation.  Figure 1 shows relative solar
radiation throughout the contiguous U.S. and can be used as
an additional tool to indicate the needs for monitoring secon-
dary pollutants.

     3.1.4  Local Effects
     Topography
     The dispersion patterns in some sectors of an area or
region can be significantly altered by local topographical
factors.  Those which will be used in this guideline along
with meteorological factors to indicate need for additional
monitors in an adequate network- are:
     . Valley Effects
       Valleys tend to channel the wind flow along their
       axis, restrict horizontal dispersion, increase the
       tendency for inversions to form, and may cause aero-
       dynamic downwash from stacks not extending above the
       valley walls.  Air quality discontinuities between'
       valley-ridge sectors often exist.  Thus, valleys
       almost always need monitors in excess of the
       required minimums.
     . Shoreline Effects
       Airflow along shorelines undergoes frequent changes
       brought about by the changes in relative temperature
       of the air and water.  Discontinuities and conver-
       gence zones in the dispersion patterns occur which
       indicate need for monitoring beyond required minimums.

-------
                        11
soo
    Figure   1. Mean daily solar radiation (langleys) annual.  (Stern,   1968)

-------
                           12
     . Hilly and Mountainous Terrain Effects
       Complexities introduced by hills and mountains include
       disrupted airflow patterns, intersection of their
       interface by elevated plumes, induced mechanical tur-
       bulence and more frequent inversions in low-lying
       protected areas.  Hilly and mountainous terrain usually
       increase the need for monitors.
     Urban Effects
     Virtually all meteorological parameters are influenced
to some extent by cities.  Urban effects tend to modify
meteorological parameters in the following major ways rela-
tive to rural locations:
     . Wind direction variability is increased
     . Average wind speeds are lighter
     . Instability is increased
     . Mixing depths are greater
     . Local influences are greater.
     The complexity and variability of urban factors do not
allow general quantitative assessments.  Therefore, in this
guideline, urban effects are not used directly to indicate
the number of sites that may be needed.  Instead, the user
should be aware of urban effects when considering other factors
(such as meteorology, climatology, etc.) and should make adjust-
ments where necessary which allow for urban influences.

     3.2  Size of Monitoring Network
     The basic network size refers to the number of monitors
needed or required to fulfill the objectives of a monitoring

-------
                           13
program.  Ultimately, the number of sampling stations neces-
sary will depend primarily on the existing pollution levels,
their variability, and the size of the region (availability
of resources is also an important consideration).   The size
of the network, however, must be sufficient to define the
area(s) where ambient concentrations may be expected to exceed
air quality standards.  Information on air quality in other
areas including the nonurban portions of the region should be
also collected.
     In many AQCR's, there is a need to increase the level
and intensity of monitoring for carbon monoxide and oxidants.
On the other hand, S02 and TSP existing networks appear to be
adequate in most of the AQCR's for fulfilling the objectives
of the SIP's.
     The following subsections review existing guidance on
the design of minimally adequate networks—representing the
lowest level of monitoring activity commensurate with overall
air quality objectives.  Possible procedures for supplementing
the minimum network to more adequately fulfill monitoring
objectives are presented also.

     3.2.1  Minimum Network (Existing Requirements)
     A first approximation to the minimum number of stations
required in a region may be obtained from general curves based
on a qualitative evaluation of cities of different population
classes in terms of their existing networks pollution patterns,
geographic distribution of sources, and the like.   The relation-
ship between population and network size (see below) was derived
                         4
from such investigations,  combined with experience.  In general,

-------
                           14
population is a good index to determine network size.  In
certain situations, however, such as the relative absence of
sulfur dioxide in some western portions of the U.S., such
relationships may not be applicable.  In these situations,
additional information such as source strengths and their
locations is essential before a network size can be deter-
mined.
     Based on the above population relationship and according
to a priority classification assigned to each AQCR for carbon
monoxide, nitrogen dioxide, particulate matter, photochemical
oxidants, and sulfur dioxide, the minimum size of an air
quality monitoring network was determined.  An AQCR was
assigned a priority classification according to a comparison
of its air quality levels to the air quality standards or
based on its potential for violation of an air quality stan-
dard.  Generally, in Priority I AQCR's, the air quality is
poorer than primary standards.  In Priority II regions, it
is between secondary and primary levels and in Priority III
regions, it is better than secondary standards.  For parti-
culate matter and sulfur dioxide, the classification criteria
provide for Priorities of I, II, or III while for carbon
monoxide, nitrogen dioxide, and photochemical oxidants, Priori-
ties of I or III are applicable.
     Table 1 presents the minimum number of air quality moni-
toring sites by AQCR classification and population class.
Note that the reference method for nitrogen dioxide has been
revoked.  Three candidate methods have been proposed to replace
the former reference method.  An evaluation of these methods

-------
              Table  1.    Minimum  Number  of  Air  Quality  Monitoring  Sites
                                                                                                     I  ','
  Classification
   g( region
                     Pollutant
     Measurement method '     Minimum frequency at sampling     Begton population
                                                                                     Minimum number of sir
                                                                                    quality monltorlr.f sites »
              SuspendedpertlculaUs... High volume satnplo	On«24-bours»mpl«.«vBrjeda7«*.
              Suite dioxide..
  Tape sampler	One sample eTery 1 houn	

. PararoBanlllns or equivalent'. One 24-hour sample every 6 days
                              (gas bubbler).*
              Cofbon monoxide	


              Photochemical oitdants.


              Nitrogen dloitde	
             . Suspended paniculate*.

              Sulfur dioxide	
. Nondlsperslve Infrared or
   equivalent.*

. Gas phase cbemflinnlnesence.
   or equivalent.'

. 24-hour sampling method
   (3 acobs-H ochhelser
   method). *
. High volume sampler	
  Tape sampler		
. Fararosanillns or equivalent*.
             . Suspended particulars..
              Btulur dioxide	
. High volume sampUr	
j Pira.-osanUioe or equivalent «.
                                                                 Continuous	
                                                                 Continuous	
  Continuous	
One 24-hour s:\mple every 14
  days (gas bubbler).*

One24-hoursarnple every 6dajrJ •
One sampie' every 2 hours	
One 24-hcur ssmp'.e every 6 days
  (gas bubbler).*
Continuous	
Or.e24-hours;i:np!eevery6days •
One 24-hour simple every 6 days
  (gas bubbler!.*
 Le.«3 than 100.000	4.            '•   "  "'  '
 lOO.OOO-l.OOO.OOO	4-t-O.S per 100.000 population *
 1.000.001-6.0CO.OOO	7.5+0.25 per 100.KO populat'cn •
 Aboie5,000.000	U+0.\6p<>r IGO.Oud pnpulttlori '
	One per 250.000 population «no
                          to eight sites.
 Les< than 100.000	.-..-. 3.
 ICO.iKO-l.COO.iAJO	2.5-0.5 per 100.000 population •
 1,000.001-5.000.000	6J-0.15 per 100.i») population ••
 Above 5.000.000	11+0.05 per 100.000 population
. Less than 100.000	1.                          '
 lOO.OOO-S.COO.OiK)	1+0.15 per 100.001 population «
 Above J.ftO.iXW	6+0.05 par lOO/.vO population.'
. Less th»n 100.000	 1.
 IOO.000-5.OiXi.OX)	 1+0.15 per 100.000 population •
 Above S.iXO.COO	6+0.05 per 100,000 populitlon.'
. Less than 100.000	 I.
 100.000~S.KO.MO	 1+0. IS per lOO.OCO population •
 AboTt5.Ci4.tYO	6+0.05 per IOC ICO populitlon.*
 Lfs.' tlun KO.OOO	3.
 100.000-1.010,000	4+0.6 per 100,000'population •
 Above 1.000,000	 10.
	s.
	1.
                       . 1.
                        1.
                       . I.
    • Equivalent to 61 random samples per ypor.
    • Equivalent to C6 risdom samples per yeir.
    • Total population of a region. VVh»n required number of samplers Includ^-s a fraction, round-off to nearest whole number.
    * Equivalent meth"ii orj il) Gas Chrorr..itccr!iphlc Separation—Flime Photometric Detection (provided Teflon Is used tl-.--ouf.nbutthe instrument system In parts expose
to the air stream). (21 f'..\~> Photometric Detection (provided interfering ;ui!ur compound.' present In 'ijntflcant qiuntiii/s are removed), (1) Coulometrlc Detection (provide
oxldlilng and reducir.? Interferences auch as Oi. Npi. and Ui5 are rer.iov.-l'. and Ml the worn-it .<•!  Pari.-os.\niiip.j Procedure.
    • Equivalent rr.ot^od ij Gii Chror::.'.:''CT:irri!c Sep-Aratton—Cit^lytic Conv.^r?ion— F'i-.in>: lo-u.»tli:n Detec'.:or..
    'Equivalent meth->Ji a:e il) Po!u. (0-0.5 p.p.m.).
                                               20 up. n:.' (0.01 p.p.m.).
                                               5 minutes.
                                               5 minutes.
                                               «1 percent per day and *2 percent p«
            1.1 mg.Jn.1 (1 p.p.m.)	
            2 percent (full scsle).
                         .
                  ••1 p.;rcrnt per day and
                    3 days.
                  • 4 percent.
                  S days.
                  *0.5 percent (fnll scale.).
                  W Mf.'m.' (0.01 p.p.m.).
                  «5°C.
                  2 percent (full scale).
                                                                                                                                     2 percent p<
                                                                     POLLUTANTS
                                    Specification
                                                                  Nitrogen dioxide
                                                       Uydrocarlxms (corrected for methane)
                           Ranpe.	O-lS'Our'm1 '0-1 p.p.m.)	
                           Minimum detectable sensitivity	19 *ip mj (0.01 p.p.m.)		
                           Rise time. W7,,	 6 minutes	
                           Fall time, 9U70	* minutes	
                           Zero drift	±1"",, [X:r day and ±2% per 3 days
                                                          (full scale).
                           Span drift	dbl1^ per  day and ±2% per 3 days
                                                          (full scale).
                           Precision	±4%	
                           Opcratiou i»Tiod	'.	9 days	
                           Noise	 ±0.5r*c (full scale)	
                           Interference equivalent	1'j »s mi (0.01 p.p.m.)	
                           Operating tcmj^-iature fluctuation. ±5& C	
                           Linearity	2% (full scale)	
                                                       0-3 mp'm> (0-5 p.p.m.).
                                                       0.13 mr m' (0.20 p.p.m.).
                                                       6 minutes.
                                                       5 minutes.
                                                       ±11  P-T day and ±2% per J days
                                                        (full scale).
                                                       ±lTc  Per day and ±2% per I days
                                                        (full scale).
                                                       ±2%.
                                                       3 days.
                                                       ±0.5% (full scale).
                                                       0.03 mg'm" (0.06 p.p.m.).
                                                       ±6°C.
                                                       2% (full scale).
       The various specifications are defined as follows:
       Range: The minimum and maximum mfssurement limits.
       Minimum detectable sensitivity: The srr-.a!:..-;! amount of input conccntratiun which can be deUcted as concentration approaches lero.
       Rise tirnt yO percent: The interval between inirial re^pon^e time and time to VO percent response after a step increaje in inlet concentr&tion.
       Fall time W> percent: The interval tetwf-n lr.it!:»! rc5i-o:^'- tim*1 and time to '/) perc/.-nt ri^iion'e alter a st*-p 'I'.cre.ije in the inlet concentratioh.
       Zero drill: The chu:.?e m mstrumrr.t ouiimt over i f.aii-d ti:ne p. nod ol unadjusted cc.ntii.uous operation, when the input cor.ontration is lero.
       Span drift: The change in instrument output over a VS'A period of unadiu-'ted continuous op^raUon. when the input coni>r.tnition Is a stated  upscale value.
       Precision: The d'-pree of a2r-.-r:i' :.t between rep-^i-.-d i.i'Si5urcrnents of the &ame concentration iwhlch shall be the midpoint ol the slated range) expressed ftl tbl
   tverag? deviation of the sinele results from the mean.                                             .            •
       Operation period: The perii,J ol thr.e. ov.-r w.'iii-h tiie instrument can be expected to op.'rate unattended within specifications.
       Noise: Spont^r.r-ou? di-vijjiior.5 frf.-:n a rntan oui:"it not c:*u.-cd \>'j ir.put concentration chanpes.                                            \
       Intrrfxri-iicv Ci^:v ,:•>:.{:  T::- r*"..'.-.''! ir.dicnt. d irir.<-;.tr.itio:i due to t:ie totil ol I:...- ir.t« rj-ri-r.cn commonly found in ambient air.
       Operating trn-,[>i-r>iture fluctui-.ti"n: Tiie mnbii-M t/'ir.p- ruture Kuctuation ovir wr.;c!i .'Cited «[i-cir.c»tions will b<: met.
       Linearity: The maximum deviation btiwmn an actual instrument reading and tl;e reading pr> dieted bv a straight line drawn between upftr and lower calibration
   points.
   *EPA  is   currently  evaluating"three  measurement   techniques   for  N07
    and   will   publish  a  new  reference   method.     The  minimum   sampling
    frequency   may  also  change  depending  on  •   ,e  analytical   technioue
    chosen.

-------
                             16
is still underway.  Meanwhile, in cases where it appears
desirable to continue NO- monitoring activities, the Jacobs
Hochheiser technique should not be used.

     3.2.2  Additional Monitoring (Suggested Guidance)
     It is recognized that the scheme for determining the
minimum requirements of an AQCR written in regulation form
may not be flexible enough to allow for adequate monitoring
in every AQCR in the country.  Further, issues and new require-
ments such as no significant deterioration, indirect sources,
transportation control plans, and supplementary control systems
may have increased the need for monitoring above the minimum
requirements.  Appendix B presents two possible methodologies
which may be used for determining an adequate network size.
One is baser) on the existing pollution levels and patterns
in an area.  The other is based on the application of topo-
graphic and climatological weighting factors to the minimum
implementation plan monitoring requirements.
     Both methods apply only to SCU and TSP and Priority I
oxidant and N02 AQCR's.  CO is not covered because it is
usually more of a localized rather than a regionwide problem.
Priority III AQCR's do not require monitoring for CO, oxidants,
and N0? at this time.

     3.3  Location of Monitoring Stations
     Selecting the locations of stations and samplers involves
decisions regarding  (1) distribution of samplers within the
region and (2)  specific site selection for each station.  The

-------
                             17
first decision requires consideration of monitoring objec-

tives, overall pollution patterns, and the needs for govern-

mental jurisdictional coverage.  Selection of the particular

site is based on representativeness of the area and other

practical aspects such as housing the samplers, electric

power, and security from vandalism.
     The information required for selecting sampler location

Is essentially the same as that for determining network size,
i.e., isopleth maps, population density maps, source loca-
tions.  Following are suggested guidelines:

     1.  The priority area is the zone of highest pollutant
         concentration within the region.  One or more sta-
         tions are to be located in this area.

     2.  Close attention should be given to densely populated
         areas within the jTtcjiOii, cspecictj-xy wiifcin uht;y are in
         the vicinity of heavy emissions.

     3.  For assessing the quality of air entering the region,
         stations must also be situated on the periphery of
         the region.  Meteorological factors such as frequen-
         cies of wind direction are of primary importance in
         locating these stations.

     4.  For determining the effects of future development on
         the environment, sampling should be undertaken in
         areas of projected growth.

     5.  A major objective of monitoring is evaluation of the
         progress made in attaining the desired air quality.
         For this purpose, sampling stations should be stra-
         tegically situated to facilitate evaluation of the
         implemented control tactics.

     6.  Some information of air quality should be available
         to represent all portions of the region.

-------
                             18
     The air quality monitoring network should consist of
stations that are situated primarily to document the highest
pollution levels in the region, to measure population exposure,
to measure the pollution generated by specific classes of
sources, and to record the nonurban levels of pollution.  Many
stations will be capable of meeting more than one of these
criteria; e.g., a station located in a densely populated area
besides measuring population exposure could also document the
changes in pollutant concentrations resulting from new control
strategy employed in the area.
     Although the sampler locations depend on many factors,
some idea of sampler distribution may be obtained from Tables
2 and 3, which show sampler location as a function of network
size.  Table 2 summarizes distribution of mechanical samplers,
such as Hi-Vols; Table 3,shows distribution of automatic
samplers.  With respect to locations shown in Tables 2 and 3,
it will be necessary to consider wind patterns, source loca-
tions, and distribution of emissions in selecting approximate
locations for these sites.  For example, stations in the highly
populated area should be so situated that they can accurately
assess the pollution impact under different meteorological
conditions.  Although both types of stations follow the same
general pattern, the tendency is for wider distribution of
mechanical sampling stations.
     In the case of the reactive secondary pollutants, the
best sampling locations are, in most cases, away from the
sources which emit the necessary precursors (and contribute
to the reaction processes).  Thus, the use of emission density

-------
                           19

   Table 2.  DISTRIBUTION OF MCCrPJSICAL  (INTEGRATED)
                   SAMPLING STATIONS'1

Number of stations in:
n_
Total number
of stations
1
2
3
4
5
10
15
• 20
25
30
alncludes Hi-Vol
(for oxidants,
Center city/
industrial
1
1
2
2
2
5
8
12
14
17
sampler SO-
a sampling t
Residential
zones Nonurban
_
1
1
2
2
3
5
6
8
10
and NO^. 24-hour cc
ime over 20 minutes
_
-

-
1
2
2
2
3
3
sllector
is not
 recommended).

 At least one monitor for each pollutant should be in the
 area of maximum concentration.
    Table 3.  DISTRIBUTION OF AUTOMATIC  (CONTINUOUS)
                   SAMPLING STATIONS3

Total number
of stations
1
2
3
4
5
6
10
15
Number
Center city/
industrial
1
1
2
2-3
3
4
6
10
of stations in:
Residential
zones Nonurbanc
. _ _
T_ _
1
1-2
o _
2
4
5
alncludes SO2, CO, No2, and oxidant  (ozone).


 At least one monitor for each pollutant should be in-
 the area of maximum concentration.

c
 Where ozone damage has been identified in nonurban areas,
 monitoring may be necessary.

-------
                              20
and land use maps are not always helpful in determining sam-
pling site locations.  They can, however, be used in conjunc-
tion with information on the direction and magnitude of
prevailing mid-morning winds to provide approximate sampling
locations.  In general, the maximum concentrations are indi-
cated to occur between 5 and 15 miles downwind from the
downtown or area of. heavy traffic density.  However, if the
winds are light and variable, high levels may occur in the
vicinity of the pollutant emissions such as the center city.
The location of good NO- and oxidant sampling sites is a diffi-
cult process and in many cases is based largely on intuition
or trial and error.  The use of mobile NO- and oxidant samplers
could be helpful in locating areas of high concentration.
     It is the intent of these guidelines to suggest that a
simple network be developed Lo measure the concentration of as
many pollutants as possible.  It is likely that common sites,
although not necessarily ideal for each pollutant, may be
selected to provide adequate coverage for the pollutants of
concern.  Each pollutant, however, should be considered indi-
vidually during the design phase to pinpoint pockets of high
pollution that otherwise might be overlooked.
     The final task in determining sampler placement is to
find a specific location with the proper facilities for oper-
ating the sampler.  Availability of space and power, accessi-
bility, security, and representativeness of the site determine
the precise location.

     3.4  Sampling Frequency
     Sampling averaging times depend mainly on the primary use
of the data.  Accordingly, to show compliance with, or progress

-------
                              21
towards meeting ambient air standards, the sampling system
must be capable of producing data consistent with the aver-
aging times specified by the standards.
     Current regulations specify the frequency of sampling
for the criteria pollutants to meet minimum"requirements
(Table 1).  Continuous sampling is specified except for 24-
hour hi-volume for suspended particulate matter and 24-hour
gas bubblers for SO .  (At this time, the frequency that may
be specified for N02 sampling is not known.)  The hi-volume
and gas bubbler measurements are required in all AQCR's at
least once every six days, equivalent to about 61 random
samples per year.  Twenty-four-hour samples should be taken
from midnight to midnight  (LST)  to represent calendar days
and to permit direct utilization of the sampling data with
standard daily meteorological summaries.
     The following are recommended frequencies for non-con-
tinuous, hi-volume, and bubbler sampling in order to more
adequately define TSP and S02 levels relative to the NAAQS.

     3.4.1  Recommended Frequencies - Urban Areas
     In general, the importance of measurements made at the
most polluted sampling sites in an urban AQCR makes it advis-
able to increase the frequency of sampling at those sites
above the minimum requirements.   It is recommended that the
most frequent hi-volume samples be taken at the site(s)
where the highest 24-hour and annual averages are expected
based on past measurements or modeling estimates.  This pro-
cedure will minimize the uncertainties in determining whether

-------
                             22
the 24-hour NAAQS levels for particulate matter were exceeded.
Correspondingly, a more precise estimate of the annual average
will also be derived.
     For S02/ continuous instruments can be used in place of
bubblers in areas of maximum concentrations.  Accordingly, it
is recommended that in Priority I AQCR's, the continuous sam-
pling sites cover the areas of highest 24-hour and annual
average concentrations.  This constitutes no significant
change from present requirements for S02 monitoring.
     For TSP and S02/ resources are generally not available
to operate the entire network on a daily basis.  Adequate
coverage may be maintained at non-critical sites (i.e., sites
other than maximum concentration sites) with intermittent sam-
pling at frequencies calculated statistically for desired levels
of precision.  In order .to increase the statistical precision
of the estimate for the annual average, a systematic sampling
schedule should be utilized, such as suggested by Akland.
Also, the frequency of air monitoring necessary to character-
ize an air pollutant for a given time period and area can be
determined from statistical relationships that predict the
precision of the sample mean as a function of the frequency
of sampling, the standard deviation of the logs of the indi-
vidual measurements, and the level of confidence.  Thus, the
minimum frequency requirements may not be adequate for all
locations and levels of confidence desired.

     3.4.2  Recommendations for Isolated Point Sources
     For isolated point sources, the areas of maximum concen-
tration on a short-term (up to 24' hours) a.re of primary concern.

-------
                             23
Experience has shown that such sources rarely cause violations
of long-term  (annual) standards.  S02 and TSP sources shown by
the method in section 3.5 to have the potential for causing a
violation of NAAQS should be monitored by at least one downward
site more frequently than minimally required.  Specifically, at
this site, continuous instruments for SG>2 and sampling more
frequently than once every six days for TSP is advisee' .
     Bubbler  (24-hour) sampler(s) at the key site(s) are less
desirable because of the need for monitoring for the 3-hour
secondary S02 ambient standard.   The 3-hour standard is especially
relevant in many nonurban areas because of its relation to vege-
tation damage.
     The key site(s) for monitoring for isolated point sources
should be located on the basis of expected highest concentra-
tions for a given pollutsnt.  Ordinarily, only NAAQS for SO-
and TSP would be expected to be threatened by emissions from
isolated point sources; therefore, no recommendations for moni-
toring other criteria pollutants are made at this time.

     3.5  Isolated Point Source Monitoring
     Additional monitoring for point sources in multiple source set-
tings is not recommended unless models or other, information
show that certain sources predominantly contribute to ground-
level concentrations.  A predominant source in this context
would be defined as one which would contribute 90 percent or
more of the non-background concentrations over an extensive
area.  In particular, models would also generally specify the
location of the maximum concentration expected from these sources.

-------
                             24
     For isolated sources situated in relatively level terrain,
a screening model procedure* presented in Appendix C can be
utilized for making a determination of which particulate and
sulfur dioxide sources should be monitored.  This procedure
is not applicable where turbulence in the wake of the plant
(emission source) building or nearby structure is apt to cause
aerodynamic downwash of the plume.  The procedure is also not
applicable where concentration measurements at elevated levels
above ground (such as on tops of buildings) are desired or
where there are significant terrain features above the ground-
level elevation of the plant.  Suggestions for identifying the
above circumstances follow.
     Where the supporting structure for a stack or where build-
ings or other such obstructions exist within a distance of 10
stack heights and where the height of any of these structures
is more than 2/5 the height of the stack, then aerodynamic
downwash of plumes is likely to occur and a detailed analysis
of the specific case is necessary.  '
     Similarly, a detailed analysis is needed where terrain
elevations more than 2/5 the height of the stack exist within
10 kilometers of a point source.  In the latter circumstance,
the greatest impact may occur on the higher terrain under
meteorological conditions which are much different from those
assumed to cause the maximum in this procedure.  Other unfore-
seen conditions may arise in evaluating the impact of point
sources which may necessitate detailed analysis.
*Note that this procedure does not apply to sources covered by
regulations for which monitoring is prescribed such as those
that may operate supplementary control systems.

-------
                             25
     For each of the sources for which the need for monitoring
is determined from the above screening procedure, a minimum of
three sampling sites are suggested.  Two should be along the
most frequent downwind direction(s) and one should be along
the direction that is predominantly upwind.  Annual wind roses
can be used in this determination.  The samplers should be
placed at distances where maximum short-term (1-24 hour) con-
centrations are most likely to occur.  (The long-term annual
standards are unlikely to be threatened by an isolated point
source.)  The distance to the maximum concentration is a func-
tion of effective source height and atmospheric stability.  A
reasonable estimate of this distance can be .derived from Figure 2,
Effective source height is the sum of physical stack height and
estimated plume rise.  The Briggs  plume rise or other appropri-
ate plume rise equations may l?o used.  Where resources allow,
a preliminary sampling survey  (possibly including mobile sam-
pling)  should be carried out to locate areas of maximum concen-
tration and to verify the appropriateness of dispersion estimates,

4.  INSTRUMENT SITING

     4.1  General Considerations
     In the selection of a particular site for a single sampler
or a complex station, it is essential that the sampler(s)  be
situated to yield data representative of the location and not
be unduly influenced by the immediate surroundings.  Little
definitive information is available concerning how air quality
measurements are affected by the nearness of buildings, height

-------
                           10'
vo
CM
                       z
                       3
                       3
                       li. —
                       O t






                       If"'
                       o a:
                       is
< u
> -l
                       = 5
                       X O
                       o 
-------
                              27
 from ground and the  like.   There  are, however,  general guide-

 lines that  can  be  provided  based  on  operational experience:

      1.   Avoid  sites where  there  are restrictions  to  air  flow
          in the vicinity of the air  inlet—such as adjacent  to
          buildings,  parapets,  trees, etc.

      2.   Avoid  sampling sites  that are  unduly  influenced  by
          down-wash from a minor local source or by reentrain-
          ment of ground dust,  such as a stack  located on  the
          roof of a building where the air  inlet is located or
          close  to  ground level near  an  unpaved road.  In  the
          latter case,  either elevate the sampler intake above
          the level of  maximum  ground turbulence effect or
          place  the sampler  intake away  from the source of
          ground dust.

      3.   The monitoring site should  be  generally inaccessible
          to the public and  should have  adequate security,
          electricity,  and plumbing.

      4.   Uniformity  in height  above  ground level is desirable.
          Roof-top  samplers  should be utilized  in moderate to-
          high density  areas (in terms of structures).  Ground-
          level  samplers should be utilized in  low  or  sparse
          density areas (in  terms  of  structures).

      5.   For CO or NC>2 monitoring, samplers should not be
          located in  the median area  of  multilane highways.
      4.2   Specific  Considerations

      Specific  guidelines  for  siting  air monitoring  stations  in
.areas of maximum pollutant  concentrations  are presented  in

 Table 4.   These  guidelines  cover the monitoring of  multiple

 source areas;  guidance  for  monitoring  specific sources is
 presented  in Section  3.5.
      Sulfur dioxide can be  considered  to be rather  well  mixed

 near  the ground  at  receptors  not overly affected by specific

-------
                             28
point sources.  Therefore, either ground or roof-top sampling
is recommended.
     Similarly, TSP is usually well mixed within the first few
hundred feet above the ground, but only roof-top sampling is
recommended to avoid the influence of possible reentrainment
of particulates close to ground level.
     Distance from the street is specified in the sampling
location guidelines for measuring peak 1-hour and 8-hour con-
centration values of CO because of the strong dependence of
CO concentration on nearness to the street.  For the same rea-
son, height from the ground of the air inlet is more restric-
tive than for the other pollutants.  It is desirable, however,
to sample as close as possible to the breathing zone within
practical considerations  (i.e., proper exposure, security from
                  i >-»*-* <-;i vv f ^*.C
sampling within street canyons, the side of the street which
is opposite the side facing the roof-top-level winds is more
likely to experience the highest concentrations (Figure 3) .
     The urban background site for CO should be utilized to
measure the maximum areawide concentrations to which the
general population is exposed.  Thus, either roof top or
ground-level sampling in urban or suburban areas is recommended.
This station should not be adjacent to major thoroughfares  (not
closer than 50 feet from the street curb) to rule out the influ-
ence of localized peaks due to roadway traffic.
     There are no well established meteorological dispersion
models presently available for selecting areas of expected
maximum concentration for the secondary pollutants  (oxidants
and N02) -  Probable high concentration areas described in the

-------
                            29
                                         MEAN
                                         WIND
                                              BACKGROUND
                                            CO CONCENTRATION
 .BUILDING
BUILDING
                          TRAFFIC
                           LANE
Figure  3.   Schematic  of Cross-Street  Circulation
            in Street  Canyon (from Users Manual
            APRAC-1A,  Urban Diffusion  Model, Sep-
            tember 1972)

-------
                           30
table for these pollutants are based on: (1) available infor-
mation on the reaction kinetics of atmospheric photochemical
reactions involving hydrocarbons, nitrogen oxides, and oxi-
dants; (2) on diurnal variation in pollutant concentrations;
(3) on distribution of primary mobile sources of pollution;
and,  (4)  on meteorological factors.  A minimum distance away
from major traffic arteries and parking areas is specified
for the oxidant monitoring site because NO emissions from
motor vehicles consume atmospheric ozone.  N02 is considered
both as a primary stationary source pollutant and as a secon-
dary pollutant and air monitoring stations for this pollutant
should be located consistent with the respective station
location guide1-'nes.  Differences in horizontal and vertical
clearance distances are based on increased probability of
reaction between reactive gases and vertical surfaces.

-------
rablc 4.  SITING GUIDELINES  FOR AREAS OF ESTIMATED MAXIMUM PDLLUTANT  CONCENTRATIONS
                                                                                     POSITION OF
POLLUTANT CATEGORY
        Stationary
Source Pollutant
        Mobile
Source Pollutant
POLLUTANT
SO,
Particulatea

CO  (Peak)
                      CO  (Urban
                      Background)
STATION LOCATION
SUPPORTING
STRUCTURE
Determined from atir.osphere    Ground or
diffusion model, historical   Roof Top
data, emission density, and
representative of population
exposure.
                                        Same  as above
Same as above

Representing area of high
traffic.density, slow
moving traffic & obstruc-
tions to air flow (till
buildings) & pedestrian
population such as nnjor
downtown traffic inter-
sections.  1C-15 feet:
from street curb.

Representing area of high
traffic density, but not
adjacent to major thorough-
fares,  in center-city or
suburban areas.  (>50 feet
from street c-urb).
Ground or
Roof Top

Roof Top

Ground
                                                Ground or
                                                Roof Top
VERTICAL CLEARANCE
'ABOVE SUPPORTING
STRUCTURE. FEF.T

      10-15
      10-15
HORIZONTAL CLEARAXC;
BEYOND SUPPORTING
STRUCTURE. FEETa

       '> 5
       >5
       10-15
       10-15

       5-10

       5-10
                   10-15

-------
-'uble 4.  SITING GUIDELINES FOR AREAS OF ESTIMATED MAXIMUM IOLLUTANT CONCENTRATIONS  (CONTINUED)
 •T.LUTANT CATEGORY    POLLUTANT
 :condary Pollutant    Oxidants
NO-
STATION LOCATION
Representing resldcr.cial
arcn downwind of dovntown
area (5-15 niilcs frcn down-
town and > 300 feet from
major traffic articrJc-s or
parking areas).

Same as above
                                                                                     POSITION 0? AIR INLET
SUPPORTING  VERTICAL CLEARANCE  HORIZONTAL CLEARAKCI
Sr-VJCTUR'-:   A20VE  SUPPORTING    BIJYCXD SUPPORTING
            S'f]vUCT"J]\K,  FEET     STRUCTUIyE^ FHETa
Ground or
Roof Top
                                                                      Ground or
                                                                      Roof Top
                                                                   10-15
                                                                   10-15
                  10-15
                  10-15
> 5
> 5
                                                                                                                            Ul
                                                                                                                            is;
   Not applicable where air  inlet  is  located above supporting structure.

   Downwind of prevailing daytime  wind  direction during oxd.dr.nt season.

   When  standard reference method  (or equivalent) is suggested.

-------
                              33
5.   REFERENCES
1.  Guidelines:  Air Quality Surveillance Networks,  AP-98,  U.S.
    Environmental Protection Agency,  Research Triangle Park,
    North Carolina, May 1971.

2.  Guidelines for Technical Services of a State Air Pollution
    Control Agency, APTD-1347, U.S. Environmental Protection
    Agency, Research Triangle Park, North Carolina,  November
    1972.

3.  OAQPS Guideline Series, Number 1.2-007, Air Quality Moni-
    toring Interim Guidance, Monitoring and Data Analysis
    Division, August 1973.

4.  A Contribution to the Problem of Placement of Air Pollution
    Samplers, NBS 10284, National Bureau of Standards, U.S.
    Department of Commerce, Washington, D.C., May 1970.

5.  Akland, J., Design of Sampling Schedules, JAPCA  22(4),
    April 1972,

6.  Hunt, W.F., The Precision Associated with the Sampling  Fre-
    quency of Log Normally Distributed Air Pollutant Measure-
    ments, JAPCA 22(9), September 1972.

7.  Briggs,G.A., Plume Rise, Atomic Energy Commission, Oak
    Ridge, Tennessee, 1969.

-------
                                                  APPENDIX A
ATMOSPHERIC
                                                     0F  fllE tJNiyED  STATES
 DEPARTMENT  OF  HEALTH,  EDO-

      CATION,  AND WELFARE
       Office of the  S«cr*lory

 AIR  POUUTION PREVENTION AND
              CONTROL

   Definition of  Atmospheric  Areat
  Notice is hereby given that, pursuant to
section 107(*> U> of the Clean Air Act. as
amended by the  Air Quality Act oJ 1B67
(Public Law 8t>-]48>. the  Atmospheric
area* of the Nation are defined as set out
below  on the  basis of these conditions
which aDect the Interchange and diffu-
sion of pollutants In .the atmosphere.
  Important meteoroloirlttJ parameters
that eSect the Interchange and diffusion
of airborne pollutants  arc the frequency.
persistence,  and height  variation  of
stable (inversion) layers of air and speed
and direction of find. Accordingly, the
boundaries  of the Atmospheric areas are
based  on annual averages  of  (a)  low-
level Inversion frequency.  area, that is.
a history of the experience of air move-
ments as it relates to the dilution of pol-
lutants. This concept of  dilution  clima-
tology is embodied in the High Air Pollu-
tion Potential  Advisory System.
Initialed by  the National  Center lor Air
                  Pollution Control (NCAPC) in the earl-
                  em Qnlltd States in I860 and the western
                  United States in 1963, and now Adminis-
                  tered by  the  Environmental  Science
                  Services  Administration  (ESSA).  Tht:
                  HAPP Advisory System provides ft fort-
                  cast of weather conditions conducive to
                  the accumulation of  air pollutants over
                  large areas, a  latter which  WAS con-
                  sidered In the definition of these Atmos-
                  pheric ureas.
                    Because cf the direct relationship of
                  the area boundaries to the averr.i:e me:-
                  teorological  conditions  of  larEe-scaSe
                  areas, these boundaries do not necetsariiv
                  reflect the  actuaj meteorology  in  tin-
                  Immediate vicinity of the  boundaries. In
                  other words, there will alu-avs be special
                  "boundary conditions" characterised by
                  the movement of  tiir, together v,'ith air-
                  borne pollutants, across  the .boundary.
                  The boundaries are shown  as rones oi>
                  the map in order to reflect this boundary
                  condition.
                    Furthermore, since the boundary  be-
                  tween any two areas is defined by  average
                  annual conditions, it Is transitory on the
                  basis of shorter period (e.g., seasons! or
                  diurnal)   variations  in   meteorological
                  conditions, with the  result that Pi;u-
                  burgh. for exafnple. i.'.  under the influence
                  of the average dilution climatology of the
                  Appalachian Atmospheric area  during
                  certain tunes of thr year  and under  ttie
                  Influence of the Great Lakes-Northeast
                  Atmospheric area at  other times during
                  the year. Similarly. Portlc.nd, Ore's.. New
                  York City, or any other place in the near
vlcinlty of an Atmospheric ana bound-
ary, could be under  the influence ol a'
neichborinc  Atmospheric  area during
certain periods.
  Major topographical f cot urea are alao
reflected in  the delineation  of Atmos-
pheric nreas. The eastern boundary ol
the two Atmospheric areas on the West
Coast lies for the msai part at the 2.000-
to 3.000-foot elevation contour interval
on the western  slope of th« first major
mountain chtUn, antl It marks In gen-
eral  the Inlfijid extent  of Uie  laajor
inliiience of mnrittine air. The boundary
between the Rceiy Mountain Aj«a nnd
the  Great  Plain*  Area  is  esscr.Mally
located at the 3.000- to 4.000-fpot eleva-
tion contour interval. Tile cflccts of the
Great Lakes and the Appalachian Moun-
tains art npoarcnt  In th* location of
boundaries between Atmospheric nreas
In the ebftern United States.
  A  brief description of  each Atmoi-
phcric tree Is given in th« attach?d U.ble.
including the geographical extent o:' each
area and the major characteristics of the
dilution climate. Definition of Atmos-
pheric areaa outside  of the contiguous
United States has betn deferred.
  The existence of Atmosphsric  ureas,
o4 defined herein, does not in any way
limit the designation of Air Quality Con-
trol  rccioiis pursuant  to  secUon  107
(a>(2> of the Clean Air Act, as amended.
  Dated: January 8. 1968.
  I SEAL 1         JORW W. GARDNER,
                         Secretary.
               ':£$:#A"^ r ATMOSPHERIC AREAS 0? THE  UNITED STATES
                                                       >• Cttan Air>et',.mom«xJo4 1
                  ,
  ;^' '.-,.; -AREA.-  *"
  :ALIFORN;A
   OREGON
   COASTAL  f  ;".'•-.
     AREA
                        V J :l-;f*& \ '-i^i^T^^F^T LAKES -NO^^IjT/^-4-^


                        :/.:^^..;,v.4 :: V.'^ -;\.| |;'. "frvj /^- ''"* :•>§&;>:.I:-,'"i

-------
                                                          A-2
                      Atmospheric  Areas   of   the  United  States
                                                                       NOTICES
  Dwcmxrrav or AYMMPB^IIC AMAI  AMD  Tana CRA&ACTBKIVTICB, AIM  QOAUTt  Act  or  1987,
                                          ftaCTIOJI  10T (A) (I)
                                      Extcottfm*
                                                                                       topogrmpble*!
Caiifereta-Oraaoa


Vaftt&ftao cowtal
 Ore* ?Ub» BTM	.«
 Gnat Lakw-Nerthwct
Appalachian ana	
Id 14-AUantlc ooattal ar*a
fiouthrvxldai
                          Xxt*nd» About 50 to to nO«t InJaad from
                            tin Pacific Oo**a.
                           itAndj about 20 to 10 mQ*a tnU.nd from
                           lha  £*cffci fioond rerun, iwn "wticft
                           Lfc<  a*3i*ra  boundary fciletiila tcuvu*
                           «e$rw»rd to mo vicinity  of teWair
                           oc ii« Colombia Rlvar and  then vert*
                           irard to ilMt»a«t.
                          Extand* «ao£vvd  from th« Calttrruia-
                           Qrwon and Vv nhtoftoo accaf&l ri^M . to
  cr&t
  of thft
  cuurn
                                o   bonndtry.
                                lni tr tbc 3,0:30. to^.o.^^X'Ji
                                v-ii contour iJjtarrot tT.'.rit in
                                         mounUin  ri^-iv o.  Thu
                                             «m;ch.t4 t.^.ai  Uve
                                            In  ?^ont«.n» m
                                                   «rVy Heua-
                                                 i UJv>f w
      j-n  N«w Meria>. tn tr e
        .  to taduda Lt» Bl^ i'itod ir«>oa
  of Ttii*.
  itand* HMrt^rvd frcra tis»
  Uui irm to the Mlw-wip
  0( Ml:ac>art; to  tha  ijora.  :t
  rtifwt  o/ Ullnola, *,*uh*'»ai.«-n
  BDutr.wtatAm WU'.-crj^n, &*id  rJ>  tut
  extreme owihewt Mlui«toiA.
In  »d dill era to re«IaDJ
  Orru  I^ton,  t!iu  «
  nonbera tvoihlrcis
                                                  the
                                                        to  th«
                                                        'ci  taa
                                                        &;n ot
                     .         .
          area of jicri.;iwwUTti  ^^
        all  o( Ha-if  Ycnt EIM^ t
  6rtJtm« •outhera p*:t of the  H
  Rir« Vf.Uey,  and i>.« N«w  r.n^ tnd
  6t»i« Dortb of t^a Coaaea^c
  Uifcnd co«*-
  iTltmrua, eutcrn Vtr;irJft u> ilw Ati
  tlo  ccxuttlne  M  Ih«  i^ovJh  Curaa
  bordtf  u  correlative lor u>» tncii r.
  Wltti tLe 20O to fr,O-.'iMl OF^JI  .*%» level
  contour irtwrmi. TLu  ecr.v^ir bi-m-r
  M th* (ootniilj of ttn. u;u« Kui^a iVou
  Uin Rwiffa dUtlnjru'j^na l^-> r?.lfcOTe[
  flM  ocuuh&i piMa 10 th,j r.-ut turn t
                                   O:w»rd to U«> Ocli (.; Mexico.
                                     oarusera i1cnr*K,  *nj  U
                                   la UH w*at and uortn by two
                                                         plain
                                      tii»
                          from  tia*niB »u;bw«
                          Out, Inc-Judlnf th« Ne»
                          Lory; Uiimd re^io-a. '^-
                          fioutb Ctrolla* border
                          •jjd «.tt«Ddj lulfcuil to
                          it«ndt touth trcm th«
                          C«dv nee? tin* to inciudj Ui* t
                          hii/ of Florida.
                                                                     preV«Uin(t
                                                                    ptn«: lu;o-
                                                                    Ulkt^m  la
                                          cur.itfci Ta;;^y» &nd b*Htii.  «.
                                          »«nttBtx>r>.  cincOlneca.  acd relaUvriy
                                          L'tu wj>1» 4» duicu'.ant f,^turt4 0! ti«
                                          t.Hrn,.>, fc-ii\;h  d'.iiUifUlsiMA  into ws*
                                          ::on t;-,<) ii-i,tv-«nt KYM. b'-cta; ;»;-,i»[tT
                                          n  tr-rji-ri-.t,  pcrtlcnUiny COI'T-S *t:iU*
                                          ttAd a'.x't.'is i'tJLtoru;  Ltta  bvju^it ti-cnn
                                          p*.(jiir« rav.i.tr,  tn a tot* cocurrvcr^ o{
                                          p.!-f*l?:-*fti 'ji-i^ntiiioft.
                                          oTOirr&f-i;^  r-:r.ukU>n,  rhannxUnf  of
                                                                 {f th« JJifrnxjo
                                                                 f  t&« diiutioa
                                                                 Belatlr«ly  fiu  terrain,  which  stretchw
                                                                   Crxtn ttft CtiftdlJUi txvtler to tho UuU of
                                                                   Mftisco.  c*i-iJ'M't«ni«e  Hit  t'fpofTi'^P^y.
                                                                   Vhs rjiluU^M cw.ijut* ui cCwciH.eru*.! by
                                                                    .
                                                                 (Ion »:ni 1.-0 freouoiU oocarrtTiw ol nsi»-
                                                                 clTcly t;Jf -ft viinoJ with rrpiuiy cnfcjQjio^
                                                                 rae'.vo-'cU^.' J»l coodlnons.
                                                                 h» m*t<**r;:»:*7 ts chcrfcjsefUxrf  by &*
                                                                 qatit  s-.L-.-ir.r* piflMRfci  x'itA  atic!>da&t
                                                                 bU;» H»Uitl\ w;3  ^cn"»nlly T^"4 di»!n!oa
                                                                 condit'.n:.^, fJun^t tUt s;,r;r^ ati-J mfly
                                                                 niTonier  r.-xiiha. « tails  tl-3«u^ torn
                                                                 over I?:P fx-,U wusn cJ tha Or*n I.ucft*
                                                                 tud  AllRT.la Occ<*o caiiiuloA low-ltTftl
                                                                  too tot oi

                                                                 IVcIr.cnl
                                                                           LJ
                                                                           iveturta of tb« dilution
                                                                           r.^-t »UiJ spc^Ji Mid UM most
                                                                           j;a^r.bLlon  cor.^.t^loiis  of &ay
                                                                           i o( th« Hocky Mouuuuu.
                                       GhaUow mltlnf depths, leu tr*qacnt k>v-
                                         kThl siJili'isty nod blgiwr  wtad
                                         tre fr,;'.Hires of tb« dUutVon ciliuat
                                         t:i*.t'ji7auo tbU couUJ area Irom
                                         adjacent.
                                       Tb* dlm\t« of tht* arm
                                              tu-moflne la B
                                               tlo&  Is  pticilcaUy  nci-.v:i;*i*at
                                               U b iiUAil frc^cenejr of i'jw-ts»«i

-------
                 ATTACIJME.NT

             ADDITIONAL ATMOSPHERIC AREA?
Atmospheric Area

South Coastal Alaska
North and  Central
Alaska
Tropical
  Hawaiian  Islands
  Guam
  Puerto  Rico
  American  Samoa
Extent of Area

From southern tip
along coast up to
30 miles inland
to mouth of Yukon
River
The part of Alaska
excluding  the
south coastal
section.
Entire areas.
Meteorological and
Topographical
Characteristics

Maritime air prevails
with light  to moderate
winds along with
greater frequency of
fog, cloudiness and
precipitation and less
low level stability
than inland and nor-
thern sections.

Characterized by •
lengthy periods of very
strong and persistent
inversions in  the cold
season.   Long  Alaskan
nights almost  eliminate
the  diurnal cycle of  in-
version - lapse conditic
typical  of lower latitiid
Attendant inversion
winds  are quite low.
Storms are less frequent
than in South  Coastal
Alaska-.

The climate is predom-
inately tropical  marine;
atmospheric stagnations
are practically nonex-
istent; small incidences
of low level stability
except in topographically
protected inland areas.
Relatively  good vertical
mixing prevails.

-------
                                B-l
                     .   APPENDIX B
    The following are several possible: methods fcr determining
a more adequate number of stations for an. AQCR as contrasted tc
the- minimum required based on varying levels of information.
Note that the actual number of stations finally decided upon for
a Region should be the result of temper!nc the derived number by
practical considerations, resources available, fuel use patterns»
and source configurations.  Also the total adequate number of
monitors is found by summing tha number in-cessary fcr the urban
area together with those needed for isolated point sources dis-
cussed in Section 3.5.
    a-   Method A Isopleth Haps (SC2 and TSP Only)
    An adequate number of stations ten be .approximated from in-
formation on existing levels of pollution- as a function of the area
of the region.  Isopleth maps resulting from diffusion models
(See Appendix D) are useful in this determination..  At the present
time, use of this mathematical abroach is limited to the design of
the monitoring networks for suspended particulates and sulfur dioxide.
    The equation for estimating adequate network size relates the
number of stations to the degree of pollution and the land area of
the region.  It is based on tho fact that more stations are needed
in zones where ambient air pollutant con a.-ntr aliens may be expected
to exceed the ambient air quality standards.  The equation ccnr.idsrs
distinct areas:   the area., X, where the pollution levels arc higher
than the ambient air quality standard; the area, Y, where pollution

-------
levels are above background but lower, than the standard; and the area,
Z, where existing concentrations are at background levels.  In these
equations all  air quality data are expressed in terms of annual. -aye rages.
The total number of samplers, N, required for the  entire region is ob-
tained by summing the  estimated numbers of samplers  for each of the three
subareas:-
     "•vvx
The subareas are described as follows:
     N  = 0.0965      Cm " Cs   X
     N  = 0.0096      Cs " Cb
                      Cs
     N2 = 0.0004  Z
Where:
                                                                  ' '    3
     Cm = Value of maximum isopleth (with a contour  interval of 10),yg/m
                                           3
     C   = Ambient air quality standard, yg/m  annual average.
      •}
     Cr  = Value of the minimum isopleth (with a  contour interval of 10),
              ">
         V g/m^ annual average
     X   = Area wherein concentrations are higher than ambient air quality
                     p
          standard, km
     Y   = Area wherein concentrations are above  background but less then
                             p
          ambient standard, km
                                                                2
     Z   = Area wherein concentrations are at background levels, km
Estimated background values for total suspended  participates and Sp

-------
                       TABLE 1
    TSP AND SO2 VALUES FOR NONURBAN BACKGROUND TERM
                              •"\                V\.
                     Proximate     Intermediate     Remote0
Total suspended       ,  45              40            20
  particulate
Sulfur dioxide          20   '   •        10
5
 Proximate values based upon NASN stations in the following
 states:  Connecticut, Delaware, District of Columbia, Maryland,
 Massachusetts, New Jersey, New York, Pennsylvania, Rhode islanc


 Intermediate values 'for all other states.

c
 Remote values based upon NASN stations, in the following states
 Colorado, Idaho, Minnesota, Montana, Nebraska, Nevada,
 New Hampshire, New Mexico, North Dakota, Utah, VJisconsin,
 Wyoming.

-------
                                B-4
for use when isopleth information is not available are listed in Table 1.
     Use of these equations requires the division of the region into three
zones on the basis of iso-intensity lines, representing the ambient air
quality standard and the background value appropriate for the region.  The
land areas of each zone are determined from the isopleth map, as are the
maximum and minimum concentrations in the region.  The above equations
should not be used to estimate the numbers of background stations where
regions encoirpass large unpopulated areas.  No more than two or three
background stations should be necessary in any region.
     The equation for determining number of stations was derived from
an analysis of the relationship between pollution levels and patterns,
geometric distribution of sources, meteorology, and land area in the
National Capital Interstate Air Quality Control Region.   The equation
was applied to several other cities in the United States with various
population and pollutant distributions.  As mentioned earlier, it is
applicable only to SOg and TSP networks.
     An application of the above to Washington, D.C. data for suspended
particulate matter yields-the following:
                              Cm = 100  g/m3
                              Cs =  75  g/m3
                              Cb =  40  g/m3
                              X  - 417 Km2
                              Y  = 3032 Km2
                              Z  - 2231 Km2

-------
     N  * 0.0965 (W * 7§) 417
      •         '      75	    '  •
        » 13
     Nw = 0.0096 (75 -'40) 3889
      y              75
        = 17
     Nz =-.0004 .(2231)
        _ i
     N  = N  + N  + N
     "    NX   ny   NZ
        = 13+17+1
        = 31
     b-   Method B Multiplication Factors (S02> TSP, Oxidants, N02)
     If past air quality ai\d/or model Information are not available,  then  the
adequate number of monitoring stations for particulates, sulfur dioxide,
                                     t
nitrogen dioxide, and oxidants can be determined by adjusting the mini-
mum number through a multiplication process with factors which influence
air quality levels discussed in Section 3.1.  The procedure is outlined
below:
     Np = (TF x CF) X Mp ^
where N  = adequate number of stations required for a given pollutant
     Tp = Topography Factor
     Cp = Climatology Factor
     Mp = Minimum number of monitoring stations for a particular
          pollutant (from Table 1 Section 3.2)

-------
                      TOPOGRAPHY FACTOR

Regime                Description                Factor

Valley-ridge          Continuous contours         1.8
                      of greater than 300
                      feet between a valley
                      and a ridge within a
                      mile of the horizontal
                      distance

Hilly-                Terrain elevations          1.5
mountainous           greater than 800-1000
                      feet between hills or
                      mountains and valley
                      floor

Shoreline             Bodies of water of a        1.2
                      size at least equal
                      to the Great Salt Lake

Level or              No marked contours  -        1.0
gently rolling        or shorelines


     These topographic factors are relative numbers based on the factors

influencing air quality discussed in the previous section for each of the

regimes listed.  The description used should describe the urban area of

the AQCR or where the worst pollution areas are located rather than the

entire sampling area to be covered.  It may be necessary to subdivide the

AQCR if the topographic features are significantly variable.

-------
                                       •••: •-'-•••'••-- •^•••" "•;•- '- -  '^' -- Ifc.,-, .,..-
                                       ''
                       CLIMATOLOGY FACTOR

Atmospheric Area9      *  '     Short-Termb       Long-Term^

California-Oregon                2.0               1.6
  coastal
Washington. coastal               1.4               1.4
Rocky Mountain                   2.0               1.1
Great Plains                     1.0               1.0
Great Lakes-Northeast            1.1               1.4
Appalachian                      1.6               1.4
Mid-Atlantic coastal             1.4               1.0
South Florida                    1.0               1.0
Tropical         .                1.0               1.0
South Coastal Alaska             1.5               1.5
North and Central Alaska         2.0               1.8

Note:.  The use of the short and long-term factors should  be  according

to the particular pollutant for which the network is  being designed.

               Pollutant             factor

               Nitrogen dioxide      Long-term

               Sulfur dioxide        Short-term; long-term

               Suspended             Short-term; long-term
                 particulates

               Oxidants              Short-term
                           f
     For sulfur dioxide and particulates, the choice  of factor  should

be based on which one is  quantitatively grpater in  the  particular

Atmospheric Area being considered.
a See Appendix A

b Based on isopleths of total  number of forecast-days of high meteorological
  potential for air pollution  in a 5-ytar period.   (Holzworth, AP-101,  1972
  (Fig. 71})

c Based on a consideration of  ranking average ventilation factors  (Holzworth,
  AP-101, 1972 (Table 3))

-------
                               B-8
    As an example, the determination of an adequate number of sulfur
dioxide samplers for a Region with the follov.'ing characteristics is as
follows:
    Population = 7,800,000
    Topography = shoreline
    Atmospheric Area = Mid-Atlantic coastal
    Tp (shoreline) =1.2
    Cp (Mid-Atlantic ccastal) = 1.4 (short-term is  higher)
    Mp (sulfur dioxide)  = 6 + 0.05 per ICC,COO population
                        = 6 + 0.05 (78)
                        = 10
                        = \1.2 x 1.4)  x  10
    f1'
    'sulfur dioxide     _ -,

-------
                         \t- I
                       APPENDIX C

      SCREENING PROCEDURE* FOR DETERMINING THE NECESSITY
           OF MONITORING ELEVATED POINT SOURCES
     The screening procedure  in a  step-by-step manner is as follows:
Steps 1 through 4 are used  to determine plume rise for various  wind
speeds.  If there is more than 1 stack, each stack should be considered
separately through Step 8.  Step 5 determines the effective height of
emission for the various wind speeds.  Steps 6 through 8 determine
the maximum T-hour concentration from the source and Step 9 estimates
the concentration for a slightly longer averaging tima.   Step 10 es-
timates the total maximum concentration by adding the background to
that due to the point source.  Step 11 compares the estimated
maximum concentration with  the standard and the result indicates
whether or not the source exceeds  the" standard.  The required
source information is:
     Q = maximum emission rate at  peak production of the plant
         for the pollutant  considered, g sec"
     h = physical stack height above the ground,  m
     d = inside top diameter  of the stack, m.
     v = stack gas exit  velocity,, m sec"
     T = stack gas exit temperature, °K
   Abstracted from "A Sample ScYoening Technique for Estimating the
   Impact of a Point Source of Air  Pollution Re'lativa to the Air
   Quality Standards," D.B. Turnsr  and E.L. Martinez, EPA, April 1D73.
   This  paper  is  still  in  draft  form  and has  not been offi-
   cially cleared,  therefore1,  this  procedure  is  interim and
   subject to  some  later  revision.

