EPA
United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park, NC 27711
EPA-454/B-93-051
March 1994
Air
PHOTOCHEMICAL
ASSESSMENT MONITORING
STATIONS IMPLEMENTATION
MANUAL
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c
EPA-454/B-93-051
X
PHOTOCHEMICAL ASSESSMENT MONITORING
STATIONS
IMPLEMENTATION MANUAL
U. S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Radiation
Office of Air Quality Planning and Standards
Technical Support Division
Research Triangle Park, North Carolina 27711
March 1994
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NOTICE
This document has been reviewed in accordance with United
States Environmental Protection Agency policy and approved for
publication. Mention of trade names or commercial products
does not constitute endorsement or recommendation for use.
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FOREWORD
This document replaces the Enhanced Ozone Monitoring Network Design and
Siting Criteria Guidance Document, EPA-450/4-91-033, dated November
1991. This implementation manual is being published in loose-leaf form for
the convenience of the user; periodically, additional sections of the document
not included with this first publication and subsequent revisions will be sent to
the user community.
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TABLE OF CONTENTS
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SECTION
PAGE REV. REV.
NO. NO. DATE
LIST OF TABLES
LIST OF FIGURES
LIST OF ABBREVIATIONS AND ACRONYMS
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1.0 INTRODUCTION (22 pages)
1.1 REGULATORY BACKGROUND
AND OBJECTIVES
1.2 DEVELOPING DATA QUALITY
OBJECTIVES
1.3 PAMS PROGRAM OBJECTIVES
AND INITIAL DATA QUALITY
OBJECTIVES
1.4 GENERAL APPROACH
1.5 ORGANIZATION
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2.0 NETWORK DESIGN AND SITING FOR PAMS
(30 pages) 2-1 0
2.1 INTRODUCTION 2-1 0
2.2 PAMS SITE DESCRIPTIONS 2-2 0
2.3 SELECTION OF CANDIDATE PAMS SITES 2-6 0
2.3.1 Spatial Scales 2-6 0
2.3.2 General Monitoring Area 2-7 0
2.3.3 Selection of General Site Locations 2-8 0
2.3.4 Selection of Final PAMS Sites 2-11 0
2.3.5 The Use of Saturation Monitoring
Techniques 2-16 0
2.3.6 Practical Considerations and Constraints 2-17 0
2.3.7 Screening for Effects from Nearby
Emissions Sources 2-20 0
2.3.8 Probe Siting and Exposure Criteria 2-26 0
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3.0 MONITORING METHODS AND NETWORK
OPERATIONS (14 pages)
3.1 MONITORING METHODS
3.2 OPERATING SCHEDULES AND SAMPLING
FREQUENCIES
3.2.1 General Operating Requirements
3.2.2 Explanation of Specific PAMS Network
Requirements
3.2.3 Requirements for MSA/CMSAs With
Populations Less Than 500,000
3.2.4 Requirements for MSA/CMSAs With
Populations of 500,000 to 1,000,000
3.2.5 Requirements for MSA/CMSAs With
Populations of 1,000,000 to 2,000,000
3.2.6 Requirements for MSA/CMSAs With
Populations of Greater Than 2,000,000
3.3 ALTERNATIVE SAMPLING AND ANALYSIS
METHODOLOGY
3.4 MONITORING FOR AIR TOXICS
4.0 PAMS NETWORK PLAN AND APPROVAL
(40 pages)
4.1 INTRODUCTION
4.2 REQUIREMENTS FOR STANDARD PAMS
NETWORK PLANS
4.2.1 Summary Procedures for Review and
Approval of Standard PAMS
Network Plans
4.2.2 Completeness Criteria for Standard
PAMS Network Plans
4.2.3 Acceptance Criteria for Standard PAMS
Network Plans
4.3 REQUIREMENTS FOR ALTERNATIVE
NETWORK PLANS
4.3.1 Summary Procedures for Review and
Approval of an Alternative PAMS
Network Plans
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4.3.2 Regulatory Provisions for Alternative
PAMS Network Plans
4.3.3 Completeness Criteria For Alternative
PAMS Network Plans
4.3.4 Acceptance Criteria For Alternative
PAMS Network Plans
4.4 COMPLETENESS CHECKLIST FOR PAMS
NETWORK PLANS
4.4.1 Instructions for Using Checklist
4.4.2 Completeness Checklist for PAMS
Network Plans
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6.0 THE AEROMETRIC INFORMATION RETRIEVAL
SYSTEM (6 pages)
6.1 OVERVIEW
6.2 DATA INPUT AND UPDATE PROCEDURES
6.3 DATA RETRIEVAL
7.0 TECHNOLOGY TRANSFER NETWORK (TTN)
(10 pages)
7.1 BACKGROUND
7.2 THE AMBIENT MONITORING
TECHNOLOGY INFORMATION CENTER
BULLETIN BOARD
7.3 OTHER TTN BULLETIN BOARDS
7.4 USING THE AMTIC/TTN
7.4.1 Conventional Modem Dialup
7.4.2 EPA Ethernet Connection
7.4.3 X.25 Pads (Packet Switching Network)
7.4.4 Internet
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8.0 REFERENCES (3 pages)
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APPENDICES
APPENDIX A - PAMS PROPOSAL AND FINAL RULE A-l
APPENDIX B - METEOROLOGICALLY ADJUSTED OZONE TRENDS IN
URBAN AREAS B-l
APPENDIX C - GUIDELINE FOR THE INTERPRETATION OF OZONE AIR
QUALITY STANDARDS C-l
APPENDIX D - QUESTIONS AND ANSWERS ON THE PHOTOCHEMICAL
ASSESSMENT MONITORING STATIONS (PAMS) NETWORK BASED ON THE
APRIL 27-29, 1993 TELECONFERENCE WORKSHOP D-l
APPENDIX E - UPDATED ESTIMATED CANCER INCIDENCE FOR
SELECTED TOXIC AIR POLLUTANTS E-l
APPENDIX F - SAMPLE WIND ROSES FOR THE PAMS PROGRAM F-l
APPENDIX G - OUTPUTS FROM THE SCREEN MODEL G-l
APPENDIX H - LIST OF DESIGNATED REFERENCE AND EQUIVALENT
METHODS H-l
APPENDIX I - SAMPLE SUBMITTAL MATERIALS AND ADDITIONAL
GUIDANCE 1-1
APPENDIX J - AIR QUALITY INDICATORS J-l
APPENDIX K - SAMPLE OUTPUTS FROM AIRS GRAPHICS K-l
APPENDIX L - BIBLIOGRAPHY L-l
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NUMBER
1-1 Nonattainment Severity Classifications
2-1 Estimated PAMS Requirements for
Currently-Affected Areas
2-2 PAMS Measurement Scales
2-3 Sample Source VOC Emissions Profile
2-4 Useful Equations for VOC Mixtures
2-5 Separation Distance Between PAMS and Roadways
(Edge of Nearest Traffic Lane)
3-1 PAMS Minimum Network Requirements
3-2 Target VOC Ozone Precursors and Synonyms
3-3A Target VOC Ozone Precursors - Hydrocarbons
3-3B Target VOC Ozone Precursors - Carbonyls
3-4 Ozone Monitoring Seasons PAMS-Affected States
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NUMBER
1-1 PAMS Ozone Nonattainment Areas
1-2 PAMS Program and Design Objectives
2-1 Isolated Area Network Design
2-2 Multi-Area and Transport Area Network Design
2-3 Sector Analysis Network Design
2-4 Preferred Site #2 - Emissions Mix
2-5 Sample Emissions Inventory Descriptions
2-6 Network Design - Light Winds
2-7 Point Source Effects on Siting
2-8 Area Source Effects on Siting
4-1 Procedures for Review and Approval of
Standard PAMS Network Plans
4-2 Procedures for Review and Approval .of
Alternative PAMS Network Plans
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List of Abbreviations and Acronyms
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LIST OF ABBREVIATIONS AND ACRONYMS
ACT
AFS
AG
AGENCY
AIRS
ALAPCO
AMS
AMTIC
APT!
AQCR
AQS
AREAL
BACT
BBS
BLIS
BPS
C
CAAA
CBD
CDS
CFR
CHIEF
CICS
CMSA
COMPLI
Clean Air Act
AIRS Facility Subsystem
AIRS Graphics
United States Environmental Protection Agency
Aerometric Information Retrieval System
Association of Local Air Pollution Control Officials
Area and Mobile Subsystem (AIRS)
Ambient Monitoring Technology Information Center
Air Pollution Training Institute
Air Quality Control Region
Air Quality Subsystem (AIRS)
Atmospheric Research and Exposure Assessment Laboratory
Best Available Control Technology
Bulletin Board System
RACT/BACT/LAER Information Systems
Bytes Per Second
Carbon
Clean Air Act Amendments of 1990
Central Business District
Compliance Data System
Code of Federal Regulations
Clearinghouse for Inventories/Emission Factors
Customer Information Control System
Consolidated Metropolitan Statistical Area
COMPLIance Information on Stationary Sources of Air Pollution
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CTC
CYO
DQO
EKMA
EMTIC
EPA
FTPS
FRM
FY
GCS
HNO3
ID
LAER
MCB
MSA
MW
NAAQS
NADB
NAMS
NARS
NATICH
NCC
NEDS
NESHAP
NMOC
NO
NO2
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Control Technology Center
Create-Your-Own
Data Quality Objective
Empirical Kinetic Modeling Approach
Emission Measurement Technical Information Center
United States Environmental Protection Agency
Federal Information Processing Standards
Federal Reference Method
Fiscal Year
Geographic and Common Subsystem (AIRS)
Nitric Acid
Identification
Lowest Achievable Emission Rate
Model Change Bulletin
Metropolitan Statistical Area
Molecular Weight
National Ambient Air Quality Standards
National Air Data Branch
National Air Monitoring Stations
National Asbestos Registry System
National Air Toxics Information Clearinghouse
National Computer Center
National Emissions Data System
National Emission Standards for Hazardous Air Pollutants
Nonmethane Organic Compound
Nitrogen Oxide
Nitrogen Dioxide
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NO,
NOy
NSPS
NSR
NWS
OAQPS
QMS
PAMS
PAN
PICS
PPB
PPM
PSD
PWD
QA
QC
RACT
REVIEW
COMMITTEE
RFP
ROM
RTV
RULE
SAROAD
SCRAM
SIP
Oxides of Nitrogen
Total Reactive Oxides of Nitrogen
New Source Performance Standard
New Source Review
National Weather Service
Ozone
Office of Air Quality Planning and Standards
Office of Mobile Sources
Photochemical Assessment Monitoring Stations
Peroxyacetyl Nitrate
Products of Incomplete Combustion
Parts Per Billion
Parts Per Million
Prevention of Significant Deterioration
Primary Wind Direction
Quality Assurance
Qnalitxr f"^r>r*l-rn1
b*h»—> *J <-~v**l*-*w~
Reasonably Available Control Technology
EPA PAMS Network Design Review Committee
Reasonable Further Progress
Regional Oxidant Model
Ready-to-View
40 CFR Part 58, as Amended February 12, 1993
Storage and Retrieval of Aerometric Data
Support Center for Regulatory Air Models
State Implementation Plan
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SLAMS
SOP
SPM
SSCD
STAPPA
SYSOP
T
TAD
TO
TTN
UAM
UTM
V
VOC
W
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State and Local Air Monitoring Stations
Standard Operating Procedure(s)
Special Purpose Monitor
Stationary Source Compliance Division
State and Territorial Air Pollution Program Administrators
Systems Operator
Temperature
Technical Assistance Document
Toxic Organic Method
Technology Transfer Network
Urban. Airshed Model
Universal Transverse Mercator
Volume
Volatile Organic Compound(s)
Weight
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1.0 INTRODUCTION
1.1 REGULATORY BACKGROUND AND OBJECTIVES
Section 182(c)(l) of the 1990 Clean Air Act Amendments (CAAA) required the
Administrator to promulgate rules for the enhanced monitoring of ozone, oxides of nitrogen
(NOJ, and volatile organic compounds (VOC) to obtain more comprehensive and
representative data on ozone air pollution. Immediately following the promulgation of such
rules, the affected States were to commence such actions as were necessary to adopt and
implement a program to improve ambient monitoring activities and the monitoring of
emissions of NOX and VOC. Each State Implementation Plan (SIP) for the affected areas
must contain measures to implement the ambient monitoring of such air pollutants. The
subsequent revisions to Title 40, Code of Federal Regulations, Part 58 (40 CFR 58)
(Reference 1) required States to establish Photochemical Assessment Monitoring Stations
(PAMS) as part of their SIP monitoring networks in ozone nonattainment areas classified as
serious, severe, or extreme (Figure 1-1). The criteria for judging the severity of an ozone
nonattainment area utilizing the ozone design value is listed in Table 1-1. The air quality
design value is intended to provide a measure of the need for reduction in ozone
concentrations essential to achieve attainment or, equivalently, the degree of severity of the
nonattainment area represented by the monitoring site. Given the expected exceedance form
of the ozone National Ambient Air Quality Standard (NAAQS), the ozone design value is
defined as the concentration with the expected number of exceedances equal to one (see
References 2 and 3).
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O
E
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TABLE 1-1. NONATTAINMENT SEVERITY CLASSIFICATIONS
NONATTAINMENT AREA
CLASSIFICATION
Marginal
Moderate
Serious
Severe
Extreme
OZONE DESIGN VALUE (ppm)
0.121 up to 0.138
0.138 up to 0.160
0.160 up to 0.1 80
0.180 up to 0.280
0.280 and above
The principal reasons for requiring the collection of additional ambient air pollutant and
meteorological data are, primarily, the lack of attainment of the NAAQS for ozone
nationwide, and, secondly, the need for a more comprehensive air quality database for ozone
and its precursors.
The chief objective of the enhanced ozone monitoring revisions is to provide an air
quality database that will assist air pollution control agencies in evaluating, tracking the
progress of, and, if necessary, refining control strategies for attaining the ozone NAAQS.
Ambient concentrations of ozone and ozone precursors will be used to make
attainment/nonattainment decisions, aid in tracking VOC and NO, emission inventory
reductions, better characterize the nature and extent of the ozone problem, and prepare air
quality trends. In addition, data from the PAMS will provide an improved database for
evaluating photochemical model performance, especially for future control strategy mid-
course corrections as part of the continuing air quality management process. The data will be
particularly useful to States in ensuring the implementation of the most cost-effective
regulatory controls.
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This document was designed to familiarize State and local air authorities with the
enhanced ozone monitoring program and to provide guidance for designing PAMS networks.
In addition to this revised document, EPA has also prepared a revised guidance document on
PAMS measurement methods for ozone and ozone precursor compounds entitled Technical
Assistance Document for Sampling and Analysis of Ozone Precursors (Reference 4). The
user is encouraged to refer to that document for information on manual and automated
sampling techniques for VOC, nonmethane organic compounds (NMOC), and methodologies
for measuring NOX and carbonyls.
1.2 DEVELOPING DATA QUALITY OBJECTIVES
Data Quality Objectives (DQOs) are statements that relate the quality of environmental
measurements to the level of uncertainty that decision-makers are willing to accept for results
derived from the data. The process of developing DQOs starts with the program or project
objectives, in which the goals of the monitoring are laid out This is followed by a
description of the data objectives, which state the kind of monitoring that will be performed.
The DQOs then carry the process to its conclusion, stating how "good" the data need to be to
satisfy the program objectives, with a specified level of confidence. Thus, it is critical that
any set of DQOs be tied closely to the Program Objectives, ensuring that the monitoring will
truly address the stated needs.
It is never possible to be absolutely certain that a future data set will satisfy the data
needs exactly. There is always a chance that variables, variation, and uncertainty beyond the
program's control will lead to a "softness" in the data and a resulting uncertainty that the
subsequent decisions are appropriate. For example, it is not possible to be 100% certain that
a downward trend in ozone concentration has been confirmed or denied, since it is possible
that local meteorology unexpectedly affected the two highest-reading days, one way or the
other. By carefully designing the equipment and schedules, however, it is possible to reduce
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to acceptable levels the possibility of making an erroneous call. In order to accomplish this
task, it is first necessary to narrow each Program Objective to one or more specific
monitoring or data objectives that must be accomplished in order to allow the Program
Objective to be met. Then, a meaningful DQO can be developed for each Program Objective.
The DQOs themselves must quantify the variability or possible error as well as
possible in order for the decision-making risk to be assessed fairly. This can only happen if
there is a base of experience using the technologies and/or methods to be used in the project.
In the case of the PAMS Program, there has never been a monitoring program of this scope
covering these parameters and with similar project objectives.
During the summer of 1990, the EPA conducted a major monitoring study in Atlanta,
Georgia, to address ozone measurements and their precursors. This project was undertaken to
obtain an information base to support the development and implementation of improved
strategies for reducing ozone in cities that are not attaining the NAAQS for ozone. The study
was jointly sponsored by the EPA Atmospheric Research and Exposure Assessment
Laboratory (AREAL) and the Office of Air Quality Planning and Standards (OAQPS), located
in the Research Triangle Park, North Carolina. This study is further described in References
5, 6, and 7. The data compiled in the Atlanta Study, among others, have provided initial
information for the development of these DQOs.
The next section of this document contains the program objectives and specific DQOs
that have been developed for the PAMS Program. As described above, these DQOs are tied
directly to each of the Program Objectives. This is done informally through a narrowed focus
on specific monitoring objectives. It is important to note, however, that all possible uses of
the PAMS data are not now known; therefore, every practical attempt should be made to
improve the quality of the data beyond that necessary to satisfy the explicit DQOs specified
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here. In addition, the DQOs may be used as guides for evaluating requests to utilize
alternative networks, methods, etc.
The DQOs included in this document are preliminary and are expected to be updated
as
• improvements are made in the monitoring and statistical methodologies;
• changes and/or additions are made in the Program Objectives or in the specific
uses of the data; and/or
• results of the monitoring indicate a need.
13 PAMS PROGRAM OBJECTIVES AND INITIAL DATA QUALITY
OBJECTIVES
In contrast to the State and Local Air Monitoring Stations (SLAMS) and National Air
Monitoring Stations (NAMS) network and siting design criteria, which are pollutant specific,
PAMS design considerations are site specific. Concurrent measurements of ozone, NOX,
speciated VOC (including carbonyls), and meteorology are obtained at each PAMS site; upper
air meteorological parameters, however, are required only in one representative location in
each affected area. Design criteria for the PAMS network are based on selection of an array
of sites located specifically to monitor the impact of an area's emissions of ozone precursors
given the predominant wind directions associated with high ozone events. Specific and often
different monitoring objectives (and often different data uses) are therefore associated with
each specific PAMS location. The overall network should supply information sufficient to
develop responsible and cost-effective ozone control strategies; provide appropriate data
support for photochemical grid modeling efforts; allow the reconciliation of emissions
inventories; enable characterization of ozone, ozone precursor and meteorological trends;
provide for improved assessments of ozone attainment; and provide a measure of information
for determining population exposure. A maximum of five PAMS sites is required in an
affected nonattainment area depending on the population of the Metropolitan Statistical
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Area/Consolidated Metropolitan Statistical Area (MSA/CMSA) or nonattainment area, .
whichever is larger.
The monitoring objectives for PAMS can be classified into the six general categories
depicted in Figure 1-2. A monitoring network based on these six principles will provide the
initial stepping stones that constitute a pathway toward attainment of the NAAQS for ozone.
RESPONSIBLE/
COST-EFFECTIVE
CONTROL
^STRATEGIES'
«•
#1
RECONCILIATION
OF EMISSIONS
INVENTORIES
#3
voc
NOx
OZONE
METEOROLOGY
UPPER AIR
CARBONYLS
ATTAINMENT/
NONATTAINMENT
DECISIONS
PHOTOCHEMICAL
MODELING
SUPPORT
#2
OZONE AND
PRECURSOR TRENDS
POPULATION
EXPOSURE ANALYSES
#5 #6
FIGURE 1-2. PAMS PROGRAM AND DESIGN OBJECTIVES
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The design of a PAMS program should result in a network which can be used to
maximize the utility of these data and program design objectives. The EPA acknowledges
that compromises must be achieved (i.e., some more crucial objectives will be better satisfied
than other less important objectives). Nevertheless, each affected air pollution control agency
should make every effort to craft a network which satisfies as many of these objectives as
practicable, yet does not become a financial or operational burden.
OBJECTIVE #1: Provide a speciated ambient air database which is both representative and
useful for ascertaining ambient profiles and distinguishing among various individual VOC.
These data can later be used as evaluation tools for control strategies, cost-effectiveness, and
for understanding the mechanisms of pollutant transport.
RESPONSIBLE/
COST-EFFECTIVE
CONTROL
STRATEGIES
Clearly, a fundamental objective of the enhanced ozone and ozone precursor
monitoring regulations is to provide a mechanism whereby air pollution control agencies can
obtain an air quality database that will assist in evaluating, tracking the progress of, and, if
necessary, refining control strategies for attaining the ozone NAAQS. This comprehensive
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database will allow the States to focus their control strategies where they will be the most
beneficial to attain the NAAQS and to reevaluate their existing ozone control programs with
the aim of appropriate mid-course corrections as part of the continuing air quality
management process. These PAMS data, especially those collected at Sites #1 and #2 (see
Section 2.2 for network site descriptions), will enhance the characterization of ozone
concentrations and provide critical information on the precursors which cause ozone.
Speciation of measured VOC data and additional NOX data are expected to allow the
determination of which species are most affected by local emissions reductions and assist in
developing cost-effective, selective VOC and/or NOX reductions and control strategies.
INITIAL DQOs FOR OBJECTIVE #1:
The primary purpose of the PAMS monitoring networks is to provide speciated
ambient air quality data that can be used
• initially, to provide baseline profiles, and
• eventually, to evaluate and develop cost-effective ozone control strategies.
Based on the results of the Atlanta Study and other recent ambient air monitoring
projects, the PAMS network design and monitoring practices can provide this information. It
is important to include both the network configurations and the monitoring practices
themselves in defining the necessary quality of the monitoring efforts. The DQOs for this
project objective are thus complex and, to some degree subjective. It is not possible to
specify exactly the monitoring accuracy that is needed or possible, since an effort of this
scope has never been conducted for the precursor compounds. However, based on the Atlanta
Study and on EPA's considerable experience with the NAMS/SLAMS networks, it is possible
to define DQOs that make sense.
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Quantifiable DQOs refer to the ability of the network to identify diurnal trends in the
monitoring data corresponding to the diurnal meteorological and emission patterns, and to
detect changes in those patterns after control strategies have been implemented.
Daily Patterns
Ambient monitoring data for all of the pollutants considered in the PAMS program
will be used to:
Determine whether or not there is a daily cycle or pattern in the concentrations
of one or more of the pollutants;
Determine whether or not there is a change in the daily cycle or pattern over
time; and,
By implication, contribute to the evaluation of whether the SIP controls or
other factors (such as land or resource use changes or voluntary emission
reductions) are having an effect on the pattern.
Based on the ozone precursor and ozone data available, it is believed that the most
likely daily cycle would be what is termed "a diurnal cycle" in which the concentration of
one or more pollutants increases to a level significantly above the mean at one time during
the day, and/or decreases to a level significantly below the mean at another time during the
day. An easily measurable surrogate for the diurnal cycle would be the presence or absence
of a single hourly (or three-hourly) time period within a day with a mean concentration 20%
above or below the daily mean. In order to allow a determination of whether this represents
a pattern, the data must be of sufficient quality to show that this phenomenon has occurred
over a given period of time.
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Thus, the following is the first DQO.
DQO #1.1 The data for any given pollutant measured at a PAMS site must be able to
show the presence of a diurnal pattern, if one exists, with an 80% confidence
level
In an individual day, a "diurnal cycle" is the presence of any given hourly (or three-
hourly) time period at a given site for which the mean concentration of the specific pollutant
is at least 20% above or below the mean concentration for that day. A "diurnal pattern" is
the presence of a diurnal cycle that persists over a defined set of daily measurements. A
diurnal pattern is defined as occurring when the mean of the averages of the single specific
hourly (or three-hourly) periods is at least 20% above or below the mean of the daily
averages over the defined set of days. In this case, the defined set of days (the averaging
time periods) are defined as those days for all sites and pollutants for which daily data are
available during the ozone season.
Effects of Controls on Daily Patterns
The second value of the PAMS data as they relate to daily patterns will be the data's
ability to identify a change in the patterns once ozone control strategies have been
implemented.
Thus, the following is the second DQO.
DQO #13 The data for any given pollutant measured at a PAMS site must be able to
show a change in the diurnal pattern, if a change exists, -with an 80%
confidence level
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A diurnal cycle and a diurnal pattern, as well as the defined set of monitoring days,
are the same as for DQO #1.1. The magnitude of the diurnal pattern is the specific percent
difference between the mean of the hourly (or three-hourly) values and the daily averages. A
change in the diurnal pattern is defined as an increase or decrease in the percent differences
of greater than 20% of the daily averages.
OBJECTIVE #2: Provide local, current meteorological and ambient data to serve as initial
and boundary condition information for photochemical grid models. These data can later be
used as a baseline for model evaluation and to minimize model adjustments and reliance on
default settings.
rNTTlAL/lOUNDARY CONDITIONS
PHOTOCHEMICAL
MODELING
SUPPORT
MODEL EVALUATION
MINIMIZE MODEL ADJUSTMENTS
The PAMS network requirements are tailored to provide specific data measurements
which can be utilized by photochemical modelers to refine their estimates of initial and
boundary conditions, provide a means to evaluate the predictive capability of the models, and
minimize the adjustment of model inputs. Such information will tend to increase the
probability that the model's calculations will reflect the "right answer for the right reason"
rather than the "right answer for the wrong reason" and reduce the uncertainties associated
with estimated model inputs. In fact, the upwind site (Site #1) and the downwind site (Site
#4) are located so as to quantify the atmospheric conditions at the upwind and downwind
extremes of the photochemical modeling domain.
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Heretofore, the national air pollution control program has not had the benefit of
comprehensive ozone precursor data as a tool for evaluating, calibrating, or otherwise
adjusting and conducting reality checks on the operation of the Urban Airshed Model (UAM).
EPA views the PAMS networks as vital steps forward in complementing grid model
applications.
INITIAL DQO FOR OBJECTIVE #2:
PAMS data will serve as important inputs to mathematical and statistical
photochemical grid models, in particular, the UAM. The networks, then, must be able to
produce data and data quality sufficient for use in those models. The specific data quality
needed, however, is not easily quantifiable, since the models will "run" with data of almost
any quality. Better data will simply improve the predictive power of the models. As a result,
modeling needs are that the data be "as good as they can be." In practice, this means that the
monitoring must satisfy all of the criteria specified in the regulations. This includes all
aspects of monitor siting, as well as operation.
Thus, the DQO is as follows.
DQO #2.1 The speciated VOC, ozone, NOX and meteorological data must satisfy the
regulations, including monitor siting, operation, and data quality criteria.
OBJECTIVE #3: Provide a representative, speciated ambient air database which is
characteristic of source emission impacts. These data can be particularly useful in analyzing
emissions inventory issues and corroborating progress toward attainment.
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The emissions inventory serves as an essential element of the air management process
as well as a fundamental input for photochemical models. Verification of reported inventories
and the tracking of changes in the atmospheric VOC profiles can assist in the evaluation of
control strategy effectiveness. Given that the inventory is the foundation building block for
the entire SIP development process, it is critical that its accuracy be optimized. While the
regulatory assessments of progress will be made in terms of emission inventory estimates, the
ambient data can provide independent trend analyses and corroboration of these assessments
which either verify or highlight possible errors in emissions trends indicated by inventories.
The ambient assessments, using speciated data, can gauge the accuracy of estimated changes
in emissions. The speciated data can also be used to assess the quality of the speciated VOC
and NO, emission inventories. Utilizing other computer modeling techniques, PAMS data
will help resolve the roles of transported and locally emitted ozone precursors in producing an
observed exceedance and may be utilized to identify specific sources emitting excessive
concentrations of precursors.
PAMS data will be used to corroborate the quality of VOC and NOX emissions
inventories. Although a perfect mathematical relationship between emissions inventories and
ambient measurements does not exist, a comparison of the relative concentrations of various
compounds in the ambient air over a given time period can be contrasted roughly to
emissions inventory estimates over the same time period to evaluate the accuracy of the
emissions inventory reductions. In addition, PAMS data that are gathered year round, such as
the VOC and NOX concentrations at the #2 Sites, will allow tracking of the VOC and NOX
emission reductions on peak and high ozone days (as well as on an annual and seasonal
basis), provide additional information necessary to support Reasonable Further Progress (RFP)
calculations, and corroborate emissions trends analyses.
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INITIAL DQOs FOR OBJECTIVE #3:
There are two DQOs for this Program Objective, one dealing with total VOC, and the
other with speciated VOC.
Total VOC Monitoring
In order for the PAMS data to be useful for this purpose, the network design and
operation must be sufficient to allow a detection of a 3% annual reduction in the seasonal
average concentration over a 5-year monitoring period. The same percent reduction is
specified by Title I of the CAAA for emission reductions for most nonattainment areas. The
season will most often be defined as the highest three-month period.
The results from the Atlanta Study are useful for predicting the likelihood of detecting
a trend in ambient concentrations over time. Based on selected speciated VOC data and the
pooled VOC data, the results indicate that the pooling of data from more than one site clearly
improves the probability that the network will detect a trend in ambient concentrations. For
this reason, the ability of the network to assess the relative accuracy of emissions inventories
for an MSA/CMSA will increase significantly with the addition of a second #2 Site.
Based on the analysis of the predictive value of the Atlanta Study data, the following
is the DQO.
DQO #3.1 The monitoring data for Total Volatile Organic Compound (Total VOC)
concentrations collected at #2 Sites must be able to demonstrate a 3% annual
trend (upward or downward) over a 5-year monitoring period, if it exists,
with an 80% confidence level
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The power, or probability of detecting such a trend for the #2 Site will be 70%. As
an example, in an MSA with an actual reduction in Total VOC ambient concentrations of
greater than 15% over a 5-year period (that is, more than 3% per year), we can have an 80%
confidence level that the data will demonstrate that reduction at least 70% of the time.
Speciated VOC Monitoring
As part of the emissions inventory reconciliation, speciated VOC data will be used for
the following:
• Determining baseline species profiles.
• Determining and differentiating the contributions of various sources and source
types.
• Determining changes in species profiles over time (as may have resulted from
emission control programs, land or resource use changes, voluntary reductions,
etc.).
Because of the combined effects of the large mass of data that will be collected, and
the expected variability between sites and between individual compounds, the data may not
provide meaningful information on the changes in one compound from one year to the next.
In order to assess these changes, it may be necessary to group the speciated VOC into classes.
The results from the Atlanta Study are useful for predicting the likelihood of detecting
a trend in ambient concentrations over time. Selected speciated VOC data indicate that the
pooling of data by compound class clearly improves the probability that the network will
detect a trend in ambient concentrations.
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Thus, the following is the second DQO.
DQO #33 The speciated VOC monitoring data collected at a #2 Site, when composited
into categories, must be able to demonstrate a 20% change (upward or
downward) in the seasonal average between two consecutive years, if it exists,
with an 80% confidence level
OBJECTIVE #4: Provide ambient data measurements which would allow later preparation
of unadjusted and adjusted pollutant trends reports.
OZONE AND
PRECURSOR TRENDS
Long-term PAMS data will be used to assess ambient trends for speciated VOC, NOX,
and, in a more limited way, for toxic air pollutants. Multiple statistical indicators will be
tracked, including ozone and its precursors during the events encompassing the days during
each year with the highest ozone concentrations, the seasonal means for these pollutants, and
the annual means at representative locations. The more PAMS that are established in and
near nonattainment areas, the more accurate the trends data will become. Note, however, that
in general it will only be appropriate to combine data from like sites; therefore, trends will
likely need to be constructed on a site-by-site or combination-of-like-sites basis. As the
spatial distribution and number of ozone and precursor monitors improves, trends analyses
will be less influenced by instrument or site location anomalies. The requirement that surface
meteorological monitoring be established at each PAMS will help maximize the utility of
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these trends analyses by permitting comparisons with meteorological data and transport
influences. The meteorological data can also help interpret the ambient air pollution trends
by taking meteorological factors into account.
There are two basic concepts which may be employed in preparing trends analyses: (1)
displaying unadjusted measurements which portray the quality of the air actually breathed by
the public, and (2) calculating adjusted trends to infer progress towards attainment of
standards due to the influences of pollutant control programs. In either case, the cornerstone
of the analyses are the actual air quality and meteorological measurements such as those
required by PAMS. Particularly, for evaluating the effectiveness of control programs, it may
be appropriate to integrate such factors as meteorology and emissions inventory data. (Note
Appendix B of this document; a similar process could be utilized for VOC.) Since all PAMS
sites will gather comprehensive ambient data in addition to surface meteorological
measurements, all data will be useful for developing pollutant trends, particularly from Sites
#2 and #3.
INITIAL DQOs FOR OBJECTIVE #4:
Based on the historical trends found to be of interest in previous Trends Reports, and
on an analysis of the data from the Atlanta Study, the following is the DQO.
DQO #4.1 The composite monitoring data for a given MSA/CMSA for ozone, NO& and
speciated VOC must be able to demonstrate a yearly downward trend with an
80% confidence level until an area achieves attainment.
The composite data are defined as the average of the ozone season data for a given
pollutant over like monitoring sites in the MSA/CMSA over a 10-year period, as follows:
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Ozone -
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annual second highest daily maximum one-hour concentration
seasonal average
Depending on the total number of sites in an MSA/CMSA, the power, or probability
of detecting such a trend will be as follows:
1 Site - 70%
2 Sites - 80%
3 Sites - 90%
As an example, in an MSA with a single #2 Site and with an actual reduction in
toluene ambient concentrations of more than 30% over a 10-year period (that is, over 3% per
year), we can have an 80% confidence level that the data will demonstrate that reduction at
least 70% of the time.
OBJECTIVE #5: Provide additional measurements of selected criteria pollutants. Such
measurements can later be used for attainment/nonattainment decisions and to construct
NAAQS maintenance plans.
JUDGE ATTAINMENT
ATTAINMENT/
NONATTAINMENT
DECISIONS
SUBSTANTIATE SUCCESS
Stim>RrMAB
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Appendix C of this document). Additionally, the nitrogen dioxide (NOz) data can be utilized
to augment monitoring for compliance with the NAAQS for NO2 where such data are
gathered with the Federal Reference Method (FRM) and taken on a year-round basis.
Ultimately, the success of any air pollution control strategy is appraised by its ability to
achieve compliance with the NAAQS. (Note that the PAMS will expand the spatial coverage
of NAAQS monitoring.) Although the data at any PAMS site can be used for these purposes,
it is expected that Site #3 will more likely constitute the maximum concentration site for
comparison with the NAAQS. Further, the additional data will provide an expanded
foundation for developing and administering maintenance plans required by the CAA.
The ambient ozone monitoring data collected at the PAMS stations must be sufficient
for use in the determinations of attainment status with respect to the ozone NAAQS. As
such, the data must satisfy all of the criteria specified in the NAMS and SLAMS network
regulations, namely 40 CFR 58, which specifies the monitoring criteria (such as monitor
location) and the data quality criteria (such as the required precision and accuracy.)
INITIAL DQOs FOR OBJECTIVE #5:
Thus, the DQO is as follows.
DQO #5.1 The ozone (and NO2 where appropriate) monitoring data must satisfy the
criteria specified in the NAMS and SLAMS monitoring regulations (see
Reference 1), including monitor siting, operation, and data quality criteria.
OBJECTIVE #6: Provide additional measurements of selected criteria and non-criteria
pollutants from properly-sited locations. Such measurements can later be used for evaluating
population exposure to air toxics as well as criteria pollutants.
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BETTER SPATIAL REPRESENTATION
POPULATION
EXPOSURE ANALYSES
PAMS data can be used to better characterize ozone and toxic air pollutant exposure
to populations living in serious, severe, or extreme areas. Annual mean toxic air pollutant
concentrations can be calculated to help estimate the average exposure of the population in
urban environments to individual VOC species which are considered toxic. Specifically, by
measuring the VOC targeted by PAMS, a number of toxic air pollutants will also be
measured. Although compliance with Title I, Section 182 of the CAAA does not require the
measurement and analysis of additional toxic air pollutants, EPA believes that the PAMS
stations can serve as cost-effective platforms for an enhanced air toxics monitoring program.
