OAQPS NO. 1.2-013

    Office of Air Quality Planning and Standards

      Research Triangle Park, North Carolina

                          TABLE OF CONTENTS

PREFACE                                                     i
1.  Introduction                                            1
2.  Data Flow Procedures                                     3
    2.1  Current Data Flow System                            3
    2.2  Current Data Editing                                7
    2.3  Current Data Validation and Certification           8
    2.4  Current Data Verification                          12
    2.5  Future Data  Flow  System                            12
    2.6  Future Data  Editing                                14
    2.7  Future Data  Validation                             14
3.  Regional  Office Air Quality Data Responsibilities       15
    3.1  Current Areas of  Responsibility                    16
    3.2  Future Areas of Responsibility                     30
4.  Current Techniques for SIP Progress Evaluation          32
                                           PROPERTY OF:
                                           NATIONAL VEHICLE AND FUEL EMJSSIONS
                                           LABORATORY LIBRARY
                                           20GO THAVERWOOD DRIVF,
                                           ANN ARBOR, W

                           LIST OF FIGURES

FIGURE                                                        PAGE
1.  Current Air Quality Data Flow System                       4
2.  Future Data Flow                                          13
3.  Data Anomaly Processing Flow                              24
4.  Typical S02 Annual Pattern                                28
5.  Typical S0? Annual Pattern With Constant
    Baseline Drift                                            28
6.  Typical S02 Annual Pattern With Abrupt Baseline
    Change                                                    28
7.  Typical S02 Annual Pattern With Seasonal Abnormality      28
8.  Influence of Nearby Source on SOp Annual Pattern
9.  Plan Revision Management System                           33


     The Monitoring and Data Analysis Division of the Office of Air
Duality Planning and Standards has prepared this report entitled
"Procedures for Flow* and Auditing of Air Quality Data" for use by the Regional
Offices of the Environmental Protection Agency.  The purpose of the
report is to provide guidance information on current data auditing
techniques that should be followed as part of the procedure for in-
putting air quality data into the National Aerometric Data Bank.  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 than detailed information concerning
specific elements.  The AEROS (Aerometric and Emissions Reporting
System) 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 interpretation.  Further, any risks
involved in policy decisions concerning National Ambient Air Ouality
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."

     The purpose of this Guideline, the fifth9 in a series to be issued
by the Monitoring and Data Analysis Division (MDAD) of the Office of
Air Duality Planning and Standards, is to provide the Regional  Offices
of EPA with guidance on data auditing techniques that should be
followed as part of the procedure for inputting air quality data into
the National Aerometric Data Bank.   Information and suggestions are
presented for both the current and planned computer systems concerning:
          ' Data Flow
          ' Data Editing
          ' Data Validation
          ' Data Correction Procedures and Certification
          * Data Verification
          ' Statistical Flagging Techniques
In conjunction with this Guideline, the MDAD is also developing sophisti-
cated data edit, validation and quality control programs which should help
smooth the transition between current and planned Regional Office air
quality data responsibilities.
     This report will serve on an interim basis until more explicit and
detailed guidance is developed by the Monitoring and Data Analysis Division
as a result of the expected interaction with the Regional Offices on air
 This document supercedes a previously issued interim report entitled
 "Evaluation of Suspect Air Duality Data" OADPS # 1.2-006 issued in
 August 1973.
 Information presented in this report is also intended to alert the
 Regional Offices of their increasing responsibilities with respect to
 air quality data as a result of the planned upgrading of the EPA/RTP
 computer system.

  quality data handling techniques and  procedures.  For purposes  of
  definition the following terms are listed as they are used in this
       Data Check (Data Screen, Screening)
           The comparing of a piece of data to a specified entity.
           The comparison may be manual  (visual), or automatic (com-
           puterized).  The entity may be a code or location (edit)
           or a value (validation).
       Data Auditing
           The systematic checking of  identifying information and data
           before or after it resides  on the Aerometric and Emissions
           Reporting System.  Includes EDIT, VALIDATION, VERIFICATION,
       Data Edit (Edit Check)
           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
       Data Validation (Validation Screen)
           The comparing of data values to a set of predetermined criteria
           concerning minimum and maximum limits, deviation from average
           values, percent change overtime, etc., either manually or
       Data Anomaly (Anomalous Data)
           Any data or data summary about which some problem exists  or
           about which there arises a  question as to its integrity of
Data  Flag  (Flagging)
     Calling  attention to  and  uniquely  identifying data  for
     further  action, the flagging  maybe  done  manually or automatically.