-------
Step 1
     Find stack gas volume flow from:
        Vf = 0.785
Step 2
     Find the buoyancy flux parameter from:

                   Tc - 293
        F= 3.12 Vf -^	
                      s
Step 3
     Find the product of plume rise times wind speed by the
following:
        If F is less than 55:
            AH.   = 21.4 F 3/4
                 where AH is plume rise, m
                 and u is wind speed, m sec
        If F is greater than or equal to 55:
            AH.u  = 38.7 F3/5
Step 4
     Determine the plums rise,  H, for each of these five wind
                                         ii
speeds: 0.5, l.CL 2.0, 3.0, and 5.0 m sec
     These are found from:    /
            AVI  = (AH.u)/u

-------
                          C-3
Step 5
     Find  the effective height of emission, H, for each of the
above wind speeds.  H 1s in meters.
        H  = aH +  h
Step 6
     For each of  the 5 H's corresponding to the 5 wind speeds
estimate xu/Q from Figure  5 as a function of H.
Alternatively, each xu/Q can be estimated from the equation:
       xu/Q = a Hb
where a and b are as given In the following table for the appropriate
range of H.
Range of H
(meters)
10 to 20
20 to 50
50 to 100
100 to 2000
Step 7
a
0.05405
0.07537
0.03612
0.02164

b
-1.587
-1.698
-1.510
-1.399

     For each xu/Q found in Step 6, determine the x/Q corresponding
to each wind speed as follows:
        x/Q = xu/Q
               u                          ;
     If there is more than one stack being considered, Steps 1
                               /
through 8 must, be applied for each stack separately.  The values

-------
                           C-4
found for each stack in Step 8 are then added together.  This value
of the concentration can be considered a maximum for the 1-hour
averaging time.
Step 8
     Using the maximum of the five x/Q values found in Step 7,
find the concentration, xDk» due to this point source from:

        xpn(ugm~3) » 106 Q x/Q
Step 9
     If the above value is to be compared with an air quality
standard having a different averaging time, determine the x,  by
                                                           r
multiplying xPh by the appropriate value in the following table.

-------
                                                 C-5
             Figure 1.   Maximum xu^Q as a Function  of Effective  Height of
                           Emission,  H, where x  is  Concentration, u  is Wind
                           Speed,  and  Q  is Emission Rate.
      _2
   10 7o
                                          m
        -i-4-ft-.
           |4T
           ~!
                                                                                 EtE
        a^.
                                 ---I—
                                       ~y~r;;i4'll- "
                                       ™r.rrr.t.t:-
   10
                                  --!:-!
        -:-.-V-i-v-	 [•- 	|--=! ]

        -7-'"t-M T- -I--- j-~	h-rH
                     •-I H-J!--i
                                    rtrf™rr
                                     •h.-rr
                                         ^=
                                                     _
                                                  ••t—
 L V 3
i	i    ^
     x
I
 TJ 3
 Is- ;
                   ^::-|
                             I--:::}
                               zfo-

          -r-:--i-—
                mm
                   vfeti
        _:... ....:.,... ^. . j ... _Lj^.. . j \_--_- I -_• • i_- -1^_J;—I-  • h^j;-:-—

f
ao-fl
' o '"!'"
 O  3 (•—
 f:  8f~
                                                                   TP-
                                                           m
     .=£=;
                          -f__4_
                    ±:;V"h::;
                           \
       r
      .. I
      J r-
                :!•• -I-
.til
                    •^.••!-i;-:-:[:i:-:j:E:--

                                .piim^iTrii .-I-
                                                   in-r^;

                                                          .-_.j_...._.

                                                       • •: r
                                                        '••r~
                               •n

                                     ^^-l-ruvtj^:

                                     ~	-i—j.-^;.---f-...,.
                                                               :i^r^L;x;-^i
1:1:
                              f--i-^-F4-

                                                                                           J4i
                                                                                             .
                                                                 j .... ..;. .1..  . | .....,., . ... .
                                                                 •.|-.-.--.,i:..-.: :v!.:::|..,:-.-
                                                                  r..., ..,_.__....„-.... . .._.
                                                                 '•"'  ;
10
                                     • 1
                                   i	.i	)	
                                                                                        ^ .,-,- .
                                                                                          rt--h-r-
                                                                                          ^•i . n:.,--;
                                                                  n
                          4   !>  f. 7 a s ;c
                                                         4   5678'.' 10
                                                                                             6 7 8  a !C
                            50
                                   100
              200  300
                                      Effective Height,  H  (meters)

-------
                                      C-6
                            Figure  1,  Continued
                                            H£=
    Trm •---j- "' ••;-;• —[---i-- r
                    -~;)••  \i, r:i
                    H—~V-j—j-
                                          j_ii^iii
                                          •••;--; -• i  -
                                                    TTT - •:-••-1. ~
                                                    •   I   L..L. J.   :
             lilillliiEa^

                                  TT™

                                                                              —f-'-H
                                                                       J^lii
                                                 s
                                                                            I  - 1
10-
  6


  7


  6



  5



  4






 >

 X




  2
            IZH±tl
                                       .1... i.
     ±z:_h
'•rio -

 8  9
' 6


u  !

                                      u_X-_i^;:
                                      ..t..:. v i
                                               t~'i -
                ]    '•   '
                                       • • •  j ,  , .. .j. . !
                                                         .l..i -..I.
                                                       -h
                       ••i :.l_.:^_L.Li^^
                         , |-|.-: -•..;.(


                  ^

                         -- I7
                      -
               •- •••


                      i •.-.-.I
                      "   ""
                     |- j -
ssflii^^Oi^i^^^
	^•M.-..:...,....-.,	i. ..t... !....L.fI.J-!:
                                                            -I-
                                                                  I
                                            ^rHS
                                  ..'.17i_:li.L.j	T.......
                                                                           .'m-
                                                                            i	| „.

                 . I .. I. .

              :-:-:--|:-i-r

                                                                —.:'—T-
                                              ••-]-.. ip-pr^j;...:

                                                ;: .j...±.hj:h..
                                                                        —4 -.
                                                                         .• .. j .
                                                                           .

                                          ^'^""rttn^l'-ssj:-^

                                                                   :J.
                       .•
                                       t::.-;-:7
io-t^±r:
   1io
                                                                       :|::::!.:T
                                                                       LlL-Lii
                                    2bo 3 o    5  'boo   2ot


                               Effective Height,  H (meters)

-------
                             C-7
      Averaging  Time                        Correction
          1  hour  .                            1.0
          3  hours                               0.75
         24  hours                               0.25
 Step  10
      Find the quantity xm,v> where  B  is  the maximum expected back-
                        max
 ground concentration of the pollutant considered for the averaging
 time  and  frequency of occurrence of the  standard within a 10 kilometer
 radius of the source considered, that is,  due  to other sources than
 the one  being considered, and XD is the  maximum short-term concentra-
 tion  from the point source from Step  9.
                        x    = B ^  Y
                        "max        Ap
 Step  11
                                                   -3
      S is the short-term air quality  standard  (pg m  ).  If xmau is
                                                             max
 less  than 1/2 S, it is probable that  the source considered will not
 cause concentrations exceeding the  short-term  air quality standard
 and therefore source monitoring is  not required.
     If x -,« is roore than 2S, it is almost certain that the source
         max
concerned will cause concentrations exceeding the short-term standard
and therefore source monitoring should be undertaken.
     !f x.^v, is more tlian V2S but less than 2S, more detailed analysis
         inciX
of the impact of this source upon air quality should be performed to
determine if source monitoring ii required.

-------
                             C-8.
     An example of this procedure 1s as follows:
     A source emits sulfur dioxide at a rate of 1200 grams per
second from a stack which is 100 meters high and has an inside
diameter of 3 meters.  The stack gas velocity is 7.6 meters per
second and the stack gas temperature is 420°F (489° Kelvin).  Sho
Should monitoring be recommended for this plant?
a.  Compute the stack gas volume flow from:
     V = 0.785 V$d2 = (0.785) (7.6) (3)2 - 53.7 m3/sec
b.  Compute the buoyancy flux F = 3.12 V /l-_a.v  Assume ambient
    temperature is 68°F = 293K.  F = (3.12) (53.7) (1- SI-) =
    67.2 m4/sec3
c.  Since F is greater than 55, AH.u = 38.7 F3/5 = (38.7)(67.2)3/5=
         2
    483 m /sec
d.  Determine plume rise for each of five wind speeds:
    (1)  u = 0.5, AH = (AH,u)/u = 483/.05 = 966m
    (2)  u = 1.0, AH = 483/1 = 483m
    (3)  u = 2.0, AH = 433/2 = 242m
    (4)  u = 3.0, AH = 483/3 « 161m
    (5)  u = 5.0, AH = 483/5 = 97m
e.  Find the effective height of emission (plume height) H = AH *• h,
                                         *
    for each wind spsed
    (1)  556 + 100 = 1066
    (2)  483 -f 100 = 583
    (3)  242 + 100 « 342

-------
                             C-9
    (4)  161 + 100 = 261
    (5)  97 + 100 = 197
f.  Estimate xu/Q from Figure 4 for each wind speed, and divide by u
    in each case to get x/Q:
    (1)  (1.25'10"6)/(0.5) = 2.5 X 10"6
    (2)  (2.9'10"6)/(1.0) = 2.9 X 10"6
    (3)  (6.2'10~6)/(2.0) = 3.1 X 10~6
    (4)  (9.5'10~6)/(3.0) = 3.1 X 10~6
    (5)  (13.6'10"6)/(5.0) = 2.7 X 10"6
g.  The maximum x/Q in the above step is 3.1  X 10.  Using this
    value,  and a Q of 1200 g/sec.   * Cx/Q](Q) = (3.1  X 10"6)  (1200)
                               . '   = 3700'10"6g/m3 =  3700 vg/m3.
Since this value (3700) is more than 1/2S (or 1300) but less
than 2S (or 5200), a more detailed analysis of the  impact of this
source should be performed for air monitoring purposes.

-------

                                  D-l
                              APPENDIX D
                COMPUTERIZED ATMOSPHERIC DIFFUSION MODELS
                          AVAILABLE FROM EPA

     Numerous variations of atmospheric diffusion models exist which may
be utilized in the design of air quality monitoring networks.   The Air
Quality Display Model (AQDM) is suitable for the long-term, urban appli-
cations involving sulfur oxides and particulate matter.   Other models
are available including those in the EPA UNAMAP system designed for inter-
active remote computer terminal operation and are readily available to
EPA Regional Offices.  The latest UNAMAP catalog of models, v/ith a brief
description of each, is presented below.  A comprehensive air  quality
modeling guideline is presently being developed by the Monitoring and
Data Analysis Division.
     There are no models which adequately describe the source-receptor-
relationship for photochemical air pollutants.  A few models of this
type are under development and some may be available in  the near future.

-------
GUIDELINE  SERIES
          OAQPS NO.  .1.2-016
      GUIDELINES FOR DESIGNATION OF




      AIR QUALITY MAINTENANCE AREAS
    . ENVIRONMENTAL PROTECTION AGENCY
    Office of Air Quality Planning and Standards





      Research Triangle Park, North Carolina

-------
                                                          OAQPS  Guideline
                    GUIDELINES  FOR DESIGNATION  OF
                    AIR QUALITY MAINTENANCE  AREAS
                    Standards  Implementation  Branch
                 Control  Programs Development Division
              Office of Air Quality Planning  and Standards
                 U.  S.  Environmental  Protection Agency

                         January 11,  1974
iJOTE:  Revisions and additions at end

-------
                    Preface

     These guidelines are presented herein in their final  form.
Although a "Second Draft" dated December 21, 1973, had been
circulated, it contained only the  first  three  sections.  The
first three sections  with minor revisions  are  enclosed herein with
the  remainder of the guidelines for completeness.   The revisions
of the first three sections are:
     (a)  The Table of Contents was revised to include three
          Appendices
     (b)  In the flow diagram on p. II-l, the reapplication of
          the initial designation criteria has been eliminated.
     (c)  On p. II-3, in the list of types of areas which  might
          be used for designation, '^counties" is takenout  of the
          heading "groupings of," since a single county could,
          in some cases be designated as an AQMA.
     (d)  On p. III-l, reference to the reapplication of the
          initial designation criteria has been deleted.
     (e)   On p.  III-l  and III-2, criteria related  to  air quality
          have been revised so that the  air quality data for the
          past two years must be considered in applying the criteria.
     To aid the reader in following the  techniques for projecting
emissions and air quality, three example calculations are  presented
in Appendix B for a hypothetical area to determine whether the area
has  the potential for violating a NAAQS within 10 year.
     To aid the States in estimating future manpower requirements
for  the maintenance of standards program, Appendix C contains a list
of tasks anticipated within the coming year and a half.

-------
                TABLE  OF  CONTENTS
  I.   Background and  Introduction
 II.   General  Instructions  and  Discussion
III.   Initial  Designation Criteria
 IV.   Method of Projecting  Emissions
  V.   Instructions  for Modeling Air Quality Concentrations
 VI.   Projections of  Demographic and  Economic  Indicators by SMSA
  Appendix A - Basis  for  Initial Designation Criteria
  Appendix B - Example of Analyses for a Hypothetical SMSA Employing
               the  "Back-Up"  Method of Estimating Emissions
  Appendix C - List of Tasks  to be Performed for Maintenance of
               Standards  Program

-------
                          AIR QUALITY MAINTENANCE AREAS j  ,

1.   Background and introducti on
    Pursuant to 40 CFR 51.12(e), published on June 18,  1973,  in  the  Federal
    Register, Volume 38, P.  15834, all  State implementation plans  ".  .  .
    shall identify those areas (counties, urbanized areas, standard
    metropolitan statistical  areas, et cetera) which,  due  to  current air
    quality and/or project growth rate, may have  the potential  for
    exceeding any national standard within the subsequent  10-year  period."
    After areas  are identified by the States, EPA will  review  these
    designations and will r,repare an official list of  areas  by  June 1974.
    For these areas, the States must then perform a thorough  air quality
    analysis of each of these  areas ; where this  analysis  shows  that an
     oreowill definitely not maintain a NAAQS during the 10-year period,
    a plan must be developed for that  area  which demonstrates  that  the
    standard will be maintained.
    As stated in the preamble to the above-cited  rulemaking,  EPA intends  to
    provide assistance to the States in
         a.   identifying the areas (for reference, "air quality  maintenance
             areas" - AQMA's) which may exceed a  national  standard within
             the next ten years, and
         b.   analyzing the impact of growth and development on  air quality  in
             such problem areas.

     These present guidelines are to assist the States  in  identifying AQMA's
and do not require as extensive an analysis as will the guidelines for
analyzing the impact of growth which will be issued in the Spring  of 1974;
guidelines for preparation of plans for maintenance of air quality will be
issued in late summer of 1974.  The overall timetable  for  plan  development
with regard to 40 CFR 51.12, paragraphs (e) through (h) is:
     March 18,'1974      State submission of identification of AQMA's
     June 18,  1974       EPA  publication  of  list of AQMA's
     June 18,  1975       State submission of:
                         a.   impact on  air quality  of projected  growth  in
                             AQMA's
                         b.   where needed,  a plan  to prevent  any national
                             ambient air  quality  standards (NAAQS)  from

-------
                            being exceeded over the 10 year period from
                            the date of plan submittal.
A detailed timetable of State and EPA activity over the next two years
.'or trie maintenance of standards program is presented in Table  1-1.
    EPA intends that the guidelines be  easy to follow
yet still be sufficiently responsive to insure that as many appropriate
AQMA's as possible are designated without over-desigation.   Because of  the
complex nature of the tasks involved and because of the many uncertainties
inherent in tne projection of emissions and air quality, the guidelines
are written to obtain some degree of consistency in the information to  be
submitted by the States, while still allowing for innovative approaches.
    Prior to preparation of these guidelines, EPA consulted with several
State and local air pollution control agencies and regional planning com-
missions.  EPA has attempted to incorporate the,advice thus obtained in
these guidelines.  Although every attempt has been made to  anticipate and
address questions which may arises invariably unresolved issues will occur.
Where questions do arise it is recommended that the appropriate EPA Regional
Office be contacted for guidance.
    The guidelines for AQMA designation are written for the State agency
responsible for designation.  In most cases this will be the State air  pollu-
tion control  agency.  Because the impact of the provisions  for maintenance
of standards  will affect areas which are of concern to other State agencies
and local general purpose governments (such as those responsible for
regional land use and transportation planning, water pollution control, etc.),
it is advisable for the designating agency to solicit comment from these  agencies
and involve them in the designation process.
                               1-2

-------
Federal EPA Designation of AQMA's
    As indicated above, EPA will review the list of designated AQMA's
submitted by the States and will publish, after allowing for public
comment, an official list of AQMA's by June 1974.  Due to time and  manpower
constraints, EPA will not be able to analyze in detail  each  State  which
does not submit any material concerning AQMA  designations.   Consequently,
EPA's designation for States which do not offer a submission will  be on
the basis of SMSA's whose growth rates for particular demographic-economic
indicators exceed a specified value.  In addition, the present value of
the indicator, current air quality and the meteorological  conditions which
present a pollution potential would be incorporated in EPA's criteria  for
AQMA designation.  In most cases, actual emissions and air quality per se
would not be projected by EPA.  The critical growth rates  would be determined
as follows:
    a.  Percentage growth rates for population and earnings  by industrial
        category have been obtained on an SMSA basis for the years 1975-1985.
    b.  SMSA's have been listed by regional priority classification  for
        each pollutant and ranked by percentage growth rate for population
        and edrnings by industrial category.
    c.  Using best judgement, demographic-economic indicators would be
        selected as representative of each pollutant-source category combina-
        tion.
    d.  After scrutiny of the spread of growth rates, critical growth  rates
        would be selected using best judgement for each demographic-economic
        indicator corresponding to a pollutant-source category combination.
    The critical growth rates per demographic-economic indicator would vary
depending on the pollutant priority classification of the AQCR in which  the
                                1-3

-------
SMSA is located.  Thus, a lower critical  growth rate would be  specified
for those, areas having a currently significant air quality problem
(Priority I regions) than for those areas which do not have a  currently
significant air quality problem (Priority III  regions).
future Guidelines
    In addition to these guidelines on AQMA designation,  EPA will publish
two other sets of guidelines, one concerning the detailed analysis  and
projection of air quality for the AQMA's  and the other concerning the
development of a plan for maintenance of  NAAQS where needed.   These future
guidelines are briefly discussed below:

A.  Guidelines for AQMA Analysis
    The analysis step is intended to determine whether air quality  limits
are indeed threatened, and if so, when, where, and which  are the principal
sources involved.  The results of this analysis will be useful  in deter-
mining whether an SIP revision is necessary, and in formulating alternative
plans if they are needed.
    Descriptive analysis would proceed along the general  lines described
below concerning analytical  procedures for selecting AQMA's except  that
the analysis  would  be more thorough.  In particular, the following steps
would be followed:
    1.  The quantity of emission of each  pollutant for which the AQMA  is
        designated would be projected to  1985.  This projection would
        consider:
        a.  present emissions by source category and, if possible,  by
            location.
        b.  expected growth of each source category based on past trends
            and  highly probable  future contingencies.
                                1-4

-------
        c.  Present and highly probable future emission restrictions
            on new and existing sources.
    2.  The 1985 projected emission inventory would be allocated  to
        the land in the least desirable*  pattern which would be permitted
        under present land use restrictions.   This "scenario"  is  the  one
        which would result in the most centralized locations of new sources
        of emission.  Presf.it zoning patterns and land use  plans  would
        be used in allocating new sources to  the land.
    3.  1985 air quality would be estimated from the emission  pattern scenario,
        preferably using a calibrated diffusion model.   If  this is impossible
        in the time available, a less sophisticated model must be used.
    The models, emission factors, growth  projection techniques, etc.  suitable
for performing the analysis will be forthcoming in May of 1974.

B.  Guidelines for Development of Air Quality Maintenance Plans
    In late spring or early summer 1974,  EPA  will issue guidelines to  States
on the preparation and submittal of 10-year air quality maintenance plans.
These plans, which will be due on June 18, 1975, will  pertain  only to portions
of States designated as Air Quality Maintenance Areas  (AQMA's) by the Adminis-
trator in June 1974.  The guidelines will be  organized around  four subject
areas.  The first relates to the mechanics of preparing and implementing  the
plans.  Topics ranging from plan format to procedures  for categorizing  emis-
sion sources will be covered.  The second subject a.rea deals with the
evaluation of the air quality implications of local land use and  transportation
plans.  It may be discovered in some AQMA's that growth plans  are incompatible
with air quality maintenance, and need to be  revised.   The  third  subject  area
''Least desirable from an air quality maintenance  point of view
                              1-5

-------
will include a list of maintenance strategies.   Emission  allocations,
transportation controls, fuel  and energy conservation  measures,  and
other strategies will  be discussed, along with  procedures  to quantita-
tively estimate their impact on air quality.  The  final subject  area
will cover the coordination of air quality maintenance plans with other
environmental planning activities.  These include  water quality  planning
and L''ts review of environmental impact statements.
                                  1-6

-------
   >
   00
                  tn m
                  c -o
                  3 -h
                  fB rt
                   m
n
—i o
*"~* *TI
<:

-< 3
CO XD
r~> cr
m r~

I 3
m
   co
   §
   O
   to
                  e~> co
                  o «-t
                  3 Oi
                  rt rt
                  -1 I)
                  O
                  — ' o
                    o
                  -O 3
                  — ' Q.
                  01 C
                  3 n
                  in <-f
      ID >

      3 o.
      O — '
      3 V;
      rt l/i
                    3
                    O.
                    o
                   T3
                 "3
                 <

                 n>
                 O
O — 'T3
3   — <
C1- — 'OI
3-^^ 3
*/> (S3 t/1
                 XI CO
                 (B r+
                 < Ol
                 C3
                ' ro
             co 3
             C VI
  3
  — '• O
                 —i 70
                 o (o
                 -o <
                 t/l -<•
                   n>
                 co s
                 C t/>
                 CT
             3 r*
             O rt)
                 n> CD
                •   3
                •   a.
U2



CO
                 Now     •                           |


                 EPA  Issiwc_s_AQUA Guidelines for Designating  AQMA's and for
                   e s r i m; ting  manpower needs
                 Meet with  Federal  Agencies, State, Local  Government representative?
                             States  Submit Areas Designated as  AQMAs
                             EPA Begins Revision of State Designations and Development of
                               Designations where States Fail  to  Submit

                             Analysis  Guidelines to States  from EPA
                             EPA  Announces Hearings on Own Designations
                             EPA Holds Hearings on Own Designations
                             EPA Publishes Final List of AQMA's
                 Plan  Development Guidelines to States  from EPA
                 Plan  Development Regulations Proposed  in  Federal Register
                 Brief  Regional  Office on Plan Development
                             Final  Promulgation of Plan  Development Regulations
                             Draft  Plan Completed by States
                             States  Announce Hearings; Distribute  Plans
                             States  Hold Hearings
                             States  Submit Plans to EPA
                             EPA Starts Work on Plans for  States  that Fail to Submit
                               Approvable Plans
                             EPA Plan Approval/Disapproval  of State Plans
                             EPA Announces Hearings on  Own  Plans for States that Did  Not
                    Submit  Approvable Plans


                  EPA  Holds Hearings on Own Plans
                             EPA Promulgates Plans for  States  that have Not Submitted  Plans
                   1-7

-------
II.  General Instruction and Discussion                    !

     The general approach which this guideline  presents is depicted as

follows; the Roman numerals refer to the portions of the Guidelin*in which

that item is described:
     SMSA's automatically
     excluded as AQMA's «-
   SMSA1  excluded
   as  AQMA's
                              all  SMSA's
Apply initial
 designation
  criteria
    (III)
SMSA's automatically
included as AQMA's
                                       SMSA's neither automatically
                                       excluded or included
                             Predict 1985
                            emissions (l\l]
                              Predict 1985
                             air quality
 Determine if
  NAAQS's  are
  maintained
 .SMSA's  included
IK  AQMA's

-------
a';  beogrspiiical areai to be considered

    (I)  ThorT.' appear; to be a need to specify which areas, as a minimum,

    ^'iiould ';.•:• ari^sly^od in determining which areas are or are not to be

    '..esioncir.rt! as AQMA' r,.   The areas selected are the Standard Metropolitan

    Sr ;
-------
             constitute  the  boundaries  of  the  area.   Designation by ;currently
             defined  areas,  however,  does  not  mean that the subsequent detailed
             analysis of the AQMA  and possible control strategy must apply to the
             entire AQMA as  originally  designated—the analysis and plan can be
             restricted  to selected problem  areas within  the AQMA.  On the other
             hand, one should be aware  that  designated areas have been referenced
             in  the proposed regulations for review  of indirect sources in all but
             three States (38 F.R. ^9893,  Federal Register of  October 30, 1973).
             If  the regulation is  promulgated  as proposed, the size of facilities
             which would be  exempt from review will  be smaller in the designated
             areas  (AQMA's)  than in the non-designated areas.  Until EPA publishes
             the list of AQMA's   in  June  1974,  all SMSA's would, for purposes
             of  the proposed indirect source review  regulation, be considered
             designated  areas.
                  In  addition, one should  be aware of possible relationships between
             the designated  areas  (AQMA's) and the areas  to be chosen under the
             forthcoming regulations  concerning significant deterioration.  For
             instance, if the significant  deterioration regulations provide that  some
             (probably urban) areas are permitted to deteriorate up to the secondary
             national  ambient air  quality  standard,  these areas will probably be  the
             same areas  as the AQMA's.  Therefore, it might be appropriate to designate
             an  area  large enough  to  allow for the proper amount of desired growth.
                 A non-exhaustive  list  of types of areas  which might  be  used  for
            designation  include:
                 AQCR's
                 SMSA'S
                 Urbanized Areas
                 Counties
               fCities
Groupings of:  ^ Townships
               VJBoroughs

-------
     Planning regions used for transportation,  land use or other planning
     Sub-state planning districts
(2)  Designations should be pollutant-specific  and should indicate
the pollutants for which the area is designated.   The detailed analysis
required for each of the finally designated AQMA's would then be done
only on the basis of tnose pollutants which are identified as proolems
in exceeding air quality standards in the future.
(:)  Fo:- uniformity and to avoid proliferation  of designated AQMA's  a
single boundary for each AQMA should be chosen  regardless of the number
of pollutints for which a potential problem exists.  Actual  pollutant
problems within the area may overlap or be mutually exclusive (e.g.,
one part of an AQMA may experience growth in mobile source pollutants
while another part may suffer an increase in SC^ emissions from fuel
combustion), but only one AQMA should be designated which enclosed
all the problem areas of a particular geographic location.
(4)  In the case of SMSA's which cross State boundaries, the respective
States should coordinate their designations.  An SMSA constitutes, by
definition, "...for general economic and social purposes, a single
community...".  Therefore, it is recommended that, for an interstate
Si'lSA, one AQMA be designated jointly by the respective States.  It is highly
desirable that one single integrated plan be adopted by all  States involved.
However, if this is not practi cal then all State plans in interstate AQMA's
should be at least comoatible with one another.
     It may be, however, that one State's portion of an SMSA may
experience growth in emissions while the adjacent State's portion may
not; in this case, it may be desirable for the growth State to designate
an AQMA in (and/or around) its portion of the SMSA, but for the non-
growth State not to designate in its portion.  Obviously, one State
cannot designate an AQMA, a part of which is located in another State.
Interstate cooperation will be necessary to resolve any conflicts.

-------
(5)  Enclosed as an attachment to Part VI  of these Guidelines are
projections of demographic and economic activity for SMSA's prepared
by the U. S. Department of Commerce, Bureau of Economic Activity
(BEA).  BEA projections were made on the basis of SMSA's as they
existed as of January 7, 1972.  The Part VI attachment includes the
county composition of the SMSA's as they existed at that time.
Since January 7, 1972, several revisions to the composition of
SMSA's have been made, the latest in August 1972.  Therefore, the
January 7, 1972, SMSA's may have slightly different boundaries than
the currently-defined SMSA's.  The question arises as to which
boundary should be used for AQMA designation.  EPA recommends that
the January 7, 1972, SMSA's be analyzed.  Those SMSA's which
are determined to be problem areas should than be designated as
AQMA's on the basis of the current (1973) SMSA composition.  For
those SMSA's newly designated since 1972 and SMSA's in Puerto Rico
for which no BEA projections exist, the states should develop;their
own basis for projection based on data from various planning agencies
                            II-5

-------
(b)   Factors to consider in  designating AQMA's.
     In deciding upon  the particular  boundaries of an AQMA, the
following factors should be  considered.
     1.  The AQMA should include  all  of the  territory which shares a
         common air envelopeand a common  aggregation of sources.  This
         will  usually  be an  urba"ized area plus some adjoining areas
         which are now undeveloped but which are expected  to develop in
         the next 10 years or so.  It may include satelite communities
         which are now separated  from the central urbanized area but
         will, in 10-20 years, become part of the central  urbanized
         area and thus share the  air  resource.
     2.  Use of areas  previously  designated  by agencies of various kinds
         may have merit in that a data base  may be available and a prolif-
         eration of "regions" can be  avoided.  Examples are regional
         planning areas; State designated planning areas;  transportation
         planning areas; etc.
     3.  Emission control  and other air conservation measures necessary to
         maintain air  quality standards in the urbanized and developing
         parts of major urban centers may be quite stringent.  Applica-
         tion of such  stringent measures  in  isolated or undeveloped
         areas may not be advantageous.   Thus, inclusion of large  rural
         areas in an AQMA may not be  desirable.
     4.  Design and implementation of air conservation measures will
         involve certain governmental agencies.   Common boundary  lines
         for AQMA's and one  or some combination  of  jurisdictional  areas
         of implementing agencies may have  merit from an  operational  point
         of view.
                                   II-6

-------
     5.  Long-range transport of pollutants  is  a matter of concern.
         It is also true that if ambient  air standards are maintained
         near an aggregation of sources,  such standards will also usually
         be maintained at more distant  locations.  Therefore, it may not
         be necessary to include those  areas on the  periphery of an
         aggregation of sources in  order  to  assure maintenance of standards
         at locations distant from  the  aggregation of sources.
     6.  The influence of topography and  geography on dispersion of
         pollutants and on overall  community growth  patterns should be
         considered.
     7.  When designating AQMA's, preparation of detailed air quality
         projections and development of any  needed abatement strategies
         will need to be based on presently  available land use, transporta-
         tion and other plans because of  tinie constraints.  It may be,
         however, that new general  regional  development plans will be pre-
         pared in the future because of air  quality  considerations or
         other reasons.  The AQMA designation would  desirably be compat-
         able with any such future  community planning activity.
(c)  Changes in Boundaries of AQMA's
     The designation of the boundaries  of an AQMA in March of 1974 will
not preclude changes in such boundaries at the  time  that more detailed air
quality analyses and abatement/maintenance plans are submitted in 1975, or
at some other time.
(d)  Withdrawal of AQMA Designation
     Areas designated in March or June  or 1974  may be "de-designated" if
subsequent, more detailed analyses  indicate thatMn  fact the ambient air
                                     II-7

-------
I'uality standards will  not be jeopardized in  the  coming  10 years.
Therefore, in borderline cases arising in initial  abbreviated  analysis,
it is appropriate to designate the area and proceed with more  detailed
analyses.

(e)  Metropolitan Areas and Sparsely Urbanized Areas
     The principal objective of designation of AQMA's  and subsequent
development of plans to maintain ambient air  quality standards is  to
provide a  mechanism for management of general overall  urban  growth as
related to air quality, with due consideration of other  aspects of
community  growth.  New source review procedures which  involve  a deter-
mination that the new source will meet emission regulations  and not
cause or contribute to contravention of ambient air quality  standards
will be d  part of the overall maintenance plan in urban  areas.  In
lightly urbanized areas and in rural areas, it is considered that
properly administered new source review procedures will  be adequate
to assure  maintenance of air quality standards and therefore,  more com-
plex and burdensome maintenance programs will not ordinarily be needed.
                                   11-8

-------
 (f)  Assumptions concerning fuel  availability
     In projecting emissions from fuel burning sources, certain assumptions
must be made concerning the future availability and use of types of fuel.
The assumptions used must be specified in the material  submitted in support
of the designation.  These will be considered valid if based upon current
trends and/or projected fuel use requirements.  New facilities which might
change local fuel use patterns, such as refineries, nuclear power plants,
oil pipelines, coal gasification facilities, etc., but which have not already
been committed for completion by 1985, cannot be assumed to have an impact
on fuel availability in the designator process.  In addition, the current
fuel shortage cannot be assumed to continue ad infinitum, thus, resulting
in zero growth in emissions from fuel combustion.
(g)  Assumptions concerning emission and air quality baselines
     (1)  Emission baseline — In order to estimate emissions between the
     time standards are attained and 1985, it is necessary to determine
     emissions at the time standards are attained.  Some State implemen-
     tation plans (SIPs) contain these projections of emissions and these
     can be used where available.  If not available, these attainment date
     emissions can be calculated by the method presented below, which is
     based on concepts developed in the Manual for Analysis of State Imple-
     mentation Plan Progress, prepared for EPA by the Research Triangle
     Institute.  Regulations which are currently in existence should be used
     to project emissions.  Regulations which are planned, but not yet pro-
     mulgated, will not be accepted for such projections in the designation
     process.
                                  11-9

-------
     (2)  Air quality baseline—Several  of the  models  presented below for
     use in predicting air quality  require the  use  of  air quality  at the
     time of implementation of existing  regulations.   As with  emissions,
     the SIP's may contain projections of air quality  at the  time  of full
     SIP implementation, and these  air quality  values  can he  used.  For
     cases where air quality projections are not  contained  in  the  SIP, it
     may be assumed that the NAAQS  will  be achieved,  unless there  is reason
     to believe otherwise.  Alternatively, recent (1972-1973)  air  quality
     flat.; may be projected to 1975  and  hence to 1985,  making proper  adjust-
     ments for growth and scheduled abatement ~ i . ..ns.
           Oecriuse of  the  nature of photochemical oxidants, there may be
     r'.ffe'i areas which experience high  oxidant concentrations caused by
     hydrocarbons omitted  from either distant man-made sources or natural
     sources.   It is  recommended that these  rural areas not be designated as
     AQttA's in  that, it would be meaningless  to design a control strategy for
     these areas since they do not contain controllable sources of hydro-
     carbons.   In addition, Federal programs are planned which will eventually
     reduce hydrocarbon emissions nationwide.
          -A similar problem exists for  areas subject to high total suspended
     particulars matter concentrations  due to uncontrollable fugitive dust
     from natural  causes.   It is  recommended that particulate  matter measure-
     ments resulting from such fugitive  dust not  be the  basis  for  projecting
     air quality for the purpose  of AQMA designation.
(h)  Air quality standards to be  considered.
     The following national ambient air  quality standards  should be
considered in designating areas in  which standards may be  exceeded:
                               II- 10

-------
Pollutant _ Primary _ Secondary _
Parti cul ate matter    (a)  75 yg/m3,  annual         150 yg/m3,  second  highest
                           geometric  mean           24-hr  average  per  year
                      (b) 260 yg/m3,  second  high-
                          est 24-hr average  per
Sulfur dioxide        (a)  80 yg/m3, annual  arith-  1300 ug/m3,  second  highest
                          metic mean               3-hour average  per  year
                      (b) 365 yg/m3, second  high-
                          est 24-hr average  per
               _ year _
Carbon monoxide             10 mg/m3, second highest 0-hour average  per year
Photochemical           16Q yg/m3} sec0nd highest 1-hour average per year
  oxi c cin LS
Nitrogen dioxide        100 yg/m3, annual  drithmetic average
     For carbon monoxide, assume that the  1-hour standard will  be maintained if
the 8-hour standard is maintained.  As in  the original  SIPs,  a  demonstration of
achieving the oxidant standard will imply that the hydrocarbon  standard is also
achieved.
     Although States may designate on the  basis of air  quality  standards
more stringent than the national ambient air quality standards,  EPA itself
will, should the occasion ever arise, only act  to the  extent necessary to
insure attainment of the national  ambient  air quality standards.
(i)  Years for which projections must be made
     Air quality standards must be maintained throughout the  ten years
following submission of the detailed analysis of the AQMA's.   Projections of
air quality must, therefore, be made for the year 1985  and for  any other
years within the ten-year period in which it is believed that concentrations
may temporarily exceed a NAAQS.

(j)  List of information which must accompany choice or rejection of AQMA's
     For each SMSA within the State which  is exempted from designation on
the basis of the initial criteria (presented below), the submittal must
include the reasons for the exemption.    n_n

-------
     For each SMSA within the State which  is  not  exempted based on the
initial criteria, a projection of air quality for each  pollutant not
exempted must accompany the submittal.  Such  projection must  include all
calculations, except where a computerized  model is used.  If  a computerized
model is employed, the submittal  must describe the model used.  If the pro-
jection method is not one of the methods recommended  by EPA below, the
submittal must describe the method.
     A summary table of the designations and  rationale  similar to that
presented in Table II-l should accompany the  submittal.
(k)  Procedural requirements
     The areas designated by the States and eventually  \-y EPA will have
the force of regulation by virture of the  requirement that:  (a) for these
areas, a determination must be made of whether NAAQS  will be  maintained,
and (b) a plan may have to be submitted for maintenance of  the standards.
Because of these reasons, designations must be subjected to  public hearing
prior to submission to EPA by March 18, 1974.  The rationale  behind the
requirement of public hearing on AQMA designation is  basically that the
decision to designate or not designate areas  as AQMA's  is of such importance,
considering the economic and developmental implications of  such decisions,
that the widest public participation in such  decisions  should be allowed.
In holding such hearings, the States should consider  the rationale upon
which decisions were made to include or exclude all SMSA's,  or parts  thereof,
within their boundaries.
     The regulations concerning public hearing and submission of plan  (40
CFR 51, Sections 51.4 and 51.5) are applicable with regard  to submission
of the designated area.
                              II. 12

-------
                                Table  II-l
          Summary of AQMA Designations  for  State of
Area*

Reason not
Designated**

Reason
Designated**

Designation for
TSP

so2

CO
\
Ox

NU2

* Must include at least all  SMSA's within  the  State
**Reasons would be either "Initial Criteria" or  "Actual  Projection"
                                11-13

-------
Ill.  Initial Designation Criteria
      The   criteria immediately below were  developed  to enable  the States
to eliminate obvious non-ppoblem areas and include obvious problem areas
without performing an analysis of projected  air quality.  Any SMSA which
is not eliminated, or automatically included as an AQMA under these
criteria, is expected to undergo the analysis  described in section IV of
this document to determine the 1985 emissions.   After  application of these
initial  criteria, any SMSA which is not automatically  excluded or included
is expected to undergo a projection of 1985  emissions  and air quality by
techniques such as those presented in section  IV and V of this guideline.
Bear in mind that in case of a conflict between inclusion and exclusion
criteria, inclusion criteria take prededence.
    The technical derivation of these criteria is presented  as Appendix
               •
    A.  Elimination of obvious non-problem areas.
        SMSA's which meet the following criteria may be automatically
    excluded from consideration as an AQMA for the particular pollutant;
    supporting information must substantiate this exclusion:
         1.  Particulate matter:
             (a)  SMSA's which are located in  AQCR's where data  for the
             past two years indicates the AQCR is below all  NAAQS.
         2.  Sulfur dioxide:
             (a)  SMSA's which are located in  AQCR's where data  for the
             past two years indicated that the AQCR  is below all NAAQS
             and, the product of  (i) the air quality concentration  in  the
             base year and  (ii) the relative growth  in SMSA total  earnings

-------
        between the base year and 1985,  is  less  than  the  national


        ambient air quality standards.


    3.  Carbon monoxide:


        (a)  SMSA's whose air quality  is less  than  25 p.p.m.,


        maximum 8-hour average during  the past two  years.


    4.  Photochemical  oxidants:   SMSA's


        (a)  which have no transportation control strategy  for


        photochemical  oxidants,  and


        (b)  which are located in AQCR's with  a  maximum 1-hour

                                                   3
        oxidant concentration of less  than  320 yg/m  during the  past


        two years.


    5.  Nitrogen dioxide:


        (a)  SMSA's not designated by  the inclusion criteria in


        Part III B5 are excluded.


8.   Inclusion of obvious problem areas


    Areas  which meet any one of the following  criteria should be


designated, in whole or at least in part, as  an  AQMA  for  the particular


pollutant.


    1.  Particulate matter:


        (a)  Areas within AQCR's which  are not projected  to attain  the


        NAAQS for particulate matter by 1985.


    2.  Sulfur dioxide:


        (a)  Areas within AQCR's which  are not projected  to attain


        the NAAQS for sulfur dioxide by 1985.


    3.  Carbon monoxide:


        No automatic inclusion criteria.


    4.  Photochemical  oxidants:


        (a)  Any areas for which a transportation control strategy


        for photochemical oxidants is  required (Table III-l).



                                 Ill-2

-------
5.  Nitrogen dioxide:
    (a)  The appropriate  parts  of  those SMSA's whose central
    cities are Los  Angeles,  Chicago, New York, Denver, and
    Salt Lake City.
                      III-3

-------
                            TABLE  III-l
AQCR's in Which Transportation Control Strategies are Required
                                                                 Required for
SUitfi
' "as!, a
/is ibaina

Arizona
California




"'.•lorado
District of
Columbia
Illinois
•idiana
i ouisiana
Maryland

i'tassachusetts

••'•nnesota
Missouri
New Jersey

r'ew York

i-fevada
Ohio
Oregon
iynnsylvania

!"xas



AQCR
Northern Alaska Intrastate
Mobile-Pensacola-Panama City-So. Mississippi Interstate
Metropolitan Birmingham Intrastate
Phoenix-Tucson Intrastate
San Francisco Bay Area Intrastate
Sacramento Valley lutrastate
Metropolitan Los Angeles Intrastate
San Joaquin Valley Intrastate
San Diego Intrastate
Metropolitan Denver Intrastate
National Capital Interstate

Metropolitan Chicago Interstate
Metropolitan Indianapolis Interstate
Southern Louisiana-Southeast Texas Interstate
National Capital Interstate
Metropolitan Baltimore Intrastate
Metropolitan Boston Intrastate
Hartford-New Haven-Springfield Interstate
Minneapolis-St. Paul Interstate
Metropolitan Kansas City Interstate
New Jersey-New York-Connecticut Interstate
Metropolitan Philadelphia Interstate
New Jersey-New York-Connecticut Interstate
Genesee-Finger Lakes Intrastate
Clark-Mohave Interstate
Metropolitan Cincinnati Interstate
Portland Interstate
Metropolitan Philadelphia Interstate
Southwest Pennsylvania Intrastate
Metropolitan San Antonio Intrastate
Metropolitan Dallas-Ft. Worth Intrastate
Austin-Waco Intrastate
III-4
CO
X

X
X
X
X
X
X
X
X
X

X
X

X
X
X
X
X
X
X
X
X

X

X
X
X




Ox

X
X

X
X
X
X
X
X
X


X
X
X
X
X
X


X
X
X
X
X
X
X
X
X
X
X
X


-------
                                   TABLE IZI-1 (Cbnt.)                           ...
                                                                            Required  for

State	A.QCR	CO	Ox
Texas (cont.)



Utah
Virginia^
Washington

Kansas
El Paso-Las Cruces-Alamagordo Interstate
Corpus Christi -Victori a Intrastate
Metropolitan Houston-Gal veston Intrastate
Southern Louisiana-Southeast Texas Interstate*
Wasatch Front Intrastate
National Capitol Interstate
Puget Sound Intrastate
Eastern Washington-Northern Idaho Interstate
Metropolitan Kansas City Interstate




X
X
X
X
X
X
X
X
X

X



   *Currently under study - May require only stationary source control
                                       III-5

-------
IV.  Method of Projecting Emissions
     In order to Identify those SMSA's which  could become  AQMA's  during  the
period of 1975-1985, it will  be necessary to  first determine  1970 emissions,
project these emissions to 1975 (or 1977 for  areas granted extensions) to
account for current SIP control strategy reductions,  arid then further project
emissions to 1985 using Bureau of Economic Analysis (BEA)  indicators of
growth in population and earnings for SMSA's.  (BEA indicators are presented
in Section VI of these guidelines.)  From the 1985 emissions, air quality  can
then be estimated by techniques presented in  Section V and compared with the
applicable standards to determine if the area being considered is,  in fact,  to
be designated as an AQMA.  In many cases, 1975 emissions will already have been
estimated for the purpose of developing SIP control strategies.   In the  event
that 1975 emissions are given in the State's  implementation plan  by county and
they are still valid, they may be used directly and no projection to, 1975  would,
of course, be necessary.    For ease in both  computation and  review, emissions
can be recorded by county within each SMSA as shown in Table  IV-1.   A suggisted
process for projecting emissions is presented in the flow  diagram of Figuro  IV-1.
(1)  PROJECTION OF 1975 EMISSIONS
          Two methods for projecting 1975 emissions are presented below, a
*
     "preferred" method and a "back-up" method.  By implication,  EPA expects
     the "preferred" method to be used for the most part 1n each  State.  Only
     where time does not permit or where the  workload will be great (such  as
     for those States which have a large number of SMSA's  to  be analyzed)
     should the "back-up" method be used.   Before  deciding to< use the "back-up"
     method, States should discuss the problems of using the  ^preferred" method
     with the representative  responsible for  maintenance of standards in the
     appropriate EPA Regional  Office.   CO, HC, and NOX emissions  from transpor-
     tation sources can be calculated to 1985 directly by  the method presented
     below in item (2).
          (a)  Preferred method
               (i)  This method is the same used in the development of the
               original implementation plans, i.e., a source-by-source tabulation

-------
                        TABLE  IV-1.   Emission Projection Calculations

                           (A  table  such  as  this  should be prepared for each pollutant)
A
Source
Class
B C C-l
Reduction Growth
1970 Factors Factor
Emi
ssions
(1975/1970)
0
1975
Emi
ssions
E
Growth
Rate
[(1985/
1975)-!]
F
Emis
si on
Factor
Ad jus
tment
Q
' 1985
Emissions
G = D|
;i + EF
   Fuel  Combustion
    Power plants
    Point sources  (exclud  pp)
    Area sources
<     Subtotal
i
ro
   Industrial Process

    Point sources  (Subtotal)

   Solid Waste  Disposal

    Point sources
    Area sources
      Subtotal

   Transportation

    LDV
    MDV
    HDV
      Subtotal
   Miscellaneous

    Point sources
    Area sources
      Subtotal
      TOTAL

-------
                Figure IV-1.   Calculation of 1975 and 1985  Emissions
            Determine 1970 emissions  by source  category  from  state  files,
            SIP's or NEDS data banlc       	  	__	
           [Assemble county emission; jiataJnto SMSA totals  for  1970
         PREFERRED METHOD
1
Apply SIP control strategies to each
source to determine allowable emis-
sions in 1975

BACK-UP METHOD
                     Apply reduction factors in Table IV-2
                     to emissions from 1970 uncontrolled
                     power plants to obtain 1975 controlled
                     emissions.  (Use more specific estimates
                     if available.)	
Calculate T97b emissions from new
power plants using capacity of planned
new units from utility data or "Steam-
Electric PI ant Factors" and apply
regulations,        	    _.
                     Calculate 1975 emissions from new  ower
                     plants, using capacity of planned  nits
                     from utility data or "Steam-Electr c
                     Plant  Factors"..and aplying  regula i045.
                   I
 For industrial  process, solid waste
 and misc.  sniirrps,  calculate arowth  in
emissions from 1970 to 1975 using BEA
economic 1ndicaiors.
            app
                      For  industrial  process,  solid wast  and
                      misc.  sources  determine' 1975 cont oiled
                      emissions by applying  reduction  factors
                      from Table  IV-2 (or  local  regulations)
                      to 1970  emissions, by  source category
                                        I
                                                For industrial process, solid waste
                                                and misc. sources, calculate growth
                                               in emissions from 1970 to 1975 using
                                               BEA Indicators	
             .Determine 1985 emissions from transportation sources using
             Jformula Q19fl5 • £(Qha,.p) G^jE, (for CO, HC and N0y)
              Determine growth of emissions from 1975 to 1985 for all  sources
              other than transportation using BEA indicators	
              Determine 1985 controlled emissions from 1975 emissions  for
              industrial process, solid waste, and miscellaneous sources,
              using BEA growth factors and emission factor adjustments
                                          I
             [Total  1985 emissions from all  source categories
                                      IV-3

-------
                 of emissions  allowed under  the applicable control strategies
                .contained  in  the  State's  Implementation plan.  Data should be
                 presented  and submitted in  a  form similar to that presented in
                 Appendix D of 40  CFR Part 51.
                 (ii)   For  projections  of  new  steam generating power plants, it
                 is  recommended that States  contact electric utility companies
                 directly.   If time does not permit this, use 1975 i rejections
                 of new capacity in the latest edition  (1972) of  "St .>am-E1(. ctric
                 PlantFactors"  published by  the National Coal Association.
                 (iii)   After  the  source-by-source tabulation of  allowable emissions
                 has been computed, tabulate the allowable emissions Into  the
                 following  categories and  use  the recommended projection parameter
                 to  account for growth  to  1975.
                                                       Recommended B£A
                                  Category             Proje c 11 on Par ameter*
                        Fuel  combustion (excluding pp)    Total  earnings
                        Industrial orocesses              Manufacturing earnings
                        Solid waste                       Population
                        Miscellaneous                     Total  earnings
                 (iv)   Emissions from these  four categories and power plants can
                 be  recorded in Tablu IV-1.
  *EPA's  recommendation  that  these  parameters  be  used was based  upon  available
  information  and was  not  the result  of a  statistical analysis to  determine  an
-(  accurate correlation between emissions from  a particular  category and  an
  economic or  demographic  parameter.   Furthermore,  the  user of these  projections
  should  be aware that it  is  not known what  relationship exists  between  an
  increase in  an economic  Indicator and an increase in  emissions from a
  particular category.  Another complicating factor is  the  present energy
  situation-It is not  known what effect the  current situation will have  on long-
  term growth.                                           '
                                            IV-4

-------
           (b)  Back-up Method
               The  following technique Is based on 1970 summary NEDS data,
           and  uses  average emission reduction factors derived from analysis
           of point  source emissions in six AQCR's (S':. Louis* Denver,
           Washington, D.C., Seattle,  Indianapolis, and Boston).  These factors
           represent reductions  in emissions resulting from imposition of
           typical  regulations under the SIP process.  Power plant emissions
           are  calculated separately from other sources because of the
           importance of their emission and because        different emissicn
           reduction ratios must be applied to them pLs the fact that proje< tions
                          * *
           of new power plants are readily-available.  Obviously, SIP emission
           limitations varv widely and thus the factors may over- or under-
           estimate  results  in some cases.  In the Intarest of alleviating  a
           time-consuming burden, however, EPA offers  this technique as a sub-
           stitute for a detailed source-by-source and detailed category analysis
           only in those States  where  time does not permit use of the "preferred"
           method.
 BACK-UP METHOD
 STEP A - Determine  1970 Emissions
      Using emissions summaries  for each  county 1n the AQMA,  from States files,
 •
 SIP emissions  summaries, or NEDS data bank, obtain and record 1970 emissions  for
 each pollutant by point and area source  category; I.e.,  fuel combustion,  industrial
 processes, solid waste, transportation,  and miscellaneous.   Show emissions for
 power plants  separate from  other fuel combustion  sources.   Emissions can  be
', recorded 1n this manner as  shown on  Table IV-1,  "Emission Projection Calculations."

 STEP B - Determine 1975 Power Plant  Emissions
      Calculate power plant  emissions  from existing  and  new plants  using data
 from "Steam-Electric Plant  Factors"  published yearly by  the National Coal  Association.
                                             IV-5

-------
       1.  Power plants existing 1n 1970


          a.  Multiply 1970 SIP emissions by the emission reduction factors


          in Table IV-2 (or more specific factors,'if available)  to get


          1975 controlled emissions.  This reduction applies only to those


          plants which were not controlled to SIP regulations in  1970.   For


          power plants which were under control in 1970, extend 1970 emissions


          unchanged to 1985.


       2.  New power plants


          It is preferable tf the State contact electric utility  companies

                                                                i
       directly to obtain projections of new power plaats .  If time does not


       permit this, use 1975 projections of new capacity in the latest edition


       (1972) of "Steam-Electric Plant Factors".  Calculate emissions in 1975


       for additional capacity over 1970 using appropriate factors for losses


       allowed by Fedora! New Source Performance Standards, or SIP regulations


       in the event the SIP regulations either take effect earlier or- are more


       stringent than the NSPS.



 STEP  C - Determining 1975 Emissions (excluding growth) from Sources Other Than


          Power Plants and  Transportation Sources


       Determine allowable emissions in 1975 for point and area sources (other
 *
 than  power plants and transportation sources) by source category using the


 emission reduction factors given in Table IV-2.  If a State feels that its  own


 regulations or those of a local agency within its boundaries would result in


' values significantly different from those produced by use of the factors in


.Table IV-2, then the State should use Its own regulations or those of the


 appropriate local agency in determining 1975 emissions.  Such regulations


 should be documented.  Since this estimate does  not account for growth between


 1970  and 1975, the  results of using Table IV-2 must be modified by the projected


 growth in emissions for each source category.



                                     IV-6

-------
                              TABLE  IV-2

                       EMISSION REDUCTION  FACTORS3

               (Ratio of 1975 allowable emissions  to  1970  emissions)
Source Category
Fuel combustion
Point sources less power generation
Area sources
Power generation sources
Industrial processes
Solid Waste
Point sources
Area sources
Transportation
Miscellaneous
Point sources
Area sources
Parti cul ate
Matter

0.44
0.48
0.50
0.43

0.29
0.28
1.0

1.0
1.0
S0x

0.43
0.57
0.43
0.37

1.0
0.82
1.0

1.0
1.0
HC

1.0
T.O
1 .0
0.47

1.0
0-88
*

0.48
1.0
CO

1.0
1.0
1.0
o.io

.52
0.88
*

1.0
1.0
N0x

1.0
1.0
1.0
1.0

1.0
1.0
*

1.0
.1.0
*Calculated by different method - see text

a.  These emission reduction factors for 1975 as compared to 1970 are based
    on a composite of expected and existing conditions and emission control
    regulations in St. Louis, Denver, Washington, D.C., Seattle, Indianapolis
    and Boston.
    All agencies should develop such factors for conditions in each area
    under consideration whenever possible.  The factors above should only be
    used when such specific factors cannot be prepared.
                                      IV-7

-------
                                                                            **
STEP n - Projected Growth Rates from 1970 to 1975
     To obtain 1975 emissions for all  sources except  power plants, multiply
emissions determined in Step C above by growth factors  obtained from avail-
able data or 8EA projections,  (see footnote, p. I\N4) determined as follows:
     1.  For fuel  combustion sources,  except power plants  (where the method
     of calculating growth has been previously explained), it is sugge; ted
     that the growth rate be based on the percent  increase In total  earnings
     from 1970 to 1975 for the particular SMSA.
     2.  For industrial processes, the growth rate can  be  based on the
                                                               t
     percent increase in manufacturing earnings.
     3.  For solid waste emissions, the growth factor can  be based on
     the percent increase in population for 1970 to 1975.
     4.  For miscellaneous emissions,  the growth factor can be based on the
     increase in total earnings as was suggested for the category of fuel
     combustion sources.
     5.  For particulate matter and SOx emissions  from transportation, the
     growth factor can be based on the Increase 1n population.
These growth factors can be Inserted in Column C-l.
 (2) PROJECTION OF 1985 EMISSIONS
      For transportation sources, the following formula may be used to computer
 1985 emissions using 1972 baseline data for N02 and 1970 baseline data for all
• other pollutants    (1t Is not necessary to make a calculation to determine the
.level of 1975 emissions for transportation sources):   ;
 **CO, HC, and NOx emissions from transportation sources can be calculated to
    1985 directly by the method presented below in item (2)
                                       IV-8

-------
                            *  ,      G1E1
                           1=1          1
            where   QIQRB  a Projected  1985 emissions
                 (Qbase)   = Baseline emission from source category 1.
                       G.  = Growth  factor for source category 1.
                       E^  = Emission factor  ratio for source category 1.
     Project 1985 emissions from 1975 emissions  for all  source  ca:egories
other than transportation  using the formula: *
                F. = C1  (1  + D.Ej)
                                                                    (2)
        Where:   F = 1985 emissions  from source category  1           •
                C = 1975 emissions  from source category  1
                D = growth  rate of  emissions between 1975  and 1985 for
                    source  category i
                E = emission factor  adjustment for source
                    category 1  (applied only to Industrial  process sources-
                    for all other categories E^  = 1)
     Growth rates (D in formula 2)  for emissions between 1975 and 1985 are the
same as those used to project 1975  emissions (see footnote, p.I\^j).  That  is,
the percent increase 1n total earnings projected for 1975-1985 may be used to
project emissions from fuel combustion; the
percent Increase in manufacturing earnings may be used for Industrial processes;
the percent Increase in population may be used for solid waste emissions and
particulate matter and SOx emissions from transportation;  and the percent  increase
in total earnings may be used for the miscellaneous category.  For power plants,
1t 1s  again recommended that the State contact electric utility companies
*This  formula would  not be used  for  power plants if actual existing and
  projected  emissions are available.
                                       IV-9

-------
directly.  If time does not permit this,  the  percent  Increase In  total
earnings projected for 1975-1985 may be  used  to  project  1985 power  plant
emissions since.it appears to be most closely related to the increased
demand for electric power.  Add these power plant  emissions to  the
emissions extended unchanged from 1970 to get total  1985 emissions  from
power plants.
     An adjustment will be needed to account  for control between  1975 and
1985 of new industrial process sources because of  forthcoming new source
performance standards.  Generally, these standards will  be more stringent
than limitations presently contained in the SIPs.   TV adjustment needed  to
account for future new source performance standards would be  the  rctio of
the estimated percent allowable emissions under the future new  source
performance standards to the percent allowable emissions under  the  current
SIP control strategy.  These ratios, of course,  vary widely  among industrial
categories,  Furthermore, EPA has only a rough idea of what  the standards  will
eventually be.  It is suggested, therefore, that a composite  adjustment
factor of 0.40 be used as the "E" value in Equation 2 for industrial  process
sources for each pollutant.  Bear in mind that this "E" value  applies  only
to industrial process sources.  For other source categories,  use  E=l.
*
Note:  Examples of the method of projecting 1985 emission and  air  quality,  using
       tne "back-up" method of projecting 1975 emissions, is enclosed in
       Appendix B of these guidelines.
                                       IV-10

-------
V.  Instructions for Modeling Air Quality Concentrations
1.  Introduction
     This portion of the guideline presents  information concerning models
recommended for use in predicting 1985 air quality,  once  1985  emissions
have been calculated.  After this air quality prediction  is  made, the
designation of AQMA's can be made, i.e.,  those areas which are predicted
to exceed the standard can be selected.
     This portion of the guideline is divided into  four parts:
          1.   Introduction
          2.   Analytical Techniques for CO Concentrations
          3.   Analytical Techniques for Relating Oxidant  Concentrations
              to Hydrocarbon Emission
          4.   Analytical Techniques for Relating Projected Emissions
              of other Pollutants to Air Quality
2.  Analytical Techniques for CO
     Once carbon monoxide emissions have been projected to 1985,  using
techniques found in Part IV of these Guidelines, "Methods of projecting
emissions," air quality concentrations for CO can be determined using
the following techniques,
     High CO concentrations are observed primarily near areas  of high
traffic density.  "Rollback" models for CO have been criticized for giving
undue weight to stationary source CO emission and to vehicle emission  growth
in the suburbs as compared to vehicle emission growth on  streets  in the  fully
developed parts of urban areas where most existing air sampling sites  are
located.  The following model mitigates these problems by giving the most
weight (80%) to local traffic near the air sampling station  and relatively
less weight  (20%) to total regional emission.