The adjunct use of PAMS for air toxics monitoring will allow the consideration of air toxics
impacts in the development of future ozone control strategies. The establishment of a second
PAMS Site #2 in an MSA/CMSA will provide an even better database for such uses. Both
Sites #2 and #3 will probably be the best choices for exposure analyses for air toxics and
ozone respectively. EPA notes that the PAMS network is not ideal as a source of primary
ambient air toxics data and regards the collection of air toxics data as an incidental and
secondary, though still important, objective of the PAMS system (see also Appendix J).
INITIAL DQO FOR OBJECTIVE #6:
The DQO is as follows.
DQO 6.1 The speciated VOC monitoring data must be able to provide annual average
concentration data at #2 Sites to within ±50%, with a confidence level of
80%.
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1.4 GENERAL APPROACH
Design criteria for the PAMS network are based on the selection of an array of data
collection sites that satisfy the monitoring objectives as described in Section 1.3 of this
document and which are further delineated in Appendix D, Section 4, of 40 CFR 58. These
sites would allow ambient data on ozone precursor source areas and predominant wind
directions associated with high ozone events to be collected and made accessible through the
Aerometric Information Retrieval System (AIRS) national database. Specific monitoring
objectives are associated with each site location or combination of site locations. The PAMS
network design will enable better characterization of precursor emission sources within an
MSA/CMSA, transport of ozone and ozone precursors into and out of an MSA/CMSA, and
photochemical processes that result in ozone exceedances.
1.5 ORGANIZATION
Section 2.0 of this document describes the PAMS network design and includes
minimum network requirements, and descriptions of monitoring sites and the site selection
process. Section 3.0 defines monitoring methods and network operations. Section 4.0
describes the network planning and approval process. Section 5.0 is reserved. Section 6
contains information on AIRS. Section 7.0 deals with the Technology Transfer Network
(TTN). Section 8.0 contains references.
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2.0 NETWORK DESIGN AND SITING FOR PAMS
2.1 INTRODUCTION
Title 40, Code of Federal Regulations. Part 58 establishes specific criteria and
requirements for national ambient air monitoring systems and provides for the reporting of the
collected measurements and associated data to a national computerized database. Inasmuch as
the vast majority of ambient monitoring stations are operated by the State and local air
pollution control agencies, these existing rules form the foundation for the SLAMS.
Additionally, these agencies operate other ambient monitoring stations which are termed
Special Purpose Monitors (SPM). Although the data collected at most SPM are acceptable to
satisfy national monitoring goals, the stations have been established for SIP purposes and are
not required to comply with the strict data reporting requirements of SLAMS.
A subset of the SLAMS monitors has been formally designated as NAMS. These
stations require the approval of EPA Headquarters prior to establishment or alteration and
therefore provide the nation with a sense of permanence for at least a base or core national
monitoring network. The newly-instituted PAMS will also constitute a subset of the SLAMS
monitors and may be located coincident to NAMS sites.
Each PAMS station will sample for speciated VOC including several carbonyls, ozone,
NOX, and surface (10-meter) meteorological parameters; the frequency requirements vary
somewhat with the size of the MSA/CMSA. Additionally, each area must monitor upper air
meteorology at one representative site. The Rules allow a 5-year transition or phase-in
schedule for the program at a rate of at least one station per area per year. Further, the Rules
provide for the submission and approval of alternative network designs and sampling
schemes. Such alternative mechanisms for compliance with the Rules are especially valuable
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to States which are currently engaged in other forms of ozone precursor monitoring which
have proved adequate for their SIP needs.
2.2 PAMS SITE DESCRIPTIONS
The PAMS network array for an area should be fashioned to supply measurements
which will assist States in understanding and solving ozone nonattainment problems. EPA
has determined that for the larger areas, the minimum network which will provide data
sufficient to satisfy a number of important monitoring objectives should consist of five sites
(Figure 2-1):
Site #1 - Upwind and background characterization site. These sites are
established to characterize upwind background and transported ozone
and its precursor concentrations entering the area and will identify those
areas which are subjected to overwhelming incoming transport of ozone.
The #1 Sites are located in the predominant morning upwind direction
from the local area of maximum precursor emissions and at a distance
sufficient to obtain urban scale measurements. Typically, these sites
will be located near the upwind edge of the photochemical grid model
domain.
Site #2 - Maximum ozone precursor emissions impact site. These sites are
established to monitor the magnitude and type of precursor emissions in
the area where maximum precursor emissions representative of the
MSA/CMSA are expected to impact and are suited for the monitoring
of urban air toxic pollutants. The #2 Sites are located immediately
downwind (using the same morning wind direction as for locating Site
#1) of the area of maximum precursor emissions and are typically
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FIGURE 2-1. ISOLATED AREA
NETWORK DESIGN
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©
CENTRAL BUSINESS DISTRICT
URBANIZED FRINGE
LEGEND:
©- PAMS SITES
Ul - HIGH OZONE DAY PREDOMINANT MORNING WIND DIRECTION
U2 - SECOND MOST PREDOMINANT HIGH OZONE DAY MORNING WIND DIRECTION
U3 - HIGH OZONE DAY PREDOMINANT AFTERNOON WIND DIRECTION
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placed near the downwind boundary of the central business district
(CBD) or primary area of precursor emissions mix to obtain
neighborhood scale measurements. Additionally, a second #2 Site may
be required depending on the size of the area, and should be placed in
the second-most predominant morning wind direction.
Site #3 - Maximum ozone concentration site. These sites are intended to
monitor maximum ozone concentrations occurring downwind from the
area of maximum precursor emissions. Locations for #3 Sites should be
chosen so that urban scale measurements are obtained. Typically, these
sites are located 10 to 30 miles from the fringe of the urban area.
Site #4 - Extreme downwind monitoring site. These sites are established to
characterize the extreme downwind transported ozone and its precursor
concentrations exiting the area and will identify those areas which are
potentially contributing to overwhelming ozone transport into other
areas. The #4 Sites are located in the predominant afternoon downwind
direction from the local area of maximum precursor emissions at a
distance sufficient to obtain urban scale measurements. Typically, these
sites will be located near the downwind edge of the photochemical grid
model domain.
States which experience significant impact from long-range transport of ozone or its
precursors or are proximate to other nonattainment areas (even in other States) can
collectively submit a network description which contains alternative sites to those that would
be required for an isolated area as shown in Figure 2-1. Such coordinated network plans
should, as a guide, be based on the example depicted in Figure 2-2, and must include a
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FIGURE 2-2. MULTI-AREA AND
TRANSPORT AREA
NETWORK DESIGN
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CITYY
CENTRAL
BUSINESS DISTRICT
CITYZ
/
URBANIZED
FRINGE
Ul
LEGEND:
U3
t
NOTE: PAMS CAN SERVE
MULTIPLE PURPOSES FOR
MORE THAN ONE MSA/CMSA.
CD- PAMS SITES
Ul - HIGH OZONE DAY PREDOMINANT MORNING WIND DIRECTION
U2 - SECOND MOST PREDOMINANT HIGH OZONE DAY MORNING WIND DIRECTION
U3 - HIGH OZONE DAY PREDOMINANT AFTERNOON WIND DIRECTION
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demonstration that the alternative design satisfies the monitoring data uses and fulfills the
PAMS objectives described in Section 1.3.
23 SELECTION OF CANDIDATE PAMS SITES
Site selection is one of the most important tasks associated with monitoring network
design and must result in the most representative location to monitor the air quality conditions
being assessed. General recommendations for site selection are provided in this document.
Additional details concerning site selection for monitoring ozone and precursor pollutants may
be found in Site Selection for the Monitoring of Photochemical Air Pollutants (Reference
9). PAMS site selection will follow the general guidance found in that reference. It is
further recommended that photochemical models be used to assist in the design of the PAMS
network.
2.3.1 Spatial Scales
The basis for monitor site selection, according to the referenced guidelines, is to first
match each site-specific monitoring objective to an appropriate scale of spatial representation,
and to then choose a monitoring location that is characteristic of that spatial scale. Five
spatial scales are commonly applied to air pollution monitoring: microscale, middle scale,
neighborhood scale, urban scale, and regional scale. The spatial scales that are most relevant
to the enhanced ozone monitoring network are the urban and neighborhood scales.
The regional scale defines conditions within an area of reasonably homogeneous
geography and extends in distance from tens to hundreds of kilometers.
The urban scale characterizes city-wide conditions with dimensions on the order of 4
to 50 km. Measurements on an "urban" scale represent concentration distributions over a
metropolitan area. Monitoring on this scale relates to precursor emission distributions and
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control strategy plans for an MSA/CMSA. PAMS Sites #1, #3, and #4 are characteristic of
the urban scale.
The neighborhood scale defines conditions within some extended areas of the city that
have a relatively uniform land use and range from 0.5 to 4 km. Measurements on a
neighborhood scale represent conditions throughout a homogeneous urban subregion.
Precursor concentrations, on this scale of a few kilometers, will become well mixed and can
be used to assess exposure impacts and track emissions. Neighborhood data will provide
information on pollutants relative to residential and local business districts. VOC sampling at
Site #2 is characteristic of a neighborhood scale. Measurements of these reactants are ideally
located just downwind of the edge of the urban core emission areas. Further definition of
neighborhood and urban scales is provided in Appendix D of 40 CFR 58 and Reference 9.
2.3.2 General Monitoring Area
After choosing the appropriate spatial scale of representation, a general monitoring
area must be selected that is characteristic of the required spatial scale and consistent with the
monitoring objectives. This is done by reviewing certain background information, including
area land use patterns, emissions inventories, population densities, traffic distributions,
climatological and meteorological data, and any existing monitoring data. The use of gridded
photochemical models is especially useful in defining expected areas of steep concentration
gradients and important source/receptor relationships. Candidate monitoring sites are then
selected from within the general monitoring area by eliminating from consideration all
locations that might be unduly influenced by emissions from specific non-representative
pollution sources or by non-representative topography.
Using the previous guidance, a close examination should be made of the MS As or
CMSAs under review before selecting the monitor locations. A distinction should be made
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between MSAs that are isolated and those that are consolidated into a corridor of urban areas.
The possibility of multi-day transport should be considered in defining isolated urban areas or
corridors of urban areas. Table 2-1 shows all current areas in the United States listed as
serious, severe, or extreme and delineates the size of the minimum PAMS network required
by 40 CFR 58.
Meteorological factors are used to identify which general monitoring areas qualify for
upwind or downwind PAMS sites. The wind patterns, combined with the length of time
required to form ozone, are important factors in locating the monitors for measuring both
maximum precursor and maximum downwind ozone concentrations. The idealized network
design described in this section is partly based on consideration of meteorological conditions.
Meteorological data measurements from existing sites or often from National Weather Service
(NWS) stations can be used to determine the influence of prevailing wind patterns on major
sources in order to pinpoint optimum monitor locations. If available, gridded photochemical
air quality models should be utilized to assist in the siting process.
2.3.3 Selection of General Site Locations
There is considerable flexibility when micrositing each PAMS within a nonattainment
area or transport region. Based on the Rule and the number of required sites obtained from
Table 2-1 (or computed from Table 3-1), the recommended zone areas illustrated in
Figure 2-3 should be considered for narrowing the choices for a final site location. The
prime area for locating a site would be defined by a 45° sector drawn from the center of the
MSA/CMSA (or more accurately, from the centroid of the emissions in the MSA/CMSA)
utilizing the appropriate wind direction designated by the Rule. The centroid may be
calculated utilizing computer modeling techniques or subjectively located using emissions
density maps. The Sector would be limited at its ends by the stipulations of the Rule
regarding approximate distances from the edge of the Central Business District (CBD) or area
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TABLE 2-1. ESTIMATED PAMS REQUIREMENTS FOR CURRENTLY-AFFECTED
AREAS
CURRENTLY-AFFECTED AREA NAME
Beaumont-Port Arthur, TX
Portsmouth-Dover-Rochester, NH-ME
Southeast Desert Modified AQMA, CA
Baton Rouge, LA
El Paso, TX
Springfield, MA
Ventura County, CA
Milwaukee-Racine, WI
Providence-Pawtucket-Fall River, RI-MA
Sacramento, CA
Atlanta, GA
Baltimore, MD
Boston-Lawrence-Worcester, MA-NH
Chicago-Gary-Lake County (IL), IL-IN-W1
Greater Connecticut, CT
Houston-Galveston-Brazoria, TX
Los Angeles-South Coast Air Basin, CA
New York-New Jersey-Long Island, NY-NJ-CT
Philadelphia-Wilmington-Trenton, PA-NJ-DE-MD
San Diego, CA
San Joaquin Valley, CA
Washington, DC-MD-VA
Totals
POPULATION
RANGE
Less Than
500,000
500,000 to
1,000,000
1,000,000 to
2,000,000
More Than
2,000,000
CLASSIFICATION
OF
NONATTAINMENT
AREA
Serious
Serious
Severe
Serious
Serious
Serious
Severe
Severe
Serious
Serious
Serious
Severe
Serious
Severe
Serious
Severe
Extreme
Severe
Severe
Severe
Serious
Serious
22 Areas
MINIMUM
NUMBER OF
REQUIRED
SITES
2
2
2
3
3
3
3
4
4
4
5
5
5
5
5
5
5
5
5
5
5
5
90
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of maximum precursor emissions. Note that as depicted in Figure 2-4, an MS A/CMS A may
be proximate to a fixed area of stationary emissions sources which may be distinctly separate
from the CBD. In such cases, the PAMS site should be located in conjunction with the
centroid of the emissions, or in relation to an area which approximates the best mix of similar
sources. The use of this sectoring technique allows an air pollution control agency to limit its
area of search for appropriate PAMS monitoring sites.
2.3.4 Selection of Final PAMS Sites
There are three fundamental criteria to consider when locating a final PAMS site:
sector analysis, distance, and proximate sources. These three criteria are considered carefully
by EPA when approving or disapproving a candidate site for PAMS.
Sector Analysis - The site needs to be located in the appropriate downwind (or
upwind) sector (approximately 45°) and as indicated by Figure 2-3 utilizing appropriate wind
directions. Ideally, local/nearby meteorological information is used to develop wind roses to
place these sectors. If current, local information is not available, the wind roses contained in
Appendix F may be used. These roses were generated in accordance with the intent of the
Rule utilizing the following criteria:
Years Used For The 10-Year Data Set: 1982-1991
Years Used For The 5-Year Data Set: 1987-1991
• Months used: June, July, and August
• Ozone Conducive Criteria:
Temperature > 85° F
7:00-10:00 a.m. Wind Speed < 10 Knots
1:00- 4:00 p.m. Wind Speed < 14 Knots
1:00- 4:00 p.m. Relative Humidity < 60%
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• Observed High Ozone Days: Ozone Concentration > 0.10 ppm
• Morning Was Defined As 7:00-10:00 a.m. Local Time
Afternoon Was Defined As 1:00-4:00 p.m. Local Time
The Arms Of The Ruses, Point To Where The Wind Was Coming From
The Length Of The Arm Is Proportional To The Percentage Of Time
That The Wind Was Coming From That Direction
• The Various Pieces Of The Arm Represent Speed Categories
Rather than using a few single day wind roses to delineate the appropriate sectors, it is vital
that long-term average roses be employed for the specified time periods on high ozone days
or on those days which exhibit the potential for producing high ozone levels. A 5- or 10-year
database should be sufficient to avoid problems with variability.
Distance - PAMS sites should be located at distances appropriate to obtain a
representative sample of the area's precursor emissions and represent the appropriate
monitoring scale as shown in Table 2-2.
TABLE 2-2. PAMS MEASUREMENT SCALES
SITE
#1
#2
#2a
#3
#4
DIRECTION
Hi-Ozone (Or Ozone-Conducive)
Day Predominant A.M. Wind
Hi-Ozone (Or Ozone-Conducive)
Day Predominant A.M. Wind
Hi-Ozone (Or Ozone-Conducive)
Day Second-Most Predominant
A.M. Wind
Hi-Ozone (Or Ozone-Conducive)
Day Predominant P.M. Wind
Hi-Ozone (Or Ozone-Conducive)
Day Predominant P.M. Wind
LOCATION
Upwind Edge of
Photochemical Model Domain
Area of Representative Maximum
Precursor Emissions - Immediately
Downwind (Primary A.M. Wind)
Area of Maximum Representative
Precursor Emissions - Immediately
Downwind (Secondary A.M. Wind)
Fringe of Urban Area - 10 to 30
Miles Downwind
MSA/CMSA at Downwind Edge of
Photochemical Model Domain
MEASUREMENT SCALE
Urban
Neighborhood
Neighborhood
Urban
Urban
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Most importantly, PAMS sites should be located to measure a representative mix of the
ambient precursors present in a nonattainment MSA/CMSA. Sites #1 should be placed to
intercept the incoming plume of precursors and ozone from other urban areas upwind and
provide information to supplement the data for photochemical modeling.
Sites #2 should be placed in an area where the representative precursor mix from the
particular MSA/CMSA is expected to impact. To ensure that the sensitivities of the sampling
methods are optimized, it is vital that within this sector of impact the levels measured by the
Site #2 are maximized. This location may differ dramatically from a monitoring site which
has been noted to have the maximum historical ozone precursor measurements. Additionally,
although the Rule observes that the #2 Site may typically be located near the downwind
boundary of the CBD, there are a number of situations where this location would not be
appropriate. For example, if a MSA/CMSA contained a significant percentage of stationary
sources which were located in an area different from the CBD, the #2 Site might need to
achieve a compromise location (Figure 2-5) which would monitor both CBD (mostly mobile
and combustion) sources and the group of stationary sources. Ideally, the State would
propose more than one #2 Site for these purposes. Further, a very large MSA/CMSA,
especially those which extend over a number of smaller urban areas and across State lines,
may need to adjust the location of the #2 Site such that it is close enough to the stationary
sources so that the effects of the sources' emissions are not lost in the magnitude of the
mobile source emissions.
Siting for #2 sites should also, within reason, represent the composition of the
emissions inventory. For example, for an emissions inventory as shown in Figure 2-5(a)
which has a 70% mobile source component, Site #2 should not be located so that it is entirely
dominated by stationary point sources. Conversely, as depicted by Figure 2-5(b), an area
which has a significant stationary source component should clearly not contain a PAMS
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FIGURE 2-5. SAMPLE EMISSIONS INVENTORY DESCRIPTIONS
70%
35%
10%
MOBILE
15%
POINT
10%
50%
AREA
5%
BIOGENIC
monitor which is overwhelmed by mobile sources. The difficulty for the Site #2 will be
obtaining a reasonable mix of sources which complements the mix of the emissions inventory.
Information on emissions inventories such as included in Figure 2-5, should be made a part of
any PAMS network plan submittal.
Sites #3 should routinely correspond to the maximum ozone site for the MSA/CMSA
which is located downwind. Note that this #3 Site may not necessarily be collocated with the
ozone design value site for a particular MSA/CMSA. Historically, the design value site may
even be located upwind of the area and be influenced totally by long-range transport of
ozone. Further, an existing site downwind, measuring the highest ozone levels in the area,
may not be the ideal location for a PAMS #3 Site. Site #3 should be reevaluated in light of
the wind directions for siting stipulated by the PAMS Rules, possibly requiring the
establishment of a new location for PAMS.
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Sites #4 should be balanced to provide sufficient downwind information to assist in
photochemical grid models, and also provide the information necessary to replace a Site #1
for a downwind MS A/CMS A whenever possible.
A State or local agency may wish to locate monitoring sites more precisely than this
rather simplified sector analysis would allow. In such cases, conventional vector analysis
employing the appropriate wind roses may be used to track emissions over time and locate
the PAMS sites.
2.3.5 The Use of Saturation Monitoring Techniques
Following the use of a sector and/or vector analysis to locate the suitable area for a
PAMS site, especially the #2 Site, it is preferable to utilize a short-term sampling study to
choose the final PAMS location. A technique which is currently available to simplify such a
monitoring project is the use of "saturation" monitors. Such a study entails the deployment of
a number of portable samplers during the time period of interest, in this case the PAMS
monitoring season, at potential PAMS sites located within the appropriate sector for the
particular site being located. The data from as short a time period as 10 days can be
analyzed to predict with some surety, which sites would be the best candidates for permanent
PAMS installations.
For Sites #1, #3, and #4, such sampling could potentially focus on ozone with either
portable monitors or with passive ozone monitors, modified for short-term use in the ambient
air (see References 10, 11, and 12). These techniques will generally provide average
concentrations. For Sites #2, VOC canister samplers with fixed orifices such as used by
sampling method TO-12 with speciation would be more appropriate. PAMS sites would
commonly be sited in the area of maximum concentration located in the appropriate sector,
yet not unduly influenced by any particular point source of emissions. Since saturation
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studies generally provide only a limited data set, avoiding these particular local influences is
highly important. The usefulness of the short-term data sets can be enhanced by sampling
only on days predicted to experience high ozone levels. Further information on the use of
such saturation sampling techniques can be obtained from Reference 13.
2.3.6 Practical Considerations and Constraints
The are a number of practical considerations which may affect PAMS siting such as
costs, security, topography, and meteorology.
Costs - Given the expense of installing the new technologies for monitoring required
by the PAMS Rules, it is possible that one of the strong driving forces for choosing a
particular site may be State or local budget constraints. EPA estimates the nationwide
cost of constructing a minimum PAMS network to be in excess of $79 million over
the first 5 years of the program, the period designated by the Rule for phase-in. In an
effort to foster compliance with Congressional intent, the EPA formally began funding
the PAMS program through the §105 Grant process in FY-93. It is expected that air
pollution control agencies will supplement the grant funds via use of user fees such as
permit charges, automobile tag fees, etc. Nevertheless, it is important that the quality
of PAMS sites not be compromised simply for costs' sake. Since the data will be
used to satisfy a number of program objectives, it is clearly advantageous to choose
the best available site within the limits of the agency's budget constraints.
In some cases, a State or local agency may be able to locate the PAMS monitors at an
existing SLAMS, NAMS, or private monitoring site. Since some of these existing site
locations may be adequate for PAMS, it would be prudent, especially in light of
funding shortfalls, to evaluate these existing stations to determine which are properly
located to meet the PAMS objectives.
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^*
Security - Experience has shown that in some cases, a particular sector of a
MSA/CMSA may not be appropriate for the establishment of an ambient monitoring
station simply due to problems with the security of the equipment in a certain area. If
the problems cannot be remedied via the use of standard security measures such as
lighting, fences, etc., then attempts should be made to locate the site as near to the
identified sector as possible while maintaining adequate security.
Topography - In cases where unique topography would cause difficulties in locating a
PAMS site (e.g., a site located offshore by the sector analysis), an alternate site or
strategy may be proposed by the State or local agency. Such alternatives must meet
the additional requirements outlined in Section 4.3 of this document.
Meteorology - (Reference 14) In many areas, there are three types of high ozone days:
namely, overwhelming transport, weak transport (or mixed transport and stagnation)
and stagnation. The wind rose concept to site monitors is only applicable to the
transport types, but not applicable to the stagnation type. In general, transport types
dominate north of 40°N, stagnation types dominate the Ohio River Valley and northern
Gulf Coast, and a mixture of the two is observed in the rest of the eastern United
States. In areas where stagnation dominates the high ozone days, a well-defined
primary wind direction (PWD) may not be available. If no well-defined PWD can be
resolved, the major axes of the emissions sources should be used as substitutes for the
PWDs and the PAMS monitors should be located along these axes (Figure 2-6) with
ozone monitors located not more than 10 miles from the urban fringe. The reasons for
these recommendations are as follows: (1) Completely calm conditions seldom last
more than one hour during the day. Most stagnation days have light (<3kts), but
variable winds; (2) Ozone concentrations are likely to be the highest when the winds
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are along the axis of emissions, because precursor concentrations are likely to be
highest and dispersion is minimal.
For coastal cities, synoptic winds are generally influenced by the Seabreeze or lake
breeze circulations. This is typically reflected in the difference of the morning and
afternoon PWDs. The maximum ozone monitors should be located at the downwind
side of the resultant winds (i.e., the vector average of the morning and afternoon
PWDs), keeping the monitors close to the sea/lake breeze convergence zone.
2.3.7 Screening for Effects from Nearby Emissions Sources
The success of the PAMS monitoring program is predicated on the fact that no site is
unduly influenced by any one stationary emissions source or small group of emissions
sources. Any significant influences would cause the ambient levels measured by that
particular site to mimic the emissions rates of this source or sources rather than following the
changes in nonattainment area-wide emissions as intended by the Rule. For purposes of this
screening procedure, if more than 10% of the typical "lower end" concentration measured in
an urban area is due to a nearby source of precursor emissions, then the PAMS site must be
relocated or a more refined analysis conducted than is presented here. In order to minimize
the possibility of locating a source-influenced site, the following simplified procedure has
been included:
a. After locating potential PAMS sites, access the AIRS Facility Subsystem (see
Section 6.0) database or other emissions information to determine the proximity
of any ozone precursor emissions sources.
b. If any sources are closer than 3000 meters in the predominant upwind direction
from the proposed monitoring site, calculate (from the emissions inventory) the
average emissions rate during a typical summer day in grams per second.
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c. Enter either Figure 2-7 for point sources (stack emissions) or Figure 2-8 for
area sources (multiple sources and/or fugitive emissions, e.g., landfills, lagoons,
etc.) with the distance to the proximate source in meters on the X-axis. (Model
inputs and outputs are located in Appendix G of this document for reference.)
d. Read the corresponding concentration in micrograms per cubic meter (ug/m3)
from either the "urban" site or the "rural" site graph. Note that the algorithms
utilized by the SCREEN2 Model (see Reference 15) differentiate between sites
which are located in an urban setting and those which would be considered
rural due to the differences in plume rise noted from large paved and "built-
over" areas to natural areas such as fields, grass, and trees. As a "rule of
thumb", Site #2 should be considered urban. Depending on the situation, Sites
#1, #3, and #4 may be considered urban or rural. For example, in a transport
area such as the northeastern United States, Sites #1, #3, and #4 are most likely
to be urban in nature, whereas in an isolated nonattainment area, the upwind
and downwind sites would more likely be considered rural.
e. Multiply the resultant concentration obtained from the graph by the emissions
from the source in grams per second to obtain the resultant concentration due
to the source at the proposed site location.
f. Compare this resultant concentration to a typical concentration for the
nonattainment area in question.
g. If the computed value is greater than 10% of the typical concentration, then the
site may be improperly sited and be overly reflective of changes in precursor
emissions from a local source or group of sources. In this case, further more
detailed modeling analyses are recommended to clarify the actual impact of the
source(s) on the monitoring site; or, the air pollution control agency should
consider alternate site locations.
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FOR EXAMPLE, a typical "lower end" concentration of Total VOC noted in a recent
short-term urban study was approximately .358 ppmC (358 ppbC).
a. AIRS identifies a stationary source of VOC approximately 2000 meters upwind
of a potential PAMS Site #2 located in an urban setting. Most emissions were
fugitive or from roof vents.
b. The average daily emissions for this source were determined to be
approximately 157 pounds of VOC or 6.54 pounds per hour (24-hour
operation). Since the emissions were determined to be approximately 6.54
pounds per hour then:
Emissions = (6.54 lb/hr)(454 g/lb)(l/3600 hr/sec) = .825 g/sec
The typical mix of compounds in the source emissions obtained from emissions
inventory data [or in this case, from the EPA Volatile Organic
CompoundIParticulate Matter Speciation Data System (SPECIATE)] was as
follows:
TABLE 2-3. SAMPLE SOURCE VOC EMISSIONS PROFILE
COMPOUND
Hexane
Heptane
Trimethylfluorosilane
Benzene
Toluene
NO. CARBONS
6
7
3
6
7
MOL. WEIGHT
86.17
100.20
92.00
78.11
92.13
%w/w
7.00
35.80
40.00
13.60
3.60
c. Since the emissions from this source were mostly fugitive or from roof vents
without stacks, Figure 2-8 was consulted.
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d. Accordingly, from this graph, at a PAMS site located 2000 meters downwind,
this source could affect the VOC measurements by 23 pg/m3 per gram/second
of emissions.
e. Then, the
Change in Concentration Due to the Source = (.825 g/sec)(23 pg-sec/m3-g)
= 19 pg/m3
Utilizing Equation #5 from Table 2-4 and the information in Table 2-3,
Molecular Weight,^ = (86.17)(.07) + (100.20)(.358) + (92)(.4) + (78.11)(.136) + (92.13)(.036)
Molecular Weight^ = 92. g/g-mole
f. The typical urban concentration could be estimated by Equation #2 from Table
2-4,
pg/m3 « (ppbV)(MW) x 273°K, assuming T = 25°C
22.4 298°K
where ppbV is estimated from Equation #1 from Table 2-4 as,
ppbV = ppbC -=- (#C Atoms)
For this mix,
#C AtomsAVBlAGE = (6)(.07) + (7)(.358) + (3)(.4) + (6)(.136) + (7)(.036)
•
from Equation #5 of Table 2-4, or
#C AtomsAV^OT = 5.2
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Then, given that ppbC = 358,
ppbV - 358 -r 5.2 = 68.8 ppbC
and the typical urban concentration in pg/m3 would be
pg/m3 « (68.8K92.6) x 273°K, assuming T = 25°C
22.4 298°K
or
pg/m3 = 260
Then the percent impact this one source has on the proposed PAMS site is
estimated to be
(19 pg/m3 -r 260 pg/m3) x 100% = 7.3%
g. Since this value is less than the "rule-of-thumb" cut-off value of 10%, the site
is considered not unduly influenced by the identified source according to the
screening procedure and may be approved as a PAMS monitoring site. If the
screening value was greater than 10%, more complex analyses would need to
be conducted to support site approval. For the site to be approved, the results
of more comprehensive modeling analyses would need to indicate an impact of
less than 10%.
2.3.8 Probe Siting and Exposure Criteria
The probe siting and exposure criteria for PAMS monitors are similar to those for
NAMS/SLAMS monitors for such items as the minimum distance of the inlet probe from
obstructions, vertical and horizontal probe placement, minimum distances from trees, and
spacing from roadways. These criteria are given in the following subsections. More detailed
guidance can be found in References 4, 9, and 16.
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TABLE 2-4. USEFUL EQUATIONS FOR VOC MIXTURES
1. For estimating ppbV from ppbC:
ppbV = ppbC -r (#C Atoms)
Example: For benzene (C^^), with a concentration of 6.0 ppbC:
ppbV «= 6 T 6 = 1 and therefore
6 ppbC « 1 ppbV for benzene
Where,
ppbC = parts per billion as carbon
ppbV = parts per billion by volume
2. For calculating concentrations in ug/m3, given the constituents of a VOC mix and the concentration in
ppbV then,
ug/m3 = (ppbV)(MW) x 273°K. assuming T = 25°C
22.4 298°K
3. For calculating concentrations in ppbV, given the constituents of a VOC mix and the concentration in
ug/m3 then,
ppbV = (ue/m3)(22.4) x 298°K. assuming T = 25°C
MW 273°K
' or ppbV = (ug/m3) x 24.45
MW
4. Or,
ppbC = (#C) (ug/m3)(22.4) x 298°K. assuming T = 25°C
MW 273°K
and, ppbC = (#C) (ug/m3) x 24.45
MW
5. For VOC mixes:
Molecular Weight = MW = [Z(MW)(%w/w) + 100] and
#Carbons = #C = [Z(#C)(%w/w) -5- 100]
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Vertical and Horizontal Probe Placement - To achieve comparability with NAMS/SLAMS
ozone monitoring data, the height of the inlet probe for PAMS monitors should be as close as
possible to the breathing zone, but must be located 3 to 15 meters above ground level. Since
PAMS involve multi-pollutant measurements, this range serves as a practical compromise for
finding suitable probe positions in the siting area. The probe must also be located more than
1 meter vertically or horizontally away from any supporting structure. Since VOC are not
routinely measured as part of most NAMS/SLAMS monitoring programs, additional siting
criteria comparable to those required for Prevention of Significant Deterioration (PSD)
(Reference 17) monitoring of noncriteria pollutants should also be applied. These criteria
include a minimum separation distance of 2 meters between the inlet probe and any walls,
parapets, penthouses, etc. for probes located on roofs or other structures. In addition, probes
should be located far from any furnace or incineration flues.
Spacing from Obstructions - The probe must be located away from obstacles and buildings
such that the distance between any obstacle and the inlet probe is at least twice the height that
the obstacle protrudes above the sampler. There must be unrestricted airflow in an arc of at
least 270° around the inlet probe, and the predominant and second most predominant wind
direction during the sampling period must be included in the 270° arc. If the probe is located
on the side of a building, 180° clearance is required.
Spacing from Trees - Trees can provide surfaces for adsorption and/or chemical reactions,
and can also affect normal wind flow patterns. To limit these effects, probe inlets should be
placed at least 20 meters from the dripline of any trees and must be more than 10 meters
from the dripline of any trees that are located between the urban city core area (or other area
of maximum ozone precursor emissions) and the monitoring station along the predominant
sampling period daytime wind direction utilized for establishing the site.
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Spacing from Roads - Motor vehicle emissions constitute a major source of both ozone
precursors and ozone-scavenging compounds. It is important, therefore, to maintain a
minimum separation distance between roadways and PAMS monitoring sites such that the
representation of the resulting monitoring data is not compromised. Table 2-5 gives the
required minimum separation distances from roadways for various traffic volumes. The
minimum separation distance must also be maintained between a PAMS station and other
similar areas of automotive traffic, such as parking lots. Nearby roads should be far enough
away from Sites #2 and #3 probe inlets to avoid producing localized ozone sinks. Likewise,
nearby roads should not be located near Sites #1, #3, and #4 probe inlets, as precursor
pollutants could have a local influence on these area-representative sites.
TABLE 2-5. SEPARATION DISTANCE BETWEEN PAMS AND ROADWAYS
(EDGE OF NEAREST TRAFFIC LANE)1
ROADWAY AVERAGE DAILY TRAFFIC
VEHICLES PER DAY
<10,000
15,000
20,000
40,000
70,000
> 11 0,000
MINIMUM SEPARATION DISTANCE BETWEEN
ROADWAYS AND STATIONS IN METERS2
>10
20
30
50
100
>250
1 Reference 1, Appendix E
1 Distances should be interpolated based on traffic flow.
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Exposure of Meteorological Instruments - The 10-meter meteorological tower at each
PAMS site should be located such that the resulting measurement data are representative of
the meteorological conditions that affect pollutant transport and dispersion within the area that
the monitoring site is intended to represent. Meteorological instruments should be located
away from the immediate influence of trees, buildings, steep slopes, ridges, cliffs, and
hollows.
Additional guidance for siting meteorological instruments is given in References 4, 16.
17, 18, and 19.
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3.0 MONITORING METHODS AND NETWORK
OPERATIONS
3.1 MONITORING METHODS
The Code of Federal Regulations Part 50 (40 CFR 50) delineates the NAAQS for six
ambient air pollutants, often termed "criteria" pollutants. The associated approved or
"reference" methods for ambient sampling and analysis (in accordance with 40 CFR 53) are
also codified in the appendices to Part 50. Acceptable equivalent methods, as determined by
the procedures outlined in 40 CFR Part 53 (Reference 20), are periodically published by the
EPA Atmospheric Research and Exposure Assessment Laboratory (AREAL). The most
recent list is included in Appendix H of this document.
The PAMS rules (40 CFR 58) require the use of automated reference or equivalent
methods to monitor for ambient concentrations of ozone, NO, NO2, and NOX, when measured
at PAMS stations. Current methods for measuring N02 also measure NO and NOX, therefore,
the result of the PAMS rules is to require continuous monitoring for ozone and N02 and the
additional reporting of the coincidently measured NO and NOX.
The Federal Reference Method (FRM) for NO2 has limited ability to accurately
describe the role of NOX in the local photochemical process during all periods of a summer
day, and to discriminate among the impacts of various sources of NOX. Consequently, EPA
has encouraged State air pollution control agencies to employ more sensitive measurement
techniques for NOX. Additionally, EPA has noted the value of deploying instrumentation
designed to measure total reactive oxides of nitrogen (N0y), which includes such compounds
as NOX, NO, NO2, peroxyacetyl nitrate (PAN), and nitric acid (HNO3). Since the PAMS
network is primarily designed to quantify the local precursors of ozone and not serve as an
additional principal network for N02 attainment purposes, EPA is predisposed to allow such
non-FRM techniques for the measurement of NOX. Any techniques other than the FRM,
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however, will need to be detailed in the network description required by 40 CFR 58.40 and
subsequently approved by the Administrator as part of an area-specific plan. Further, the
Agency has recognized 'that the measurement of more highly oxidized forms of nitrogen
requires a high degree of skill/training using non-standard techniques to measure pollutants at
very low concentrations and has determined that it is premature to require such efforts in a
routinely-operated network. Future revisions to this guidance will contain information for
conducting more sensitive and definitive NOX measurements.