          information.   Anomalous data may be identified (flagged
          by a report)  either manually or automatically by edit checks,
          validation or any other flagging technique.
     Data Verification
          The total  process involved in determining the existence  of
          data which, while not on NADB, has  been  indicated as  existing
          by knowledgeable sources.
     Data Certification
          The process by which data currently residing on NADB  is  deter-
          mined to be correct and complete or is  receded by individuals
          sufficiently  knowledgeable to have  background authority  and
          data to represent the source.
     This Section presents the current procedures  for  processing air
quality data.  These procedures include, as required,  data editing,
validation, verification, certification and flagging technioues for  SIP
progress evaluation.
     2.1  Current Data  Flow System
               The general flow of air quality data from the States
          through the Regional Offices to the National Aerometric  Data
          Bank is presented in Figure 1.  The steps in the system  are
          as follows:
               a.  The  State agency submits air ouality data to the
          appropriate EPA Regional Office as  part of the State  Imple-
          mentation Plan reporting procedures.  These  reports which
          are forwarded on a quarterly basis  contain the air quality


data and new site descriptions for the State's air monitoring
stations.  The data may be sent in more frequently than
quarterly if desired, 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, beginning with that used in plan
preparation, must be submitted.  It is strongly encouraged
that all reliable data obtained by the State which satisfies
the criteria established for monitoring network adequacy be
     b.  The NEDS/SAROAD contact in the Regional Office arranges
for keypunching of forms if necessary and then mails the data to
the MDAD's National Air Data Branch in card or tape form.
     c.  Air Quality data submitted to the National Air Data
Branch should have the following characteristics:
         i.  Data must be coded in SAROAD format.
         ii.  Data values less than the monitoring minimum de-
             tectable sensitivity should be reported as a "zero"
             value.  A value equal to half the minimum detectable
             sensitivity will be substituted when calculating
             summary statistics for continuous data.
       iii.  It  is desirable that the data be  representative of
             a consecutive three-month period  for which at least
             75  oercent of the data values are valid.  A non-
             detectable measurement,  i.e., a value  below the
             minimum detectable sensitivity  (Limits of Detection),

             is considered valid.   Summary statistics  are  not
             automatically machine  computed if  greater than
             50 percent of the valid  measurements  are  below  the
             minimum detectable concentration.   However,  if  the
             criteria are not met,  the data should still  be  sub-
             mitted particularly for  evaluation of maximum value
             standards.  For  noncontiguous 24-hour data there
             should be at least five  data  points in the quarter,
             with at least two months being reported and  a mini-
             mum of two data  values in the month with  the  least
             number of data value reported.
        iv.   Data must represent an interval  of one-hour  or
             greater — shorter interval  data must be  averaged
             over an hour.
         v.   Data must be representative  of the conditions of
             the site for the period  of time specified; modifi-
             cation of the environment in  which the site  is
             located must be  reported to  the MDAD  by the  State
             and/or the Regional Office.
     d.  Data are processed using the SAROAD edit  program and
the error messages generated  are provided  to the AEROS contact.
     e.  Investigation and correction of  potential errors is
accomplished by the Regional  Office in conjunction with the
States using procedures described later in this document.
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  Aerometric Data
     Bank's computer programs.  The data  will  fail to pass  the
     edit programs for the following reasons:
          a.  No existing site description.  Before any data are
     accepted, the site file must contain the information from
     the site identification form.  The program checks the  12-digit
     site code on the data and if no corresponding record is availa-
     ble in the site file, the data are rejected.   Therefore,  the
     site identification must be entered  before data from a new site
     can be accepted.
          b.  No existing description of  sampling or analytical
     method.  The program automatically rejects data if a record
     of the method used to generate the data is not available.
          c.  No match on the pollutant-method-interval-unit
     combinations for these codes.  Anything else will be rejected.
     For example, there is no monthly interval suspended particu-
     late data using a hi-vol sampler and gravimetric analysis.
          d.  Any data field other than "Agency" or "Interval"
     which has been coded in alphabetic rather than numeric
          e.  Data on the wrong form, such as trying to send 24-
     hour data on the hourly data form.
          f.  Incorrect start hour.  For hourly data the start hour
     must be 00 or 12.  For two-hour data through twelve-hour data