-------
         The model  divides  observed  CO  concentration  into two parts.
that due to local  t:affic,  and that  due to  the  entire urbanized area.
Changes in emissions from each of these components  are projected  and
1985 concentration is predicted using modified  rollback techniques.  The
model equations are:

             F  = F  + F  + b                                         (1)
                        PL GL* EL + PH
          0."8(B -b)  "       P  + P
                                   H
                        PL GL EL * PH GH EH * PS GS ES
                                  100%
         where
             FT = Total future (1985) CO concentration (PPM)
             F.  = Future concentration due to local traffic
             P.. = Future concentration due to urban emission

              b  = Background concentration
              B  = Baseline concentration (measured or estimated)
             PL  = Percent emission from light duty vehicles (gross vehicle
                  weight'< 6000 Ib)
             PH  = Percent emission from other mobile  sources  (gross  vehicle
                  weight > 6000 Ib)                                   '
             Pg  = Percent emission from stationary sources
             G  = Growth factor over the projection period, G* 7* G
             E  =  Expected  ratio of 1985 emission to baseline emission
                  for a  composite source.  (Obtained from Table V-1)
             G*  =  Growth factor for traffic on the local  street    near
                  critical  air sampling stations.
                                  V-2

-------
     Equations 1, 2, and 3 may be  used  to  estimate  1985 CO concentrations
in those areas which cannot be eliminated  by  using  the initial designation
criteria.  The information needed  to  apply the  equations  is:
     a.  Baseline air quality (B)-second worst  8-hour average, during most
         recent year at a site where  the public has  access for at least 8
         hours.
     b.  Background CO concentration  (b)-use  1  p.p.m. if  data to the
         contrary is unavailable.
     c.  Percentage contribution of light  and heavy duty  vehicles and
         stationary sources to the baseline year emission inventory  (Same
         year as air quality data).  This  information should be computed
         from the latest emission  inventory available locally.  If local
         data is unavailable, the  NEDS  data file contains emission data by
         county which may be used. [Note: Trucks  and other heavy duty vehicles
         may contribute a greater  proportion  of emissions in the area where  the
         critical air sampling station  is  located.   If so, and if the informa-
         tion is available, the appropriate P^  and  PH should be used in
         Equation (2).  Otherwise, the  same PL  and  PH should be used in
         Equations (2) and (3)].  If  the  data is not delineated by types of
         mobile source, assume that the ratio of PL/PH =8.0.
     d.  Growth rates from past trends  for the  source categories.  Ideally,  the
         growth rates should be based on  a direct indicator of emission poten-
         tial such as vehicle miles,  material processed,  kilowatts generated,
         etc.   It may be necessary to use  an  indirect   indicator such  as  the
         BEA projections of population  and economic activity.  Growth in popu-
         lation is recommended as  a logical choice  of estimator of mobile
         source emissions.
     e.  Emission factor ratios.  Nationwide  emission  factor  ratios  for motor
         vehicles are presented in Table  V-l.  If local  mobile source emission
         factors are expected to differ'from  the national be  virtue  of  trans-
         portation controls, unusual  vehicle  life

                                     V-3

-------
                          TABLE  V-l

                      EMISSION FACTOR RATIOS*
         Year                 HDV  & MDV            LDV

1970**
1975
1977
1980
1985
1990

1970**
1975
1977
1980
1985
1990
Carbon monoxide
1.00
.83
.76
.66
.53
.53
Hydrocarbons
1.00
.77
.68
.40
.40
.40

1.00
.59
.45
.29
.08
.08

1.00
.50
.39
.25
.07
.07
 *Ratio of emissions  in  given  year  to base year (base year is 1970 for
  CO and HC)

**For data bases  other than  1970  (such as 1971, 1972, 1973) for CO and
  HC, interpolate between  1970 and  1975  values.
                                      V-4

-------
         expectancy or other reasons, local emission factor ratios
         may be used.  The procedure for calculating composite vehicle
         emission factors is presented in EPA-450/2-73-003 Kircher and
         Armstrong "An Interim Report on Motor Vehicle Emission Estima-
         tion"!
              The emission factor ratio for stationary sources will
         depend on the particular source mix in the area and on state
         regulations for stationary source CO emission.  If such informa-
         tion is unavailable, then t^e following emission factor ratios
         may be used:
                                          CO Emission Factor
                    Source                 Ratio 1970-1985
                  Power plants                  1.0
                  Industry                      0.5
                  Area sources (stationary)     1.0
         The overall stationary source emission factor ratio is calcu-
         lated from
           E      .   =   PPP EPP + PI EI + PA EA
            composite   	5—T~B—+"5	
                            HPP   KS   KA
3.  Relating Oxidant Concentration  to Hydrocarbon Emission
    Appendix J to 40 CFR  Part 51  "Requirements  for  Preparation, Adoption,  and
Submittal of Implementation Plans"  (published  in  the  August  14, 1971,  and
republished November 25,  1971,  Federal  Register)  presents an estimate  of the
hydrocarbon emission reduction  needed to  obtain  the NAAQS for photochemical
oxidant.   This estimate is  based  on  an  "envelope  curve" which encloses data
points for non-methane hydrocarbon  and  oxidant  concentrations in  several cities.
                                   V-5

-------
                                    There is evidence to suggest that
HC/NOx ratios should decrease due to emission control regulations in force
and expected.  This should result in somewhat more oxidant reduction,
although the amount of additional reduction cannot be quantified at present.
Therefore, Appendix J must be considered a conservative estimate in that it
may require more HC reduction than needed, but probably does not require less
    Appendix J should be used as follows:  •
        1.   Project 1985 HC emissions as shown in Steps A-D of Section IV.
        2.   Determine  the expected emission change by
               "expected =   bK* '           X 100%
                                base
        3.   Determine the required percentage hydrocarbon emission reduction
             using Aopendix J and the highest observed 1-hour oxidant concen-
             tration during the 'baseline year.
        4.   If R required from step 3 is greater than R expected from
             step 2, the area should be designated an AQMA for oxidant.  This
             will be especially true if RexDectec| is a negative number.
                                   V-6

-------
4.  Ai'ia^v/LiCfM 7euiiiif|iit;$  fur- Pol lui-mi i.s Giiitr 'Lndii  oxidants  and 'JJ--Pel citing



    Projected Emission to Air Quality



    a.  Proportional roll forward model



        Present air quality may be projected to 1985 for pollutants



    other than  oxidants  and  CO  (i.e.,  air  quality  may  be projected  for TSP,  S02,



    and NO ) using the proportional roll forward model  as shown in the
          A


    following formula.




              C1985 = b +  ''base 'b>





     Where:  C-igoc = projected concentration




             b     = background concentration



             C,     = baseline concentration




             Q-iggc = projected emission




             Q.     = baseline emission



     While the proportional roll forward technique  is a potential means for



selecting which counties or SMSA's to designate as AQMA's, it has several



shortcomings which may render it unsuitable, or impossible, to apply.



These are:



     a.  Base year air quality observations are required,



     b.  The monitoring data must be representative of the area  of



         interest (i.e. a monitor dominated by a single point source or



         a small number of select sources may result in anomalous pre-



         dictions),



     c.  The meteorology occurring during the base period must be similar



         to that which is of interest during the period being modeled.



         As a result of these limitations, it may  be necessary to designate



         AQMA's using analytical techniques which:





                                 V-7

-------
              1.  DC not require previous  air quality observations, and
              2.  take some explicit account, at  least  in  a  rough sense,
                  of meteorological  differences.
     Where the above conditions apply with particular force,  it may be
appropriate to use the Miller-Holzworth model described in the next
section.

b.  Miller-Holzworth Model
     The Miller-Holzworth Model can  be uscJ only  for the calculation
of annual averages of suspended particulaie matter and  sulfur dioxide.
The Miller-Holzworth Model  1-3 for area sources assumes concentrations
to be a function of emission density, wind speed,  atmospheric mixing
depth and city size.  The model implicitly assumes that the  atmosphere
is slightly unstable (between Turner Stability Classes  C and  D6)
Stability assumptions cannot be varied. The model,  as  formulated
below,  estimates the city-wide average concentration  for the sampling time
of interest.  The relationship among average city-wide concentration,
emission density, city size, wind speed and mixing depth is
                  X*.011Q  [3.61 H°-13
             where x"  = average city-wide concentration, ugm/m3
             Q  =  emission density, t/y-mi2
             H  =  mixing depth, m
             S  =  alonq-vn'nd distance of the city (miles).  When  this  is  not known
                  ass'j;Ti3 S = ./ITFeT.   The  "area"  is  the  urbanized  portion
                  of the city.
             u  =  wind  speed, m/sec                                -
                                     lio
In cities in which 16CO'S/u < .471 H    , mixing depth is' unimportant
and x beco;r.es   x~  = -044 Q (1600 S/u)'115                               (2) •
                                 V-8

-------
The procedure one would use in applying the radel would depend on
whether air quality data were available, and  the pollutant and sampling
time being analyzed.

                (1)  If no air quality data are available
                     (a.)  Use emission density estimates obtained  from
                          the use of Part IV of these Guidelines,  "Methods
                                                             p
                          of Projecting Emissions"  (tons/y-mi )
                     (b)  For annual standards such  as the NAAQS for
                          nitrogen dioxide, refer to Figs. 1  and 11, in refer-
                          ence 3  showing the mean  annual morning  mixing
                          depths and wind speeds for the United States.
                          Select the values of "H"  and "u" which are
                          appropriate for the area  of the country  being
                          analyzed.  Use these in Eq. (1) or  Eq. (2).
                     (c)  For short term (1-hr.--24-hr.) standards  refer.
                          to Figs. 2 and 12, in reference 3,  showing mean v.inter
                          morning mixing depths and  wind speeds.   Use the
                          indicated values  in Eq.  (1) or Eq.  (2).
                (2)  If Air Quality Data are Available
                     (a)  Take emission projections  obtained  from  the use of
                          Part IV of these  Guidelines, "Methods of Projecting
                          Emissions."
                     (b)  Subtract present  emission  density from projected
                          emission density.
                     (c)  Apply the Miller-Holzworth Model as described above,
                          except use the difference  between projected and
                          present emission  densities in Equation (1) or (2) to
                          obtain
                                     V-9

-------
              A x =
[V ,, ,.0.13 .  800 S   i5Jj< 10"_5) u H1'26]
[3.61 >i     - -Tj-lT "	S       J  (la;
          or  A 1= -Oil AQ (1600 S/u)'115                                 (2a)
                          (d)  Add A ^ to the observed air quality  levels.

             (3)   Use  of A Calibrated  Mi 1 ler-Holzv.'orth Model
                  Wherever possible,  it would be preferable  to  use a
                  version of the  model  which  har b^n  calibrated  with
                  observed data.   Figure  1  in Appendix A  of  the
                  40 CFR Part  51  is  such  a  version  which  has  been
                  calibrated for  annual TSP  and  S02 concentrations in
                  cases  where  mixing  depth  is unimportant.   Such  cases
                  would  occur  when
                      1600 S/u <  .471  H1-'3
                  In many cases,  mixing depth remains  relatively  unimportant
                  for  pollutant travel  times  greater than .471  H  '   .   Thus,
                  if the annual concentration of TSP or S02  concentrations
                  is of  interest, Fig.  1  in Appendix A of 40 CFR  Part  51
                  should be  used  instead  of Eqs. (1),  (la),  (2) or  (2a).
                                                                         (
C.  Estimation of Short  Term Concentrations for  S02 and Particulates
     It is necessary that the  short term standards  for SO- and TSP be
maintained as well  as  the annual  standards.  Two methods  may be employed
to estimate compliance with  short term  standards: roll forward and  the log-
normal  relationship.
     1.  Roll forward
         The proportional model given  in section 4(a) may be applied
     directly to  short term  concentration.  The  second highest 24-hr or
                                 V-10

-------
           3 hr concentration* observed in the AQMA is entered as
           C.     and the calculated C, gg^ is compared with the appro-
           priate short term standard.
       2.  Log-Normal model is an empirical  relationship developed by
           Dr. Larsen  of EPA.  The model allows the estimation of short-term
           maximum   concentration given the annual average and a char-
           acteristic parameter of the concentration distribution called
           the Geometric Standard Deviation (GSD).  Table 14 of R.I.  Larsen's
           "A Mathematical Model for Relating Air Quality Measurements  to
           Air Quality Standards," AP-89, is reproduced below.  Using this
           table, the peak concentration may be calculated from the annual
           average provided the GSD is known.  The GSD is routinely calculated
           for air quality data in the SAROAD data bank.
4.  Comparison of projected air quality with NAAQS.   After air quality  concen-
trations have been projected to 1985,  a comparison to the  NAAQS  presented on
p. 1 1 -7 can be made.   If the projected air quality of an  area  exceeds a  NAAQS,
the area should be designated an AQMA  for that  pollutant;  conversely, if the
projected air quality does not exceed  a NAAQS,  the area  does not  have to be
designated as an AQMA for that pollutant.
NOTE:  Examples of the method of projecting  1985  emissions and air quality
       using  the "back-up" method of projecting 1975 emissions,  is  enclosed
       in Appendix Bvof these guidelines.
*Short term standards are not to be exceeded more  than  once  per year.
 Thus, ft is the second highest value that must meet  NAAQS.

-------
    Table 14. RATIO OF EXPECTED ANNUAL MAXIMUM POLLUTANT CONCENTRATION TO
         ARITHMETIC MEAN CONCENTRATION FOR VARIOUS AVERAGING TIMES
                    AND STANDARD GEOMETRIC DEVIATIONS
Sta
1 tec
'.00
1.07
1.14
1.21
1.29
1.36
:.44
1.51
1.59
1.67
1.75
1.63
1.91
1.99
2.08
2.16
2.25
2.34
2.42
2.51

2.60
2.69
2.78
2.87
2.97

3.06
3.15
3.25
3.34
3.34


3.54
3.64
5 min
ndard
av
Ihrl
1.00 1.00
1.0C M.05
1.11
1.1V
geometric deviation for
fir aging times of:
3hr
1.00
1.05
1.10J 1.09
1.15
1.23 1.20
!.29 1.25
1.34 1.30
1.40 1.36
1.46 1.40
l.o 2
1.58
1 .64
1.70
1.76
1.82
1.88
1.94
2.00
2.0G
2.12

2.19
2.25
2.31
1.14
1.19
1.23
1.23
8hr
1.00
1.04
1.09
1.13
1.17
1.22
,.26
1 3? 1.30
1.3?
1.45 1.42
i.r.o
1.55
1.46
1.51
1.60 1.55
1 .GS
1.70
1.60
1.64
'..?{•> 1.6R
1.80 1.74
1.85 i 1.78
1.90
1.95

2.00
2.05
1.83
1.87
1.34
1 .39
1.43
1.47
1.51
1.55
1.59
1.63
1.08
1.72
1 day
1.00
1.04
1.08
1.12
1.16
1.20
1.24
1.27
1.31
1.35
1.39'
1.42
1.45
1.50
1.53
1.57
4 days
1.00
1.04
1.07
1.10
1.14
1.17
1.20
1.24
1.27
1.30
1.33
1.36
1.39
1.42
1.45
1.48
.6! 1.51
.64
1.76 .68
1.80
1
1.92
1.84
I.Sfi J1.88
2.10 2.00
237 2.15_2.05.
2.43

2.50
2.56
2.62
2.69
2.75


2.81
2.83
3.74 j 2.94
3.83
3.93

4.04
4.14
4.24
4.34
4.45
4.55
4.66
4.76
4.87
4.97
3.00
3.07

3.13
3.20
3.26
3.33
3.39
3.46
3.52
3.59
3.65
3.72
1.92
1.96
2.20 2.09 2.00

2.25
2.30
2.35
2.40
2.415


2.50
2.55
2.60
2.14
2.18
2.23
2.27
2.32

2.04
2.08
2.12
2.16
2.20
I

2.36
2.41
2.45
2.65 j 2.49
2.70 2.54

2.75 2.56
2.80
2.85
2.90
2.95
3.00
3.05
3.10
3.15
3.20
2.63
2.67
2.71
2.76
2.80
2.84
2.89
2.93
2.98
2.24
2.27
2.31
2.35
2.39

2.43
2.47
2.51
2.55
2.59
2.62
2.66
2.70
2.74
2.78
.71

.??>
.78
.82
.85
.89

1.92
1.96
1.99
2.03
2.06


2.00
2.13
2.16
2.19
2.23

2.26
2.29
2.33
2.36
2.39
2.42
2.46
2.49
2.52
2.55
1.54
1.57
1.60

1.63
1.66
1.69
1.72
1.74

1.77
1.80
1.83
1.85
1.88


1.91
1.93
1.96
1.99
2.01

2.04
2.07
2.09
2.12
2.14
2.17
2,20
2.22
2.25
2.27
1 mo
1.00
1.03
1.05
1.08
1.10
1.12
.15
.17
.19
.21
.24
.26
.28
1.30
1.32
1.34
1.36
1.38
1.40
1.42

1.44
1.46
1.47
1.49
1.51

1.53
1.55
1.56
1.58
1.60


1.62
1.63
1.65
1.67
1.68

1.70
1.71
1.73
.75
.76
.78
.79
.81
1.82
1.84
Ratio of annual maximum concentration to mean
concentration for averaging times of:
1 sec
1.00
1.44
2.04
2.83
3.86
5.18
6.3b
8.94
11.53
14.69
18.53
23.14
28.65
35.16
42.83
51.78
62.18
74.18
87.96
103.70

121.61
141.88
164.73
190.39
219.09

251.07
286.61
325.94
369.37
417.15

5 min
1.00
1.27
1.59
1.97
2.42
2.93
3.51
4.18
4.93
5.77
6.71
7.76
8.92
1hr
1.00
1.20
1.43
1.69
1.97
2.28
2.63
3.00
341
•:..fw
; :52
4.82
5.37
10.19 j 5.95
11.58; 6.5G
13.VI 7,21
14.76
16.5G
7.90
8.62
3hr
1.00
1.17
1.37
1.57
1.80
2.05
8hr
1.00
1.15
1.31
1.48
1.66
1.86
2.31 2.06
2.GO 2.28
2.9C 2.5I
3.22 2.75
3.56
3.92
4.oO
4.70
5.12
5.bt>
6.01
6.49
18.50 9.39 i 6.98
20.bf»

22.83
25.24
27.81
30.55
33.47

36.GG
39.84
43.31
46.97
50.82

j
469.601 5483
527.00
539.67
657.92
732.07

812.47
899.45
993.34
1094.51
1203.31
1320.11
1445.27
1579.16
1722.17
1874.68
59.14
63.60
68.28
73.17
10.19

1 1 .03
11.91
12.83
1 3.78
14.78

15.81
16.89
18.00
19.15
20.34


21.57
22.84
24.14
25.49
26.87
j
78.28
83.61
89.16
94.94
100.94
107.17
113.64
120.34
127.28
134.46
28.29
29.75
31.24
32.78
34.35
35.95
37.60
39.28
40.99
42.74
7.49

£.03
8.58
9.16
9.74
10.34

10.97
11.61
12.27
12.94
13.64


14.35
15.07
15.82
16.58
17.35

18.14
18.95
19.77
20.60
21.45
22.32
23.20
24.09
25.00
25.92
3.00
3.26
3.53
3.81
4.10
4.40
4.71
5.03
5.36
570

6.04
6.40
6.76
7.14
7.52

7.91
8.30
8.71
9.12
9.54


9.97
10.40
10.84
11.28
11.74

12.20
12.66
13.13
13.61
14.09
14.58
15.07
15.57
16.07
16.57
1day
1 00-
1.12
1.25
1.38
1.52
1.67
1.82
1.98
2.14
231
2.48
2,65
2.84
3.02
3.21
3.40
3.60
3.80
4.00
4.21

4.42
4.64
4.85
5.07
5.29

5.52
5.75
5.98
6.21
6.44


6.68
6.92
7.16
7.40
7.64

7.89
8.13
8.38
8.63
8.88
9.13
9.38
9.64
9.89
10.15
4 days
1.00
1.09
1.18
1.27
1.36
1.46
1.56
1.65
1.75
1.85
1.95.
2.05
2.15
2.26.
2.36
2. -16
2.57
2.67
277
2.38

2.98
3.09
3.19
3.30
3.40

3.51
3.01
3.72
3.32
3.93


4.03
4.13
4.24
4.34
4.44

4.55
4.65
4.75
4.86
4.96
5.06
5.16
5.26
5.36
5.46
1 mo
1.00
1.04
1.08
1.12
1.16
1.20
1.24
1.28
1.31
1.35
1.38
1.42
1.45
1.48
1.52
1.55
1.58
1.61
1.64
1.67

1.70
1.73
1.75
1.78
1.81

1.83
1.86
1.88
1.91
1.93


1.96
1.98
2.00
2.03
2.05

2.07
2.09
2.11
2.13
2.16
2.18
2.20
2.22
2.24
2.25
46
MODEL RELATING AIR QUALITY MEASUREMENTS TO STANDARDS

                  V-12

-------
Table 14(Continued). RATIO OF EXPECTED ANNUAL MAXIMUM POLLUTANT CONCENTRATION TO
          ARITHMETIC MEAN CONCENTRATION FOR VARIOUS AVERAGING TIMES
                      AND STANDARD GEOMETRIC DEVIATIONS
Standard geometric deviation for
averaging times of:
1 sec
5.08
5.19
5.30
5.41
5.52
5.63
5.74
5.85
5.96
6.08
6.19
6.30
6.42
6.53
6.65
5 min
3.78
3.85
3.91
3.98
4.05
4.11
4.18
4.24
4.31
4.38
4.44
4.51
4.58
4.65
4.71
1 hr
3.25
3.30
3.35
3.40
3.45
3.50
3.55
3.60
3.65
3.70
3.75
3.80
3.85
3.90
3.95
3hr
3.02
3.06
3.11
3.15
3.19
3.24
3.28
3.32
3.37
3.41
3.45
3.50
3.54
3.58
3.63
8hr
2.81
2.85
2.89
2.93
2.97
3.00
3.04
3.08
3.12
3.15
3.19
3.23
3.27
3.30
3.34
1day
2.59
2.62
2.65
2.68
2.71
2.75
2.78
2.81
2.84
2.87
2.90
2.93
2.96
3.00
3.03
4 days
2.30
2.32
2.35
2.37
2.39
2.42
2.44
2.47
2.49
2.52
2.54
.2.56
2.59
2.61
2.63
1 mo
1.85
1.87
1.88
1.90
1.91
1.93
1.94
1.95
1.97
1.98
2.00
2.01
2.02
2.04
2.05
Ratio of annual maximum concentration to mean
concentration for averaging times of:
1 sec
2037.07
2209.73
2393.06
2587.45
2793.31
3011.02
3241.01
3483.66
3739.39
4008.61
4291.72
4589.13
4901 .25
5228.49
5571.26
5 min
141.87
149.53
157.43
165.58
173.97
182.61
191.50
200.63
210.02
?'<».65
229.54
739.67
250.06
Ihr
44.53
46.35
48.20
50.09
52.01
53.96
55.95
57.97
60.02
62.1!
64.22
66.37
68.55
260.70 | /0.75
271.59
72.99
3hr
26.85
27.79
28.75
29.72
30.71
31.70
32.71
33.72
34.75
35.79
36.84
27.90
38.97
40.05
41.14
8hr
17.09
17.60
18.12
18.65
19.17
19.71
20.24
20.78
21.32
21.87
22.42
22.97
23.53
24.09
24.65
1day
10.40
10.66
10.92
11.18
11.44
11.70
11.96
12.22
12.48
12.74
13.00
13.26
13.53
13.79
14.05
4 days
5.56
5.66
5.76
5.86
5.96
6.05
6.15
6.25
6.34
6.44
6.53
6.63
6.72
6.82
6.91
1 mo
2.27
2.29
2.31
2.33
2.35
2.36
2.38
2.40
2.41
2.43
2.45
2.46,
2.48
2.49
2.51
Aver aging-Time Analyses
47
                                     V-13

-------
References

1.  Miller, M.E.  and Holzworth,  G.C.;  "An Atmospheric Diffusion Model
    for Metropolitan Areas";  JAPCA 17  pp. 46-50;  (1967)

2.  Federal Register 36 No.  158, August  14,  1971; Part 420--"Requirements
    for Preparation, Adoption and Submittal  of  Implementation Plans";
    Appendix A pp.  15494-15495.

3.  Holzworth, G.C.; "Mixing  Heights,  Wind Speeds, and Potential for
    Urban Air Pollution Throughout the Contiguous United States";
    CAP Publication AP-101  (January 1972).

4.  Kircher, D.S.  and Armstrong, D.P., "An Interim Report on Motor
    Vehicle Emission Estimation," EPA-450/2-73-003, October 1973.

5.  Turner, D. B., "Workbook of Atmospheric  Dispersion Estimates."
    999-AP-26 (1969).
                                 V-14

-------
VI.   Projections of Demographic  and  Economic  Indicators by SMSA

Enclosed in this section are the following:
1.  Projections of demographic and economic indicators by SMSA.
    Each State will receive only the date  pertinent  to its State.
    These projections were taken directly  from  Population and Ecpnomic
    Activity in the United States and Standard  Metropolitan Statistical
    Areas - Historical and Projected - 1950 - 2020,  prepared by  the
    U. S. Department of Commerce, Bureau of Economic Analysis (BEA)  in
    July 1972.
2.  A portion of the introduction to the BEA  projections  cited above,
    outlining the assumptions made in the  development of  the projections,
3.  A list of States and the name of the SMSA's located in each  State.
    This list is of the SMSA's as of January  7, 1972, not the most
    current list.
4.  A list of the SMSA's and the counties  which are  contained within
    each SMSA.  Again, these are the SMSA's of  January  7, 1972.

-------
                              INTRODUCTION

    This report presents projections of economic activity and population for
each of the Nation's  253  standard metropolitan statistical areas (SMSA's). l_/

    Although SMSA's include only 477 of the 3, 073 counties in the country,
they account currently for 70 percent of the Nation's population and 77 per-
cent of all personal income.  Because of the increasing concentration of
population in SMSA's and the attendant problems,  SMSA's are the object of
accelerating planning efforts.  Economic projections for these areas are
essential for rational water quality management planning as well as for  many
other uses  outside of the water resources field.

    These  SMSA projections are an extension of the OBERS 2/ water re-
sources program which has produced national and regional historical and
projected measures  of economic activity.  The measures include total
personal income, total population,  per capita income,  total employment,
total earnings, earnings for each of 28 industries  and indexes of production
for 4 mining and 15 manufacturing industry groups.  They include historical
data for 1950, 1959,  1968 and  1970 and projected data for 1975, 1980, 1985,
1990, 2000, and 2020.  Most users will not need the full array of data pre-
sentedo  However, the project  was designed to meet the wide variety of uses
to which the projections  may be put.

    These  projections, as with all efforts to look into the economic future,
are based upon an extension of past relationships.   The methodology used
has four characteristics which distinguish the results from those  of a simple
linear extension of trends at a  summary level.
     !_/  These include SMSA's as defined by OMB as of January 7, 1972, ex-
cluding those  in Puerto Rico and with the New England SMSA's defined on a
county rather than a township basis.  A list of the SMSA's and their county
composition is appended.  Included as SMSA's are Burlington, Vermont and
Cheyenne, Wyoming which are not designated as SMSA's by OMB, but which
are included in this report so that for planning purposes  every State has  at
least one SMSA or SMSA equivalent.

     "i_l  The OBERS program, initiated at the request of the Water Resources
Council (WRC) is  a joint undertaking of the Bureau of Economic Analysis (BEA)
of the Department of Commerce and  the Economic Research Service  (ERS) of
the Department of Agriculture.  This program acquired the acronym of OBERS
in the mid  1960's at which time BEA was  named the Office of Business
Economics  (OBE) and is a combination of OBE-ERS.  The widespread accept-
ance of the  term has  led to its continued use as a descriptive title of  the pro-
jection program even though OBE has been renamed BEA,

-------
      Fi ••••-!, the basic projections were made for 173 economic areas which
          entire Nation.  These areas were delineated by BEA using criteria
 ih ... make the areas especially suitable lor economic projection and analysis.

          nd, the 'economic area projections were made within the framework
          ons 1 inHi"-:dua'1 :.ndustries  in each of the 173 areas.  Various methods
•v'ere use:! t:, make the projections, depending upon the individual industry's
role in nil-: aiea's economy.  However, the methods used insure that in each
c.f :)ie 173 area.-- projected income and employment constitute an economy
\\.ih -.\r, inte rrally balanced structure.  The fact that the projections v/ere
prepared in inrlustri'-i! detail and  thus include the effects of variations  in
growth rates among individual, industries makes it possible for the projected
ovi'i-all economic, path of an area to depart substantially from past trends.

       i'fti; :v>:vhSA projections in this report have been broken out from the
econo.-riic arcA projections prepared under the OBERS program.  The
.methodology used in. 'breaking  out the SMSA projections was to determine
for each projected item the  trend in each SMSA's share of the  economic
area  of which i'c is a part.  This  trend in share was then extended on the
basis oi •:. i.Uect 1 ••„• a s L square:? regression line.  Projected percentages
were applied rr. t'h'' parent are:;, totals to obtain absolute values, with the
results subjected to judgmental review and adjustment by regional econo-
mists.  Ti'.is procedure builds on the large amount of analytical work done
for the Nation  and ,.ts economic areas and yields  a. set of projections which
are c.^nsvste.r.'t with rhose  being used by other agencies in planning.  The
projections at  the ecoy.ofJiLc area level have been reviewed by many State
agencies and field offices of Federal agencies.  Their suggested changes
have  been wva.'uated and taken into  account in a revision of initial pro-
jections.  The Sivl'SA breakouts reflect these  revisions.  3/
    _3/  A more complete description of the procedures employed in making
these SMSA projections is appended to this  report.  A detailed explanation
of the concepts and methodology used in preparing the OBERS projections
is contained in a report to be published shortly by the WRC entitled,  The
1972 OBERS Projections - Economic  Activity in  the United States by BEA
Economic Area.  Water  Resources Region and  Subarea,  and States, Historic -
al and Projected 1929-2020.

-------
                THE NATURE OF THE OBERS PROJECTIONS
      The OBERS projections, as are all other projections, are conditional
 orecasts  of the  future.  Inasmuch as it is not possible to foresee the future,
 lov.-ever,  projections must be based  on an extension of past relationships
 oelieved to have future relevance for the measures being projected.  The
 choice of the past relationships to be extended and the methodology for ex-
 tending them are based on assumptions, some of which are stated explicitly
 and some  of which are implicit in the projection methodology.  The pro-
 ;ections represent estimates of economic activity expected to develop during
 :he projection period if all assumed conditions  materialize.  The assumptions
 C-hosen represent those conditions believed to have the greatest probability of
 •2alization.  Thus the projections'represent  an attempt, imperfect though it
 .nay be, to forecast the economic future with the specification of assumptions
 and methodology introducing maximum objectivity into the process and giving
 the user a basis for appraising the validity of the projections.  The specifi-
 cation  of assumptions and methodology facilitates a consideration of alterna-
 tive projections  based on different assumptions and provides a foundation for
 the evaluation of program-oriented "what if"  questions.  The use of alterna-
 tive projections  will often be to reflect assumptions that are likely to material-
ize only if a specific program is undertaken to bring them about.

 Reliability

      Differing orders of reliability characterize the  various elements of the
 projections.  These differences are caused by variations in the length of the
 projection period, the size of the aggregate being projected, potentials for
 product substitution, and many other factors. A general understanding on
 the part of the user of the degree of reliability associated with any projection
 should help avoid misinterpretation and inappropriate use.  However, levels
 of reliability for the projections  cannot be stated in statistical terms.  They
 can only be evaluated qualitatively by the user with the results interpreted
 in light of the uses to which the projections will be put.

      Long range projections are less reliable than are those made for short
 periods; projections of small aggregates are  less reliable  than those of large
 magnitude.  Thus, projections for  1980 are more reliable  than those for 2020,
 and the reliability associated with the projections for any given industry in an
 SMSA is less than that for the same industry  in the Nation as a whole.  The
 reliability of the projections for  a minor industry will be much less than that
 for the more aggregated estimates of total  production, total employment or
 total income.

-------
     .'•Bother major factor in reliability of the projections  arises from
  •'  •/•..',£•:<•-s in the confidence that can be attached to basic assumptions used.
   • ••: assumptions are highly reliable characterizations of the future while
  .;or.9 .-ri* more conjectural.  A projection of the labor force at the national
  • 1 for 1 r?QO, for example, will almost certainly be  quite accurate because
  . Ir.U.. r force for those years will be drawn almost entirely from a popula-
  •>:'i  v/nose number and age distribution are known at the present time. The
  .. >r major uncertainty is the proportion of the population that will desire
co enter the labor force  and this fraction exhibits substantial stability,
ur<\v?ver, projection of the labor force  or of employment  in a given sub-
national area is related  not only to the current population of that area but
•\!so to interregional migration resulting from changes 'in employment
. .Ti-v-.rtumties.  Therefore, the future labor force of the smaller area depends
;•:•! ' Actors  which are less certain than those determining the  size  of the
'"3'ior.al labor force.

     Potential errors in  the planning process growing out  of errors in the
projections cannot be eliminated,  but their effects can be minimized through
the use  of sensitivity analysis  and by maintaining flexibility in plans in order
to accommodate deviations from the projections when they occur.

"\s9uroptions
     The projections  are based on longrun  or secular  trends  and ignore
the cyclical fluctuations which characterize the shortrun path of the economy.
The  general  assumptions that  underlie the projections are as follows:

     (1)  Growth of population will be  conditioned by a decline  of fertility
rates from those of the  1962-1965 period.

     (2)  Nationally, reasonably full employment,  represented by a 4 percent
unemployment rate,  will prevail  at the  points for which projections are made;
as in the past, unemployment  will be disproportionately distributed regionally,
but the disproportion will diminish.

     (3)  No foreign conflicts are assumed to occur at the projection dates.

     (4)  Continued technological progress and capital accumulation will support
a growth in private output per manhour of  3 percent annually.

     (5)  The new products that will appear  will be accommodated  within the
existing industrial classification  system, and,  therefore, no new  industrial
classifications are provided.

     (6)  Growth in output can be achieved without ecological disaster or
serious deterioration, although diversion of resources for pollution control
will  cause changes in the industrial mix of output.

-------
    The .regional projections are based on the following additional
assumptions:

    (1) Most factors that have influenced historical shifts in "export" indus-
try location will continue into the future with varying degrees of intensity.

    (2) Trends toward economic area self-sufficiency in local-service indus-
tries will continue.

    (3) Workers will migrate to areas of economic opportunities and away
-;.rom slow-growth or declining areas0

    (4) Regional earnings per worker and income per capita will continue
to converge toward the national average.

    (5) Regional employment /population ratios will tend to move toward the
national ratio.

-------
  "YATE
               B.E.A SMSA CODE AND TITLE
           INDEX OF TABLES

SHSA'S LISTED ALPHABETICALLY BY STATE

                        STATE        B.E.A SMS* CODE AND TITLE
                                                                                                                                   PAGE
ALABAMA
                                                                       CONNECTICUT
          323  BIRMINGHAM, ALA.
          943  COLUMBUS. GA.-ALA.
          555  FLORENCE. AL«.
          3*0  GAOSOEN, ALA.
          384  HUNTSVILLEt ALA.
          «24  MOBILE. ALA.
          42&  MONTGOMERY. ALA.
          508  TUSCALOOSA, ALA.
             72
            118
            164
            178

            210
            296
            304
            482
                                                                       930
                                                                       932
                                                                       931
                                                                       933
               BRIOG£PORT-NOR«ALK-STAMFORO. CONN.
               HARTFORD-NEK BRITAIN.  CONN.
               NEK HAVEN. WATERBURY-MERIOEN. CONN.
               NORWICH.GHOTON-NEW LONDON. CONN.
                                                                       DELAWARE
                                                                                 521  WILMINGTON, DEL.-N.J.-MD.
 80
202
S14
                                                                                                                                    510
ARIZONA
 .•;«/>NSAS
          531  ANCHORAGE. ALASKA
          4Jo  PHOENIX, ARIZ.
          $06  TUCSON, ARIZ.
366  FORT SMITH. ARK.-OKLA.
407  LITTLE KOCK-NOrtTH LITTLE ROCK. ARK.
418  MEMPHIS, TENN.-ARK..

451  PINE BLUFF. ARK.
502  TEXARKANA, TEX.-ARK.
CALIFORNIA
          30S  ANAHEIM-SANTA ANA.GARDEN GROVE. CALIF.
          316  BAKERSFIELD. CALIF.
          369  FRESNO. CALIF.
          409  LOS ANGELES-LUNG BEACH. CALIF.
          542  MODESTO. CALIF.
          445  OXNARO-SIMI VALLEY-VENTURA, CALIF.
          476  RIVERSIDE.SAN BERNADINO-ONTARIO. CALIF.
          468  SACRAMENTO, CALIF.
          533  SALINAS-SEASIOe-MONTEREY, CALIF.
          477  SAN DIEGO, CALIF.
          478  SAN FRANCISCO-OAKLAND, CALIF.
          479  SAN JOSE. CALIF.
          481  SANTA BARBAHA.SANTA MARIA-LOMPOC. CALIF.
          565  SANTA CRUZ. CALIF.
          $46  SANTA ROSA, CALIF.
          496  STOCKTON. CALIF.
          511  VALLEJO-FAIHf ULO-NAPA, CALIF.
                                                              36
            354
            478
                                                             170
                                                             262
                                                             288
                                                             356
                                                             470
             34
             54
            176
            268
            300
            340
            386
            396
            406
            414

            416
            418
            420
            422
            424

            458
            488
                                                                       D. C.
                                                                       FLORIDA
GEORGIA
HAWAII
                                                                                 513  WASHINGTON. D.C.-MD.-VA.
                                553  OAYTONA BEACH. FLA.
                                365  FORT LAUDEROALE-HOLLYWOOD,  FLA.
                                556  FORT MYERS. FLA.
                                J40  GAINESVILLE. FLA.
                                388  JACKSONVILLE. FLA.
                                559  LAKELAND-PINTER HAVEN. FLA.
                                5Ti  MELBOURNE.TITUSVILLE-COCOA, FLA.
                                420  MIAMI, FLA.
                                444  ORLANDO, FLA.
                                447  PENSACOLA, FLA.
                                567  SARASOTA. FLA.
                                499  TALLAHASSEE. FLA.
                                500  TAMPA.ST. PETERSBURG. FLA.
                                516  WEST PALM BEACH, FLA.
          302  ALBANY, GA.
          312  ATLANTA. GA.
          314  AUGUSTA. GA.-S.C.
          337  CHATTANOOGA. TENN.-GA.
          343  COLUMBUS. GA..ALA.
          414  MACON, GA.
          482  SAVANNAH, GA.
                                                                                 181  HONOLULU• HAWAII
                                                             130
                                                             166
                                                             168
                                                             180
                                                             218
                                                             242
                                                             286
                                                             290
                                                             336
                                                             346
                                                             426
                                                             464

                                                             466
                                                             496
                                                                                                                           20
                                                                                                                           46
                                                                                                                           50
                                                                                                                          102
                                                                                                                          118
                                                                                                                          276
                                                                                                                          428
                                                                                                                                    204
COLORADO
          341  COLORADO SPRINGS. COLO.
          350  DENVER. COLO.
          4»9  PUEBLO. CULO.
            112
            134
            372
                                                                        IDAHO
          325  BOISE CITY, IDAHO
                                                              76
                                                                        ILLINOIS
                                                                                 324  BLOOMINGTON-NOMMAL.  ILL.
                                                                                                                           •..,,"<•' :.J'.'- •'...' s .'••..-.   4,
                                                                                                                            '•  \ ••"••• I   '•>   I    •  if ,

-------
  STATF
               B.C. A SMSA CODE AND TITLC
                                                            |ND£» Of  TAbLES

                                                 SMSA'S LISTED ALPHABETICALLY BY STATE

                                                            PAGE          STATE        B.E.A  SMSA CODt  AND  TITLE
                                                                                                                                   PAGE
ILLINOIS       CONTINUED

          333  CHAMPAIGN.URBANA,  ILL.                          94
          336  C»-iCAGO.  ILL.                                  106
          347  0«VENPO»T-HOCK  ISLAND-MOLINE.  IOWA-ILL.        126
          349  CEOTUU.  ILL.                                  132
          4«e  PECBIA.  ILL.                                   348
          467  RCCKFCRD.  ILL.                                 394
          471  ST.  LOUIS,  MO.-ILL.                            402
          490  SPRING*ULO.  ILL,                              448
                                                                       LOUISIANA      CONTINUED

                                                                                 485  SHREVEPORT. LA.
                                                                       MAINE
                                                                                  9<>0
                                                                                  939
                                                                                      LEwISTON-AUBURN, MAINE
                                                                                      PORTLAND-SOUTH PORTLAND MAINE
                                                                       254
                                                                       362
INDIANA
IOBA
KANSAS
          309  ANDERSON, IND.
          35)  CINCINNATI, CH
          359  EV»r.iV!LLE. INU.-KY.
          367  FOPT «AtNE. IND.
          372  0»«T-MAMM0.1D-E«ST CH1C»60. INC.
          365  UCUNlPOLIS. IND.
          529  L«F*?ETTE.»EST LAFAYETTE, IND.
          >1C  L3USVILLE. KV.-IND.
          *27  HUNC1E. INO.
          *89  SCt'TH BEND. INC.
          301  TERRE HAUTE. INO.
          33;  CEC»I RAPIDS. IOWA
          31.7  DAVENPORT.ROCK ISLAND.MOLINE. low A-ILL,
          351  CE5 "DINES, IOWA
          353  31'SUO'JE, IOWA
          <,<.}  CM«HA, NEBfi.-lOwA
          486  S10U« CITY. 1OA-NEBR.
          525  WATERLOO. IOWA
          392  KANSAS CITY. MO..HANS.
          50k  TOPEKA, HANS.
          518  WICHITA. HANS,
                                                              38
                                                             toe
                                                             15*
                                                             172
                                                             ie»
                                                             212
                                                             238
                                                             270
                                                             306
                                                             ««2
                                                             468
                                                              92
                                                             126
                                                             136
                                                             HO
                                                             334
                                                             438
                                                             496
                                                             226
                                                             474
                                                             502
                                                                       MARYLAND
                    317  BALTIMORE, MO.
                    513  WASHINGTON, O.C.-MD.-V*.
                    521  WILMINGTON, DEL.-N.J..MD.
          MASSACHUSETTS

                    934
                    935
                    936
                    937
                    936
          MICHIGAN
                    310
                    552
                    319
                    352
                    36k
                    373
                    386
                    391
                    398
                    428
                    469
                    903
                                                                                       BOSTON,  MASS.
                                                                                       FALL  R|VER-NE»  BEDFORD,  MASS.
                                                                                       PITTSFIELO.  MASS.
                                                                                       SPRINGF1ELD.CHICOPEE-HOLYOKE.  MASS.
                                                                                       WORCESTER-FITCHBURG-LEOMINSTEH.  MASS.
ANN ARBOR, MICH.
BATTLE CREEK, MICH.
BAY CITY. MICH.
DETROIT. MICH.
FLINT, MICH.
GUotD RAPIDS. MICH.
JACKSON, MICH.
KALAMAZOO, MICH.
LANSING.EAST LANSING, MICH.  .
MUSKEGOI.-MUSKEGCIN HEIGHTS. MICH.
SAGINAH, MICH.
TOLEDO, OHIO-MICH.
                                               56
                                              494
                                              510
                                                                                                                                     78
                                                                                                                                     156
                                                                                                                                     360
                                                                                                                                     454
                                                                                                                                     514
 40
 60
 62
138
162
188
214
224
246
308
398
472
KENTUCKY
                                                                        MINNESOTA
          339  CINCINNATI, OHIO-KY.-IMD.
          359  EvunivKU. Inu.-KY.
          383  NUMU4C.TON-ASMLAND. w.VA.-KY.-OHlO
          ..Ok  LEXINGTON, KY.
          410  LOUISVILLE, KY.-INO.
          543  OHENSBORO, KY.
                                                             108
                                                             IJ4
                                                             208
                                                             256
                                                             270
                                                             338
                    354  OULUTH-SUPEDIOR. MINN..WIS.
                    361  FARGC.MOORI-HEAD. N.DAK..MINN.
                    423  MINNEAPOLIS.ST. PAUL,  MINN.
                    945  ROCHESTER, MINN.
                                              142
                                              158
                                              296  r
                                              190
                                                                        MISSISSIPPI
LOUISIANA
          551  ALEXANDRIA. LA.
          318  BATON ROUGE. LA.
          395  LAF,AYETTE. LA.
          3"96 ''LAKE .CHAR'C£i«t.LA.
          »25  MONROE, LA.    '• •
          434  NEW ORLEANS, LA.
 26
 98
236
240
302
316
                                                                                  535   BILOXI-GULFPORT,  MISS.
                                                                                  387   JACKSON,  MISS.
                                                                       MISSOURI
                                                                                                                                      68
                                                                                                                                     216
                                                                                                                                     114


-------
               8.6.A SHSA CODE AND TITLE
                                                            INDEX OF TABLES
                                                 SMSA'S LISTED ALPHABETICALLY  BY STATE
                                                            PACE         STATE        B.E.A SMSA CODE AND TITLE
                                                                                                                                   PAGE
MISSOURI       CONTINUED

          392  KANSAS CITY. MO.-KANS.
          470  ST. JOSEPH, HO.
          »71  ST. LOUIS, MO.-ILL.
          491  SPRINGFIELD. HO.
                                                                       NEW YORK
                                              226
                                              400
                                              402
                                              4JO
                    563
                    466
                    49T
                    910
CONTINUED
POUGHKEEPSIE. N.Y.
ROCHESTER. N.Y.
SYRACUSE. N.Y.
UTICA-ROME. N.Y.
366
392
460
NEBRASKA
          321  BILLINGS. MONT.
          374  GREAT FALLS, HONT.
          406  LINCOLN, NEBR.
          443  OMAHA. NEBR.-IOWA
          486  SIOUX CITY, 10WA-NEBR.
PtVAOA
          400
          463
LAS VEGAS. NEV.
RENO. NEV.
•:.•« HAMPSHIRE

          941  MANCHESTER, N.H.
K~M JERSEY
          309  ALLENTOWN.BETHLEHEM-EASTON, PA.-N.J.
          313  ATLANTIC CITY, N.J.
          369  JERSEY CITY, N.J.
          360  LONG BRANCH.ASBURY PARK. N.J.
          561  NEK BRUNSWICK-PERTH AMBOY-SAYREVILLE» N.J.
          436  NEWARK, N.J.
          446  PATERSON-CLIFTON-PASSAIC. N.J.
          449  PHILADELPHIA. PA.-N.J.
          509  TRENTON. N.J.
          536  VINELANO-M1LLVILLE-BRIOGETON, N.J.
          521  WILMINGTON, DEL.-N.J.-HO.
NEW MEXICO
          304  ALBUQUERQUE. N.MEX.
                                               66
                                              190
                                              260
                                              134
                                              438
290
J80
                                                             280
                                               28
                                               48
                                              220
                                              264
                                              312
                                              320
                                              344
                                              352
                                              476
                                              490
                                              510
                                                              24
          NORTH CAROLINA

                    311
                    336
                    355
                    362
                    557
                    176
                    461
                    922
ASHEV1LLE, N.C.
CHARLOTTE, N.C.
DURHAM, N.C.
FAYETTEVILLE, N.C.
GASTONU. N.C.
GREENSBORO-WINSTON-SALEM-HIGH POINT>N.C.
RALEIGH, N.C.
WILMINGTON, N.C.
                                                                       NORTH DAKOTA

                                                                                 361  FARGO-MOOREHEAO. N.OAK.-MINN.
                                                                       OHIO
                                                                       OKLAHOMA
                    301  AKRON. OHIO
                    331  CANTON, OHIO
                    339  CINCINNATI, OHIO-KY.-IND.
                    340  CLEVELAND, OHIO
                    344  COLUMBUS, OHIO
                    348  DAYTON, OHIO
                    378  HAHILTON-HIODLETOWN, OHIO
                    383  HUNTINGTON-ASHLANO, W.VA.-KY.-OHIO
                    405  LIMA, OHIO
                    408  LORAIN-ELYRIA, OHIO
                    5JO  MANSFIELD. OHIO
                    962  PARKEHSBURG-HAH1ETTA, W.VA.-OHIO
                    492  SPRINGFIELD, OHIO
                    499  STEUBENVILLE-NEIRTON. OHIO-W.VA.
                    503  TOLEDO, OHIO-MICH.
                    517  WHEELING, W.VA.-OHIO
                    526  YOUNGSTOWN-WARREN, OHIO
                                                                                 366  FORT SMITH. ARK.-OKLA.
                                                                                 402  LAWTON, OKLA.
                                                                                 442  OKLAHOMA CITY, OKLA.
                                                                                 507  TULSA, OKLA.
                                                                                                                     100
                                                                                                                     144
                                                                                                                     160
                                                                                                                     186
                                                                                                                     194
                                                                                                                     376
                                                                                                                     512
                                                                                                                                    158
                                               18
                                               90
                                              108
                                              110
                                              120
                                              128
                                              198
                                              208
                                              258
                                              266
                                              282
                                              342
                                              492
                                              456
                                              472
                                              500
                                              520
                                                                                                                     170
                                                                                                                     252
                                                                                                                     3)2
                                                                                                                     480
KTW YORK
                                                                       OREGON
          303  ALBANY-SCHENECTAOV-TROY, N.Y.
          322  BINGHAHTON, N.Y.-PA.
          330  BUFFALO, N.Y.
          994  ELHIRA. N.Y.
          435  NEW YORK. N.Y.
                                               22-
                                               70
                                               86
                                              148
                                              318
                                                                                  358   EUGENE-SPHINGFIELO. OREG.
                                                                                  456   PORTLAND. OREG.-WASH.
                                                                                  472   SALEM, OREG.
                                                                                                                     152
                                                                                                                     364
                                                                                                                     404

-------
               B.E.A  SMSA CODE AND TITLE
                                                            INCEX  OF  TABLES

                                                 SMSA'S LISTED  ALPHABETICALLY  BY  ST«T£

                                                            PAGE          STATE        B.C.* SKSA CODE AND TITLE
                                                                                                                                   BAGC
                                                                       TEXAS
          30!
          306
          Sil
          351
          379
          390
          39?
          *'«•?
          45?
          462
          "•S3
          120
          S69
          529
Al.LENTO»N-BE.T«L£HE"-EASTON. PA.-N.J.
AlTCCNA, PA.
8|NG"A«TGN. n.r.-PA.
E"lEt p«.
HIRHJSBL'RG. P».
JC«".STO»N.' PA.
LANCASTER, PA.
PHILADELPHIA, PA..N.J.
PITTS3UUGH, P».
RfAOlNG. PA.
SCPANTOf". 5>A.
• KKES-BAKRE-HAZLETON, PA.
•1LLIAMSPQHT. PA.
YORKi PA.
               PROVISENCE-PA»TUC*ET-WAR»1JC*.
SOOTH C«»OLINA
          3I-.
          568
SOUTH OAKOTA
AUGUSTA, GA.-S.C.
CHARLESTON. S.C.
COLUMBIA, s.c.
GBEENVILLE, S.C.
SPARTANbUKG, S.C.
               SIOUX FALLS, S.OAK.
                                               28
                                               30
                                               TO
                                              150
                                              200
                                              222
                                              2*»
                                              392
                                              358
                                              378
                                              *30
                                              906
                                              508
                                              911
                                                             368
                                                              93
                                                              96
                                                             116
                                                             196
                                                             ««*
                                                        UTAH
                                                                       VERMONT
                                                        VIRGINIA
     CONTINUED

»2l  HIDLANO. TE«.
»»0  ODESSA, TEX.
»7*  SAN ANGtLO. TEX.
»75  SAN ANTONIO, TEX.
53*  SHERiAN.OtNISoN. TEX,
502  TfXAKKANA, TtX.-»HK.
509  TTLEK, TEX.
512  xACO, TEX.
519  kICHlTA FALLS, TEX.
                                                                                 *«.!  OGOEN, UTAH
                                                                                 »56  PDOVO.ORE.M, UTAH
                                                                                 »T3  SALT LAKE CII», UTAH
                                                                                 92?  BURLINGTON, VT.
                                                                  413  LYNCMBURG. VA,
                                                                  437  NEWPORT NEliS-HAMPTON, VA.
                                                                  43e  NORFOLK-PORTSMOUTH. VA.
                                                                  944  PETERSBURG-HOPE«ELL, VA.
                                                                  464  RICHMOND, VA.
                                                                  469  ROANOKE, VA.
                                                                  913  WASHINGTON, D.C.-MD.-VA,
292
32«
410
412
4J4
470
484
492
504
                                                                                                                      330
                                                                                                                      370
                                                                                                                      406
                                                                                                                                      88
                                                                                                                      27*
                                                                                                                      322
                                                                                                                      32*
                                                                                                                      390
                                                                                                                      384
                                                                                                                      388
                                                                                                                      494
                                                                       WASHINGTON
TENNESSEE
          337  CHATTANOOGA. TENN.-GA.
          394  KNO>VILLE, TENN.
          418  MEMPHIS, TENN.-ARK.
          429  NASHVILLE. TENN.
                                              102
                                              232
                                              288
                                              310
                                                                  496  PORTLAND, OKEG.-WASH.
                                                                  964  RICHLAND-KtNNE»lCK« HASH.
                                                                  484  SEATTLE-EVERETT, «ASH.
                                                                  4B9  SPOKANE. HASH.
                                                                  498  TACOMA, MASH.
                                                                  $70  YAKIMA, MASH.
                                                    96*
                                                    382
                                                    432
                                                    *»6
                                                    462
                                                    916
TEXAS
          300  ABILENE. TEH.
          307  AHARlLLO, TEX.
          S15  AUSTIN, TEX.
          3^0  BEAUMONT-PORT ARTHUR-ORANGE, TEX.
          329  eROwnSvILLE-HARLlNGEN.SAN BENITO. TE>.
          538  BRVAN.COLLEGE STATION, TEX.
          j»i  CORPUS CHRISTI, TEX.
          346  DALLAS. TE>.
          316  EL PAbO. TEX.
          368  fORT »ORTH, TEX.
          }71  OALVESTON-TEXAS CITY. TEX.
          382  "OUSTON, TEx.
          558  KILLEEN-TEMPLE, TEX.
          399  LAREOU, TEX.
          412  LUBBOCK, TEx.
          932  ACALLEN.PHARR.EDINBURO. TEX.
                                               16
                                               32
                                               92
                                               64
                                               82
                                               84
                                              122
                                              124
                                              146
                                              174
                                              182
                                              206
                                              230
                                              248
                                              272
                                              284
                                                        WEST VIRGINIA

                                                                  335
                                                                  383
                                                                  962
                                                                  495
                                                        WISCONSIN
     CHARLESTON. ».VA.
     HUNTINGTON-ASHLAND, W.VA.-KY.-OHIO
     PARKERS6URG-MARIETTA, M.VA..OHIO
     STEUBENvlLLE-kEIRTON, OHIO-w.VA.
                                                                  917  HHEELING, D.VA..OHIO
                                                                  537  APPL'ETON-OSHKOSH,  *is.
                                                                  394  DULUTh-SUPERIUK, MINN.-HIS.
                                                                  379  GREEN  BAY,  »lb.
                                                                  393  HENOSHA,  »is.
 98
208
342
456
900
                                                     42
                                                    142
                                                    192
                                                    228

-------
-iVITE        B.E.A SHSA CODE AND TITLE
     CONTINUED

9*1  LA CSOSSE, HIS.
»19  MADISON. HIS.
*22  MILWAUKEE. MIS.
*60  RACINE. MIS.
                                                          INDEX OF TABLES

                                                      LISTED ALPHABETICALLY BY STATE

                                                          PAGE
                                                           21*
                                                           278
                                                           2»»
                                                           JT»
"t.NG
             CHEYENNE. *yo.
                                                           10*

-------
    The following is a list of the Standard  Metropolitan  Statistical
Areas (SMSA's) indicating the constituent counties  as  of  January  7,
1972.  The projections ofDemographic and economic  indicators,  done
by the Bureau of Economic Analysis (BEA), Department of Commerce,
was made on the basis of SMSA's as they were defined as of  January 7,
1972.
    The following SMSA designation differs from the official  designation
of the Office of Management and Budget in one respect:  SMSA's  in the
New England States are officially defined on a township,  rather than a
county basis; BEA projections for these New  England SMSA's, however,
are based upon geographic areas which are defined on.a whole-county
basis.  Thus, for example, the Fitchburg-Leominster, Mass., SMSA, and
the Worcester, Mass., SMSA are combined in the BEA projections  into one
area, Worcester County, even though the Fitchburg-Leominster SMSA
officially includes several townships from another county (Middlesex)
and portions of Worcester County are not officially located in  either
SMSA.