With the promulgation of the PAMS rules, for the first time, EPA rules require
national ambient monitoring for pollutants (such as VOC and meteorological parameters)
which do not have associated NAAQS. Additionally, no FRMs have been established for
these compounds. Consequently, to maintain a reasonable level of national consistency and
comparability, States are required by 40 CFR 58, Appendix C, to follow the guidance for
sampling and analysis of these parameters published in References 4, 16, 17, 18, and 19.
The Technical Assistance Document for Sampling and Analysis of Ozone Precursors
(hereafter referred to as the Technical Assistance Document or TAD) provides technical
information and guidance to Regional, State, and local air pollution control agencies
responsible for measuring ozone precursor compounds in the ambient air. Sampling and
analytical methodology for speciated VOC, total non-methane organic compounds (NMOC)
and selected carbonyl compounds (i.e., formaldehyde, acetaldehyde and acetone) are
specifically addressed. This document also addresses the methodology for measuring NOX
and discusses many of the issues associated with measuring N0y and includes technical
direction, to supplement the information provided in Reference 16, for measuring the
meteorological parameters prescribed by the regulations.
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EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-3
The technical guidance for measuring VOC ozone precursors is based on emerging
and developing technology. Guidance for automated applications, in particular, is based to a
significant extent on the experience obtained from the application of the technology during
past ozone precursor studies such as the 1990 Atlanta Ozone Precursor Study. The VOC
sampling and analysis methods explained in the Technical Assistance Document are based on
these state-of-the-art emerging technologies, and they will be subjected to continuing
evaluation and will be periodically revised to incorporate resulting improvements and
clarifications.
3.2 OPERATING SCHEDULES AND SAMPLING FREQUENCIES
3.2.1 General Operating Requirements
In addition to requiring reasonably consistent methodologies for sampling precursors
and meteorological parameters, 40 CFR 58.13 (and subsequently 40 CFR 58, Appendix D),
specifies minimum network requirements and sampling frequencies. For clarity, Table 2 of
Appendix D of the codified Rule has been reformatted and follows as Table 3-1. The
monitoring requirements are explained further in Sections 3.2.3 to 3.2.6 of this document. In
summary, these standards require the use of continuous monitors for ozone, NOX and
meteorological parameters. VOC and carbonyls can utilize manual methods, but due to the
required frequencies, continuous monitoring technology appears to be more cost-effective.
Further information on the target VOC listed in Reference 4 may be found in Tables 3-2 and
3-3.
Section 4.3 of 40 CFR 58, Appendix D, stipulates that the PAMS monitoring should
be conducted annually throughout the months of June, July and August as a minimum. In
most States, these months incorporate the periods when peak ozone values are likely to occur.
EPA, however, encourages the States to extend the PAMS monitoring period whenever
feasible to include the entire ozone season or perhaps the entire calendar year. Monitoring
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EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-4
TABLE 3-1. PAMS MINIMUM NETWORK REQUIREMENTS
MINIMUM NETWORK REQUIREMENTS |
POPULATION OFMSA/CMSA
LESS THAN 500,000
500,000
TO
1,000,000
1,000,000
TO
2,000,000
GREATER
THAN
2,000,000
FREQ
TYPE
AorC
A/Dor
C/F
AorC
B/E
AorC
AorC
B/E
B/E
AorC
AorC
B/E
B/E
AorC
AorC
SITE LOCATION
(1)
(2)
(1)
(2)
(3)
(1)
(2)
(2)
(3)
(1)
(2)
(2)
(3)
(4)
1
Type
A
B
C
VOC SAMPLING FREQUENCY REQUIREMENTS
Requirement
8 3-Hour Samples Every Third Dav
1 24-Hour Sample Every Sixth Day _
8 3-Hour Samples Everyday
1 24-Hour Samgle Every_Sixth Day_£year-round)
8 3-Hr Samples 5 Hi-Event/Previous Days & Every 6th
1 24-Hour Sample Every Sixth Day
»
Day
ICARBONYL SAMPLING FREQUENCY REQUIREMENTS |
Type
D
E
F
Requirement
8 3-Hour Samples Every Third Day
8 3-Hour Samples Everyday
8 3-Hr Samples 5 Hi-Event/Previous Days &
Every 6th Day
MINIMUM PHASE-IN |
YEARS AFTER
PROMULGATION
1
2
3
4
5
NUMBER OF
SITES OPERATING
1
2
3
4
5
OPERATING
SITE LOCATION
RECOMMENDATIO*
2
2,3
1,2,3
1,2,3,4
1,2,2,3,4
which is conducted on an intermittent schedule should be coincident with the previously-
established intermittent schedule for particulate matter sampling. The codified ozone
monitoring seasons for the PAMS-affected States are displayed in Table 3-4.
-------
TABLE 3-2. TARGET VOC OZONE PRECURSORS AND SYNONYMS
CHEMICAL ABSTRACT
SERVICE. (CAS) #
74-86-2
74-85-1
74-84-0
115-07-1
74-98-6
75-28-5
106-98-9
106-97-8
624-64-6
590-18-1
563-45-1
78-78-4
109-67-1
109-66-0
78-79-5
646-04-8
627-20-3
513-35-9
75-83-2
142-29-0
691-37-2
287-92-3
79-29-8
107-83-5
96-14-0
76-32-91
110-54-3
4050-47-7
7688-21-3
96-37-7
108-08-7
71-43-2
110-82-7
591-76-4
565-59-3
589-34-4
540-84-1
142-82-5
108-87-2
565-75-3
108-88-3
592-27-8
589-81-1
111-65-9
100-41-4
10642-3
100-42-5
95-47-6
111-84-2
98-82-8
103-65-1
7785-70-8*
108-67-8
95-63-6
127-91-3*
124-18-5
1120-21-4
108-38-3
50-00-0
67-64-1
75-07-0
-
PAMS RECOGNIZED
REPORTING NAME
Acetylene
Ethylene
Ethane
Propylene
Propane
Isobuune
1-Butene
n-Butane
trans-2-Butene
cis-2-Butene
3-Methyl-l-Butene
Isopentane
1-Pentene
n-Pentane
Isoprene
trans-2-Pentene
cis-2-Pentene
2-Methyl-2-Butene
2,2-Dimethylbutane
Cyclopentene
4-Methyl-l-Pentene
Cyclopentane
2.3-Dimethylbutane
2-Methylpentane
3-Methylpentane
2-Methyl-l-Pentene
n-Hexane
trans-2-Hexene
cis-2-Hexene
Methylcyclopentane
2,4-Dimethylpentane
Benzene
Cyclohexane
2-Methylhexane
2,3-Dimethylpentane
3-Methylhexane
2,2,4-Trimethylpentane
n-Heptane
Methylcyclohexane
2.3,4-Trimethylpentane
Toluene
2-Methylheptane
3-Methylheptane
n-Octane
Ethylbenzene
p-Xylene**
Styrene
o-Xylene
n-Nonane
Isopropylbenzene
n-Propylbenzene
a-Pinene
1,3,5-Trimethylbenzene
1 ,2,4-Trimethylbenzene
B-Pinene
n-Decane
n-Undecane
m-Xylene**
Formaldehyde
Acetone
Acetaldehyde
Total non-methane organic compounds
COMMON"
SYNONYM
Ethyne
Ethene
Methylmethane
Propene
Dimethylmethane
2-Methylpropane
Ethylethylene
Butane
Isopropylethylene
2-Methylbuiane
Propylethylene
Amyl Hydride
3-Methyl-l ,3-Butadiene
cis-6-n-Amylene
Neohexane
Pentamethylene
Diisopropyl
Isohexane
Diethylmethylmethane
1 -Methyl-1 -Propylethylene
Hexametbylene
Isoheptane
Dipropylm ethane
Hexahydrotoluene
Methylbenzene
Isooctane
Phenylethane
1 ,4-Dimethylbenzene
Ethenylbenzene
1 ,2-Dimethylbenzene
Nonyl Hydride
Cumene
1-Phenylpropane
Mesitylene
Pseudocumene
Nopinene
1 ,3 -Dimethylbenzene
Oxymethylene
Ehmethylketone
Acetic Aldehyde
Total NMOC
EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-5
'Generic CAS #'s for these compounds. **Co-eluters on the GC column.
-------
TABLE 3-3A. TARGET VOC OZONE PRECURSORS - HYDROCARBONS
EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-6
CHEMICAL
ABSTRACT
SERVICE, (CAS) #
74-86-2
74-85-1
74-84-0
115-07-1
74-98-6
75-28-5
106-98-9
106-97-8
624-64-6
590-18-1
563-45-1
78-78-4
109-67-1
109-66-0
78-79-5
646-04-8
627-20-3
513-35-9
75-83-2
142-29-0
691-37-2
287-92-3
79-29-8
107-83-5
96-14-0
763-29-1
110-54-3
4050-47-7
7688-21-3
96-37-7
108-08-7
71-43-2
110-82-7
591-76-4
565-59-3
589-34-4
540-84-1
142-82-5
108-87-2
565-75-3
108-88-3
592-27-8
589-81-1
111-65-9
100-41-4
-
106-42-3
100-42-5
95-47-6
111-84-2
98-82-8
103-65-1
7785-70-8*
108-67-8
95-63-6
127-91-3
124-18-5
1120-21-4
108-38-3
—
PAMS RECOGNIZED
REPORTING NAME
Acetylene
Ethylene
Ethane
Propylene
Propane
Isobuiane
1-Butene
n-I Jtane
truiis-I-Buiefie
cis-2-Butene
3-Methyl-l-Bmene
Isopentane
1-Pentene
n-Pentane
Isoprene
trans-2-Pentene
cis-2-Pentene
2-Methyl-2-Butene
2.2-Dimethylbutane
Cyclopentene
4-Methyl-l-Pemene
Cyclopentane
2,3-Dimeihylbutane
2-Methylpentane
3-Methylpentane
2-Methyl-l-Pente" •
n-Hexane
Uans-2-Hexene
cis-2-Hexene
Methylcyclopentane
2,4-Dimeshylpiniane
Benzene
Cyclohexane
2-Methylhexane
2,3-Dunethylpentane
3-Methylhexane
2,2,4-Tnmethylpentane
n-Heptane
Methylcyclohexane
2,3./l -Trimethylpentane
Toluene
2-Methylheptane
3-Methylheptane
n-Octane
Ethylbenzene
m/p-Xvlene**
(p-Xyiene)**
Styrene
o-Xylene
n-Nonane
Isopropylbenzene
n-Propylbenzene
alpha-Pinene
1 34-Trimethylbenzene
1 ,2,4-Trimethy Ibenzene
beta-Pinene
n-Decane
n-Undecane
(m-Xylene)**
Total Non-Methane Organic Compounds
AIRS
PARAMETER
CODE#
43206
43203
43202
43205
43204
43214
43280
43212
43216
43217
43282
43221
43224
43220
43243
43226
43227
43228
43244
43283
43234
43242
43284
43285
43230
43246
43231
43289
43290
43262
43247
45201
43248
43263
43291
43249
43250
43232
4326!
43252
45202
43960
43253
43233
45203
45109
45206
45220
45204
43235
45210
45209
43256
45207
45208
43257
43238
43954
45205
43102
CHEMICAL
FORMULA
c:H2
C,H4
CJH,
C,H<
C3H,
C4H]<>
C4H,
C4H,0
C4H,
C4H,
C5H10
C5HP.
C5H10
C5H,2
C5H,0
CjHio
CsH10
C5H10
C«H14
C5H,
C5H10
CjH10
C,HU
QHU
C,H14
C«H,2
C6H,4
C6H,2
C6H,2
C6H,2
C,H,6
CSH6
CSH12
C,H16
C,H16
C,H,,
C,H,,
CjH,,
C,H14
C,H,,
C,H,
C.H.,
C,H,,
C.H.,
CfH10
-- .
C|H10
C,H,
C,HIO
C,Ha
C^12
C^,2
a-C10H16
C^12
C^12
6-C|oH,6
CioH^
C..H*
C,H,,
PAMS
RECOGNIZED
ABBREVIATION
acety
ethyl
eihan
prpyl
propa
isbta
Ibute
nbuta
t2bte
c2bte
3mlbe
ispna
Ipnte
npma
ispre
t2pne
c2pne
2m2be
22dmb
cypne
4mlpe
cypna
23dmb
2mpna
3mpna
2mlpe
nhexa
t2hex
c2hex
mcpna
24dmp
benz
cyhxa
2mhxa
23dmp
3mhxa
224tmp
nhept
mcyhx
234tmp
tolu
2mhep
3mhep
noct
, ebenz
m/pxy
pxyl
styr
oxyl
nnon
ispbz
npbz
apine
135tmb
124tmb
bpine
ndec
nundc
mxyl
tnmoc
'Generic CAS # for this compound. **m-Xylene and p-Xylene co-elute on the GC column, use m/p-Xylene parameter code for reporting.
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EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-7
TABLE 3-3B. TARGET VOC OZONE PRECURSORS - CARBONYLS
CHEMICAL
ABSTRACT
SERVICE, (CAS) #
50-00-0
67-64-1
75-07-0
PAMS RECOGNIZED
REPORTING NAME
Formaldehyde
Acetone
Acetaldehyde
AIRS
PARAMETER
CODE*
43502
43551
43503
CHEMICAL
FORMULA
HCHO
CHjCOCH,
CHjCHO
PAMS
RECOGNIZED
ABBREVIATION
form
acet
aceta
TABLE 3-4. OZONE MONITORING SEASONS
PAMS-AFFECTED STATES
STATE
California
Connecticut
Delaware
District of Columbia
Georgia
Illinois
Indiana
Louisiana
Maine
Maryland
Massachusetts
New Hampshire
New Jersey
New York
Pennsylvania
Rhode Island
Texas AQCR 4, 5, 7, 10, 11
Texas AQCR 1, 2, 3, 6, 8, 9, 12
Virginia
Wisconsin
BEGIN MONTH
January
April
April
April
March
April
April
January
April
April
April
April
April
April
April
April
January
March
April
April
END MONTH
December
October
October
October
November
October
October
December
October
October
October
October
October
October
October
October
December
October
October
October
3.2.2 Explanation of Specific PAMS Network Requirements
For ease in determining the specific monitoring requirements for any particular
MSA/CMSA, the following sections detail the minimum network requirements specified by
Table 3-1.
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EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-8
3.2.3 Requirements for MSA/CMSAs With Populations Less Than 500,000
The following is a summary of the PAMS monitoring requirements for small
MSA/CMSAs having populations of less than 500,000, according to the most recent decennial
United States census population report:
REQUIRED
MONITORING
SITE
POLLUTANT
MINIMUM MONITORING FREQUENCIES
voc
SITE#1
Carbonyls
Eight 3-hour samples every third day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-iound)
OR if an agency chooses to monitor episodes, the following may be substituted:
Eight 3-hour samples on the five peak ozone days plus each previous day and,
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
No resulatory requirement - Monitoring is preferred according to the schedule
chosen for VOC
SITE #2
VOC
Carbonyls
VOC
Carbonyls
Eight 3-hour samples every third day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
and,
Eight 3-hour samples every third day during the monitoring period and,
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
OR if an agency chooses to monitor episodes, the following may be substituted:
Eight ?-hour samples on the five peak ozone days plus each previous day and,
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
and.
Eight 3-hour samples on the five peak ozone days plus each previous day and,
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
In addition to the required monitoring for VOC and carbonyls, the following
monitoring for other measurements is specified by the Rule:
REQUIRED
MONITORING
SITE
ALL SITES
ONE
REPRESENTATIVE
SITE PER AREA
POLLUTANT
Ozone
Oxides of
Nitrogen
Meteorology
Upper Air
Measurements
MINIMUM MONITORING REQUIREMENTS
Continuous monitoring during the entire ozone season listed in Table 3-2
Continuous monitoring during the PAMS monitoring period (preferably year-round)
Surface (10-meter) continuous monitoring of wind speed/direction, ambient °T,
barometric pressure, relative humidity, and solar radiation during the PAMS
monitoring period (preferably year-round)
Continuous monitoring of mixing height or surrogate during the PAMS
monitoring period (preferably year-round)
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EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-9
Since only two PAMS monitoring stations are required for these MSA/CMSAs, the
recommended order for establishing sites is Site #2, then Site #1. The network should be
complete within 2 years.
3.2.4 Requirements for MSA/CMSAs With Populations of 500,000 to 1,000,000
The following is a summary of the PAMS monitoring requirements for MSA/CMSAs
having populations of 500,000 to 1,000,000, according to the most recent decennial United
States census population report:
REQUIRED
MONITORING
SITE
POLLUTANT
MINIMUM MONITORING FREQUENCIES
SITE#1
voc
Caibonyls
Eight 3-hour samples every third day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
OR if an agency chooses to monitor episodes, the following,may be substituted:
Eight 3-hour samples on the five peak ozone days plus each previous day and,
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
No regulatory requirement - Monitoring is preferred according to the schedule
chosen for VOC
SITE #2
VOC
Carbonyls
Eight 3-hour samples every day during the monitoring period and,
One 24-hour sample every sixth day year-round and,
Eight 3-hour samples every day during the monitoring period and,
One 24-hour sample every sixth day year-round
SITE #3
VOC
Carbonyls
Eight 3-hour samples every third day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
OR if an agency chooses to monitor episodes, the following may be substituted:
Eight 3-hour samples on the five peak ozone days plus each previous day and.
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
No regulatory requirement - Monitoring is preferred according to the schedule
chosen for VOC
In addition to the required monitoring for VOC and carbonyls, the following
monitoring for other measurements is specified by the Rule:
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EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-10
REQUIRED
MONITORING
SITE
ALL SITES
ONE
REPRESENTATIVE
SITE PER AREA
POLLUTANT
Ozone
Oxides of
Nitrogen
Meteorology
Upper Air
Measurements
MINIMUM MONITORING REQUIREMENTS
Continuous monitoring during the entire ozone season listed in Table 3-2
Continuous monitoring during the PAMS monitoring period (preferably year-round)
Surface (10-meter) continuous monitoring of wind speed/direction, ambient °T,
barometric pressure, relative humidity, and solar radiation during the PAMS
monitoring period (preferably year-round)
Continuous monitoring of mixing height or surrogate during the PAMS
monitoring period (preferably year-round)
Since three PAMS monitoring stations are required for these MSA/CMSAs, the recommended
order for establishment of sites is Site #2, Site #3, then Site #1. The network should be
complete within 3 years.
3.2.5 Requirements for MSA/CMSAs With Populations of 1,000,000 to 2,000,000
The following is a summary of the PAMS monitoring requirements for MSA/CMSAs
having populations of 1,000,000 to 2,000,000, according to the most recent decennial United
States census population report:
REQUIRED
MONITORING
SITE
POLLUTANT
MINIMUM MONITORING FREQUENCIES
SITE#1
voc
Carbonvls
Eight 3-hour samples every third day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
OR if an agency chooses to monitor episodes, the following may be substituted:
Eight 3-hour samples on the five peak ozone days plus each previous day and,
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
No regulatory requirement - Monitoring is preferred according to the schedule
chosen for VOC
SITE #2
VOC
Carbonyls
Eight 3-hour samples every day during the monitoring period and,
One 24-hour sample every sixth day year-round and,
Eight 3-hour samples every day during the monitoring period and.
One 24-hour sample every sixth day year-round
SITE #2
(Second)
VOC
Carbonyls
Eight 3-hour samples every day during the monitoring period and.
One 24-hour sample every sixth day year-round and,
Eight 3-hour samples every day during the monitoring period and,
One 24-hour sample every sixth day year-round
SITE #3
VOC
Carbonyls
Eight 3-hour samples every third day during the monitoring period and,
One 24-hour sample every sixth day during the monitoring"period (preferably year-round)
OR if an agency chooses to monitor episodes, the following may be substituted:
Eight 3-hour samples on the five peak ozone days plus each previous day and,
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
No regulatory requirement - Monitoring is preferred according to the schedule
chosen fo'r VOC
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EPA-454/B-93-051
Section No.: 3
Revision No.: 0
Date: March 1994
Page 3-11
In addition to the required monitoring for VOC and carbonyls, the following
monitoring for other measurements is specified by the Rule:
REQUIRED
MONITORING SITE
ALL SITES
ONE
REPRESENTATIVE
SITE PER AREA
POLLUTANT
Ozone
Oxides of
Nitrogen
Meteorology
Upper Air
Measurements
MINIMUM MONITORING REQUIREMENTS
Continuous monitoring during the enure ozone season listed in Table 3-2
Continuous monitoring during the PAMS monitoring period (preferably year-round)
Surface (10-meter) continuous monitoring of wind speed/direction, ambient °T,
barometric pressure, relative humidity, and solar radiation during the PAMS
monitoring period (preferably year-round)
Continuous monitoring of mixing height or surrogate during the PAMS
monitoring period (preferably year-round)
Since four PAMS monitoring stations are required for these MSA/CMSAs, the recommended
order for establishment of sites is Site #2, Site #3, Site #1, then the second Site #2. The
network should be complete within 4 years.
3.2.6 Requirements for MSA/CMSAs With Populations of Greater Than 2,000,000
The following is a summary of the PAMS monitoring requirements for MSA/CMSAs
having populations of greater than 2,000,000, according to the most recent decennial United
States census population report:
REQUIRED
MONITORING
SITE
SITE#1
SITE #2
POLLUTANT
VOC
Carbonyls
VOC
Carbonyls
MINIMUM MONITORING FREQUENCIES
Eight 3-hour samples every third day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
OR if an agency chooses to monitor episodes, the following may be substituted:
Eight 3-hour samples on the five peak ozone days plus each previous day and.
Eight 3 -hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
No regulatory requirement - Monitoring is preferred according to the schedule
chosen for VOC
Eight 3-hour samples every day during the monitoring period and,
One 24-hour sample every sixth day year-round and.
Eight 3-hour samples every day during the monitoring period and,
One 24-hour sample every sixth day year-round
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EPA-454/B-93-051
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Revision No.: 0
Date: March 1994
Page 3-12
REQUIRED
MONITORING
SITE
POLLUTANT
MINIMUM MONITORING FREQUENCIES
SITE #2
(Second)
VOC
Carbonvls
Eight 3-hour samples every day during the monitoring period and.
One 24-hour sample every sixth day year-round and.
High: ?-hour samples every day during the monitoring period and.
One 24-hour sample every sixth day year-round
VOC
SITE #3
Carbonyls
Eight 3-hour samples every third day daring the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
OR if an agency chooses to monitor episodes, the following may be substituted:
Eight 3-hour samples on the five peak ozone days plus each previous day and,
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
No regulatory requirement - Monitoring is preferred according to the schedule
chosen for VOC
VOC
SITE 4
Carbonyls
Eight 3-hour samples every third day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
OR if an agency chooses to monitor episodes, the following may be substituted:
Eight 3-hour samples on the five peak ozone days plus each previous day and,
Eight 3-hour samples every sixth day during the monitoring period and.
One 24-hour sample every sixth day during the monitoring period (preferably year-round)
No regulatory requirement - Monitoring is preferred according to the schedule
chosen for VOC
In addition to the required mon: orin-T for VOC and carbonyls, the following
monitoring for other measurements is specified by the Rule:
REQUIRED
MONITORING
SITE
ALL SITES
ONE
REPRESENTATIVE
SITE PER AREA
POLLUTANT
Ozone
Oxides of
Nitrogen
Meteorology
Upper Air
Measurements
MINIMUM MONITORING REQUIREMENTS
Continuous monitoring during the entire ozone season listed in Table 3-2
Continuous monitoring during the PAMS monitoring period (preferably year-round)
Surface (10-meter) continuous monitoring of wind speed/direction, ambient T,
barometric pressure, relative humidity, and solar radiation during the PAMS
monitoring period (preferably year-round)
Continuous monitoring of mixing height or surrogate during the PAMS
monitoring period (preferably year-round)
Since five PAMS monitoring stations are required for these MSA/CMSAs, the recommended
order for establishment of sites is Site #2, Site #3, Site #1, Site #4, and then the second Site
#2. The network should be complete within 5 years.
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Intermittent monitoring in all MSA/CMSAs, regardless of population, should be
coincident with the previously-established intermittent schedule for particulate matter to
ensure a degree of national consistency in accordance with 40 CFR 58, Appendix D, Section
4.3.
33 ALTERNATIVE SAMPLING AND ANALYSIS METHODOLOGY
EPA recognizes that State and local air pollution control agencies will be subject to
unique problems and authority limitations. Further, their operation of the PAMS network
may need to be tailored to complement unusual geographical and demographical situations,
especially distinctive meteorology. Appendix C of 40 CFR 58 notes that deviations from the
guidance are acceptable for sampling and analysis so long as the alternatives are detailed in
the network description required by §58.40 and subsequently approved by the Administrator.
3.4 MONITORING FOR AIR TOXICS
An urban air toxics monitoring research program is required for a number of VOC
species and other hazardous air pollutants by Title HI, Section 301, of the CAAA. EPA
believes that the PAMS stations will be available as platforms for the additional monitoring of
air toxics compounds. Specifically, it is noted by the Agency that by measuring the VOC
targeted in Reference 4, a number of toxic air pollutants will also be measured. Although
compliance with Title I, Section 182 of the Act does not require the measurement and
analysis of additional toxic air pollutants, the Agency believes that the PAMS stations can
serve as cost-effective platforms for an enhanced air toxics research and ambient monitoring
program. The adjunct use of PAMS for air toxics monitoring will allow the consideration of
air toxics impacts in the development of future ozone control strategies. The establishment of
a second PAMS #2 site will provide an even better database for such uses. The Agency,
however, notes that the PAMS network is not ideally located as a source of primary air toxics
data, but the network will serve as a base for future air toxics monitoring activities.
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Methods typically used for air toxics measurement are not addressed in this guidance
document Manual methods, such as canister sampling for VOC species, will be used for
both quality assurance purposes to check the continuous VOC measurement data and to
provide estimates of annual means for air toxics assessment purposes. Other hazardous
compounds, including metals, pesticides, semi-volatiles, polar compounds and products of
incomplete combustion (PICs) will be measured, provided resources are available.
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4.0 PAMS NETWORK PLAN AND APPROVAL
4.1 INTRODUCTION
Two types of network plans are allowed under the Part 58 PAMS regulations: (1) a
standard network plan, which conforms to the criteria for a network description as described
in Section 58.41 and Appendices A and D of the Rule, including all of the elements listed:
and (2) an alternate network plan, which includes one or more of the acceptable alternative
network elements described in the Rule, but otherwise complies with the criteria for a
standard network.
The procedures for reviewing a State or local agency PAMS network plan consist of
two steps: in the first step, the submitted network plan is reviewed for administrative
completeness; in the second step, the plan is reviewed for conformance to the PAMS
acceptance criteria.
4.2 REQUIREMENTS FOR STANDARD PAMS NETWORK PLANS
The Part 58 regulations allow for submittal of standard or alternate network plans.
Standard network plans, which are described in this section, conform to the criteria for a
network description outlined in Section 58.41 and Appendices A and D of the Rule. In order
for a standard plan to be approved the plan must meet the completeness criteria contained in
Section 4.2.2 and the acceptance criteria of Section 4.2.3. A summary of the review and
approval process and a description of the completeness and acceptability criteria for standard
network plans are included in the remainder of this section. A decision tree flow diagram of
this procedure is presented in Figure 4-1.
-------
Begia: State/Local agency
submits PAMS network plan la
EPA Regional Office.
Regional Office requests
fubirittbig agency to submit miring >
additional information and naUfle
PA Headquarters of suiiia..
Regional Office
ib-wards the plan lo EPA Headq
\wiih recommendation, far review^
EPA
Headquarters
reviews the plan. Are any
of UK critic*! cktnnls
In Section 4.2.2
missing?
epoiiAl Office
-- rtcrircs the reviled pbiu
Are ftiiT of the crKkal dcmenU in
or is the plan
considered
nad equate?
EPA-454/B-93/051
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f EPA Headquarters contacts
Regional Office lo mform
V. lh pursue a standard
PAMS network
review?
EPA Headquarters informs
Regional Office who then
contacts agenc?.
Kbnuttinc agency b inf
of the Cmnmiaee's determination
that there are alternative
provisions.
The Regional Office
notifies the subintling agency that
the plan contains deficiencies and
suspends further action on the plan
until it receives corrections.
The
Revkw Committee
evaluates the plan. Does it
meet the acceptance criteria
In Section 4.2J?
reels the plan and resubimts
II lo the Regional Office
/'Suhmilting agencv must
f submit an alternative
I PAMS network plan.
Nv See Figure 4.1
X^EPAapproresthepton \
/ and sends approval toter to \
V Regional Office who then sends U /
Nylo the submitting agencj.^^'
FIGURE 4-1. PROCEDURES FOR REVIEW AND APPROVAL OF STANDARD
PAMS NETWORK PLANS
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4.2.1 Summary Procedures for Review and Approval of a Standard PAMS Network
Plans
1. State/local agencies prepare a PAMS standard network plan (including the critical
elements and sub-items of a standard plan which are listed and described in
Section 4.2.2) and declare the plan as a standard plan. Joint network plans may be
submitted by groups of State/local agencies in accordance with Section 58.40 of the 40
CFR Part 58 regulations. Agencies are encouraged to work with Regional Offices in
network plan development.
2. The plan is submitted to the appropriate EPA Regional Office for preliminary review.
If any of the critical elements are missing or considered inadequate, the Regional
Office requests that the submitting agency remit the additional or revised material and
notifies EPA Headquarters of the plan receipt and status.
3. State/local agencies submit missing and/or new material to the Regional Office which
reviews the material for completeness and adequacy, and subsequently forwards the
information to EPA Headquarters with the Regional recommendation when deemed
complete.
4. EPA Headquarters conducts a general review of the overall plan and reviews the
standard network plan according to the standard plan completeness criteria described
in Section 4.2.2. If any of the critical items are judged to be incomplete or missing,
the Regional Office is contacted, which in turn requests the additional or missing
material from the responsible agency or agencies (in the case of a multi-area plan).
5. EPA Headquarters reviews the resubmitted material and determines if the plan
submittal is complete. If incomplete, the cycle is repeated until the plan satisfies the
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completeness criteria. After a plan is determined to be complete, it is sent to the EPA
PAMS Network Design Review Committee (Review Committee) for a standard
network plan acceptability determination. If the submitted plan is judged to contain
any of the Part 58 allowable alternative plan revisions, the plan is reviewed according
to the alternative plan review procedures presented in Section 4.3.1. Before
proceeding with the alternative plan review process, EPA Headquarters notifies the
Regional Office that the plan is considered to be an alternative plan and that a final
decision is needed from the responsible agency official(s) on whether EPA should
proceed. The Regional Office notifies the appropriate agency; if that agency's
official(s) agree that the plan is an alternative network plan and desire an alternative
plan review, the plan is processed according to the alternative plan review procedures
presented in Section 4.3.1. If the agency disagrees and prefers to continue to seek a
standard plan review, alternative plan provision(s) must be removed and replaced with
the standard network plan provision(s).
6. The Review Committee reviews the standard network plan for conformance to the
standard plan acceptance criteria listed and described in Section 4.2.3 (Alternative plan
acceptance criteria are described in Section 4.3.3). If the submitted plan is determined
to conform to the standard plan acceptance criteria, the Review Committee
recommends approval of the network plan and forwards it to the EPA approving
official for formal approval. Note that formal approval is only for each of the sites
that are to be established in the next ozone monitoring period. The process is
repeated each year additional sites are to be implemented. Complete approval of
the entire network plan is contingent upon completion of each phase of the
network description including conformance to the PAMS network design criteria.
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7. The EPA approving official signs an approval memorandum and sends it to the
Regional Office which notifies responsible agency official(s).
8. If the Review Committee determines that the standard network plan does not satisfy
the critical elements, the Regional Office is contacted. The Regional Office notifies
the responsible submitting agency official(s) of the deficiencies and requests corrective
action to be taken. EPA Headquarters holds the plan in abeyance until the plan
corrections are received.
9. The State/local agency submits the corrected deficiencies to the Regional Office. The
Regional Office reviews the material for completeness and forwards it to EPA
Headquarters with the Regional recommendation when .judged complete.
10. The Review Committee reviews corrections and if the revised plan is determined to
conform to the standard plan acceptance criteria, the Review Committee recommends
plan approval and forwards it to the EPA approving official for formal approval.
11. The EPA approving official signs the PAMS standard network plan approval
memorandum and submits it to the Regional Office which then notifies the responsible
agency official(s).
4.2.2 Completeness Criteria for Standard PAMS Network Plans
The completeness determination consists of checking the submitted plan against the
prescribed list of critical elements of a network plan, which have been grouped into the
following categories:
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• Network overview
• Site identification
• Sampling and analysis methods
• Monitoring period
• Sampling frequencies
• Meteorological monitoring
• Network implementation schedule
• Quality assurance
In order to be considered complete, a plan must include each of these basic elements. Within
these basic elements are a number of specific items that need to be included in the plan in
order for the basic element to be complete. These specific items are described in Section
4.2.3.
When submitting a completed standard network plan to the EPA Regional Office, the
responsible State or local agency should label it as a standard plan, and ensure that it contains
all the critical elements described in this section and listed in the Checklist contained in
Section 4.4. The elements of the submitted network plan must fully conform to the criteria
laid out in this section and 40 CFR Part 58. If the review by the EPA Regional Office
determines that any of the critical elements are missing and/or the plan is considered
inadequate, the submitting agency will be requested to provide the missing items and/or
submit additional material. After the standard network plan is deemed complete and adequate
by the Regional Office, it is forwarded to EPA Headquarters.
To avoid delay and confusion in the approval process, all materials required as part of
a network plan submittal must be included in the submittal package. References alone to
other documents or database retrievals are not acceptable.
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The remainder of this section is devoted to detailed descriptions of the categories of
critical elements listed previously. The individual critical elements which make up each
category are enumerated, along with the criteria for acceptability.
4.2.3 Acceptance Criteria for Standard PAMS Network Plans
Once the standard network plan is determined to be administratively complete, it is
forwarded to the Review Committee where it is reviewed for conformance to the standard
plan acceptance criteria, which are based on the network plan requirements specified in the
regulations.
Network Overview - In order to be acceptable, a PAMS MSA/CMSA network plan must
include a clear description of the entire network. The network overview should contain a brief
narrative describing the number and types of sites that will make up the network, and the
rationale for their placement. The narrative should also briefly describe the monitoring area
represented, noting any geographical features, emissions information, meteorological and
climatological trends, or other factors which influenced the design of the network. Pertinent
information must be included as a part of the network plan submittal package, rather than
referenced.
Each PAMS network description must include a description of the monitoring area
represented [Section 58.41 (a)]. The description of the monitoring area represented must
include information on the population and nonattainment status of the network plan
MSA/CMSA. The number and types of PAMS sites required for a given area depend on
these two factors (Table 4-1). For areas with serious, severe, or extreme nonattainment status,
the minimum requirements vary from two sites for an MSA/CMSA with a population under
500,000; to five sites for an MSA/CMSA with a population over 2,000,000. Further guidance
on network design and siting is provided in Section 2 of this document. The description must
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TABLE 4-1. MINIMUM PAMS NETWORK REQUIREMENTS8
Population of MSA/CMSA or
nonattainment areab
Less than 500,000
500,000 to 1,000,000
1,000,000 to 2,000,000
More than 2,000,000
Number of sites of each type
Upwind
Background
(#1)
/
/
/
/
Maximum
Representative
Precursors
(#2)
/
/
wV
//
Maximum
Ozone
(#3)
/
/
/
Downwind
Transport
(#4)
/
For nonattainment areas classified as serious, severe, or extreme
Whichever is larger
also include a map of the entire MSA/CMSA, showing the proposed relative location of the
sites that make up the PAMS network, and a detailed area map showing the precise location
for the sites to be installed during the current ozone monitoring period. In addition, the
description should include the sued dJcuess, County, Parish, or Township;
Latitude/Longitude; and Universal Transverse Mercator (UTM) coordinates for each proposed
site which is scheduled for operation in the next ozone monitoring period. Other information,
such as emissions inventories for ozone precursors, meteorological data, climatological
summaries, or topographic maps showing land features and geographical influences must be
included. Preferred examples of this information are provided in Appendix I.
Provisions have been made in the regulations to allow for alternative networks with a
different number or arrangement of sites, including multi-area networks covering several
MSAs/CMSAs (40 CFR Part 58, Appendix D, Section 4.2). Plans containing an alternate
number or arrangement of sites must be submitted as alternate network plans in accordance
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with the requirements for submittal of alternative network plans discussed in Section 4.3 of
this manual.