     legitimate values are given on page 36  of the  SAROAD  Users
     Manual.    For twenty-four hour or greater data,  legitimate
     values are from 00 to 23.  Anything else is  automatically
          g.   Data incorrect.   Data are checked for meaningful
     days.  Examples of meaningless days are February 30 or April  31.
     Some data  had to be rejected  because the year  was designated  as
     1977.  Eventually, the capability to flag data which  have a date
     other than the current quarter will be  added.  However,  this
     capability will be delayed until  all back data 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 two zeros, a blank,  and an
     eight instead of three zeros  and  an eight would  be rejected.
          i.   Decimal place indicator  not between 0 and 5.  The data
     which are currently being generated all have fewer than five
     decimal  places.
2.3  Current Data Validation and Certification
          Currently, the manual procedure used by the MDAD in the
     identification of potentially anomalous data values depends,
     to a large extent, on chance  discovery  by someone scanning a
     computer printout of either raw data or summary  statistics.
     Automatic procedures have not yet been  developed for  computer

This process of detecting questionable data values will be
supplanted when the data system is transferred to the Univac
computer in August, 1974.  Potentially anomalous values will
be objectively identified as a step in the addition of all
new data to the file.  Both parametric and non-parametric tests
could be applied to the incoming data and a listing printed of
all values that meet one or another of the test criteria for
flagging.  Examples of such tests are given below.
Non-parametric tests
     ' Values that are larger than the arithmetic mean of the
       data by some preassigned factor (such as 2).
     ' Values that are some factor, say 1.5 times larger than
       the estimated assigned 99th percentile of the data.
     ' Hourly values that differ from adjacent values by more
       than some preassigned ratio, suggesting some abrupt
       change in baseline or a transient interference.
     ' Chebyschev type tests, wherein values that are more than
       four standard deviations away from the mean are to be
       considered suspect.
Parametric tests
     Efficient use of these tests depends on knowledge of the
frequency distribution of the quantity being measured.  Example
of such tests are presented below.  (The sensitivity of these
tests can be determined analytically from the frequency distri-

     • Detection of any values that are larger by some factor
       (e.g., 1.5) than the expected value of the assigned 99th
       percentile of the distribution under question.
     ' The finding that the average of K >_ 5 successive values
       falls outside the (y +_ 3o_) limit, where y and a  are the
       mean and the variance of the distribution under question.
Note:  The difference between the non-parametric test and the para-
metric test is that in the former, the assigned percentile is esti-
mated from the data, whereas in the latter it is theoretically
     Validation of the pollutant measurements involves technical
judgment about what constitutes questionable data, and is expected
to be applied systematically in the form of a set of criteria
defining, for each pollutant, what constitutes an unusual or anomalous
value or an abnormal fluctuation.  Excursions outside 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 correction.
    Pefinitions of what constitute unusual values or abnormal
fluctuations are required for each pollutant.  These criteria
should be defined by people familiar with the characteristic behavior
of the pollutants and the instruments used to measure them.  Realis-
tically, these criteria for identifying questionable values should
be open to revision.  Once developed, these criteria can be readily
incorporated as a standard element in the data bank's editing and/or
validation procedures.

     Certification by States is accomplished by using available  SAROAD
output to determine the accuracy and completeness  of all  submitted
data.  Particular emphasis should be placed on the following:
     a.  Site identification information
     b.  Methods of collection and analysis
     c.  Integrity of the actual data
All three items must be coded and represented on the data bank as
accurately as possible to insure the proper interpretation and
evaluation of the data.
     Certification may be triggered by either of two mechanisms:
First, any time there are FDIT or VALIDATION reports flagging either
incorrect data or data of a questionable nature, implicit certifica-
tion is required.  This means that the data must be corrected and
resubmitted, if necessary; otherwise, for data which has  been
flagged as being possibly invalid, no action is necessary if the
data is correct as it was submitted.
     The second trigger for certification may be dependent upon
time or the number of anomalies being reported for a specific
subset of data.  It may be determined that an agency should inspect
a set of data to certify it as being correct and complete.  In this
situation, and it will always be identified as such, the  appropriate
agency must make any corrections necessary to the data and must
always respond in writing that the data are correct as they stand
or that the corrections which have been attached will solve the

2.4  Current Data Verification
          Currently the entire procedure of data verification  is
     being handled through contractual  resources.   This involves
     the use of reference publications  to determine the probable
     existence of additional  air quality data.   Once NADB is aware
     of this data the necessary steps are taken with the appropriate
     agency to coordinate the submission of the data to the National
     Aerometric Data Bank.
2.5  Future Data Flow System
          As previously mentioned, it is expected that the Regional
     Offices will assume more responsibility with respect to the
     validation of air quality data.  This will be accomplished by
     their taking a central role in the screening of air quality
     data before it is inputted into the National  Aerometric Data
     Bank.  The screening will involve not only editing the coding
     format but also the validation of the measurements.
          During the transition period of shifting more responsibility
     to the Regional Offices, it is anticipated, at least initially,
     that the MDAD will do minimal revalidation of the data.  Also,
     the flagging technique for measuring SIP progress will 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  (Figure 2).