-------
       ABILENE,  TEX.
                                       COW? COMPOSITION OF jl-^A' i
                                    SMSA'S LISTED IN B.E.A. COOL NUMBER ORDER


                                                    313   ATLANTIC  CITY, N.J.
 301
302
30*
305
306
307
306
309
310
311
JONES
TAYLOR

AKRON, OHIO

PORTAGE
SUMMIT

ALBANY, GA.

DOUGHERTY

ALBANY-SCHENECTAOY-TROY, N.Y.

ALBANY
RENSSELAER
SARATOGA
SCHENECTADY

ALBUQUERQUE, N.M.

BERNALILLO
ALLENTOWN-BETHLEHEM-EASTON. PA
WARREN
LEHIGH
NORTHAMPTON

ALTOONA, PA.

BLAIR

AMARILLO, TEX.

POTTER
RANDALL

ANAHEIM.SANTA ANA-GARDEN GRQVE
ORANGE

ANDERSON, INO.

MADISON

ANN AHBQR, MICH.

WASHTENAw

ASHEVILLE, N.C.
TEX.
TEX.



OHIO
OHIO

.

GA.



' N.Y.
N.Y.
N.Y.
N.Y.



N.M.
.-N.J..
N.J.
PA.
PA.



PA.



TEX,
TEX.

. CAL.
CAL.



IND.



MICH.


ATLANTIC

314 AUGUSTA, GA.-S.C.

AJKEN
RICHMOND

315 AUSTIN, TEX.
(
TRAVIS

. 316 BAKERSKIELD, CAL.

KERN

317 BALTIMORE* MD.
ANNE ARUNDEL
BALTIMORE
BALTIMORE (INDEPENDENT CITY)
CARROLL
HARFORD
HOWARD
318 BATON ROUGE, LA.
EAST BATON ROUGE

319 BAY CITY, MICH.

BAY

320 BEAUMONT-PORT ARTHUR-ORANGE, TEX

JEFFERSON
ORANGE

321 BILLINGS, MONT.
YELLOWSTONE

322 BINGHAMTON, N.Y. -PA.

BROOME
TIOGA
SUSOUEHANNA

323 BIRMINGHAM, ALA.
JEFFERSON
SHELBY
WALKER
N.J.



s.c.
GA.



TEX.



CAL.


MD.
MD.
MD.
MO.
MD.
MD.

LA.



MICH,

•

TEX.
TEX.


MONT.



N.Y.
N.Y.
PA.


ALA.
ALA.
ALA.
        BUNCOMBE
312   ATLANTA, GA.

        CLAYTON
        COBB
        GWINETT
        DEKALB * FULTON
                                      N.C.
GA.
GA.
GA.
GA.
                                                   324   BLOOMINGTON-NORMAL, ILL,

                                                           MCLEAN
                                                                                         ILL.

-------
   COUNTY COMPOSITION OF
SMSA'S LISUD IN B.E.A.  CODE NUMBEH ORDER
12"


3?9



330



•m


332


333


334


33S


336





337




338










339




BOISE QTY, IDA.

AJA
BKOXflSVRLE.HAKLINGEN.SAN
CAMERON


BUFFALO, N.Y.
ERIE
til AGARA

CANTON. CHJO
STARK.

CEDAR RAPIDS, IA.
LINN

CHAMPAJGN-URBANAt ILL.

CHAMPAIGN
CHARLESTON, S.C.
BERKELEY
CHARLESTON
CHARLESTON, W.VA.
KANAWHA

CHARLOTTE, N.C.

MECKLENBURG
UN I ON


CHATTANOOGA, TENN.-GA.

HAMILTON
W«L*ER

CHICAGO, ILL.

LAKE
COOK
DU PAGE
KANE
LAKE
MCHENRY
WILL


CINCINNATI, OHlO-KY.-JND.
CLERMONT
HAMILTON
WARREN
DFARbORN


IDA.
BFNITO, TEX.
TEX.



N. Y»
N.Y.


OHIO


IOWA



ILL.

S.C.
S.C.

W.VA.



N.C.
N.C.




TENN.
GA.



INO.
ILL.
ILL.
ILL.
ILL.
ILL.
ILL.



OHIO
OHIO
OHIO
INO.
BOONE
CAMPBELL
KENTON
340 CLEVELAND, OHIO
CUYAHOGA
GfAUGA
LA6 DALLAS. TEX.

COLLIN
DALLAS
DENTON
ELLIS
KAUFMAN
ROCKWALL

347 DAVENPORT-ROCK ISLAND-MOLINE.

HENRY
ROCK ISLAND
SCOTT


348 DAYTON, OHIO

GREENE
MIAMI
MONTGOMERY
PREBLE

349 DECATUR, ILL.

MACON
(CY,
KY.
KY.

OHIO
OHIO
OHIO
OHIO


COLO.


S.C.
S.C.


GA.
GA,
ALA.

OHIO
OHIO
OHIO

TEX.
TEX.



TEX.
TEX,
TEX.
TEX.
TEX.
TEX.

IA.-ILL.

ILL.
ILL.
IOWA




OHIO
OHIO
OHIO
OHIO



ILL.

-------
                                      COUNTY COMPOSITION OF SMSA'S
                                   SM5A«S LISTED I« B.E.A. CODE NUMBER ORUE«
350   DENVER* COLO.
                                                  36*   FLINT* MICH.



351

352



353


35*



355


356

•
357

358


359



361



362





ADAMS
ARAPAHOE
BOULDER -
DENVER
JEFFERSON
DES MOJNES, IA.
POLK
DETROITi MICH,
MACOMB
OAKLAND
WAYNE

DUBUOUE, IA.
DUBUOUE

DULUTH-SUPERIOR, MINN.-WISC.
DOUGLAS
ST. LOUIS

DURHAM, N.C.
DURHAM
ORANGE
EL PASO, TEX.
EL PASO
ERIE* PA.
ERIE
EUGENE-SPRINGFIELD, ORE,
LANE

EVANSVILLE, IND.-XY.
VANDERBU9GH
WARWICK
HENDERSON
FARGO-MOORHFAD, N.D.-MINN,
CLAY
CASS

FAYETTEVILLE, N.C.
CUMBERLAND




COLO.
COLO.
COLO.
COLO.
COLO.

IOWA

MICH.
MICH.
MICH.


IOWA


wise.
MINN.


N.C.
N.C.

TEX.

PA.

ORE.


IND.
IND.
KY.

MINN.
N.D.


N.C.




GENESEE
LAPEER

365 FORT LAUDERDALE-HOLLYWOOD, FLA
BROWARD
366 FORT SMJTH, ARK. -OKLA.
CRAWFORD
SEBASTIAN
LE FLORE
SEOUOYAH

367 FORT WAYNE, IND.
ALLEN

368 FORT WORTH, TEX,
JOHNSON
TARRANT

369 FRESNO, CAL.
FRESNO

370 GADSDEN, ALA.
ETOWAH
371 GALVESTON-TEXAS CITY, TEX.
GALVESTON
372 GARY-HAMMOND-EAST CHICAGO, IND
LAKE
PORTER

373 GRAND RAPIDS, MICH,
KENT
OTTAWA

37* GREAT FALLS, MONT.
CASCADE
375 GREEN BAY* MSC.

BROWN

376 GREENSBORO-* I NSTGN-SALEM-H I GH
FORSYTH
GUILFCRD
RANDOLPH
YADKIN
MICH.
MICH.

t
FLA.

ARK.
ARK.
OKLA.
OKLA.


IND.


TEX.
TEX.


CAL.


ALA.

TEX.
.
IND.
IND.


MICH.
MICH.


MONT,


WISC.

P01NT*N
N.C.
N.C.
N.C.
fi.C.

-------
                    COUNTY COMPOSITION or
                 SMSA'S LISTtD IN B.E.A, CODE NOP-BER ORDER
S.C.
                                338   JACKSONVILLEi  fLA.



'•"'•


379





361

382





383




38*


385






386


387

-- .-•*'"v
^•TLNVjLLr
PiO-E'iS

HAKlLTCM-MtDC!L£TOWN»
DUTLtR

HA^P J SbuRCi PA
'
CfMBEKLAND
DAiPHIN
Pr i^R Y

HONOLULU, HAWAII
HONOLULU
HOUSTON, TEX,

BRAZORJA
FC&T BENO
HARHIS
LIBfcRTY
MONTGOMERY

HUNT I NGT ON. ASHLAND,
LAWRENCE
CA8ELL
WAYNE
BOYD

HUNTSVILLE, ALA.
LIMESTONE
MADISON

INDIANAPOLIS, IND.
DOONE
HAMILTON
HANCOCK
HENDRICKS
JOHNSON
MARION
MORGAN
SHELBY
JACKSON, MJCH,
JACKSON

JACKSON, MISS.
HINDS
•) y.R/VNKIN
S.C.
s.c.

OHJO
OHIO



PA.
PA.
PA.


HAWAII


TEX.
TEX.
TEX.
TEX.
TEX.

W.VA.-KY.-OHIO
OHIO
W.VA.
W.VA.
KY.


ALA.
ALA.


IND.
IND.
IND.
IND.
IND.
IND.
IND.
IND.

MICH.


MISS.
MISS.


389


390





391

392





393


39*



395
'

396


397


398



399

VUVML

JERSF* CITY, N.J.
HUDSON

JOHNSTOWN, PA.

CAMBRIA
SOMERSET
•

KALAMA200, MJCH.
KALAMAZOO
KANSAS CITY, MO. -KAN,
CASS
CLAY
JACKSON
PLATTE
JOHNSON
WYANDOTTE

KENOSHA, WJSC,
KENOSHA

KNQXVILLE» TENN.
ANDERSON
BLOUNT
KNOX
LAFAYETTE' LA.
LAFAYETTE

LAKE CHARLES, LA.
CALCASIEU

LANCASTER, PA.

LANCASTER
LANSING-EAST LANSING, MICH.
CLINTON
EATON
INGHAM

LAREDO. TEX.
Ljraa
ruA.


N.J.



PA.
PA.



MICH.

MO.
MO.
MO.
MO.
KAN.
KAN.


wise.


TENN.
TENN.
TENN.

LA.


LA.



PA.

MICH.
MICH.
MICH.


TCw _
                                  ^ ^   ^

-------
                                      COUNTY COMPOSITION Of SMSA'S
                                   SMSA'S LISTED IN B.E.A.  CODE  NUMBER  ORDER
40C   LAS VEGAS, NEV.
402   LAWTON, OKLA.

        COMANCHE


404   LEXINGTON, KY,

        FAYETTE


      LIMA, OHIO
                                      NEV.
                                      OKLA.
                                      »CY.
                                                        MEMPHIS, TENN.-ARK.
                                                          SHELBY
                                                          CRITTENDEN
420   MIAMI, FLA.
        DADE

421   MIDLAND, TEX.
        MIDLAND

422   MILWAUKEE, wise.
                                                                                        TENN.
                                                                                        ARK.
                                                                                        FLA.
                                                                                        TEX.
\, ALLEN
,v, PUTNAM
' ' , VW -*ERT


406 LINCOLN, N£B.
LANCASTER

OHIO
OHIO
OHIO



NEB.

407 LITTLE ROCK. NORTH LITTLE ROCK, ARK.

PULASKI
SALINE

408 LORAIN-ELYRIA
LORAIN



ARK.
ARK.

, OHIO
OHIO



MILWAUKEE
OZAUKEE
WASHINGTON-
WAUKESHA

423 MINNEAPOLIS-ST. PAUL, MINN
ANQKA
DAKOTA
HENNEPIN
RAMSEY
WASHINGTON

424 MOBILE, ALA.
BALDWIN
MOBILE


wise.
wise.
MISC.
wise.

.
MINN.
MINN.
MINN.
MINN.
MINN.
i
!|
ALA!
ALA.I
1 '
409 LOS ANGELES-LONG BEACH, CAL.

LOS ANGELES
«na»

CAL.
«a»
410 LOUISVILLE, KY..IND.
CLARK
FLOYD
JEFFERSON

412 LUEBOCK, TEX,

LUBEOCK

IND.
IND.
KY.



TEX.

425 MONROE, LA.

OUACHJTA
426 MONTGOMERY, ALA.
ELMOPE
MONTGOMERY

427 MUNCIE, IND.

DELAWARE

428 MUSKEGON-MUSKEGON HEIGHTS,


LA.

ALA.
ALA.



IND.

MICH.
413 LYNCHBURGt VA,

AMHERST
CAMPBELL

414 K.ACON, GA.

8138
HOUSTCN

415 MADISON, Wjsc

DftNE

1^4;>>-Kv;:...:.--V

VA.
VA.



GA.
GA.

1

wise*

••' /' •'-'V":'-.1C '••'"'.'•''''""•' • '• ':"';
MUSKEGON


429 NASHViLLEt TENN.
DAV5DSON
5UMNER
KILSCN

434 NEW ORLEANS, LA.

JtF':tRSON
C~LE...';o
!j',. '.r.S.-:. -s
si. ; t*:Mif. c
MICH.



TENN.
TENN,
TENN.



LA.
Uft;
LA.
> ** '

-------
'.3i   t.C1* YC'I-'K* N.Y.
                                       COUNTY rOMPOSlTICN OF SMSA'S
                                    SMSA'S LISTtD IN B.E.A. CODE NUMBER  ORDER
    446   PATf.R!>ON-CLJFTON-PASSAIC«  N.J.
fi.'.yl.'-IJ
RLOLAflO
!.>l'H OLK
hi '-.TC'iL-TFR
r,!> YORK. CITY (5 BOKOUGHS)
!•••»
•**•"» -
se.
^^^^^^MMB^k
22?^


436 NEWARK. N.J.
ESSEX
MORRIS
UNION


437 NEWPORT NEwS-HAMPTON» VA.

YORK


N.Y.
N.Y.
N.Y.
N.Y.
N.Y.
35T
ss
5£
7ST



N.J.
N.J.
N.J.




VA.


UFRGEN
PASSAIC


447 PENSACOLA. FLA.
ESCAMBIA
SANTA ROSA
446 PEORIAt ILL.
PEOHIA
TAZEWELL
WOODFORD .

449 PHILADELPHIA, PA. -N.J.

BURLINGTON
CAMOEN
GLOUCESTER
BUCKS
CHESTER
DELAWARE
MONTGOMERY
PHILADELPHIA
N.J.
N.J.



FLA.
FLA.

ILL.
ILL.
ILL.



N.J.
N.J.
N.J.
. PA.
PA.
PA.
PA.
PA.
438 NORFOLK-VIRGINIA BEACH-PORTSMOUTH, VA,
CHESAPEAKE CITY
VIRGINIA BEACH
VA.
VA.
450 PHOENIX, ARIZ.



440   ODESSA, TEX.

        ECTOR

441   QGDEN, UTAH

        WEBER
                                       TEX.
                                       UTAH
            MARICOPA

    451    PINE BLUFF, ARK.
            JEFFERSON
    45Z    PITTSBURGH, PA.
445   OXNAPD-SIMI VALLEY-VENTURA,  CAL'IF',

        VENTURA      ,         .:.   •--   CAL..
-,       >;•;.; PUEBLO  '   .

    460   .RACINE* WISC.
 f  ' .     ' ,      •     .
 '        ; :  RACINE   .
                                                                                          ARIZ.
                                                                                          ARK.


442 OKLAHOMA CITY, OKLA,

CANADIAN
CLEVELAND
OKLAHOMA

443 OMAHA, NEB.-IA.
. . •' ' .,
: ' PCTTAWAJ-TAMIE
,•-..-•" -DOUGLAS '"•-,-••> "•"•? .-^-^
SARPY . . '••

444 ORLANDO, FLA,'
ORANGE
'SEMINOLE .. • .




OKLA,
OKLA.
OKLA,



JOWA^
••"•.-> ,'''
*''\ ,, -r • ' - ' • ' •
456 .PROVO-OREM, UTAH
•• ,.' UTAH • ;-'.v .• •;•';•-
-' , ' . :"' .. ''. . . ' -.,.'' ' "• / •••'; ..
.- 459:. PUEBL-0,. COLO, ."'.';•- < •'' ,
PA.
PA.
PA.
PA.



WASH.
-,ORE. -
•;<-<- wfei"'!
ORE. 'i
. ,


UTAH' ,-•
• ? '• ..,-•• '"•
"'..'' ' '•
                                                                                          'COLO,
                                                                                          wise.

-------
                                      COUNTY COMPOSITION OF SMSA'S
                                   SMSA'S LISTED IN B.E.A. CODE NUMBER ORDER
                                                  472   SALEM, ORE.
462
463
465
466
46?
468
MAKE

READING, PA.

BERKS


RENO, NEV.
WASHOE

RICHMOND, VA.
CHESTERFIELD
HANOVER
HENRICO

ROANOKE, VA.

ROANOKE

ROCHESTER, N.Y.
LIVINGSTON
MONROE
ORLEANS
WAYNE
ROCKFORD, ILL.
BOONE
WINNEBAGO

SACRAMENTO, CAU.
PLACER
SACRAMENTO
YOLO

N.C.



PA.



NEV.


VA.
VA.
VA.



VA.


N.Y.
N.Y.
N.Y.
N.Y.

ILL.
ILL.


CAL.
CAL.
CAL.

MARION
POLK

473 SALT LAKE CITY. UTAH

DAVIS
SALT LAKE

474 SAN ANGELO. TEX.
TOM GREEN

475 SAN ANTONIO, TEX.

BEXAR
GUADALUPE

ORE.
ORE.



UTAH
UTAH


TEX.



TEX.
TEX.

476 RIVERSIDE-SAN BERNARDINO-ONTARIO, CALIf.

RIVERSIDE
SAN BERNARDINO
477 SAN DIEGO, CAL.

SAN DIE&0

470 SAN FRANCISCO-OAKLAND, CAL.
ALAMEDA
CONTRA COSTA
MARIN
SAN FRANCISCO
SAN MATED

479 SAN JOSE. CAL.
SANTA CLARA

CAL.
CAL.


CAL.


CAL.
CAL.
CAL.
CAL.
CAL.


CAL.
469   SAGINAW, MICH.

        SAG INAW


470   ST. JOSEPH, MO.

        BUCHANAN


471   ST. LOUIS, MO.-ILL.

        MADISON
        ST. CLAIR
        FRANKLIN
        JEFFERSO'4
        ST. CHARLES
        ST. LOUIS
MICH.
MO.
ILL,
ILL,
MO,
MO.
MO.
MO,
461   SANTA BARBARA-SANTA MARJA-LOMPoC, CALIF.


        SANTA BARBARA                 CAL.
        ST. LOUIS (INDEPENDENT CITY)  MO.
48Z   SAVANNAH, GA.

        CHATHAM


483   SCRANTON, PA.

        LACKAWANNA


484   SEATTLE-EVERETT, WASH.

        KING
        SNOHCMI5H
                                                  GA.
PA.
                                                                                        WASH.
                                                                                        WASH ,

-------
                                       COUNTY COMPOSITION OF  SMSA'S
                                          LisTto  in B.E.A. CODE NUMBER ORDER
 ABU    SHPfVti-'CRT,  LA.
            500   TAMPA-ST. PETERSBURG, FLA.

* 6
487

',88

689
HOS51ER
CADOO
SIOUX CITY, IA.-NEB.
WCODBURY
DAKOTA
SIOuX FALLS, 5.0.
MINNEHAHA
SOUTH BEND, INC.
MARSHALL
57. JOSEPH
SPOKANE, WASH.
LA,
LA.

IOWA
NEB.
S.D,

IND.
IND.

HILL3BOROUGH
PINELLAS
501 TERRE HAUTE, IND.
CLAY
SULLIVAN
VERMILLION
VI GO
502 TEXARKANA. .TEX.-ARK.
MILLER
BOWIE
503 TOLEDO. OHIO-MICH,
MONROE
LUCAS
WOOD
FLA.
FLA.

IND.
IND,
IND.
IND.

ARK.
TEX.

MICH.
OHIO
OHIO
        SPOKANE

490   SPRINGFIELD, ILL,
        SANGAMON

«9l   SPRINGFIELD. MO.
        GREENE

492   SPRINGFIELD, OHIO
        CLARK

495   STEUBENVILLE-WEIRTON, OHIO-W.VA.
        JEFFERSON
        BROOKE
        HANCOCK

*96   STOCKTON, CAL.
        SAN JOAOUIN

497   SYRACUSE, N.Y,
        MADISON
        ONONDAGA
        OSWEGO

498   TACOMA, WASH.
        PIERCE

499   TALLAHASSEE, FLA.
        LEON                          FLA.
WASH.
ILL,
MO.
OHIO
OHIO
W.VA.
W.VA,
CAL,
N.Y,
N.Y.
N.Y.
WASH,
504   TOPEKA, KAN.
        SHAWNEE
505   TRENTON, N.J.
        MERCER
506   TUCSON. ARIZ.
        PIMA
507   TULSA. OKLA.
        CREEK
        05AGE
        TULSA
508   TUSCALOOSA, ALA.
        TUSCAL005A

509   TYLER. TEX.
        SMITH

510   UTICA-ROME, N.Y.
        HERKIMER
        ONE I DA
511   VALLEJO-FAIRFIELD-NAPA. CALIF.
        NAPA
        SOLANO
                                                  KAN,
                                                  N.J.
                                                  ARIZ.
OKLA.
OKLA.
OKLA.
                                                  ALA*
                                                  TEX,
                                                  N.Y.
                                                  N.Y.
                                                  CAL.
                                                  CAL.

-------
                                      COUNTY COMPOSITION OF SMSA'S
                                   SMSA'S LISTED IN B.E.A. CODE NUMBER ORDER
512   WACO, TEX.

        MC LENNAN

513   WASHINGTON, D.C.-MD.-VA.

        MONTGOMERY
        PRINCE GEORGES
        DISTRICT OF COLUMBIA
        ARLINGTON
        FAIRFAX
        LOUDOUN
        PRINCE WILLIAM

515   WATERLOO, IA.
        BLACK HAWK

516   WEST PALM BEACH, FLA.

        PALM BEACH

517   WHEELING, W.VA.-OHIO

        BELMONT
                                                  525   YORK, PA.
        MARSHALL
        OHIO
5i8   WICHITA, KAN.

        BUTLER
        SEDGWICK
TEX.


MD.
MD.
D.C.
VA.
VA.
VA.
VA.
ADAMS
YORK
526 YOUNGSTOWN.WARREN, OHIO

MAHQNING
TRUMBULL


527 BURLINGTON, VT.

PA.
PA.


OHIO
OHIO




                                      IOWA
                                      FLA,
                                      OHIO
W.VA,
W.VA,
KAN.
KAN.
                    CHITTENDEN


            528   CHEYENNE, WYO.

                    LARAMIE
                                                                                        VT.
                                                                                        WYOM.
529   LAFAYETTE-WEST LAFAYETTE* IND.

        TIPPECANOE                    INO.

530   MANSFIELD, OHIO
        RICHLAND                      OHIO

531   ANCHORAGE* ALASKA
        THIRD JUDICIAL DISTRICT       ALASKA

532   MCALLEN-PHARR-EOINBURG, TEX.

        HIDALGO                       TEX.
      WICHITA FALLS, TEX.

        ARCHER
        WICHITA
520   WILKES-BARRE-HA2LETON, PA,

        LUZERNE


521   WILMINGTON, DEL.-N.J.-MD.

        SALEM
        NEW CASTLE
        CECIL


522   WILMINGTON, N.C.

        BRUNSWICK
        NEW HANOVER
TEX.
TEX.
PA.
N.J.
DEL,
MD.
N.C,
N.C,
533   SALINAS-SEASIDE-MONTEREY,1 CALIF.

        MONTEREY                      CAL.
53*   S.HERMAN-DEN1SON, TEX,
        GRAYSON

535   BILOXI-GULFPORT, MISS.
'•       HARRISON
                                                  TEX.
                                                  MISS.
            536   VINEI.AND-MILLVILLE-BRIDGETON, N.J,

                    CUMBERLAND                    N.J.
537   APPLETCN-OSHKOSH, WISCONSIN

        CALUMET                       WISC,
        OUTAGAMIE                     WISC,
        WINNEBAOO                     wise,

-------
                                      COUNTY COMPOSITION OF SMSA'S
                                        j LISTED IN B.E.A. CODE NUMBER ORDER
538   (.•RVMI-CCUtv.i STATION, TEXAS
                                      TEX,
539
5-C
          MISSOURI
        BOONE
GAINESVILLE, FLORIDA
  ALACHUA

Li CRC5SC. *; SCONS IN
  LA C
            O, CALIFORNIA
        STANISLAUS
        D4VIES
                                      FLA.
                                      WISC.
                                CALIF.
                                KY.
      Ptli;R:ii".'RG.COLONIAL HEIGHTS-HOPEWELL. VA,
551
Jii
        35NWICD1E » PETERSBURG  .
        PRJNCE OECROE » HOPEWELL
ROCHESTER, MINNESOTA
  OLMSTEAO
SANTA ROSA. CALIFORNIA
  SONOMA
ALEXANDRIA, LA.
  RAPIDES
tiATTLF. CREEK. MICH.
  CALHOUN
553   CAYTONA BEACH. FLA.
E'.MIPA. N. Y,
  CHEMUNG

FLORENCE. ALA.
  COLBERT
  LAUOEROALE
                                VA.
                                VA.
                                      MINN.
                                      CALIF.
                                      LA.
                                      MICH.
                                      FLA,
                                      N.Y.
                                      ALA.
                                      ALA.
                                                  F03T  MYERS,  FLA.
                                                    LEE
            557   GASTCNIA. N.  C.
MO.                 GASTON
            558   KILLEEN. TEMPLE. TEXAS
                    BELL
                    COR TELL
                                                                                        FLA.
                                                                                        N.C.
TEX.
TEX.
            559   LAKELAND-WINTER HAVEN. FLA.
                    POLK                          FLA,
            560   LONG BRANCH. ASBURY PARK, N. J.
                    MONMOUTH
                                                                                        N.J.
            56i    NEW BRUNSWICK-PERTH AMBQY-SAYREVILLE.
                    MIDDLESEX                     N.J.
            562   PARKERSBUKG-MARJETTA, w,VA._OHJO
                    WASHINGTON                    OHIO
                    WOOD                          W.VA.
            563   POUGHKEEP51E. N. Y.
                    DUTCHESS
            564   RICHLAND-KENNEWJCK, WASH.
                    BENTON
                    FRANKLIN
            565   SANTA CRUZ. CAL.
                    SANTA CRUZ
            567   SARASOTA, FLA.
                    5ARASOTA
            568   SPARTANBURG, S. C.
                    SPARTANBURG
            569   WJLLIAMSPORT, PA.
                    LYCOMING
            570   YAKIMA» WASH.
                    YAKJMA
                                                                                        N.Y.
                                                                                        WASH.
                                                                                        WASH.
                                                                                        CAL.
                                                                                        FLA,
                                                                                        s.c.
                                                                                        PA.
                                                                                        WASH.

-------
                                             COMPOSITION Of 5
                                   SMSA'S LISTED IN B.E.A. CODE NUMBER ORDER
571   MELBOURNE-TITUSVILLE-COCOA, FLA.

        BREVARD                       FLA.

930   BRIDGEPORT-NORWALK-STAMFORD-DANBuRYt CONN

        FAIRFJELD                     CONN.

931   NEW HAVEN-WATERBURY-MERIDEN, CONN.

        NEW HAVEN                     CONN.

*32   HARTFORD-NEW BRITAIN-BRISTCU CONN.

        HARTFORD                      CONN.

933   NORWICH-GROTON-NEW LONDON. CONN.

        NEW LONDON                    CONN.
            942   PROVIDENCE-WARWJCK-PAWTUCKET.  R.I.
93*   BOSTON. MASS.

        ESSEX
        MIDDLESEX
        NORFOLK
        PLYMOUTH
        SUFFOLK
MASS.
MASS.
MASS.
MASS.
MASS.
935   FALL RIVER-NEW BEDFORD. MASS.

        BRISTOL                       MASS,
936   PITTSFJELD, MASS.

        BERKSHIRE
MASS,
937   SPRINGFIELD-CHICOP£E-HOLYOKEt MASS.
        HAMPOEN
        HAMPSHIRE
MASS.
MASS.
938   WORCE5TER-FITCHBURG-LEOMIN5TER, MASS.
        WORCESTER                     MASS.
939   PORTLAND-SOUTH PORTLAND, ME.
9<.o   LEWISTCN-AUSURN, ME,
        ANDROSCOGGIN

941   MANCHESTER-NASHUA. N.H,
        HILLSBO«CUGH
                                      ME.
ME.
N.H.
                    BRISTOL
                    KENT
                    PROVIDENCE
R.I.
R.I.
R.I.

-------
•:   -x A—Basis  for  Initial Designation Criteria
•   ' '
     This Appendix provides  the  technical derivation of the initial  desig-
nation criteria presented in Section III of the Guideline.

A.  Carbon Monoxide
     The exclusion criteria  of 25 p. p.m., 8 hr. average, is derived  using
the model for CO presented in Section V of this report and "worst case"
data.  If an area has  measured an 8 hr. maximum CO concentration less  than
25 p. p.m., it may be excluded as an AQMA for CO.  If present CO concentra-
tion is 25 p. p.m. or more, then  1985 CO concentration should be estimated
using the model presented in Section V and relevant data for the area  in
question.
     The calculations  and reasoning leading to the selection of 25 p. p.m.
8 hr. average as the exclusion threshold are now presented.
     Urban background is  normally taken to be 1 ppm, so b = 1.0.
     The most  often violated standard for CO  is the 8  hr. standard
of 9 ppm, so F.  =  9.0.
     G, and G, will be assumed equal.  Mobile source growth is
about 5%/ year maximum for  urbanized areas.   If a 1970 baseline  is
chosen, then the  projection  period is 15 years.  The growth factor
is derived from  the growth  rate by
          G =  (1 + r)n =  (1  + .05)15 = 2.08
A growth factor  of 2.0 will  be used for all urban sources, so
GI = G, = G =2.0.
     Growth of local  traffic (G*) will be less than total urban
growth due to  "saturation"  of local streets.  G* will  be  taken  as  1.2.
     The worst case division of baseline emissions  is  that where
stationary sources and heavy duty vehicles contribute  most.   Current
data for 26 AQCRs  with high  CO emissions indicate that PI = 70%,
P. = 10%, P   = 20% is about the worst case situation.

-------
          The  expected ratios of composite emission factors for the period
     H.'70-193U arc- approximately E-j = 0.1, E,  = 0.5, E  =1.0.
               Ft  •• F,  + Fu * b
                9  - F,  + Fu 4 ,
      	Fl_     .	1   1EV *  hG h Eh                                    (2)

          F,       70 x 1.2 x 0.1 + 10 x 1.2 x 0.5
                             70 + 10
           Fu     . Pl¥l  * Wh * PsGsEs                        (3)
           B^b            100%
           F      70 x 2 x 0.1 + 10 x 2 x 0.5 +  20  x  2  x  1.0
                                     Too
             F1  = .
             Fu  = .128 (B-l)
              9  -. .144 (B-l) + .128 (B-l) +1
              B  = 30.4 ppm

     Thus, if a  CO concentration  of 30.4 p. p.m.,  8 hr.  average  was  observed
in 1970, and the CO emission distribution,  growth rates,  and emission  factor
ratios are as assumed, then the 8 hr.  CO standard of 9  p. p.m. would just  be
met in 1985.  Since CO concentration is  quite sensitive to location, and
since the location of CO monitors in 1970 was not likely  to coinside exactly
with the points  of maximum 8 hr CO concentration, an exclusion  criteria of
25 rather than 30.4 p. p.m. has been adopted.
     There is no initial  inclusion threshold  for  CO.  In  most areas, emissions
of CO are predominately from mobile sources so that mobile source performance
standards should reduce CO concentrations below the NAAQS  before  1985.
                                  A-2

-------
  •
lf
        B.  Total Suspended Parti culates



             Nationwide emissions of TSP are not expected to increase.   The



        combination of SIP requirements for existing source emission reduction,



        attrition of existing sources, and the requirement that new sources



        meet NSPS should result in a continuing decrease in TSP emissions through



        1985.  Therefore, areas in which all NAAQS for TSP are presently being



        met need not be designated as AQMA's for TSP.



             There is no inclusion threshold for TSP other than the projected



        violation of a NAAQS in 1985.  Those areas where a "reasonable  time"



        for attainment of a secondary NAAQS for TSP extends beyond 1985 must



        be declared AQMA's for TSP.  For other areas currently exceeding NAAQS



        for TSP, the analytical techniques presented in Section V may be used



        to project TSP concentration to 1985.



        C.  Sulfur Oxides



             Nationally, most SIP requirements for control of S02 in urban areas have been



        implemented.  Control methods for SOX emissions are not as advanced as controls




        for TSP.  Consequently, growth of SO  sources may result in a net
                                            X


        increase in SO  emission even though NSPS for SO  are applied to new
                      A                                 /\


        sources.  Therefore, an indicator of growth is contained in the



        exclusion criteria for SO  .
                                 A


             If  the products of the highest measured S0? concentrations for each



        averaging time and a growth factor based on projected SMSA total earnings



        is less  than any NAAQS for SOp, the area may be excluded as an AQMA for



        SOp.  Total earnings in the SMSA was selected as the best indicator of



        emission growth  potential that is readily available.  The growth factor            n


                                                                                             f


-------
                        "      100   " V.
                                         o
           Where
                 G  =  relative growth factor
                 r  =  growth  rate, %/year
                 n  =  number  of years between the base year and 1985
                 Vg5  = value in dollars  in 1985 of total earnings
                 Vb   = value in dollars  in base year of total earnings
        The  inclusion criteria for S02 is identical to that for TSP.

   D.  Photochemical  oxidants
        All  areas for which  transportation controls are required for
   oxidants  must be designated AQMA's for oxidants.  Although MSPS*and
   •'•'S PS* for  hydrocarbons will lower oxidant concentrations below NAAQS
   by  1985 in some  areas, other areas, particularly those with high sta-
   tionary source HC  emissions, may have difficulty meeting NAAQS without
   further HC emission control.  It is,  therefore, considered prudent to
   subject areas requiring special HC emission control (i.e., transporta-
   tion control areas) to the air quality maintenance analysis required
   following AQMA designation.
        An area may be excluded from AQMA designation if (1) it is not a
   transportation control area for oxidants, and (2) measured peak hourly
   oxidant concentration is  less than twice the NAAQS for oxidants (0.16
   p..p.m.  or 320 yg/m ).  This latter exclusion threshold,, is arrived...at\-\
     -•N -,-•-    ,--•":^-^.:(  Mv\ .-^Ov.V-i  C"^' <':"'• •
   through the following reasoning.-'   •:         .      . ;-•         -'    .
        The'combination of MSPS, NSP'S and: growth is- expected to result'in'
       :      .          .             '      ••.:'... :".'• ._ . t     i.-\~ f, •'  •:•.!>
   about  a 55% reduction in  HC emission  from, the Average metropoli.tan   '•;,
   area by T985.  Both Appendix J  and prpportional. models indicate  that a"
    - •	 :.  •. .  '  ,.      .. .   .  .;.   ; .. • •  •-.  :•''•'';•; .;.•'; .-)K'-;.  ,-.>".''
•**New source  performance standards     A_4.          .-   ,.

-------
55% HC emission reduction should produce a 55% oxidant concentration


reduction.  Furthermore, the reduction in the HC/NO  ratio which is
                                                   /\

the likely consequence of present and expected emission control  regula-


tions, should reduce oxidant concentrations even more than predicted


by Appendix J or proportional modeling.  It follows that an area


presently exhibiting less than double the NAAQS for oxidant should


achieve NAAQS by 1985 provided MSPS and NSPS are effectively applied


and enforced.
                                                              3
     Areas which exhibit oxidant concentrations above 320 yg/m  but


are not subject to transportation controls may estimate 1985 oxidant


concentration using the methods presented in Section V.




E.  Nitrogen dioxide


     Future NOp concentrations were projected by EPA for all regions


likely to exceed NCL NAAQS.  These projections were made in connection


with the re-examination of the MSPS for NO.  The results of this
                                          /\

analysis indicate that NAAQS for N02 are threatened only in the Los


Angeles, Chicago, New York, Denver, and Wasatch Front AQCR's.  Con-


sequently, only the urbanized portions of these AQCR's need be


designated AQMA's for NOp.  All other areas may be omitted.
                  S - \






                  \ *
                               •< 4  V
                                i



                             J  A-5

-------
APPENDIX B - Examples of Analyses for a Hypothetical SMSA Employing the
      "Back-Uo" Method of Estimating Emissions
     This appendix presents example calculations for carbon monoxide, sulfur
dioxide, and hydrocarbons/photochemical oxidants.  The hypothetical SMSA is
assumed to be located in a state which will be under a significant burden and
must resort to the "back-up" method of calculating emissions allowed after
application of all SIP control strategies.  As stated in Section IV of this
guideline, however, the "preferred" method is to be employed in most cases,
rather than the "back-up" method.  The "preferred" method is the method used by
the states in developing the control strategies for "example regions", i.e.,
application of SIP regulations to all emissions, source-by-source, to
determine allowable emissions in 1975  (or 1977, if an extension for attaining
the NAAQS was granted).  The "back-up" method is presented here merely to demon-
strate its use, but its use should be restricted to those States which will
be faced with a heavy burden in designating the air quality maintenance "areas.
Before deciding to use the "back-up" method, States should discuss the
problems of using the preferred method with the representative responsible
for maintenance of standards in the appropriate EPA Regional Office.
Example 1 - Carbon Monoxide
     (a)  Assume that the hypothetical SMSA has a current carbon monoxide air
     quality of 30 ppm, second highest 8-hour average per year.  Upon applica-
     tion of the initial designation criteria found in Section JII of the
   3^t8&^;-:1^                                          automatic  /'  ^
   .. "• : ,o.> •••';'-':.''   '   •••-.''  .. • •  •;'"  . •-    . '   '   ' _   • .     •   . , : .    '  •  \'\ <-.

-------
     Fuel combustion
       Power plants                         1200
       Point sources excluding power plants  400
       Area Sources                          400
         Subtotal                                    2000
     Industrial point sources                        7000
     Solid waste disposal
       Point sources                         100
       Area sources               ;          1900	
         Subtotal                                    2000
     Transportation
       LDV                                755000
       MDV                                . 40000
       HDV                                 55000	
         Subtotal                                  850000
     Miscellaneous
       Point sources                         500
       Area sources                          500	
         Subtotal                                    1000
                     TOTAL                        862,000

This data is entered in Column B of Table B-l as shown. -


(b)  Assume that the following annual growth rates were projected for the
hypothetical area [the 5-year (1970-1975) and 1.0-year (1975-1985)
compounded growth rates are also given].    r           _  ^   •••'*
        Category               - Arinual',  ,    : 5-vyear      10-year  ;   ;
 ;    Population "••"V           2.1%'}     ;   : 11*  "      .23%
     Total earnings        '      4.5%   .        25%       /  55%
     Manufacturing earnings      4.1%           22^    ,   ;   50%

 (c)  Assume for the hypothetical area that  new power plants  would  con-
 tribute an  additional  300  tons of CO per year in  1975.
                            B-2

-------
                 TABLE B-l.  Emission Projection Calculation Table (Carbon monoxide)









CD
1
co
A
.
Source
Class
Fuel Combustion
Power plants
Point sources (exclud pp)
Area sources
Subtotal
Industrial Process
Point sources (subtotal)
B -

1970
Emissions

1200 -
400
400
2000

7000
-c
Reduction
Factors
(Table IV-2)

1.0
1.0
1.0.

0.10
C-l
Growth
Factor
(1975/1970)

—
1.25
1.25

1.22
0

1975
Emissions
1500
(=1200+300)
500
500
25W

900R
E
Growth
Rate
'(1985/1 975'-!)


. •
0.55

0.50
F .
Emission
Factor
Adjustment



1.00

.40
G
1985
Emissions
G = 0(1 + EF


•
2900R
Q
1100K
Solid Waste Disposal
Point sources
Area sources
Subtotal
Transportation
LDV
MOV
HDV
Subtotal
Miscellaneous
Point sources
Area sources
Subtotal
TOTALS
100 .52
1900 .88
2000

755,000
40,000
55,000
850,000

500
500
862,000
1.10 57
1.10 1840,, . R
T900* 0.23 ' 1.00 2,300"
D
83,000p
29,000jj
40 jUUUrj
152,000K

• .
1.25 1250 0-55 1.00 1 ,900R
, • leo.oooJL
R-indicates rounding

-------
(d)  Place the proper emission reduction factors from Table  IV-2  in
col uniti C.
(e)  The growth factor for 1970-1975 is inserted in Column  C-l.   It  is
obtained from the 5-year demographic-economic parameters, and expressed
as the ratio of the  1975 value to the 1970 value (i.e.,  25% is expressed
as 1.25).
(f)  Column D is calculated fcr all  categories except power  plants and
transportation by taking the product of columns  B, C, and  C-l.   The
1975 power plant emissions are given by the product of columns B  and C,
to which is added the emissions from new power plants.
(g)  The appropriate 10-year growth rates are entered in  column  E for all
categories except transportation; these rates are expressed  as the ratio
of the 1985 value to the 1975 value, minus unity (one).
(h)  The appropriate emission factor adjustments are entered in  Column  F.
(i)'  Column G is computed for all categories except transportation by the
given equation.
(j)  Transportation emissions are then calculated by equation (1) from
Part IV:
     ^1985 =  «W GiEi
     The growth rate for transportation emissions should be determined
from available data if such exists.   If no such data exists, use the growth
rate for population.  For the hypothetical area, this is 2.1%.  Therefore,
G = (1+ .021)15 = 1.37.  E values are found in Table V-l.  For carbon
monoxide, E,DV = 0.08; EMDV = 0.53,  and EM™ = 0.53.
                             B-4

-------
.  .  Q85 = (755,000)0.37)(. 08)  + (40,000)0 .37)(. 53) +  (55,000)0 .37)(.53)



        = 83,000               + 29,000              +  40,000



        = 152,000 tons  per year





(k)   Total column G for a grand total  of  160,000 tons/year 1985 emissions



for carbon monoxide.



(1)   Carbon monoxide  concentrations  are calculated by the method given on



p. V^l.  Assume a growth factor G* for local  street traffic of 1.0 if an



actual  value is not known.






     F  = 0 JUR-M fP R* F + P  G* F  1
     r.    U.O^D u; L"I u . n. T r,,u u^uJ
          B + 30 ppm



          b = 1  ppm



          P,  = 87.6       Pw  =  11.0     (Refers to  1970 percentages calcu-

           L               M             lated from Table B-l)


          G*L =  1.0       G*H = 1.0



          EL = 0.08       EH  =  0.53
       - 0 o /on n  r...8)  +  (11 .0)(1 .0)(.
         u.o ^u i;  L            87>6  +  11>Q
               •(87.6)(1.0)(.Q8)





  - °-8(29)  ^iMwA


  = 3.01  ppm



U
    F.. = 0.2 (B-b) [PLGLEL+ PH6HEH+ PSGSES]
                            TOOT



Since stationary source emissions  for 1985  have  already been computed,



'DSGSES = the ratl° °^ ^^ stationary source emissions to total 1975


emissions or = 8,000/862,000 = 1%



     GL = GH = 1.37       (=1970 to 1985  growth  in  population)
                           B-5

-------
        F  = 0.2 (30-1) r(87.6)(1.37)(.08) + (11 .0(1 .37)(.53)  + 1
                                         i__^
           ~- 0.2(29) r9.6_+ 8.0
                     L   TOO
        Fu=1.0
           = 3.0 +1.0+1
           =5.0 ppm.  second highest 8-hour average
Conclusion
    Since this concentration is below the standard of 9 ppm,  second highest
8-hour average, this SMSA would not be designated as an AQMA  for CO.

Example 2 - Sulfur dioxide
    (a)  Assume that the hypothetical area has a most recent  annual arithmetic
                                      3
    mean S02 concentration of 150 ug/m ,  but has been projected to attain the
    SOp secondary standard before 1985.  Since the current air quality concen-
    tration for SO- is above even the primary standard, the area cannot be
    automatically eliminated as an obvious non-problem area.   Likewise, since
    the attainment of the secondary NAAQS has been projected  before 1985 due
    to the current control strategy, the  area cannot be automatically included
    as an obvious problem area.  Consequently, the area must  be subjected to
    further analysis consisting of a projection of emissions  and air quality.
         Note that if the current air quality concentration were below the
    secondary NAAQS for SOp, one would compute the product of the current
    concentration and the relative growth in total earnings between the base
    year and 1985 (the relative growth =  1 + the percentage growth rate over
    the period of interest).  If this product is still below  the secondary
                                B-6

-------
NAAQS for S02, the area could be automatically excluded as an AQMA;
if this product were above the secondary NAAQS for SCL, analysis would
be required for the area to determine if it should be selected as an
AQMA.
     Assume that the hypothetical area has the following 1970 emissions
                                   ~f
of S0? in tons/year:
     Fuel combustion
          Power plants                      250,000
          Point sources (excluding power    1nn nnn
                           plants)          100'000
          Area sources                      100,000	
             Subtotal                                 450,000
     Industrial point sources                          60,000
          Solid Waste disposal
             Point sources
             Area sources
               Subtotal                                  NEC
     Transportation
          LVD
          Other mobile
             Subtotal                                   2,000
     Miscellaneous
          Point sources
          Area sources
             Subtotal                                 	0
                             TOTAL                    512,000
     This data entered into Column B of Table B-2 as shown
(b)  The same growth rates apply as in Example 1 above.
(c)  Assume for the hypothetical area that new powir plants would contri-
bute an additional 20,000 tons/year in 1975.  Of course, in actuality, it
is recommended that this figure be obtained from consultation with
electric utility companies.
                               B-7

-------
                         TABLE B-2.  Emission Projection Calculation Table (Sulfur Dioxide)
A
Source
Class
Fuel Combustion
Power plants
Point sources (exclud pp)
Area sources
Subtotal
Industrial Process
T3 Point sources (subtotal)
Solid Waste Disposal
Point sources
Area sources
Subtotal
Transportation
LDV
MDV
HDV
Subtotal
Miscellaneous
Point sources
Area sources
Subtotal
TOTALS
B . -C
Reduction
1970 Factors
Emissions (Table IV-2)
250,000- 0.43
100,000 0.43
100,000 0.57
450,000
60,000 .37

. «NEG ' m —

2,000 1.00
0
512,000
C-l D E
Growth Growth
Factor 1975 Rate
(1975/1970) Emissions '(1985/1975'-!)
130,000
___ (=110,000+20,000)
1.25 54,000R ,
1.25 54, 00"
2?C,000 0.55
1.2 2 27,000R 0.51

0

1.10 ,2,200 • 0.23
» *
•
•
0 — '

F . 6
Emission 1985
Factor Emissions
Adjustment G = D(l + E!
1.0 370,000R
0.4 34,000R

—

i.o • 2,oo6R
•

406,000
R-indicates  rounding

-------
 (d)   Pla.ce  the  proper emission reduction factors from Table  IV-2  in
 Column  C.
 (e)   The growth" for 1970-1985 is inserted in Column  C-l obtained  from
 the  5-year  demographic-economic parameters, expressed as  the  ratio of
 the  1975 value  to the 1970 value (i.e., 25% is expressed  as  1.25). .  For
 particulate  matter and S0? from transportation sources, assume  the same
 growth  as that  of population.
 (f)   Column  D Is  calculated for all categories except pov;er  plants and
 transportation  by taking ths product of columns B, C, and  C-l.  The  1975
 power plant  emissions are given oy the product of columns  B  and C, to
 which is addad  ths emission from new power plants.
 (g)   The appropriate  10-year arouth factors are entered in Column £  of  all
 categories.  For  particulate matter and S00 from transportation,  assume
 the  same growth as population.  The growth factors here are  expressed as
 the  ratio of the  1585 value to the 1975 value, minus unity (one).
 (h)   The appropriate  emission factor adjustments are entered  in Column  F.
 (i)   Column  G is  cGiiiputed for all  categories by the  given equation.
 (j)   Column  G is  totalled, yielding 1985 SO,, emissions of 406,000 tons/year.
 (k)   SOr, concentrations  can now t:e calculated.  Assume that  the area has
 an annuu'i arvchmeilc  iwrin 50,: cf.-';'.:entr.-:.tion of 150 u^/m".  For  this  example.,
 the  incn.':-^!.!:-!  •v'd-rsic1  cf •;..!:: iv-!"; •;:•,•-1 ;o'i :.wor!.n ra^'i (p.  V-C)  will  bt
u.'.od  to ;:-;":;'cCt :;ir Duality.   •-;::.• v.<>-.£ vnr.l  •:;•:"; s hypcthetlca'i  Z''*':i\  has an
area  of 1000 square :.;i icrroccrs.   The; urD;";vi .v•'..:! ai'ea  is hypothesized  to  us
400  square kilometers (160 m1")  and that 85 percent  of the emissions are
emitted within  the urbanized area.
      Therefore, the 1970 and 1985  emissions from the urbanized  area, together
with  the emission  densities sre:
                               B-9

-------
                                    1975                1985
Si-ISA  (tons/year)                   512,000             406,000
Urban  area  (tons/year)            435,000             345,000
Urban  area  emission density  . -
  (tons/year/™2)                    2'72B               2'160

The incremental  Mi11er-Holr,.'orth iv-oclel is  given  by:
AX =  .on AQ  [3.51  HOJ3  + ^  - :(!•!.fLjIClbJiL-^]  (A)
                            -tii              O '
  or
For the hypothetical  SilSA, issu;!)1..; the fcllov;ir,o  con-Jiticr
- a niesn annual  'norning mix ing height: or 500  ni.  -  !•!
- a mean annual  nornir.n wind soea-.1 of 5 Pi/sec. - ';
- a city size  = \-400 kn2 - J10 I'.;:'=  12.4 r,:i  - S

If IGOOS/u  <0..'71  ii"1'1", ;:..,uotiOii [; is -.isad.
    l&QO  (1~-) = 3970
    0.471 H1'13  -  0.471  (5GO)1'13   - 0.471  (1100) -  518
Since 16005/u >0,471  H1'1", equation A is used.
Ir,?.; •.-:;:.•.: V.:r:-.   ':
     -6.38  (12.1)
     - 77 ug/rii3
     X1985 = X1970 +  AX
           - 150 -  77
           =  73 ug/nr  annual  arichi^tic

                           B-10

-------
(1)  To calculate  the  short term concentrations, the log-normal
model described  on p.  V-ll  of the guideline is used.  Assume that
the most recent  standard  geometric deviation of the hypothetical
area is 2.05  for averaging" times of 3 hours, the ratio of the annual
maximum 3-hour concentration to the mean concentration is 9.74.  These
values are underlined  for reference in the table of p. V-12.  There-
fore, the projected  3-hcur maximum conc.cn trati or? is:
         (73  uG/in3)(9.74)  -  710  i.g/^3.
^•')  r:20£lMJvGn..-'  ~  Since 710  i-Q/"'!3,  3-hour rw.xir.u:ni concentrations is
less than the  standard  of  1300 i^g/m3,  second highest 3-hour value per
year, the area would not be  designated as an AO'-;A for SO,,,
                           B-ll

-------
Example  3  -  Hydrocarbons and Photochemical  Gxidants
(a)   Assume-that the area has  a  current photochemical oxiclant  concentration
                 3
      of  350  ug/m r second highesi  1-hour concentration per year,  but the
      area  is not required to have  a  transportation control strategy.   There-
      fore,  it cannot be automatically  included or excluded based  on  the
      criteria presented in Section  111  of the guideline.  The  area must,
      therefore, be subjected to  further analysis consisting  of an estimate
      of  crfiissiopiS c::ici air quality.
iiOTtl:  T!;e  projection of emissions  is  net presented her:;, since it is cone
in a  fashion much ti.e ?o<-« as  for  cciroor: monoxide,,  In^UKiJ, it is assumed
that  total  1970 hydrocarbon emissions  v/ere  170,000 tons p^r  year  and that
1985  hydrocarbon emissions are project^c '.:o !./•.;• "iOO.,000 i-.>':':$  "cr yaar.

(b)   Part  V    of ti;2 rui.-:li'Vin? presents th;; •::'.-;thod fcv sscv-'atinc; ^hoto-
      chemical  oxidant concentrations. •  The  expected emission reduction  is
      given by
             'expected "     K~~~        A  JJ'*
             R         =  12ji^iI.::..J.2Q.^il  v ipnq'
              expected          170,r.OO    "'   A (U"'C
                           n ."r
                             ;•.:!'; •".>. ;:^ivl:  •..;;•-..-••,;•;•.•. ;: '..-.• ,;." ;;.:;j ug/ii:"  (0.18 ppi
     second  highest 1-hour c.cnceraraLicn  per yoar,  Appendix j indicates  that:
     a reduction  of 60 percent is required.
CONCLUSION;   Since  the required, reduction of GO percent is greater than  the
expected reduction  of -VI.2, t!o c.!'••.••;;•  -,'ouu: L •? ::?s1cn:,;.?H: c'S sn A'};/:A  for  piio'.
chemical oxidants.
                                  B-12

-------
                  APPENDIX C - LIST OF TASKS


     This preliminary list of tasks is being  provided  for  use  by the States


to outline the work they must do in maintaining standards.  The list can be


used to plan and schedule activities and to estimate manpower  requirements.


A more detailed description of the work to be done  will  be provided in  the


guidelines which will follow.  This list of tasks,  however, should not  be


construed as a final outline of the plan.