Site Identification - Detailed information, noted in the previous section and further described
or demonstrated in Appendix I, must be supplied for sites to be implemented in the next
ozone monitoring period. In order to be complete, a PAMS network plan should include the
following for each site scheduled for operation in the next ozone monitoring period.
1. AIRS site and monitor ID information for each proposed station [See list of required
information in the Checklist (Section 4), Section HI, Part B].
2. Morning wind roses for high ozone days (days exceeding 0.1 ppm) or ozone
conducive days for Site #1 and Site #2 monitoring sites. Alternate methods of
specifying the wind direction must be approved by EPA. (40 CFR Part 58, Appendix
D, Section 4.2). In situations where simple wind roses are not applicable, appropriate
representative wind direction summaries should be included.
3. Afternoon wind roses for high ozone days or ozone conducive days for Site #3 and
Site #4 monitoring sites. Alternate methods of specifying the wind direction must be
approved by EPA. (40 CFR Part 58, Appendix D, Section 4.2).
4. Maps showing nearby ozone precursor emission sources of 10 tons/year or greater for
the immediate surroundings of the site (within l/4 mile of the site), and a less detailed
map for the entire MSA/CMSA (See Appendix I of this document for a detailed
description of required emissions information for sites to be established in future
years).
5. Breakdown of source categories (mobile/point/area). (See Appendix I of this
document).
6. Description of terrain around sites, including roadways and land use (topographic map
preferred).
7. Photographs and/or video of sites.
8. Details of meteorological monitoring.
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9. Other information as available - modeling information, saturation monitoring results,
etc.
Detailed site information must be submitted to the Regional Office no later than January 1 of
the year in which a site is scheduled for implementation [40 CFR Part 58, Section 58.41(d)].
Less detailed information (a map of the general location of the site, a description of the site
number, and morning and afternoon wind roses for high ozone days) should be supplied for
sites to be implemented in future years [40 CFR Part 58, Section 58.41(d)].
Sampling and Analysis Methods - The PAMS program requires monitoring of multiple
pollutants (NO, NO2, NOx, ozone, carbonyls, and speciated VOC) at each of the sites in
affected MSAs/CMSAs. In order to ensure that comparable data are produced, it is essential
that the sampling and analysis methodologies called for in the Part 58 regulations and the
Technical Assistance Document, are used by all PAMS networks.
Use of automated reference or equivalent methods (40 CFR Part 58, Section 50.1) is
required for ozone, and recommended for NO, NO2, and NOX (40 CFR Part 58, Appendix C,
Sections 4.1 and 4.2). VOC and carbonyl monitoring must be performed using the methods
described in the TAD (40 CFR Part 58, Appendix C, Section 4.3) or approved alternative
methodology. Meteorological measurements must be conducted according to the guidance in
the TAD described above, and the Quality Assurance Handbook for Air Pollution
Measurement Systems: Volume TV, Meteorological Measurements (40 CFR Part 58,
Appendix C, Section 4.3). Details of reference or equivalent methods and unmodified
methods from the TAD need not be included in network plan submittals; they may be
referenced.
. Regulatory provisions allow for the use of alternative methods to measure NO, N02,
NOX, VOC, and carbonyls (40 CFR Part 58, Appendix C, Sections 4.2 and 4.3). Plans which
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include any modifications to the designated methods, or propose alternate methodologies,
must be submitted as alternative network plans in accordance with the requirements discussed
in Section 4.3 of this document Complete documentation of the modification or alternative
methods must be submitted with the alternate network plan.
Monitoring Period - At a minimum, ozone precursor monitoring must be conducted during
the months of June, July, and August, when peak ozone conditions are generally expected.
Monitoring during the entire prescribed ozone season for an area as defined in 40 CFR
Part 58, Appendix D, is preferred. Alternate precursor monitoring periods may be submitted
for approval as part of a PAMS alternative network description (40 CFR Part 58, Appendix
D, Section 4.3) in accordance with the requirements described in Section 4.3 of this manual.
Sampling Frequencies - Monitoring of ozone for the PAMS network must be continuous,
and on the same schedule as the NAMS/SLAMS networks (40 CFR Part 58, Appendix D,
Section 2.5). Monitoring for NO, N02, and NO^ should be continuous and may be limited to
the months of June, July and August. Several sampling frequency options are available for
monitoring of VOC and carbonyls by PAMS networks (see Section 4.3.2 of this document)
(40 CFR Part 58, Appendix D, Section 4.4, Table 2). Some of the available sampling
frequency options call for monitoring on and before peak ozone days. Agencies choosing to
use these options must provide a description of the ozone event forecasting scheme they will
use to predict peak ozone days and a demonstration of its effectiveness (40 CFR Part 58,
Appendix D, Section 4.4). The demonstration must be based on recent ambient ozone data
(preferably not more than 5 years old), from years that are representative of typical weather
patterns in the area.
The regulations provide for the use of alternative sampling frequencies [40 CFR Part
58, Section 58.40(a)(3)]. Plans containing alternative sampling frequencies must be submitted
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as alternate network plans, in accordance with the requirements described in Section 4.3. In
order to be approved, a PAMS network plan incorporating an alternative sampling frequency
must include a demonstration of its equivalency with the prescribed Part 58 PAMS frequency.
Meteorological Monitoring - Each PAMS station, or a nearby area representative of each
PAMS, must be equipped with meteorological monitoring equipment, including wind
measurements at 10 meters above ground (40 CFR Part 58, Appendix D, Section 4.6).
Details on the meteorological equipment at each site must be included in the individual site
description.
One upper air meteorological monitoring site is required for each PAMS-affected area.
The upper air monitoring site may be located separately from the other PAMS sites, but it
must be representative of the upper air data in the MSA/CMSA nonattainment area (40 CFR
Part 58, Appendix D, Section 4.6). The PAMS network description must contain a detailed
description of the upper air monitoring measurement system, including monitoring methods
and frequencies, and specific site location.
Network Implementation Schedule - PAMS network plans must include a schedule for
implementing the entire network [40 CFR Part 58, Section 58.41(h)]. The schedule must
include a timetable for locating, establishing, and submitting the AIRS site ID form for each
scheduled PAMS site that has not been located at the time the network plan is submitted.
The schedule must include a timetable for phasing in the required number and types of sites
according to the priorities defined in 40 CFR Part 58, Appendix D, Sections 4.4 and 4.5. The
recommended order of site implementation called for in Part 58 is as follows: primary Site
#2, Site #3, Site #1, Site #4, and last, the secondary Site #2.
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Quality Assurance (QA) - PAMS network plans must include a schedule for modification of
the QA program already in place for NAMS/SLAMS to include QA for the PAMS network
[40 CFR Part 58, Section 58.41 (h)(3)]. PAMS QA programs must be designed in accordance
with the provisions of 40 CFR Part 58, Appendix A, which includes requirements for QA
activities and reporting, and data quality assessment.
4.3 REQUIREMENTS FOR ALTERNATIVE PAMS NETWORK PLANS
If a proposed plan has been determined to contain any of the alternative elements that
are allowed under the alternative element provisions of the regulations (alternate sampling and
analysis methods, sampling frequency, sampling period, number and type of sites, and
alternate procedures for selecting wind direction), the plan is declared an alternate plan. In
order for an alternative plan to be approved the plan must meet the completeness criteria
contained in Section 4.3.3 and the acceptance criteria of Section 4.3.4. The completeness
criteria for alternative plans include all of the requirements of a standard plan plus the
Section 4.3.3 criteria. Alternate plans are subject to additional network plan submittal
requirements as described in this section. The plan is examined for administrative
completeness with regard to these additional items. If the plan is found to be incomplete, the
submitting agency will be notified and requested to submit the missing information or data.
After the alternative plan is judged to be administratively complete, it is forwarded to the
Review Committee and evaluated for conformance to the acceptance criteria for alternative
plans. The alternative network plan review and approval process is summarized below, and
illustrated in a decision tree flow diagram (Figure 4-2).
-------
ntinued from Figure 4-1.
tate/Local agency lubmlU alternative
PAMS network plan to EPA
Regional Office.
EPA
egional Office reviews
alternative plan. Are an; of the
critical elements In Section 4-3.3
missing or considered
dequate?
Regional Office requests
submitting agency to submit missing
r additional information and not!
A Headquarters of status.
Regional Office
receives the plan. Art any o"
the critical elements in Section 4.3.3
missing or considered
inadequate?
forwards the alternative plan to
EPA Headquarters, with
mendation. for review
EPA
Headquarters
reviews the alternative plan.
Are an; of the critical elements
In Section 4.3-3
missing?
EPA Headquarters
sends the plan to the EPA Re> kw
Committee for an alternative
twork plan evlauation.
The Review
Committee evalua tes
the plan. Does i( meet
the acceptance criteria
in Section 4.3.4?
The Regional Office
notifies the submitting agency that
the plan contains deficiencies and
suspends further action on the plan
ntfl it receives correction
The submitting agency N.
corrects the plan and resubmib it ]
to the Regional Office. I
Regional Office
reviews plan.
Are revisions considered
Inadequate?
The Review
ommittee evaluates the plan.
Does it meet the acceptance
riteria in Section 4.3.4?
EPA approves the plan
and sends approval letter to
Regional Office who then submits
plan to the submitting agencr.
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FIGURE 4-2. PROCEDURES FOR REVIEW AND APPROVAL OF ALTERNATIVE
PAMS NETWORK PLANS
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4.3.1 Summary Procedures for Review and Approval of Alternative PAMS Network
Plans
1. State/local agencies prepare a PAMS alternative network plan (includes the critical
elements of an alternative plan which are listed and described in this section).
Agencies are encouraged to work with the Regional Offices during plan development.
2. The plan is submitted to the EPA Regional Office for preliminary review. If any of
the PAMS alternative plan critical elements items are missing or considered
inadequate, the Regional Office requests the submitting agency to send the missing
material and/or revise the submitted material.
3. The State/local agencies submit missing or revised material to the Regional Office; the
Regional Office reviews the material for completeness and adequacy and forwards it to
EPA Headquarters with the Regional recommendation when it is considered complete
and adequate.
4. EPA Headquarters reviews the network plan for the alternative plan completeness
determination. If any of the critical element items of an alternative plan are valued as
incomplete or missing, the Regional Office is contacted, which in turn requests the
additional or missing material from the responsible agency or agencies (in the case of
a multi-area plan).
5. The State/local agency sends the missing or additional material to the appropriate
Regional Office. Regional Office sends the material to EPA Headquarters with the
Regional recommendation when ruled complete and adequate.
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6. EPA Headquarters reviews the resubmitted material and determines whether the
alternative plan submittal is complete. If incomplete, the cycle is repeated until the
plan satisfies the completeness criteria. After the alternative plan is determined to be
complete, it is sent to the EPA Review Committee for an alternative plan acceptability
determination.
7. The EPA Review Committee reviews the alternative network plan for conformance to
the acceptance criteria for an alternative plan. If the submitted plan is determined to
conform to the alternative plan acceptance criteria, the Review Committee
recommends approval of the network plan and forwards the plan to the EPA approving
official for formal approval. Note that the PAMS alternative network plan formal
approval only applies to each of the sites that are to be established in the next
ozone monitoring period. The process is repeated each year for all additional
sites scheduled for implementation in that same year. Complete approval of the
entire network plan is contingent upon completion of each phase of the entire
network description.
8. The EPA approving official signs an alternative network plan approval memorandum
and sends it to the Regional Office, which notifies the responsible agency official(s).
9. If the EPA Review Committee determines that the alternative network plan does not
satisfy the critical elements delineated in Section 4.3, the Regional Office is contacted.
The Regional Office notifies the responsible submitting agency official(s) of the
deficiencies and requests that corrective action be taken. EPA Headquarters holds the
plan in abeyance until the plan corrections are received. In some cases EPA may
consider a plan for conditional approval.
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10. The State/local agency submits the corrected deficiencies to the appropriate Regional
Office. The Regional Office reviews the material for completeness and forwards to
EPA Headquarters with a recommendation when the Region considers the corrected
alternative network plan complete.
11. The EPA Review Committee reviews the corrections. If the revised plan is
determined to conform to the alternative plan acceptance criteria, the Review
Committee recommends approval of the alternative plan and forwards the plan to the
EPA PAMS network plan approving official for formal approval.
12. The EPA approving official signs the PAMS alternative network plan approval
memorandum and submits it to the Regional Office which then notifies the responsible
agency official(s).
4.3,2 Regulatory Provisions for Alternative PAMS Network Plans
The PAMS regulations have been crafted to allow PAMS networks to be tailored to fit
the individual needs of State and local programs. The purpose of the flexibility written into
the rule is to ensure that the overall goals of the PAMS program are met while allowing for
States to design their networks and take into account any factors that are unique to their own
programs (e.g., problems, strategies, limitations, and particular authorities, or physical
constraints such as geography, demographics, or unusual meteorology).
The PAMS regulations contain provisions for alternative network elements in five
areas:
• Sites - Number and Arrangement
• Methodology - Sampling and Analysis
• Monitoring Season - Months with Highest Ozone
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« Sampling Frequency
• Meteorology - Establishing Wind Directions for Siting
If a State chooses to incorporate one or more of these alternative elements in its
PAMS network design submittal, it must state that its submittal is an alternative PAMS
network design. In order to be accepted, a network plan containing alternative elements must
demonstrate fulfillment of the PAMS monitoring objectives and program objectives. The
PAMS monitoring objectives are the basis for the four PAMS site designations and include
the following:
• Upwind background (#1 Sites)
• Representative maximum precursors (#2 Sites)
• Maximum ozone (#3 Sites)
• Downwind transport (#4 Sites)
The PAMS program objectives are also referred to as PAMS data uses and include the
following (more detailed descriptions are included in Section 4.3.4):
• NAAQS attainment and control strategies
• SIP control strategy evaluation
• Emissions tracking
• Exposure assessment
• Support for urban airshed modeling
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4.3.3 Completeness Criteria For Alternative PAMS Network Plans
Network plans for PAMS networks containing alternative elements must include all
the elements of a standard PAMS network plan. Alternative network plans must also include
the following documentation:
• Narrative explanation of the alternative element(s)
• Justification for the alternative elements
• Demonstration of comparability
An alternative network plan will be considered complete if each of these items and
associated material is presented. Alternative elements must correspond to one of the five
alternative element areas specified in the regulations. If material from one part of a network
plan submittal is applicable elsewhere (for example, a justification for an alternative method),
it may be referenced in the other portions of the plan. For each required documentation,
however, the applicable material must be contained somewhere within the submittal package.
Network plan submittals containing references to sources not contained within the submittal
package will be considered incomplete. After review by the Regional Office, if any element
is found missing or considered inadequate, the submitting agency will be asked to supply the
missing items.
Section 4.3.4 of this document contains more detailed guidance on the types of
information that may be used to fulfill this requirement, and instances in which such
demonstrations may be required.
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4.3.4 Acceptance Criteria For Alternative PAMS Network Plans
After the alternative network plan is determined to be administratively complete, it
must be reviewed for conformance to the alternative plan acceptance criteria. These criteria
are as follows:
• The acceptance criteria for all the standard elements contained in the alternative
plan (Section 4.2.2 of this document)
• A detailed narrative explanation of the alternative elements
• A justification for the alternative elements
• A demonstration of compliance with the monitoring objectives and data uses
The standard network plan acceptance criteria are described in Section 4.2.2 of this
document To be considered acceptable, the narrative explanation must clearly describe the
proposed alternative elements. For example, if an alternate measurement method is proposed,
a complete description of the alternate method must be included in the plan. Details similar
to those included in standard operating procedures (SOPs) should be submitted. The
justification should fully explain why the alternative element is proposed, such as
geographical constraints, local ordinance restrictions, physical obstructions, and/or improved
data quality. The comparability demonstration must provide a thorough explanation showing
that the proposed alternative network will produce results comparable to those produced by a
standard PAMS network, and that the proposed network will fulfill the PAMS monitoring
objectives and data uses. When using alternative sampling or analytical methods (including
meteorological methods) or alternative sampling or monitoring frequencies, the documentation
for the demonstration must: (a) include historical data collected within the last three years or
during the time period used to declare the MSA/CMSA nonattainment, and (b) show a
relationship between the proposed alternative methodology and the methodology described in
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the TAD. Rulings on the acceptability of alternative methods will be made on a case-by-case
basis by the EPA Review Committee.
The PAMS regulations were designed to allow flexibility in implementation. They
contain several provisions for alternatives to the prescribed standard network design. Section
58.40(a)(3) of the PAMS regulations states "Alternative networks, including different
monitoring schedules, periods, or methods, may be submitted, but they must include a
demonstration that they satisfy the monitoring data uses and fulfill the PAMS monitoring
objectives as described in sections 4.1 and 4.2 of appendix D to this part." Sections 4.1 and
4.2 of Appendix D to 40 CFR Part 58 contain detailed descriptions of the PAMS data uses
and monitoring objectives, respectively.
There are five major PAMS data uses described in Section 4.1 of Appendix D to 40
CFR Part 58. Alternative network plans must demonstrate that they can meet these data uses:
• NAAQS attainment and control strategy development
• SIP control strategy evaluation
• Emissions tracking
Trends
• Exposure assessment
The five major data uses, examples of particular data uses specified in the regulations, and
how alternative network plans will be assessed on their ability to meet these data uses are
discussed in the following sections.
In addition, the regulations specify certain uses within the five major categories of
data uses. Each of these particular uses is listed below and discussed in the context of how
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to demonstrate that an alternative network plan will meet these particular uses. In cases
where a particular use may be met based on another objective or criterion, the discussion will
indicate how to reference the material contained elsewhere and explain how the other material
is relevant to meeting a particular data use.
NAAQS Attainment and Control Strategy Development - For this PAMS data use
category, the regulations list the following six particular uses and additional subsidiary uses:
• monitor exceedances
• provide input for attainment/nonattainment decisions
• help resolve roles of transported and locally emitted ozone precursors in
producing an observed exceedance
• identify specific sources emitting excessive ozone precursor concentrations and
potentially contributing to ozone exceedances
• enhance the characterization of ozone concentrations
• provide critical information on the precursors causing ozone and thus extend
the database for future demonstrations based on photochemical grid modeling
and other approved analytical methods
areas and episodes to model to develop appropriate control strategies
boundary conditions required by the models to produce quantifiable
estimates of necessary emissions reductions
evaluation of the predictive capability of the models used
Particular uses, such as monitoring exceedances of the NAAQS and helping to resolve
the role transported and locally emitted ozone precursors play in producing observed
exceedances, are strongly dependent on meeting criteria for site locations, sampling
frequency, and monitoring period. The criteria used to assess the adequacy of the alternative
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plan for a particular data use will be whether the alternative network plan provides data of
sufficient quantity, quality, representativeness, and comparability compared to the standard
network design. Among the questions that should be answered are the following:
1. Will the alternative network design provide data that are compatible with
making an informed attainment/nonattainment decision? For example, will the
design capture the highest ozone concentration days? Will the time resolution
of ozone precursors be compatible with meteorological measurements and
allow adequate differentiation of upwind/downwind conditions and transport?
2. Will the alternative network design provide data that are compatible in spatial
and temporal bounds and resolution with applicable photochemical grid
models?
3. Are there special conditions (either geographic, meteorological, or logistical)
that would prevent the standard network design from being implemented or
providing the data intended, or are there special conditions that mean that the
alternative network design will do a better job of meeting the data uses or other
PAMS objectives?
Identifying specific sources emitting excessive ozone precursor concentrations and
potentially contributing to ozone exceedances is strongly dependent on siting criteria,
particularly those dealing with location with respect to certain source types, the scale of
representativeness, the absence of very localized influences, etc.
Among the questions to be answered are the following:
1. Will the alternative network design provide data that are comparable to and
representative of the general conditions of the typical type of PAMS?
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2. On what basis were the specific sources identified as possibly emitting
excessive ozone precursors, and how much of a contribution to ozone
exceedances are these sources expected to make?
3. How will the alternative network design characterize precursor emissions from
these sources?
SIP Control Strategy Evaluation - The PAMS regulations discuss the following data uses
under the category SIP control strategy evaluation:
• Evaluating the effectiveness of control strategies using long term PAMS data
• Evaluating the impact of VOC and NOX emission reductions on ambient air
quality ozone levels
• Determining which organic species are most affected by emissions reductions
The PAMS alternative network plan must demonstrate that the VOC and NOX data will be
comparable to the data collected by the sampling stations from a standard network. At a
minimum, the comparability demonstration required should answer the following questions:
1. Will the alternative plan provide fixed permanent monitoring stations that will
provide valid, quality assured data for long-term PAMS control strategy
evaluation and in particular for the time period covering control strategy
implementation?
2. Will the alternative plan capture VOC speciated compounds and NOX
concentrations in the area of representative maximum concentrations in order to
tie in air quality levels with emission sources in the MSA/CMSA?
3. Will the data collected by the alternative network represent around-the-clock
concentrations so that any major VOC emissions occurring at different time
periods during the day are accounted for, thus allowing for the development of
strategies that are most suited and cost-effective for the area?
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Emissions Tracking - The following four uses are cited in the Part 58 regulations for the
PAMS data use category of emissions tracking:
• Corroborate the quality of VOC and NOX emission inventories
• Track the reduction of VOC and NOX emissions
• Support reasonable further progress (RFP) calculations
• Corroborate emissions trends reporting
In general, for emission inventory corroboration, tracking of emissions, RFP calculations, and
the corroboration of emissions trends, an alternative network plan must demonstrate that its
VOC and NOX ambient air quality data will be capable of providing enhanced or similar data
compared to a standard network plan. The following questions need to be answered:
1. Will the alternative network capture the maximum representative VOC
concentration?
2. Will the alternative network be able to discriminate among anthropogenic and
biogenic VOC contributors?
3. Will the alternative plan allow for the corroboration of RFP calculations?
Preliminary guidance recommends that data from Site #2 be used for comparison to
emissions inventory estimates and that data from Site #3 may be used on a case-by-case
basis. The alternative network plan must demonstrate that its proposed monitoring stations
will provide data comparable to a Site #2. In addition, the alternative network plan must
show that its sampling schedule will provide data comparable to sampling for all of the
weekdays to comply with the emission inventory's collection and reporting of data based on a
summer weekday. Weekdays should be emphasized in the comparability analyses. Since
RFP emission reduction requirements apply exclusively to anthropogenic emissions, emission
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inventory estimates should exclude biogenic emissions. Also, since acetaldehyde and
formaldehyde are normally secondary reactive products in ozone formation, it is good practice
to exclude them from the emissions estimates unless they are emitted as primary pollutants.
Finally, ethane, which is not considered a reactive hydrocarbon, should also be omitted.
Because the emission inventories exclude these pollutants, the alternative plan should
demonstrate that appropriate procedures could be implemented to subtract such pollutants
from the ambient data collected.
Trends - For this PAMS data use category, the regulations give the following five particular
uses and additional subsidiary uses:
establish speciated VOC, NOX, and limited toxic air pollutant trends using long-
term data
supplement the ozone trend? database
track multiple statistical indicators
ozone and its precursors during the events for the days of each year
with the highest ozone concentrations
seasonal means for these pollutants
annual means at representative locations
compare pollutant trends analyses with meteorological trends and transport
influences through the use of PAMS surface meteorological monitoring
help to interpret ambient air pollution trends by taking meteorological factors
into account with the use of PAMS meteorological data
In general, an alternative network design must demonstrate that its speciated VOC,
NOX, and limited toxic air pollutant data will be roughly comparable to or better than the data
from the standard network design in terms of representativeness (spatial and temporal), data
quality for statistical indicators (e.g., accuracy and precision), and compatibility with
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meteorological data. The design should explicitly list and candidly discuss any tradeoffs in
trend analyses. For example, will the alternative monitoring network design provide better
statistical analysis for events with high ozone concentrations at the expense of poorer or
biased statistical analysis of seasonal or annual trends? Will an alternative design provide for
a better analysis of toxic air pollutant trends at the expense of annual and seasonal ozone
means? On what basis were these choices made? Reviewers of alternative designs will
evaluate their suitability for trends reporting giving greatest weight to the following:
1. tracking statistical indicators for ozone and its precursors for the highest ozone
concentration events during the year
2. providing unbiased seasonal and annual means at representative locations
3. establishing speciated VOC, NOX, and toxic air pollutant trend data over the
long-term
4. providing the appropriate quantity and precision of measurements to permit
trends reporting
The alternative network design must also address the ability of the design to provide
pollutant data and meteorological data that are consistent with one another spatially and
temporally. Will the meteorological data be representative of the area where the pollutant
data are being acquired? For example, will airport data or other meteorological data in
complex terrain be adequate to characterize the movement of air parcels over the area where
toxic pollutants are being sampled?
Exposure Assessment - The regulations provide two particular uses for this data category.
Better characterize ozone and toxic air pollutant exposure to populations living
in serious, severe, or extreme areas
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Calculate the annual mean toxic air pollutant concentrations to help estimate
the average risk to the population associated with individual toxic VOC species
in urban environments
In general, alternative PAMS network designs must demonstrate that they can provide
equivalent or improved estimates of population exposure to ozone and toxic air pollutants. In
practice, it is desirable that the network design show that one or more monitoring locations
will be representative of general population exposure and demonstrate that annual mean
concentrations of toxic air pollutants will not be biased by the proposed sampling schedule or
frequency. For example, alternative network designs using a predictive scheme for sampling
on the highest ozone concentration days must show how statistically representative and
unbiased sampling can be obtained for annual sources of toxic air pollutants. In addition, the
application should address any tradeoffs made by alternative designs between trend reporting
and exposure assessments, and the rationale for doing so. For example, a given
nonattainment area may have varied and geographically dispersed sources of toxic air
pollutants. If the meteorological and boundary conditions for the area are believed to be
relatively simple, the network may be appropriate to better characterize exposure to toxic
pollutants.
4.4 COMPLETENESS CHECKLIST FOR PAMS NETWORK PLANS
4.4.1 Instructions for Using Checklist
The following checklist is intended for persons preparing PAMS network plans and for
persons reviewing and approving those plans. The checklist will help the user determine
whether or not the information requirements of a PAMS network plan have been satisfied.
The checklist is organized into five sections. Section I identifies background
information about the proposed plan, such as the agency submitting it and the classification of
the ozone nonattainment area. Section n covers the design of the network; the required
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number and types of sites for the nonattainment area. Section HI reviews several site-specific
information requirements, such as AIRS site ID forms, and several network information
requirements, such as the sampling methods to be used at all of the network's proposed sites.
Section IV covers the network schedule for both the implementation and operation of new
sites. The last section, Section V, provides a quick overview of the completeness status of
the proposed network plan.
If a State or local agency has not provided the necessary data and information in its
plan, this should be indicated on the checklist. The agency using the appropriate procedures
should be contacted to obtain the necessary data and information. If the proposed plan
includes alternative provisions, such as a site layout that differs from those stipulated in the
regulations, documentation must be provided supporting the alternative elements. The
documentation must demonstrate that the plan will meet the data uses and monitoring
objectives of a standard PAMS network plan.
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4.4.2 Completeness Checklist for PAMS Network Plan
Section I General Information
A. State or Local Agency:.
Contact:
Address:
Telephone #:_
State or Local Agency (if more than one):.
Contact:
Address:
Telephone #:_
State or Local Agency (if more than one):.
Contact:
Address:
Telephone #:_
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B. EPA designation of the ozone nonattainment area. Please check the one that applies.
Serious:.^ Severe: Extreme:
C. In which range does the population of the metropolitan statistical area (MSA) or the
consolidated metropolitan statistical area (CMS A) fall?
Less than 500,000:
500,000 to 1,000,000:_
1,000,000 to 2,000,000:.
More than 2,000,000:
D. AIRS Name and number of the MSA/CMSA
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E. Is the proposed plan for an isolated area network or for a multi-area, transport
network? Please circle one.
Isolated area network or Multi-area, transport network
F. If the plan is for a multi-area network, are all the other affected agencies identified in the
plan? Please circle one. Y or N
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Section n Network Design
A. Based on the information provided in Section I, please fill in the box as it applies.
Population of MSA/CMSA
Less than 500,000
500,000 to 1,000,000
1,000,000 to 2,000,000
More than 2,000,000
Required #
of Sites
2
3
4
5
Required Types
of Sites
1,2
1,2,3
1, 2, 2, 3
1, 2, 2, 3, 4
Proposed #
of Sites
Proposed Types
of Sites
B. If the State has submitted a plan for a network design that differs from the required
number of sites or types of sites, the plan is considered an alternative plan. If this
occurs, has the following information been supplied? Please check appropriate space for
each question:
1.
2.
3.
4.
5.
A narrative explanation?
Sufficient justification?
Demonstration of comparability?
Demonstration that the monitoring objectives are met?
Demonstration that the dam UM^ are sauMleu?
Y
N
Section HI Network Description • Site Specific
A. Identification of the Monitoring Area
Each PAMS network description must include a description of the monitoring area. Are
the following items included in the description?
1.
2.
A map of the entire MSA/CMSA with the proposed location of each site,
including those to be established in future years? (Sites to be established in future
years may be indicated within a 2 km radius on the MSA/CMSA map.)
Climatological information?
Y
N
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B. Identification of PAMS Sites
1. Full Site Description: The following requirements apply to individual PAMS sites
that are scheduled to be implemented during the coming year. Except for the
sites scheduled to begin monitoring in 1993, the information for each site should
be supplied before the first of January of the year in which they are to be
implemented. Was the information included in the plan?
a. Completed AIRS site ID information for each proposed site? (AMP380
report required, not individual ID forms.)
Site Identification Form Items
i. Card Al, Columns 1-59, 79-80
ii. Card A2, Columns 1-22, 35-36, 79-80
iii. Card A3, Columns 1-52, 79-80, repeat for each major roadway
surrounding the site. A minimum of one roadway group is required.
iv. Card A4, Columns 1-12, 13-27, 79-80 or 28-50, 79-80
v. Card A5, Columns 1-80
b. Completed AIRS monitor ID information for each proposed site as an
AMP380 report? ID information required for each monitored pollutant
(VOC, carbonyls, ozone, NO,, meteorological parameters).
Monitor Identification Form Items
i. Card Fl, Columns 1-38, 72-75, 79-80, plus 39-44 for existing sites
ii. Card F2, Columns 1-80
iii. Card F3, Columns 1-16, 23-46 (as applicable), 79-80
Y
N
c.
d.
e.
f.
A map of the area within a 1/4 mile radius of the proposed site? (Should
include roadways, buildings, stationary sources, tree lines, etc.)
A topographical map showing land features and geographical influences?
Emissions inventories and maps for ozone precursors (as described in
Section 2 and Attachment C)?
Meteorological data?
i. A.M. wind roses for number 1 and 2 sites on high ozone or ozone
conducive days?
ii. P.M. wind roses for number 3 and 4 sites on high ozone or ozone
conducive days?
Y
N
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2.
General Site Description: The following information applies to PAMS sites to be
implemented in future years.
a. Description of the role the site will play in the network (e.g., PAMS site
number)?
b. Wind roses for high ozone or ozone conducive days?
i. A.M. wind roses for number 1 and 2 sites?
ii. P.M. wind roses for number 3 and 4 sites?
C. Sampling and Analysis Methods
1.
Do the proposed sampling and analysis methods adhere to the following
guidelines?
a. Reference or equivalent methods for ozone?
b. Reference or equivalent methods for N02, NO, NO,,?
c. For VOC monitoring, the methods described in Technical Assistance
Document for Sampling and Analysis of Ozone Precursors (TAD)?
d. For meteorological measurements, the guidance provided by the TAD and the
Quality Assurance Handbook for Air Pollution Measurement Systems:
Volume IV. Meteorological Measurements!
2.
3.
4.
5.
If the answer to l.b. is no, do the NO, NO2 and NOX methods adhere to the
guidance in the TAD?
For reference or equivalent methods, have the designation numbers been supplied?
Does the plan account for the sampling of all of the pollutants (VOC, NOX,
carbonyls) at each of the sites?
If the State/local agency has indicated that the sampling and analysis
method(s) differ from the methods described in the TAD, the plan is
considered an alternative plan. If this occurs, has the following information
been supplied?
a. A narrative explanation?
b. Sufficient justification?
c. Demonstration of comparability?
d. Demonstration that the monitoring objectives are met?
e. Demonstration that the data uses are satisfied?
Y
N
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D. Sampling Frequencies
1.
AreN
Oi (including
NO and NO,J
measured
continuously?
Y
N
2. Which of the following sampling frequencies does the State propose to use? Please circle
the letters that apply.
Population of MSA or CMSA
Less than 500,000
500,000 to 1,000,000
1,000,000 to 2,000,000
More than 2,000,000
Required Site
Type
1
2
1
2
1 3
1
2
2
1 3
1
2
2
I 3
4
Minimum Speciated
VOC Sampling
Frequency
AorC
AorC
AorC
B
r AorC
AorC
B
B
AorC
AorC
B
B
AorC
AorC
Minimum
Carbonyl
Sampling
Frequency
DorF
E
E
E
E
E
A = Eight 3-hour samples every third day and one additional 24-hour sample every sixth day during the
monitoring period.
B = Eight 3-hour samples every day during the monitoring period and one additional 24-hour sample even- sixth
day year-round.
C = Eight 3-hour samples on the five peak ozone days plus each previous day, eight 3-hour samples every sixth
day and one additional 24-hour sample every sixth day during the monitoring period.
D = Eight 3-hour samples every third day during the monitoring period.
E = Eight 3-hour samples every day during the monitoring period.
F = Eight 3-hour samples on the five peak ozone days plus each previous day and eight 3-hour samples every
sixth day during the monitoring period.
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3.
4.
5.
6.
Do the sampling frequencies for carbonyls match the sampling frequencies for
speciated VOC including year round 1/6 day sampling?
If sampling frequencies C or F are proposed, did the State submit an ozone event
forecasting scheme?
If the site will collect multiple samples on a daily basis, do the samples begin at
midnight local time and consist of sequential nonoverlapping sampling periods?
If the State proposes to use alternative sampling frequencies, the plan is
considered an alternative plan. If this occurs, has the following information
been supplied?
a. A narrative explanation?
b. Sufficient justification?
c. Demonstration of comparability?
d. Demonstration that the monitoring objectives are met?
e. Demonstration that the data uses are satisfied?
Y
N
E. Meteorological Monitoring
1.
2.
3.
4.
Does the plan include a provision for equipping each of the proposed PAMS sites
or area representative of a PAMS with surface meteorological monitoring
equipment, including a 10-meter tower?
Is there a plan for establishing an upper air meteorological monitoring site?
Is the site representative of the upper air data in the nonattainment area?
Has the State supplied documentation that the upper air meteorological data will
meet the needs of the State's modeling program?
Y
N
Section IV Network Schedule
The following items on the checklist pertain to the entire PAMS network for the given
nonattainment area:
A. Implementation Schedule
1.
2.
3.
4.
Does the plan include a schedule for implementing each PAMS site?
Does the schedule comply with the EPA recommendations for priority of
implementation? (See Appendix D, Section 4.4, 40 CFR Part 58.)
Does the schedule include a timetable for submitting the AIRS site ID information
(AMP380 report) for each scheduled PAMS site that had not been located at the time
the network description was submitted?
Does the plan include a schedule for implementing quality assurance procedures?
Y
N
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B. Operating Schedules
1.
2.
Does the operating schedule of the PAMS network meet the minimum requirement that
the monitoring be conducted during the months of June, July and August?
If the State proposes an alternative operating schedule for the site, the plan is
considered an alternative plan. If this occurs, has the following information been
supplied?
a. A narrative explanation?
b. Sufficient justification?
c. Demonstration of comparability?
d. Demonstration that the monitoring objectives are met?
e. Demonstration that the data uses are satisfied?
Y
N
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Section V Summary Checklist for PAMS Network Plan
Item On Checklist
Section I General Information
A. Name of agency, address, contact, etc.
B. EPA designation of nonattainment area
C. Population range of MSA/CMSA
D. AIRS Name and number of MSA/CMSA
E. Isolated vs. multi-area network
F. Identification of other affected agencies
Section n Network Design
A. Table 1. Network Design
B.I. Narrative explanation (for alternative plan)
B.2. Sufficient justification (for alternative plan)
B.3. Demonstration of comparability (for alternative plan)
B.4. Monitoring objectives met (for alternative plan)
B.5. Data uses satisfied (for alternative plan)
Yes
No
Section in Network Description - Site Specific
A. 1 . Map of MSA/CMSA area
A.2. Climatological information (optional;
B.l.a. Completed AIRS site ID information (AMP380 report)
B.l.b. Relevant hardcopy form for PAMS
B.l.c. 1/4 mile radius map
B.l.d. Topographical map
B.l.e. Emissions inventories for ozone precursors (VOC, NO, N02, NOJ
B.l.f. Meteorological data
B.l.f.i High ozone or ozone conducive days - A.M. wind roses for number
and 2 sites
B.l.f.ii High ozone or ozone conductive days - P.M. wind roses for number
and 4 sites
1
3
B.2.a. Description of sites role within network
B.2.b.i High ozone or ozone conducive days - A.M. wind roses for number
and 2 sites
B.2.b.ii High ozone or ozone conducive days - P.M. wind roses for number
and 4 sites
1
3
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Item On Checklist
Section in Network Description - Site Specific cont'd.