                     State/Local Agencies
                                                                         Flog (Including edit  and  validation)

                                                                            Air Quality and  Emissions  Data
                                                                               Regional Office
                                                                             KEDS/SARQAD Contacts
National Air Data Branch
Data Processing Section

2.6  Future Data Editing
          One of the highest priorities within MDAD concerns making
     available all Edit and Validation programs to each Regional
     Office.  It has been determined that this can best be accom-
     plished by providing terminal edit capability on the RTCC-
     UNIVAC 1110.
          The procedure to be followed would involve either trans-
     mitting or mailing the AQ report in a computer readable medium
     (cards or tape) to RTCC.  Once the data has arrived, the edit/
     validation programs could be executed via the Regional Office
     terminal with the error diagnostics being returned via the
     medium speed remote terminal.  This output could then be returned
     to the appropriate agency as required.
          After a successful edit of the data has been completed the
     culled data would be identified to NADB who would concatenate
     several Regional Office data sets into a single update.  Any
     additional errors generated by the actual update (i.e., duplicate
     data) would be routed directly to the appropriate Regional Office.
2.7  Future Data Validation
          As data are audited by the Terminal Edit/Validation program
     it is planned that, in addition to the edit rejection listing
     being produced, a special report will be generated which auto-
     matically will identify data which seem for one reason or
     another to be invalid.  This data although identified in the
     validation report will nevertheless be updated onto the SAROAD

               Due to storage constraints there are no plans for these
          data to be further "flagged" while stored.  It is imperative
          that the data be checked immediately to determine its validity
          by the submitting agency.  If the data are confirmed to be
          correct no further action is necessary.  If, however, the data
          are incorrect then the agency must immediately code the neces-
          sary changes and/or deletions and submit these to the appropriate
          Regional Office.
               In addition to the types of validation tests already
          discussed the following list illustrates the computerized
          hourly validation checks under consideration:
                         CO                        100 ppm
                         S02                         2 ppm
              Ozone (Total Oxidant)                 .7 ppm
              Total Hydrocarbons                    1C ppm
              Non-methane Hydrocarbons               5 ppm
                         N02                         2 ppm
                         NO                          3 ppm
                         NO                          5 ppm
              Total Suspended Particulate         2000 g/m
     This Section presents recommendations and suggestions as to those
methods and techniques which the Regional Offices can employ to validate
air quality data.  The Monitoring and Data Analysis Division recognizes
that some of the areas of responsibility are beyond the capability of some
of the Regional Offices at this time.  In these cases, the MDAD will

vide technical  and other assistance on an as  needed basis  in  order
t the current and planned data flow system operate in  the  most
icient and effective manner possible.
  3.1  Current Areas of Responsibility
            At this time, there are various tasks which the Regional
       Offices perform in the validation of air quality data.  These
       include the following:
            a.   Preliminary Data Inspection
                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 care-
            lessness in correctly filling out their SAROAD sheets,  the
            Regional Office may want to check these sheets for  their
            "correctness" as discussed in Section 2 rather than just
            for their completeness.
                 If the data submitted to the Regional Office from  the
            States are in the form of punched cards, the Regional Office
            can visually inspect the batch to make sure that pertinent
            columns are punched and aligned correctly.  The Regional
            Office may find it desirable to actually print out  or list
            the data from selected agencies before forwarding the cards

to MDAD.  If the data are sent on magnetic tape,  there
is little the Regional Office can do,  at present,  but
forward it on.
b.   Interrogate Data Bank, Data Requests and Manual
     Some existing SAROAD outputs are  available which the
Regional Office may find helpful in evaluating their  air
quality data.  The Regional Office can request output from
the data bank and get quarterly and yearly frequency  dis-
tribution lists for each sampling station.  The output
includes the site description at the top of each  page and
a frequency distribution for each pollutant, year or
quarter-year.  The number of observations, minimum, maximum,
and the percentile values are listed for each pollutant-
quarter-year.  The arithmetic mean, geometric mean, and
geometric standard deviation are given only for those
pollutant-quarter-years which meet National Aerometric
Data Bank criteria.
     The frequency distributions are available on a  national,
EPA regional and State basis.  Other options include  the
ability to request the distribution for limited numbers of
pollutants, years or quarters.
     These and other outputs and remote batch and inter-
active access methods are more fully defined and  discussed
in the SAROAD Terminal Users Manual,  and the Regional
Office MEDS/SAROAD contact should be contacted for addi-
tional information.