     The tasks involved can be partitioned into three  major groups:


     I.  Submit Areas Designated as AQMA.-!s


     II.  Analyze Emissions and Air Quality--!975  to 1985


     III.  Develop and Submit a 10 Year Plan  for Air Quality Maintenance


     A list of the specific tasks in each of  these  groups  is given below:



I.  Submit Areas Designated as AQMA-'s.


     The objective of this group of tasks is  to determine  which SMSAs and


other areas meet the criteria for designation of AQMA's.   The  tasks are:


     1.  Assemble information on emission inventory, air quality, emission


         regulations, status of compliance and future  power plant construc-


         tion and fuel use patterns.


     2.  Apply initial designation criteria,  using  procedures  outlined  in


         the guidelines, to arrive at designated AQMA's.


     3.  Conduct public hearings in designated AQMA's.


     4.  Submit designated AQMA's to EPA with back  up  documentation.


II.  Analyze Emissions and Air Quality--!975  to 1985
                                                              i

     The objective of this group of tasks is  to determine  which  areas  are


really problem areas with regard to maintaining standards, and thus which


areas  require maintenance plans.  This determination  will  be  done  by  conducting


an in-depth analysis  of all  the major factors that will affect air quality in


the period  1975  to  1985 using  guidelines and models to be  issued by EPA.

-------
     The tasks to be performed here have a  different  purpose  than  those per-
formed in Group I above.   In the case of Group I  tasks,  it was  only  necessary
to identify AQMA's on the basis of specific designation  criteria.  However,
Group II tasks must go beyond that and quantitatively evaluate  the air pollution
problem in each AQMA for the period 1975 to 1985.   The tasks  are:
     1.  Determine baseline emissions for each pollutant for  which the AQMA
         was designated
         a.  by source category
         b.  by location as required by EPA models
     2.  Identify principal sources (baseline and projected  to  1985)
     3.  Acquire all necessary data to determine  growth  in emissions from
         1975 to 1985 by source category and location for each  pollutant.
         This would involve acquiring data on:
         a.  Past trends
         b.  Planned and projected economic and demographic  growth
         c.  Projected control technology
         d.  Present and future regulations for new and  existing sources
                                                             \
         e.  Meteorological data.
     4.  Project a detailed emission inventory for 1975  to  1985 by source
         category for each pollutant.
     5.  Project 1975 to 1985 air quality using calibrated  diffusion models
         to be provided by EPA.  Use these models to:
         a.  Analyze the impact of indirect sources
         b.  Analyze the impact of new sources
     6.  Determine which AQMA's are problem areas and require 10 year mainte-
         nance plans.  (A problem area is any portion of an  AQMA where the
         above analysis indicates any standard may be violated at any time
         between  the date of  attainment of the standard and 1985.)

                                      C-2

-------
'-1.   Develop and Su Limit a 10-Year Plan  for Air Quality Maintenance
    The objective of this group of tasks  is to have the States develop and
submit a plan for maintenance of air  quality  in 1975 to 1985 in each AQMA
determined to be a problem area.   The tasks to be  performed by the states
can be inferred from the following outline of the  content of the plan:
     1.  Plan overview -- Each State  must prepare  a plan overview document
         summarizing the contents of  the plan.  It should include the following:
         a.  A description of what the plan is about, and why it is required,
             so that lay citizens will  have sufficient background knowledge
             to participate in public hearings on  the Plan.
         b.  A list of documents that constitute  the plan, with each
             document or portion thereof identified according to the
             pollutant and AQMA it deals with.
         c.  A list of any documents  or portions  of the SIP, as it will
             exist immediately prior  to the submission of the 10-Year Plan,
             that are being revised,  rescinded, or supplemented by the
             10-Year Plan, and a brief description of the salient features
             of such changes.
     2.  Required Dei.ionstrations
        Each State must:
        a.   Certify that public hearings have been held pursuant to
            40 CFR 51.4(d).
        b.   Demonstrate the presence  of legal authority to adopt and
            implement the 10-Year plan, pursuant  to 40 CFR 51.11.
        c.   Provide documentation that the  intergovernmental cooperation
            required by 40 CFR 51.21 (a)  and 51.21(c) has been established.
            Identify the local agencies pursuant  to 40 CFR 51.21(b)(l)  and
            describe the distribution of responsibilities among state and
            local agencies in preparing, submitting and implementing the
            10-year plan.
                                     C-3

-------
d.  Describe how the 10-year plan will  provide  for coordination of
    air quality maintenance activites with other local  environmental
    protection activites including, but not limited to,  the  following
    activi ties.
    (i) Water planning
   (ii) Solid waste disposal planning
  (iii) Comprehensive and environmental health  planning
   (iv) Review of transportation plans.
 e.  Describe the procedures designed to ensure that air quality
    maintenance activities and programs to be undertaken pursuant
    to the 10-year plan are coordinated with all  other
    activities and programs being carried out in accordance
    with the applicable SIP.
f.   Provide a description of the resources available to the
    State and local  agencies and the resources  needed to carry
    out the entire SIP during the ensuing 5 year period, pursuant
    to 49 CFR 51.20.   This should include a general description
    of the staff that will  be required to prepare and implement
    the 10 year plan for each AQMA, and a proposed budget showing
    the costs of all  phases of the 10 year plan.
g.   Provide timetables that specify the dates by which  classes of
    sources must comply with emission regulations.  Also, provide
    a timetable for  attaining secondary standards in each AQMA
    for each pollutant under  consideration in the AQMA,  and if
    the timetable is  different from the one already in  the SIP,
    provide an  explanation of the difference.
h.   Describe the procedures used for evaluating the air quality
    implications of  existing land use plans, transportation  plans
    and zoning maos.
                         C-4

-------
Maintenance Strategies
a.  The State shall provide a  detailed  description  of the control
    strategies to be used  in the  plan pursuant  to 40  CFR 51.12(a)
    through (d).
    For each AQMA and for  each  problem  pollutant within  that AQMA
    (as identified  through analysis  in  Group  II'above),  the State
    shall describe  ths specific control  strategy to be used, and
    shew how that, str-jr/Hiy ',/i'il r.isinrain polluf.ant  'levels with in '..he
    stapdar.'js. •  •
b.  For strategic?  thai will have-  an arcu v/idi  irnpc-ct on emissions,
    the Sti-te shall provide a  Gon::.-nstrati&n  01"  that impact.  All
    National An!; lint Air Quality  Standards shall be
    considered.  Interrelationships  among control strategies shall
    be discussed,   'btxiod  legal authority that  might  be  irmovative,
    unusual or particularly difficult to obl-rlii shall  be described.
c.  The State shall provide results  of  all detailed analysis mdoe
    to determine growth of emission  sources  in  1975 to 1^35 together
    w i t h t.!'; e s u p;) o r t i >.) n r a t i o n a 1 e.
d.  The St^Lv1 shd'! : orovnh results  of  all detailed a--v.ly^ss made  tc
   ths  Sto-i'.a  finds  t/i^y ?.ro '."scc-ii;.^ry arrj fr^p; ic.^b lo:
     1.   Emission density zoning—a regulatory system  in which  the  maximum
         legal  rats of emissions of air pollutants from any  given land area
         is limited by the size of the s^ea.
     2.   Emission allocations—a regulatory system in  v.'hich  the maximum
         legal  rate of emissions of air pollutants from any  given political
         juris.diction or other area is assigned by an  allocation procedure

-------
    and suitable restrictions are imposed if an area uses up its
    allocation.
3.  Transportation controls—including encouragement of mass transit
    and strategies discussed in the Preamble to State Implementation
    Plan Transportation Controls published in the Federal Re g 1 s te r
    on November 6, 1973, pp. 30606 through -30633.
4.  A methodolooy for controlling proposed r,?v,; or modified buildings,
    structures, facilities, or installation, Including (Municipal v/^ste
    water treatment facilities.
5.  Fuel and energy conservation objectives.
6.  Regulatory and other types of strategies to integrate eir quality
    consideration into the development of ?roa, point, anr line sources,
    including zoning and subdivision regulations, ssv/ar and water connec
    tion plans, re zoning and building plans, capital improvement prst; ram
    and open space reservations.
7.  Mechanisms to integrate air quality consi aerations into revisions of
    local or regional development plans, and rischanisms to insure thst.
    development proceed-; in accordance v.'ith duly adopted plans.
8.  The effects of more restrictive emission controls and n •;.../ source
    perfor.../. ice standards.

     burning.
11.   Any other pertinent stra
     applicable.
                                   -v.-rich are found to be necessary and

-------
              UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
f                       Office of Air Quality Planning and Standards
**'** ww*-0                 Research Triangle Park, North Carolina 27711

                               Februari  14,  1974     ,
                         i      i       I       I
  Recipients of Guidelines for 'Designation of Air Quality Maintenance Areas

  Dear Recipient:

       Since the distribution of the OAQPS document, Guidelines for
  Designation of Air Quality Maintenance Areas, several questions arose
  regarding the validity of the emission factor ratios for carbon mono-
  xide and hydrocarbons from heavy- and medium-duty vehicles (Table V-l,
  p. V-4, of the document).  Several comments have also been received
  regarding the reasonableness of the 25 ppm initial designation criteria
  for carbon monoxide on page III-2.  A review of the questions and comments
  led to a decision to revise these portions of the guidelines document.
  A discussion of each of these issues and the revisions are presented below.

       1.   'Validity of the emission factor ratios for medium- and heavy-
            duty vehicles.
            The emission factor ratios for medium- and heavy-duty vehicles
       for carbon monoxide and hydrocarbon emissions, presented in Table
       V-l (p. V-4) of the guidelines, have been revised to reflect the
       regulations promulgated in 40 CFR Part 85, which limits emissions
       from these vehicles.  These regulations and the second edition of
       Compilation of.Air Pollution Emission Factors* classify light-duty
       vehicles AS those with a gross vehicle weight (GVW) of 6,000 pounds
       or less and combine medium- and heavy-duty vehicles into the one
       category, heavy-duty vehicles, defined as those vehicles with a GVW
       of greater than 6,000 pounds.

            Consequently, composite emission factors and emission factor
       ratios have been recalculated for heavy-duty vehicles (HDVs), and
       Table V-l has been revised accordingly.  In the calculation of the
       revised ratios, the emission factors for HDVs are taken from Compi-
       lation of Air Pollution Emission Factors.  The factors for gasoline-
       powered vehicles are used for a11 HDV's, gasoline and diesel.
       Diesel emission rates for CO and hydrocarbons are much less than
       gasoline emission rates and the contribution of emissions from
       diesel HCVs is only a small percentage of total HDV emissions.
       Therefore, use of the HDV gasoline emission factors exclusively
       will result in a slight overestimation of total emissions.  This
       appears tolerable since the resulting air quality will err on the
       side of not automatically exempting some areas as AQMAs.  The
  *U.S. Environmental Protection Agency, Compilation of Air Pollution Emission
   Factors, Second Edition.  EPA Publication No. AP-42, Research Tr,iangle Park,
   North Carolina.

-------
     revised Table V-1 is enclosed as Attachment A.   The factors therein
     for hydrocarbon and carbon monoxide emissions must be used for
   ,  analyzing areas for AQMA designation.

     2.   Initial designation criteria for carbon monoxide

          There are two separate problems with the automatic exclusion
     criteria for carbon monoxide:  first, the revised emission factor
     ratios (see (1) above) will change the cutoff concentrations; and
     second, the 8-to-l ratio of emissions of light- and heavy-duty
     vehicles assumed in the basis for the criteria (Appendix A, p. A-l)
     is questionable.  The latter problem arose because the 8-to-l ratio
     between light- to heavy-duty vehicles was based upon data for entire
     AQCRs.  For purposes of AQMA designation, however, the interest lies
     mainly in urban areas, particularly the central business districts,
     where there is usually a greater proportion of trucks, buses, and
     other heavy-duty vehicles than there are across whole AQCRs.  Con-
     sequently, a variable CO exclusion criteria has been developed in
     which the exclusionary concentration limit depends on the mix of
     LDV and HDV emissions on heavily-travelled downtown streets.  The
     revised CO exclusion criteria and its derivation appear in Attach-
     ments B and C (enclosed), respectively.

     As a result of these revisions, several related and supportive revisions
must be made for the sake of consistency.  These are described in Attachment
D (enclosed).   Although the numerical results in example analyses for hypo-
thetical SMSAs in Appendix B for carbon monoxide and hydrocarbons are now
inaccurate, considering the above revisions, the examples themselves will
remain unrevised.  The examples were developed merely to indicate the
methodology; the revisions do not change the methodology of projecting
emissions and air quality, except that the medium-duty vehicles (MDV)
category no longer exists.
                                    Svcerely y
                                    Jean J. Schueneman
                                         Director
                                     Control Programs
                                   Development Division
Enclosures

-------
                            Attachment A
                              Table  V-l
                       Emission Factor Ratios*
Year

1970**
1975
1980
1985

1970**
1975
1980
1985
HDV
Carbon monoxide
1.00
0.96
0.94
0.93
Hydrocarbons
1.00
0.92
0.82
0.79
LDV

1.00
0.59
0.29
0.08

1.00
0.50
0.25
0.07
 *Ratio of emissions in given year to base  year,  1970.
**For data bases other than 1970 (such as  1971,  1972,  1973)  for  CO and
  HC, interpolate between 1970 and 1975 values.

-------
                             Attachment B
Revision to initial  exclusion criteria for carbon monoxide,  p.  III-2,
paragraph A-3.
3.   Carbon monoxide:
     Use Figure III-1 and the following procedures to determine those
SMSA's which can be  excluded from consideration as an AQMA:
     (a)  Estimate the percent contribution of CO emissions  from light-
     duty vehicles to total  mobile source carbon monoxide emissions  on
     heavily used, central  city streets; choose the area where  LDV con-
     tribution  is representative of the local  area in the vicinity of
     the air quality monitoring site.
     (b)  Locate the point on Figure III-l corresponding to  the highest
     measured 8-hour CO concentration  in the central  city in 1970 and  the
     LDV contribution to local mobile  source emissions estimated under (a),
     above. .
     (c)  If the intersection determined in (b), above, lies on or below
     the curve, the  area may be automatically eliminated from consideration
     as an AQMA; if  the point lies above the curve, proceed  with the
     analysis described in Section V,  paragraph V-2.

-------
IO X I O TO TH C IN C K  4 O O 7 3
v x TO INCHIS        "-.ot if. •: '• *
  KZU?fti- a ESSCR CO
       ..EXCLUSION    lTERJON '
         CTFOT-OF 'THE

      J-IBHT-.AND-HEAVY-
                                  _(j& .LOCAUSffREETS
                   mob 1-1 ^"-- sour
2nt "of! local

-------
                           Attachment C
Appendix A - Revised Basis for Initial  Designation Criteria
     This revised portion of Appendix A provides the technical  derivation
of the initial designation criteria presented in the revised Section III
of these guidelines.  This revision is to be used in place of pages
A-l and A-2 of the original Appendix A.

A.   Carbon Monoxide
     The variable exclusion criterion for carbon monoxide presented in the
revised Section III is derived using the model  for CO presented in Section
V of these guidelines.  The criterion is in the form of a curve which
specifies, for a given local vehicle mix of light- vs.  heavy-duty vehicle
emissions, a critical CO concentration below which an SMSA can be excluded
from consideration as an AQMA, and above which  the SMSA must be subjected
to further analysis using the techniques presented in Section IV and V
of this document.  The derivation of the criterion curve follows:
     The CO model presented in Section V of this document is represented
by the three following equations:
           r          p  r* p  + p
           hL         PL bL hL   PH
        oT8rB~^F7  =       PT"*7^                                   {2)
                      PL GL EL * PH GH EH + PS GS  ES
            __    _
        072TB -67               100%

-------
     where
          FT  = Total  future (1985)  CO concentration (PPM)
          F,  « Future concentration due to local  traffic
          F||  = Future concentration due to urban emission

         b =  Background  concentration
         B =  Baseline  concentration (measured or estimated)
        P,  =  Percent emission  from light duty vehicles (gross vehicle
              weight '<  6000 Ib)  .
        P^ =  Percent emission  from  other mobile sources  (qross  vehicle
              weight  >  6000 Ib)
        P~ =  Percent emission  from stationary sources
         G =  Growth  factor over the projection period, G* } G
         E =  Expected  ratio of 1985 emission to baseline emission
              for a composite source.
        G* =  Growth  factor  for traffic on the local street of interest

     The "future"  air quality (Fy)  will be set equal to the CO standard,
and the light- vs.  heavy-duty vehicle  mix will be varied for the local  street
condition to  yield  corresponding  critical baseline concentrations.

     The following  assumptions  will  be made in applying the model:
     (a)  Background  concentration  (b) =  1 ppm.
     (b)  The CO standard to be considered is the 8-hour standard of 9
     ppm (=  FT).
     (c)  The growth  of.mobile  and  stationary sources will be assumed to
     be five  percent  annually (r) for  urban areas.  For a 1970 baseline,
     the projection period to 1985  is  15 years (n).   Thus, the growth

-------
factor is given by

           G = (1 + r)n  =  (I + -05)15 = 2.08

Therefore, a 1970-1985 growth factor of 2.0 will be used for all

urban sources, so

           GL = Gf| = Gs = 2.0


(d)  Growth of local traffic (G, * and Gu*) will be less than total

urban growth due to "saturation" of local streets with traffic

currently; assume G,* = G,* = 1.2.


(e)  The emission factor ratios from Table V-l will be used; no control

over stationary sources of CO will be assumed; thus

                      EL = 0.08

                      EH =0.93

                      Es=1.0


(f)  The percent contribution of CO emissions from stationary sources

is assumed to be 20.  The percent contribution of CO emissions from

light- and heavy-duty vehicles for the local street case will be

treated differently than for the urban case.  For the local street

case (FL), the PL and PH values will vary; for the urban case (Fy),

assume PL = 20 and PH = 10.  In either case, since P<- = 20, P.  + P.,

= 80.

     For the local case, equation (2) is used; inserting the values

assumed above yields

        FL      = PL (1.2)(0.08)  + PH (1.2)(0.93)

     0.8 (B-l)    ;80

            FI  = (B-1)[PL (0.096) + PH(0.09)]
             L                  80

-------
     For the urban case, equation (3) is used, yielding


     Fn        (70)(2.0)(0.08) + (10)(2.0)(0.93) + (20)(2.0)(1.0)
      u                               100
   0.2(8-1)
     From equation (1 ),


               FT = FL + FU + b


     Inserting the above values yields

                    P,  (0.096) + Pu (0.90)
          9 = (B-l)[-± -  — -H - ]  + (B-l)(0.140)
      or
   r
=  L
                    ,     i
          B =    j-PL(0.096)
                           80


     Substituting varying values of P.  and P., yields the corresponding


values of B given in Table A-l.  From these values, the criteria curve given


as Figure III-l  is  derived.


     There is no initial inclusion threshold for CO.  As a result, any


area which is not automatically excluded must be subjected to further


analysis as indicated in Sections IV and V.

-------
      Table A-l
Solutions to Equation
                8         	i
                                   + 1
'B = L P.
r I

[-
Percent of LDV emissions
contribution to total
local street vehicle
emissions
0
10
20
30
40
50
60
70
80
90
100
(0.096) + PH(0.90)
1
80 J


P.
. L
0
8
16
24
32
40
48
56
64
72
80
+ 0.140



PH
H
80
72
64
56
48
40
32
24
16
8
0
                                            8.7
                                            9.3
                                            10.1
                                            11.0
                                            12.1
                                            13.5
                                            15.3
                                            17.8
                                            21.2
                                            26.3
                                            34.9

-------
                              Attachment D



                         Supplementary Revisions




1.   Page IV-2, Table IV-1,  Delete the subcategory "MDV" (for "medium


     duty vehicles"), under the "Transportation" source class, from the


     table.






2.   Page V-3, paragraph (c) should be replaced with the following:


    "(c)  Percentage contribution of- light- and heavy-duty vehicles and



     stationary sources to the baseline year emission inventory (same year


     as air quality data).  This information should be computed from the


     latest emission inventory available locally.  If local  data is un-


     available, the National Emissions Data System (NEDS) data file contains


     emission data by county which may be used.  The users of equations (1),


     (2), and (3) must distinguish between two sets of P.  and P  values for


     the local traffic and general urban cases:  in the calculation of F. ,
     use the P,  and P,. values used in the application of the initial designation


     criteria for CO; in the calculation of F..


     corresponding to the general urban area."
criteria for CO; in the calculation of F... use the P,  and Pu values
                                        U           L      n

-------
I
          GUIDELINE  SERIES
                    OAQPS NO. 1,2-0111
                GUIDELINES FOR THE EVALUATION
                   OF AIR QUALITY TRENDS
          ^inT• i i_m i^n
            VS. ENVIRONMENTAL PROTECTION AGENCY
              Office of Air Quality Planning and Standards

                Research Triangle Park, North Carolina

-------
                                      FEBRUARY 1974
              Guideline Series
              OAQPS No. 1.2-014
      GUIDELINE FOR THE EVALUATION OF

             AIR QUALITY TRENDS
    U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF AIR QUALITY PLANNING AND STANDARDS
    MONITORING AND DATA ANALYSIS DIVISION
RESEARCH TRIANGLE PARK,' NORTH CAROLINA  27711

-------
                    TABLE OF CONTENTS
PREFACE                                                   i


1.  INTRODUCTION                                        '  1

    1.1.  Purpose                                         1
    1.2.  Usefulness                                      1
    1.3.  Limitations                                     1


2.  DATA REQUIREMENTS AND SELECTION                       3

    2.1.  Minimum Requirements                            3
    2.2.  Form of the Data                                3
    2.3.  Data Selection for Trends Analysis              4
3.  CONTRIBUTING FACTORS TO TRENDS                        5


4.  STATISTICAL METHODOLOGY                               6

    4.1.  General Discussion                              6
    4.2.  Statistical Parameters                          7
    4.3.  Time Periods                                    8
    4.4.  Specific Methods                                9
          4.4.1.  Graphical Analysis                      9
          4.4.2.  Correlation Techniques                 10
                  4.4.2.1.  Daniel's Test for Trend      12

                  4.4.2.2.  Parametric Correlation       14
                            Technique
          4.4.3.  Regression Techniques                  15

                  4.4.3.1.  Simple Linear Model          15
                  4.4.3.2.  Exponential Model            16

          4.4.4.  Test for Trend in Proportion Of
                  Observation Above A Standard           16

5.  ASSESSING REGIONAL TRENDS                            18


6.  INTERPRETATION OF TRENDS                             19


REFERENCES                                               25

-------
                LIST OF FIGURES AND  TABLES
FIGURE 1  THREE YEAR RUNNING AVERAGES  OF  TOTAL
          SUSPENDED PARTICULATE - New  Haven,  Conn.
FIGURE 2  THREE YEAR RUNNING AVERAGES OF TOTAL
          SUSPENDED PARTICULATE - Tucson, Ariz.
Page

 12


 12
TABLE 1   SUMMARY OF APPLICATION OF STATISTICAL         11
          PROCEDURES FOR CLASSIFYING TRENDS

TABLE 2   QUANTILES OF THE SPEARMAN TEST STATISTIC      22

TABLE 3   NORMAL DISTRIBUTION                           23

TABLE 4   PERCENTILES OF THE t DISTRIBUTION             24

TABLE 5   CHI-SQUARE DISTRIBUTION                       25

-------
                           PREFACE
     The Monitoring and Data Analysis Division of the Office
of Air Quality Planning and Standards has prepared this re-
port entitled "Evaluation of Air Quality Trends" for use by
the Regional Offices of the Environmental Protection Agency.
The purpose of this report is to provide guidance information
on current air quality trend evaluation techniques.  Adherence
to the guidance presented in the report will, hopefully, en-
sure mutually compatible ambient air quality trend evaluation
by all States and Regions and will also facilitate trend in-
terpretation.  Further, any risks involved in policy decisions
concerning National Ambient Air Quality Standards should be
minimized.  This report will serve on an interim basis until
more specific and detailed guidance on this subject is
presented.

-------
                 TRENDS ANALYSIS GUIDELINE

1.  INTRODUCTION
1.1.  Purpose
     The purpose of this guideline is to outline procedures
that can be  employed by the air pollution data analyst
to  evaluate  trends in air quality.  Trends will be generally
considered as the broad long-term movement in the overall time
sequence of  historical air quality measurements.  It will be
examined in  two ways.  First will be in the form of a trend
line or curve over time.  Second will be a statistical
categorization of the general direction of the movement over
time, i.e.,  upward, downward, or no change.  Associated with
the second approach can be estimates of the rate of change of
deterioration or improvement in the air quality.  Most trend
analysis can be performed upon aggregate measures of air
quality estimates such as averages.  For some pollutants,
however, the behavior of the short-term air quality, such as
maximum 1-hour concentrations, is important.  The behavior
of  short-term air quality estimates do not necessarily lend
themselves to the same kind of statistical treatment and as
such, are treated using different techniques.
1.2.  Usefulness
    Evaluation of the long-term trend in a sequence of air
quality parameters such as annual means is important in order
to assess the relative effectiveness of control strategies and
to determine the impact    of emission growth or reduction
on the air quality over time.
1.3.  Limitations
    The evaluation of air quality trends is largely a subjec-
tive procedure.  Various statistical techniques are available
to facilitate the evaluation, but insight and auxiliary know-

-------
ledge are often necessary for the final determination.  The
methods of trends analysis presented in this guideline are
primarily descriptive.  They are designed to consider the
trend in a single pollutant over time.   They will be useful as
a data reduction tool which will transform a collection of
air quality measurements or summary statistics over time
into a simpler form which can then be more easily interpreted.
In this manner the complex problem of analyzing the long-term
relationships among many different air pollutants monitored
at various monitoring locations in a given area or Air Quality
Control Region (AQCR) can be examined.
    The classification of a long-term trend into a single
category such as up or down is subject to certain constraints
and assumptions.   These include the time frame of interest,
assumptions about the seasonal behavior of the pollutant and
the type of statistical variability inherent in the measure-
ments.  The individual techniques presented depend on such
considerations in varying degrees.
    The techniques that are discussed are retrospective in  .
nature, that is to say they describe the historical record
of air quality measurements.  No attempt will be made here
to forecast or predict future air quality from past/ experienced
air quality.  Such techniques do exist, but for successful
application, they should not be based on historical air quality
measurements alone.  A diffusion model or modified rollback
procedure-*- may be used for air quality projections, thereby
accounting for emissions, regulations, growth and meteorology.

-------
2.  DATA -REQUIREMENTS AND SELECTION
2.1.  Minimum Requirements
    •In order to analyze the trend in a pollutant, a time
sequence of measurements or summary statistics over several
years is required.  Because of seasonal fluctuations., a
trend should not be determined from one year's worth of measure-
ments.  The data can be in any aggregate form of air quality
measurements (hourly, weekly, monthly, quarterly, or annual
estimates).  Ideally, the time series should not have any
significant gaps in the continuity of the series although
some gaps can be tolerated.  Temporal balance is essential.
For example, a single quarterly estimate may be omitted from
the sequence of many quarterly estimates if there is not a
pronounced seasonality.  Missing data can introduce bias in the
determination of the trend.  This can be minimized with the
availability of some prior knowledge of the data or some
auxiliary information on meteorology and emissions.  In any
e.vent such omissions should be clearly indicated.  If the
data satisfy the validity criteria as outlined in the
                                                 2
Guideline for the Evaluation of Air Quality Data,  there
should not be any problem.  Appropriate procedures useful
for analyzing trends when entire annual estimates are not
available will be discussed in Section 4 on statistical
techniques.
2.2.  Form of the Data
    An appropriate analysis can be based on several forms of
the data.  A preliminary analysis may be performed on the
data at hand, usually available in air quality publications.
For example, evaluation of the trend can be based on summary
statistics such as annual/quarterly averages and percentiles.
If a more detailed analysis is desired, the original raw data
may have to be utilized.  There is generally a trade off
between the type of aggregate measure utilized because the
larger the interval for the aggregate, the more precision
and stability is contained in the estimate, but the fewer
the number of time sequenced estimates are available for the

-------
trend analysis.  It is sometimes advantageous to deal with
certain estimates  (such as daily or annual) in order to
remove predictable factors such as diurnal and seasonal
variation respectively.
2.3.  Data Selection for Trends Analyses
    When considering the analysis of the time series of
measurements for a pollutant, certain precautions should be
observed.  In order to minimize the introduction of bias into
the evaluation, the data should be a product of the same
analytical (chemical and instrumental) methodology at the
same sampling site location for the entire time period under
consideration.  A common instance of this problem is a minor
instrument modification or movement.  If one is willing to
relax this rule in order to create the only possible complete
record of data for the analysis, then one must be willing to
accept the possibility of creating an apparent trend when none
exists, or indicating no trend when one does exist.
    Any change in the overall trend, especially an abrupt
shift or alteration coincident with the modification, must
be considered suspect.  For completeness and maximum accuracy,
all modifications to the placement or type of monitoring
equipment should be investigated, recorded, and considered in
the trend evaluation.  The possibility of bias can be overlooked
when the air monitoring specialist insures that there should not
be any discontinuity in the data.  However, it must be kept
in mind that often the reason for instrument change was that
something was wrong with the previous instrument or methodology.

-------
3.  CONTRIBUTING FACTORS TO TRENDS
    There are both determinant and random factors which
affect the trend of air quality measurements.  The determinant
factors include emissions, meteorological variables, and other
factors having a predictable influence.  Random factors are pri-
marily sampling and analysis errors, transient meteorological
phenomenon and random fluctuations in emissions.  With appropriate
auxiliary information on the environs of a monitoring site,
the reliability of apparent trends can be appraised.  For
example, environmental change such as urban renewal in the
vicinity of the sampling site can create the impression of
an apparent trend caused by area wide deterioration.  More-
over, in light of such localized change, the representativeness
of that particular sampling site and its corresponding trend
for an entire city or AQCR would have to be questioned.
    An unusually cold winter may cause an annual average to
be unusually high, possibly contributing to an apparent trend
in the preliminary trend evaluation.  In this case, auxiliary
meteorological information on degree days, chill factor, etc.,
together with the original raw data would be necessary to con-
firm the suspicion.

-------
4.  STATISTICAL METHODOLOGY
    4.1.  General Discussion
    Statistical techniques are desirable for an objective
description and classification of the trend.  They are
necessary to sort out the real change in air quality that is
distinguishable from the inherent random variability in air
quality measurements.  Although the statistical techniques
are objective in the sense that they are reproducible and
anyone applying them correctly will come up with the same
result, they are nevertheless subject to error.  These are
the standard type I and type II errors of hypothesis testing
                                  3 4
discussed in texts on statistics.  '
    Statistical techniques can be descriptive or inferential.
Descriptive statistics provide estimates of unknown parameters
such as means, variances and rates of change.  These are based
on a set of empirical data drawn from the entire population
of possible values.  Inferences can be made about the popu-
lation from which the data were sampled by judging the statis-
tical significance.  In general, this involves making certain
assumptions about the population, such as the distribu-
tion being log-normal.  Then the value of calculated test
statistic, derived from the sample of data, is compared to a
specific quantile of the assumed distribution of the test
statistic.  These are usually available in tabulated form.
This quantile defines the significance or a level and
specifies a critical value or pair of critical values of the
test statistic.
    The statistical significance can be utilized in more than
one way.  The traditional or classical approach is to pre-
select the a level and its corresponding quantile.  Then a test
of hypothesis is performed such as testing if no trend has
occurred.  If the test statistic falls in the predetermined
critical region defined by the extremal values of the test
statistic, the hypothesis is rejected.  By implication, if
the value of the statistic does not fall in the critical
region, the hypothesis is accepted.  For example, in trend
analysis, the assumed underlying distribution of the test

-------
statistic of the air quality parameters corresponds to that
of .a random variable without trend, that is, the null hypothesis
is there is not any trend.  A rejection of the hypothesis
is interpreted as the existence of a trend.  Then the trend
is    or is not significant at the particular a level.  Any
other possible information in.the test statistic is then usually
ignored.
    A second utilization of the statistical significance does
not involve a preselected a level, per se.  The statistical signi-
ficance of the test statistic is defined by the significance
level associated with the tabulated value equal to or just
below the calculated statistic.  Then the resultant signi-
ficance level can be compared to a preselected level to classify
the test parameter but in addition, can be used to judge the
relative strength of the result compared with other cases.
    Conventionally, preselected levels of 0.10, 0.05 or
0.01 are utilized.  These would usually correspond to quantiles.
of 0.95, 0.975 and 0.995 respectively of a two sided statistical
test for both upward or downward trends.  The smaller the a or
significance level, the less likely a trend would be declared
erroneously.  One might then say the trend is highly signi-
ficant.  Levels like 0.10 would be used as preliminary in-
dicators of trend whereas smaller levels would be used to more
vigorously test for significant trends at an individual site.
The likelihood of correctly accepting a pattern as a non-
trend is determined by the power of the individual statistical
techniques.
4.2.  Statistical Parameters
    Air quality data may have different meanings when reviewed
by different aggregate measures, although they frequently vary
together.  For example, a sequence of the average of maximum
daily 8-hour or 1-hour concentrations can depict similair trends
in direction but perhaps not similar in magnitude.

-------
Nevertheless, it is useful to examine the trend in various
aggregate measures, especially those relating to the air
quality standards.  In this manner the progress with respect to
achieving each standard can be assessed.  Such useful parameters
are annual means and percent of observations exceeding
the short-term standards.  Once the parameter is selected,
a statistical test, is not always necessary because the trend
may be obvious, but may be convenient for documentation
purposes.
4.3.  Time Periods
    The time frame of the data under consideration can seriously
affect the classification of the overall trend.  For instance,
if concentrations decreased sharply in the 4-years from 1960
to 1963 but remained level in the 8-years from 1964 to 1971,
then the 12-year trend from 1960-1971 would probably be down-
ward, whereas, the trend 8-years from 1964-1971 would result
as no change.  On the other hand, if concentrations experienced
an increase from 1964-1971, its trend would be classified up-
ward, whereas the overall trend from 1960-1971 might still
be classified downward.  Therefore, it can be seen that the
classification of trend is clearly dependent on the time frame
under consideration.
    The time frame for evaluation should be selected in an
objective manner.  Usually the availability of data is the
determining factor, but the interval can be preselected
based on knowledge of the temporal pattern of emissions.
It is desirable to perform the trend evaluation over several
different time intervals in order to obtain a more complete
description of the overall pattern and to avoid the afore-
mentioned problems.  In the first Annual Trends Report,5
long-term trends were considered during the periods 1960-
1967, 1964-1971, 1960-1971, and 1968-1971.  It was not un-
common for the trend determined by evaluating the data in
one time period to differ from the trend in another time
period at a single location.

-------
4.4.  Specific Methods
    There are some very sophisticated methods providing time
series analysis of air quality data.  These have been presented
in some recent publications. 6,7  A.I though the methods can provide
much information, they can be difficult to use and generally
require assistance of a computer.  Some of the simplier ap-
proaches utilized in the Federal trends reports  will be
presented in this guideline.  The techniques are oriented towards
examining the concentration or frequency of occurrence of air
quality measurements.

4.4.1.  Graphical Analysis
    When performing a trend analysis., it is extremely desirable
to look at the data in graphic form.  Usually plotting
quarterly or annual statistics over time will be sufficient
to depict the basic temporal pattern.  At this point the
determination of the trend may be intuitively clear.  In
order to facilitate the interpretation of the overall pattern,
it can be helpful to determine an objective trend line for the
data.  This can be simply obtained by calculating a moving
average of the observations.  This will provide a smoother
and simpler representation of the original data.  For quarterly
estimates, a moving annual average consisting of four quarterly
estimates will eliminate the seasonal fluctuations and remove
much of random variation as well.  When considering annual
estimates over several years, a three-year moving average will
smooth out much of the year-to-year variation.  In specific
instances other averaging schemes may be considered.  The se-
lection of the appropriate moving average is subject to personal
judgement.  VJhen employing the moving average, estimates of
the trend line at the beginning and end of the data time series
are usually omitted.
    Other curve smoothing techniques such as the Whittaker-
Henderson smoothing formula have previously been employed in
the analysis of air quality trends, but they can be more
difficult to apply since they generally require the use of a
computer.

-------
                           10
Example la;  Figure 1 depicts a trend line for annual geo-
metric Total Suspended Particulate  (TSP) monitored at the
N/ASN site in New Haven, Connecticut from 1960-1971.  The
curve was obtained by computing a 3-year moving average of the
annual estimates and plotting each point at the middle year
of each 3-year group.  It characterizes the trend as reversing
direction during the 12-year period.
Ex amp 1. e_lb_;  Figure 2 depicts an analagous trend line for TSP
at the Tucson, Arizona NASN site.  In this instance, the
trend line depicts a long-terra downward trend which has
stabilized in the latter years.

    The trend lines thus formed provides a nice descriptive
tool for the evaluation of the overall trend.  Since subjective
bias may creep into the interpretation of the trend, objective
techniques are desirable to classify the overall pattern and
quantify the amount of change.  The following constitutes a
variety of statistical techniques which have been useful for
this purpose.  Several techniques may be appropriate to analyze
a given set of data.  It may be desirable to employ more than
one since occasionally they can produce different conclusions
due to some of the different assumptions on which they are
based.  It is not uncommon, however, for several sets of
assumptions to seem equally reasonable.  It is at this point
that subjective judgement of the auxiliary information contributes
to assessing the various formal results.  For convenience,
Table 1 summarizes the typical usage of the particular statistical
procedures.  In each case, the procedure assumes at least that
the observations or the air quality parameters could have
occurred with 'equal likelihood.
4.4.2.  Correlation Techniques
    These techniques consider the statistical significance of
the correlation of pollutant observations or summary statistics
with, the sequence in which they were observed.  Since the time
interval between observations is not considered, missing ob~
s erva tions can be ignored.

-------
     TABLE 1  SUMMARY OF APPLICATION OF STATISTICAL PROCEDURES FOR CLASSIFYING TRENDS
     Type of Analysis
      Form of Data
     Techniaue
Trend in short-term air quality
Trend in long-term air quality
       (averages)
Estimation of rate of change
in long-term air quality
Specific quantiles or maxi-
mum value per year or of
a given quarter/season

Percent observations greater
than specific concentration   |
between two time periods

Annual averages or average
level for specific quarter/
season over several years

Same as Above
Spearman Correlation
                                                                       Chi-Square
Spearman Correlation
        or
Parametric Correlation*

    Regression*
 ^Additional assumption required that observations are normally (log-normally) distributed.

-------
125
                                    NEW HAVEN, CONNECTICUT
100
 75
 25
                                                                                                            GEOMETRIC  MEAN

                                                                                                    OTHREE YEAR AVERAGE
     60
110
61
62
                                   63
                              64
                                                       65
                                        66         67         68         69
                          YEAR
    FIGURE 2 -THREE YEAR RUNNING AVERAGES  OF  TOTAL SUSPENDED PARTICULATE
                                                                                                         70
                                                                                                    71
100
                                            V


                                            -OU
                                                       TUCSON, ARIZONA
                                                                                                           L  GEOMETRIC KKAN


                                                                                                      THREE YEAR AVERAGE
               Cl
          62
                                  63
                             65
                          YEAR
                                                 66
67
                                                                     63
                                                                                              69
                                                                                         70
                                                                                                   71

-------
                              13
    Tliey can be applied to any set of aggregate measure of
pollutant values,  subject to the assumption that they are
equally likely and independent.  Therefore, if seasonality is
suspected,  annual  estimates should be used or individual
seasonal estimates should be considered  separately.
    Two types of these procedures are presented.  The first
is nonparametric   meaning no further assumptions are necessary,
It examines for a  consistently changing  series.  The second
is parametric, requiring the additional  assumption, frequently
encountered, that  the data or their logarithms are normally
distributed.  It is sensitive to a constant absolute or
percentage  change.
4.4.2.1.  Daniels  Test for Trend using the Spearman Rank
          Correlation
    In order to utilize this procedure,  at least four observa-
tions should be available.  Given observations X-,,  ..., X
and their corresponding relative ranks R(X,),  ..., R(X }, the
test statistic is  the Spearman Rank Correlation Coefficient:

                      p =  1 -     6T
                              n(n2-!)
                              2
         where  T = Z[R(Xi)-i] , that is, the summed squares
of the differences between each values rank and its sequential
order, i, in the series of n observations.  The absolute
value of p is compared with a critical value w  in Table 2,
if n <30, and with w =X / J n-1, if n >> 30, where X  is the
p quantile of a  standard normal random variable obtained from
Table 3.  If |p|> w  then a trend is declared significant
at the a=2p significance level.  A positive value of p in-
dicates an upward trend while a negjitive value of p in-
dicates a downward trend.  It can be noted that the estimate
of the Spearman  rank correlation coefficient p is merely the
usual product moment correlation of the ranks of the ob-
servations with  the order in which the observations were
taken.

-------
                              14
•Example  2a,:  Applications  of  Daniel's  Test for Trend on Tucson
 TSP Data 1964-1971.   The following table  provides  the annual
 geometric means,  their  relative  values and the index over
 time.
x*
i
R(Xi)
i
128

8
1
118

7
2
80

3
3
89

5
4
70

1
5
78

2
6
96

6
7
88 •

4
8
If ties had occurred, the ranks can be determined by averaging
the ranks among the tied observations, or preferably utilizing
the data estimates to the next available place, even if it is
not a significant digit.
    T = £ (R(X .)-i)2
      = (8-1)2 +  (7-2)2 +  (3-3)2 +  (5-4)2 +  (1-5)2 +  (2-6)2
        + (6-7)2 + (4-8)2
      = 49 + 25 _+ 0 + 1 + 16 + 16 + 1 + 16
      = 124
      _ -I      6T
   p  - 1-	
            n(n^-l)

      = 0.476
    The .90 quantile of the Spearman test statistic is  .5000
for n=8.  Therefore,  apparent downward trend would not be
accepted even at the a= 0.20 significance level.
    Using the entire twelve year record of data, p=-0.769.
This is greater than the .995 quantile for n=12.  Therefore,
the 12-year trend can clearly be classified downward.
    The Spearman coefficient on the data from 1968-1971 is
p=+0.80.  This pattern is upward but is only significant at
the 0.20 level.  The technique is not very powerful at such
small sample sizes.

-------
                                15
    The  above  technique is primarily useful for classifying the
temporal pattern as upward or downward and indicating the con-
sistency of  the  pattern by the statistical significance level.
4.4.2.2.   Parametric Correlation Technique
    Let  X-,  i=l,n be a sequence of observations or their
logarithms.  The test statistic is
         /      I   ~                        9
    T  = \'n-?   Jc  ft               c = 1  (n -1)
    1   2J -...-__ •.-- ___ £•>     where         — _
            ~~""
                                      12
                                                   X.
                                           ,.
                                 3 = -   (1- - )
                                      .nc       2
                                  a2= 1  I (X.-X)2
                                      ™""""      JL
                                      n
T is compared to the p quantile of Students t statistics with
 (n-2)  degrees of freedom provided in Table 4.  If  |T|> t then
the trend  is  declared significant at the a=2 (1-p)  significance
level.   A  positive value of T indicates an upward  trend,
while  a  negative value of T indicates a downward trend.
Example  2b:   Application of Parametric Correlation Technique
to Tucson, Arizona TSP Data 1964-1971.
    T  = yn-2 Jc  3/N/a2-c32
    c  = 1   (n2-!)  = 1  (64-1)  = 5.25
       12           12
=     !    ( -3.5 In  (128) -2.5  In  (118)  -1.5 In (80)
   8(5.25)   -0.5 In  (89) +0.5  In  (70)  +  1.5  In (78)  +
             +2.5 In  (96) +  3.5  In  (88)  }
= -1.985/42 =  -.047
 2 _  1 Z  (X.-X)2 =11  X.2  -  (S X.)  = .03715
U  —  "Q"     -1-       ~Q     ^         1	
      8             8           —g	

then T = t/6  /5.25  (-0.047/  / 037-5.25T.~00?)'
       •= -1.65

-------
                              16

 This value lies between, the ..90 ^3. .95 quantile of the
 students t statistic.  Therefore, the trend can be considered
 significant at the 0.20 level but not. the 0.10 level.
      Both the Spearman and the parametric correlation techniques
 failed to detect a trend during 1964-1970 because of the year-to-
 year variability in the annual estimates.
     Considering the entire 12-year period, the value of the
 test statistic T=-3.810.  This is significant at the .01 level,
 and  the trend can therefore be classified downward.  The value
 of the corresponding test statistic for the 4-year interval
 1968-1971 is T=+2.15.  This is only significant at the 0.20
 level.  Note the similarity between these results and those
 obtained by using the simpler non-parametric analogue.
 4.4.3.  Regression Techniques
     For this technique,  the temporal distance between observa-
 tions is considered.  Its primary application is to produce
 estimates of the constant rate of absolute or percent change
 (growth or decay)  over time.
 4.4.3.1.  Simple Linear Model
     To estimate a constant absolute change, b.,  corresponding to
 the  model X=a+bT,
     /^
     b = Z(T^-T)X.j              where pollutant concentration, X.
         /       O/~    — /    ^vic"f'c:Pi'f"'f~'iTno'T1
         Jr /m _rp\ •<- -A] (X • —X)      <=-K..L_l_,j clt UXJIIK •*• T*
             i        i
The  estimate of "a" is    a = x - bT .
The  statistical  significva^co of the estimate of  b as compared with
an assumed value  b0 can be tested by computing
               B  - (b-b0)//s2/I(T-T)2

where  ??- - {T. (X-X) 2~IE (T-T)X] 2/l (T-T) 2] }/ (n-2)
and comparing  B with  the Student's  t  statistic,  t, at the .p quantile,
with n-2 degrees  of freedom.  If IB! > t then  the  rate of change
is significantly different than b0   at the  a=2p significance  llevel.

-------
                               17
 In a similar manner, a confidence interval can be created
      •              S\                              S\      ~f	- — _•___ri—«~ J_M__
 about the estimate b.  The interval is defined as b ± t vs^/i. (T-T)
 This interval contains the "true" rate of change, b, with
 Probability 1-a.

 4.4.3.2.   Exponential Model
      To  estimate the percent  rate of change,  r corresponding
                  T
 to  the model X~ar.,  calculate and test significance  of log (r)
 by  substituting  log  (X.)  for  X.  in the formulae of the previous
 section.   The  rate of change  is  usually presented as a change
 of  (r-1)  x 100%  per  unit  of time.
 Example  3;   The  above regression techniques  are applied to the
 TSP data for New Haven, Connecticut.
      The estimates of absolute and percentage rates  of change
 are presented  for the time intervals 1960-1971, 1964-1971,  and
 1968-1971.
                        Rates of Change
               Absolute                  Percent
0.26
-2.24
-(-7.00
1960-1971
1964-1971
1968-1971
+ 0.27
-3.46
+ 9.26
This again  demonstrates  that  the  choice of time interval can
play an  important  role in  the determination of  an estimated
rate of  change.
4.4.4.   Test for Trend in Proportion of Observations Above
        A Standard (Chi Square Analysis)

    This technique is useful  to test for a change in  the
extreme value or short-term statistics.  It compares  the
percent of  observations  above a given  threshold concentration,
such as a 1-hour standard, between two time periods.   It is
desirable to consider independent observations.   Therefore,
for hourly  data one should consider at most one observation

-------
                               18
per day, e.g.,  the maximum observation  per  day  or  the  obser-
vation of  a  particular  hour.   In  general, observations
•derived by intermittent sampling  can  be considered independent.
                      No.  Obs  = Standard No. Obs  > Standard
     TIME PERIOD  I
     TIME PERIOD  II
                             b
                             d
                                                              n.
                                        n.
                                                              N
The  test  should  only  be  used if  there  are  at least five
observations  in  each  of  the  four cells..
Let  p.,--b/n, be the  proportion of observations in  time period I
that are  above the  standard.   Similarly, p =d/n2  for time
period  II.
      One can test  (i) for any change  between the two time•
periods disregarding  whether it  is  an  increase or a decrease,
e.e., P-]~P2 or  (ii) specific direction of  change  between the
two  time  periods, say p,
-------
                               19
                     £  standard    >standard
1964-1967
1968-1971
j 662
| 714
154
111
TOTALS 1376 265
! n1 = 816
j n2 = 825
1641
    T _   (n +n2)  (ad-bc)
         n,n~ (a+.c) (b-i-d)

          (1641) [(662) (111)  -  (154) (714)]2
             (816)  (825)  (1376)  (265)
      =  8.9

At .the level of significance of  .05,  the calculated value  of  T
exceeds the tabulated statistic  at .90 quantile - 2.706.  It can
therefore be concluded that short-term oxidant  levels  have
significantly decreased  in  recent years  at  the  particular
site.
5.  ASSESSING REGIONAL TRENDS
    Trends can be discussed in terms  of measurements at  a
single location over time or collectively at a  group of  sites
over time for the purpose of assessing national or regional
trends.  The collective  analysis has  been employed in  the
Federal Trends Reports^.
    In general, the assessment can be done  in two ways.  The
recommended approach is  to  determine  the trend  at each indi-
vidual site and then summarize the results  for  the group of
sites.  The trend at each individual  site can be classified
as upv/ard, downward, or  no  change.  This may be done over  a
variety of time periods, but it is important to separately
consider the Scime time interval for each site.  The summary
would then be in the form of the number of  upward trends,
downward trends and no change.  In order to consider trends
at various concentration levels, the  analysis may be considered
for separate groups of sites with typically high or low  concen-
trations .

-------
                             20
    An alternate approach is to consider a composite index
of the data from all the sites at each point in time, such as
a composite average over time.  This composite form of the
data lends itself to a convenient graphical summary, however,
there are some limitations.  In general, the composite can be
dominated by a few individual sites.  Say for example, the group
of sites is diverse and constitute a wide range of concentration
levels.  Then a composite average can be dominated by the
behavior of the sites with the highest concentration levels,
thereby hiding the behavior at the sites with the lower concen-
tration levels.  Also, the rate of change of the composite
may not represent the typical rate of change of the individual
sites.  A zero rate of change may in fact be a product of an
equal number of increasing and decreasing patterns.  Another
source of error may be the non-independence or misrepresen-
tation of the sampling stations.  For example, within a
particular AQCR the vast majority of the sampling locations can
be concentrated within a single urban area, while the remaining
sites are distributed throughout the remainder of the region.
An equal weighing of the sampling information within the AQCR
may actually favor certain well monitored districts and as
such, misrepresent the entire AQCR.  Moreover, many of the
sites in that single urban area may provide equivalent or in a
sense redundant information in terms of trends or concentration
levels.  A logical solution may be to form a weighted average
of the sites within the AQCR according to spatial location or
by combining information within separate homogeneous groupings
such as business, industrial, residential, etc.
    It can be seen it is imperative to investigate and con-
sider the pollutant behavior and relative circumstances at
individual sites in the evaluation of regional trends.
6.  INTERPRETATION OF TRENDS
    The classification of the trend of an air pollutant is
a description of its historical behavior.  Thir. can be done

-------
                             21
by means of a fitted curve, an estimate of the rate of change
or a qualitative description such as upward or downward.  This
classification is only a starting point.  The reality of the
so-called trend and the possible explanations depends on many
factors, each of which must enter into the final analysis.
    First of all, steps should be taken to ensure that the
trend is not a product of changes in instrumentation, metho-
doloqy, site location, etc.  If these are the case, experience
may dictate the relative effect of any of these factors.
    Secondly, if the historical data record is only a partial
sampling of the entire time period studied, perhaps derived
by intermittent sampling, then the implication of the
apparent trend must be considered.  That is, is the historical
rec-ord representative of the true air quality history or was
it influenced by unrepresentative transient phenomenon?  This
evaluation may involve the investigation of the reality and
representativeness of the extreme measurements which are
causing the apparent change in air quality.
    Thirdly, the representativeness of the trend at a particu-
lar site of a larger area must be considered.  A site located
in the central business district of an urban area may not be
representative of the entire city  nor its AQCR.  This
qualification  applies  to the  sites  of  the National
Air Surveillance Network.
    Fourth, the trend is merely a representation of past air
quality.  Without accompanying data on meteorology and
emission patterns, the trend should not be extrapolated to
predict future concentration levels or continued direction of
change.

-------
                                        22
TABT E  2               QUANTILKS OF TIII: SPKAKMAN TLST STATISTIC"
n
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20

21
22
23
24
25

26
27
28
29
30
For n

p = .WO
.8000
.7000
.6000
.5357
.5000
.4667
.4424
.4182
.3986
.3791
.3626
.3500
.3382
.3260
.3148
.3070
.2977
0
.2909
.2829
.2767
.2704
.2646

.2588
.2540
.2490
.2443
.2400
greater than

.950
.8000
.8000
.7714
.6786
.6190
.5833
.5515
.5273
.4965
.4780
.4593
.4429
.4265
.4118
.3994
.3895
.3789

.3688
.3597
.3518
.3435
.3362

.3299
.3236
.3175
.3113
.3059
30 the ap

.975

.9000
.8286
.7450
.7143
.6833
.6364
.6091
.5804
.5549
.5341
.5179
.5000
.4853
.4716
.4579
.4451

.4351
.424 1
.4150
.4061
.3977

.3894
.3822
.3749
.3685
.3620
proximate cjuaniilcs
*i>
.990

.9000
.8857
.8571
.8095
.7667
.7333
.7000
.6713
.6429
.6220
.6000
.5824
.5637
.5480
.5333
.5203

.5078
.4963
.4852
.4748
.4654

.4564
.4481
.4401
.4320
.4251
of^ may

.995


.9429
.8929
.8571
.8167
.7818
.7455
.7273
.6578
.6747
.6536
.6324
.6152
.5975
V5825
.5684

.5545
.5426
.5306
.5200
.5100
0 ,
.5002
.4915
.4828
.4744
.4665
be obtained

.999



.9643
.9286
.9000
.8667
.8364
.8182
.7912
.7670
.7-16-t
.7265
.7083
.6904
* .6737
.65S6

.6455
.6318
.6186
.6070
.5962

.5856
.5757
.5660
.5567
.5479
from

    where .r,, is the p quantile of a standard normal random variable obtained from
    Table 1.

    SOL'KCt.  Adapted from Glassor and Winter (1961), with corrections.
      " The entries in this table aie selected quaniilcs % of the Spearman rank correlaiinn
    C0i-flicicni p when used as a test sUitiilie. The lower quaniiles may be obtained from Ihc
    equation
                                      •"„ = -ww
    The critical region corresponds to values of p smaller than (or greater than) but not includ-
    ing the appropriate quantile. Note  that  the median of p  is 0.

-------
                                23
TABLE
«•„
-3.7190
-3.2905
-3.0902
-2.5758
-2.3263
-2.1701
-2.0537
- .9600
- .8808
- .7507
- .6449
- .5548
- .4758
- .4395
- .4051
- .3408
- .2816
- .2265
- .1750
- .1264
-1.0803
-1.0364
-.9945
-.9542
-.9154
-.8779
-.8416
-.8064
-.7722
-.7388
-.7063
-.6745
-.6433
-.6128
-.5828
-.5534-
-.5244
-.4959
3
y
.0001
.0005
.001
.005
.01
.015
.02
.025
.03
.04
.05
.06
.07
.075
.08
.09,
.10
.11
.12
.13
.14
.15
.16
.17
.18
.19
.20
.21
.22
.23
.24
.25
.26
.27
.28
.29
.30
.31
INUKMAI. IJ
»'„
-.4677
-.4399
-.4125
-.3853
-.3585
-.3319
-.3055
-.2793
-.2533
. -.2275
-.2019
-.1764
-.1510
-.1257
-.1004
-.0753
-.0502
-.0251
.0000
.0251
.0502
.0753
.1004
.1257
.1510
.1764
.2019
.2275
.2533
.2793
.3055
.3319
.3585
.3853
.4125
.4399
.4677
. .4959
ISTKIUUTION"
P "V
.32 .5244
.33 .5534
.34 .5828
.35 .6128
.36 .6433
.37 .6745
..38 .7063
.39 .7388
.40 .7722
.41 .8064
.42 .8416
.43 .8779
.44 .9154
.45 .9542
.46 .9945
.47 .0364
.48 .0803
.49 .1264
.50 .1750
.51 .2265
.52 .2816
.53 .3408
.54 .4051
.55 .4395
.56 .4758
.57 .5548
.58 .6449
.59 . .7507
.60 .8808
.61 .9600
.62 2.0537
.63 2.1701
.64 2.3263
.65 2.5758
.66 3.0902
.67 3.2905
.68 3.7190
.69

/'
.70
.71
.72
.73
.74
.75
.76
.77
.78
.79
.80
.81
.82
.83
.84
.85
"• .86
.87
.88
.89
.90
.91
.92
.925
.93
.94
.95
.96
.97
.975
.98
.985
.99
.995
.999
.9995
.9999

SOURCE.  Abridged from Tables 3 and 4, pp. 111-112, Pearson and Hartley (1962).
  "The entries in this table arc quantiles if,, of the standard normal random variable H.
selected so P(W £ wf) — p and P(W > wv) = !—/».