C.I. a. Reference or equivalent methods for ozone
C.l.b. Reference or equivalent methods for NO,
C.l.c. VOC monitoring - TAD
C.l.d. Meteorological measurements - TAD and QA Handbook
C.2. Adherence of NO, N02 and NO, methods to guidance in the TAD
C.3. Designation numbers for reference or equivalent methods (optional)
C.4. Accounting for the sampling of all relevant pollutants
C.S.a. Narrative explanation (for alternative plan)
C.5.b. Sufficient justification (for alternative plan)
C.5.c. Demonstration of comparability (for alternative plan)
C.5.d. Monitoring objectives met (for alternative plan)
C.5.e. Data uses satisfied (for alternative plan)
D.I. Continuous measuring of ozone and NOX
D.2. Table 2. Sampling Frequencies for VOC, carbonyls
D.3. Matching of sampling frequencies for carbonyls and speciated VOC
D.4. Ozone event forecasting scheme for sampling frequencies C or F
D.5. Daily sampling - beginning at midnight local time; sequential,
nonoverlapping periods
D.6.a. Narrative explanation (for alternative plan)
D.6.b. Sufficient justification (for alternative plan)
D.6.C. Demonstration of comparability (for alternative plan)
D.6.d. Monitoring objectives met (for alternative plan)
D.6.e. Data uses satisfied (for alternative plan)
E.I. Equipping PAMS sites or locations representative of PAMS with
meteorological monitoring equipment
E.2. Upper air meteorological monitoring site
E.3. Site representative of upper air data in nonattainment area
E.4. Upper air data meeting needs of State's modeling program
Yes
No |
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Item On Checklist
Section IV Network Schedule
A.I. Schedule for implementing each site of PAMS network
A.2. Timetable for phasing in required number and types of sites
A.3. EPA's recommendations for priority of implementation met by schedule
A.4. Schedule for sites not located on network description
A.5. Schedule for implementing quality assurance procedures
B.I. Requirement for conducting monitoring during June, July, and August
B.2.a. Narrative explanation (for alternative plan)
B.2.b. Sufficient justification (for alternative plan)
B.2.c. Demonstration of comparability (for alternative plan)
B.2.d. Monitoring objectives met (for alternative plan)
B.2.e. Data uses satisfied (for alternative plan)
Yes
No
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5.0 "RESERVED"
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6.0 THE AEROMETRIC INFORMATION RETRIEVAL
SYSTEM
6.1 OVERVIEW
The Aerometric Information Retrieval System (AIRS) is a computer-based repository of
information about airborne pollution in the United States. AIRS was developed to allow State and
local air pollution control agencies to submit and retrieve air pollution data. The system is
administered by the EPA and may be used by anyone with access to the EPA computer system.
AIRS consists of five subsystems: the Air Quality Subsystem (AQS), the AIRS Facility
Subsystem (AFS), the Area and Mobile Subsystem (AMS), the Geographic and Common Subsystem
(GCS), and AIRS Graphics (AG).
• AQS contains air quality information, such as measurements of ambient air pollutant
concentrations and meteorological conditions reported by thousands of monitoring stations
operated by State and local agencies and the EPA. In addition to individual
measurements, this subsystem contains summary statistics for each monitoring station,
such as the annual arithmetic mean and number of times the measured concentration
exceeded a national ambient air quality standard. AQS also contains descriptive
information about each monitoring station, including its geographic location and the
operating agency. AQS will be the subsystem designated for the storage of PAMS
ambient measurements data. AQS contains four types of air quality data:
(1) Monitoring Site Descriptions characterize the monitoring sites that provide data to
AIRS. The information, which resides in the AIRS Site file, includes site location
[geographic coordinates, street address, city, county, State, Air Quality Control
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Region (AQCR), etc.], site operational dates, the organization responsible for the
monitor operation, and many other items. State and local agencies provide site
information to AIRS.
(2) Raw Data are the individual values of pollutant concentrations or meteorological
conditions measured at the monitoring sites and supplied to AIRS by the State and
local agencies that operate the monitors. AIRS contains three raw data files:
(a) The hourly file contains data sampled at intervals of less that 24 hours (of
which the 1-hour interval is most common).
(b) The daily file contains data for sampling intervals of 24 hours or more (of
which the 24-hour interval is most common).
(c) The composite file contains data from composite samples (multiple samples
combined and analyzed as one).
There are actually two sets cf raw data files. One set holds public data, and the other
holds private, or "secured" data that are available only to the supplying organization.
(3) Summary Data are derived from raw data. There are two summary files in AIRS:
the air quality summary file and the SLAMS summary file. The air quality summary
file is derived entirely by AIRS software from information in the raw data files;
there is no direct input to the file. Conversely, the SLAMS summary file consists
entirely of the annual summary data each SLAMS monitoring agency is required to
submit to the EPA in accordance with the CAA.
(4) Precision and Accuracy Data characterize the precision and accuracy of air quality
monitors. The AIRS precision-accuracy file contains summaries of the precision and
accuracy of groups of monitors (all those operated by a particular reporting
organization).
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The AIRS AQS site file, raw data files, and air quality summary file contain all data that
were in SAROAD, the predecessor of AIRS. The AIRS/AQS site file includes information
about discontinued monitoring sites as well as active sites. The AQS raw data and summary
files contain all values from SAROAD, some of which date back to 1957. Since the AQS
uses the Federal Information Processing Standards (FIPS) geographic codes, site IDs were
changed when the data were converted from SAROAD.
• AFS contains point source emissions and compliance information. AFS is essentially a
merging of the former National Emissions Data System (NEDS) and the Compliance Data
System (CDS). AFS became operational in 1989.
• AMS contains emissions information from sources that are too small to be stored in AFS
and also holds information about mobile sources as well as biogenic data. AMS is the
newest of the subsystems and became operational in 1993.
• GCS contains reference information that is used by all the subsystems. Reference
information includes codes and code descriptions used to identify places, pollutants, and
processes; populations of cities, counties, and similar geo-political entities; and numerical
values, such as air quality standards and emission factors. EPA compiles and maintains
this reference information.
• AG utilizes information from all the above subsystems, and displays the data graphically.
Maps, bar charts, line graphs, and multiple line charts are all available via AG. Maps
may be generated on a national, State, or county level. Future enhancements include
maps by MSA and zip codes. (Samples of typical outputs from AG may be found in
Appendix K.)
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6.2 DATA INPUT AND UPDATE PROCEDURES
Nearly all the air quality data in AQS come directly from the SLAMS and NAMS air
monitoring networks, which are operated by State and local pollution control agencies. A small
amount of raw data comes from the EPA or private sources.
New air quality data are loaded into the AQS and existing data are modified or deleted using
transactions that have the format of punched cards (80-character records). There are transactions for
site and monitor information, SLAMS summary data, and raw data. A local, State, or EPA
organization submitting air quality data to AQS creates a file of transactions (usually on magnetic
tape) on the IBM computer system at the EPA's National Computer Center (NCC). The organization
submitting data uses AQS software to load the transaction into a "screening file," check the validity
of the transactions, and correct any errors found. A screening file is part of the AQS database and is
used to hold AQS transactions during validation. Each organization submitting data to AQS has a
screening file for its own exclusive use.
When the transactions in a screening file have passed validation checks, the organization
submitting the data notifies the AIRS database administrator that the screening file is ready to be
used for updating the AIRS database. The database administrator performs updates on a regular
schedule (usually once per week) using all screening files that are ready at that time. The
transactions used to update the database are automatically removed from the screening file by the
update program; any transactions that have not passed validation checks or that have been excluded
from update processing by the submitting organization remain in the screening file. To complete
the update cycle, the database administrator notifies the submitting organization that the update has
been completed, and that the screening file is ready to accept a new set of transactions. Further
information on data submission, validation, and updates procedures can be found in volumes AQ2 •
The AQS Data Coding Manual (Reference 21) and AQS - AQS Data Storage Manual
(Reference 22).
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6.3 DATA RETRIEVAL
The air quality data in AIRS are public and as such are available to any person or
organization with legitimate access to the EPA NCC. There are a few minor procedural requirements
for retrieving air quality data, however, which result from computer center policies and procedures.
AIRS users must be able to use the Customer Information Control System (CICS) and NATURAL
(programming language) on the IBM computer system. Users also must have the functional
equivalent of an IBM 3270 terminal. The AIRS hotline may be contacted for further information at
1-800-333-7909.
There are three ways to retrieve air quality data from the AIRS database. The easiest way is
to use the standard reports that have been defined by the National Air Data Branch (NADB). There
are two types of standard reports, batch and on-line. The batch standard reports allow users to
produce a printed report or data file (or both). The user specifies the criteria for data selection and
sorting, and chooses the option that affect the report format or content. The AIRS software
automatically takes this information and submits a batch run to produce the report and/or workfile.
Therefore, the user does not have to construct the output format of the report The on-line standard
reports allow users to view a report screen. The user specifies the criteria for data selection and the
AIRS software retrieves the data that meet the criteria and produces a report screen. Volume AQ4 -
Air Quality Retrievals Manual (Reference 23) contains instructions for using the standard reporting
facility and describes the features of each report.
If the standard air quality reports or the on-line data retrievals do not satisfy the user's
requirements, other reports can be defined using the AIRS ad hoc reporting function. The use of "ad
hoc" requires reasonable knowledge of the organization of the database, names of data fields, etc.
Volume AQ5 - AQS Ad Hoc Retrievals Manual (Reference 24) explains how to use the ad hoc
reporting function.
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The third type of data retrieval available for air quality data is via AIRS Graphics. AG has
both "ready-to-view" (RTV) maps (such as monitor locations, nonattainment areas) as well as
"create-your-own" (CYO) maps. The information used in constructing the RTV maps cannot be
changed. The CYO maps allow the users to select geographic areas, parameters desired, and time
period of interest. Used in conjunction with a raw data listing workfile from AQS, AG can even
produce time-series line graphs. The data from AG can be viewed on-line and/or in hard copy.
Further information on data handling for PAMS and AIRS may be found in References 21-24
of this manual.
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7.0 TECHNOLOGY TRANSFER NETWORK (TTN)
7.1 BACKGROUND
The Technology Transfer Network (TTN) is a network of electronic bulletin boards developed
and operated by EPA's OAQPS in the Research Triangle Park. North Carolina. The network
provides information and technology exchange in multiple areas of air pollution control, ranging
from emission test methods to regulatory air pollution models.
The TTN is comprised of a number of electronic bulletin board systems (BBS) which are
computer systems comprised of hardware and software that receive telephone calls from other
computers. The BBS concept began as a means for users to enter messages and read messages
addressed to them by other users. The modern BBS performs a variety of services that include the
exchange of programs, software, databases, and files of all descriptions. The most important function
of a BBS is easy and friendly access to expedite and promote the exchange of information. Users
are free to scan messages and pick those which are of particular interest. Information may be
exchanged over long distances and at high speeds. For the ambient air monitoring community,
especially PAMS users, the TTN is a vehicle for accessing the Ambient Monitoring Technology
Information Center (AMTIC).
7.2 THE AMBIENT MONITORING TECHNOLOGY INFORMATION
CENTER BULLETIN BOARD
The AMTIC BBS is accessed through the TTN and is available to all persons interested in
ambient monitoring. It currently contains all FRM and Equivalent Methods for the criteria
pollutants, all Toxic Organic (TO) Methods, all Federal regulations pertaining to ambient air
monitoring, information on quality assurance/quality control (QA/QC), monitoring studies,
information pertaining to ambient monitoring publications and documents, available related training
courses, upcoming meetings of interest, air quality trend and nonattainment information,
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photochemical assessment monitoring documents and regulations, points of contact, public message
boards, and more.
There is no cost to utilize AMTIC unless the user is accessing the system through a long
distance telephone line (in which case the user is paying the cost of the call). To access the AMTIC
or TTN, the following steps are necessary:
Step 1 - Install a modem and communications software on your computer; a wide variety are
available.
Step 2 - Set the following parameters on your communications software:
Data Bits: 8
Parity: N
Stop Bits: 1
Terminal Emulation: VT100 or ANSI
Step 3 - Call the network using your communications software:
(919) 541-5742 for a 1200, 2400, or 9600 bps modem
Step 4 - Log on to the system and answer the questions on the screen.
First Name? - Type your first name and press ENTER.
Last Name? - Type your last name and press ENTER.
Calling from (City, State)? - Type your city and state abbreviation, for example, Raleigh,
NC and press ENTER.
You are then asked to verify this information - Type Y or N.
Next, select a password that you can easily remember. After this, you will see some
information about the system. Press ENTER until you reach the main menu for unregistered
users. At this point you can select an option or exit the system. Options available include
Descriptions of OAQPS TTN Bulletin Board System, which contains a brief description of the
different bulletin boards available on the network, and System Utilities, which contains
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various options that are also available after you are a registered user. To select an option.
type the character shown within the brackets (< >).
Step 5 - Select Registration and enter your company name, address, and telephone number.
Then select the bulletin board you plan to use most often. For PAMS users, this should be
AMTIC. Note that you will still be able to access any bulletin board on the network.
You are asked to verify this information. (Type Y, N, or Q for quit.)
After this information is accepted, you will see the Registered Users menu. From here you
can access any BBS.
13 OTHER TTN BULLETIN BOARDS
Currently, in addition to AMTIC, access to the following bulletin boards is available through
the TTN:
AIRS - Aerometric Information Retrieval System - The focus of the AIRS BBS is to
encourage the exchange of information among State and local agencies that utilize AIRS
documents and information. AIRS BBS is operated by OAQPS and NADB.
The AIRS BBS maintains the current AIRSLETTER; relevant brochures, pamphlets, and
bulletins; and information on meetings, conferences, training seminars, and permits.
User-supplied AIRS-related demonstration software is circulated, as well as EPA PC-based
AIRS related software. All AIRS user's manuals and guides are available for download. The
AIRS bulletin board also contains a current listing of AIRS contact personnel. Answers to
frequently asked questions are available, as well as public and private electronic mail for use
in obtaining information from the AIRS user community.
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APTI - Air Pollution Training Institute - The Air Pollution Training Institute (APTI) offers
the widest scope of air pollution training in the United States. Funded by the EPA, APTI
develops instructional material for and provides technical assistance to training activities
conducted in support of the nation's regulatory programs of air pollution abatement.
EPA-sponsored lecture and laboratory courses, using APTI materials, are scheduled at several
locations across the country. Self-instructional courses, providing opportunities for individual
training at home or in places of employment, are obtainable from APTI. Training material is
continually updated, and individual courses undergo periodic major revision.
APTI publishes a "Chronological Schedule of Air Pollution Training Courses" generally once
a year. This publication describes the training being offered with a description of the APTI
courses and how to obtain the training. If you would like a copy of "Chronological Schedule
of Air Pollution Training Courses" contact the Registrar at (919) 541-2497.
BLIS - RACT/BACT/LAER Information System - The BLIS BBS contains information
from the Reasonably Available Control Technology (RACT)/Best Available Control
Technology (BACT)/Lowest Achievable Emission Rate (LAER) Clearinghouse. This
information is distilled from air permits submitted by most of the State and local air pollution
control programs in the United States. The data are meant to assist State/local agency
personnel and private companies in determining what types of controls other air pollution
agencies have applied to various sources. The BLIS database option allows the user to
perform interactive searches of the database.
CAAA - Clean Air Act Amendments - The Clean Air Act Amendments Bulletin Board
System (CAAA BBS) is designed to provide access to information on the CAAA. Through
this electronic information dissemination vehicle, the CAAA BBS allows regulators, the
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regulated community and members of the general public to easily obtain access to that
information that is relevant to the CAAA. In this manner, the task of understanding,
implementing and complying with the requirements of the new law will be made easier.
CHIEF - Clearinghouse for Inventories/Emission Factors - The CHIEF BBS provides
access to tools for estimating emissions of air pollutants and performing air emission
inventories. CHIEF will serve as EPA's central clearinghouse for the latest information on
air emission inventories and emission factors. Emission estimation databases, newsletters,
announcements, and guidance on performing inventories will be included in CHIEF.
COMPLI - COMPLIance Information on Stationary Sources of Air Pollution - The
COMPLI BBS contains three databases:
• NARS - National Asbestos Registry System - A listing of all asbestos contractors,
their inspections and the results of them. This database is used to target contractors
for inspection.
• Determinations Index - This is a compilation of clarifications and determinations
issued by EPA concerning selected subparts of the Federal Register. It consists of
two major parts: NSPS determinations and NESHAP determinations.
• Woodstoves - A database of EPA Certified Woodstoves and woodstove
manufacturers.
This COMPLI BBS is maintained by EPA's Stationary Source Compliance Division (SSCD).
Problems, suggestions, or additional information should be directed to the COMPLI BBS
SYSOP.
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CTC - Control Technology Center - The CTC is a cooperative effort for engineering
assistance to State and local air pollution control agencies (and private companies to an
extent) by the Air and Energy Engineering Research Laboratory (AEERL) and OAQPS. It is
a cooperative effort with the State and Territorial Air Pollution Program Administrators
(STAPPA) and the Association of Local Air Pollution Control Officials (ALAPCO).
The CTC provides three levels of assistance:
HOTLINE - (919) 541-0800
Engineering Assistance
Technical Guidance
The CTC's goal is to provide technical support to State and local agencies and to EPA
Regional Offices in implementing air pollution control programs. The CTC assists regulatory
and permitting agencies, but does not provide policy guidance and compliance advice which
is the responsibility of the EPA Regional Office. CTC services are available at no cost to
State and local air pollution control agencies and EPA Regional Offices. Other government
agencies may use the HOTLINE for technical assistance or to order CTC documents.
EMTIC - Emission Measurement Technical Information Center - The EMTIC BBS
provides technical guidance on stationary source emission testing issues, particularly to those
who conduct and/or oversee emissions tests in support of the development and
implementation of emission standards, emission factors, and SIPs.
NATICH - National Air Toxics Information Clearinghouse - NATICH is an information
service cooperatively provided by EPA and STAPPA/ALAPCO to support their efforts at
controlling toxic (non-criteria) air pollutants. Thus, the Clearinghouse is designed to facilitate
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the exchange of information among federal, State, and local agencies concerned with control
of toxic air pollutants.
To achieve this goal the Clearinghouse annually collects, classifies, and disseminates
information submitted by State and local agencies regarding their air toxics programs. In
addition, NATICH also provides information on current federal activities in controlling air
toxics.
The Clearinghouse provides the following:
Quarterly Newsletter
Hardcopy Reports of the Database Contents
Telephone Helpline: (919) 541-0850
NSR - New Source Review - The NSR BBS provides material and information pertaining to
New Source Review (NSR) permitting. The user can search the abstracted index of the "New
Source Review Prevention of Significant Deterioration and Nonattainment Area Guidance
Notebook" by selected key words or a customized text word or text string.
OAQPS - Office of Air Quality Planning and Standards - This bulletin board provides
fundamental information regarding the organization and function of each unit in EPA's
OAQPS. Additionally, information services and reports on the status of air pollution control
activities are available.
OMS - Office of Mobile Sources - The purpose of the bulletin board is to provide the user
with information pertaining to mobile source emissions, including regulations, test results,
models, guidance, etc. The following information is available on the BBS:
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• Office of Mobile Sources Contact List
• OMS Rulemaking Packages and Reports per the Clean Air Act
• Vehicle and Engine Certification Guidance
• Fuel Economy Information
• Vehicle Emissions Models (e.g., MOBILES)
• Public Awareness Information ("Fact Sheets")
• Other Relevant Mobile Source Emission Documents
SCRAM - Support Center for Regulatory Air Models - The SCRAM BBS is the
Agency's primary source for the acquisition of the computer codes for the regulatory air
models. Changes to the models, including updates, corrections, and new regulatory codes are
main features of the SCRAM. Significant announcements and new information are indicated
in the SCRAM ALERTS section of the BBS.
The new user can obtain a quick review of BBS services by browsing through the main
menu options. In addition to code, model related news and important bulletins are provided
concerning model modifications, status, etc. An especially important feature is the "Model
Change Bulletin" (MCB) provided for each model/program. MCB #1 lists information on the
initial status of that model; new MCBs are posted for each model as required.
7.4 USING THE AMTIC/TTN
The TTN and AMTIC are available 24 hours per day, 7 days per week except for Monday
morning 8:00 a.m. to 12:00 noon Eastern Time (unless otherwise noted), when the system is down
for maintenance and system backup.
There are several methods for accessing the TTN BBS. Some methods may involve incurring
long distance telephone charges, but others are completely free. Not all methods are available to all
people. The following access methods are currently available:
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Conventional Modem Dialup
EPA Ethernet Connection
X.25 Pads (Packet Switching Network)
Internet
7.4.1 Conventional Modem Dialup
Anyone with a computer, a modem, and communications software may log on to the TTN by
setting their modem to 8 data bits, no parity, and 1 stop bit (8-N-l), and dialing (919)541-5742.
New users must fill out a short registration survey, and will be given full access on their first call.
Using this method, the user must pay any long distance charges that are accrued.
7.4.2 EPA Ethernet Connection
This method of connection is available only to EPA employees located in Research Triangle
Park, NC. The EPA Ethernet allows all users free access to the TTN through Crosstalk.
7.4.3 X.25 Pads (Packet Switching Network)
To promote electronic communications among the EPA Regional Offices, the EPA has
arranged for a network of X.25 pads connecting the EPA Regional Offices to computer facilities in
Research Triangle Park, NC. The X.25 pads allow users to dial up a local number in their city and
connect to remote computer facilities. Access to the X.25 pads is available to all EPA Regional
Offices and may be available to State and local Air Quality Control Offices as well. For further
information, contact your local EPA Regional Office.
7.4.4 Internet
The TTN is now available through Internet. If you are connected to the Internet via an
"Internet Access Provide" you can now reach the TTN. To reach the TTN on Internet, you must
invoke the "TELNET" service. "TELNET" is capable of hosting a fully interactive session. Other
Internet services such as Internet mail and FTP will not allow you to connect to the TTN.
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Use the following "TELNET" command, which includes the TTN Internet address:
TELNET ttnbbs.rtpnc.epa.gov
Your Internet provider may use a slightly different procedure or syntax. If you are unsure
how to initiate a "TELNET" session, please check with your Internet provider. Accessing the TTN
through the Internet is free of charge. However, your Internet access provider may charge a fee for
access to the Internet.
Assistance with accessing the systems may be obtained during normal business hours (Eastern
Time) by contacting the TTN Helpline at (919)541-5384.
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8.0 REFERENCES
1. Code of Federal Regulations, Title 40, Part 58, U.S. Government Printing Office, 1992.
2. Clean Air Act Ozone Design Value Study, Preliminary Draft, U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, April 1993.
3. Guideline for the Interpretation of Ozone Air Quality Standards, EPA-450/4-79-003, U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina, January 1979.
4. Purdue, Larry J., Dave-Paul Dayton, Joann Rice and Joan Bursey, Technical Assistance
Document for Sampling and Analysis of Ozone Precursors, EPA-600/8-91-215, U.S.
Environmental Protection Agency, Atmospheric Research and Exposure Assessment
Laboratory, Research Triangle Park, North Carolina, October 1991.
5. Purdue, Larry J., "Summer 1990 Atlanta Ozone Precursor Study," presented at the VOC
Workshop Assessment and Evaluation, Amersfoort, The Netherlands, January 26-28, 1993.
6. Purdue, Larry J., J. A. Reagan, W. A. Lonneman, T. C. Lawless, R. J. Drago, G. Zalaquet, M.
Holdren, D. Smith, C. Spicer and A. Pate, Atlanta Ozone Precursor Monitoring Study, U.S.
.Environmental Protection Agency, Atmospheric Research and Exposure Assessment
Laboratory, Research Triangle Park, North Carolina, April 3, 1992.
7. Lewis, Charles W. and Ten L. Conner, "Source Reconciliation of Ambient Volatile Organic
Compounds Measured in the Atlanta 1990 Summer Study: The Mobile Source Component,"
U.S. Environmental Protection Agency, Atmospheric Research and Exposure Assessment
Laboratory, Research Triangle Park, North Carolina, September 1991.
8. Code of Federal Regulations, Title 40, Part 50, U.S. Government Printing Office, 1992.
9. Ludwig, F.L. and E. Shelar, Site Selection for the Monitoring of Photochemical Air
Pollutants, EPA-450/3-78-013, U.S. Environmental Protection Agency, Research Triangle
Park, North Carolina, April 1978.
10. Liu, L.-J. Sally, Petros Koutrakis, Helen H. Suh, James D. Mulik, and Robert M. Burton,
"Use of Personal Measurements for Ozone Exposure Assessment: A Pilot Study,"
"Environmental Health Perspectives," Journal of the National Institute of Environmental
Health Sciences, Vol. 101, No. 4, September 1993.
-------
EPA-454/B-93/051
Section No.: 8
Revision No. 0
Date: March 1994
Page 8-2
11. Mulik, James D., Jerry L. Yarns, Petros Koutrakis, Mike Wolfson, Dennis Williams, William
Ellenson, and Keith Kronmiller, "The Passive Sampling Device as a Simple Tool for
Assessing Ecological Change - An Extended Monitoring Study in Ambient Air," presented at
the Measurement of Toxic and Related Air Pollutants symposium, Durham, North Carolina,
May 1992.
12. Koutrakis, Petros, Jack M. Wolfson, Arnold Bunyaviroch, Susan E. Froehlich, Koichiro
Hirano, and James D. Mulik, "Measurement of Ambient Ozone Using a Nitrite-Coated Filter,"
Analytical Chemistry, Vol. 65, 1993.
13. Schweiss, Jon, "Draft Guidance for the Use of Portable Samplers," U.S. Environmental
Protection Agency, Seattle, Washington, February 1991.
14. Shao-Hang Chu, "Meteorological Considerations in Siting Monitors of Photochemical
Pollutants," presented at the Regional Photochemical Measurement and Modeling Study
Conference, San Diego, California, November 1993.
15. Screening Procedures for Estimating the Air Quality Impact of Stationary Sources, Revised,
EPA-454/R-92-019, U.S. Environmental Protection Agency, Research Triangle Park, North
Carolina, October 1992.
16. Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV:
Meteorological Measurements, EPA-600/4-82-060, U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina, 1989.
17. Ambient Monitoring Guidelines for Prevention of Significant Deterioration (PSD), EPA-
450/4-87-007, U.S. Environmental Protection Agency, Research Triangle Park, May 1987.
18. On-Site Meteorological Program Guidance for Regulatory Modeling Applications, EPA-
450/4-87-013, U.S. Environmental Protection Agency, Research Triangle Park, North
Carolina, 1987.
19. On-Site Meteorological Instrumentation Requirements to Characterize Diffusion from Point
Sources, EPA-600/9-81-020, U.S. Environmental Protection Agency, Research Triangle Park,
North Carolina, 1981.
20. Code of Federal Regulations, Title 40, Part 53, U.S. Government Printing Office, 1992.
21. AIRS Users Guide, Volume AQ2, "Air Quality Data Coding," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, 1993.
-------
EPA-454/B-93/051
Section No.: 8
Revision No. 0
Date: March 1994
Page 8-3
22. AIRS Users Guide, Volume AQ3, "Air Quality Data Storage," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, 1993.
23. AIRS Users Guide, Volume AQ4, "Air Quality Data Retrieval," U.S. Environmental
Protection Agency, Research Triangle Park, North Carolina, 1993.
24. AIRS Users Guide, Volume AQ5, "AIRS Ad Hoc Retrieval," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, 1993.
A list of bibliographic material related to PAMS implementation and monitoring is included in
Appendix L.
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EPA-454/B-93/051
Appendix A
Revision No. 0
Date: March 1994
Page A-l
APPENDIX A
PAMS PROPOSAL AND FINAL RULE
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federal Register / Vol. 57. Mo. 43 / Wednesday, Match 4.1092 / Propped Rutet
7887
PMOTECTO*
AGENCY
•aanct; Eavgammimtal Protection
Ageaty.^
.._. .•UKtuurr.Tbisjiatice proposes to revise
regulations (40 QFR part 58) to Include
provisions for enhanced monitoring oT
ozone and oxides of nitrogen. end lor
additional monitoring of volatile organic
coinpotBidi Pt"^V"^*t\fl aldehydes) »nA
meteorological parameters. These
revisions «w being proposed is
accordance with title L section 1£2 ol
the 1890 Qeaa Air Act Amendments.
The rerisions would require States to
establish photoc?***"'*^ ••••f«m*nt
monitoring stations IPAMSj as part of
their State Implementation Plan {SIP)
monitoring network in ozone
nonattainmeot areas classified as
serious, severe, or extreme. Ind»ih>ri in
the proposal an minimum criteria for
network design, monitor siting.
monitoring methods, operating schedule.
quality assurance, and data submittal.
DATES: Comments aus! be received on
or before April 3.1882.
anmgitffc Submit comments to
duplicate copies are preferred) to:
JeotraJ Docket Section, US.
Environmental Protection Agency, Attn.
Docket Ma A-BJ-22. 401 M Street SW.
Washington. DC 20460. Docket No. A-
81-22 i* located in the Central Docket
Section of the US. Environmental
Protactioa Agency. West Tower Lobby
Gallery 1401M St, SW, Washington.
DC 20460. The docket may be inspected
between 8 aon. and 4 pjn. on weekdays.
A reasonable fee nay be charged for
copying.
KM FURTHM WPOMMATION CONTACT:
fariadinf J. Dorocx. Technicai Support
Division (MD-14J. Office of Air Quality
Planning gad St«tt/t«n4« U.S.
Environmental Protection Agency.
Research Triangle Park. N.C 27711.
phone: 019-441-6432 or (FTS) 820-5051.
Background
Section 110(aX2](C) of the Ctean Air
Act requires ambient air quality
monitoring for pirpoacs of the State
Implemeotatioa Plan (SIP) end reporting
of the data to EPA. Uniform criteria for
measuring air quality and provisions for
the reporting of a daily air pollution
index are required by auction SI* of the
VWPte » V «v«M«p WWVV •W*t«M»«MMM
.Mayt0.tf79(44Htrxn).EPA .
esUblisaed 40 Cra part SB which .
provided dstaJkd isxuBTCSBSBts far air
quality surveillance sad data reporting
far all the pollutants except lead for
which ambient air quality standards
(criteria •oUatants) has been
established. OB September 3.1981 (46
PR 44164) asodlar nlas were
promulgated far bad and on Jury 1,1987
(52 PR 21740) iorpartieulate matter
Thf jfftfgff rf *fcf y«A»nj>»d nr»p»
today is to amide an air qaality date
base that wiO assist air pollution control
agencies in evaluating, tracking the
progress of. and. if aecsssary. refining
control strategies for attaining the ozone
National Ambient Air Quality Standards
(NAAQS). Ambient concentrations of
ozone (O»). oxides of nitrogen (NO,.
NO,, and NO), and speciated volatile
organk compounds (VOQ mdading
aldehydes (or their surrogates) and
meteorological date collected by fee
PAMS will be seed to tnake attainment/
nonattainneot decisions, aid fa tracking
VOC and NO, emission Inventory
reductions, better characterize the
nature and extent of the ozone problem.
and prepare ah quality trends, bi
addition, date from the PAMS will
provide an improved data bate for
evaluating model performance.
especially for future control strategy
mid-course corrections as part of the
continuing air quality management
process. The data will be particularly
useful to states in ensuring the
implementation t>f the most cost
effective, socially acceptable regulatory
controls.
The regulations proposed m this
requirements for the enhancement of
ambient air monitoring for ozone and
nitrogen oxides ss well ss monitoring
for speosted VOC and meteoi oiogjcal
parameters. Tide L section 182 of the
1990 Clean Air Act Amendments
requires enchanced monitoring for
ozone and its precursors. Also, section
184(d) requires that the best available
air quality monitoring and nodding
techniques be «sed in soaking
determinations wmjeiuuig the
contribution of sources m one ares to
concentrations of ozone in another area
which is a nonattemment area for
ozone. In the process of developing
proposed regulations to address this
requirement the EPA •ought the
assistance of the Standard Air
Monitoring Work Group (SAMWG).
SAMWG sMmbers represent State and
local air pollution control agencies sad
EPA program and regional offices.
SAMWG SBembefswent an active
partner in deveiapha] and reviewing the
1979 part SB rulenaking pickage which
formally ectabbshad *e existing
framework of the •ssbient air quality
surveillance and data reporting
regulations. They also played a
prominent rale in all •abwtraent
revisions to part 8*.
According!y. the Agency is solidting
comment on all npects of me proposed
rules and particularly on the general
scope and adequacy of the proposal the
necessity and/or adequacy of the
individual components of the monitoring
approach, and the Agency's estimated
monitoring costs.
Proposed Ravisioas to Part SS—AmbienI
Air Quality Surveillance
Section 5&1 Definitions
The revision* pcopuaeJ today would
add definitions of the terms "PAMS"
(pbotochraucal assessment monitoring
stations). "NOT (nitrogen dioxide).
-NO" (nitrogen oxide). -NO." (oxides of
nitrogen). ~VOCr (voiatile organic
Section 583 Purpote
Currently, part SB mntains a provision
to establish a national ambient air
quality monitoring netumk far the
purpose of providing timely air quality
data upon which to base national
ambient air assessments and policy
decisions. This national network is a
subset of die State and Local Air
Monitoring Stations (SLAMS), and these
stations in the network are designated
as National Air Monitoring Stations
(NAMS).Tbe NAMS are subject to
monitoring and reporting requirements
contained in subpart D of part SB. The
proposed revision to this section adds a
revised paragraph (d) which explains
that part SB acts to establish a network
of PAMS which are also subsets to
SLAMS but subject to monitoring and
reporting requirements contained in the
redesigned and revised scbpart E of
this part
Section S8J3 Operating Schedule
The current operating schedule for
SLAMS continooBS analyzers is given in
paragraph (a) of this section and
requires collecting cmiscuitire hourly
averages except during periods of
routine maintenance, instnaient
calibration, and periods or seasons
exempted by the Regional
Administrator.This same operating
schedule also applies to the proposed
PAMS continuous O» and NO, analyzers
and automated gas chromatognphs. For
manual methods except for lead, the
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7688 Federal Register / Vol 67. No. 43 / Wednesday. March 4.1992 / Proposed Rules
cmmt requirements ere specified in
paragraph (b) ud require States to .
obtain at toast one 24-hour sample every
0 days except during periods or seasons
exempted by the Regional
Administrator. Paragraph (b) is being
revised to also exempt manual VOC
sample*. In addition, a new paragraph
(c) is proposed which presents the
operating schedule for manual apeeiated
VOC measurements. Changes to
operating schedules for PAMS must be
approved by the Administrator. The
existing paragraph (e) is redeaignatud as
paragraph (d). lie Agency seeks
comment on the proposed operating
schedule for PAMS and the ""y1'"!
frequencies for VOC and aldehydes.
Section 5830 Air quality MurveilJance:
Plan content
This section originally required States
by January 1.1860 to submit a SIP
revision which included provisions for
establishing and operating the SLAMS
network to measure ambient
concentrations of those pollutants for
which standards have been established
in part 50 of title 40 (criteria pollutants).
The section included provisions to apply
to criteria of part 58 of title 40,
appendices A (quality assurance), C
(monitoring methods). O (network
design), and E (probe siting) to designing
and implementing the SLAMS network.
It also provided for an annual network
review and monitoring during all
•tanges of air pollution episodes.
Currently. | S&20 does not require
States to include in their SIP a provision
for monitoring non-criteria pollutants.
Because enhanced ozone monitoring
will require monitoring of non-criteria
pollutants (NO,. NO, and spedated
VOC) and meteorology, paragraph (a) of
this section is revised to include a
provision that SLAMS designated as
PAMS will obtain these additional
measurements. It is likely that due to the
multiple monitoring objective for PAMS,
that the site locations will in some
cases, coincide with existing SLAMS (or
NAMS) monitoring sites. In these cases.
the sites only need to be supplemented
with those instruments necessary to
.comply with PAMS monitoring
requirements. To establish the PAMS, a
new paragraph (I) provides that States
with ozone nonattainment areas
designated as serious, severe, or
extreme will be required to submit a SIP
revision which includes additional
provisions for monitoring these nan* .
criteria pollutants and obtaining
meteorological data. These revisions
would be due 0 months after the
effective date of promulgation or
redesignation and reclassification of any
•area to serious, severe, or extreme
ozone nonattainment The Agency seeks
comment regarding the adequacy of the
e-montb period for preparation and
promulgation of SIP revisions to
BodatePAMS.