     The Regional Office will, in the future,  be able to
make comparisons between measured air quality  data and
that which they, and/or the State and local  agencies,
intuitively feel is reasonable for that geographical  area,
station and pollutant.
c.   Check Anomalous Data
     Anomalous or questionable data values may arise from
the data flow system as a result of the following procedures:
edit checks, validation screen and the application of the
flagging technique.  The Regional Office has the responsi-
bility of either accepting, rejecting or modifying the data
value or average in question.  In this regard, the Regional
Office has the option of requesting that the originating
agency determine the validity of the data or provide certain
information and documentation so that they may make the
final determination.
     The procedure used to check out any specific data
value prior to the initiation of an anomaly request to
NADB could depend on:  the Regional Office's assessment
of the originating agency in terms of its capability,
quality control program, and previous performance.  MDAD
suggests that the following sequence of steps be followed
in order to check out anomalous data values or composite
averages.  In all cases, it should be recognized that any
agency which alters, manipulates or transcribes a data
value in any way is potentially capable of introducing an

error.  When a data value is identified as being Questionable,
the responsible agency must determine whether or not the  data
value maintained its integrity throughout the agency's  data
acquisition and processing system.
     The data should be traced through the SAROAD system,
the Regional Offices, State agency  and/or local  agency  to
its original recording, whether it  be a value from a computer
readout, paper tape printer, strip  chart, 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, multipli-
cation and transcribing).  Further  discussion of these  errors
and methods to reduce their frequency may be found in already
published guideline documents. ' '
     If no errors have been identified in the internal  check,
at all agency levels, the verification and evaluation process
should continue down two similar but separate paths. Which
path is chosen depends on whether the data in question  is a
single value or a composite average.
         i.  Evaluating Specific Air Quality Data Values
            ' Instrument Calibration, Specifications and Operations
             The operation and calibration of continuous  instru-
             ments is of the utmost importance in the production
             of valid air quality data.  The instrument cali-
             bration should be reviewed for the time period  in
             question, both before and after the suspect  data

  point,   It  should  be  determined  if  the  instru-
  ment was operating within  pre-determined
  performance specifications such  as  drift,
  operating temperature fluctuations,  unattended
  operational  periods,  etc.   These performance
  specifications  for automatic monitors are  defined
  and published in  the  Federal Register   and sum-
                                         3 4
  marized in  various guideline documents.  '   These
  specifications  are likely, however,  to  be  super-
  ceded by those  published  in the  October 12, 1973,
  issue of the Federal  Register  on proposed
  Eauivalency Regulations.   Guidelines on air guality
  control practices  and error tracing techniques are
  also available.
  Before and  After  Readings
  If the instrument generating the data was  found to
  be "in control,"  the  values immediately before and
  after should be determined. Comparisons between the
  percent and/or gross  deviations  could  be made.   Ideally,
  this difference in concentration should be determined
  through a statistical analysis of historical  data.
  For example, it may  be determined that  a difference
  of 0.05 ppm in SO^ concentration for successive  hourly
  averages occurs very  rarely (less than  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  ppm  between
   6  AM and  7  AM may  be  common  but would be suspect if
                                    3  *;
   it occurred between 2 AM  and 3 AM.
1   Other Instruments  at  the  Same Location
   Observing the behavior  of other instruments at
   the same  location  would give the  evaluator a quali-
   tative insight into the possible  reasons for the
   anomalous reading.  If  all of the instruments  showed
   a  general increase, meteorological factors might be
   considered  while a dramatic  deviation over the same
   short period  of time  may  indicate an electrical
   problem or  an air  conditioning malfunction.  On the
   other hand, if the other  instruments behaved normally,
   a  temporary influence of  a single pollutant 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  instruments  (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.
   Micrometeorological  influences should not be over-
   looked  either.   The  station may be under the influence
   of subsidence effects  from the urban heat island or
                                7 8
   upslope-downslope  influences.
'   Meteorological Conditions
   No attempt to explain  an anomalous air quality data
   point would be complete without a consideration of
   the meteorological conditions present at the time of
   the reading.  A  passing front and strong inversion,
   extended calms or  strong winds are conditions which
                                     7 8
   have a  great impact  on air quality.  '   Influences of
   precipitation, temperature and season could be included
   to interpret the reasonableness of the data as well.
'   Time-Series Check
   Investigating a  time series  plot  of the data might
   reveal  a repetitious pattern  during  similar time
   periods.  An extreme excursion might thus be explained.
   For example, the instrument may be extremely tempera-
   ture 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 and adversely affect a  given air monitoring
     station's representativeness.   Examples of this might
     be an adjacent apartment house or supermarket changing
     from garbage haul-away to an incinerator.   Urban
     renewal may also render the location temporarily un-
     representative.   It may be beneficial  for  each  agency
     or Regional Office to maintain a  map and photograph
     of each site showing influencing  site characteristics.
     These could be updated on a periodic basis.   The site
     location, sampling probe material  and configuration
     should also be within the bounds  of those  specified
     in published guidelines.   Figure 4 presents  a  step-
     wise review and guide to the verification  of  specific
     data values.  It should provide the Regional  Offices
     with an overall  picture of the suggested processing
     of State  and local air duality data.
ii.   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 include both geometric
     and arithmetic means, standard deviations, and  the
     frequency distribution in percentiles.  Both  the