-------
                                                                  24
                           TABLE  4
PERCENTILES OF  THE  t DISTRIBUTION
\
df
^
1
2
3
4
5
6
7
8
9
10"
11
12
13
14
15
16
17
18
19
20
21
22
23
24 '
25
26
27
28
29
30
40
60
120
X
«.w
.325
.289
.277
.271
.267
.265
.263
.262
.261
.260
.260
.259
.259
.258
>.258
.258
.257
.257
.257
.257
.257
.256
.256
.256
.256
.256
.256
.256
.256
.256
.255
.254
.254
.253
'.70
.727
.617
.584
.569
.559
.553
.549
.546
.543
.542
.540
.539
.538
.537
.536
.535
.534
.534
.533
.533
• .532 ,
.532
.532
.531
.531
.531
.531
.530
.530
..530
.529
.527
.526
.524
*.8D
1.376
1.061
.978
.941
.920
.906
.896
.889
" .883
.879
.876
.873
.870
.868
.866
.865
.863
.862
.861
.860
.859
.858
.858
.857
.856.
.856
.855
.855
.854
.854
.851
.848
.845
.842
'.90
3.078
1.886
1.638
1.533
1.476
1.440
1.415
1.397
1.383
1.372
1.363
1.356
1.350
1.345
1.341
1.337
1.333
1.330
1.328
1.325
1.323
1.321
1.319
1.318
1.316
1.315
1.314
1.313
1.311
1.310
1.303
'.95
6.314
2.920
2.353
2.132
2.015
1.943
1.895
1.860
1.833
1.812
1.796
1.782
1.771
1.761
1.753
1.746
1.740
1.734
1.729
1.725
1.721
1.717
1.714
1.711
1.708
1.706
1.703
1.701
1.699
1.697
1.6S4
1.296 1.671
1.289 i 1.C5S
1.282
1.645
'.975
12.706
4.303
3.182
2.776
2.571
2.447
2.365
2.306
2.262
2.228
2.201
2.179
2.160
2.145
2.131
2.120
2.110
2.101
2.093
2.086
2.080
2.074
2.069 '
2.064
2.060
2.056
2.052
2.0-18
2.045
2.042
2.021
2.000
1.9SO
1.960
'.99
31.821
6.965
4.541
3.747
3.365
3.143
2.998
2.896
2.821
2.764
2.718
2.681
2.650
2.624
2.602
2. 583
2.567
2.552
2.539
2.528
2.518
2.508
2.500
2.492
2.485
2.479
2.473
2M67
2. 462
2.457
2.423
'.Mi
63.657
9.925
5.841
4.604
4.032
3.707
3.499
3.355
3.250
3.169
3.106
3.055
3.012
2.977
2.947
2.921
2.898
2.878
2.861
2.845
2.831
2.819
2.807
2.797
2.787
2.779
2.771
2.763
2.756
2.750
2.704
2.390 ! 2.6GO
2.35S ! 2.617
2.326
2.576
Ao'*M>!' W. J Hiv-m ;tn.| F. J. M:»v*y. Jr .  ropyr;>:M, 1V.T, Mr'.'iraw-Hill
Curi.jmny, Inc.  l.'nun-s uri^inatly ffuin T;ti)U* HI of ,S:i.li.
-------
                               25
TABLE 5  QUANTILES OF A CHI SQUARE RANDOM VARIABLE WITH
                      ONE DEGREE OF FREEDOM
              Quantile, p
W
.750
.900
.950
.975
.990
.995
.999
1.323
2.706
3.841
5.024
6.635
7.879
10.830

-------
                             26
                         REFERENCES
lt  Federal Register/ 36, No.  158,  page  15490,  August 14,  1971.

2.  "Guidelines for the Evaluation  of  Air  Quality Data"  U.  S.
    Environmental Protection Agency, Office  of  Air Quality
    Planning and Standards, Research Triangle Park,  N.C.,
    OAQPS No. 1.2-015*, January 1974.

3.  Conover, T\T. J. , ".Practical Non-Parametric Statistics ,"
    John Wiley & Sons , "~lnc . , NT" Y77~T97;U

4.  Torrie, J. PI. and Steel, R. C.,  "Principles and Procedures
    of Statistics, McGraw Hill PublisTvIlr^T:b~~~^^7~M^  ?. ,  I960

5.  "National Air Monitoring Program:   Air Quality and Emission
                      l:\T, Vo lumc~T",  CT  ST~ITnvirori3'nenT;al
                     7~0 f f i ce of Air Quality Planning and
    Standards, Research Triangle  Park,  N.  C.

6.   Merz, P. IT., Painter, L. J. ,  Ryason,  P.  R. ,  "Aerometric
  •  Data Analysis --Time Series Analysis  and Forecast and
    Atmospheric Smog Diagram".

7.   Tiao, G". C. , Box, G. E. P., and  Hamming,  W.  J. ,  "Analysis
    of Los Angeles Photochemical  Smog Data:   A Statistical
    Overview," Technical Report t-331, Department of  Statistics,
    University of Wisconsin, Madison.

-------
!
j
|
|
j
!
i
i
         GUIDELINE  SERIES
                   OAQPS NO. 1,2-015
GUIDELINES FOR THE EVALUATION

 .   OF AIR QUALITY DATA
                        J%ttiiiwm^^^^lT
            VS. ENVIRONMENTAL PROTECTION AGENCY
             Office of Air Quality Planning and Standards



               Research Triangle Park, North Carolina

-------
               GUIDELINE SERIES

               OAQPS NO. 1.2-015
       GUIDELINES  FOR THE EVALUATION OF
               AIR  QUALITY DATA
   U.  S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF AIR  QUALITY PLANNING AND STANDARDS
   MONITORING  AND DATA ANALYSIS DIVISION
RESEARCH TRIANGLE PARK,  NORTH CAROLINA  27711

-------
                    TABLE OF CONTENTS
                                                    PAGE


PREFACE                                               i

1.  INTRODUCTION                                      1

2.  BASIC CONVENTIONS FOR HANDLING AIR QUALITY DATA   2

      2.1.  Significant Figures                       3
      2.2.  Minimum Detectable Limit                  3

3.  CHARACTERISTIC PATTERNS OF AIR QUALITY DATA       5

      3.1.  Seasonal Patterns                         7
      3.2.  Diurnal Patterns                          7
      3.3.  Frequency Distribution                   10

4.  SUMMARIZING AIR QUALITY DATA                     10

      4.1.  Indicating Typical Values                13
      4.2.  Indicating Maximum Values                15
      4.3.  Indicators of Spread                     17

5.  MAKING INFERENCES FROM AIR QUALITY DATA          17

      5.1.  Inferences About a Particular Site       19
      5.2.  Inferences About a Region                22

6.  SOME STATISTICAL TESTS                           24

      6.1.  Student's T-test                         26
      6.2.  Non-Parametric Quantile Test             28

7.  BASIC MEANS OF OBTAINING AIR QUALITY DATA        29

-------
                LIST OF TABLES AND FIGURES
                                                   PAGE

TABLE 1  Suggested Reporting Accuracy        •        4
         For Raw Data
TABLE 2  Minimum Detectable Limits for Selected
         Measurement Techniques                      6

TABLE 3  Number of Hours Above Oxidant Standard     11
         By Month and Time of Day  (1971 Data)

TABLE 4  Maximum and Second High Values (Phila.)    16
         for Various Sampling Schemes

TABLE 5  Geometric Means, Medians, and 90th         18
         Percentile Values  For Table 4

TABLE 6  Summary Criteria for Continuous            21
         Measurements

TABLE 7  Probability of Selecting Two or More       23
         Days When Site is Above Standard

TABLE 8  NADB Output for Common Questions on        31
         Air Quality
FIGURE 1  Graphs of Monthly Averages for Various     8
          Pollutants at a Particular Site

FIGURE 2  Graphs of Seasonal Patterns for Various    9
          Pollutants at a Particular Site

FIGURE 3  Frequency Distribution - TSP (Phila.)     12

-------
                           PREFACE

     The Monitoring and Data Analysis Division of the Office
of Air Quality Planning and Standards has prepared this
guideline entitled "Guidelines for the Evaluation of Air
Quality Data" for use by the Regional Offices of the Environ-
mental Protection Agency.  The purpose of the report is to
provide guidance information on current air quality data
evaluation techniques.  Adherence to the guidance presented
in the report will, hopefully, ensure mutually compatible
ambient air quality data evaluation by all States and Regions.
Fux-ther, any risks involved in policy decisions concerning
National Ambient Air Quality Standards should be minimized.
This report will serve on an interim basis until more
specific and detailed guidance on this subject is developed.

-------
1.   INTRODUCTION





         The purpose of this guideline document is to present




    the basic elenents of air quality data analysis that are




    essential in preparing reports describing the air quality.



    status of a given region.  With this aim in mind, emphasis has



    been placed upon describing both the conventions and the




    methodology to be employed with minimum discussion of the




    associated statistical theory.  Much of the material that



    is presented has been treated before but for the sake of



    completeness,  is reiterated in this document with appropriate



    references indicated.



         Since the phrase "air quality data" covers a variety



    of possible data sets/ it is convenient to indicate the



    exact nature of this phrase as used in this paper.   For present



    purposes, the  term "air quality data" refers to a set of  ob-



    servations for a particular pollutant having the following




    properties:



              1.   All measurements were made at the same site.



              2.   Uniform methodology was employed.



              3.   All measurements have the same averaging time.



         It should be noted that the statistical treatments described



    here for s\ach  a data set constitute a minimum effort.  There



   . are a variety  of more sophisticated techniques available  that



    could be used  to extract more information from the data.   In



    general, the  degree of effort devoted to data analysis should

-------
    be consistent with the value associated with the data.   This



    can be viewed in financial terms as cost of data analysis



    versus cost of data collection or cost of data analysis versus



    potential cost of control strategies, etc.  In most cases,



    the extent of the data analysis phase is determined by a sub-



    jective judgment of what is appropriate.  It should be noted



    that no matter how extensive the data analysis effort is, the



    end result can be no better than the original data.  This



    point is particularly important because throughout the following



    discussions no analysis is made concerning the errors inherent



   .in the measurement method.  Therefore, it is essential that



    the air quality data analyst be aware of the shortcomings in



    the data and the conclusions that are "statistically signifi-



    cant" be carefully evaluated to .determine if they are "really



    significant."



2.  BASIC CONVENTIONS FOR HANDLING AIR QUALITY DATA



         Before discussing the analysis of air quality data, it



    is essential that certain basic conventions be presented for



    handling the raw data.  These conventions are introduced to



    prevent the air quality summaries from appearing to be more



    accurate than the data warrants.  These conventions have been



    discussed previously  (Nehls and Akland, 1973) and are repeated



    here since they are the procedures presently employed by EPA



    in maintaining the National Aerometric Data Bank.

-------
           The  two  topics  treated  in this section both relate to



      the relative  precision of  the raw data with respect to the



      methodology employed in  obtaining the measurement.  The first



      topic concerns  the number  of significant figures that should




      be reported while the second deals with values that are below




      the minimum detectable limit.




2.1.  Significant Figures



           The  number of significant figures that are meaningful



      for a particular air quality measurement is limited by the




      methodology employed.  To  use more significant figures than



      is warranted  by the  sensitivity of the analytical procedure



      adds no real  information and can often be misleading.



      Table 1 presents the suggested reporting accuracy for rax-/ data



      for various pollutants.  While the conventions apply to the



      raw data  it is  also  useful to specify the accuracy of geometric



      and annual means.  For simplicity, the general convention is



      that all means  be reported to one more significant digit than



      the raw data.



2.2.  Minimum Detectable Limit




           Some reported pollutant measurements are below the limit



      of detection  for the analytical procedure.  In such cases,



      the reported  number  should be viewed as representing a range



      from zero to  the minimum detectable.  However, in order to



      use such  data in computing annual summary statistics such as

-------
 TABLE 1 -  SUGGESTED REPORTING ACCURACY FOR RAW DATA
                                     Number of Decimal Places





Pollutant                                ug/m       ppm
Suspended Particulate Matter               0



Benzene Soluble Organic Matter             1



Sulfates                                   1



Nitrates                                   1



Ammonium                                   1



Sulfur Dioxide                             0          2



Nitrogen Dioxide                           0          2



Nitric Oxide                        (       0          2



Carbon Monoxide                            1          0



Total oxidants                             0          2



Total Hydrocarbons                         1          1



Ozone                                      0          3



Methane                                    1          1

-------
    geometric means it is convenient to have a convention indi-



    cating what value should be substituted for a measurement




    below the minimum detectable.  As a general rule, each value



    below the minimum detectable is replaced by a value approxi-



    mately equal to one-half the minimum detectable.  Table 2




    indicates selected minimum detectable limits used by the




    National Aerometric Data Bank  (NADB) for various analytical



    methods.  A complete listing may be obtained from the National



    Air Data Branch, EPA, Research Triangle Park, N. C. 27711.



    The mid-point substitution was selected after examining the



    statistical distribution of the data (Nehls and Akland, 1973).



    It should be noted that in comparing data over several years,



    a standard minimum detectable should be used unless it has



    changed by an order of magnitude.



         In preparing summary statistics, if more than 25% of the



    observations are less than the minimum detectable no statistics



    are computed from the data.



3.  CHARACTERISTIC PATTERNS OF AIR QUALITY DATA



         Before summarizing any data, some thought should be given



    to the characteristics of the raw data.  This is particularly



    true of air quality data for which strong seasonal and diurnal



    patterns may effect the interpretation of the data.  For



    example, the maximum hourly oxidant value for a year based on



    4,000 observations could have completely different meanings,



    depending upon whether the observations were made primarily



    during the winter or -the summer.  This section presents

-------
                                       TABLE 2

            MINIMUM DETECTABLE LIMITS FOR SELECTED MEASUREMENT TECHNIQUES
     Pollutant
Collection
 Method
    Analysis Method
Units
  Minimum
Detectable
•Suspended Particulate

Nitrate

Sulfate

Carbon Monoxide

Sulfur Dioxide

Total Oxidants
 Hi-Vol

 Hi-Vol

 Hi-Vol

 Instrumental

 Gas Bubbler

 Instrumental
Gravimetric                 ug/m"

Reduction-Diazo Coupling    ug/irT

                           !
Colorimetric                ug/m"

Nondispensive Infra-Red     mg/m"

West-Gaeke Sulfamic Acid    ug/m"

Colorimetric Neutral KI     ug/m"
            1.0

             .05

             .5

             .575

            5.0

           19.6
            CTi

-------
      examples of soma of these patterns.  The analysis of these



      patterns can frequently be an end in itself since they pro-



      vide insight into the behavior of the pollutant.  7m awareness



      of these patterns also provides a means for screening the data



      for anomolous values.  It should be noted that while the



      following discussion is general in nature, the characteristic



      pattern at a given site is a function of local factors such



      as emissions and meteorology and as a consequence characteristic




      pattern may be specific to that site or locality.



3.1.  Seasonal Patterns



           Figure 1 displays graphs of monthly averages for various



      pollutants at a particular site.  Superimposed on these graphs



      is a smooth curve selected to emphasize the long term trend in



      the data.  Figure 2 displays smoothed curves illustrating the



      seasonal patterns in the data.  The intensity of the seasonal



      pattern for a particular pollutant may vary from site to site



      within an area depending upon factors such as proximity to point



      sources.  A knowledge of the seasonality of a pollutant can



      provide .useful information for interpreting the data since it



      suggests the season in which maximum concentrations would be



      expected.



3.2.  Diurnal Patterns



           In addition to seasonal patterns some pollutants also have



      pronounced diurnal patterns.  These patterns may be due to



      factors such ar. solar radiation, traffic density, etc. which



      influence pollution levels.

-------
             or -,'jMTii:1,;:  ;.\w-.
                          J-O.K VARI
                                                          S AT A PAJVI-ICUL;-.::
                                               I
  2

  2f



  10
  0
                         IM KA-W:I>
             M.;/V;i MIITI.K (?'< i.')
    63 *£4  ' 65 "66  ' 67 '68  ' 69 ' 70 ' 71  ' 72
                                                     sni.riiK IIUIXTIH:
                                                 iNSTHtiMKNTAi. O'::'K'i:TiMrn;u'
                                                    ur./ct.i MI.TI:;; us C)
                                           63
                   ' 64 ' 65  ' 66 ' 67 ' 68   69 70  71  'fH
 300

 200
  50
                       NITRIC OXIDE
                   INSTRUMENTAL COLORIMETRIC
                      UG/CU KtlTER (25 C)
                                       1000

                                        &00

                                        600

                                        400

                                        200

                                         0
      '    '   I
    60  69  70  71
                           OXIDES OK NITROCK.'l
                         INSTRUMENTAL COLORIMi.TKIC
                           UG/CU METER (25 C)
                  72
                                           68  6?  70  71   72
400

300.

200

10_p_

 0
 12!
                 SUSPENDED PARTICULATE
                 HI-VOL GRAVIMETRIC
                  UG/CU METER (25 C)
4MrW-W
v\l^
                      COLOHIMETRIC NEUTRAL KI
                   UG/CU H1JTKR' (25 C)
                                                 25JLJ
-V
            1021
iM
       SB  59^  oO  ol   62  oJ   6-1  6i   CG  67  68
                    TOTAL OXIDANTS
                                                      TOTAL- HXD.IOCAPJJOMS
                                                  INSTRUMENTAL FLAME ION1ZATTON
                                                       UG/CU KETER (25 C)
                                        25f
                                           T5  ' C-l I 65 I 66  TV Tl  f 6'J '  70 i 71 T77

                                                      NITROGI::) DIOXIDE
                                                    INSTRUMENTAL COLORIUL'TI'.IC
                                                     UG/CU KLTilR (25  C)
                                                I
                                                                                    i
                                                                                     I

-------
.  Hl-v.u, i'•!••••.'. I:1. .': !(U'
  ui'iA'u WITH  ('.".>  c)
     5V '  58  ' 59  '  60 '  61 ' 62  T3  '6-1  "65  '66  ' 67  '  68  I 69    '
                                                                                      N::':'i(t:::i.M',M.  t:n:;iM:': :.!-:SIVK  i::i'!<\-i--i n
                                                                                              MI;/CU MK-rrii  (-'5 O
                                                    63 '  64 ' 65  '  66 ' 67  "itf  '  C9 '  VO '  71  '  .2
100
                                SULFUR DIOXIDE
                         INSTRUMENTAL CONDUCTIMETRIC
                              UG/CU MKTEH (25 C)
     63' 64  '55  '  66  ' 6768    69    70   71    72
                                                 200.

                                                 15£

                                                 10JL

                                                  5J1

                                                   0
                                                                    NITROGEN DIOXIDE
                                                               INSTRUMENTAL COLORIMETRIC
                                                                   UG/CU METER  (25  C)
                                                      63 '  64  '  65 '  6.6 '  67  '  68 '  69 '   70  .' '71 '  72
                                TOTAL OXIDANTS
                    INSTRUMENTAL COLORIMETRIC NEUTRAL KI
                              UG/CU METER (25 C)
                                                                             BQJ

                                                                             ,f.nt
      63    64   65    66  ' 6768'  69   ' VO  ' 71'  72
                                                                   OXIDES OF  NITROGEN
                                                                INSTRUMENTAL  COLORIMETRIC
                                                                   OG/CU METER (25 C)
                                                     68  '  69 '  70 '  71  '  'U
1A&S.
 Uii-
  n
                             TOTAL HYDROCARBONS
                        INSTRUMENTAL  FLW1E IONIZATION
                                                                            5_QO
                                                                      NITRIC OXIDE
                                                                INSTRUMENTAL COLORIMETRIC
                                                                   UG/CU W:TER  (25 C)

-------
                                    10
           Table 3 suru'iari xos the 1971 oxidant data for the Downtown




      Los Angelas sites operated by Los /vncjoles Air Pollution Control



     ' District.  The number of times that the national oxidant .stan-



      dard was exceeded is presented by month and hour of the day.



      The marginal totals indicate both the diurnal pattern and the




      seasonal pattern.



3.3.   Frequency Distributions




           One characteristic pattern of air quality data that is



      particularly important becomes apparent after examining some



      frequency distributions.  Many quantities are assumed to have



      a symmetric distribution about the average such as the normal



      distribution.   Figure 3 shows the frequency distribution for



      total suspended particulate data from Philadelphia.  It is



      apparent that  this distribution is not symmetric.  However,



      Figure 4 shows the frequency distribution for the logs of



      this same data.  The distribution is more symmetric and may



      be approximated by a normal curve.  Data having.this property



      is said to be  log-normally distributed and this is a common



      assumption regarding air quality data (Larsen, 1971).



  4.   SUMMARIZING AIR QUALITY DATA



           In prepciring a summary of air quality data,  pne of the



      moot important steps is to determine the purpose of the



      •summary.   The  usual use of these summaries is to indicate



      typical levels and peak levels.   This section discusses



      some: of the basic statistics that can be used for this purpose.

-------
•TABLE  3    NUMBER OF  HOURS ABOVE OXIDANT  STANDARD
           BY MONTH AND  TIME  OF DAY   (1971  DATA)
               DOWNTOWN LOS ANGELES
M12345678. 910
T.-,*J '
?Z3
:V-.R 1 1
A~I> 4
: L. 1 1
Ju:; 129
JI:L 2 13
;:;G ' 28
S::?T 3 6
^C^ ' 2
w s— J. A
:;ov ' .
D~C
11

1
1
6
3
9
19
17
10
7


N
1
4
3
8
4
12
18
16
10
5
1

1
2
4
3
S
4
12
15
16
10
9
1

2
2
4
2
7
3
11
11
7
. 6
6


3
3
3
1
7
1
6
4
3
1
2


TOTAL BY
456789 10 11 MONTH
8
16
12
31 44
1 16
2 'l 65
1 83
1 70
46
31
2
Y
0 {.
IOTAL BY
HOUR 1 10 43 73 82 84 59 31 7 3 3QT

-------
 4.60-4.6?
4.70-4.7S
 4.30=4.8^
 4.90-4.9^
 500-5.f;
 5.10-5.1!
.5.20-5.2';
 5.30-5.3f
  ,40--:
 5.50-5.5-.J
   30-39
  .40-49
   50-59
  "60-69'
  '70-79
   80-89
  ^90-99
 100-109
 110-119
 120-129
 130-139
 140-149
 1-50-159
 160-169
 170-179
 180-189
 ]90-199
 200-209
 210-219
 220-229
 .239-239
.240-249
                                                                                       CD
                                                                                       cr
                                                                                      -o
                                                                                      o
                                                                                      o
                                                                                      •— (
                                                                                      co
                                                                                      -H
                                                                                      PO
                                                                                      I — t
                                                                                      C3
                                                                                      GO
                                                                                      13
10
cr>
to

-------
                                     13
      The first two subsections discuss the treatment of typical

      and peak values.   The third discusses the range of the data.

4.1.   Indicating Typical Values

           This section discusses the arithmetic mean, the median,

      and the geometric mean as indicators of typical values.   The

      arithmetic mean and the median are frequently used in air

      pollution studies' because of certain properties of the log-normal

      distribution.  In choosing the appropriate statistic, the purpo.se

      of the summary must be considered.  While all three may indicate

      typical values, if the purpose of the summary is to compare

      the data to the National Ambient Air Quality Standards,  then

      the standard suggests the appropriate statistic.  A commonly

      used statistic to indicate typical values is the mode.  The

      mode is the value that occurs most frequently.   The use of the

      mode is not discussed here since it is frequently of little

      value in summarizing air quality data.  For example, the mode

      for oxidant could be near the minimum detectable due to low

      values throughout the night.

           Arithmetic Mean

                Given a set of n observations, say X.. , X~, ..., X ,

      the arithmetic mean is simply    — _ 1
                                       x ~ n"
                   n the term "average"  is  used the arithmetic mean

      is  usually what is meant.

-------
                              14
     Modj an


          Ihe median is the middle value of the data.  That


is if the data is ranked in order of magnitude so that


        ... < X  then the median is   X,,,-,     if n is odd,
            —  n                       n+x
                                        T
         +   X   .  i \   if n is even.
            H
             2
          2

          The median is a convenient statistic that is not


influenced as much as the arithmetic mean by changes in the


extremely high or low values of the distribution.


     Gconietrie Mean


          Given a set of n observations, say X.., X_ ... X ,


the geometric mean is  g =  (X,'X_...X ) 'n  .


          Since this probably  is the least  intuitive of the


statistics presented, it is worthwhile to discuss it in


more detail.


          If distribution is symmetric, such as the normal


distribution, then the expected value of the arithmetic mean


and median are identical.  However, for a log-normally


distributed variable, it is the expected value of the geometric


mean that approximates the expected value of the median.


Therefore, since some air pollutants have a distribution that


is approximately log-normal, the geometric ir.ean became used as


a convenient method of summarizing the data and for to till


suspended particulate, the annual standards are expressed as


geometric means.

-------
                7iS an alternate computational formula, it should

      be noted that
                   ,   M                  • . (\   n        ")
           log 9 = £  2Z  log x. or g = EXl')±  SI  log x. S .
                   n  i=l       x           (^  i=l       J

4.2.   Indicating Maximum Values

           As in the previous section, the purpose of the summary

      is a critical factor in determining the appropriate statistic.

      Maximum values may be indicated by listing the maximum and/or

      the second highest value.  The second highest value is important

      since compliance with the short-term air quality standards is

      determined by this value.  However, there are other statistics

      that are useful for indicating maximum values.  The principle

      difficulty with using the second highest value is that it does

      not allow for differences in sample sizes.  For example,  if

      two monitoring devices are side by side and one monitors  every

      day of the year while the other monitors only every sixth day,

      it would be expected that the second high value for the  every

      day device would be higher than the every sixth day device

      even though both monitored the same air.  Table 4 illustrcites

      how the second high value may vary depending upon different

      sampling frequencies based upon total suspended particulate

      data fx-om a Philadelphia site that sampled daily..

           To allow for this dependence upon sample size, various

      percentiles are sometimes used to indicate maximum values.

      For example, the 99th percentile might be used for hourly

      data while the 90th might be appropriiitc for daily measurements.

-------
TABLE 4        MAXIMUM AND SECOND HIGH VALUES  ( PHILADELPHIA-1969)
Sampling Schedule
Everyday
Every Sixth Day
M
1!
II
II
II
Every Fifteenth Day
M
n
n
n
n
n
ii
n
n
11
n
n
n
n
Observations
365
61
61
61
61
61
60
25
25
25
25
25
24
24
24
24
24
24
24
24
24
24
Maximum
325
219
195
244
215
325
239
205
325
239
219
234
201
215
195
133
195
160
244
215
179
238
Second Highest
244
215
171
233
211
234
205
176
207
191
196
165
198
211
183
173
169
154
199
201
171
205

-------
                                  17
      By using a percontilc value, aliov.'unce  is made  for varying



      sampling frequencies from site to site and year to year.



      Table 5 indicates the 90th percentile  for the  sampling



      schedules used in Table 4.



4.3.   Indicators of Spread



           In addition to an indication of typical and peak valuer;,



      it is also desirable to have a measure of how  variable the



      data is.  Did it fluctuate widely or were all  values fairly



      uniform?  The customary statistics for this purpose are either



      the arithmetic standard deviation or the geometric standard



      deviation.  Ranges or perccntiles could also be used depending



      upon the desired use of the summary but they are not discussed,



      The basic formulas for the arithmetic  and the  geometric



      standard deviations are given below.



           Let X1,  X_, ..., X  be a set of n observations.



      Then the arithmetic standard deviation is:


                            	 •?"") i /•?       	  i   «2—  v
                            ^\ <- I JL/ 4^   •    ^^  X   N    Jv •
                           -"N        where x = —   2	   i
                               -I              n   ._,
            -G-  £"
    and the geometric standard deviation  is


                                          1/2
          S9
               = EXP f-  2H  (In X.  -  Ing 2]

                     Ln  i=l       x        J
    where g is the geometric mean.



5.   MAKING INFERENCES FROM AIR QUALITY DATA



         Once the air quality data  has been summarized, it is in a



    convenient form to be examined  so  that  conclusions can be made



    regarding air quality.   At this point the  data is either

-------
         T? r:
         jLi J
GEOMETRIC MEANS, MEDIANS, AND  90TH PERCENTILE VALUES

        FOR SAMPLING DATA OF TABLE 4
Sampling Schedule
       Observations
Goo'.nstric Mean
Median
90th Percentile
Everyday ~ 365
Every Sixth Day • 61
61
61
61
61
60
Every Fifteenth Day 25
25
25
25
25
24
24
24
24
24
" 24
• " 24
24
24
24
102.
99.
95.
113.
107.
106.
34.
. 100.
114.
125.
104.
100.
99.
104.
102.
92.
100.
92 .
104.
107.
94.
£9.
6
8
2
6
2
4
7
2
6
0
o
8
8
4
4
1
n
O
0
6
2
1
6
97
105
93
113
101
105
o /..
Ill
121
130
95
105
90
98
99
95
96
88
97
109
C £
98
171
162
155
188
177
'171
15'0
175
173
1.89
T n •> i— «
•*--'— CD
148
190
177
171
143
• 162
'140
186
173
162
155

-------
                                    19
      extremely useful or extremely dangerous depending upon the
      quality of the  summary.  This section, discusses these inferences
      to illustrate the potential G./in.gers thc\t can-result-from in-
      adequate sur-aaries. -For convenience, the discussion is divided
      into two parts.  The first deals with inferences about a
      particular site whiJe'the second deals with inferences .about
      a region.
5.1.  Inferences About a Particular Site
           This section discusses inferences that can be made about
      a given site from one year's data for a particular pollutant.
      Since any conclusions based upon the data can be no better
      than the data itself, the most important part of the summary
      is to decide if the data gives adequate annual coverage.  This
      relates directly to the previous discussion of characteristic
      patterns.  If an annual average is to be computed from the
      data,-then' it is 'essential that.all portions of the year be
      represented equally.  An examination of the seasonality that
      exists for certain pollutants shows why this is essential.
      As a convenient rule, it may be assumed that if each calendar.
      quarter contains at least 20% of the total observations then
      the sample is adequately balanced.  If this is not the case,
      then a inore appropriate way to determine the annual average is to
      use a weighted mean calculated £is follows:
           (1)  determine the average for each quarter and
           (2)  compute the average of these four quarterly averages.
           While the previous constraint applies to the seasonal balance
      of the sample, it is cilso essential to have a restriction on
      the 'minimum number of--observations that are required1 to compute
      an annual in-ian.  Such constraints are employed in the National
      Aerometric Data Bank system (:;ehls and Akland, 1973) and to
      maintain uniformity, they are repeated here.  For continuous

-------
                              20
measurements at least 75\j of the total possible observations



should be present before summary statistics are calculated.



The exact requirements are given in Table -6.  For intermittent



sampling data, there must be at least five observations



per quarter and if one month has no observations the remaining



two months in that quarter must both have at lecist two obser-



vations.  While these conventions are used in general, it is



of course possible to modify them for' certain explications.



For the most part the general intention of these restrictions



is to ensure that the observations are sufficiently represen-



tative of the entire year to calculate an-annual mean.  For



peak value statistics such as the number of times a certain



value is exceeded the constraint is not essential in'showing•



violations.  For example/ tv/p hourly oxidant values in excess



of the standard is sufficient to show non-compliance even if



there were no other observations that year.  Nevertheless, to



assess the extent of the problem, data sufficient to meet the



requirements for determining a mean x-;ould be advantageous



although for seasonal pollutants it could suffice to summarize



only particular quarters or months.



     In discussing the inferences that can be made from a given



sample, it is worth observing that while the annucil mean can be



either under- or over-estimated the maximum and the second



high values can only be underestimated assuming no •• instrumental



error.  For example,  if a simple., •hypergcor.ietric probability

-------
  TABLE G
SUMMARY CRITERIA FOR CONTINUOUS MEASUREMENTS
   Time Interval
                  Minimum Number of Observations
3-hour running average
8-hour running average
24-hour
Monthly
Quarterly
Yearly
                3 consecutive hourly observations
                6 hourly observations
                18 hourly observations
                21 daily averages
                3 consecutive monthly averages
                9 monthly averages with at  least
                  two monthIv averaces per  ouarter

-------
                                    22
     ;;sodcl is assumed,  Table 7 shows the probability of detecting



     violations of trio  short-term standard as a function of



     saiT.plin;; frequency.   From this table it may be seen that if



    .samples are taken  every sixth day the probability of detecting



     two excursions above the standard is less than 50^ unless the



     site actually exceeds the standard 10 days per year.  This



     illustrates the weaknesses associated with determining maximum



     values on the basis  of intermittent sampling.



          Two possible  solutions to this problem are (1) to



     intensify sampling schedules or (2) to use mathematical



     equations to extrapolate from the data to predict maximum



     values.  At the present time, there is no convenient predictive



   i  formula that can be  applied on a general basis to give sufficiently



     accurate maximum values.  As a guide, the predictive formula



     developed by Larsen  (1971) based on the log-normal distribution



     may be used to determine the possible magnitude of the under-




     estimation due to intermittent sampling.  However, this



     empirical model assumes log-normality and independence and



     should not be used to determine compliance with the standards



     since its predictive accuracy has not been fully documented.



5.2.  Inferences About a Region



          Once conclusions have been made for each site in a region



     the next step is to  draw conclusions concerning the region*  If



     any one of the sites exceeds the NAAQS then the region is not



     in compliance.  It should also be pointed out that the worst

-------
T7vBL£  7         PROBABILITY  OF SELECTING  TWO  OR MORE  DAYS  WHEN  SITE
                                   IS  ABOVE STANDARD
                                   Sampling Frequency - Days per year

        Actual no.
        of excursions             61/365               122/365            183/365
•>
i_
4
6
8
10
' 12
14
16
13
20
22
24
26
.03
.13
.26
.40
.52
.62
.71
.78
.83
.87
.91
.93
.95
.11
.41
.65
.81
.90
.95
.97
.98
.99
.99
.99
.99
.99
.25
.69
.89
.96
.99
.99
.99
.99
.99
.99
.99
.99
.99

-------
site in the  region may Ktill  underestimate  the magnitude of
the air" pol.lviti.on problem.  The  only way  in which a  site may
overestimate the  air pollution problem  is if  it  is not
representative of the air to  which  receptors  are exposed.  There
are guideline documents discussing  this subject.  While it is
relc.tivcly easy to compare the uir  quality  in a  region with
the !'];>J\OS it is not so easy to compare  one  region with another.
For e-xii'uple,  one  region may choose  to concentrate most of its
monitoring efforts at sites having  high pollution potential while
another region may have numerous sites  monitoring background
levels.  Therefore,  extreme caution should  be used if such
comparisons  must  be made and  particular attention should be
given to the placement of monitoring sites.
Some Statistical  Tests
    When making inferences  from  air quality data it  is frequently
necessary to have some objective means  to make judgments.  This
is the point at which statistical inference becomes  useful.  The
previous treatment has used statistics  merely for descriptive
purposes in  order to conveniently summarize the  data.  The
purpose of statistical inference is to  objectively substantiate
generalisations made from the data.  For  this reason, two basic
statistical  tests are discussed.                  '
    While these statistical tests are relatively straight forward,
a certain degree  of caution is required regarding the underlying
assumptions  Lhat  determine their validity.  Since one of thor.o
cissun.pt.ioni;  is particularly important in  applications dealing

-------
with air quality data, it will bo discussed in detail.
    In statistics, it is commonly assumed that the data to be
analyzed is a random sample-, of all the data and that the
measurements' are independent.  While this may be approximately'
true, for intermittent 'data collected on a sampling scheme com-
parable to that employed by the NASN, it may not be true for
all samples.  For the most part, those statistical assumptions
are merely a mathematical formulation of'common sense ideas.
Certainly, if data were only collected on Sundays, it would
not be expected',that the average of these numbers is truely
representative of the annual average.  Sampling schedules that
only monitor certain days of the. week resxilt in non-random
samples and their degree of usefulness is inherently limited.
The problem of independence is somewhat, more subtle.  For
example, successive hourly oxidant measurements are not in-
dependent.  While the concept of statistical independence
may be clearly defined in mathematical terms, it is possible
to present an intuitive notion of what it entails.  Two
numbers may be thought of as being independent if knowing
one of the numbers does not help in guessing what the other
number is.  The classical example of this is rolling dice in
which knowing'what number occurred on one die does not improve
a guess of what number occurred on the other.  With this in
mind, it is apparent that knowing one hourly oxidant value
helps in guessing what the next hourly value will be.  It

-------
                                    26
      should be notc.cl that it 'is not necessary that it make the
      guess a certainty-only that it improve the chances of guessing
     . correctly.      •'.•.•.           •
          With the ideas' of randomness and independence in mind,  it
      is possible to present two statistical techniques that are
      generally useful in practice.   The first test is commonly known
      as student's t-test and is useful for examining the mean.  The
      second test.is the non-parametric quantile test and despite
      the rather elegant name it is a convenient test for the median
      and other percentiles and is very easy to use.
6.1.   Student's t-test                          .
          The Student's t-test is a commonly, used statistical test for
      data that may be assumed to be normally distributed.  As mentioned
      earlier, air pollution is frequently assumed to be log-normally
      distributed so that the t-test may be employed to examine the
     . logarithms of the data.  The application of this technique to
      determine confidence intervals for annual goemetric means has
      been discussed by Hunt (1972)  and is briefly treated here.   This
      present discussion examines construction of a confidence in-
      terval for an annual mean.  Extensions to comparisons of two
      means may also be performed but are not treated here since the,
     . approach is almost Identical and can be found in basic statistical
      texts.  More general tests concerning trends at .a site are ex-
      amined in the guideline document for trend analysis.
          The basic application ic that a cot of data from an intermittent
      monitoring device has been obtained.  This data has been used
      to determine the annual, geometric mean.  Since this data re-

-------
                               21
presents only  a  fraction of  the  total number of days in the year,
the question arises  us  to how close the nioun of the-, data in to
the actual  annual  raean.   The statistical technique employed for
this purpose is  the  confidence interval so that a probability
statement may  be made regarding  the range of the true annual
ir,ean.
    To calculate a 95^  confidence: interval for the geometric
mean, the interval is first  constructed for the arithmetic moan
of the logarithms.  To  do this,  the following calculations
are nee es s ary:
               1
    Let >:,   =: n E  log x.    , where n is the sample size
            g     1=1
     3t slog
              = fn
1/2
                        n-1
                     s.
    Let d =  t,   ,0   — ••-$• (1-|J)JV'6  where t,  „/0 is obtained
              l-a/2   y/jp     N              l-a/2
    from a table  for Stxident's  t-test where 1-ct is the con-
    fidence  level and N is the  possible number of samples
    e.g. 365 for  daily  samples.
Then the lower  and  upper confidence intervals' for the geometric
mean, denoted as  L  and  U respectively, are given by

    L -- EXPCx.,    -  d)
              log

and U = EXP(x3    +  d) .

    It should be  noted  that in  the above formulas the finite
correction factor, (!-") ,  was used since it is asr.vniuid that the

-------
                                    28
      population size is finite rather than infinite.   For  example,



      in considering daily measurements it is assumed  that  the



      population size is 3G5,  i.e.  the total immber of days in  the



      year.



6.2.   Non-Parametric Quantile  Test



          In discussing thc't-test  it was  pointed out  that  it is



      necessary to assume that the  logarithms of the air pollution



      measurements are normally distributed.  In some  cases,  it may



      not be desirable to make this assumption.   For example, an



      examination of the data  may show that such an assumption  is



      unwarranted.  For such cases, non-parametric statistical  tests



      are appropriate since they do not require  any assumptions



      regarding the form of the underlying distribution. Moreover,



      non-parametric tests are frequently  quite  easy to employ  since



      many of the calculations are  relatively simple.   A variety



      of non-parametric tests  are available.  A  more detailed des-



     . cription of the test discussed here  is available in the text



      by-Conover (1971).



          Quantile is a.more general term  than percentile.   For the



      present discussion,  the  test  is used to examine  the median  but



      it may also be applied to any percentiles  or quantiles,  It is



      also assumed that there  are more than 20 observations since



      this is generally true for air quality problems  and reduces



      the need for tables.              :     •   .

-------
                                   29
        Let x ,, x~, ..., x  bo a sample of air quality measurements





    and suppose it is desired to tost if the annual median is



    greater than a specific value, say s.




        Then it is only necessary to calculate the following two



    values:



        T - the number of sample values less than or equal to s
    eind t ~ pn + w  ./ np(l-p)  , where n is the sample size p is




            the quantile value and w  is the a quantile of a standard



            normal random variable.



        For te.sts at the .05 level w  is - 1.645.



        For tests concerning the median the quantile value is.  .5



        so the above formula becomes
        t=.5n- 1.645   /.25n
          = ,5n - .822  J n



        If T is less than t then the conclusion may be stated that



    "the median is greater than s" and that the result was obtained



    by employing the quantile test "at the 5% level."




7.  Basic Means of Obtaining Air Quality Data



        One station continuously monitoring oxidant can produce



    8,760 observations.  Therefore, considerable caution should



    be exercised when requesting air quality data since there is



    ci considerable risk of being inundated with unnecessary numbers.



    Usually when questions arise concerning air quality, the answer



    Ttiay be given in terras of summary statistics and it is not necessary



    to review the raw data.  Certain basic sources include the various

-------
                               30






periodic reports from State and  local agencies as well as




F.PA's reports on the NASN and CAMP monitoring efforts.




Overviev; reports with extensive  appendices  such as Thc_Jiatig_nr>l



7ar Monitoring Program;  -AirQuality and Emission Trends Annual



Report, are also available.




     The National  Aorometric  Data Bah3:  provides many



summary  files  that may  be  accessed by  time  sharing  terminals.



In addition, the NADB provides  printouts  containing general




information  that may be'easily .looked  up  with no  need to



access the computer.  Table  8  lists frequent questions and a



readily  available  source«,

-------
TABLE 8
NADB OUTPUT FOR COMMON QUESTIONS OK AIR QUALITY
ivhat data is available nationwide for a
     particular pollutant?
                                                          Source
                                        Inventory by pollutant
What c7.ata is available for a particular
     geographical region?
                                        Inventory by site
vrhat was maximum value at a site (annual) ?
                                        Any inventory
What was mean value at a site (annual)?
                                        Any inventory -
                                           if valid year
How many observations (annual)?
                                        Any inventory
Status of a site with respect to NAAQS?
Frequency Distribution
                                        Time Sharing Option  (TSO)
Quarterly or monthly data
                                        Time Sharing Option
Raw data
                                        Time Sharing Option
Description of the site such as UTM coordi-
     nates, county, operating agency, etc.
                                        Site File

-------
                               30






periodic reports  from  State  and  local  agencies  as  well  as




E.PA's reports on  the NASM and  CAMP monitoring efforts.



Overview reports  with  extensive  appendices  such as The  National




7-.ir Monitoring Program;  Air Quality and  E m i s s ion  Trends _Anmicil



Repp_r_t, are also  available.




      The National Acroinotric Data Bank provider, many



summary files  that may be  accessed by  time  sharing terminals.



In addition,  the  N7vDB  provides printouts  containing general




information  that  may bo easily looked  np  with  no need  to



access  the computer.   Table  8  lists  frequent questions  and a




readily available source.

-------
GUIDELINE  SERIES
          OAQPS NO.  /
    DESIGNATION OF CRITERIA POLLUTANT
   ANALYTICAL METHODS AS ACCEPTABLE/NOT
        ACCEPTABLE FOR PURPOSES OF
            DATA ANALYSIS
   US. ENVIRONMENTAL PROTECTION AGENCY
    Office of Air Quality Planning and Standards

      Research Triangle Park, North Carolina

-------
                .  UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
                      Office of Air Quality  Planning  and Standards
                      Research  Triangle  Park,  North Carolina 27711

   3JECT:  Designation  of  Criteria Pollutant  Analytical           DATE:    8  ^ *l37'1
          Methods  as Acceptable/Not Acceptable for
 FROM-     Purposes of  Data  Analysis

          Robert E. Neliga.n,  Director  .   •-   /.-(.• y^--•
          Monitoring and  Data Analysis Division

          Surveillance and  Analysis Division Directors, Region I-X

               Enclosed is  a  draft  copy  of a guideline document dealing with the
          acceptability of  commonly used  air pollutant analytical methods.  This
          guideline has been  prepared cooperatively with the Quality Assurance
          and  Environmental  Morn'toring Laboratory of  the NERC-PJP.

               We  have categorized  the various analytical methods into three
          groupings:   acceptable, tentatively acceptable and unacceptable.  The
          Regional Offices  should work with  the States in ensuring that the
          "unacceptable"  methods  are replaced with acceptable ones as soon as
          possible.  All  "tentatively acceptable" methods are instrumental,, and
          they could be used  for  five years  (to allow time to switch to acceptable
          methods) or  until  equivalency  testing enables us to change their status
          to either acceptable  or unacceptable.  The  data from unacceptable methods
          will _no  longer  be  stored  in the data bank after July I, 1974.....        "~~

               The guideline  also contains a listing  of the number of monitoring
          sites in each State for each of the methods and an Appendix which
          contains an  explanation of why  a method has been classified unacceptable.

               At  this time,  we would like to  have any comments regarding this
          document as  well  as the name of a  person in your office to whom questions
          regarding implementation  of this policy can be directed.  Please forward
          your comments and  the  name of your office representative to
          Mr.  William  Cox (919/688-8312), by March 11, 1974.

          Enclosure

          cc:   Air and Water  Division Directors
                Region I-X
               G.  Ozolins
               D.  Shearer
               T.  Mauser
               L.  Bockh
               B.  Steigerwald
               D.  Goodwin
               J.  Padgett
               J.  Schueneman
               J.  Hammer!e
               H.  Slater
               G.  Morgan
EPA Form 1320-6 (Rev. 6-72)

-------
                                                      DRAFT
             DESIGNATION OF CRITERIA POLLUTANT
            ANALYTICAL METHODS AS ACCEPTABLE/NOT
                  ACCEPTABLE FOR PURPOSES OF
                        DATA ANALYSIS
                      February 1974
                   OAQPS Number 1.2 - 018
          Monitoring and Data Analysis Division
      Office of Air Quality Planning and Standards
                           and
Quality Assurance; and Environmental Monitoring Laboratory
         National Environrnenta.1 Research Center
         Research Triangle Park, North Carolina

-------
     Designation of Criteria Pollutant Analytical
       Methods as Acceptable/Not Acceptable for
              Purposes of Data Analysis


    It is well known to all who analyze criteria pollutants
that some procedures and methods are better than others.
Because important decisions, such as compliance achieve-
ments and State Implementation Plan (SIP) revisions, are
based on data derived from these methods, it is imperative
that only the best available data be xised.  In order to
restrict the proliferation of bad data, we have decided
to categorize the ability of analytical methods to yield
data acceptable for our needs.  This guideline summarizes
our thinking on the acceptability of analytical methods
presently being used.  As the equivalency program comes
into practice, we will add to, or change, the set of ac-
ceptable methods, but following is our current thinking
on the matter.
    Table I lists all those analytical methods, data for
which were submitted by the States in 1972.  We have ranked
the individual methods as "acceptable" tentatively ac-
ceptable" and "not acceptable."  Data from those classified
"acceptable" will be used for trend analyses, compliance
calculations, summaries, etc.  Data from those ranked "not
acceptable" will not be used after July 31, 1974, and will
not.be entered into the NADB after that date.  Data from
those methods labeled "tentatively acceptable" will be used
until mid-1979.  These methods are all instrumental methods,
and since we judge the useful lifetime of air pollution in-
struments to be five years, this allows a time period in
which to amortize and purchase "acceptable" instrumentation.
It is possible that some of these tentatively acceptable
methods may be changed to the acceptable category upon
completion of successful equivalency testing.   (Note that

-------
                           -2-
all instruments may not be on the list at this time - they
will appear on revised lists as a result of having passed
the tests in the equivalency program).
    Si.nce only data from those methods ranked "acceptable"
will be used for air quality trend analyses and compliance
with NAAQS, it would be prudent for those states and local
agencies which are presently using "not acceptable" methods
to change their practices.  Otherwise, in 'the near future,
there will be no acceptable data from those agencies on
which to make judgiaents of their progress.  Six months
should be sufficient time for laboratory personnel to be-
come proficient with new "acceptable" manual methods, thus
the date, July 31, 1974, after which only data from these
methods will be entered into the NADB.
    In improving the data base on which important and costly
decisions are made, the Regional Offices thus have the key
role.  These Offices must

    1.  see that "acceptable" methods are adopted as soon
as possible in accordance with the time-scale discussed
herein

    2.  see that the states spend their money only for
"acceptable" instrumentation.

    To help the Regional Offices identify which states re-
ported data by which method in 1972, we have included Table II,
a printout of the data from which Table I was prepared.  Note
that the printout is by pollutant code and method.
    As a further aid, we have attached. 7\ppendix A, an extract
from a forthcoming document "A Description of the Analytical
Techniques and Associated SAROAD Method Codes Used in Storing
Data in tho National Air Data Bank" OAQPS 1.2-017.  This
will help decide which analytical method an agency is
actually u-ing and t.hc SAROAD number-;;,.;: thod code under v:hir;n
tho data should be submitted to NAD.o.

-------
                           -3-
    Lastly, there is attached /Appendix B, a short paragraph,
for each of the "not acceptable" and "tentatively acceptable"
methods, giving our reasons for ranking them in these cate-
gories.

-------
                                               •  '        TABLE 1
                                           1972 .Pollutant-Method-r.tations Summary
I
•to
ollutant Code
 IP  11101 91
!0   42101 11
          12
          21
Method
Hi-Vol
NDirt
Coulomctrlc
Flame lonization
                                                    Ho.  of
                                                   Stations
Percent
of Total
  100
   99
    0
    1
  100
Acceptable
    X
    X
Tentatively
Acceptable
   Not
Acceptable
I
    4.2401 11       Colorimetric
          13       Conductimetrie
          14       Coulometric
          15       Autometer
          16       Flame Photometric
          31       Hydrogen Peroxide
          33       Sequential Conductimetric
          91       West-Gaeke-sulfamic acid
          92    *  West-Gaeke Bubbler
          93       Conductimotric Bubbler

    42602 11       Colorimetric
          12       Colorimotric
          13       Coulometric
          14       Chemiluminescence
          71       J-H Bubbler (orifice)
          72       Saltzman
          91       J-H Bubbler (frit)
          94       Sodium Arscnite
          95       TEA
          96       TGS
 lal Ox 44101
             11    Alkaline KI Instrumental
             13    Coulometric
             14    Keut KI Colorimetric
             15    Coulometric
             51    Phenolpht.halin
             81    Alkaline KI Bubbler
             82    Ferrous Oxidation
         44201 11    Chemiluroinescence
               13    Coulomftric
68
80
76
1
12
38
3
1040
45
2
1365
110
15
5
36
11
11
BIG
28
1032
49
10
75
13
= 5
64
85
301
62
1
63
5
7
6
0
0
3
0
76
3
0
100
12
1
0
3
1
1
79
3
100
16
3
25
4
2
22
28
100
99
1
100




X


X



X
X
X
X






X





X


                                                                                                   X
                                                                                                   X
                                                                                                   X
                                                                                                   X

                                                                                                   X
                                                                                                   X
                                                                                                   X
                                                                                                   X
                                                                                                   X
                                                                                                                  X
                                                                                                                  X
                                                                                                                   X
                                                                                                                   X
                                                                                                                   X
                                                                                                                   X
                                                                                                                   X
                                                                                                                   X
                                if I'1

-------
«.".i[ ' ' ' "•' .
til:
H» ' • v..
1
"TATE
II T A T E
STAtt
§TATF
JTATE
(TATF
•TATE
STATE
ITATE
STATE "
•TATE
K-ATE
,., F
|r ATE
STATE
ITATE
KATE"
ATF
• ATE
STA.TF
|ATE
STATE
3§ATE'"
S»ATE
STATE
r-^-_^__-,-__^_^._,^
C.L J\T
ccu.NT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT 	
COUNT
COUNT"
COUNT" "
COUNT""'"
COUNT
COUNT ""
COUNT
COUNT""
" COUNT '
COUNT
COUNT".""
COUNT'
COUNT""
COUNT
COUNT "
COUNT
HI 01
11 Ml
111J1
1 i 1 0 1
11101
11101'"
11101"
11101
11101
11101
11101
"'Tiiol
" TTioi ~ 	
""ifibi
11101
111 01
~ 11 101 ,
i i i o i
"11 101
uior
lliui"
11101
1 1 I 0 1
1U01
r'=TH ':'.•' ';". : ...'.•;"".' ....', NUMBER OF ' !:- ..' '.'. ',-. ' 'V ' ., -...;•:'
,T)E • SITES '
91
91
91
91
91
91
91
91
"91
9 1 "
91
91
91
91
91
9 1
91
91
91
91
9f
9)
91
ALABAMA
ALASKA
A^I/QNA
AP KANSAS
CALI FOPNIA
CPIORADO
CONNECTICUT
OELAWARE
DIST COLUMBIA
FLORIDA
GEORGIA
'HA WAI I 	 ""
'IDAHO 	
ILLINOIS
INDIANA "
IOWA
KANSAS
KENTUCKY
LOUISIANA
MAINE 	
MARYLAND •
MASSACHUSETTS
MICHIGAN
MISSISSIPPI
63 '
19 .
33
32
19
69
26
16
45
31
30
54
128
30
59
90
12
7
85
52
109
59
2
\

-------
TABLE II

STAT =
STATf-
STATF
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATF
S ,TE
STATF
STATE
STATE
STATE
STATE
STATE
STATF
STATE
STATE
STATT
STATF
STATF
1
COUNT
CUUMT
. COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
CCUNT
COUMT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
CO! 'NT
COUNT
CPU-NT
CG'.m
COUNT
CO'iM
C'.J'P, T
V_* • ) t~
11101
11101
1110 I
11101
11101
nioi
11101
1.11. 31
11 101
11101
1110 1
11101
11101
11101
11 10 I
1 1 1 0 1
11 101
11101
11101
11101
11101
111') 1
lil Jl
11 101'
r •' r T i -.
CMIH
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91
91

M'ISSOJRI
MONTANA
NEBRASKA
NEVADA
i\E'.-/ HAMPSHIRE
NEW JERSEY
NEW MEXICO
NFK YORK
NORTH CAROLINA
NORTH DAKOTA
OHIO
OKLAHOMA
OP-FGON
PEHMSYLVAHIA
PUERTO PICO
RHODE ISLAND
SOUTH CAROLINA
SOUTH DAKOTA
TENNESSEE
TEXAS
.UTAH
VC-MfJ'JT
V I P fi I Nl I A
•A-ASMINGTCN
NUMBER OF
SITES 1
49
2
36
41
26
79
28
233
199
16
137
95
48
105
5
23
75
	 2
98
192
8
2
122
57

-------
TABLE II
1
STATE.
JAJE
STATE
WATT
MjATE
POLUTCOD
SATE
STATE
ATE
IATE
ATE
• ATE
STATE
ATE
yATE
P-ATE
•FATE
STATE
JUTE
f'/vTE
.ATE
•TATF
STATE
IT A T F
S T ' T E'

CLIMNT
COUNT
C.UUNT
COUf4T
CCVJNT
COM NT
COUNT
CCJUMT
COUNT
COUNT
COUNT
COUNT
COUNJT
COUNT
COU^T
COUNT
COUNT
COUNT
COUNT
COUNT
COUi\.T
CC Jl^T
CCUMT
CiVJ-JT
C-O'i^iT
PuLUJTANT
CPHE c
lllul
"111 61
11 101
IHOl
lliQi
11 10 1
"42101
42101
42101
42101
___.__.._. 	
42101
42101
42101
42101
42101
4?i01
42101
"42101
.._ -^21cj|
42101
4 ? 1 0 I
~" 42 1, H
42101 ""
4?10l
'TM
•i'.)G
01
n ' •
91
9l"
91
•ii
11 '
11
11
11
1 1 	
11
11
11
11
11
11
11
11
11 "
11
11
11
11
1 1

.WEST VIPGINM
V,1 1 SCO N.SIM
"WYOMING
GUAM
VIRGIN ISLANDS
ALABAMA
ALASKA
ARIZONA
CALIFORNIA
"COLnRADh
OIST COLUMBIA
FLORIDA
GEORGIA
HAWAII
ILLINOIS
INDIANA
IOWA
KANSAS 	
KENTUCKY "
LOUIS I ANA
MARYLAND
MASS \OIUSETTS
MICHIGAN •
••4 I .V^- SOT A
NUMBER OF • . '
SITES .
39
7 : ' *• /' •
^
11
4
2828
2
1
3
51
1
2
6
2
1
1
3
2
5
	 7'"
3
19
5
3
3

-------
                      -'    •     '
TABLE II
f
\
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
S,,.TE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
POLUTCOn
STATE
PPLUTCfK)
STATE
rTL'.rCOi)

CO'JMT
ceo .T
COMMT-
CC'.INT
COUNT
Cp'.MT
CCU NT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
CC'H NT
CO.J-,T
C^,.:T
ctn?
42101
42101
42101
421J1
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
42101
A 2 I 0 1
coot
ii .
n
11
n
ii
11
11
11
11
11
11
11
ii
11
1 1
11
11
11
11
11
12
12
21
21

VlSS^I
ME^AS'A ' :
NEVADA
!!?'•) JERSEY
Hc\i MEXICO
S-'EW ViYtK.
NCMTH CAROLINA
OHIO
OKLAHOMA
OREGON
PENNSYLVANIA
RHODE ISLAND
TENNESSEE
TEXAS
UTAH
VIP-GINIA
WASHINGTON
WEST VIRGINIA '
WISCONSIN

OHIO

KENTUCKY •.