This revision is in accord with section
182 of title I of the 1990 Clean Air Act
Amendments. Other revisions to 1 5&20
adds the word "criteria"before the
words "pollutant except Pb". This
change is being proposed since the
proposed revisions in paragraph (a)
t^li wi«n
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Federal Register / Vol 87. No. 43 / Wednesday. March 4.. 1992 / Propoied Rules 7589
ule. u>d the recognized
Deed for flexibility, the PAMS network*
11 be subject to die approval of the
linif tntor. More detailed
.jtmation regarding the uses of PAMS .
data may be found in appendix D of the •
propoaal Hie Agency seeks comment on
the appropriatenesa of the intended
PAMS data uaea and probable data
.relate to ozone pi
aniaaiona.it
- Jtctiea 88.43 PAMS Methodology
Thii section would require that aD
PAMS meet die PAMS monitoring
methodology requirement* specified in •
appendix C Existing station* would be
required to meet the method ••
requirement* at the time of network
•description submlttaL Future stations •
would need to meet those requirement*
upon their establishment
Section SS.44 PAMS Network
Completion
The completion date for the
establishment of the PAMS network
would be 5 year* after the effective date
of the promulgation of the regulation* or
redesigns lion and redassification of the
area to serious, severe, or extreme
ozone nonattainmenL A five-year phase-
in period was proposed to follow a.
naionable buildup of resources at "the
' State and local agency level to
accommodate the expected evolution of
' - sampling technology, and to allow a
iring-up" period to develop the
jttiny expertise and infrastructure
to conduct this complex mointoring
effort Full details of the proposed 5-year
traatition process are provided in
appendix D.
In light of the importance of the PAMS
data to the development and evaluation
of alternative State Implementation Plan
(SIP) strategies, the Agency seek*
comment on the pro* and con* of shorter
or longer phase-in period*, especially a*
they relate to modelling demonstration*
required of the affected area*. The
Agency therefore seeks comment on
period* of 1.2.3 year* or longer.
Section 58.4S PAMS Date Submittol
Thii section would establish the
reporting requirements for the PAMS
data. The data from O», and NO,
(including NO and NO» data) monitor*
would be required to be submitted to
EPA's Aerometric Information Retrieval
System (AIRS)—Air Quality Sub*y»tem
(AQS) within 60 days following the end
of each quarterly reporting period.
Meteorological data and apeciated VOC
data must be submitted within 6 months
after the end of the quarterly reporting
(period.Inasmuch as meteorological data
will often be used to interpret ozone •
tcursor ambient data and how they
also is required to be submitted within
the 8-month time frame specified for
.apedated VOC data. Given the
complexity and interpretive expertise
required to analyze spedated VOC data
and especially given the rapid evolution
of the monitoring technology. 6 months
was established aa a reasonable time
period for spedated VOC data :
BubmittaL The Agency seeks comment
on the reasonableness of *hi« time
peirod, .
Section 58.46 System Modification
.. This section would include a
requirement that any change* in the
PAMS network be evaluated during the
annual SLAMS review specified in
15&20. Changes that are proposed by
the State would be evaluated by the
EPA Regional Office and must be
approved by the Administrator. An
implementation time of 1 year would be
granted to complete the approved
change*. This procedure would al*o
apply to change* to the PAMS network
which resulted from a redesignation of
the area to attainment
Revisions to Appendix A-Quality
Assurance Requirements for State and
.Local Air Monitoring Stations (SLAMS)
Appendix A ia being revited to
include a provision that refer* to Agency
guidance on quality assurance criteria
for VOC measurement*. Monitoring
technique* for spedated VOC are
emerging technologic*, and quality
assurance criteria equivalent to that in
part SB for the criteria pollutant* are
currently not. available for VOC. EPA i*.
however, preparing guidance on VOC
mointoring technology and this
document will addreii quality
assurance for VOC as well aa for
meteorological measurement*.
Appendix. C—Monitoring Methodology
The requirement* in appendix C were
promulgated to provide limitation* on
the allowance of methods to be u*ed in
the SLAMS and NAMS network. The
purpose of the limitation* are to reitrict
allowable method* to thote which have
been tested and proven to be reliable or
to thoie which show aignificant
probability of being reliable.
The proposed revision* to appendix C
would include a aimilar but leu
reitrictive limitation on PAMS
measurements. The revicion* would
require that PAMS Ob and NO,
monitoring method* be automated
reference or equivalent methods.
However, reference or equivalent
method* for meteorological
meaturements or spedated VOC
measurements an not available since •
reference or equivalent requirement* or
apedfications for these methods are not
currently included in EPA regulations. In
the absence of such spedfications and
because of EPA concerns about the need
for minimum uniform criteria concerning
measurement methodology. EPA has
• prepared a document which provides
Agency guidance on method* for .
• conducting meteorological •
measurement* and measurements for
"VOC Appendix C would require States
to use this guideline document in
•••electing and conducting such
measurements at PAMS. Should States
prefer to propose alternative methods
lor conducting VOC measurements, the
methods must be detailed in the
network description required by i 5&.40.
Such proposed alternative methodology
must be published in the Federal
Register, subjected to public comment
and subsequently approved by the
Administrator.
Appendix D—Network Design for State
and Local Air Monitoring Stations
(SLAMS). National Air Monitoring
Stations (NAMS). and Photochemical
Assessment Monitoring Stations
(PAMS)
Appendix D currently contain*
criteria to be uied in designing networks
to meet the monitoring objective* for
SLAMS and NAMS. The design criteria
are intended to provide uniformity in
locating air monitoring stations for the
SLAMS and NAMS networks. A new
section 4 of appendix D is being
proposed to provide a similar concept of
minimum criteria for designing a PAMS
network. Section 4 contain* a
description of the major uses of data
from the PAMS. These uses indude
ozone attainment/nonattainment
deciaions. preparation of control
strategies for ozone nonattainment
. areas, tracking of VOC NO,, and toxic
air pollutant emiuion inventory
reduction*, providing future input to
photochemical model* and data for
model evaluation, preparation of air
quality trend*, and characterization of
population expoiure to ozone and urban
air toxic pollutant*. Specific objectives
that muit be addressed indude
assessing ambient trends in VOC and its
specie*, determining spatial and diurnal
variability of VOC apedes and
assessing changes in the spedes profiles
that occur over time, particularly those
occurring due to the reformulation of
fuels. Note that data from stations which
operate NO* monitors year round can
also be utilized to determine attainment
or nonattainment with the NOi National
Ambient Air Quality Standard which is
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Register / Vol 57. No. 43 / Wednesday, March 4.1S92 / Proposed Rule*
expressed as as aaaoal arithmetic
mean.
d sniiiW i
ilii
network to adequately satisfy an of .
these deUase* would require
. extraordinary resources; consequently, •
practical compromise on the minimum
number of stations in a PAMS network
_ Si proposed Tbejncposal identifies five
types of PAMS, which hive different
monitoring objectives or functions *
relative to the MSA/CMSA
Boaattainmest area. The number and
types of stations vary depending on the
size of the MSA/CMSA or
Bonattainment area, whichever is larger.
For a larger MSA/CMSA, as many as
five sites would be needed to provide a
data base sufficient to consider spatial
variations and to develop treads for
VOC and its species within that MSA/
CMSA. By utilizing population as a
•arrogate for total MSA/CMSA (or
BonattsJnment ana) eeaisaiona density,
the requirements far numbers of sites is
stratified from two to five sites per area.
Such differing criteria am repaired to
scconodate the impact of transport OB
the smaller MSA's/CMSA's. to account
for the spatial variations inherent to
Urge anas, and to satisfy the differing
data needs of large versos saaU areas
due to the mtracUbffity of the exone
Bonattanment problem. Given these
assumptions, the Agency seeks
comment on the extent to which the
aforesaid "practical compromise"
feet-work requirements would provide
sufficient data to fulfill the data uses
described in appendix D, section 4.1 and
4.2. aad sommarixed in Table 1.
Additionally. «*»»«>*"« is sovght
regarding the cost and content of
substitute mechanisms for establishing
which weak) alto folfffl the proposed
objectives and data me*. In particular.
the Agency seeks information on
substitute sampling regimes (both
frequency and oontion). toe use of
statistical approaches to supplement (o
fa lieu of) sampling, sad other sampling
Biethods.
The Agency renngntm that other
proxies for emissions density, and
therefore vfljuircmests for combers of
sampling sites, could have been
tendered. The Agency also seeks
couttent OB wnetnef BMfe complex
Biechanisms which iachide factors such
as precufsoi omissions, feognphy,
indkatom ttc, should be Btilned
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Federal Register / Vol. 57, No. 43 / Wednesday. March 4.1992 / Proposed Rules
7691
ui
Ei
s
i
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7892 Federal Register / VoL 57. No. 43 / Wednesday. March 4. 1992 / Proposed Rules
•••••^
Typep) PAMS sites would
characterize the upwind background *
and transported precursor *
concentrations entering the
Bonattainment area. Type (2) site* '
would be intended to monitor areas of
maximum precursor (VOC and NOJ
emissions, be ideally suited for the
monitoring of urban air toxic pollutants,
and might typically be located near the
predominantly downwind edge of the
central business district or other area of
mtTtmym precursor emissions such as
from a large industrial area or major
traffic area. Type (2) sites, however,
should not be unduly influenced by
•ingle emission sources. The Agency
seeks comment on the reasonableness of
the view that this one site would suffice
for the purpose of reporting on urban air
toxics and assessing exposure. Type (3)
sites would monitor changes in
precursor concentrations and ratios
downwind of the emission sources and
would be located between Kites (2) and
(4) typically at the population fringe of
the urbanized area. Type (4) and Type
(5) sites would be sites located to
measure the maximum ozone
concentrations. Site (4) would be located
in the predominant downwind direction
during the ozone period and site (5)
would be located in the second most
predominant downwind direction. Given
the large variability in emissions.
meteorology, geography, etc. from area
to area, the Agency recognizes that
situations may occur where the
minimum monitoring system required by
the proposed rule is inadequate. The
Agency also seeks comment on the
criteria for determining such inadequacy
and on a process for resolving the issue.
Because of the relatively large
resource requirements to conduct PAMS
monitoring. 3 months is being proposed
as the mhihniim annual precursor
monitoring period for the PAMS;
however. EPA encourages the
establishment of a monitoring period for
the entire ozone aeason in order to
provide a more comprehensive air
quality data base and increase the
possibility of actually conducting
monitoring during most of the worst
ozone episodes. PAMS ozone monitors
snust adhere to the ozone monitoring
aeason specified in section Z5 of
appendix D.
Also included in appendix D are
driteria for establishing ground level
meteorological stations and a
KGoniDcoQ.8 uOii for ODt&uxsinfi tipper Air
meteorological data. Ground level
stations would be required to be
operational upon establishment of the
station. The Agency requests ia»mm»nt
on tbf general P*M for meteorological
stations and the adequacy of the
proposed oo-site measurements. Based
en comments received during the
Streamlined review process, the Agency
recognizes that m rare cases it may not
be possible to site a 10-meter
meteorological monitoring tower at •
particular PAMS site. The Agency.
therefore, •»*^« rmtm>»nt« on thf
criteria to determine bow meteorological
data collected at a nearby site could be '
used to represent the meteorology at a
PAMS she where the tower and the air
monitoring equipment cannot be
collocated.
Appendix. S—Probe Siting Criteria for
Ambient Air Quality Monitoring
This appendix currently contains
detailed provisions for specifically
locating the sampler or analyzer probe
inlet after the general location of the
SLAMS or NAMS sampler or monitor
has been selected.
Overall the siting criteria for the
PAMS monitors are similar to the
NAMS/SLAMS criteria for such items as
the minimum distance of the inlet probe
from obstructions, vertical and
horizontal probe placement mUk« CoMjr (ILX H-M-WI
•HWJE-MD.
W).
SZ060.000
2450JDO
2.11TJOO
2.0600X
2josaooo
2450.000
..1J73J20
I
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•Men! fiesbtar / Vol. V. No. 43 / Wadnetday. March 11992 / ftoposed fiulei
7693
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Tabled also delineates the estimated
increases in monitoring costs (above the
present national ambient air monitoring
network) associated with fee
establishment of PAMS sitei in the
•fleeted areas. For the purpose of these
estimates. EPA has assumed that 64
ozone monitors and 66 NO, BMuritora
which are currently in operation will be
converted to PAMS components. The
cost estimates, therefore, do not include
any provision for these monitors aince
••eration and sample analysis costs are
eady included in the current national
.mbient airmoniloring program. The
cost estimates for each MSA/CMSA do
include new capital expenditures.
operational costs, and labor costs
associated with the hiring of new eeroor
environmental chemists/
chromatographers and jtatisticiau/data
analysts. The PAMS costs are expressed
as 5-year cumulative costs, from
initiation of the network through
required completion (beted on the
phase-in schedule proposed in appendix
Dj which amounts to a total of
approximately $45 million nationally.
Continuing •*""»•! costs for the
operation and maintenance of me PAMS
system, tadndmg an allowance for
equipment replacement are about 911J&
million. By comparison, current national
costs for routine ozone-related
monitoring programs involve the
operation of 626 timiie monitors for
$13* million and 329 NO, monitors at
jioj million TJCf J^BAT* ^^o^rcflt &OTAJ .
criteria monitoring capital and operating
costs amount to $57 million annually.
further detail on the bases for these cost
estimates is provided in Table 3.
TABIE 3. COST test ENHANCED OZONE
MONTTORMQ STATION
IMT only)_.
•-month.
13matt\.
«BOO
7300
9JBOO
tztoo
•0300
S7JOO
41300.
15.400
•UNO
2.400
19300
*a.7oo
X2.no
47.100
^-
as.4oo
SJOJBOO
uoo
CBOO
•xno
During the rmt year of operation, the
PAMS network U likely to oost
approximately S52 fldUion.
Additionally, present ozone control cost
estimates amount to S8-10 billion on an
annual basis compared to a continuing
investment of leas man S12 million to
operate PAMS (only O2 percent). PAMS
are designed to ensure mat the most
cost-effective ozone control ttrategies
are devised in implemented and provide
the basis to track their cuccess.
Impact on Small Eotitiaa
The Regulatory flexibility Act
requires that all Federal Agencies
consider the impacts of final regulations
on smaH entities, which are defined to
be small businesses, amail
organizations, and wnalJ governmental.
furUdfetioni (5 U&C. on el «eq.). EPA's
consideration panaant to this Act
indicates that no small entity group
would be attzuficantly •fffp**'* IB an
adverse way by the proposal Therefore.
pursuant to 5 UAC.905(b). the
Administrator certifies that these
proposed amendments would not have a
significant economic impact on a
substantial number of small entities
Other Reviews
Since this revision is classified at
minor, no additional reviews are
required. The proposed revisions to part
58 were submitted to the Office of
Management and Budget IOMB) for
review {under Executive Order 122291).
This is not a ~major" rule under EO.
12291 oecaase it don not meet any of
the criteria defined in the Executive
Order.
Paperwork KedurKnn Act
The Office of Management and Budget
(OMB) has approved the information •
collection requirements for Ambient Air
Quality Networks under the provisions
of the Paperwork Reduction Act 44
U.S.C 3501 e/ «eo. and has assigned
OMB control number 2060-0064. The
information collection requirements in
this proposed rule, which will amend the
Information Collection Request (ICR) for
Ambient Air Quality Networks, have
been submitted for approval to the OMB
under the Paperwork Reduction Act 44
U.S.C. 3501 et «eo. An 1CR has been
prepared by EPA (1CR No. MO08) and a
copy may be obtained from Sandy
Farmer. Information Policy Branch (PM-
223Y): U. S. Environmental Protection
Agency. 401M Street SW, Washington.
DC 20460 or by calling (202) 280-2740.
This proposed rale it estimated to
increase the annual burden of affected
control agencies by 88*40 hours for the
-------
7694 Federal Register / Vol 87. No. 43 / Wednesday. March 4.1992 / Proposed Rulet
first fuD year of operation. This burden
would increase to 287,495 hours in the
fifth year of implementation when all
required sampling is operational; This
estimate includes the time for site
installation, sampler operation, data
reduction, data reporting, and data
analysis.
Send comments regarding the burden
estimate or any other aspect of tills
collection of information, including
suggestions for reducing this burden, to
Chief. Information Policy Branch (PM-
223Y); U. S. Environmental Protection
Agency. 401 M Street SW* Washington.
DC 2046ft and to the Office of
Information and Regulatory Affairs.
Office of Management and Budget
Washington. DC 20503. marked
-Attention: Desk Officer for EPA." The
final rule will respond to any OMB or
public comments on the information
collection requirements contained in *^"'*
proposal
List of Subjects m 40 CFR Part 58
Air pollution control
Intergovernmental relations. Air quality
surveillance and data reporting,
Pollutant standard index. Quality
assurance program. Ambient air quality
monitoring network design and siting.
Dated: January 22. 1992.
William URtllly.
For the reasons set forth in the
Preamble, part 58 of chapter I of title 40
of the Code of Federal Regulations is
proposed to be amended as follows:
PART M-AMBIEMT AIR QUALITY
SURVEILLANCE .
1. Authority citation for 40 part 58 is
revised to read as follows:
Authority: 42 US.C. 7410. 7801(a), 7813. and
7618.
2. Section 58.1 is amended by revising
paragraph (f) and by adding paragraphs
(w). (x). and (y) to read as follows:
188.1 Deflnmona.
• • • • •
(f) NO, means nitrogen dioxide. NO
means nitrogen oxide; NO* means
oxides of nitrogen and is defined as the
sum of the concentrations of NO* and
NO.
(w) PAMS means Photc
Assessment Monitoring Stations.
(x) VOC means volatile organic
compounds.
' (y\ Meteorological measurements
means continuous measurements of
wind speed, wind direction, barometric
pressure, temperature, relative humidity.
and solar radiation.
a. Section 58J is amended by
ndeaignating paragraph (d) as
paragraph (e) and by adding a new
paragraph (d) to read as follows:
(d) This section also acts to establish
• Photochemical Assessment Monitoring
Stations (PAMS) network as a subset of
the State's SLAMS network for the
purpose of enhanced monitoring in
ozone nonattainment areas listed as
serious, severe, or extreme. The PAMS
network will be subject to the data
reporting and monitoring methodology
requirements as contained in subpart E
of this part
4. Section BUS is amended by
revising paragraph (b): redesigns ting
paragraph (c) as paragraph (d); and
adding a new paragraph (c) to read as
follows:
188.19
cludin
(b) For manual methods (e
PM* samplers and PAMS VOC
samplers), at least one 24-hour sample
must be obtained every sixth day except
during periods or seasons exempted by
the Regional Administrator.
(c) For PAMS VOC samplers, samples
must be obtained as specified in section
4.4 of appendixD to this part. PAMS
operating schedules must be included as
part of the network description required
by f 58.40 and must be approved by the
Administrator.
• * • • •
5. Section 58£0 is amended by
revising paragraphs (a) and (c) and
adding paragraph (f) to read as follows:
f58£0 Air quality aurvtttanet: Wan
(a) Provide for the establishment of an
air quality surveillance system that
consists of a network of monitoring
stations designated as State and Local
Air Monitoring Stations (SLAMS) which
measure ambient concentrations of
those pollutants for which standards
have been established in part 50 of this
chapter. SLAMS (including NAMS)
designated as PAMS will also obtain
ambient concentrations of spedated
VOC and NO,, and meteorological
measurements. PAMS may therefore be
located at existing SLAMS or NAMS
sites when appropriate.
• • • • •
(c) Provide for the operation of at
least one SLAMS per criteria pollutant
except Pb during any stage of an air
pollution episode as defined in the plan.
(f) Within 6 months after the effective
date of promulgation or date of
nonattainment designation (whichev
is later). States with ozone ""
nonattainment areas designated as
serious, severe, or extreme shall adopT
and submit a plan revision to the
Administrator. The plan revision will
provide for the establishment and
maintenance of PAMS. Each PAMS site
will provide for the monitoring of
ambient concentrations of criteria
pollutant (O». NOi.J. and non-criteria
pollutant (NO,. NO. and spedated VOC)
as stipulated in section 4£ of appendix
D to this part and meteorological
measurements. The PAMS network is *
part of the SLAMS (indnding NAMS)
network and the plan provisions in
paragraphs (a) through (e) of this section
will apply to the revision.
•ubpartE(|88.40) plsdsslgnat«4as
*jpsftP(|tC8JO,SM1) IBadaalgnatad
ea Subpart 0 (II 8840, 8841}]
8, Subparts E (I S8.40) and F (U 58JO
and &BJ51) are redesigns ted as subparts
T (1 58£0) and C (i 1 58.60 and 5841).
respectively. Subpart E is added to read
as follows:
Subpart E-Fh
MonttorlneSts
t
torn (PAMS)
Stc.
8*40 PAMS network establishment
88.41 PAMS network description.
8M2 PAMS approval
88.43 PAMS methodology.
88.44 PAMS network completion.
58.45 PAMS data sobmittaL
88.46 System •«««
-------
federal Ee^rter / Vol S7. No. 43 / Wednesday. March 4.1992 / Proposed Rtrhs
7695
the States Involved. Network
descriptions shall lie f^T'***^ tb
«be appropriate Regional Office|a).
tenative networks saay a* Mbmitted.
jt they tnusi coolitde • demonstration
oat Ikey satisfy the eaonitarinf, data
eses and fulfill the PAMS morritoriag
objectives described to sections 4.1 and
42 of appendixD to this part. Certain
alternative plans desulbed in section
Oof appendixD to this part most be
•-published intbeTedaral Register.
subjected to p*'m* conunen U and
subsequently approved by the
Administrator. •
(b) For purposes of plan development
and approval AMScsi
(a j The require
apply only to those stations designated
as PAMS by the network description
required by 116.40.
(b) All data shall be submitted to fl>e
Administrator in aorrH^"rn> with ^*
format and for the reporting periods
specified in fS&SS.
(c)The State shall report O,. NO. NOi.
and NO, data within 40 days following
the end of each quarterly reporting
period.
(d) The State ahall report speciated
VOC data and meteorological data
within 6 snonths following the end ol
each quarterly reporting period.
|SL46 «v*ta«J
(a) Any proposed changes to the
PAMS network description will be
evaluated during the annual SLAMS
Network Review specified to 1 5620.
Changes proposed by the State most be
approved by the Administrator. The
State will be allowed 1 year (until the
next annual evaluation} to
the appropriate changes to the PAMS
network.
(b} PAMS network requirements ave
mandatory only for serious, severe, mnd
extreme ozone nottattainnent areas.
When such area is Tedeshjnated to
attainment, the State may revise its
PAMS monitoring program subject to
approval by the Administrator.
7. A new sentence is added before the
last sentence in the first paragraph of
aection 12 of appendix A to read su
follows:
Appendix A— OuaUty t
Requirements for State and Locad Air
Monitoring Stations (SIAMS) •
£2 * • * Quality
VOCand eaeteorotoficaJ
PAMSUcoBtainaviiareiBeaceS.* **
• • • • « t
e. References S,«. and 7. of Appendix
A are redesigns ted as references 8.7.
and B repecfnrery «nd new reference 5 is
added to read as fcfllowr
Refen
•
B. Ttchnica] Guidance for Monitoring
Laboratory. V3. EaviraDBanlal Protection
Affency. RaMarch Triangle f»A.HC.Dnti
May 1991.
a Sections 4-0. U and 5.1 of appendix
C sue redesign* ted as sections 4A 6J.
and 1. respectively (reference S.1
therefore will become reference 1 of
aection 6.0). sections 4A Z and 3 are
added and newly redeslguated Section
U) is revised to read as Iallows:
Appendix C-Anbieat Ak Quality
Methodology
UD JTlOtDCfttOUGOl ACetBaTaTflWIu MOfBtQfHlf
Station* fPAMS)
tu *4stha6jBsedforOkS90nitarii««t
PAMS must be automated reference or
•qdralm •ethod* «s defined in I H.1 of
this chapter.
4J AaelfafldssndfarNOaadNO.
monitoring it PAMS omit be sntoBated
reference or equivalent methods u defined
for NOi in 150.1 of thii chapter.
4J Methods for aeiBwUugical
measurementa and rpetiited VOC
nonhining sre isdnded in the ftadasce
provided is references I. end 9. if slieiuatrre
VOC monitoring methodology, which ii not
included in the guidance. Upropoaed, it miut
be detailed in the network description
required by I Sfi.40 and Aiut be puhliahed in
the Fedexal Ra«kkK. «tb}«ct to public
eoouneat. aadsuhMquently approved by the
tJORffe.
1. Pehon.7}.]. Cddeline TorPsrticulate
Episode MonitoriBS Methods, CEOMET
Technotofiei. fac, Rockvnle. MD. Prepared
for US. £nriromnenti] Protection Afency,
ResearchTittnele Park. NC. EPA Contract
NO. ea-oz-ssM. EPA «so/4-e»-oos. rebmaiy
1963.
i Technical Guidance lor Monitoring
Ozone Precursor Co£a. AiBOsnberic
Research and £xposun Asaeeaoent
Labontorjr. 1LS. EoTiransaental Protection
A«ency. Rne«rch Tru&fle Patk. NC ZTni.
Draft May un.
S. Quahty Aswraaot Headbook for Air
Polktioa Meaaareoent SjraMBs: Vohune IV.
MeteoroleficaJ MMiaraoeati.
EnwonmeBtaJ MoBftoiu{ fiyetana
Laboratory, US. EenrircRunental Protection
Agency, Reaecroh Triangle PtA.WC 77711.
EPA 600/4-
-------
7696 Federal Register / Vol 57. No. 43 / Wednesday. March 4. 1992 / Proposed Rules
i D—Network Design far State
I Local Air Moxdiadnf Stations
(SLAMS), National Air Monitoring
Station (NAMS). sad Photochemical
Asmsmint Mooltodnj Sutions
(PAMS)
11. The seccod sentence of the first
paragraph of Section 1 of Appendix D is
nvistd to read u follows:
I* • •llalsooesafbas criteria for
eWtcrmining the number and location of
National Air Monitoring Stations (MAMS)
•ad Photochemical Asset sment Monitoring
Stations (PAMS). These criteria will also be
wed by EPA IB eratustitg the adequacy of
the SLAMS/NAMS/PAMS networks.* • •
• • • • •
12. Section 4 and section 5 of
appendix D are ndesignated as section
S and section 6, respectively. A new
•action 4 is added to read as follows:
4 Network Design for Phelochemica]
Astettmeni Monitoring Station* (PAMS)
fa order to obtain more comprehensive and
isuiaaantative data on etone air pollution.
the 1990 Clean Air Act Amendments require
fit'tiK** monitoring for ozone (O«)«xides of
nitrogen (NO.), and volatile organic
mnrffl""** (VOC) in ozone nonattaiament
•reas classified at serious, severe, or
ejitrttp* This will be acoompliahed through
the eatabliahment of a network of
photochemical aaaeaament monitoring
stations PAMS}.
4.1 PAMS data nse*-Oata from the
PAMS arc to tended to satisfy aeveral
cuinrid*"* needs related to attainment of the
National Ambient Air Quality Standards
(NAAQS). SIP control strategy development
end evaluation, corroboiation of emissions
tracking, preparation, of trends appraisals,
and exposure assessment
(») NAAQS attainment and control
ttrategy development Ukc SLAMS and
NAMS data, PAMS data will be used for
monitoring ozone exceedances and providing
kaput for attainment/nonanainment
decisions, b addition, PAMS data will help
resolve the roles of transported and locally
emitted ozone precursors in producing an
observed exeeedance and may be utilized to
identify specific sources contributing to
observed exceedanoes and excessive
concentrations of ozone precursors. PAMS
data will also assist in characterizing the
concentrations of ozone and precursors
occurring on days when high ozone levels are
measured and therefore extend the data base
available for future attainment
demonstrations. These demonstrations will
be baaed on photochemical grid modeling
and other approved analytical methods and
wfll provide a basis for prospective mid-
eourae control strategy corrections. PAMS
data will provide (1) information concerning
which areas and episodes to model to
develop appropriate control strategies; (2)
boundary conditions required by the models
to produce quantifiable estimates of needed
emissions reductions; and (3) a means to
evaluate the predictive capability of the
sudds used.
(b) SIP control strategy enhiotion. The
PAMS win provide data for SD> control
strategy evaluation. Long-term PAMS data
will be need to evaluate the eflactiveaaea of
these control strategies. Data could be used
to validate the impact of VOC and NO,
emission reductions on air quality levels for
ozone if retrieved at the end of a time period
during which control measures were
implemented. Additionally, •«"^'*rit
monitoring data will be used to determine in
what portion of the day. the VOC emiaaions
reductions occur. Spedation of measured
VOC data will allow determination of which
organic apedea are moat afiected by the
emisslpT* reductions ***^ aaaiat in developing
cost effective selective VOC redactions and
control strategies, A State or local air
pollution control agency can therefore ensure
that strategies which are implemented in
fteir particular nonattainment area, are those
which are best suited for that area and
•chieve ue greatest VOC end NO, emissions
reductions (and therefore largest impact) at
the least coat
(c) fmfr««if.« tracking. PAMS data wjfl be
used to corroborate the quality of VOC and
NO, emission inventories. Although a perfect
mathematical relationship between emission
inventories end ambient measurements does
not yet exist a qualitative assessment of the
relative contributions of various compounds
to the ambient air could be roughly compared
to current emission inventory estimates to
judge the accuracy of the emission
inventories. In addition, PAMS data which is
gathered year round will allow tracking of
VOC and NO, emission reductions, provide
additional information necessary to
demonstrate Reasonable Further Progress
(RFP) toward the specific reductions required
to achieve the ozone NAAQS, and
corroborate emissions bends analyses. While
the regulatory assessments of progress will
be made in terms of emission inventory
estimates, the ambient data can provide
independent trends analyses and
ccrroboratfon of these assessments which
either verify or highlight possible errors tat
emissions trends indicated by inventories.
Tfce ambient assessments, using apedated
data, can gage the accuracy of estimated
changes is emissions. Toe speciated data **"
also be used to aasess the quality of the VOC
speciated and NO, emission inventories for
input during photochemical grid modeling
exercises and identify urban air toxic
pollutant problems which deserve closer
scrutiny.
The spedatad VOC data wfll be used to
determine changes in the spedes profile, •
resulting from the emission control program,
ptrticulary those resulting from the
reformulation of fuels,
(d) Trends. Long-term PAMS data will be
used to establish spedatad VOC NO, and
toxic air pollutant trends, and supplement the
Oi trends data base. Multiple statistical
indicators will be tracked, including ozone
and its precursors on the ten days during • •
each year with the highest ozone
concentration, the seasonal means for these
pollutants,aTu^ the f*"*^!! in^f^f ^\
representative locations. •
The more PAMS that are established in
and near nonattainment areas, the more
effective the treads data will become. As the
spatial distribution tnd number of ozone and
ozone precursor monitors improves, trends
analyses will be leas influenced by
instrument or site location anomalies. Th/
requirement that surface meteorological
SBonitoring baestablished at each PAMS.
help maximize the utility of these trends
analyses by comparisons with meteorological
trends, and transport influences. The
aaeteorological data will also help interpret
the ambient air pollution trends.
(e) Expoture assessment. PAMS data will
be used to better characterize ozone and
toxic air pollutant exposure to populations
bvtagm serious, severe, or extreme areas.
Annual mean toxic air pollutant
concentrations will be calculated to
determine the risk to the population
aaaodated with individual VOC spedes in
4J PAMS monitoring objectiret.--UB&.e
the SLAMS and NAMS design criteria which
are pollutant specific, PAMS design criteria
an spedfic to site location. Concurrent
ppmg
NlJaw
ut* of 0*. NO* spedated VOC
and meteorology arc obtained at PAMS.
Design criteria for the PAMS network are
based on selection of an array of aite
locations relative to ozone precursor source
areas and predominant wind directions
associated with high ozone events. Specific
monitoring objectives are assodated with
each location. The overall design should
enable characterization of precursor emission
sources within the area, transport of ozone
and its precursors into and out from the area,
and the photochemical processes related to
•zone nonattainiment as WeO u developing
an initial urban air toxic pollutant data ~
Specific objectives that must be addresae
include assessing ambient trends in O», NC
NO,. NO, VOC and VOC species,
determining spatial and diurnal variability of
O». NO. NOi. NO., and VOC spedes and
j.xMteg changes n the VOC spedea
profiles that occur over time, particularly
those occurring due to the reformulation of
fuels. A maximum of five PAMS sites are
required in an affected nonattainment area
depending on the population of the
Metropolitan Statistical Area/Consolidated
Metropolitan Statistical Area (MSA/CMSA)
or nonattainment area, whichever is larger.
Specific monitoring objectives assodated
with each of these sites result in five distinct
site types.
Type (1) sites are established to
characterize upwind background and
transported ozone and its precursor
concentrations entering the area and will
identify those areas which are subjected to
overwhelming transport Type (1) sites are
located in the predominant upwind direction
from the local area of maximum precursor
emissions during the ozone season and at a
distance sufficient to ensure urban scale
measurements are obtained as defined
elsewhere in this Appendix, Typically, the (1)
sites wfll be located 10-M miles in the
predominant upwind direction from the dty
nmita or fringe of the urbanized area. Data
measured at site type (1) will be used
principally for the following purposes:
-------
Federal Register / Vol. 87. No. 43 / Wednesday. March 4.1992 / Proposed Rules
7697
•• Future development and evaluation of
control etntegiea,
~ Identification of Booming emissions.
Zombontion of NO, and VOC emission
jjtorie*.
• Establishment of boundary eondltiou for
future photochemical grid mortfling and Bid-
come control strategy changes. ••
• An»ly»i» of pollutant trend*.
Type (2) *itM an established to monitor
the magnitude mnd type of precursor
omissions in the ana where maximum
~ tnitM'^t an expeStedto impact and art
Ideally suited for the monitorial of urban air
toxic pollutant*. Type (2) altet an located
Immediately downwind of the ana of
maximum precursor eolation* and are
typically placed near the downwind
boundary of the central business diatrict to
•mure neighborhood acale measurements are
obtained. Data mearund at aite type (2) will
be aaed principally for the following
purposes?
• Development and evaluation of imminent
and futon control strategies,
• Corrobontion of NO. and VOC emi**ion
Inventories.
• ABgumentation of RFP tracking.
• Verification of photochemical grid model
performance*
• Chancterisation of ozone and toxic air
pollutant exposure* (maTiimim aite for toxic
omissions impact),
• Analysis of pollutant trend*, particularly
toxic air pollutants and annual ambient
spedated VOC trend* to compare with trend*
to annual VOC cmiaaion estima let,
• Determination of attainment with the
NAAQS for NO, and 0,
*ype (3) aitet monitor change* in precursor
sentrations and ratio* downwind of the
. Type (J) etna should be
located in an intermadiatt position between
to an* of maximum precursor emissions
and the downwind area whan maximum
uld be expected to
*na
eighborhood scale
it* are
obtained (between alias (2) and (4)).
Typically, type (3) aites an 10-20 miles from
the central business district or at the triage of
the urbanised ana to the predominant
•own wind direction during the tTTtntf season*
Data measured at aite type (3) will be used
principally for the following purposes:
• Determination of attainment with the
NAAQS, for NO, and O. (this site may
coincide with an exi*ting maximum NO,
NAMS monitoring site).
• Measurement of transport and reactivity
• Verification of photochemical grid model
• Charetteriration of air pollutant
• Conobontion of NO, and VOC emission
tnven tones.
• Augmentation of RFP tracking.
• Analysis of pollutant trends.
Type (4) and (S) sites are intended to
octuning downwind from the area of
-------
F«d«r«l Regirttr / Vol 57. No. 43 / Wednesday. March 4.1992 / Propoied Rulei
Figure 1 - Isolated Area Network Design
CENTRAL BUSINESS DISTRICT
URBAN/ZED FRINGE
Note: U1 and U2 represent the first and second most
predominant wind direction during the ozone season.