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   standard  deviations and the magnitude of the dif-
   ference between  the geometric and the arithmetic
   means  are more sensitive  to a few extremely high
   values than  to many moderately  high  levels.  Inspec-
   tion of the  values corresponding to  the hiqher  per-
   centiles  would also show  the influence of  abnormally
   high values.  On the  average, standard deviations do
   not generally change  much from  year-to-year.
•   List Individual  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 should  be listed.
   From inspection  of this list, it can be determined
   if the average was influenced by a relatively few
   large  values 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
   of its representativeness of the pollutant of interest,

the averaging time of interest, and the pollutant
receptor.  The operation of the site should be
evaluated in terms of sampling methodology, mainte-
nance procedures, calibration procedures and quality
control practices.  The actual sampling probe and
manifold material, configuration and placement should
also be evaluated.  Guidelines describing in detail
these aspects of air quality monitoring have been
Plot Data
Comparing a visual plot of the current data to that
of prior years on a typical annual  pattern could further
pinpoint reasons to accept or reject the annual average
in question.  Note that, however, some year-to-year
variation is expected.  Figure 4 presents a typical
SCU annual  pattern based on expected monthly averages
(exaggerated for purposes of illustration). .Figure 5
also shows this same pattern with a constantly in-
creasing baseline drift.  A pattern of this type
suggests a continuing long-term failure (change) in
a component of the instrument, deterioration in the
supplies being used or a subtle change in the environ-
ment.  Figure 6 presents the typical pattern with an
abrupt dislocation of the base line.  This may be
indicative of a change in struments, methods of
analysis, procedures used or personnel.  It should

  not be arbitrarily assumed that any such shift
  is wrong.  For instance, the analytical method
  may have been changed to the standard reference
  method, sources of interferences may have been
  eliminated or the operators may be following the
  procedure correctly for the first time.  Figure 7
  presents a seasonal abnormality in the expected
  pattern.  It should be kept in mind that a devia-
  tion  from the expected pattern can be negative as
  well  as positive.  Figure 8 demonstrates how the
  expected pattern can be smoothed (masked) by a
  nearby source whose emissions are fairly constant
  throughout the year.  The pattern may also show
  part  of the year as "normal" and part of the year
  "masked" if there are pronounced seasonal wind
  direction changes.  For those pollutants such as
  oxidants whose peak values occur during a single
  season a plot of weekly or bi-weekly averages through
  the period of interest would provide more information
  on the cyclical patterns than monthly averages.
'  Check Prior Data for Trend
  Plotting at least four previous annual averages
  along with the current year and visually inspecting
  the graph could give the evaluator a qualitative
  insight  into whether the current annual average  is
  a significant deviation from or an extension of  the
  projected trend.