NUMBER OF
SITES '
10
i
i
22
1
13
2
13
4
2
2
2
4
1
4
9
.10
1
1
223
i
1
2
2

-------
TABLE II
•
STATfr
STATE
STATE
l
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE "
STATE
STATE
STAfE
STATE
IPOLUTCOD
STATE
I
STATE
(STATE
r
STATE
1
PATE
STATE
STATE
UATE
1
S"" ' TF

COUNT
COUNT
COUNT

COUNT
COUNT
COUNT
COUNT "~
COUNT :"
COUNT
COJNT
"COUNT'
COUNT
COUNT
"COUNT""
COUNT ""
COUNT""
COUNT"""

COUNT
CO I /NT

COUNJ

COUNT
COUNT
COUNT
COUNT
crn.'Ni' "
PULUTAXT
COOK
42401
42401
42401

42401
42401
42401
42401
42401
~ "42401
42401
42401
42401
42401
~4240i "
~ 42401"
«Vo~
42401

42401
42401

~" 42401 ~

42401
42401
42401
42401
42401
"i'TH
11
i i
11

H
11
...........
H
11
„...
11
il
11
11
~ "i 1-
11
11
13

13
13

"""13

13
13
U
13
13
NU.MDER
SITES
AKIZ'JNA
COL OS ADO
DELAWARE

DIST COLUMBIA
FLORIDA
H. II NO IS
KENTUCKY
MARYLAND
"MASSACHUSETTS 	 "
"MISSOUR'I 	
NEW JERSEY
NEW YORK
" OHIO 	
' PENNSYLVANIA
WASHINGTON
- 	 	 -
ARIZONA

"CALIFORNIA
COLORADO

' CONNECTICUT

DELAWARE
">IST COLUMBIA
FLORIDA
ILLINOIS
INDIANA '
°F . . ' i
2
1
6

2
3
1
5
1
4
5
22
7
4
4
1
68
2

18
1

1

7
2
1
1
8


-------
"TABLE II

STATE
STATE
STA'E
STAT?
STATE
STATE
STATF-
STATE
STATE
POLUTCOD
STATE
ST "E
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATF
STATF
STATE
STATE
STATE

COUNT
COUNT
COUNT
COUNT
COU^T
COUNT
COUNT
Cfl'JN'T
COUNT
COUNT.
COUNT
COUNT
COJNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT'
COUNT
CCUMT
COUNT
COUNT
P!:LtUT.A-
CHOE
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
::F CO™'
o
13
13
.. ^
13
13
13
13
13
13
14
14
14
14
14
14
14
14
14
14
14
14
14
14

••MARYLAND
MI YVrSOT A
MISSOURI
NEW YORK
OHIO
OREGON
PENNSYLVANIA
VIRGINIA
WASHINGTON

ALABAMA
ARIZONA
DIST COLUMBIA
FLORIDA
GEORGIA
INDIANA
KANSAS
KENTUCKY
MASSACHUSETTS
MICHIGAN
MINNESOTA
MISSOURI
NEW Yfm
\iV.TH CAROLINA
NUMBER OF
SITES -1 -.
.12
2
2
1
7
2
2
2
9
80
2
8
2
2
2
4
3
6
2
22
4
1
12
1

-------
••':•*:.-•'• '!;.'-.-*::v--..^:.:^;^:.-v;. -.'.••••'w-^••:•?••*•  .-•.••..•-•r••*-.•>•-.-;:  ,y  >'...*. :,-^^;„-"?ir'-^^-r^
... -• >•;,  , •.•..o:-;v^".'-*--rt -'^"'."•:« '>V ,x-.'~   ,,':  '••^  • 's': ..^5:, '-\ ^'-"^4? «??>,?rf$ "-5**$!^
                           TABLE  II
POLLUTANT MFTH
Cf3Df COUf
"TATE
•TATE
STATE
JoiuTcan
^TATE
^•OLUTCOiJ
•TATE
STATE
• OLUTCOO
"STATE 	
I j fir. an
MTATE
POLUTCOD
•TATE
STATE
•TATE
(TATE
.TATE
•TATE
ST'ATF
JTATE
(T A T E
TATE
• ,»TE
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
CCU NT

COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
CC'J'JT
COUNT
42401
««»
42401
42401
"42401
42401
42401 "~"
42401
42401
ir^cH
42401
42401
42401
~ 42401" "
42401

42401
"~42401
4240"l 	
	 42401
42401
	 42401
42401
42401
42401
14
1 4
14
14
.14
15
15
16
16
•l'6~
3 r~
31
3?
33
91
91
91
91
91
91
91
yi
91
51
. ; . . . NUI4BER (JF
SITES
OH I 0
PENNSYLVANIA
TENNESSEE
VIRGINIA

" TEN.NtSSEE

MARYLAND.
VIRGINIA
	 • • • • • •
"NEW YORK
MISSOURI

ALABAMA
ALASKA 	 "
ARIZONA
ARKANSAS
CALIFORNIA
' CHIOS ADO 	
CONNECTICUT'
HE LA WARP
01 SF COLUf-'HIA
F LURID A
'GEUKC.IA
1
1
1
2
76
1
1
11 .
1
12
38
38
3
	 3 " 	
13
7
2
16
'*
4
3
2
34
13


-------
TABLE
/
STATF.
STATF
STATE
STATE
STATF
STATE
STATE
STATb
STATF
STATF
STATE
S TE
STATE
STATf-
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STAT!-

CO'.INT
COU'lT
COUNT
COUNT
COUNT
COUNT
COUNT
COM NT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUiNT
CHJVT
CO' INT
CPiPIT
PCLL'lTA'iT
C.'/L)L
4?AOl
42401
^2401
<»?4J1
..^2^01
42'tOl
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
42401
47401
42401
424-.U
'4 r T H
cc:-r-
91
91
Qi
(il
.91
91
91
91
91
91
9 I
91
91
9i
91
91
91
91
91
91
91
91
91
91

HA-.wUI
Il.LI.NGIS
INDIANA
IOWA
KANSAS
KENTUCKY
LOUISIANA
MA I. "It
MAP YL AND
MASSACHUSETTS
MICHIGAN
MINNESOTA
MISSISSIPPI
MISSOURI
MONTANA
NEPPASKA
NEVADA
NEW HAMPSHIRE
NEW JERSEY
s
NEW MEXICO
NEW YORK
NOXTH C^hOl. IN 4
f)Hi:j
OKLAHOMA
NUMBER OF
SITES
12
38
66
2
30
98
17
6 '
49
53
24
id
2
4
1
4
3
4
8
a
34
156
67
27

-------
                                  •* .;   ,  . ,,.,,,.». .-,. ^

                                      ' »i*\     »•*   **
                                     ,'» ' • '    •-'..."
'T.'.BLE  II
                                                                              ,  1  > •*'. -J  ,»fl

t, 	 	 	
..
•1
TATE
STATE
BTATF
• TATE
STATP
BTATE
STATE
•TATE.
CATF
ATE
•TATE
STATE
1 e
KATE
ATE"
•ATE
" POLUTCOD
|ATE
STATE
MLUTCOD
MATE
POl'JTCOO
<|ATE
STATE
sB'T




mm
COUNT
COU'IT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT '
COUNT
COUNT
COUNT
COUNT


"
r)cl)n';*'JT
' 42401
42401
42401
42401
42401
42401
42401
42401
42401
42401 "
42401
42401
42401
42401
"42401
4240 i'~~
42401
"42401
" 42401
42401
42401
42602
42602
42602



'•'frT-l
.1
•n
91
91
91
»i
91
~ 9"i
91
91
91
91
91
9i
91
91
- 9l
92
92
92
93
93
11
U
11




r;-rr,~N
Pt-'N'.'SYLVAiNI A
PUERTO F ICU
RHODE ISLAND
SOUTH CAROLINA
SOUTH DAKOTA
TtNNtSSEE
TEXAS
UTAH
VIRGINIA
"WASHINGTON
WEST VIRGINIA"
WISCONSIN
K'YOMING
GUAM
VIRGIN ISLANDS

FLORIDA
MASSACHUSETTS
INDIAN*

A L A n A M A
ARIZONA
CAL I FORMA

1

_. ,_. ;T. — t_
-------


STATE
STATF
STATE
STATF
STATE
STATF
STATE
STATE
STATE
STATE
STATF
S' •'£
STATE
STATE
STATE
STATE
STATE
STATE
STATF
POL'JTCOD
STATE
STATF
STATE
STATF


COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
• . TA13L
P ILLUTANT
42602
42602
4?602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
4?602
42602
<+2602
•K 11
cm
1 1
ii
11
11
11
ii
11
11
11
11
11
11
u
u
ii
11
u
11
u
n
12
12
12
12


•«r...lfcr!C.jT
I) 1ST COLUMBIA
FLCPIOA
GEORGIA
KENTUCKY
MAI'Jfl-
MARYLAND
MASSACHUSETTS
MINNESOTA
MISSOURI
NEVADA
NEW YORK
l\!ORTH CAROLINA
UH I U
OKLAHOMA
OREGON
PENNSYLVANIA;
TENNESSEE
VIRGINIA

COLORADO
01 ST CJLUM3I A
ILLINOIS
yiSSn'JM

NUMBER OF
SITES
,
1
4
1
8
1
6
1 .
1
8
1
13
1
2
1
1
1
1
2
no.
1
1
1
1

-------
TABLE II

fT 1 M
.,,,,
KT/UE
STATE
ITATE
POL'JTCOD
ft TATE
(TATE
TATE
ftTATE
POLUTCOD
1 'r.
TATF
STATE
ITATE
* T
pr
C >\i \ T
CC;J\T
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT 	
COUNT
'COUNT
COUNT'
COUNT
c uu NT"
ecu N'T" 	
COUNT
"COUNT

COUNT
'COUNT 	
COUNT
COUNT
CO. /NT
CU'JNT
C'.J-.'NT
CLVJNT
CC;-:NT
HLUTA'JT
"i2'>02
42602
«602
42602
«"0.
42602
42602
42602
42602
42602"
42632
42602 	
42602
42602""" 	
42602
42602

42602
42602
42602 	
42602"
4 2 60 2
42602
42602
4? ',02
42^02
',« f T f j
en;);:
12
12
12
12
12
12
13
13 '
13
"13 "
1 3 " "
14
14
14
14
14

14
14
14
14
14
14
14
14
14

NF -.' .JcPShY
UH I U
Pfcf.NSYLVANIA
KH'DDJ: ISLAND
VIRGINIA

KANSAS
MINNESOTA
NEVADA
TENNESSEE

ARIZONA
COLQ PA DC-
CONNECT I CUT
DIST COLUMBIA
"ILLINOIS

INDIANA
I QUA
'KENTUCKY
KARYLANO
MASSACHUSETTS
MINNESOTA
MISsr-jKi
r-; E R '-. f- s •< A
':«:« MEXICO
NUMBER OF
SITES
5
1
1
2
2
15
2
1
1
1
5
1
1
2
2

" 1
1
3
1
1
1
2
1
1

-------
TABLE II
, POLL 'JT AM '1KTH
cnur cnoe '
STATE
ST/.TF
.STATF
_ STATE
STATE
STATE
PDLUTCOO
STATE
POLUTCOO
STATE
POLUTCOO
s re
STATE
STATE
STATE
STATE
STATE
STATE
STATF
STATF
STATE
STATE
STATE
STATE

COUNT
COUNT
COUNT _
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COU.NT
COUNT.
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT

42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602

14
1'+
1*
14
14
14
14
71
71
72
72
91
91
91
91
91
91
91
91
91
91
91
91
91

NEW YPrfK
OHIO
PENNSYLVANIA
_.. TtXAS
UTAH
VIRGINIA

MINNESOTA

INDIANA
ALABAMA
ALASKA
ARIZONA
ARKANSAS
CALI FORNIA
COLORADO
CONNECTICUT
DELAWARE
01 ST COLUMBIA
FLbKlDA
GEORGIA
HAW A I I
ILLINOIS
•' -'•'
2-*''
NUMBER OF .
SITES
2
. 5
5
2
I
2
36
11
11
11
11
13
1
5
2
16
2
4
3
2
22
13
11
4
/
                                      V

-------

'•TATE
STATE
(TATF
(T.ATE
TATE
•TATE
STATE
^-
ATE
f" "ATE
ATE
•"ATE
STATE
ITATE
STATE
ATE
MATE
STATE
"j| AT E
STATE
IATF
SJATE
^ATE
s- Tr

" COUNT
COUNT
'COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
• COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT'
COUNT
. COUNT
"CO'. INT
" CO! 'NT
rnnt
"42602
42602
	 42602
42602"
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
	 42602
42602
42602
42602
42602
426 J2
42602
r n p L
VI
""""94 ;
Si
91
91
91
91
'"""" 91
91
91
91
9 i
91
91
91
91
91 ~
"""91
91
91
'91

' IOWA
KANSAS
KbNTUCKY
LOUI SI ANA
MAINE
MARYLAND
MASSACHUSETTS
MICHIGAN
'MINNESOTA
MISSISSIPPI
MISSOURI
MONTANA
NEBRASKA
NEW HAMPSHIRE
NEW JERSEY
NEW MEXICO
NpW YORK
NORTH CAROLINA
' OHIO '
GKLAHDMA
JREGbN
PENNSYLVANIA
PUFRTH RICQ
rJHO-Tf- ISLAND
NUMBER OF
SITES
2 '
29
87
4
1
49
54
6
3
2
4
1
	 ; 	 3
4
8
7
9
	 155
"67 "
19
1
14
4
\ J

-------

STATt
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
STATE
PCT 'TCOO
STATE
>3LUTCOD
5TATE
5TATE
5TATE
->TATE
iTATE
;TATE
jTATF
,TATE
,TATE
iTATE

COMNT
COUNT
COUNT
CO'JNT
COUNT
CO'JNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
.COUNT
COUNT
COUNT
COUNT
COUNT
CO'JNT
COUNT
CU'JNT
COJ\-T
P.I LI. '11 ANT
CO )fc" '
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
42602
44 1 0 1
44101
44101
44101
44101
44101
44101
44101
44101
44101
C™
91
91
91
91
9i
91
91
91
91
91
91
91
94
94
11
11
11
11
11
11
11
tl
11
11

SOUTH CAROLINA
SOUTH DAKOTA
TtMNE SSEP
TEXAS
UTAH
VIRGINIA
WASHINGTON
WEST VIRGINIA
WISCONSIN
WYOMING
GUAM

KENTUCKY

ARIZONA
COLORADO
01 ST COLUMBIA
FLORIDA
ILLINOIS
INDIANA
IOWA .
KANSAS
MISSOURI
NcX JE^SFY
DUMBER OF
SITES
38
1
41
13
1
7
10
1 •
3
2
9
816
28
28
1
1
1
2
1
2
1
1
1
4

-------
TABLE II
	
ATF
IATF
ATF
STATE
1-'
ATF
»ATF
ATF
«ATF
PDLUTCOO
	
ATE
SJ.ATE
1 E ' ~

1ATE
POLUTCOD
JJATF'
STATE
JATE
MATE
STATE
«..
ATE
STATE
S|AT<-
SiAT E
SXATF

COUNT
COUNT
Cn-JNT
COUNT
COUNT
CPU NT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
'COUNT
"COUNT
COUNT
Cbu.N'f
COUNT
COUNT
COUNT"
COUNT
CCU-.T
CCJ'-IT
°.'M. i. UT f.
441 )1
44101
44101
44 1 0 1
441 Jl
44 t 0 1
44101
44101
44101
44101
44101
44101
44101
44101
	 ~ "44101
""44101
"44101
; 	 ~ 441 01
44101
44101
44101
44101
44101
44101
•rr .. Mf-TM
cunt
U
I L
11
11
11
il
li
11
11
11
13
13
13
13
13
	 14
14
	 14
14
14
It
14
14
14

\0''Trl CAPOLINJ
OHIO
PENNSYLVANIA
TENNESSEE
TEXAS
VIRGINIA
WASHINGTON
WISCONSIN

KANSAS
NEVADA
NEW MEXICO
WASHINGTON
ALABAMA 	
ARIZONA
CALIFORNIA
COLORADO
KENTyCKY
MINNESOTA
MISSOURI
OHIO
CRTGCN
PEriNSYLVAUI A
NUMBER OF
SITES
12
^2
8
1
4
1
4
1
1
49
3
1
1
5
10
." ' 	 1
56
1
"1 	
1
.8
2 ' ' . •
I
1
                                                  \

-------
TABLE II

STATF
STATE
POLJTCrj')
STATF
STATF
POLUTCOD
STATF
POLUTCOO
STATF
STATF
STATE
.' ^TF
POLUTCOD
STATE
STATE
STATE'
POL'JTCOn
STATE
STATF
STATF
STATE
STATE
STATE
S T A T t

C-'J'iMT
COUNT
COUNT
CPU -NT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
COUNT
C-.JLMT
COUNT
cnnr-
441 H
441 01
44101
44101
44101
44101
44101
44101
44101
44101
44101
44101
44101
44 1 0 1
44101
_441Q1
44 1 0 I
•44201
44201
44201
44201
44201
44201
44201
' r^)F
14
14
14
15
_ i'j
15
51
51
61
81
31
81
81
32
32
92
	 02
11
11
11
11
11
11
11

TE-NNCSSF"
VIRGINIA

C/LI FLWNIA
VIRGINIA

OKLAHOMA

MINNESOTA
NORTH CAROLINA
OKLAHOMA
SOUTH CAROLINA

KANSAS
KENTUCKY
JHIO

ALABAMA
COLORADO
••
OIST COLUMBIA
FLORIDA
GtfPRGI A
HAWAII
ILLINOIS
NUMBER OF
SITES
1
1
75
12
1
13
5
5
7
7
13
37
64
3
76
6
85
2
1
1
4
1
1
1

-------
TABLE II

STATE
(TATE
MT-ATE
STATE
1. "
TATE
STATE
TATE
(" TATE
TATF
•TATE
STATE
"E 	

-------
    A DESCRIPTION OF THE ANALYTICAL TECHNIQUES
    AND ASSOCIATED SAROAD METHOD CODES USED IN
STORING DATA IN THE NATIONAL AEROMETRIC DATA BANK
                    APPENDIX A
   EXTRACT FROM GUIDELINE DOCUMENT OAQPS 1.2-017
                   January 1974

-------
11101 91  SUSPENDED PARTICULATE - HI-VOL - GRAVIMETRIC
          Air is drawn at 40 to 60 ft. /min through a glass
          fiber filter by means of a blower, and the suspended
        •  particles having a diameter greater than 0.1 ym are
          collected.   The suspended particulate is reported in
          density units,  yg/m .   Oily participates or high
          humidity can cause reduced air flow through the filter.
          Therefore,  flow rates should be measured before and
          after the sampling period.
          1.   Intersociety Committee, "Methods of Air Sampling
          and Analysis,"  American Public Health Association,
          Washington,  D.C.,  1972, p 356.
          2.   "Rules  and  Regulations," Federal Register,  Vol 36,
          No. 228, U.S. Government Printing Office,  Washington,  D.C.,
          (Nov.  25, 1971),  p 22388.
          3.   "Air Quality Data for 1967," EPA APTD-0741, Office of
          Technical Information and Publications, Research Triangle
          Park,  North Carolina,  1971, p 17.

42101 11  CARBON MONOXIDE - INSTRUMENTAL - NON-DISPERSIVE INFRA-RED
          The principle is described in Vol 36- No. 228 of the
          Federal Register.   The major interference is H20 vapor
          whi'ch can be minimized by drying the air sample before
          it enters the cell.  Calibrated gases and a narrowband
          optical filter  are essential.  Variations in temperature
        •  cind pressure affect the instrument response and should
          be controlled.   Filters of 2-10 ym porosity should be
          used in the entering air stream to remove fine particulates
          1.  "Rules and Regulations," Federal Register, Vol 36,
          No. 228, (Nov.  25, 1971), p 22391.

-------
42101 12  CARBON MONOXIDE - INSTRUMENTAL - COULOMETRIC
          Atmospheric air is drawn through a heated^205 tube
          and I'2 is liberated.  The gas containing I2 is directed
        .  into an electrochemical cell where 1^ is reduced to
          iodide coulometrically.
          1.  Beckman Instrumention, Bulletin 3000 4411-4,
          Beckman Instruments, Inc., Fullerton, California.

42101 21  CARBON MONOXIDE - INSTRUMENTAL - FLAME IONIZATION
          Ambient air is introduced into two gas chromatographic
          columns in series, the first of which retains most
          pollutants except CO and CH4, and the second of which
          passes only CO.  The CO is then led over a Hi catalyst
          where it is converted to Cllq.  The CII4 is passed into
          a flame ionization detector, where the resulting measured
          current can be related to the initial CO concentration
          of the ambient- air.                     -          .
          1.  Rotterdam, Warsaw, and Bucharest, "The Status of In-
         •strumentation in Air Pollution' Control," Environmental
          Control Seminar Proceeding, U.S. Department of Commerce,
          (May 5-June 4, 1971), p 217.  '           s

42401 11  SULFUR DIOXIDE-INSTRUMENTAL-WEST GAEKE-COLORIMETER
                 t                              t
          A continuous analyzing system is set up so that the
          ambient air flows through a glass spiral absorption column
          concurrently with 0.02M sodium tetrachloromercurate.
          Dichlorosulfitomercurate ion is formed, reacted with
        •  acid-bleached pararosaniline and formaldehyde to produce
          a red-purple pararosaniline methylsulfonic acid which
          is quantitatively measured colorimetrically.  The 95%
          baseline is established, with pure reagents for 1 h and

-------
42401 13
          the instrument is then calibrated.  Air flow rate and
          reagent flow rate must be calibrated and maintained
          accurately.
          1.  Yunghans, R. S. and W. A. Monroe, Technicon Symposium
          on Automation in Analytical Chem. , 1965, p 279.
          2.  "Technicon Air Pollution Detection System," In-
          struction Manuals T 67-105 , Technicon Corp.

          SULFUR DIOXIDE-INSTRUMENTAL-CONDUCTIMETRIC
          Sulfur dioxide is absorbed in acidic lUO  which oxdizes
          it to HnSO,
                        The method is a measure of all materials
          that increase conductivity.  Thus, any materials that
          alter the conductivity of the reagent are potential in-
          terfering agents.
          1.  Beckman-Air Quality Acralyzer Operating and Service
          Manual, Scientific and Process Inst. ,Div., Fullerton,
          California, 16TW352,  (Aug. 1966).
          2.  Thomas, M.D.,  (1932), "Automatic Apparatus for the
          Determination of Small Concentrations of Sulfur Dioxide
                                           *•
          in Air," Anal. Chem.  5, 253.
          3.  M. B. Jacobs,  "The ChemicaJL Analysis .of Air Pollutants,"
          Chemical Analysis, Vol 10, Interscience Publishers, Inc.,
          New York, N.Y.,  (1960), p 394.
          4.  Water, Atmospheric Analysis,  (1971), "Annual Book of
          ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, p 272.
42401 14  SULFUR DIOXIDE-INSTKUMENTAL-COULOMETRIC
          Coulometric analyzers measure the current necessary to
          maintain a halogen concentration  (Br2 or J.^} constant in
          the sample cell.  The magnitude of this current is pro-
          portional to the amount of absorbed S02.  There are several

-------
          versions of instruments using this principle.
          1.  J. F. Welcher, "Standard Methods of Chemical Analysis,"
          D. Van Nostrand Company, Inc. Princeton, N.J., 1966,
          p 377.

42401 15  SULFUR DIOXIDE-INSTRUMENTAL-THOMAS AUTOMETER
          The Thomas Autometer is a conduct line trie analyzer de-
          veloped in 1929.

42401 16  SULFUR DIOXIDE-INSTRUMENTAL-FLAME PHOTOMETRIC
          Chroraatographic columns are used to separate S02, H_S,
          CS~, and CH-.SH.  Effluent from the columns is burned in
          a hydrogen-rich flame where a 395 nm emission band
          characteristic of sulfur is created.  A photonmltiplier
          tube is used to detect the luminescence.  Response is linear
          on a log-log scale.
          1.  H. H. Willard, L. Li Merritt, and J. A. Dean, "In-
          strumental Methods of Analysis," D. Van Nostrand Company,
          Inc., 4th Edition, 1965, p 309.

42401 31  SULFUR DIOXIDE-DAVIS INSTRUMENT-HYDROGEN PEROXIDE
          The Davis instrument is a conductiraetric instrument, and
          as such, it is much like method 42401 13.

42401 33  SULFUR DIOXIDE-DAVIS INSTRUMENT-SEQUENTIAL-COKDUCTIMETRIC
          Water is deionized by passage through an amberlite resin
          column, then its conductivity is measured.  Ambient air,
          having first passed through a scrubber of amberlite re-
          sin and soda-lime to remove CO-, is next passed through
          the deionized water where the S0~ is absorbed.  The in-
          creased conductivity of the water is a measure of the
          S02 concentration of the air.
          1.  Thomas, M.D. and J. N. Abersold, (1929), "Automatic
          7*.pparatvis for the Determination of Small Concentrations
          of Sulfur Dioxide in Air," Anal.' Chem.  1, 14.

-------
42401 91  SULFUR DIOXIDE-GAS BUBBLF.R-WEST-GAEKE-SULFAMIC ACTD
          The method is described in Vol 36, No. 228 of the Federal
          Register. (.The NASN procedure, however, uses 1.725 g/1
          sulfamic acid rather than 6 g/1 and does not use EDTA) .
          The sulfamic acid eliminates interference from oxides of
          nitrogen.  Sulfur dioxide is collected in a tetra-
          chloromercurate solution, forming a stable dichlorosulfito-
          mercurate complex.  When acid bleached pararosaniline
          is added to the collected S02 together with formaldehyde,
          the amino groups  (-NI-U) form a red-violet compound called
         " pararosaniline methylsulfonic acid which is measured spec-
          tropho.tometrically.
          1.  West, P. W. and G. C. Gaeke,  (1956), "Fixation of
          Sulfur Dioxide as Disulfito-Mercurate  (II) and Subsequent
          Colorimetric Estimation," Anal. Chem. 28, 1819.
          2.  "Rules and Regulations," Federal Register, Vol 36,
          No. 228, U.S. Government Printing Office, Washington, D.C.,
          (Nov. 25, 1971), p 22385.       ..  .  '            .
          3.  Intersociety Committee, "Methods of Air Sampling and
          Analysis," American Public Health Association, Washington, D.C.,
          1972, p 447.                   -.         ' x
          4.  "Air Quality Data for 1967-," EPA-APTD 0741, Office of
          Technical Information and Publication, Research Triangle
          Park, N.C., 1971, p 20.
             •
42401 92  SULFUR DIOXIDE-GAS BUBBLER-WEST-GAEKE
          This method is similar to method 42401 91 except that the
          sample absorbing reagent is 0..1M TCM, the starch which is
          used for standardization is made without mercuric iodide,
          and sulfamic acid is not used except when high concen-
          trations of N02 are expected.  The sulfamic acid is added
          to the sample after collection.

-------
          1.  "Selected Methods for the Measurement of Air Pollutants"
          U.S.  Department of Health, Education,  and Welfare 999 AP-.
          11, Robert A. Taft Sanitary Engineering Center, Cincinnati,
          Ohio, May 1965, p A-l.
          2.  Nauman, R. V., et al. , (1960), Anal Chejn. 32, 1307.
          3.  West, P.W. and F. Ordoveza,  (1962), Anal. Chem. 34,
          1324.                                ,

42401 93  SULFUR DIOXIDE-GAS BUBBLER-CONDUCTIMETRIC
          Manual coriduc time trie methods use the same principles as
        " instrumental conductimetric except the absorber is a
          multiple jet bubbler system and the sampling" is not con-
          tinuous.  The details are described in the reference.
          1.  Intersociety Committee, "Methods of Air Sampling
          and Analysis," American Public Health Association,
          Washington, D.C., 1972, p 456.

42602 11  NITROGEN DIOXIDE-INSTRUMENTAL-COLORlMETRIC
          The Lyshkov/ modification of the  Griess-Saltzman reagent
          is used in various continuous N02 analyzers.   Users
          should consult the manufacturer's literature for details
          of reagent preparation.
          1. •  "Rules and Regulations" Federal Register,  Vol  38,
          No.  110, USGPO Wash., D.C.,  (June 8,  1973),  p  15176.
          2.  Lyshkov;, N. A.,  (1965), "A Rapid  Sensitive Colorimetric
          Reagent for Nitrogen Dioxide in  Air" ,T. Air Poll. Control
          Assoc. 15  (No. 1.0)   481.

42602 12  NITROGEN DIOXIDE-IMSTRUMENTAL-COLORIMETRIC
          The  original Griess-Saltzman reagent  is used in  various
          continuous NO., analyzers.  Users should consult  the
                       £
          manufacturer.'s literature for details  of  reagent pre-
          paration.

-------
          1.  "Rules and Regulation," Federal Register, Vol 38,
          No. 110, USGPO, Wash., D.C., (June 8, 1973) p 15176.
          2.  Saltzman, B. E.,  (1954) "Colorimetric Micro Determination
          of Nitrogen Dioxide in the Atmosphere" Ana1. Chem. 26,
          1949.

42602 13  NITROGEN DIOXIDE-INSTRUMENTAL-COULOMETRIC
          Nitrogen dioxide is absorbed in a buffered iodide-iodine
          solution causing the equilibrium between iodine and iodide
          to be unbalanced.  The current required to re-establish
         " the equilibrium is a measure of the N02 concentration.

42602 14  NITROGEN DIOXIDE-INSTRUMENTAL-CHEMILUMINESCENCE
          The nitrogen dioxide is dravm over a gold catalytic con-
          verter v.Thich reduces N02 to NO.  The NO is then analyzed
          by method 42601 14.                  •
          1.  NO/NO/NO- Analyzer Bulletin, Bulletin 4133, Beckman  .
                   5C   <-'
          Instruments, Inc., Fullerton, Calif.'
                                           «.
                                        ;
42602 71  NITROGEN DIOXIDE-GAS BUBBLER-JACOBS-HOCHHEISER-50 Ml
          TUBE -I- ORIFICE
                                                    x
          The method is that described in the Federal Register.
          The. N02 is converted to NO~- in NaOI-I solution.  The
          collection efficiency is a function of the N02 con-
          centration and high concentrations of NO interfere.
          1.  "Rules and Regulations," Federal Register, Vol 36,
          No. 228, U.S. Government Printing Office, Washington, D.C.
          (Nov.  25, 1971) , p 22396.

42602 72  NITROGEN DIOXIDE-GAS BUBBLER-SALTZHAN  (50 Ml TUBE + ORIFICE)
          The sample is absorbed in the Griess-Saltzinan reagent
          and after 15 rain the  stable pink color is measured
          colorirnetrically cit 550 nm.

-------
          1.  Intersociety Committee, "Methods of Air Sampling
          and Analysis," American Public Health Association,
          Washington, D.C., 1972, p 329.
          2.  Saltzman, B. E.,  (1954), "Colorimetric Micro-
          Determination of Nitrogen in the Atmosphere," Anal.
          Chem. 26, 1949.

42602 91  NITROGEN DIOXIDE-GAS BUBBLER-JACOBS-HOCHHEISER  (100
          Ml TUBE 4- FRIT)
          A fritted bubbler and 100 ml tube, instead of a glass
        - tube orifice and 50 ml tube, makes this method different
          from method 42602 71.  The disadvantages of the method
          still apply.
          1.  "Selected Methods for the Measurement of Air Pollutants,"
          U.S. Department of Health, Education, and Welfare 999-
          AP-11, Robert A. Taft Sanitary Engineering Center,
          Cincinnati, Ohio, May 1965, p C-4.
          2.  Purdue, L. J. , et.al.,  (1972), "Reirivestigation
          of the Jacobs-IIochheiser Procedure for Determining  .
          Nitrogen Dioxide in Ambient Air," Environ.Sci.and Tech.6,
          152.

42602 94  NITROGEN DIOXIDE-GAS BUBBLER-NASN-SODIUM ARSENITE-FRIT
          The method is much like method 42602 91 except for the
          absorber  (l.Og of NaAs09 and 4.0g" of NaOH diluted to one
             •                    *•
          liter with distilled H20) .  The NaAs02 increases the N02
          collection efficiency, but NO still interferes.
          1.  Christie, A. A., R. G. Lidzey, and D. W. F. Radford,
          (1970) , "Field Methods for the Determination of Nitrogen
          Dioxide in Air." Analyst 05, 519.
          2.  Merryman, E. L. , et.al., "Effects of NO, C02, CH^ , H20
          and Sodium Arsenite on NO- Analysis," presented at the
          Second Conference on Natural Gas Research and Technology .
          Atlanta, Georgia, June 5, 1972.

-------
          3.   "Selected Method for the Measurement of Air Pollutants,"
          U.S. Department of Health, Education, and Welfare 999-
        .  AP-11, Robert h. Taft Sanitary Engineering Center,
          Cincinnati, Ohio, May 1965, p C-4.

44101 11  TOTAL OXIDANT-INSTRUMENTAL-ALKALINE KI
          Oxidants  in ambient  air  are absorbed  in  an alkaline  KI .-solu-
          tion.   On acidification,  iodine  is liberated  and  measured
          colorirn.Gtrically.
44101 13..  TOTAL OXIDANTS-INSTRUMENTAL-MAST MODEL 742-2
          Air is drawn over electrodes at a controlled rate to-
          gether with a continuous stream of fresh electrolyte.
          Hydrogen is maintained on the working electrode by a
          polarising voltage.   Oxidants convert I  to I~ which
          reacts with the H~,  thus depolarizing the electrode.
          The current required to repolarize the electrode  is a
          measure of the oxidant concentration of- the sample.
          1.   Mast, G. M. and H. E. Saunders, (Oct. 1962),  "Research
                                          *
          and Development of the Instrumentation of Ozone Sensing,"
          Instrument. Soc. 'of Amer. Trans. ,  1, 375.." '
          2.   Bufalini, J. J.,  (1968), "Gas Phase Titration of
          Atmospheric Ozone," Environ Sci Techno! 2, 703.
          3.   Wartburg, A. F., and B. E.  Saltzman,  (1965),
          "Absorption Tube for Removal of Interfering S02  in Analysis
          of Atmospheric'Oxidant" Anal. Chem. 37, 779.

44101 14  'TOTAL OXIDANT-INSTRUMENTAL-COLORIMETRIC-NEUTRAL KI
          Iodine is  liberated from a neutral KI solution to form
          KI^ which  is determined spectrophotoiaetrically at 352 nm.
          The ambient air is drawn counter  current  to the  flow  of
          a neutral  KI reagent.  The reaction is pll dependent and
          thus a nexitral KI solution is used.  Sulfur dioxide is

-------
          removed by using a CrO., scrubber.
          1.   Intcrnociety Committee,  "Methods of Air Sampling
          and Analysis," American Public Health Association,
          Wash.,  D.C., 1972, p 356.
          2.   Water, Atmospheric Analysis, (1971), "Annual Book
          of ASTM Standards," American Society for Testing and
          Materials, Philadelphia, Pa., Part 23,. p 518.
          3.   Wartburg, A. F., and B.  E. Saltzman, (1965),
          "Absorption Tube for Removal of Interfering SCU in
          Analysis of Atmospheric Oxidant" Anal. Chem. 37, 779
        »•
44101 15  TOTAL OXIDANT-INSTRUMENTAL-COULO^TRIC-NEUTRAL KI
          This method is beised on the same principle as 44101 13.
          The electrolyte flov.'S betv/een two electrodes which are •
          used to measure the current needed to re-establish the
          hnlogen-halide balance.  Nitrogen dibxide interference
          has to be subtracted.  Sulfur dioxide interference is
          reduced by a CrCU scrubber.
          1.   Intcrsociety Committee,  "Methods of Air Sampling
          and Analysis," American Public Health Association,
          Wash.,  D.C., 1972, p 341.     '          ' s

44101 51  TOTAL OXIDANT-GAS BUBBLKR-PHEiTOLPHTHALIN
          Phenolphthalin in the presence of CuSO^ can be oxidized
          to.phenolphthalein by anbicnt air oxidants.  Air is
          passed through 10 ml of reagent at 800 ml/min for 10
          min.  The color is read using a green filter and a
        ..  colorimeter.
          1.   M.  13. Jacobs,  (I960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Interscience
          Publishers, Inc., New York,  K. Y., p 226.

-------
44101 81  TOTAL OXIDANT-GAS BUBBLER-ALKALINE KI
          Oxidants in ambient: air arc. absorbed in an alkaline KI
          solution in a bubbler.  A stable product is formed which
          can be stored with little loss for several days.  Analysis
          is completed by addition of phorphoric acid-sulfuric
          acid reagent, liberating iodine, which is then determined
          spectrophotometrically at 352 nm.
          1.  Selected Methods for the Measurement of Air Pollutants
          U.S. DREW 999-AP-ll, RATSEC Cincinnati, Ohio, 1965,
          p E-l.
        "  2.  Water, Atmospheric Analysis,  (1971), "Annual Book of
          ASTH Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, p 391.
          3.  M. B. Jacobs,  (1960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Intersc.ie.nce
          Publishers, Inc., New York, N. Y., p'219.

44101 82  TOTAL OXIDANT-GAS BUBBLER-FERROUS OXIDATION
          Air is filtered through a Whatman No. 4 paper at 1 cfm
          then bubbled through two impingers in series containing
          the absorbing reagent.  The abcorbance is .determined
          with a blue filter and a colorimeter.  The standard is
          made by oxidizing the absorbing reagent with known
          amounts of H-O- and reading the absorbance.
          1. ^ M. B. Jacobs,  (1960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vpl 10, Interscience
          Publishers Inc., New York, N. Y., p 228.

44201 11  OZONE - INSTRUMENTAL-CHEMILUWINESCEMCE
          The Federal Register describes this method.  Ozone ozonizes
          ethylene and the excited molecule emits a spectrum peaking
          at 450 ran.  A photornultiplicr tube is used to measure the
          chemilvuninescence.
          1.  "A Chemiluminesconce Detector for Ozone Measurement,"
          BureiAi of Mines Report of Investigation RI-76.r;o, United Ptatcr.:

-------
          Department of the Interior, U.S. Government Printing
          Office, Washington, D.C.,  1972.
          2.  "Rules and Regulations," Federal Register Vol 36,
          No. 228, U.S. Government Printing Office, Washington, D.C.,
          (Nov. 25, 1971),  p 22392.

44201 13  OZONE - INSTRUMENTAL - COULOMETRIC
          This method is similar to method 44101 13.

-------
                           APPENDIX D

            Reasons for Ranking the Methods as
        'Tentatively Acceptable" and "Mot Acceptable"
 CO 42101 12
COULOMETRIC
Interferences with this method include mcr-
captans, hydrogen sulfide, olefins, acetylenes,
and v/ater vapor.  Although these interferences
may possibly be minimized by means of scrubbers,
the slow response, need for careful column prepa-
ration, and the need for well controlled
temperatures and flow rates make this an undesir-
able procedure.
 CO 42101 21
FLAME•IONIZATION
Although when carefully maintained, this pro-
cedure yields good data, because the stripper
column must be checked frequently with known
gas mixtures, agencies cannot be encouraged
to adopt the method at this time.
S02 42401 11
COLORIMETRIC
Although this instrumental procedure uses the
West-Gaeke reagent, it has not been accepted as
reference method.  Ozone may interfere.
S02 42401 13
          15
          31
          33
COKDUCTIMETRIC
AUIOMETER
HYDROGEN PEROXIDE
SEQUENTIAL COI7DUCTIMETRIC
All of these methods are conductiinetric and as
such are non-.specific for S02.

-------
S02 42401 14
                            —2—
COULOMETRIC
Lack of specificity is the chief criticism
of this method.
S02 42401 92
WEST-GAEKE BUBBLER
Oxides of nitrogen interfere.  The interference
can be eliminated by adding sulfamic acid to the
solution, in which case the method is then  S^o"
West-Gaeke-Sulfainic Acid and is reported under
code number 42401 91.
S02 42401 93
CONDUCTIMETRIC BUBBLER
The method lacks specificity.
N02 42602 71
J-H BUBBLER  (orifice)
N02 42602 91  J-H BUBBLER  (frit)
              .The objections to these methods have been detailed
              in 38 FR 15174 (June 8, 1973):  The collection
              efficiency is a function of N02 concentration
              and the presence of NO introduces a positive in-
              terference.
N02 42602- 72
SALTZMAN
This manual method suffers from interferences
from S02, ozone, PAN, and prolonged exposure
to light.
N02 42602 94
          95
          96
SODIUM ARSENITE
TEA
TGS
These manual methods are either candidates for
the MOp reference method(s) or are presently
being investigated for their characteristics.
We cannot state at this time which if any will
be acceptable.  liany agencies, however, are
using the sodium arsenitc method, despite, the

-------
                                  -3-
                   known NO interference.

TOTAL 0. 44101 11  ALKALINE KI-INSTRUMENTAL
                   The alkaline KI method produces such variable
                   results in different hands that data from one
                   site cannot be compared with data from another.

TOTAL 0  44101 13  MAST MODEL 742-2
               15  COULOMETRIC
                   These coulometric methods yield data different
                   from the neutral buffered KI reference method
                   and the difference varies from site-to-cite
                   because the mix of oxidants differs from site-
                   to- site.

TOTAL Ox 44101 51  PHENOLPHTHALIN
                   The phenolphthalin method yields values of
                   total oxidant approximately twice those ob-
                   tained by the reference method, neutral buffered
                   KI. The relation is unexplained. .
TOTAL 0  44101 81
ALKALINE KI BUBBLER
The limitations and objections to this method
are the same as those listed under method 11,
the instrumental method.
TOTAL O  44101 82
                   This is an insensitive method, the results
                   always indicating lower results than those ob-
                   tained by the neutral-buffered KI technique.
OZONE    44201 13  COULOMETRIC
                   This method is riot specific for ozone.

-------
y
           GUIDELINE  SERIES
                      OAQPS NO. 1.2-017
                A DESCRIPTION OF THE ANALYTICAL TECHNIQUES
                AND ASSOCIATED SAROAD METHOD CODES USED IN
                STORING DATA IN THE NATIONAL AEROMETRIC
                DATA BANK
              US. ENVIRONMENTAL PROTECTION AGENCY
                Office of Air Quality Planning and Standards


                 Research Triangle Park, North Carolina

-------
      A DESCRIPTION OF THE ANALYTICAL TECHNIQUES AND
          ASSOCIATED SAROAD METHOD CODES USED IN
  STORING DATA IN THE NATIONAL AEROMETRIC DATA BANK
                      OAQPS 1.2-017
                         March 1974
              Monitoring and Reports Branch
       Office of Air Quality Planning and Standards
                           and
Quality Assurance and Environmental Monitoring Laboratory
            Office of Research and Development
          National Environmental Research Center
          U. S. Environmental Protection Agency
      Research Triangle Park, North Carolina  27711

-------
                  TABLE OF CONTENTS.

                                                  Page
Introduction                 .    '                   1
Suspended Particulates                              3
Benzene Soluble Organic                             3
Soiling Index                                       4
Light Scatter                                       4
Radioactivity                                       4
Metals, by Hi-Vol, AA, Emission Spectra             6
Arsenic                                             9
Mercury                                             9
Water Soluble Particulates                         10
Benzo(A)Pyrene                                     15
Dustfall Procedures                                16
Carbon Monoxide                                    23
Sulfur Dioxide                                     24
Hydrogen Sulfide                                   27
Sulfation Rate Procedures     '                     28
Fluoride Ion                                       31
Nitrogen Oxides                                    32
Ammonium                                           36
Hydrocarbons                                       38
Aldehyde                                           39
Oxidants                                           40
Ozone                                              43

-------
    The purpose of this document is to bring together for
the first time a $AROAD code number with a description of
the analytical technique used in gathering data stored in the
National Aerometric Data Bank CNADB).  It has long been
needed.  The SAROAD code numbers and methods in this
compilation are only those for which data have been sub-
mitted since 1969.  The titles of the methods (in capital
letters following the code number) are those which were
assigned in the past and which appear in the computer
printout of Common Parameters and Methods (the "Farm File"),
similar to Code Table 4 of the SAROAD Users Manual.
    It is to be emphasized that we do not endorse all of
the procedures described herein.  Some are known to yield
erroneous or misleading data.  Nor do we endorse a par-
ticular manufacturer's instrument even though the name is
referred to in a title.  The rule governing the compilation
was:  every method used since 1969 together with its Farm
File title is to be included for the purposes of completeness.
    Beneath each SAROAD number and title there is a brief
description of the sampling and analysis principles followed
by references which the reader should consult for details.
Whenever possible, we have given references to those pub-
lications which we think should be readily available to
field workers.  In no case have we included enough details
for a worker to start an analysis program which will produce
valid data.  The references must be consulted.
    Instrumental techniques have not been thoroughly re-
ferenced and the instrument user should consult the pro-
cedure prepared by the manufacturer.

-------
    Through this publication we hope to achieve some degree
of uniformity in reporting data to. the NADB.  If, for example,
data have been submitted to the Bank under a given code number,
but the description of that method as found in this compilation
is different from the method which was actually used to obtain
the data, then the reporter must do one of three things:

    a.  he must begin submitting data under the proper
        code number which agrees with the method actually
        used; (data previously reported must be re-reported
        under the correct code);

    b.  the reporter must change his methodology to agree
        with the method described and data then submitted
        using that code number; or

    c..  a new code number must be applied for.

    We encourage the persons who submit data to the NADB
to verify with the laboratory personnel that the SAROAD codes
used agree with the analytical procedures described herein.
If there are problems or questions, we urge you to call the
chief of the data processing section, NADB, Durham, N.C.
(FTS 919/688-8247); or your SAROAD contact or quality control
coordinator in the Regional Office.  Also, we will welcome
your pointing out any errors and/or omissions in the text.
There are a few blanks which we have not been able to fill
in.

-------
11101 91  SUSPENDED PARTICULATE - HI-VOL GRAVIMETRIC
          Air is drawn at 40 to 60 ft. /rain through a glass
          fiber filter by means of a blower, and the suspended
          particles having a diameter greater than 0.1 ym are
          collected.  The flow rate of air drawn through the
          filter is measured by means of a rotameter which should
          be calibrated frequently.  The suspended particulate
          is reported in density units, yg/m .  Oily particulates
          or high humidity can cause reduced air flow through the
          filter.  Therefore, flow rates shoiald be measured before
          and after the sampling period.
          1.  Inter society Committee, "Methods of Air Sampling
          and Analysis," American Public Health Association, •
          Washington, D.C., 1972, p 365.
          2.  "Rules and Regulations," Federal Register, Vol 36,
          No. 228, U.S. Government Printing Office, Washington, D.C.,
          (Nov. 25, 1971) , p 22388.
          3.  "Air Quality Data for 1967," EPA APTD-0741, Office of
          Technical Information and Publications, Research Triangle
          Park, North Carolina, 1971, p 17.
11103 91  BENZENE SOLUBLE ORGANICS - HI-VOL BENZENE EXTRACTION
          An 8% aliquot of the filter is placed in a soxhlet
          extractor and extracted with 75 ml of benzene for 6 h.
          The benzene is evaporated and the residue is weighed and
          reported in aerometric units; yg/m .   Errors may result
          from non-volatile material in the benzene used for
          extraction.
          1.  Stanley, T. W. , J. E. Meeker and M. J. Morgan,  (1967),
          Environ. Sci. and Tech. '1, (11), 927.
         . 2.  "Air Quality. Data for 1967," EPA APTD-0741, Office
          of Technical Information and Publications, Research
          Triangle Park, North Carolina, 1971,  pp 17-18.

-------
11201 81  SOILING INDEX (COH) - TAPE SAMPLER   TRANSMITTANCE
          Air is drawn through a 1 in. diameter spot on a 'con-
          tinuous strip of filter paper.  The measurement is based
          on light transmission through the spot having the col-
          lected matter on it, and reported in COH's (coefficient
          of haze) per 1000 linear foot of sampled air.  The
          standard is a clear spot on the paper.  The inlet air
          funnel must be kept upside down, and sampling lines
          must be kept short.
          1.  Water, Atmospheric Analysis, (1971) , "Annual Book
          of ASTM Standards," American Society for Testing and
          Materials, Philadelphia, Pa., Part 23, p 420.
          2.  "Air Quality Data for 1967," EPA APTD-0741, Office
          of Technical Information and Publication, Research
          Triangle Park, North Carolina, 1971, p 20.

11202 91  SOILING INDEX (RUD) - TAPE SAMPLER - REFLECTANCE
          The sampling procedure is similar to that of 11201 81.
          Measurement of the soiling is based on light reflectance
          from the spot and is reported in RUD's (reflectance
          unit density).
          1.  Water, Atmospheric Analysis, (1971), "Annual Book
          of ASTM Standards," American Society for Testing and
          Materials, Philadelphia, Pa., Part 23, p 420.

11203 11  LIGHT SCATTER  NEPHELOMETER
          Air enters an optically black metal tube at 5 cfm.  Light
          of 410 nm is scattered from particles in the air stream.
          The amount of light scattered at 90° from the main beam
          is measured by a photomultiplier tube.
11302 91  RADIOACTIVE-GROSS-BETA-HI-VOL  PROPORTIONAL COUNTER
          The radioactive matter on a filter paper is counted with
          a beta sensitive detector to establish the gross concen-
          tration of beta emitters in the sampled ambient air.  The
          daughter products of natural radon and thoron in the at-
          mosphere can be minimized by waiting three days until they

-------
have decayed.  A self-absorption correction must be made
if inert matter on the filter interferes.
1.  Intersociety Committee, "Methods of Air Sampling and  -
Analysis," American Public Health Association, Wash., D.C.,
1972, p 379.
2.  Settler, L. R. and G. I. Coats,  (1964), "The Determi-
nation of Airborne Radioactivity," Airier'.' TridV Hygiene
Assoc., J. 22, 64.
3.  Schulte, H. F., Monitoring Airborne Radioactivity,
"Air Pollution," Vol II, 2nd Ed.f A. C. Stern, Ed.,
Academic Press, New York, N. Y., 1968, p 393.

-------
12101-12185           ATOMIC ABSORPTION  (AA)
         Aliquots of samples from the low temperature ashing
         procedure are sprayed into a reducing flame by an
         atomizer, where metal ions, are reduced to the atomic
         state.  The atoms absorb monochromatic light pro-
         duced by a lamp having a cathode made of the element
         to be measured.  The light absorbed by the atoms in
         the flame is a measure of their concentration.  The
         influence of one element on the excitation potential of
         another does not interfere.  The analysis of Al, Sb,
         As, Be, Bi, Ba, Cd, Ca, Cr, Co, Cu, Fe, Pb, Mn, Mo,
         Ni, Hg, Sn, Ti, V, and Zn is done by AA.  The AA
         is more sensitive than emission spectra for most
         metals.
         1.  W. Slavin,   "Atomic Absorption Spectroscopy,"
         Interscience Publishers, New York, 1968, pp 69-74.
         2.  Perkin Elmer Corp., Methods Manual-Analytical
         Methods for Atomic Absorption Spectrophotometry,
         The Perkin Elmer Corp., 1968.
         3.  F. J. Welcher, Standard Methods of Chemical Analysis,
         D. Van Nostrand Company, Inc., Princeton, New Jersey,
         1966, p 105.
         4.  Thompson, R. J., G. B. Morgan, and L. J. Purdue,
         (1970), "Analysis of Selected Elements in Atmospheric
         Particulate Matter by Atomic Absorption," Atomic
         Absorption Newsletter 9,  (No. 3), 55.

12102-12185              EMISSION SPECTRA          '
         A solution containing metallic ions is placed between
         two electrodes and subjected to 13-15 kilovolts AC
         discharge.  The spark so created generates enough
         heat to atomize the ions and the high voltage excites
         many electrons per atom.  Spectra characteristic of
         each element are formed when the electrons return to

-------
         their  normal  energy levels.   Internal  standards  are
         used to reference a known  spectral  line  so  that  other
         lines  can be  located.   NASN  uses  indium  and yttrium
         as internal standards.   Metals  as Sb,  Be, Bi,  Ba,
         Cd, Cr, Co, Cu,  Fe, Pb, Mn,  Mo, Ni7 Sn,  Ti, Sm,  V,
         and Zn are analyzed by emission spectra.
         1.  H. H. Willard, L.  L. Merritt, J. A.  Dean,  "In-
         strumental Methods of  Analysis,"  D. Van  Nostrand
         Company, Inc. 4th Edition, 1965,  p  280.
         2.  F. J. Welcher,"Standard Methods of Chemical  Analysis,"
         D. Van Nostrand Company, Inc.,  Princeton,  New Jersey,
         1966,  p 141.
         3.  "Air Quality Data for 1967,"  EPA-APTD 0741,  (1971),
         Office of Technical Information and Publication, Research
         Triangle Park, N.C., 1971, p 19.                   •

12102-12185        LOW TEMPERATURE ASHING  PROCEDURE
         Particulates  are ashed to remove  organic matter.  A 1 or
         2 in.  by 7 in. strip of the exposed glass filter (or a
         composite of  5-8 strips) is heated  at 150°C for 1 h. at
         1 torr with an 02 flow of 3000  ml/h.  The ashed filter
         is fluxed for 3 h. with 8  ml of 20% HC1  and 32 ml of
         40% HNO^.  The acid extract is  concentrated to 1 or 2
         ml by evaporation, centrifuged, and the  residue is
         washed three  times with dilute  HC1.  Samples from non-
         urban air are then diluted with distilled H-O to 3 ml/2
         in. strip and samples from urban  air are diluted to 4.4
                 2
         ml/9 in.  of  filter taken.  Samples so prepared are
         ready for emission spectra analysis, but must be diluted
         10 fold .for AA analysis.
         1.  Thompson, R. J., G. B. Morgan and L. J. Purdue,
         (1970) "Analysis of Selected Elements in Atmospheric
         Particulate Matter by Atomic Absorption," Atomic
         Absorption Newsletter 9, 54.

-------
12102-12185           MUFFLE FURNACE PROCEDURE
          Prior to the invention of the low temperature asher,
          organic material was removed by heating samples to
          500°C for 1 h. in a muffle furnace.  Samples are then
          extracted twice for 1 h. with 40 ml of 1:1 redistilled
          HNO-, at a temperature just below boiling.  The solution
          is filtered, evaporated to 4 ml and diluted to 10.4
          ml with H-O.  The samples are then analyzed by the
          emission spectrograph.  Metals as Sb, As, Be, Bi, Cd,
          Cr, Co, Cu, Fe, Pb, Mn, Mo, Ni, Sn, Ti, V, and Zn are
          measured by this procedure.  This procedure may volatilize
          some portion of some of the metals and thus result in
          an unknown fraction recovered.