-------
Ftdenl Repjlet / Vol. 17. No. 43 / Wednesday. March 4. 1892 I Hopo»en Kulet
7699
Figure 2 • Multi-Area/Tnnsport Network Design
City Z
TJ2
City Y
CENTRAL
BUSINESS DISTRICT
City X
URBANIZED
FRINGE
m
NotK VI and U2 npnsvrt th§ lint and sicond most
predominant wind direction during tht ozona taason.
-------
7700
Federal Register / Vol 87. No. 43 / Wednesday. March 4.1892 / Propoted Rules
Alternative plans whfchprcpoee different
seduced spatial coverage oast also bt
Bfuposed for appfciwe] by tbe AdmiBistfetor
m Ibt Federal Register. subjected to public
comment and subsequently considered by
tbe Adminiatrator for final approval or
disapproval baaed on tba comments received.
Site location* are submitted ai part of tbe
Mtwork description required by | BMO aad
are subject to approval by tbe Administrator.
O Monitoring |>eri«i^AMS precursor
monitoring will be conducted annually
throughout the month* of June. July and
August (as a Bttuhitimi) when ptiV none
values are expected in each area: however,
precursor monitoring during tbe entire ozone
aeason for the area is preferred. Alternate
precursor monitoring periods may be
submitted for approval a* a part of the PAMS
Mtwork description required by | 88.40.
Changes to tbe PAMS monitoring period must
be identified during the annual SLAMS
Network Review specified to f MJB. PAMS
none monitors must adhere to tbe ozone
monitoring season specified in Section 24 of
this Appendix D.
44 MinfaBum network reqnirementa^-The
minimum required number and type of
monitoring sites and sampling requirements
•re based on the population of tbe affected
MSA/CMSA or nonattainment area
(whichever is larger). The MSA/CMSA basis
for monitoring network requirements was
chosen because it typically is tbe most
representative of the ares which
encompasses tbe emissions sources
contributing to nonsttainmenL Tbe MSA/
CMSA emissions density can also be
effectively and conveniently portrayed by the
surrogate of population. Additionally, a
network which is adequate to characterize
the ambient air of an MSA/CMSA often must
extend beyond the boundaries of such an
area (especially for ozone and its precursor*);
therefore, the use of smaller geographical
•nits (such as counties or nonattainment
areas which are smaller than the MSA/
CMSA) for monitoring network design
purposes is inappropriate. Various sampling
requirements are imposed according to the
size of the area to accommodate the impact
of transport on the smaller MSA's/CMSA's,
to account for tbe spatial variations inherent
in large areas, to satisfy the differing data
needs of large versus small areas due to the
intractability of the ozone nonattainment
problem, and to recognize the potential
economic impact of implementation on State
and local government Population figures
•must reflect the most recent decennial US.
census population report Specific guidance
on determining network requirements is
provided in reference 19. Minimum network
requirement* are outlined below.
tf MSA/
CMSA or
(1)
(2)
Mrwum
VOC
frequency'
Mrwiwrn
atteryde
earnpkna
JMSA/
CMSA or
•00.000 to
ijOOQuOOO
IJDOO.OOO
to
tl)
(1)
B)
O)
W
tl)
(2)
(3)
H)
W
VOC
frequency
1.
Ustargsr.
vd day ana I one
•aWnpto 9i9^f flodh tity OaffviQ Ww MonrtonnQ pmodc
• DoM Xxx» aaneAa. eoerfda/ aaircts*, •wydey
and one 24-hor eampie e»e»y atari day during tie
HMKUIXI penod; D Four e-Aow eawplsa. ewsr/
tirt day dumg tie mcxtortnc eertod; E-^our *•
hoj asffipHa, eoer
Note that for purposes of network
implementation and transition only, priority
has been given to the particular monitoring
sites as follows:
• Site type (2) which provides tbe moat
comprehensive data concerning ozone
precursor emissions and toxic air pollutants.
• Site type (1) which delineates the effect
of incoming precursor emissions aad
concentrations of ozone
• Site type (4) which provides a maximum
ozone measurement and total conversion of
ozone prscursorSi
• Site type (S) which depicts the changes to
concentrations of ozone and precursors as
the pollutants travel across an area, and
• Site type (5) which serves a similar .
purpose as site type (4) to the second moat
predominant wind direction.
44 Transition penod— A variable period
of time is proposed for phasing in the
operation of all required PAMS. Within 1
year after the effective date of promulgation
or redesignation and recUssificaticn of the
area to serious, severe, or extreme ozone
nonattainmenl (whichever to later), a
minimum of one type (2) site must be
operating. Operation of the remaining sites
must at a ardntamm, be phased m over the
subsequent 4 years as outlined below:
eevonaton
Mo. * etas
apsratng
Opra-
(2)
• leelguwl
Note mat given the need to differentiate the
monitoring network requirements due to the
spatial and emissions characteristics of the
various sizes of MSA/CMSA or
•eaattammeat anas, tbe criteria and
priori ti«* given in Section 4.4 were applied.
These criteria and priorities result In
network* of varying proportions, provid
«eaeon*b»e date coverage, and etratT
atonitonng requirements,
44 Me&oroJogica] moaitofiag--^ i
to support monitoring objectives assooaied
with the need for various air quality analyse*
•ad model inputs aad performance
•valuation*, meteorological monitoring at 10
meter* above ground is required at each
PAMS site. Monitoring should begin with ate
establishment m addition, upper air
meteorological monitoring should be infested
•a warranted in areas where such date is not
available. The upper air station may be
located separately from sites (1) through (S).
The location should be representative of nt
upper air date in the nonattamment area,
Upper air meteorological date should be
collected for approximately 10 to 20 key dsyi
per year corresponding to model mput
requirements. Specific guidance on
monitoring methods and siting to provided to
reference 20 and 21.
§ Summary
IS.Tn appendix D references 19
through 23 ire added to aection B to read
u follows;
• Reference*
• • • • •
18. Enhanced Ozone Monitoring Network
Design aad Siting Criteria Guideline
Document Office of Air Quality ~
Standards. US. Environmental f
Agency. Research Triangle Park, NC
May 1991.
JO. Technical Guidance for Monitoring
Ozone Precursor Compounds. Atmospheric
Research and Exposure Assessment
Laboratory. VS. Environmental Protecttea
Agency. Research Triangle Park, NC. Draft
May Ml.
21. Quality Assurance Handbook far Air .
Pollution Measurement Systems: Volume IV.
Meteor ologlcsl Measurements.
Environmental Monitoring Systems
Laboratory, US. Environmental Protection
Agency. Research Triangle Park. NC 27711.
EPA 600/4-82-Oeo. February 1983.
22. Criteria for Assessing the RoJe of
Transported Ozone/Precursors in Oaooe
Non-Attainment Areas. Office of Air Quafcfir
Planning and Standard*. US. EnvirenmeBts)
Protection Agency. Research Triangle Park.
NC. EPA-450/4-91-015. May 1991.
23. Guidelines for Regulatory ApplicatiOB
of the Urban Airshed Model Office of Air
Quality Planning and Standards. US.
. Environmental Protection Agency. Reseera
Triangle Park. NC Draft March 1991.
14. Appendix E is amended by addinj
a new paragraph after the first
paragraph in section 9. by redesignalmf
•eetioni 10.11. and 12 ai lectioni 11. tt
and 13. redesigns ting Table 5 as Table B.
adding a new Table &, adding • new
section 10, amending the iwi aenteMg|
-------
federal Regiiter / Vol. 87. No. 43 / Wedne»day. March 4.1992 / Proposed Rules 7701
newly redeaignated aecUon 11 to add
reference to PAMS. and amending
newly redesignated section 12 by adding
an entry to the bottom of Table 6 for
VOC to read as follows: -
aba Siting Criteria for
Appt
Ambient Air Quality Monitoring
For VOCmoaHoring it those SLAMS
designsted «i PAMS, FEP teflon te
vnsceeptsble at the probe material because
of VOC adsorption and deaorption reaction*
en tfac FEP teflon. Borosilicate glaas, stainless
iteeL or iU equivalent are the acceptable
probe materials for VOC and aldehyde
sampling. Cart must be taken to ensure that
the sample reitdrncf ^*ffi* ia 20 seconds or
less.
JO fix
CfH
nt Monitoring
Station* (PAMS)
IU Horizontal and Vertical Probe
Placement.—The height of the probe inlet
mutt be located 3 to IS meten above ground
level This range provides a practical
compromise for finding soluble sites for the
multi-pollutant PAMS. The probe mlet must
also be located more than 1 meter vertically
or borizonteDy away from any supporting
structure.
102 Spacing From ObtOvctiont.—The
probe must be located away from obstacles
tad buildings such that the difaret between
the obstacles and the probe inlet is at least
twice the height that the obstacle protrude*
above the sampler. Tberesntt be
enrestrieted airflow m an art of at least THT
around the probe mlet and the predominant
wind direction far the season of grsatest
pollutant concentration must be included in
the 270* are. If tfec probe is located on the
aide of the building. leO* ctaerenee is
raanired.
103 Spacing From Roodt*-H\»
important m ue probe aitiag proosas to
minimize destructive interferences from
sources of nitrogen oxide (NO) since NO
readily reacts with osane. Table » below
provides the required«"'"«»"" separation
distance* between roadways and PAMS
(excluding upper air measuring stations):
TABLE 5.—SEPARATION DISTANCE
BETWEEN PAMS AND ROADWAYS
Udotofi
leettcian*:
VaNdesparaay:
40.000
70,000.
> 110400.
MHmum
CO
100
>«so
ahoutib*
files type* (1), (4) and (5) are intended to
be regionally representative and should not
be nndury tnllaeMed by an NO, source from
a nearby roadway. Similarly, a nearby
roadway should not act as a Iocs! atone stale
for site types 12) end (3).
10.4 Spacing From Tnet.— Tree* can
provide surfaces for adsotption and/or
reactions to occur and can obstruct nonncl
wind flow pattern*. To minimize these effect*
at PAMS. the probe tnlel should be plsced at
least 20 meten from the drip line of trees.
Since the scavenging effect of bees is greater
for ozone thsn for the other criteris
pollutants, strong consideration of this effect
must be given in locating the PAMS probe
mlet to avoid this problem. Therefore, the
samplers mo*l be at least 10 meten from the
drip line of trees the! are located between the
urban dry core area and the sampler along
the predominant summer daytime wind
direction.
104 MetfonJagicaJ Mtoturemenu —
The 10-meler meteorological lower at each
PAMS she should be located so thst
measurements can be obtained that are not
immediately influenced by surrounding
structure* and trees. It is important thst the
meteorological data reflect the origins of. end
the conditions within, the air m**t containing
the pollutants collected at the probe. Specific
guidance on siting of meteorological towers is
provided in reference* 31 and 32.
11 WahtrPrmvuiont
• • « • •
For those SLAMS also designated si
NAMS or PAMS. the request will be
forwarded to the Administrator.
Oitomion and Summary
TABLE 6.— SUMMARY or PROBE SITING CRTTERIA
MUsrt
• • •
MTV
Scale
lUighi
eoov*
UXOT
3-1 S
bean
aupponni
IM
Vertcal
•v«
Be Sfloffl
? struct**,
Mr*
HortaonW*
^i
•
uhar spacsnQ creans
f
1 ftfwuid CM >20 Mem froni ew if \ ' ' i emt iruet to 10 nwm ewn e^e gi^sjn vtwn si*
••»(*) act as an ebsaucton.
2. Osiano* SJOBI probe Met ID ons&sds nx* b* at leeat S**es«» tm&t fw obstacle probudes
ecove the real probs.
3. Must hevc unestriosd er te* In an ere of at least 270* around t» arab* Met end the
e» 270* are. I snb* fceend en aw ads o) a eOMng wresuued er Sxw HUM be 160*.
4. Spaong torn loadvay* (aee Tab* 5).
on moAop. t«s
Octane* Jt In (•tartno* to i
lonewioo/.
e>
15. Reference* number 31 and 32 are
added to newly redesignated section 13
of appendix E to read as follows:
J3 References
S3. Technical Guidance for Monitoring
Ozone Precursor Compounds. Atmospheric
Rsiesrcb and Exposure As*e**ment
Laboratory. U.S. Environmental Protection
Agency. Research Triangle Pa*. NCDraft
May 1981.
82. Quality Assurance Handbook for Air
Pollution Measurement Systems: Volume IV.
Meteorological Measurements.
Environmental Monitoring Systems
Laboratory. U.S. Environmental Protection
Agency. Research Triangle Perk, NC 27711.
EPA 600/4-12460. Febnary 1083.
fFR Doc. 82-2535 Piled W-92: MS am]
40 CFB Part 180
PUN 2070 AC-11
Aettie Acid; Tofannet Exemption
* ^
AOXNCT: Environmental Protection
Agency (EPA).
ACTION; Proposed rule. _
•UttMAirr.Thit document proposes that
an exemption from the requirement of a
-------
Friday
February 12, 1993
Part II
Environmental
Protection Agency
40 CFR Part 58
Ambient Air Quality Surveillance; Final
Rule
-------
8452 Federal Register / VoL 88. No. 28 / Friday. February 12,1993 / Rules' and Regulations
ENVIRONMENTAL PROTECTION
AGENCY
40CFRPwt58
«H20$0-AD1«
Ambient Air Quality SurvaJUanc*
AGENCY: Environmental Protection
Agency CEPA).
ACTON; Final rule. _
sjuuuumThis final rule mists the .
ambient air quality surveillance
regulations to include provisions for the
enhanced monitoring of ozone and its
precursors Including ooddw of nitrogen.
volatile organic compounds (including
carbonyls) and meteonlogical
parameters. These revisions satisfy the
requirements of title L section 182 of the
1990 Clean Air Act Amendments. These
revisions require States to establish
photochemical assessment monitoring
stations (PAMS) as part of their State
Implementation Plan (SIP) monitoring
network in ozone nonattainment areas
classified as serious, severe, or extreme.
Included in these revisions an
TpttitTmitn criteria for network design,
monitor siting, monitoring methods,
operating schedules, quality assurance,
and data submittaL
EFFECTIVE DATE: These regulations take
effect on February 12, 1993.
ADDRESSES: Docket Statement: All
comments received relative to this rule
have been placed in Docket No. A-91-
22, located in the Central Docket
Section. Room M1500 (First Floor,
Waterside Mall), U.S. Environmental
Protection Agency. 401 M Street SW.,
Washington. DC 20460. This docket is
available for public inspection and
copying from 8:30-12 a.m. and from
1:30-3:30 p.m.. Monday through Friday.
A reasonable fee may be charged for
copying.
FOR FURTHER MFORUATMN CONTACT? Geri
Dorosz-Stargardt, Technical Support
Division (MD-14), Office of Air Quality
Planning and Standards, US.
Environmental Protection Agency,
•Research Triangle Park, NC 27711.
phone: (919) 541-5492. •'
SUmaiEHTARYWFORMATJON:
Background
Section ll6(a)(2)(Q of the dean Air
Act requires ambient air quality
monitoring for purposes of the State
Implementation Plan (SIP) and reporting
of the data to EPA. Uniform criteria for
I measuring air quality and provisions for
the reporting 01 a daily air pollution
index are required by section 319 of the
Act To satisfy these requirements, on-
May 10.1979 (44 FR 27571). EPA
established 40 CFR part 58 which
provided detailed requirements for air
quality surveillance and data reporting
for all the pollutants except lead for
which ambient sir quality standards
(criteria pollutants) cad been . .
established. On September 3,1981 (46
FR 44164) similar rules were
promulgated for lead and on July 1,
1987 (52 FR 24740) for particulate
matter (PMiJ. • ' *
' On March 4.1992, these rules were
proposed in'the Federal Register as
amendments to 40 CFR part 58. These
regulations address the
1 air quality trends, and make
attainment/nejjattainment decisions. In
addition, the PAMS will provide a more
definitive database for evaluating
• photochemical model performance.
especially for future control strategy
mid-course corrections as part of the
frtriHnuJng air quality management
process. The data will be particularly
useful to States in ensuring the
implementation of the most cost*
effective regulatory controls.
In the process of developing these
regulations, EPA sought the ' '
requirements for the monitoring of
spedated volatile organic compounds
(VOQ. oxides of nitrogen (NOx), snd
meteorological parameters as well as
additional ambient air monitoring for
ozone (0>). Title I. section 182 of the-
1990 Clean Air Act Amendments
requires EPA to promulgate regulations
for the enhanced monitoring of 0] and
its precursors and for the affected States
to incorporate the requirements as apart
of their State Implementation Plans.
Also, section 184(d) requires that the
best available air quality monitoring and
modeling techniques be used in making
determinations concerning the
contribution of sources in one area to
concentrations of Oj in another area
which is a nonattainment area for
ozone. Additionally, these enhanced
ozone and ozone precursor monitoring
rules adhere to the fundamental
recommendations, regarding ambient
monitoring, of the National Academy of
Sciences (NAS) in the report entitled,
Rethinking the Ozone Problem in Urban
and Regional Air Pollution, which was
prepared pursuant to section 185B of
the 1990 Clean Air Act Amendments. In
that report, the NAS noted the need for
additional feedback mechanisms for
evaluating the effectiveness of ozone
control strategies.
The intent of these enhanced ozone
and ozone precursor monitoring
regulations is to require air pollution
control agendes to obtain an air quality
database that will assist in evaluating,
tracking the progress of. and, if
necessary, refining control strategies for
attaining the ozone National Ambient
Air Quality Staadards.(NAAQS).
Photochemical assessment monitoring
stations (PAMS) will be established to
collect ambient concentrations of ozone
(Oj). oxides of nitrogen (NOx). nitrogen
dioxide [NOJ. nitrogen oxide (NO), and
spedated VOC including carbonyls, and
meteorological data to better . .
characterize the nature and extent of the-
Oj problem, aid in tracking VOC and •'
NOx emission inventory reductions;
of the Standing Air Monitoring Work
Group (SAMWG). SAMWG was
established by EPA in 1975 to assist in
developing air monitoring strategies.
problems, and improving overall
national monitoring operations.
SAMWG members represent State and
local air pollution control agendas and
EPA program and Regional Offices.
SAMWG members were active partners
in developing and reviewing the 1979
part 58 nuemaking package which
formally established the existing
framework of the ambient air quality
surveillance and data reporting
regulations. The group also played a
prominent role in all subsequent
revisions to part 58.
Public Comments
The object of Federal Register
proposals is to allow comments on new
regulations prior to their promulgation,
thereby providing an opportunity for the
public to participate in the rulemaking
process. On March 4, 1992, these rules
were proposed in the Federal Register
with a 30-day comment period. In
response to requests from the public,
especially from the regulated •
community of State and local air
pollution control agendas, on April 3.
1992, EPA extended the public
comment period on the enhanced Oj
and Os precursor monitoring regulations-
until May 4. 1992.
EPA received 40 written comment •
letters on the proposal of March 4, 1992.
All of the written comments submitted
to EPA are contained in EP A's Docket
No. A-91-22. Of the letters reviewed. 16
come from State agendes, 10 from
industry. 2 from institutes and
universities, 6 from State/local
. associations, 5 from local agendes. and
1 from a federal agency. A list of all
commenters writing to the public docket
is provided in Docket A-91-22.
The following discussion covers the
substantive comments. A detailed
discussion of the basic concepts of the
regulations can be found in the
preamble to the March 4. 1992 proposal
-------
A Genera/ Comments
The comments discussed under this
heeding were not specific to any rule or
appendix, but wen general comments
on some aspect of the proposed
* monitoring program.
One commenter noted that the
Muskegon nonattainment ana had been
reclassified from a serious to a moderate
classification and therefore should be
' withdrawn from consideration in the
fi««l rules. Since this area and the
Sbeyboygan area have been ndassified
and are no longer serious, •even, or*
extreme Oj nonattaixunent areas, EPA
• agrees that these rules would not apply
to either Muskegon or Sheyboygan.
Accordingly, Muskegonr and
Sheyboygan are not included in EPA's
estimated requirements for PAMS. Note
that applicability of these enhanced Oj
and Oj precursor monitoring rules is
determined by the classification of the
Oj nonattainment area and not by the
bet that an area is listed specifically in
or omitted from this notice.
One commenter observed that
Ventura County, California, was created
as a separate Oj nonattainment area
from the Los Angeles Consolidated
Metropolitan Statistical Area (CMSA)
and requested clarification as to this
area's status with regard to thp •
enhanced Oj and Oj precursor . .
monitoring requirements. EPA notes
that since Ventura County was classified
as a seven Oj nonattainment ana, the
county is subject to these rules.
One commenter agreed with the basic
concepts proposed on March 4, but
suggested that the final promulgation
not add additional requirements. A
second commenter expnssed a similar
opinion that EPA not kill the effort with
additional mandates unless the Agency
is willing to proceed slowly and absorb
the costs. EPA evaluated the substantive
comments on their individual and
collective merits and has incorporated a
number of modifications to the original
proposal Only those additional
activities addressed, in the March 4
proposal, wen added. Regarding
resources, EPA has demonstrated its
willingness to participate in the funding
process; a further discussion of nsource
needs and funding follows under
Resources and Costs.
One commenter indicated that
although the regulation is reasonably
specific concerning network design, it
lacks specificity for the submittal of SIP
revisions. Given the complexity of the
rules, EPA believed that it was
necessary to provide extensive detail
concerning the design of the new FAMS
networks. The wide variability, inherent
in SIPs, precludes such specificity when
requiring SIP revisions. Each currently-
approved SIP contains appropriate
provisions for establishing and
operating the network of State and Local
Air Monitoring Stations (SLAMS)
including those stations identified as
National Air Monitoring Stations
(NAMS). The SIPs generally provide '
thatSLAMS and NAMS will measure ..
ambient concentntions of those criteria
pollutants for which standards have •
been established in 40 CFR part 50. The
SIP revisions submitted to comply with
these revisions to 40-CFR part 5830 will
. -additionally provide'for the monitoring .
of ambient concentntions of non-
criteria pollutants such as speciated
VOC including carbonyls. NO and NO*.
as well as meteorological parameters in .
the same manner that the criteria
pollutants wen addressed. Note that the
reference to aldehydes has been
changed to carbonyls to man accurately
nfiect the requirements of the technical
assistance document (Reference 2 of
Appendix C). The guidance currently
stipulates sampling and analysis for *h*
following carbonyls: Formaldehyde, •
acetaldehyde^and acetone.
The same commenter contends that
the rules indicate virtually no need for
new O) sites and a modest expansion of
the NO] monitoring effort and believes
that these conclusions an based in gnat
part on the assumption that PAMS
monitors could be located at existing Oj
and/or NOj monitoring sites. The
commenter was concerned that if this
assumption is in error, the expansion
needs of the networks may be
underestimated. In fact, EPA did assume
that some of the PAMS stations could be
located at existing SLAMS or NAMS
sites. For example, the PAMS type (3)
site is located at the downwind site
when maximum Oj concentrations an
expected to occur. This description
corresponds to the category (a) NAMS
Oj site specified in appendix D of 40
CFR part 58. Such a site is required for
all urban anas having a population of
greater than 200.000. Because most of
the nonattainment anas classified as
seven, serious, or extreme for Oj an
located in urbanized areas which exceed
this population threshold, each ana
would currently be expected to b»
operating a category (a) NAMS Oj lite.
Assuming that these sites an properly
located, it would thenfon be common •
to find the PAMS type (3) site and the
NAMS* category (a) site coincident In
siting NAMS NO] sites in urban anas
with populations greater than 1.000.000,
the monitoring sites could potentially be
collocated with one of the two PAMS
type (2) sites. Generally, EPA believes
that some collocation of PAMS and
SLAMS/NAMS aitee is highly likely. In
addition, in anas when a substantial
Dumber of SLAMS Oj and NOj sites
currently exist, it is not unreasonable,
for purposes of estimating costs, to
that the State air pollution
control agency will nlocate ambient
monitors and appurtenances nther than
purchase only new moniton to develop
the PAMS network. For example, in one
nonattainment area. 26 Oj moniton and
15 NOa monitors wen in operation
during the 1991 fiscal year compared to
a PAMS requirement of only 5 sites,
some of which could obviously be
located coincident with existing sites. In
nsponse to the concerns expnssed by .
the commenters, however. EPA has
adjusted Us cost estimates to nflect the
collocation of PAMS with existing '.
moniton at only two sites in a five-site
network. °
One commenter was doubtful that the
potential benefits to be received from
the program would be Justified given the
estimated implementation costs and the
unaddnssed technical questions. A
slower, men cautious schedule was
recommended. In designing the
requirements for the PAMS network,
EPA considered the potential benefits of
the data and weighed those against the
projected costs and uncertainties. In
light of the Agency's estimate for futun
Oj control costs of $8 to 12 billion per
year (Ozone Nonattainment Analysis—
Clean Air Amendments of 1990. Office
of Air Quality Planning and Standards,
U.S. Environmental Protection Agency,
Research Triangle Park. NC 27711.
DRAFT. September 1991). the potential
return in benefits for a cost of $5 to 12
million per year provides an
exceptionally prudent Investment.
Nevertheless, the Agency made every
effort to craft a mfahnnm requirement
which would in gnat part satisfy a •
number of important objectives, yet not
become a financial burden either upon
the air pollution control agencies or the
States (note further discussions of
financial burden in *hi« preamble under
Resources and Costs). Modifications to
the proposed five-year transitional
period address the commenter's concern
and should provide ample flexibility.
This commenter also indicated that
computer model sensitivity analyses
should be conducted for aU parameters
to be measured and that the rule should
acknowledge the need for measuring
pollutant concentntions aloft. EPA
notes that although the PAMS network
design is not the direct result of
sensitivity, analyses for each affected
area, it nevertheless reflects the current
expectations of the photochemical
models. Heretofore, the national
program has not had the benefit of the
-------
8454 Federal Regfcter J Vol 58.- No. 28 / Friday, February 12.1993 / Role* and Regulations
•vdUrfBty ofennpidiaosh* Q)
. precursor dote asa tool to evaluate,
calibrate, or otherwise adjust tad
conduct reanry tlietxa on the opeiaboD
of tha Urban Airshed Model fUAM).
EPA views the PAMS network* u •
vital stop rorwan
Y1IU KDV Jianoni *u wwmyIB mem m
grid model application* ad oootre
Stialegy UMMU18OU UIQ XV&UBUieillJ.
Ah&agh the sampling of pollutant
comautntions aloft-may abo be a '
highly valuable activity. EPA does not
agree that sodi activities should be
inauded in the specification* far • .
ynmttriKiikk nxitine measurement*, inese
rule*, however, do not preclude • Stale
agency from proposing such pollutant
measurements (made either on i routine
basis or at periodic intervals during
men intensive sampling efforts), •
iadnding them in their EPA-approved
comprehensive network description,
and subsequently utilizing Clean Air
Act Section 105 Grant monies, in pert.
to support tbeee innnitunngeffuits. In.
fact, EPA has encouraged affected air
pollution control agencies to view these
rules as a base upon which to tailor and
expand the precursor monitoring
program to meet the States' indiYidoal
needs. Monitoring pollutant '
concentrations aloft has therefore been
assigned to the category of desirable, yet
optional acthrities. • . .
Two commenters suggested that EPA
adjust its program to reflect information
from previous field studies (Le., base the-
rules on actual field-verified techniques
rather than on good technical
assumptions alone). EPA recognizes the •
value of quality measurements and
field-proven techniques. In fact, the
fundamental tenets of the propose! were
based on the demonstration of emerging
measurement technobgy.and data
obtained during a number of field
studies, particularly the Atlanta Q>
Precursor Study conducted during the
summer of 1990 (Reference 32 of
Appendix D). Although technical
assumptions were necessary to some
extent due to the emerging nature and
complexity of the measurement
technology, EPA believes that these
assumptions were warranted
considering the need for more definitive
s^r oata to oevelop unproved
compounds during multiple hours of •
the day wiD create a very large database.
Consequently, the Agency i* proceeding
torevise the capabilities ofit*
'computer-based Aerometric Informstion-
and Retrieval System (AIRS) to allow
these data to be securely stored, :
retrieved, and adequately analyzed via
the existing national system. The AIRS
Is cnrrenthr utifized by aH States for the
storage and/or retrieval of NAMS and
SLAMS data. The data required to be
submitted by §58.45 will be deposited .
is this same databank. Further
information on AIRS and it* capabilities
may be obtained by contacting any of
the 10 EPA Regional Office* or the
Natiwatl Air Data Branch, Technical
'Support Division (MD-14), Office of Air
Quality Planning and Standard*. U.S.
Environmental Protection Agency,
Research Triangle Park. North Carolina
27711. The Agency i* also revising its
technical assistance document
(Reference 2 of Appendix Q to include
additional guidance regarding the
processing of data at tb* State and local
agency level. Lew generic procedures for
data processing and validation.
In a related topic, another commeDter
estimated that the proposed rules will.
result in a workload increase of 60
percent, predominantly in data,
reporting burden. This comman,ter
advocates the developmaat by EPA oi
expert software for use with the VOC
analyzers. The Agency note* this
concern and has therefore MTtAg^aVtm
the aforesaid nKKiificatiflrn to the AIRS
system and to Us ted:
document.
Oj coutiul strategies. Slates are
encouraged to take rail advantage of
experience and data obtained in past
studies and routine monitoring efforts,
and use that experrencB to refine and
focus their individual PAMS network
designs.
One commenter noted that the
requirements for jntensrw osiry
sampling win engender major database
management activities. EPA agrees that
vie measurement ox numerous?
sistance
these considerations into the final rare*.
Specific recnmmapffitions made by this
commenter an addressed elsewhere in
thi* preamble.
Two connneoters expressed mru1 na i>
that EPA had not adequately addressed
critical issue* relating to the role of NOx
in the photodiemiealprece**. These
coounenters assert that EPA rpwt
ensure that th* data gathered will be
appropriaU for NOx sensitivity
modeling and will facilitate
»u «!*•>< TT»n«Kni\ *nA \mftf\ of various
Mure** of NOx. EPA is concerned about
thejunction of nitroganc
in> O> formation, particularly in
southeastern United Slates. Special
studies an being initiated as Joint
projects with EPA In the Southeast
employing research monitoring
concept* to derive the moct affective
strategies for NOx monitoring and
control. These integrated projects an
expected to have a significant imped on
future O> control *^**'""« Modeling
predictions of various nitrogen species
(e.g., total reactive oxides of nitrogen
(NO,). NOx. NO. NOi, peroxyacatyi
nitrate (PAN), and nitric acid (HNOJ.
etc) can then be examined by the •
research community to determine th* •
performance of chemical mecT
One commentar was concerned that a
bias in Oj measurements often occurs.
on design-value days, in part due to
differences in measurement techniques-
Wniie tna Agency cannot substantiate a
particular problem occurring on O>
design value days, the Agency notes that
data which is gathered in accordanc*
with 40 CFR part 58 and tha quality
assurance procedures of appendix A, an
acceptable for use in computing design
values and for conducting attainment/
nonattainmeni determinations.
The same commenter believes that
EPA should examine the following four •
areas more carefully before: finalizing
the rule: (1) Tha linking of monitoring
specifications with monitoring
objectives, (2) the consequences for as
urban area adhering to the Tmnfynirr^
. stipulated monitoring requirements, (3)
the rationale for recommended
averaging times, and frequencies for
sampling of VOC and (4) the rationale
for air quality and meteorological siting
requirements.The Agency considered
these suggestions, recognized their
value, and subsequeutry imuijjuiated
dants. This wiH
help ensun that chemistry, leading to •
Cb formation in urban and rural areas,
is properly characterized and may kad
tO fUTthaT p»»«faKT<»tmprfraT>^^f^ny .
EPA ha* datazmuiBd *h*t it i* prematun
to require such eflorts in a routinely .
operated network, but encourages and
recommends that States consider the
option of deploying more sensitive NOx
instruments when establishing future
PAMS sites. For the near term, the
current. NOx monitoring methodology
(Federal Reference Method for NOJ win
be acceptable. The Agency will develop
future guidance for more sensitive and
definitive NOx methods, and
measurements.
One commenter expressed concern
that many technical, logistical, and
fiscal issues remain to be reserved to
ensure tha success of the PAMS
monitoring program. This respondent
asserted that its comments, analyses and
suggestions were, for the most part.
ignored. On the contrary, however, the
Agency has considered all comments
and suggestions received by the Agency
This commenter*9 suggestions, bemg .
rather comprehensive, complicated, and
unique, received careful scrutiny by
EPA. In a number of cases, these
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*C«*w.<_k
Voi'SB. No. 28 / Friday, February 12, 1993 / Rules and Regulations 8455
.suggestions were incorporated both ID
Ihe previous dnJt proposals as well as
in Ibis final promulgation, In bet, the
final regulation has been revised to
allow alternative monitoring schemes
in section 4 of appendix D, ia part in
direct response to rtd* f*?TnTifTi>*T The
bet that EPA did not radically change
its appioadi to identically match the
suggestions of this particular respondent
in BO way ^"*fam»M thf ^porta^r* of
the suggestions, nor does it equate to
ignoring t^f **^'ftrnTni>r^ftti"nf Each
recommendation has been
elsewhere in this preamble.
S. Public Comments—.Resource* one*
Costs- ' •
Several commenten ware concerned
with the statement in the proposal
which says that the primary
responsibility for fmplffintfftirig tht
program with its associated costs rests
.with the States. Hie commenters feel
strongly that EPA needs to make a much
•*B n^ ^
proeram to ensure its success. EPA
oerstands that this unique program
Two commenten expressed strong
objections to tin use of nprogramming
of existing fundsto support the PAMS
program. As previously discussed, EPA
has prorided substantial section 105 '
Grant funds to support both FY-92 and
FY-93 monitoring activities. The
Agency expects to continue to provide
^jptfifMt topport through section 105
grants in subsequent years.
will require a strong federal presence
both as a partner in system management
and in providing appropriate technical
and financial assistance. EPA h»«
provided funds during FY-92 to initiate
monitoring for air toxics in 10 areas.
These sites, which are generally located
consistent with the requirements for
PAMS type (2) sites, will be continued
as part of the PAMS program in 1993.
Additionally, the Agency has earmarked
approximately S4.000.000 in §105 Grant
xoonies for distribution to the States, in
FY-93 and has provided technical '
support via contract and direct EPA ,
involvement and participation. Overall,
EPA will have borne the burden of
financing a significant portion of the
costs of initiating sampling during FY-
92 and FY-93. The Agency has plans for
. subsequent years which will ensure a
major ffa«tiflx«a fo; the fulfillment of the ^M*
objectives.
•Five commenten expressed concern
that EPA's estimates for the costs of
implementing this monitoring program
were too low. EPA's costs estimates ^^
were prepared from data gathered ^B
during 1990 and 1991, and thenfon an ^^
generally expnssed as 1990 and 1991
dollar*. It is not surprising that
estimate* prepared in 1992 should be
somewhat higher. In many cases it was
difficult to compare estimates prepared
by the commenten, since they often
utilized different wage scales, different
quoted equipment costs, and different
operating scenarios. In most cases,
. recognizing that these figures an only
estimates of the true implementation
costs, the Agency believes that its
original estimates reflected a reasonable
appraisal of the resources needed to
implement a minimally-acceptable
program at that time. EPA has, however,
incorporated many of the suggestions of
the commenters far computing costs and
has compiled an updated version of its
cost estimates. These estimates reflect
the changes in the boundaries of several
nonattainment areas, changes in
classification of othen, higher
equipment and labor costs, revised
sampling frequencies, additional
allocations for data processing; upper
air measurements, 63 and NOx
moniton, security concerns, and larger
monitoring shelters. For information,
the Agency's updated cost estimates for
each affected ana may be found in
Table 1.
-------
8456 Federal lagiaig / VbL 58. Ko>. 28 / Friday, February 12,1993./ Rules and Regulations
•;•• . TABLE 1.—ESIMWHJ REOUIREUEXTS FOR PAMS
Penan
BOOJOa,
BPwaTX.
900.000 tB
. ijnrcuoft
Vnn County, CA.
UOOajGOto
SeewnenkxCA.
AflaflOuGA
Cttego-Gaiy-lake Courty (BJ. BVWM
QiMttr ConMCteK. CT.
HOMIOB C*».«ten OruemiK to iwtlei reflect a balance
of the needs of the data users. .
One commenter alleged that EPA
committed to provide full funding far
all efforts required under the
most of the wuiit Oj epuodo. EPA
furtbar.LuHBiBi.
PA goes
wutluu
4<3 of appeooxx D, f^i"im utst attmuto
precursor monitoring parfodi may bit
•ubmittad for approval u • part of tha
PAMS network dttoription. lois action,
therefore, aOows a Stata to propoee a.
monitoring season which will best meet
Its particular needs as long »s the
proposal will capture those wont Q»
events. The length of any particular
PAMS monitoring season may therefore
vary from area to i
Program and further alleged that EPA
committed that ft would not require.