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  Compare With Surrounding Stations
  If there are enough surrounding sites to develop
  air quality isopleths of the area, the evaluator
  could  see how the annual average in question fits
  in with the overall picture.  For instance, if the
  point  in question was midway between the isopleth
  lines  representing 80 and 60, but the recorded value
  was 50% greater  than expected, i.e., 105, an ab-
  normality may be expected.
  This comparative technique may also be used in areas
  where  there are  not enough sites to directly plot air
  quality isopleths but where a predictive air quality
  model  has been developed and verified with a limited
  number of actual data values.  In these cases, for
  example, deviations of  +_ 100% could be suspect.
'  Meteorology
  The annual average  should be interpreted in conjunc-
  tion with meteorological conditions for the year  in
  question.  For example, if the winter of the year in
  question were the coldest in 50 years or the overall
  degree days were 50%  above the 20-year norm, an
   increased SOg average would be expected.  Suspended
   particulate values  can  be greatly affected by wind
  direction and a  disproportionate wind rose  (atypical
   for the  area) could help explain unusual values.
   Comparing  the  appropriate meteorological parameters

             such  as  rainfall,  wind  speed,  number  and  length of
             inversion,  temperature  and  degree days  to their long-
             term  averages,  i.e.,  20- or 50-year norms, before
             attempting  to change  implementation plans is suggested,
     d.   Data Bank Add/Correct/Delete Procedures.
         As  Regional  Office  interaction  with  the SAROAD data
     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 are
     incorporated  in  the data bank but have been found to be in
     error.   There are then  three  types  of  transactions which can
     be  processed  by  the SAROAD data bank:  add, correct, and
     delete.   In each case data in SAROAD format must  be submitted
     on  a separate tape  or set  of  cards  and must be  identified both
     on  the  tape and  by  an accompanying  memorandum.
          Documentation  of each of the transaction types, describing
     the processing which the data goes  through and  indicating the
     limitations of each type of transaction  has been  provided to
     the Regional  Office by  MDAD (Slaymaker's memorandum of June 6,
          The Regional Office should use the  previously discussed
     procedures to determine if identified  suspect data should be
     updated, corrected  or deleted by means of these transactions.
3.2  Future  Areas  of  Responsibility
          Future areas of Regional Office responsibility with
     respect to air quality  data include:

a.   Quality 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 pollu-
     The Control Programs Development Division has developed
a general guideline for State and #bcal wuality control pro-
grams entitled "Quality Control Practices in Processing Air
Pollution Samples.'   This guideline should help the Regional
Office establish a general quality control program at the
State and local level.
b.   Edit and Validation Checks
     When MDAD develops the data validation programs and turns
both the editor and data validation programs over to the
Regional Offices,  it  is expected that the Regional Offices
will assume the lead  in initiating edit and validation checks
on the incoming data.  High quality data should then be trans-
mitted to the National Aerometric  Data Bank via upgraded
remote access computer terminals.

     It is difficult to develop comprehensive guidance on exactly how
to determine 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 attain-
ment date.  The problem is to determine whether AQCR's are progressing
satisfactorily in relation to the emission limitations contained  within
the SIP.  To this end, a Plan Revision Management System (PRMS) was
developed to track the progress being made by States in implementing
their SIP.  PRMS provides a means for effectively combining information
contained in SAROAD (air quality) NEDS (source emissions), and CDS (enforce-
ment 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 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, moderate, or major
problem toward attainment of the NAAQS.  The tolerence limits were
developed through the application of statistical Quality control  techniques
which allow for the many variables associated with measured air duality
concentrations.  (See Figure 9)

                         Hcjurc 9
                       Particulate Matter
(1000 tons/year)
                        1970    1971    1972   1973   1974    1975   1976   1977
Air quality



    -2	o
                                   -Tolerance limits
                                          Projected air
                        1970    19X1
                1972   1973    1974    1975   1976   1977
                      Calendar Year
                      0 Me as u re d  air o u a 1 i ty
//I  Calculation cf emission  reduction fNi'DS, Emission  Regulations)
n.  Review of co:-;plii:nco  daU-s  (SIP1, CDS,- Ciiviss-io/i  Regulations)
i-3  Projection of :-\r reality
i-'':  Establ is:'i!:''.-i!t of to] oranc'.'  1 v'.:i'>;:i or bc;i!;:c!,iries
;;5  Mea'-MJied air quality  treiu.!  (S;,;;;V.:'X

     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
assessment 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.
     Initially, there are 17 AQCR's contained in the PRMS.   An additional
50 Regions were included in the system in 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
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 this 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.  The following two pages present the PRMS responsibilities and the
associated action procedures.