-------
12103-93  ARSENIC - HI-VOL   NASN-ARSINE-COLORIMETRIC
          The arsenates and oxides of arsenic are extracted from a
          2 in. square exposed filter by digestion for 1 hr with
          30 ml of 6 N HC1 at 90 °C, and then reduced to the trivalent
          state with KI and SnCl2-  Arsine is then generated by Zn
          and HC1 Gutzeit procedure.  The evolved arsine passes
          through a HLS scrubber and into an absorber containing silver
          diethyldithiocarbamate.  The resulting red complex is
          measured spectrophotometrically at 535 run.  Antimony like-
          wise forms stibine which also complexes with the carbamate
          but at low concentrations does not interfere with arsenic
          determination.  High concentrations of Mi, Cu, Cr, and
          Co interfere with arsine formation.  Many interferences
          can be minimized by using an internal standard of added
          arsenic.
          1.  Intersociety Committee, "Methods of Air Sampling and
          Analysis," American Piiblic Health Association, Wash., D.C., •
          1972, p 289.
12142 92  MERCURY - ACID IC1   ATOMIC ABSORPTION
          This is a flameless AA technique.  The total mercury is
          collected through a glass impinger in 30 ml of 0.1N
          acidic iodine monochloride at a flow-rate of 200 ml/min.
          Hglj is reduced to elemental mercury by hydroxylamine
          hydrochloride in basic solution which is aerated to
          vaporize the mercury.  The vapor is passed into a quartz
          absorption cell where it absorbs light at 253.7 nm.  This
          method is not applicable to atmosphere containing less than
          50 ng Hg/m  of air due to high and erratic blanks.
          1.  Hatch, R. W. and W." L. Ott,  (1968), "Determination
        .  of Sub-Microgram Quantities of Mercury by Atomic Absorption
          Spectrophotometry," Anal. Chem. 40, p 2085.
          2.  Lynch, A. L., R. F. Stalzer, and D. T. Lefferts, (1968),
          "Methyl and Ethyl Mercury Compounds — Recovery from Air
          and Analysis," Am. TndV Hygiene Assoc. J., 79.

-------
                                 10
12202 91  FLUORIDE-HI-VOL WILLARD-WINTER/SPECIFIC ION ELECTRODE
          The Willard-Winter distillation is carried out to remove
          interfering ions.  Two 1 3/4 in. diameter circles of the  "
          filter are placed in a platinum dish, covered with 10 ml of
          Ca(OH)2 suspension (2.5% Ca by weight), and evaporated to
          dryness over a steam bath.  The residue is heated for
          30 min. in an oven at 150°C, and ignited in a muffle
          furnace at 550°C for 5-6 h.  The ash is mixed with
          Ig AgCl04 and steam distilled using 10 ml of 60% HC104
          at 135°C.  A total of 190 ml of distillate is collected.
          The fluoride ion concentration is then measured with a
          specific ion electrode.  See 42513 91.
          1.   M.  B. Jacobs, (1960),  "The Chemical Analysis of Air
          Pollutants," Chemical Analysis,  Vol 10, Interscience
          Publishers, Inc., New York, N.Y.,  p 200.
12203 91  CHLORIDE-HI-VOL-THIOCYANATE
          Chloride in the aqueous extract of the hi-vol particulate
          sample forms mercuric chloride and liberates SCN  ion
          from mercuric thiocyanate.  The SCN~" ion forms a colored
          complex with Fe+++ ion from ferric ammonium sulfate.  The
          complex is measured colorimetrically at 416 nm.
          1.  R. B. Fisher, "Quantitative Chemical Analysis,"
          W. B. Saunders Co., Philadelphia, Pa. 1957, p 238.
          2.  Morgan, G. B., E. C. Tabor, C. Golden, and H. Clements,
          Automated Laboratory Procedure for the Analysis of Air
          Pollutants 66-p 108B, Technicon Industrial Systems,
          Tarrytown, N.Y., p 536.
12301 91  AMMONIUM - HI-VOL   NES'SLER
          Ammonium ion is .removed from an 8% aliquot of the filter by
          fluxing the filter in 50 ml of H^O for 30 min, then placed
          in a Nessler tube with 4 ml of Nessler reagent.  Should

-------
                              -  11

          the solution become cloudy, Rochelle salt solution (lOg of
          KNaC4H4Og,4H20 in 200 ml of .01N NaOH) is added dropwise
          with shaking.  The absorption is read using a No. 54 filter
          with a 50 ml glass cell, using a reagent blank as reference.
          (Rochelle salt prevents Ca and Mg precipitation at the high
          pH of the Nessler reagent).
          1.   M.  B.  Jacobs,  (1960),  "The Chemical  Analysis of Air
          Pollutants,"  Chemical  Analysis,  Vol  10,  Interscience
          Publishers,  Inc.,  New  York,  p  216.
          2.   G.  B. Morgan, E. C. Tabor, C. Golden, and H. Clements
          Automated Laboratory Procedures for the Analysis of Air
          Pollutants 66-p 108B,  Technicon Industrial Systems,
          Tarrytown, N. Y., p 536.

12301 92  AMMONIUM-HI-VOL   SODIUI1 PHENOLATE
          Ammonium ions are extracted from a 3/4 in. by 8 in. strip
          of the exposed filter by fluxing with 25 ml of H20.  The
          filtrate is diluted to 50 ml and sodium phenolate and
          sodium hypochlorite are added producing a blue complex when
          pH is above 7.0.  The absorbance is read spectrophotometrically
          at 626 nm.
          1.   Russell, J. A., (1944), "The Colorimetric Estimation
          of Small Amounts of Ammonia by the Phenol-Hypochlorite
          Reaction," J. Biol. Chem. 156, 457.
          2.   Morgan, G. B., E.  C. Tabor, C. Golden, and H. Clements,
          Automated Laboratory Procedure for the Analysis of Air
          Pollutants 66-p 108B,  Technicon Industrial Systems,
          Tarrytown, N. Y., p 536.
          3.   "Air Quality Data for 1967," EPA-APTD 0741,
          Office of Technical Information and Publication, Research
        .  Triangle Park, N.C., 1971, p 18.

-------
                                 12
12306 91  NITRATE-HI-VOL   2,4 XYLENOL
          Nitrate nitrates 2,4-xylenol,   The nitrated 2,4-xylenol
          is separated from other water soluble colored substances
          by NaOH and toluene.  A 3/4 in. strip of the filter is
          fluxed in 25 ml of H20, filtered (Whatman No. 1),  and washed
          until 50 ml of filtrate is obtained.  A 5 ml sample and
          15 ml of 85% H2SO are mixed, cooled, and 1 ml of 1% xylenol
          is added.  The solution is heated at 60°C for 0.5  h and
          diluted to 80 ml.  Then, 10 ml of toluene is added and the
          mixture is shaken for 2 min. in a separatory funnel.  The
          lower layer is discarded, 10 ml of 0.4N NaOH added, and
          the funnel again shaken for 5 min.  The lower aqueous layer
          is drawn through cotton into a cuvette.   The absorbance
          is measured at 435 nm.
          1.  "Selected Methods for the Measurement of Air Pollutants,"
          U.S.  Department of Health, Education, and Welfare  999-AP-
          11, Robert A. Taft Sanitary Engineering Center, Cincinnati,
          Ohio, May 1965, p 1-1.
          2.  Pate, J. B., E. C. Tabor,   (1962), "Analytical  Aspects
          of Glass Fiber Filters," Am. Ind. Hyg. Assoc. J. 23.
          3.  Barnes, H.,  (1950), "A Modified 2,4-Xylenol Method for
          Nitrate Estimation," Analyst 75, 388.
12306 92  NITRATE-HI-VOL   REDUCTION-DIAZO COUPLING
          The nitrate is reduced to nitrite by alkaline hydrazine,
          converted to HN02 which diazotizes sufanilamide, and coupled
          with N (Irnaphthyl)-ethylenediamine dihydrochloride which
          absorbs light at 535 nm.
          1.  Morgan, G. B., E. C. Tabor, C. Golden and H. Clements,
          Automated Laboratory Procedure for the Analysis of Air  .
          Pollutants 66, p 108B, Technicon Industrial System, .
          Tarrytown, N. Y., p 536.

-------
                                 13

          2.   "Air Quality Data for 1967," EPA-APTD 0741,
          Office of Technical Information and Publication,  Research
        '  Triangle Park, N.C., 1971, p 18.  .

12306 93  NITRATE-HI-VOL   SPECIFIC ION ELECTRODE
          The aqueous extract of a hi-vol glass fiber filter-is
          analyzed for nitrate ion by means of a specific ion
          electrode.

12345 91  PHOSPHATE - HI-VOL-MOLYBDATE •  STANNOUS CHLORIDE
          Phosphate ions in the water extract of the filter are
          precipitated as ammonium molybdophosphate in an acid
          medium, which is then reduced to a molybdenum blue com-
          plex with stannous chloride.  The absorbance is read at
          650 nm.
          1.   Water, Atmospheric Analysis,  (1971), "Annual Book of
          ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, pp 41-49.
          2.   Lundell, G. E. and J. I. Hoffman,  (1923), "Notes on
          the Determination of Phosphate," Ind. and Eng. Chem. Anal.
          Ed. 15, 71.
12403 91  SULFATE - HI-VOL   COLORIMETRIC
          Water soluble sulfate is reacted with excess reagent con-
          taining equivalent amounts of methylthymol blue and BaCl2.
          Ba++ and SOT ions form BaS04 leaving a  [SO^] equivalent
          of free methylthymol blue.  If the pH is changed from 2.8
          to 12.4 by KOH, Ba++ ion forms a chelate with the free dye.
          The unchelated dye is yellow and absorbs light at 460 nm.
          1.  Morgan, G. B., E. C. Tabor, C. Golden and H. Clements
          Automated Laboratory Procedure for the  Analysis of Air
          Pollutants 66, p 108B, Technicon Industrial Systems-
          Ta'rrytown, N. Y., p 538.

-------
                                 14
          2.  A. L. Lazrus, K. C. Hill and J. P. Lodge, "A New
          Coloriraetric Microdetermination of Sulfate Ion in Rainwater,"
          personal communication, Division o'f Atmospheric Sur-
          veillance, Research Triangle Park, N.C., 1965.
          3.  "Air Quality Data for 1967," EPA-APTD 0741,
          Office of Technical Information and Publication, Research
          Triangle Park, N.C., 1971, p 19.

12403 92  SULFATE-HI-VOL   TURBIDIMKTRIC
          The water soluble sulfate extract of the filter forms BaSO^
          in a Bad,, solution.  Suspended BaSO, particles scatter
                   ^                          ~x
          light, and the diminished intensity of a light beam is
          measured by a turbidimeter.
          An aliquot of the filter extract is chosen so that the
          sample contains the equivalent of 1 to 20 yg/m  of SOT.
          To the sample diluted to 20 ml, 1 ml of ION HC1 is added,
          followed by 4 ml of a glycerol/absolute ethanol solution
          (l:2v/v).  After mixing, the absorbance is measured at
          500 nm and compared with H~0.  Then 0.25g of BaCl^ crystals
          are added and shaken to dissolve the crystals.  After
          standing for 40 min. at 20°C, the absorbance is measured
          again.
          1.  "Selected Methods for the Measurement.of Air Pollutants,"
          U.S. Department of Health, Education, and Welfare 999 AP-11,
          Robert A. Taft Sanitary Engineering Center, Cincinnati, Ohio,
          May 1965, p 1-1.
          2.  Water, Atmospheric Analysis,  (1971), "Annual Book of
          ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, pp 50-53.
12602 91  HYDROGEN ION CONCENTRATION - HI-VOL   pH METER
          The water soluble extract of the filter is tested by a
          pH meter and the hydrogen ion is calculated from the pH
          value.

-------
                                 15

17242 91  BENZOCAJPYRENE - HI-VOL   THIN LAYER CHH01JZVTOGRAFHY
          This is a technique whereby the benzene soluble organics
          are separated by means of thin layer chromatography.  The
          isolated benzo(A)pyrene as indicated by comparison with a
          standard is removed from the thin layer plate and excited
          with radiant energy of 470 run.  The fluorescence is measured
          at 540 run.
          1.   Intersociety Committee, "Methods of Air Sampling and
          Analysis," American Public Health Association, Wash., D.C.,
          1972, p 159.

-------
                                 16
21101 51  TOTAL DUSTFALL - BUCKET   GRAVIMETRIC
          A 1 gallon container having a mouth diameter of 4.4 in.
          is placed in a copper can (5 in.  high and 5 in.  diameter)  on  a
          stand,C4 ft. above a roof  and four stories from the ground).
          Five hundred to 1500 ml of antifreeze-treated water is placed
          in the container.  The collected sample is filtered using
          Whatman No. 41H paper which is then dried and weighed.
          The filtrate is evaporated at 105°C, the residue weighed,
          and both weights added for total dustfall.
          1.  M. B. Jacobs, "The Chemical Analysis of Air Pollutants,"
          Chemical Analysis, Vol 10, Interscience Publishers, Inc.,
          New York, N.Y.,  (1960),  p 37.

21101 71  TOTAL DUSTFALL - BUCKET - GRAVIMETRIC (APCA)
          The dust falls into a glass or stainless steel container,
          5 in. in diameter and 10-15 in. high.  The top of the con-
          tainer is maintained at from 8 to 50 ft. above the ground
          and 4 ft. above any surface.  Neighboring roof surfaces
          must subtend an angle of 30° or less from the horizontal.
          Distilled water should be maintained in the container and
          a quaternary ammonium salt is added  (1 to 2 mg/1) to suppress
          algal growth.  Isopropyl alcohol may be added as antifreeze.
          The 30 day sample is filtered through a 20 mesh screen to
          remove extraneous material and treated as method 21101 51
          except that samples having antifreeze are evaporated to
          dryness at 105°C, 300 ml distilled water is added, and the
          sample again evaporated to dryness.
          1.  "Recommended Standard Method for Containing Dustfall
          Survey  (APMI-a)," (Nov. 1955), APCA Journal 5.  (No. 3),
          p 176.
21101 81  DUSTFALL - BUCKET   GRAVIMETRIC (ASTM)
          A 6 in. diameter/ 12-18 in. high,  glass, plastic/ or
          stainless steel cylinder, mounted with a bird ring, is

-------
                                 17
          use to collect the dustfall.  The analysis is the same as
          method 21101 71.
          1.  Water, Atmospheric. Analysis,  C1971), "Annual Book of
          ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, p 425.
          2.  Nader, J. S., (1958), "Dust Retention Efficiencies
          of Dustfall Collector," APCA Journal 8, p 35.

21102 81  ORGANIC FRACTION - BUCKET   GRAVIMETRIC (ASTM)
          The water insoluble residue and the filter from method
          21101 81 are dried, weighed, placed in a soxhlet apparatus,
          and extracted for 2 h using 50 ml of benzene.  Benzene
          should remain in the flask at all times.  The remaining
          residue and paper are dried at 105°C and weighed to
          report the v/eight loss as organic fraction, BSO  (benzene
          soluble organics).
          1.  Water, Atmospheric Analysis,  (1971), "Annual Book of
          ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, p 427.
21113 71  INORGANIC FRACTION •- BUCKET   GRAVIMETRIC  (APCA)

-------
                                 18
21113 81  INORGANIC FRACTION - BUCKET   GRAVIMETRIC (ASTM)
          The combined weight of water insolubles and soluble
          matter corrected for any solid present in a distilled water
          blank.
          1.   Water, Atmospheric Analysis, (1971), "Annual Book of
          ASTM Standards," American Society for Testing and Material,
          Philadelphia, Pa., Part 23, p 428.

21114 71  WATER SOLUBLE WEIGHT - BUCKET   GRAVIMETRIC (APCA)
          The sample is filtered through a 20 mesh screen to remove
          extraneous material and if antifreeze'was used, the filtrate
          is evaporated to dryness over a steam bath or in an oven
          at 105°C.  Thirty ml of distilled H-O is added, heated to
          boil, and the sample filtered through an alundum crucible.
          If no antifreeze was used, the sample is adjusted to 300
          ml and filtered through the crucible.  The filtrate is
          evaporated to a small volume.  The filtrate is placed in
          a weighed platinum crucible  (if fluoride is present) or
          else a borosilicate dish and evaporated to 25 ml.  It is
          evaporated slowly to dryness on a steam bath or in an oven
          at 105°C.  Dryings are repeated for 3 h periods until
          constant weight is obtained.
          1.   "Recommended Standard Method for Continuing Dustfall
          Survey,  (APMI-a)," (Nov. 1955), APCA Journal 5 (No. 3), 177.
21114 81  WATER SOLUBLE WEIGHT - BUCKET   GRAVIMETRIC (ASTM)
          The soluble material, described as the water soluble weight
          in method 21101 81,is evaporated in a tared platinum dish if
          fluoride or caustic materials are present or else a boro-
          silicate dish.  The dish is heated slowly until 25 ml
          remain.  Then a steam bath or a thermoregulated hot plate
          is used to evaporate to dryness at a temperature of 99°C.
          Drying is continued in an oven at 105°C until a constant

-------
                                 19
          weight is obtained.  The water soluble weight is the
          difference between this constant weight and tare.
        •  1.  Water, Atmospheric Analysis, (1971),  "Annual Book
          of ASTM Standards," American Society for Testing and
          Materials, Philadelphia,  Pa.,  Part  23, p 427.

21115 51  WATER INSOLUBLE WEIGHT - BUCKET   JACOBS METHOD
          The collected sample is filtered through a 20 mesh sieve,
          and the coarse material discarded.   The insoluble material
          in the sample is collected on a 9 cm Whatman No. 41 H
          filter.  Alternatively, a tared gooch crucible equipped with
          a light asbestos mat or an alundum  crucible could be used.
          The v/eight of the dry solid is reported as water in;-
          soluble weight.
          1.  M. B.  Jacobs, (1960), "The Chemical Analysis of Air
          Pollutants,"  Chemical Analysis, Vol 10, Interscience Publishers
          Inc.,  New York, N.Y., p 38.

21115 71  WATER INSOLUBLE WEIGHT - BUCKET   GRAVIMETRIC  (APCA)
          The water soluble weight was obtained to report the total
          dustfall, method 21101 71.  The sample is filtered
          through a 20 mesh screen, the volume made to 300 ml, boiled,
          and filtered through a weighed 35 ml alundum filter crucible.
          The crucible is dried in an oven at 105°C for 3 h, cooled,
          and the drying is repeated to constant weight.  The increased
          weight of the crucible is reported as water insoluble weight.
          1.  "Recommended Standard Method for Continuing Dustfall
          Survey (APMI-a), (Nov. 1955), APCA Journal 5  (No. 3), 176.
21115 81  WATER INSOLUBLE WEIGHT - BUCKET   GRAVIMETRIC  (ASTM)
          The material collected on a dried and weighed filter from
          method 21101 81, is dried in a weighing bottle overnight
          at 105°C.  The net weight less the weight of the filter
          paper and weighing bottle is the water insoluble weight.

-------
                                20
          1.  Water, Atmospheric Analysis, (.1971) , "Annual Book
          of ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 213, p 427.

21116 71  TOTAL WEIGHT ASH - BUCKET   GRAVIMETRIC  (APCA)
          The water insolubles and the water solubles are ignited
          in a dish at red heat for 20 to 30 min, cooled in a
          desiccator, reheated and cooled until a constant weight
          is obtained.  The dish must have been pretreated in the
          same manner.  The excess weight is the total weight ash.
          1.  M. B. Jacobs,  (1960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Interscience
          Publishers Inc., New York, N.Y., p 47.
21116 81  TOTAL WEIGHT ASH - BUCKET   GRAVIMETRIC  (ASTM)
          The total weight ash is the weight of the insoluble and
          soluble materials after the removal of BSO and the com-
          bustible materials.

-------
                                 21
22114 92, 22126 92, 22132 92, and 22136 92
          COPPER, IRON, MANGANESE, NICKEL - BUCKET   ATOMIC ABSORPTION
          Thirty ml of HN03/H20 (1/1) is added to the dustfall
          in a beaker, heated below boiling for 1 h, and concentrated
          to remove excess HNO.,.  The solids are removed by
          centrifuging.  The solution is analyzed by AA.
          1.  Water, Atmospheric Analysis,  (1971), "Annual Book of
          ASTM Standards/" American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, p 678.

22403 81  SULFATES - BUCKET   TURBIDIHETRIC (ASTM)
          Turbid samples are filtered and the temperature adjusted
          to between 15 and 30°C.   Ten ml glycerin solution (glycerin/
          H20, 1/1), and 5 ml of NaCl solution  (240g of NaCl and 20 ml
          cone. HCl/liter)  are added to 50 ml of the sample.  A 40 mm
          cell filled with the treated sample is used as the blank
          sample by setting the colorimeter to zero absorbance at 380-
          400 nm.  The cell sample is combined with the remaining
          treated sample, 0.3g of BaCl2.2H20 crystals added, and the
          mixture stirred for 1 min.  After standing for 4 min the
          mixture is stirred again for 15 sec.  The cell is then
          filled with the turbid solution and absorbance measured
          again at the same wavelength as the blank sample.
          1.  Water, Atmospheric Analysis,  (1971), "Annual Book of
          ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, p 51.
22602 81  pH (DUSTFALL) - BUCKET   pH METER
          Total acidity of the water soluble portion of the total dust-
          fall is obtained by using a pH meter, or less accurately
          by use of pH test paper.
          1.   M.  B.  Jacobs,  (1960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Interscience Publishers,
          Inc.,  New York,  N.Y., p 40.

-------
                                 22

25101 81  DUSTFALL COMBUSTIBLE-BUCKET   GRAVIMETRIC - 500-DEG.
          C. LOSS (ASTH)
          After the BSO has been remove from the water insoluble
          material,  the material and the filter paper are ashed at
          500°C in a tared crucible and the weight loss is reported as,
          "Combustibles and volatile particulates oi,ier than benzene
          soluble."
          1.  Water,  Atmospheric Analysis,  (1971), "Annual Book of
          ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa.,  Part 23,  p 428.

-------
                                 23
 42101 11  CARBON MONOXIDE - INSTRUMENTAL   NON-DISPERSIVE INFRA-RED
           The principle is described in Vol,3G..  No.  228  of the
           Federal Register.  The major interference  is  H20 vapor
           which can be minimized by drying the air sample before
           it enters the cell.   Calibrated gases  and  a narrowband
           optical filter are essential.  Variations  in  temperature
           and pressure affect the instrument response and should
           be controlled.  Filters of 2-10 ym porosity should be
           used in the entering air stream to remove  fine particulates
           1.  "Rules and Regulations," Federal Register, Vol 36,
           No. 228,  (Nov. 25, 1971), p 22391.
42101 12  CARBON MONOXIDE - INSTRUMENTAL   COULOMETRIC
          Atmospheric air is drawn through a heated 1205 tube
          and 12 is liberated.  The gas containing ^ is directed
          into an electrochemical cell where I2 is reduced to
          iodide coulometrically.
          1.  Beckman Instrumention, Bulletin 3000 4411-4,
          Beckman Instruments, Inc., Fullerton, California.
42101 21  CARBON MONOXIDE - INSTRUMENTAL   FLAME IONIZATION
          Ambient air is introduced into two gas chromatographic
          columns in series, the first of which retains most
          pollutants except CO and CH4, and the second of which
          passes only CO.  The CO is then led over a Ni catalyst
          where it is converted to CH4.  The CH4 is passed into
          a flame ionization detector, where the resulting measured
          current can be related to the initial CO concentration
          of the ambient air.  See also.43102 11 and 43201 11.
          1.   "Rules and Regulations," Federal Register, Vol 36,
          No.  228,  (Nov. 25, 1S71),  p 22391.

42102 .11  CARBON DIOXIDE-INSTRUMENTAL   INFRARED ABSORPTION
          This procedure is similar  to the NDIR procedure for carbon
          monoxide,  42101 11,  except that water does not have to
          be  removed from the air stream.

-------
42401 11  SULFUR DIOXIDE-INSTRUMENTAL   WEST-GAEKE  COLORIMETER
          A continuous analyzing system is set up so that the
          ambient air flows through a glass spiral absorption column
          concurrently with 0.02M sodium tetrachloromercurate.
          Dichlorosulfitomercurate ion is formed, reacted with
          acid-bleached pararosaniline and formaldehyde to produce
          a red-purple pararosaniline methylsulfonic acid which
          is quantitatively measured colorimetrically.   The 95%
          baseline is established with pure reagents for 1 h and
          the instrument is then calibrated.   Air flow rate and
          reagent flow rate must be calibrated and maintained
          accurately.
          1.  Yunghans, R.  S.  and W. A. Monroe, Technicon Symposium
          on Automation in Analytical Chem.,  1965,  p 279.
          2.  "Technicon Air Pollution Detection System," In-
          struction Manuals T 67-105, Technicon Corp.

42401 13  SULFUR DIOXIDE-INSTRUMENTAL   CONDUCTIMETRIC
          Sulfur dioxide is absorbed in acidic H-O- which oxidizes
          it to II-SO,.  The method is a measure of all materials
          that increase conductivity.  Thus,  any materials that
          alter the conductivity of the reagent are potential in-
          terfering agents.
          1.  Beckman Air Quality Acralyzer Operating and Service
          Manual, Scientific and Process Inst. Div., Fullerton,
          California, 16TW352, (Aug. 1966).
          2.  Thomas, M.D., (1932), "Automatic Apparatus for the
          Determination of Small Concentrations of Sulfur Dioxide
          in Air," Anal. Chem. 4, 253.
          3.   M.  B.  Jacobs,  (I960),  "The Chemical Analysis of Air
          Pollutants," Chemical Analysis,  Vol  10, Interscience  Publishers
          Inc.,  New York, N.Y., p 394.
          4.  Water, Atmospheric Analysis, (1971), "Annual Book of
          ASTM Standards," American Society for Testing and Materials,
          Philadelphia, Pa., Part 23, p 272.

42401 14  SULFUR DIOXIDE-INSTRUMENTAL   COULOMETRIC
          Coulometric analyzers measure the current necessary to
          maintain a halogen concentration (Br2 or 12)  constant in
          the sample cell.  The magnitude of this current is pro-
          portional to the amount of absorbed SO?.  There are several

-------
                                 25
          versions of instruments using this principle.
          1.   J.  F. Welcher,  "Standard Methods of Chemical Analysis,"
          D.  Van Nostrand Company, Inc. Princeton, N.J.,  1966,
          P 377.

42401 15  SULFUR DIOXIDE-INSTRUMENTAL  : THOMAS AUTOMETER
          The Thomas Autometer is a conductimetric analyzer de-
          veloped in 1929.

42401 16  SULFUR DIOXIDE-INSTRUMENTAL  FLAME PHOTOMETRIC
          Chromatographic columns are used to separate S02, H2S,
          CS,,, and CH..SH.  Effluent from the columns is burned in
          a hydrogen-rich flame where a 395 nm emission band
          characteristic of sulfur is created.  A photomultiplier
          tube is used to detect the luminescence.  Response is linear
          on a log-log scale.
          1.   H. H. Willard,  L. L. Merritt, and J. A. Dean, "In-
          strumental Methods  of Analysis," D. Van Nostrand Company,
          Inc., 4th Edition,  1965, p 309.

42401 31  SULFUR DIOXIDE-DAVIS INSTRUMENT   HYDROGEN PEROXIDE
          The Davis instrument is a conductimetric instrument, and
          as such, it is much like method 42401 13.  There are
          several models in use.

42401 33  SULFUR DIOXIDE-DAVIS INSTRUMENT   SEQUENTIAL-CONDUCTIMETRIC
          Water is deionized by passage through an amberliet resin
          column, then its conductivity is measured.  Ambient air,
          having first passed through a scrubber of amberlite re-
          sin and soda-lime to remove C02, is next passed through
 . . '.      the deionized water where the S02 is absorbed.  The in-
          creased conductivity of the water is a measure of the
          S02 concentration of the air.
          1.   Thomas, M. D. and J, N. Abersold,  (1929), "Automatic
          Apparatus for the Determination of Small Concentrations
          of Sulfur Dioxide in Air," Anal. Chem. 1, 14.

-------
                                 26
42401 91  SULFUR DIOXIDE-GAS BUBBLER   WEST-GAEKE  SULFAMIC ACID
          The method is described in Vol 36, No. 228 of the Federal
          Register.  (The NASN procedure, however,  -uses 1.725 g/1
          sulfamic acid rather than 6 g/1 and does not use EDTA).
          The sulfamic acid eliminates interference from oxides of
          nitrogen.  Sulfur dioxide is collected in a tetra-
          chlororaercurate solution,  forming a stable dichlorosulfito-
          mercurate complex.  When acid-bleached pararosaniline
          is added to the collected S02 together with formaldehyde,
          the amino groups  (-NH,) form a red-violet compound called
          pararosaniline methylsulfonic acid which is measured spec-
          trophotometrically.
          1.  West, P. W. and G. C.  Gaeke,  (1956), "Fixation of
          Sulfur Dioxide as Disulfito-Mercurate (II) and Subsequent
          Colorimetric Estimation," Anal. Chem. 28, 1819.
          2.  "Rules and Regulations," Federal Register, Vol 36,
          No. 228, U.S. Government Printing Office, Washington, D.C.,
          (Nov. 25, 1971), p 22385.
          3.  Intersociety Committee, "Methods of Air Sampling and
          Analysis," American Public Health Association, Washington, D.C.,
          1972, p 447.
          4.  "Air Quality Data for 1967," EPA-APTD 0741, Office of
          Technical Information and Publication, Research Triangle
          Park, N.C., 1971, p 20.
42401 92  SULFUR DIOXIDE-GAS BUBBLER   WEST-GAEKE
          This method is similar to method 42401 91 except that the
          sample absorbing reagent is 0.1M TCM, the starch which is
          used for standardization is made without mercuric iodide,
          and sulfamic acid is not used except when high concen-
         • trations of N07 are expected.  The sulfamic acid is added
          to the sample after collection.

-------
                                  27
           1.  "Selected Methods for the Measurement of Air Pollutants",
           U.S. Department of Health/ Education, and Welfare 999 AP-
           11, Robert A. Taft Sanitary Engineering Center, Cincinnati,
           Ohio, May 1965, p A-l.
           2.  Nauman, R. V., et al.,  (1960) , Anal Chem. 32, 1307.
           3.  West, P.W. and F. .Ordoveza,  (1962), Anal. Chem. 34,
           1324.
 42401 93  SULFUR DIOXIDE-GAS BUBBLER   CONDUCTIMETRIC
           Manual conducttmetric methods use the same principles as
           instrumental conductimetric except the absorber  is a
           multiple  jet bubbler system and  the  sampling  is  not con-
           tinuous.  The details are described  in the reference.
           1.   Intersociety Committee, "Methods of Air Sampling
           and  Analysis," American  Public Health Association,
           Washington, D.C., 1972,.p 456.
42402 71  HYDROGEN SULFIDE-TAPE SAMPLER   AISI LEAD ACETATE PAPER
          Filter paper (Whatman, No. 1) is  cut  into 2 by 4  in. strips,
          impregnated with Pb(C2H302)  (10g/100  ml H2O plus  5 ml
          CE-COOH) .and dried in H2S free air.   Air is pumped over the
          strips.  A concentration of 0.025 mg/1 of H~S  gives a
          positive test for H2S.  The stain on  the paper is com-
          pared with a color chart for H2S  concentration.
          1.   M. B. Jacobs,  (1960),  "The Analytical Chemistry of Indus
          trial Poisons,  Hazards,  and Solvents," Chemical Analysis,
          Vol 1, Interscience Publishers,  Inc.,  New York, N.Y.,
          P 108.
42402 91  HYDROGEN SULFIDE-GAS BUBBLER
          (100 ml tube + orifice)
METHYLENE BLUE
          Air is bubbled through a Cd(OH)2 solution in a large im-
          pinger at 1 cfm for 30 min.  Ferric chloride solution and
          p-aminodimethylaniline test solution are added to the im-
          pinger and agitated.  The sample is diluted and allowed to
          stand for 30 min.  The sulfide ion forms a methylene blue
          complex.   The absorbance of the sample is compared with a
          standard  which consists of 45 ml of the Cd(OH)2 solution,
          amine test solution, and the ferric chloride.

-------
          1.   Inter society Committee, "Methods of Air Sampling
          and Analysis," American Public Health Association,
          Washington, D.C., 1972, p 426.
          2.   M.  B. Jacobs, (1960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Interscience
          Publishers, Inc, New York, N.Y., p 185.
          3.   Lodge, J.  P., et al.,  (1966), "The Use of Hypodermic
          Needles as Critical Orifice," J. Air Poll. Control Assoc.
          X6, 197.
          4.   Scaringelli, F. P., S. A. Frey, B. E. Saltzman, (1967),
          "Evaluation of Teflon Permeation Tubes for use with
          Sulfur Dioxide," Am. Ind. Hyg. Assoc. J. 28, 260.

42-410 71  SULFATION RATE-LEAD PLATE   GRAVIMETRIC (HUEY)
          The Pb02 is converted to PbSO, by the SO2 in the ambient
          air and the SOT is removed by Ma-CO., and boiling H20.
          Barium chloride is used to precipitate the SOT as BaSO,.
          The dried BaSO, is weighed and the SO- equivalence is
          reported.

-------
                                 29
42410 72  SULFATION RATE-LEAD PLATE   COLORLMETRIC (HUEY)
42410 73  SULFATION RATE-LEAD PLATE   TURBIDIMETRIC  (HUEY)
          Sulfur dioxide reacts with lead peroxide to form lead
          sulfate.  The amount of SOT formation per unit time is
          the sulfation rate.  The SOT is removed from the plate
          by boiling Na-CO., solution and the pH is adjusted between'
          2.5 and 4.0 so that sulfaspend or sulfaver precipitates
          the SOT.  The absorbance of the stirred precipitate is
          read at 450 nm, turbidimetrically.
          1.  Intersociety Committee, "Methods of Air Sampling and
          Analysis," American Public Health Association, Wash., D.C.,
          1972, p 442.
          2.  Huey, N. A., M. A. Wallar, and C. D. Robson,
          (June 1969) "Field Evaluation of an Improved Sulfation
          Measurement System."  Paper No. 69-133, Air Pollution
          Control Association Annual Meeting.
          3.  Hickey, H. R., and E. R. Hendrickson,  (1965), "A
          Design Basis for Lead Dioxide Cylinder," J. Air Poll.
          Control Assoc. 15, 409.

-------
                                  30
42410 74  SULFATION RATE-LEAD PLATE   POTASSIUM CARBONATE (HUEY)
          This method is similar to method 42410 73 except K2C03
          is used instead of Na
42410 81  SULFATION RATE-RAC CANDLE   GRAVIMETRIC
42410 "91  SULFATION RATE-LEAD CANDLE   GRAVIMETRIC (MASN)
          The lead candle functions on the same principle as the
          lead plate.  Sulfation is reported as mg of S03/100 sq.
          cm/day as determined by gravimetric precipitation of
          BaSO,.  The procedure is spelled out in the report by
          Keagy, et.al.
          1.  Thomas, F. W. and C. M. Davidson, "Monitoring Sulfur
          Dioxide with Lead Peroxide Cylinders" presented at the
          53rd Meeting of APCA,  Cincinnati, Ohio,  May 22-26, 1960.
          2.  Keagy, D. M., et.al., "Sampling Stations and Time
          Required for Urban Air Pollution Surveys, Part I:  Lead
          Peroxide and Dustfall Collectors," Presented at the
          53rd Meeting of APCA,  Cincinnati, Ohio,  May 22-26, 1960.

42410 93  SULFATION RATE-LEAD CANDLE   TITRIMETRIC (NASN)
          This method is similar to method 42410 91 except that
          excess BaCl^ is added when the pll is 3 and the excess
          titrated with EDTA using Eriochrome Black T as indicator.

-------
                                 31
          1.  Wilsdon, B. H. and F. J. McConnel, C1934), "The
          Measurement of Atmospheric Sulfur Pollution by Means
          of Lead Peroxide, JV SocV Chem. TridV 53,  385,
          2.  Kainzer, A.,  (1957), Zemeht-Kalk-Gyis 10, 281.
          3.  "Standard Methods for the Examination of Water and
          Waste-water," 12th Ed., American Public Health Assoc.,
          Inc., Nev/ York, N. Y., 1965, p 147-151.

42410 94  SULFATION.RATE-LEAD CANDLE   POTASSIUM CARBONATE  (NASN)
          This method substitutes K-CO., for Na2C03 in method
          42410 91.

42410 95  SULFATION RATE-LEAD CANDLE   TURBIDIMETRIC
          Gaseous and particulate fluoride in ambient air are
          collected by filtration and chemisorption on filter
          paper impregnated with sodium formate.  Water soluble
          fluorides are extracted from the filter,  made basic
          with Na-CO.,, and complexed with citrate ion to reduce
          the iron and aluminum interference.  The fluoride ion
          concentration is measured with a specific ion electrode.
          1.  Thompson, R. J., T. B. McMullen and G. B. Morgan,
          (1971), "Fluoride Concentrations in the Ambient Air,"
          J. Air Poll. Control Assoc. 21, 484.
42513 91  FLUORIDE HI-VOL   SPECIFIC ION ELECTRODE
          The concentration of fluoride in an aqueous sample is
          measured by means of the fluoride-specific ion electrode.
          1.  Elfers, L. A. and Decker, C. E.,  (1968), Anal. Chem.,
          Vol. 40, p 1658.
          2.  Frant,  M.  S. and J.  W.  Ross, Jr., (1966),  "Electrode for
          Sensing Fluoride Ion Activity in Solution," Science 154,
          1553.

-------
                                 32
42601-11  NITRIC OXIDE-INSTRUMENTAL   COLORIMETRIC
          NO is converted to N02 by passing the ambient air through
          an aqueous KMnO. solution.  The resulting N0? is measured-
          colorimetrically.  An independent measurement of the ambient
          N02 concentration is required.  This value, subtracted
          from the first, gives a value for the NO concentration.  See
          Methods 42602 11 and 42602 12 for HO  measurement procedure.
          1.  Water, Atmospheric Analysis, (1971), "Annual Book
          of ASTM Standards," American Society for Testing and
          Materials," Philadelphia, Pa., Part 23, p 523.
          2.  Rogers, L. M. , (1958), "Nitric Oxide and Nitrogen
          Dioxide in the Los Angeles Atmosphere," J.  of Air Poll.
          Control Assoc. 8, 124.
          3.  Saltzman, B. E. ,   (1954), "Colorimetric Micro-Determination
          of Nitrogen Oxide in the Atmosphere, Anal.  Chem. ,26,  1949.
          4.  Thomas, M. D., et.al., (1956), Automatic Apparatus
          for Determination of Nitric Oxide and Nitrogen Dioxide
          in the Atmosphere, Anal. Chem. 28, 1810.
42601 14  NITRIC OXIDE-INSTRUMENTAL
          When 0., reacts with NO to form N02,
                            CHEMILUMINESCENCE
                                    some of the liberated
energy appears in the form of light of 600-875 nm.  The
reaction is extremely rapid.  The instrument generates
an excess of 03 such that the quantity of light emitted
from the reaction and measured by the instrument, is a
direct measure of the NO concentration in the sampled
air.  See also 42602 14.
1.  Fontijn, A., A. J. Sabadell and J. R. Ronco,  (1970),
Anal. Chem. 42, 575.
2.  Stevens, R. K., et.al., "Field Performance Characteristics
of Advanced Monitors for Oxides of Nitrogen, Ozone, Sulfur
Dioxide, Carbon Monoxide, Methane, and Nonmethane Hydro-
carbons," Environmental Protection Agency, Research Triangle
Park, N.C., presented at the APCA Meeting, June 1972.

-------
                                 33
42601 91  NITRIC OXIDE-GAS BUBBLER   SALTZMAN (.100 Ml TUBE + ORIFICD
          Nitrogen oxide is oxidized to NO- by KMnO. and the
          Method 42602 72 is followed.
          1.  Intersociety Committee, "Methods of Air Sampling
          and Analysis," American Public Health.Association,
          Wash., D.C., 1972, p 329.

42602 11  NITROGEN DIOXIDE-INSTRUMENTAL   COLORIMETRIC
          The Lyshkow modification of the Criess-Saltzman reagent
          is used in various continuous N02 analyzers.  Users
          should consult the manufacturer's literature for details
          of reagent preparation.
          1.  "Rules and Regulations" Federal Register, Vol 38,
          No. 110, USGPO Wash., D.C.,  (June 8,  1973), p 15176.
          2.  Lyshkow, N. A.,  (1965), "A Rapid  Sensitive Coloriinetric
          Reagent for Nitrogen Dioxide in Air" j. Air Poll.'Control
          Assoc. 15  (No. 10)  481.

42602 12  NITROGEN DIOXIDE-INSTRUMENTAL'   COLORIMETRIC
          The original Griess-Saltzman reagent  is used in various
          continuous NO~ analyzers.  Users should consult the
          manufacturer's literature  for details of  reagent pre-
          paration.
          1.  "Rules and Regulation," Federal Register, Vol 38,
          No. 110, USGPO, Wash.,  D.C., (June 8, 1973) p 15176.
          2.  Saltzman, B. E., (1954) "Colorimetric Micro-Determination
          of Nitrogen Dioxide in the Atmosphere," Anal. Chem. 25,
          1949.

-------
42602 13  NITROGEN DIOXIDE-INSTRUMENTAL   COULOMETRIC
          Nitrogen dioxide is absorbed in a buffered iodide-iodine
          solution causing the equilibrium between iodine and iodide
          to be unbalanced.  The current required to re-establish
          the equilibrium is a measure of the N02 concentration.

42602 14  NITROGEN DIOXIDE-INSTRUMENTAL   CHEMILUMINESCENCE
          The nitrogen dioxide is drawn over a gold catalytic con-
          verter which reduces N02 to NO.  The NO is then analyzed
          by method 42601 14.
          1.  NO/NOX/N02 Analyzer Bulletin, Bulletin 4133, Beckman
          Instruments, Inc., Fullerton, Calif.
42602 71
42602 72
NITROGEN DIOXIDE-GAS BUBBLER'
TUBE + ORIFICE
JACOBS-HOCHHJ3ISSR-50 Ml
The method  is  that  described  in  the  Federal  Register.
The N02  is  converted  to NO" in NaOH  solution.   The
collection  efficiency is  a function  of  the N02  con-
centration  and high concentrations of NO  interfere.
1.  "Rules  and Regulations,"  Federal Register,  Vol  36,
No. 228,  U.S.  Government  Printing Office, Washington, D.C.
 (Nov.  25, 1971),  p  22396.
NITROGEN DIOXIDE-GAS  BUBBLER   SALTZMAN (50 Ml  TUBE + ORIFICE)
The sample  is  absorbed in the Griess-Saltzman reagent
and after 15 min the  stable pink color is measured
colorimetrically at 550 nm.
1.  Intercocisty Committee, "Methods of Air Sampling and
Analysis," American Public Health Association, Washington,
D.C.,  1972,  p  329.
2.  Saltzman, B.  E.,  (1954),  "Colorimetric Micro-Determination
of Nitrogen in the Atmosphere," Anal. Chem.  2G, 1949.

-------
42602 91  NITROGEN DIOXIDE-GAS BUBBLER   JACOBS-HOCHHEISER (106
          Ml TUBE + FRIT)
          A fritted bubbler and 100 ml tube, instead of a glass
          tube orifice and 50 ml tube, makes this method different
          from method 42602 71.  The disadvantages of the method
          still apply.
          1.  "Selected Methods for the Measurement of Air Pollutants,"
          U.S. Department of Health, Education, and Welfare 999-
          AP-11, Robert A. Taft Sanitary Engineering Center,
          Cincinnati, Ohio, May 1965, p C-4.
          2.  Purdue, L. J., et.al.,  (1972), "Reinvestigation
          of the Jacobs-Hochheiser Procedure for Determining
          Nitrogen Dioxide in Ambient Air,;i Environ. Sci. and Tech. 6 ,
          152.

42602 94  NITROGEN DIOXIDE-GAS BUBBLER    NASM-SODIUM  ARSEHITE-FRIT
          The method is much like method 42602 91 except for the
          absorber (l.Og of NaAs02 and 4.Og of NaOH diluted to one
          liter with distilled H20).  The NaAs02 increases the N02
          collection efficiency, but NO still interferes.
          1.  Christie, A. A., R. G. Lidzey, and D. W. F. Radford,
          (1970), "Field Methods for the Determination of Nitrogen
          Dioxide in Air." Analyst 95, 519.
          2.  Merryman, E. L., et.al., "Effects of NO, C02, CH4, H20
          and Sodium Arsenite on NO- Analysis," presented at the
          Second Conference on Natural Gas Research and Technology.
          Atlanta, Georgia, June 5, 1972.
          3.   "Selected Methods for the Measurement of Air Pollutants,"
          U.S.  Department of Health,  Education,  and'Welfare 999-
          AP-11,  Robert A.  Taft Sanitary Engineering Center,
          Cincinnati, Ohio, May 1965,  p C-4.                "         .  ...

-------
                                                                        u
42603 11  OXIDES OF NITROGEN-INSTRUMENTAL   COLORIMETRIC
          The total oxides of nitrogen  (NO + N0~)  are measured
                                                "
          by the methods 42601 11 and 42602 12.  The instrument
          reports the total as NO  (total oxides of nitrogen).
                                 ^*     ' *-
          1.  Intersociety Committee, "Methods of Air Sampling
          and Analysis," American Public Health Association,
          Wash., D.C., 1972, p 325.

42604 91  AMMONIA-GAS BUBBLER'   NESSLER REAGENT-50 Ml TUBS + ORIFICE
          Ammonia reacts with the alkaline HgI2.2KI solution
          (Nessler reagent) to produce an orange colored complex
          that is measured colorimetrically at 400 to 425 nm.   The
          absorbing solution (3.27N H-SO.) is returned to the
          laboratory after the sampling period and Nessler reagent
          added, (lOOg of Hgl^, 70g of KI dissolved in minimum
          of H20, 160g of NaOH/500 ml, mixed when cooled and
          diluted to one liter).  Rochelle salt (0.5g of
          KNaC4H4Og.4H20/ml) is added to prevent Ca and Mg pre-
          cipitation.
          1.  M. B. Jacobs, (1960),  "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Interscience
          Publishers, Inc., New York, N. Y. , p 216.
          2.  Morgan, G. B., E. C. Tabor, C. Golden, and H. Clements
          Automated, Laboratory Procedure for the Analysis of Air
                   I
          Pollutants 66-p 108B, Technicon Industrial System,
          Tarrytown, N. Y., p 538.
          3.   Water,  Atmospheric Analysis,  (1971),  "Annual
          Book of ASTM Standards," American Society for Testing
          and  Materials,  Philadelphia,  Pa.,  Part 23,  p 236-331.

-------
                                37
42604 92  AMMONIA-GAS BUBBLER-SODIUM PHENOLATE
          The chemical principle used is the same as method
          12301 92.  Ammonia is collected in 0.0504 N H~S04 as
          (NH.)?S04 producing a blue complex with sodium
          phenolate and sodium hypqchlorite.
          1.   Russell, J.  A., (1944), "The Colorimetric Estimation
          of Small Amounts of Ammonia by the Phenol-Hypochlorite
          Reaction," J.  Biol. Chem.,  156, 457.

-------
                                38
43101' 11  TOTAL HYDROCARBONS-INSTRUMENTAL   FLAMF.
          Ambient air is passed into the, instrument where, the
          organic compounds present are burned in a hydrogen-rich
          flame.  A sensitive electrometer coupled with a
          recorder measures the current resulting from the
          ions produced in the flame.  The response is
          approximately proportional to the number of carbon
          atoms in the sample.  The analyzer is calibrated using
          methane and the results are reported as methane
          equivalents.
          1.  Intersociety Committee, "Methods of Air Sampling
          and Analysis," American Public Health Association,
          Wash., B.C., 1972, p 184.
          2. "Rules and Regulations," Federal Register,
          Vol 36, No. 228, U.S. Government Printing Office,
          Wash., D.C., (Nov. 25, 1971), p 22394.
43102 11  NONMETHANE HYDROCARBONS-INSTRUMENTAL   FLAME IONIZATION
          Measured volumes of air are delivered semicontinuously
          (4-12 times per hour) to a hydrogen flame ionization
          detector to measure its total hydrocarbon (THC) content.
          An aliquot of the same air sample is introduced into
          a stripper column which removes H?0, CO- and hydro-
          carbons other than CH..  CH, and CO are passed
          to a  gas chromatographic column where
          they are separated.  The CH4 is eluted first, and
          is measured by the flame ionization detector.  This
          value subtracted from that for THC results in a
          measure of the non-methane hydrocarbon (NMHC) concen-
          tration of the sampled air.  See also 42101 21.
        •  1.  "Rules and Regulations," Federal Register, Vol 36,
          No. 228, (.Nov. 25, 1971}, p 22394.

-------
                                39
43201 11  METHANE-INSTRUMENTAL-   FLAME IONIZATION
          A stripper chroroatographic column  (charcoal) is used to
          remove BUO, C02f and hydrocarbons other than CH..
          Methane and CO are then separated by a gas chromato-
          graphic column and the CH. measured by a hydrogen
          flame ionization detector.
          1.  Water, Atmospheric Analysis, (1971), "Annual Book
          of ASTM Standards," American Society for Testing
          and Materials, Philadelphia, Pa., Part 23, p 783.
          2.  "Rules and Regulations," Federal Register, Vol 36,
          No. 228, U.S. Government Printing Office, Wash., D.C.,
          (Nov. 25, 1971), p 22394.
          3.  Ortman, G. C., (1966), Anal. Chem. 36, 644.

43501 11  ALDEHYDE-INSTRUMENTAL   COLORIIIETRIC
          This method is an automated MBTH technique.  See 43501 91.
43501 91  ALDEHYDE-GAS BUBBLER   MBTH
          Water soluble aliphatic aldehydes  (measured as formalydehyde,
          HCHO) in the ambient air are measured using an aqueous
          3- methyl - 2- benzothiazolone hydrazone hydrochloride
          (MBTH) which forms an azine.  The excess MBTH is
          oxidized with ferric chloride and reacts with the azine
          to form a blue cationic dye in acidic media, measurable
          at 628 nm, colorimetrically.
          1.  "Selected Methods for the Measurement of Air Pollutants,"
          U.S. Department of Health, Education, and Welfare, 999-AP-ll,
          Robert A. Taft Sanitary Engineering Center, Cincinnati, Ohio,
          May 1965, p F-l.
          2.  Sawicki, E., et.al.,  (1951), Anal. Chem. 33, p 93.
          3.  Hauser, T. R. and R. L. Cummins,  (1964) ibid., 36, 679.
          4.  "Air Quality Data for 1967," EPA-APTD-0741, Office
          of Technical Information and Publication, Research Triangle
          Park, N.C., 1971, p 20.

-------
                                 40
 44101 11  TOTAL OXIDANT-INSTRUMENTAL-ALKALINE KI
           Oxidants in ambient air are absorbed in an alkaline
           KI solution.   On acidification,  iodine is liberated
           and measured colorimetrically.
44101 13  TOTAL OXIDANTS-INSTRUMENTAL  - MAST MODEL 742-2
          Air is drawn over electrodes at a controlled rate to-
          gether with a continuous stream of fresh electrolyte.
          Hydrogen is maintained on the working electrode by a
          polarizing voltage.  Oxidants convert I  to I2 which
          reacts with the H9 ,* thus depolarizing the electrode.
                           c*   \
          The current required to repolarize the electrode is a
          measure of the oxidant concentration of the sample.
          1.  Mast, G. M. and H0 E. Saunders,(Oct. 1962), "Research
          and Development of the Instrumentation of Ozone Sensing,"
          Instrume'rtt Soc.' of 'Amer. Trann., 1, 375.
          2.  Bufalini, J. J. , (1968), "Gas Phase Titration of
          Atmospheric Ozone," Environ Sci Technol 2, 703.
          3.  Wartburg, A. F., and B. E. Saltzman,  (1965),
          "Absorption Tube for Removal of Interfering SO.-, in Analysis
                                                        ^
          of Atmospheric Oxidant" Anal. Chem. 37, 779.
44101 14  TOTAL OXIDANT-INSTRUMENTAL   COLORIMETRIC-ITEUTRAL T
-------
                                                                       I i.
                                41
44101 15
removed by using a. Cr03 scrubber.
1.  Intersociety Committee, "Methods of Air Sampling
and Analysis," American Public Health Association,
Wash., D.C., 1972, p 356.
2.  Water, Atmospheric Analysis, (1971), "Annual Book
of ASTM Standards," American Society for Testing and
Materials, Philadelphia, Pa., Part 23, p 518.
3.  Wartburg, A. F., and B. E. Saltzman, (1965),
"Absorption Tube for Removal of Interfering SO- in
                                              £
Analysis of Atmospheric C;:idant" Anal. Chem. 37, 779

TOTAL OXIDANT-INSTRUMENTAL   COULOMETRIC-NEUTRAL KI
This method is based on the same principle as 44101 13,
The electrolyte flov;s between two electrodes which are
used to measure the current needed to re-establish the
halogen-halide balance.  Nitrogen dioxide interference
has to be subtracted.  Sulfur dioxide interference is
reduced by a CrCU scrubber.
1.  Intersociety Committee, "Methods of Air Sampling
and Analysis," American'Public Health Association,
Wash., D.C., 1972, p 341.
44101 51  TOTAL OXIDANT-GAS BUBBLER   PHENOLPHTHALIN
          Phenolphthalin in the presence of CuSO^ can be oxidized
          to phenolphthalein by ambient air oxidants.  Air is
          passed through 10 ml of reagent at 800 ml/min for 10
          min.  The color is read using a green filter and a
          colorimeter.
          1.  M. B. Jacobs, (1960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Interscience
          Publishers, Inc.,.New York, N. Y., p 226.

-------
                                 42
44101 81  TOTAL OXIDANT-GAS BUBBLER   ALKALINE KI
          Oxidants in ambient air ^are absorbed in an alkaline KI
          solution in a bubbler.  A stable product is formed which
          can be stored with little loss for several days.  Analysis
          is completed by addition of phosphoric acid-sulfuric
          acid reagent, liberating iodine, which is then determined
          spectrophotometrically at 352 nm.
          1.  Selected Methods for the Measurement of Air Pollutants
          U.S. DIIEW 999-AP-ll, RATSEC Cincinnati, Ohio, 1965,
          p E-l.
          2.  Water, Atmospheric Analysis,  (1971) , "Annual Book of
          ASTM Standards," American Society for Testing and Material;
          Philadelphia, Pa., Part 23, p 391.
          3.  M. B. Jacobs,  (1960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Interscience
          Publishers, Inc., New York, N. Y., p 219.

44101 82  TOTAL OXIDANT-GAS BUBBLER   FERROUS OXIDATION
          Air is filtered through a Whatman No. 4 paper at 1 cfm
          then bubbled through two impingers in series containing
          the absorbing reagent.  The absorbance is determined
          with a blue filter and a colorimeter.  The standard is
          made by oxidizing the absorbing reagent with known
          amounts of H^O- and reading the absorbance.
          1.  M. B. Jacobs,  (1960), "The Chemical Analysis of Air
          Pollutants," Chemical Analysis, Vol 10, Interscience
          Publishers Inc., New York, N. Y., p 228.

44101 83  TOTAL OXIDANT-GAS BUBBLER   NEUTRAL BUFFERED KI
          This is the reference method for standardization and
          calibration of total oxidant and ozone measuring
          techniques.   Maximum sampling time is 30 minutes.
          Sulfur dioxide interferes.

-------
                                 43
          1.  Intersociety Committee, "Methods of Air Sampling
          and Analysis," American Public Health Association,
          Wash., D.C., 1972, p 351.
          2.  "Rules  and Regulations" Federal Register, Vol 36,
          No. 228, U.S. Government Printing Office, Wash., D.C.,
           (Nov. 25, 1971) , p 22392.
          3.  "Selected Methods for the [Measurement of Air Pollutants,"
          U.S.  DREW,  999-AP-ll, R. A. Taft Sanitary Engineering
          Center, Cincinnati, Ohio, May 1965, p D-l.
44103 11  INSTRUMENTAL - TOTAL OXIDANT - 0.2(NO +
44201 11  OZONE -  INSTRUHENTAL-CHEMILUMINESCENCE
          The Federal Register describes  this method.  Ozone
          .ozonizes ethylene and  the  excited molecule emits  a
          spectrum peaking at 450 nm.  A  photomultiplier  tube  is
          used to measure the cheiniluminescence.
          1.  "A Chemiluininescence Detector for Ozone Measurement,"
          Bureau of Mines Report of  Investigation  RI-7650,
          United States Department of the Interior, U.S.  Government
          Printing Office, Wash., D.C., 1972.
          2;  "Rules and Regulations," Federal Register Vol 36, No. 228,
          U.S. Government Printing Office, Wash., D.C., (Nov. 25, 1971),
          p 22392.

44201 13  OZONE - INSTRUMENTAL - COULOMETRIC
          This method is similar to method 44101 13.

-------