                         ACTION PROCEDURES

A.  Data Review Actions

    1.   The air quality data should be  reviewed  and  work  should  pro-

        ceed to certify the data if possible.

    2.   The monitoring site should be visited  to detenriine  if  the

        monitor is properly located.

    3.   The meteorological  conditions associated with  the sampling

        period in questions should be reviewed to determine if any

        abnormal conditions could have  effected  the  air quality

    4.   The site location is source oriented and a unique projected

        curve for that site should be developed  to better analyze

        the data.

    5.   A more detailed projected curve should be developed for  the

        entire air quality control region.

B.  Program Actions

    1.   A review of the compliance schedules for the AQCR should be

        conducted to determine if any sources  have failed to meet  any scheduled
          -."•*           •                             *
        milestones or final compliance dates.
    2.   The State should be notified that a more effective  implementation of

        the new source review procedures is needed to restrict growth in

        certain areas.

    3.   A special study should be initiated to determine the cause of the

        present air quality problem and the results are expected by	.

C. 'Legal Actions

    1.   EPA/State enforcement action is necessary

    2.   Plan  revisions is determined to be necessary and the State has

        been  notified of the need for the revision.

    3.  The State's plan revision has not been submitted or approvpri

        and work has been  initiated by EPA to develop the necessary

                        PRMS  Responsibilities
OAQPS Responsibilities
  o  Calculate initial emission/time curve
  o  Develop initial  projected air quality  curve  (Proportional model)
  o  Perform the computer analysis of measured vs  projected  air  quality
  o  Notify each Regional Office of possible deficiencies
  o  Prepare a summary of the PRMS analysis for the Administrator's
       Progress Report
  0  Offer technical  assistance to the Regional Office in  investigating
       identified deficiencies
  o  If requested, rerun computer analysis  with additional  data  provided
       by the Regional Office

Reg i on a1 Office Res pon s i b i1i t i es
  °  Investigate areas with possible deficiencies
  o  Inform OAQPS of the results of the investigation
  o  If a new projected air'quality curve is determined to be necessary,
       it should be developed by the R.O.'s and submitted to OAQPS fo'r
       a rerun of the PRMS analysis.
  o  If a plan revision is determined to be necessary by the R.O., inform
       the State of the type of revision necessary to correct the plan



1,  SAROAD Users Manual, Office of Air Programs Publication No.  APTD 0663,
    EPA, Research Triangle Park, N. C., July 1971.

2.  SAROAD Terminal User's Manual, Office of Air Programs,  Publication
    No. EPA-450/2-73-004, EPA, Research Triangle Park,  N.C., October 1973.

3.  "Field Operations Guide for Automatic Air Monitoring Equipment,"
    Office of Air Programs, Publication No. APTD 0736,  EPA, Research
    Triangle Park, N.C., November 1971.

4.  "Guidelines for Technical  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 Pollution  Samples,"
    Office of Air Programs, Publication No. APTD 1132,  EPA, Research
    Triangle Park, N.C., March 1973.

6.  Federal Register, Vol. 36, No. 228, November 25,  1971,  page  22404.

7.  Lowry, W.P. and R.W. Boubel, "Meteorological Concepts in Air
    Sanitation," Type-Ink., Corvallis, Oregon, 1967.

8.  Symposium; Air Over Cities, Public Health Service,  SEC  Technical
    Report A-62-5, Cincinnati, Ohio,  November 1961.

9.  Guidelines for Development of a Quality Assurance Program, Office of
    Research and Monitoring, Quality Assurance and  Environmental Monitoring
    Laboratory, Publication N.C. EPA-R4-73-028, EPA,  Research Triangle
    Park, N.C., June 1973.

        a.  Reference Method for the Continuous Monitors of Carbon
            Monoxide in the Atmosphere.

        b.  Reference Method for the Determination  of Suspended  Particulates
            in the Atmosphere (High Value Method).

        c.  Reference Method for Measurement of Photochemical Oxidants.

        d.  Reference Method for the Determination  of Sulfur Dioxide in
            the Atmosphere.

10.  OAQPS #1.2-011  Guidelines for Determining  the Need  for Plan  Revisions
     to the Control  Strategy Portion  of the  Approved  SIP.

11.  Plan Revision Management  System, System Summary, May 1974,  USEPA, OAQPS,
     CPDD, Research Triangle Park, N.C.