'state or local agencies to peifmm the
specified monitoring if fall funding of
all materials, equipment and labor is not
provided by EPA. Teat commenter also
requested that EPA dearly articulate
this assertion in the rules promulgated
today. Another commenter asserts that
EPA indicated this Intent m the
proposed regulation, ft is common
practice far State agendas to share .
substantially la the costs of
implementing >TU^ operating aD air
pollution monitoring and control •
program*. la fact, the Qaan Air Act
Amendments of 1990. section 802.
revise section 105 of the Act to require.
that States provide aa overall mini
muni
of 40pexcsnt of the costs of
implementing programs for the
prevention and control of airpoDun'on
or implementation of national primary
and secondary ambient air quality
standards. EPA is therefore unable to
commit that ft would provide 100
percent of the funding for such a
substantial yfugiam. Evidently, some
confusion has resulted from EPA's
attempts to provide TninriTniiTn monetary
support for the implementation of the
•nh«Ti>-ad QJ and Oj precursor
monitoring regulations.
One commenter believed that
although the proposed funding far this
program may oe adequate to encompass
capital expenses, provisions, fax skilled
labor costs will be a problem. EPA nottt
that provisions for the hiring of highly
skilled chemists and statisticians wen
included in its cost estimates mn^
planning for PAMS. Further, these
estimates were reviewed by the Agency
and revised upward to reflect changet in
the national labor burden and the
expressed needs of the Sate and local
air pollution, control agencies.
One commentar believed that the _
comprehensive sampling un^ analysis
schedule stipulated by the proposed
rules is the primary contributor to the
high costs of the program. A» previously
stated. EPA is committed to only
requiring a mi'"'*"""" program which
will comprise the best technical-fiscal
b«Tflnra to satisfy a variety of data
objectives. Since the proposal was
-------
Federal EagJJtar / Vol.56. No. 28 / Friday. February 12. 1&S3 > Xtaes ana
published, EPA has refined Us sampling
and analysis ssqmnments to better
laflaet^haata needs.
B~DQ
XeduCS *^** COStS fff JTTmlai i i««i
several commsnten have recommended,
totally di£brent strategies that they.
believe trill also achieve tha data ."
objectives of the PAMS program. The
Agency has nviewed time different
proposal* and believes that thay do act
Gou&te
considered as alternative aatweiks for
wawtCf^ilaw vmvtektteifvmtaaiett avwa^bei 4f tltBaw *
an submitted pursuant to tha
requirements of 5 58.40 and appendix D
as promulgated. EPA has determined
that the suggestions ware too doaaly
tailored to particular geognphic anas to
be applied nationally.
One commantar was concerned that
tha costs of measuring air toxics was a
substantial addition to tha price of tha
PAMS program. EPA has noted that tha
FAMS stations would be available as •
platforms for tha additional monitor**;
of air toxics compounds if necessary.
Specifically, it is noted by the Agency
that by measuring the VOC targeted in
nfannce 2 appendix C, a number of
tcodc air pollutants will also be
measured. Although compliance with
title I. section 182 of tha Clean Air Act •
Amendments does not raquin the .
measurement and analysis of additional
toxic air pollutants, tha Agency believes
.that the FAMS stations can serve as
cost-effective platforms for an enhanced
adjunct use of PAMS for air toxics
monitoring will allow 1V» consideration
of air toxics impacts in the development
of nrture Oj control strategies.The
establishment of s second PAMS type
(2) site will provide en even better data
base for such uses. The Agency,
however, takes note of the concerns of
savers! nspondents that the PAMS •
network is not ideal as a source of
primary air toxics data and further,
regards the collection of air toxics data
as an incidental and secondary, though
•important, objective of the PAMS
system.
•In overall response to concerns over
the estimates of costs previously
provided by tha Agency, EPA has
recomputed its estimates induding such
additions noted previously as inflation
factors, additional r^p^M equipment,
ate; the new computations an
1 in Table 1.
definitions for the tann NO,, a relatively
new term for total reactive oxides of
•nitrogen mdnding NO, NOa.PAN.
HNOj, and organic nitrite compounds
which all participate in tjbe
research has revealed that these other
compounds may indeed play a
_,, fj, • %_ «h ^^^^^L_J| WB A
does not disagree with tha commentan.
wrestling wiih the aaigma of any kval
of Oj nonattainment-Section 182(cUl)
of tha daan Air AdT Amendments of
19BO, however, authorized the Agency
to develop rules only for those anas
classified as serious or above far Oi
nonattainment, Tha frrt ***** States with
moderate anas will not be required to
institute these specifications, should not
impede those SUta agendas from
configuring monitoring strategies which
C, Public Comments—Regulations •
Tha following discussions address the
•comments received on specific
provisions of the enhanced Oj and Oj
precursor monitoring regulations:
Since no readily-available ^""Mnrfag
method has been designated for these
on the role of NcL or other such
compounds, *tiH lies within the
research community, EPA has
determined that Indusion of any
definition and/orregulatory
requirements for monitoring for NO? is
premature. Futon revisions to 40 CFR
part 58 will nexamina the state of the
research and reconsider this issue.
Nevertheless, EPA encourages the
deployment of this emerging technology
at PAMS sites to further augment the
value of the O^and Oj precursor
measurements.
Additionally, two commenten
recommended that the definition of
VOC be clarified and perhaps focused to
indicate a reference to reactive organic
' gases. Further, one commenter
suggested that an acronym be included
for toxic air pollutants. Inasmuch as
EPA has specifically named the
compounds (VOC) targeted for
•monitoring and analysis by this
program, see reference 2 appendix C,
and expects that list to evolve as th«
monitoring program matures, the
Agency believes that a mon focused
regulatory definition is not needed at
this time. Such a move, made
prematurely, might unnecessarily
constrain development of the program
in future yean and inadvertantly limit
the data available to tha States to craft
the most effective Oj control strategies,
Since the fed of this monitoring
program an clearly Oj precursors and
Oj, these rules an not the moat
appropriate vehicle to define or name
air toxics compounds, Such actions will
be subsequently considered by the
Agency's air toxics control programs..
2. Public Crunmnnta Section 5&2—
Purpose .
One commantar £ah thai it isian
oversight not to consider application of
thtsngulation to modenta Oj
nonattainment anas. EPA notes that
enhanced information on Oj. Oi
precursors, and meteorology would be
beneficial to any State government
3. Publi
Operating
On* commantar recommended that
fotf y<«^fop be amended to restate tha
tS of
section 43 of appendix D. EPA notes
that it would be beneficial to include a
reference to section 43 in $ 58.13, and
^•<^ amended ftrt fin«i rule accordingly.
4. Public Comments—Section S820—
Air Quality Sunreillanca.Plan Content
Four commenten expressed concam
that tha requirements for VOC and/or
meteorological parameters wan too
comprehensive and constituted
excessive collection of data.
Additionally, several commentan
beHeved that the substitution of
measurements for total VOC, non- •
methane organic compounds (NMOC).
OT total non-methane hydrocarbons .
(NMHQ (note that these acronyms
essentially npreeent the same group of
PAMS data objectives, at least at some
of the designated sites. EPA has
reexamined its position regarding
requirements for the spetiation of VOC
analyses and h«c concluded *^«*
continuation of tha speciated
nquinment is both appropriate and
necessary. This conclusion is based on
the need for man definitive information
regarding VOC at the specific .
geographic locations When Q» exceeds
the National Ambient Air Quality
Standard (NAAQS). in order to address
the multi-faceted PAMS objectives. The
sampling for spedated VOC data allows
•the verification of NMOC measurements
and provides a better understanding of
the biogenic contribution to the Oj
problem. The corrbboration of progress
In the reduction of Oj precursor
^ffn<«fjpnf inventories would necessitate
the quantification of the biogenic and
•nt^TCTTv^yun^r fractions fry th"^if anas
when biogenics represent a significant
component of the ambient air.
Additionally, the Agency has modified
the sampling and analysis requirements
to nflect the acceptance of event
MTnpKng flt 3 of tha S yn>niTn«11y.
required sites. Such a modification has •
-------
8458 Federal Register / Vol. 58.-No. 28 / Friday. February 12.1893 / Rules and Regulations
the potential to reduce the data
naiioUmg requirements, costs, and level
of technology needed. The amended
sampling and analysis requirements an
specified In section 4.4 of appendix D.
Attentions to the requirements for the
measurement of meteorological
parameters are discussed in section 4.6
of appendix D. Note, however, that the
promulgated sampling requirements for
spedated VOC do not preclude the
eubmittal of alternative sampling •
schemes as a part of the network design
5 58.40.
specific details on the first PAMS type
(2) site pint general information on
other sites, would constitute a complete
is too short a time frame for SIP
development processing, and approval
fj«t« tha Xrjaf rH«i-ii««4oB nf STPy un^ff
General Comments, EPA believes that
the required SIP revision to empower
States to implement the enhanced Oj
and Oj precursor monitoring regulations
will be a relatively uncomplicated
procedure. Given the intrinsic need for
the data required in this promulgation. .
the Agency recommends that all States.'
including those which are not affected
by these rules, develop such SP
revisions. Based on a review of common
SIP procedures, EPA has subsequently
modified § 58 .20 to allow 9 months for
the submittal of a revision to the SIP for
the *«*«M»«)it»iynt and ni»ttit«n«nf^ of
PAMS.
5. Public Comments— Section 58.40—
PAMS Network Establishment
Seven commenters asserted that 6
months is insufficient time for a State to
develop and submit a PAMS network
description. Inter- and intn-Stata
cooperation, data needs, and complexity
issues were cited as reasons for the
demand for more time. EPA
Headquarters and the EPA Regional
Offices have been working with affected
State and local air pollution control
agencies as well as cooperative bodies
such as the Northeast States for
Coordinated Air Use Management
(NESCAUM) and the Mid-Atlantic
Regional Air Management Association
(MARAMA), to develop the basics of
individual and regional PAMS network
descriptions. Additionally, EPA has
provided funding during FY-92 to begin
the establishment of monitoring sites,
many of which will eventually
constitute the first PAMS type (2) sites.
Given the extensive preparatory work
conducted since 1990 by both the
Agency and the States. EPA believes
that a 6-month requirement for the
submittal of a network design is both
achievable and appropriate. In response
to the concerns of the commenters,
however, EPA has clarified, in § 58.41,
its need for detail in the initial network
design submittal and has indicated that
requirements of 5 58.40. Note, however.
that since the network design must
receive the approval of the
Administrator as stipulated by 5 58.42,
EPA will require the submittal of
subsequent phases of detailed network
design by January 1 of each year of
implementation. In this way, a State
may focus its resources on an annual
frff .
precursor monitoring rules. The Agency
has, however, modified the rules to
indicate this preference for cooperation
and Joint network design submittal.
where appropriate.
One commenter suggested that EPA
support Joint submittals. but not joint
implementation schedules. In § 58.40,
EPA indicates a preference for
coordination, but does not necessarily
require identical designs and
implementation schedules for
cooperating States. Differences in
designs and schedules would be •
evaluated on a case-by-case basis.
One commenter recommended that
at least equal attention as is given to
State-by-State plans within the same
regional area. EPA has previously
expressed its preference for regionally
coordinated network designs; but must
provide equal consideration to both
types of descriptions allowed by these
rules.
Two commenters suggested that the
approval of the PAMS program be
relegated to the Regional Offices in lieu
of requiring approval by the
Administrator. In considering this
comment EPA agrees with the
contention of the commenter that the
Regions are more familiar with the
idiosyncrasies of each Oj nonattainment
area and. as a result Regional Office
concurrence on each network design is
required. In several cases, however, the
areas subject to these rules, cross both
State and EPA Regional boundaries. The
Agency is convinced that a program of
this masnltude requires intensive
national oversight "and a high degree of
consistency and coordination; final
approval must therefore rest with a
central reviewing authority.
Two commenters suggested that
flexibility be included to allow each
network to be designed on a case-by-
case basis because each area has unique-
features such as irregular terrain or
distinct meteorology, such as sea/lake
breezes, which should be addressed
separately. EPA also believes that each
-------
juues
's network design should be
specifically tailored to
.The network design
"parameters promulgated today are those
considered by the Agency as a
minimum did/or • j"ft»"'f network for
those SUU agencies wishing to omit
comprehensive, ITBI iporlfir plannin
•amettac. Although F&A Anmt
Agency re
Cod
fA Jill 1 tit AftffTl dfltlf"^ B
t^ffH is lieu of SKtensive
trends. Those studies are noted as
references 26,27.28,29. and 30 of
appendix D. .
• Several commentm pointed «ut die
need far EPA to better articulate ...
guidance on the submittal of .
•infatmetion far network approval and
any criteria EPA would utilize for
approval of these and any alternative •
' network submittals. Further tnftmn«rt«n
oing network design is included
' "• EPAhasalso
tionand
investments in the planning process.
Note that the Agency is revising the
siting Frft*na guidance document
(Rafarence 19 of AppendixD) to i
guidance on siting and network c
tor VMS with complex terrain ori
meteorology. • ' .
ODB coQuianler recommended that a
working group be established to deal
With ll>f fffqrrlfaartMi pf mm^irrtna
strategies and network designs in the
Northeast Ozooa Transport Jtogion. The
comments? recommended two specific
groups associated with alactric utibtiasv
as technical resource* far soch a
working group. EPA *"•<"*•<"« fhft tf^
lacpoosibility ^T tha implasiaotatioo,
thanfora tha ft >"*^^«Hn»i of SIP
in section 4 of appendix
incorporated additiona
an
strategies lies with the States, the
Agency is therefore cooperating with
N£SCAUM.MARAMA.andthe- •
Regional Ozone Modeling for Northeast
Transport (ROMNET) committees to
form a working group of State, local,
and EPA officials to provide guidance in
the development of a coordinated
monitoring network for the Northeast.
.Another commentar encouraged EPA
to perform quantitative statistics!
-analyses to ensure ihflt the mfafamtm.
required network is sufficient to
corroborate emission inventories and
determine precursor trends. Due to the
frrifryinp nature pf tf** technology for
corroborating emission inventories and
procedures for determining precursor
trends, U is not feasible alibis time to
perform quantitative statistical analyses
for this purpose. EPA believes, however,
that these analyses can be performed
effectively once the PAMS networks are
in place and producing ^*t*
Adjustments based on these analyses
wfll be appropriate when the
procedures are more mature and the
data bases are more complete, To shed
light on these comments, EPA has
1 a Data QuaHrr Objectives
3) document which 1
i was used to
i the original network proposal
of March 4.1992, and this modified
final p)]f That I^T"*"* is j«i»Tlt?f>tl}
criteria regarding the approval of
alternative networks in section 4 of
eppendixD es a-part of this
promulgation* .
During the mmrnent period, aeyeral
agendas submitted proposals for their
areas which are considered to be
alternative network descriptions, EPA
wfll review those designs individually
and respond directly to the particular
agency. Tnoee designs are not
considered germane to the requirements
of the regulation and so are not
r reviewed in this notice of
downwind of a major roadway. In any
case, it is cradal to consider and
account lor local NOx sources including
roadways which may act as local
depressors for Oj when designing a
10 of
network as described in i
•appendix E. .. .__—.. . — -—
B. Public Comments— Section 58.42—
PAMS Approval - _
Note that comments submitted
Tecommendingapproval of network
designs at the EPA Kegional Office level
were previously addressed under
S 58.40.
TT»onf
The regulations promulgated today
require *h* f^**f pf cw*Vn tru-im'ff** §j
the l/^
ihst flexibility of allowing altanative
plane noted that f^**^* agency does not
uniformity of methods are r*nmtiiT.
thtt
»lly
major
efiected by one or more very large maj
stationary sources which «*»«*<<"*• a
principal source of Oj precursors far the
Additionally, if the
levels of learning with respect to their
area's Oj precursor composition and
EPA not^ *^t each air
pollution control agency program is
subjected to its own particular sat of
problems, ni "
coverage; in many cues some of these
ftctorsare quite unique. EPA, on the
other hand, must deal with national
databases and national problems under
an entirely ^••fy"ti«* §0t "f H
agency. To that end, EPA is charged
with ensuring some reasonable degree of
national '*™*i*>*nf to *^"** tional
trends, comparisons, and strategies can
be devised. Further, the Agency is
convinced that during th* phase-in
period specified in section 4J of
appendix D, most agencies will be
^•p«M« fff lacing {0 t^* r4\aTlaT^g«i of
developing the necessary expertise to
operate PAMS.
Con taming the approval of netwodc
designs, -one «*™^Tn«yi^<^» ncon
that this section (and specifically
section 42 of appendix D) be revised to
require an EPA approval or disapproval
within 60 days or the receipt of an
alternative plan. Although EPA notes
iVi»« commentar's sense of urgency with
regard to the approval and
-------
reoerai kaynar / Vol. SB, No. 2iT/; Friday, February 12, 1993 / Rules tnd Regulations
rules to establish • proas* by which
EPA could streamline the review and
i of inzsowtiw Tn
analytical techniques. Further, this
commenter recommended the use at
PAMS of a particular new type of
monitor which continuously tracks key
photochemical o?dd-month time period
allowed by § 58.45 is reasonable and
adequate for the submittal of VOC data.
Three of these commenten indicated
that allowing a reporting deadline of 9
months to a year for the first 2 yean or
so of the program would be preferable.
This data phase-in would then allow
added time for training in the
implementation and interpretation of
data and the data acquisition system.
The final rules stipulate that the VOC •
'data must be reported within 6 months
following the end ofeach quarterly
• reporting period. Since the PAMS
minimum monitoring season runs from-
Junrthrough August and encompasses
two quarterly reporting periods, the
June data would not be-due until
January 1 of the following year, and the
remainder of July and August data
would not be due until the following-
April 1. The Agency believes that when
the systems of data analysis, handling,'
and reporting are routinized. these time '
periods will be more than adequate for
VOC data reporting. The Agency
understands, however, as States begin to
wrestle with new personnel and
technology, that even such a reasonable
reporting deadline may be difficult to
meet during the initial yean of
implementation.
One commenter questioned the need
to delay submittal of the meteorological
data past the time period required for
submittal of the NOx and Oj data. EPA
agrees that the measurement and data
handling technology for meteorological
parameten is currently sufficient for •
States to be capable of submitting such
information on a more expedited
schedule. The Agency recognizes.
however, that the uses for such data in
photochemical modeling, receptor
analysis, and emissions inventory •
functions, generally requires integration
with the VOC data. Since the utility of
expediting this data submittal would be
only marginal, EPA has required that
the meteorological measurements be
submitted on the same time schedule as
theVOCdata.
Concurrent with the development of
the photochemical assessment
monitoring proposal of March 4,1992,
EPA was considering a modification to
the data reporting requirements for
SLAMS and NAMS monitoring as
iterated in §§ 58.26 and 58.35. The
stipulation for 60-day reporting for Oj, •
NO, NO:, and NOX, outlined in
§ 58.4S(c). was patterned after the
changes to the draft requirements for
NAMS. since at that time it was
expected that these other revisions
would be complete. Since the revisions
to NAMS and SLAMS requirements
have not yet been proposed and
subjected to public comment, EPA today
is promulgating a modification to
$ 58.45(c) which would cause these
pollutants to be reported on an identical
schedule to that stipulated in § 58.35 for
NAMS. Changes to the reporting
schedule for ail monitors will thus be
considered in a separate Federal
Register notice at a later date. This
modification would also be consistent
with the comments from two of the
respondents.
Two commenten expressed the belief-
that EPA should make a greater
commitment to assist the States in
developing and implementing VOC data
acquisition and processing systems to
ensure timely compliance with the 6-
month requirement for VOC data
submittal. An additional commenter
expressed a similar concern, that given
the large data handling-requirements,.
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Federal Register / VoL 58. No. 28 / Friday. February 12,1993 7 Rules and Regulations 8461
•the 6-month limitation would be
difficult to meet EPA has n
r f-,t (Involving
acquisition, processing, analysis; anH
station of VOC data which may
> needed assistance to Statas in
i handling of the mascivt VOC data
basa. Further, the Agency has xtvisad its
FAMS cost estimate* upwards to
consider the necessary cocU'of VOC
data acquisition and processing and is
uiderinB t^"* V^fa^ffi of adoitional
EPA has demonstrated its willingness
to provide substantial funding to States
for ambient air monitoring activities via
the section 105 Grant process. Although
the Agency is predisposed to' continue
to contribute to ambient air monitoring
programs such as PAMS, it is of course
subject to the limitations of section 105,
in part described in the Resources and
12. Public Comments—Appendix G—
Monitoring Methodology
guidance in the technical i
document (Reference 2 of Appendix Q.
One respondent suggested that a
target list of VOC species should be
developed and augmented with a
shorter priority list for reporting. EPA
notes that such a target lik has been
published by the Agency in reference 2
of appendix C, but believes that pladng
limits'on reporting via a priority list is
premature and would in no case be
universally applicable.
Two commenters pointed ouf the
immediate need to make appropriate
changes to the Aerometric Information
Retrieval System (AIRS), the national
ambient air monitoring database, to
•accommodate the new PAMS data
elements. EPA has incorporated such
changes to AIRS.
One commenter suggested that
$.S8.45(d) be reworded to allow the
monitoring end reporting of NMHC
(non-methane hydrocarbons) hi lieu of
•VOC. Note that this issue has been
previously addressed in comments
pertaining to § 58.20.
10. Public Comments—Section 58.46—
System Modification
One commenter stated that they
believe that changes in attainment status
should not reduce the requirementsx>f
Ihe PAMS and that monitoring should
continue to be funded by EPA. A second
commenter suggested that once an area
demonstrates attainment of the Oj
NAAQS. EPA should either reduce the
PAMS monitoring requirements or
assume responsibility for the PAMS
funding in that area. EPA believes that
continued PAMS monitoring, even after
a demonstration of attainment is
performed, will be crucial to
TTiitnufafag the Oj NAAQS over tone.
Nevertheless, if a State can demonstrate
that it can properly track unexpected
changes in the ambient VOC mix and
•mission inventories, ^
One commenter felt that the annual
network review should be conducted
and approved by the Regional
Administrator. EPA notes that the
network review for ambient air
monitoring systems described in § 58.20
is currently conducted and approved
annually by the appropriate EPA
Regional Office. Section 58.46
articulates a national approval process
lor changes to PAMS networks similar
to that required for NAMS and
referenced in §§ 58.32 and 58.36.
National data needs and consistency
dictate Headquarters EPA approval for
changes in both cases.
11. Public Comments—Appendix A—
Quality Assurance
All five commenters on this section
pointed out the explicit need for a
specific, uniform, improved system of
quality assurance (QA) for the VOC
sampling and analysis requirements
(especially) mandated by PAMS. One
equivalency of methodology must be
established at least on a regional level
and perhaps even nationally. Several
liars went so far as to
lend that EPA develop federal
respondent added the following three
recommendations for a national QA
program: (1) The establishment of
uniform QA criteria including
calibration schedules, duplicates
schedules, blanks schedules, (2) the
establishment of standardized audit
procedures, and (3) the establishment of
laboratory audit samples and an
interlaboratory exchange program
between States and EPA laboratories.
EPA is aware that the PAMS sites will
require a QA program similar to the oce
now used for SLAMS criteria pollutants.
EPA is currently developing the audit
•reference and equivalent methods for •
VOC. Further, several commenters
reiterated their perception of the need
tor routine inter-State, inter-area quality
assurance procedures. Given that the
•complexity of the technology for VOC
sampling and analysis and its rapid rate
of development and change, EPA has
chosen to publish specific guidance for
monitoring methodology in lieu of
publishing federal reference or
equivalent methods. Such guidance has
been published and is available as
reference 2 of appendix C. The Agency
will track the progress of the
development of new methods and will
reconsider the specificity of methods in
the future. EPA agrees that common and
continuing, or at least comparable,
methodologies are desirable on a region-
wide basis. Comparability of data will
be one factor used by the Agency in
approving coordinated, region-wide
network designs.
One commenter pointed out that the
rules should not preclude the expansion
of the monitoring period to longer than
3 months, noting nlf1"* that the length of
the monitoring season is not necessarily
proportional to the total network
operational costs. EPA notes that
period are promulgated today in section
4.3 of appendix D. EPA agrees with this
respondent that monitoring periods
should be consistent across a regional
network. This factor would also be
scrutinized when approving joint
networks. EPA recognizes the role that
the length of the monitoring period
plays in the computations of total costs
4«* *» A* WhU*OMUY WWaVWUJK hUV vaUUAh * » • • « \ « • «•*
materials and QA guidance required to ««* has weighted that role accordingly.
the NAAQS, it may propose changes,
even reductions, in its PAMS
monitoring network as stipulated by
$ 58.46(b). EPA is not authorized to
accept a cessation of PAMS monitoring,
however, until an area is ^designated to
attainment.
establish such a system for the pollutant
monitoring systems that will be located
at the PAMS sites. These materials for
the VOC measurement systems are being
developed in conjunction with the
evaluation study EPA is now
conducting on the candidate VOC
instrumentation for use at PAMS sites.
This study is briefly described in the
public comments on $ 58.43— PAMS
Methodology. Additionally, EPA plans
to provide VOC samples to the State and
local agencies operating PAMS sites to
assist them in validating their VOC
monitoring systems and the '.
performance of the personnel operating
these systems.
One commenter felt that'EPA should
specify a particular chromatographic
fydnTnn for use on gas chromatographs
(GCs) analyzjJBg for the various VOC.
Reference 2 of appendix C specifies
those column characteristics which
AREAL believes ere necessary to
produce meaningful data on the target
VOC compounds. The laboratory even
goes so far as to provide specifications
on several acceptable columns, but falls
short of requiring a chromatograpber to
choose any one particular design. EPA
• reiterates its position that the
technology for VOC sampling is cmpl
evolving too quickly to allow such
specificity at this time.
-------
•462 Federal Eagkto / VoL 58, No. 2ff / Friday. Fabraaiy 12. 1993./ Rulea and Regulation*
One commenter believed thai th*
VOC monitoring technology is not yet
advanced """"gh for State and local
agencies to economically operate a
speciated VOC monitoring prograa. As
previously stated, the Agency believee
that States an capable of competency in
utilizing new monitoring TnitfaO1^. frvi
in fact • number of Stats agendas an
innovations or more sensitive
monitoring device* for «ith«r VOC or
NOx. It has thaafort addad additional
T 1'V~ • IPT'lkir_-» *w» f**1!"-i-™Tlr
of *frt* technology.
* In a related iscoa^ ac
suggested that the ra
-• **** • . « •
th* equipment design aad .
standards far VOC in order to drtvt the
technology. Noting thaprogrtaaadi to
dale by the reuarcoers. oeB^nexs, eod
fabricators of VOC sampling eqidetnaei.
EPA believee that th* existing technical
spedfidty aad market pressures an
sufficient to spaik development in new-
pling and analysis
respondent
encourages the development of less
labor-intensive methodologies to
countar the specter of future resource
constraints. AREAL has continued to
articulate its support tor such efforts
and will continue to exercise- flexibility
in investigating new. more economical,
and uncomplicated procedures as
recommended by yet another
One commenter felt that EPA should
append the provisions of ma rules (and
particularly appendix Q to fadh'tBta
and encourage the use of innovative.
analytical technologies which are useful
for O) Luuliul strategies. Although EPA
ia investigating the use of such
innovative monitoring technology, ana
specifically the technology-
recommended by this commenter. the
Agency has not yet determined how the
use of these sampling methods win fit
into the currant SIP process.
Nevertheless, EPA does not wish to
preclude the use nor discourage the
X 01 &0VT S2OD2XODXUZ •
end to h*f uaradad fa*
tod if**"** A sftcomi
concerned that the stipulations of
section 4.2 of appendix C required the.
•use of reference or equivalent methods
for the monitoring of NO and NOxM
PAMS. This respondent recoaaends
the CM of more advanced and sensitive
Tnfth'vif for «M>-k m/^tffp^g EPA notes
that in great part, the use of th« NOx
data measured at PAMS is dictated by
the need for pTi^*'fr*of iofonnatioQ
xather *^""» &* comparison with *^* NOs
NAAQS. Since ma Agency does not
wish to preclude the use of potential
appendix C to indicate that such other
thodolo ma be raoaed B the
defined vis reductions of
nther than proerees ia air
tn^«nT«f^f^f« Jor pracuzsors or
'Frnlf*<<***T
Stata as aliatnativ
the Ageocy has determined *«* suc
naw tscanologiM may be propoeed and
•van encourages
uaa* it is premature to make t>»«ty
one commenter specifically raised a
number ?f t*/*^in^r*^ wnntf""* for
consideration by EPA. In response, EPA
has determined that pressurized and
nonnmsurized canister samples are"
equivalent and that drying of samples
prior to analysis to reduce walar content
uan acceptable procedure. .
Additionally, the Agency notes ^*M an
Oj scrubber is required on the carbonyl
samplers, and C-18 cartridges are
equivalent to silica gel cartridges for
such analyses. Guidance on
standardization protocols (what gas,.
how many points, what concentrations?}
will be addressed in future reviswosto
the Technical Assistance Document for
Sampling and Analysis of Qj Precursors
(EPA 600/8-91-21S). Furfltar detail
concemuig such mformation may be
found xn refervnce 2 of appendix C.
13. Publk Comments— Appeodix D—
Network Design for SLAMS, MAMS, and
PAMS
The following discuaions addracs the
comments received on specific
provisions to appendix D:
14. Public Commenia — Section 4.1 of
Appendix D-PAUS Data Uses
Fhre commenters expreind cooceea
that the PAMS program might be •
insuffidant far the purpose of verifying
emissions inventories. One suggested
that further flexibility be built into to*
regulation since techniques for
inventory verification are still in the
developmental stage*. Further, two
commenters expressed «mfli>Hng view*
in the we of air quality data and/or
• emissions inventory data for the
tradong of
time. The u*e of air quality data, and
especially that of photccheoucally
reactive species, is admittedly an
evolving science. EPA does before.
however, that such, data have beea
demonstrated to be a constructiv*.
adjunct tool to •""'•"'TH inventories hi.
qualitatively verifying their accuracy
and serving as a corroborative
instrument to f^^T»iUlioni of rtxuonaHa
further progreai (RFPJ ia reductioos o/
emissions (See HafereocM 28-30 of
Appeodix D). Note that the Clean Air
Act clearly stipulates thai RFP is
the primary tool far evaluating boih-
luryryiT *^ »«^nftjpti«- These ff^* do
notmsan the imnortanca, however, of
ensuring *^>«> those «~»i'*"T«^f •
the details of how the date generated by
PAMS can be wed to meet the data
objective*. One respondent complained
that it currently doe* not have a
program that can use the date provided
ves
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Federal Register / Vol 58. No. 28 / Friday. February 12. 1993 / "Rules and Regulations 8463
iy the PAMS. EPA has prepared .....
documents dealing with the' data quality
objectives CDOjOs) for the PAMS
^4yrT^«i)f{TfHnn« of the Continuing UM Of
such data an noted as references 26-31
of appendix D. Further, in response to .
these comments, minor revisions have '
been made to clarify section 4.1 of
appendix D. Those State agencies which
have ncognized their lack of abflitv to
use these important data may employ
the additional section 105 Grant monies
made available for PAMS toward
enhancing their data processing and
analysis capabilities.
Tour respondents noted that although
some of the stated objectives for PAMS
support application of photochemical
gnamodeung techniques, the network
design does not seem to effectively
accomplish this feat Further, three
commenters protest that the network
specifically does not meet the data
requirements of their State's
photochemical modeling protocol. EFA
fnf nexamined the overall data needs
of the photochemical modeling
community and has modified the
network to be more responsive. Since
the Agency is attempting to ensure that
PAMS is compatible with national
. needs, particular States may find that
the requirements provide better data
{ban needed to execute a Hft
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8464 Federal Register / Vol 58, No. 28 / Friday. February 12.1993 / Roles and Regulation?
The same commuter frit thai rani
aites fcr 0*^ collection of boundary
condition ^'•'^vwi monoxide (00) and
: data should be added to.the PAMS
.EPA also has recognized the
better define boundary conditions.
Consequently, section 4£ of appendixD
and Its associated Figures have been
in«v3tB«^ jo better reflect tbe
measurement of boundary conditions.
Note thf* yjpr* CO was not addressed in
section 182 of the dean Air Act
Amendments as a required pollutant for
PAMS, no monitoring requirements for •
CO were included. This i
not preclude a State from adding CO
'monitoring to its network design.
One commenter believes that due to
the effects of complex meteorology, tbe
placement of PAMS sites should be
based more on studies of past Oa
episodes rather than tbe generic model
proposed by EPA. Tbe Agency agrees in
principal witb this comment and has
altered the location of tbe PAMS sites to
correspond more dosary witb the wind
conditions associated with Oy events.
One commenter requested that EPA
provide more specificity for locating
PAMS type (2) sites, the sites where
maximum emissions an expected to
impact m response, EPA bis clarified
and added additional detail for this
site's location.
One commenter was concerned that
' many of their current NAMS and
SLAMS monitors an not located at
potential PAMS site*. EPA notes this
concern and considered that some, but
not all PAMS sites might be coincident.
with SLAMS or NAMS in its
recomputation of cost estimates.'
Reference is made to a similar
discussion under General Comment <
and Resource* and Cats In this
preamble.
One commenter also requested that
existing data be allowed to be used as
a part of alternative PAMS monitoring
schema*. Note as discussed in 5 58.40
that EPA has amended section 4.2 of
appendix D to include broad criteria for
the approval of alternative networks;
The use of existing tnfiHin»iiiin fad
existing monitoring networks is not
precluded by these change* to the rule.
16. Public Comments—Section 4.3 of
Appendix D—Monitoring Period
Ten commentars expressed opinions
regarding the length and specificity of
the monitoring period for the PAMS.
Three of those respondents supported
crucial, and that more specificity would
be ufrfiiL Three others Imikatea that
they felt that the 3-month period was
too short mru^ would create f**ffinfl
problems for affected State governments
witb a Tn season. One of these
coouaantars assarted that 5 months
would be a better choice, especially in
tbe State of California. Five commenten
believed that employing Oj level
forecasting and episode monitoring
would be a more efficient use of
resources and provide a more intensive-
database for the critical periods and "
ftf manual
the proposed requirement of 3
especially June, July, and August.
•iftinyah they ^*"^cjtffj *^">> more
sampling would obviously be better;
that consistency across regions is
as the one-In-dx-day schedule used fcr
perticulate matter.
sampling methods. One) commenter felt
t>i»+ fti» Timgth nt th* Mmplino pariflij
should best be specified on a regional
•basis and that walk a 3-month period
West
EPA agrees that more than 3-months
would be preferable and has articulated
this opinion in section 4.3. The Agency
has recognized, however, that other
particular months rather than Jane, July,
end August may, on a case-by-case basis
be more appropriate. Accordingly. EPA
has expressed its intent to allow other
monitoring periods if submitted and
. approved as a part of the networic
description required by S 58.40. In the
discussion conc&niing comments to
S 58.40 in this preamble, EPA has
clearly espoused its support for
coordination and consistency among
States and across regions and noted that
other requirements of the Clean Air Act
Amendments may require such
coordination, in *h'« case in establishing
• the monitoring period for PAMS. The
Agency's goal in choosing the 3-month
period was to attempt to capture the
highest Oj events for the year. The
Agency fats established only a "iinimum
sampling period; any affected State or
region may expand this period to a
longer time to meet its particular needs.
Flexibility has been included in the rule
to allow the use of either manual or
r-nnHTmnm sampling technologist.
Given that the Agency recognizes the
utility and efficiency of focussing its
efforts on Oj events, section 4.4
sampling requirements have been
amended in this promulgation to allow
the sampling for such events and as an
option make the use of manual methods
more feasible. A discussion of those
change* follow under section 4.4. EPA
})««tnHndafi 4 stipulation in section 4_3-
that intenniUBQt sampling "met follow
the pnviously-ectablisbed national
schedule foy jpfflfTT^^|^|^| «jimp\yr>p such,
17. Public Comments
Appendix D-Mini
Section 4.4 of
m Network
jwjoirsments
Twenty-four commenters responded
to this section of the proposed rule
ing the details of PAMS nerwodt
Eleven of those
proposed requ
naniS
respondents
concern that . . v
for VOC sampling were excessive and
the rule should be *m^p*fa{i to allow
less intensive sampling. Many suggested
that such a less-Intensive sampling
program would save funds which could
be better allocated for other purposes,
\lPPftf alQ^^OfOACQC SftOQMflXU^JK {OF
example. Several commentars included
ipling plans for
on in lieu of the
sch'edula. Six commentars believed that
tpmm^** m**m
ieu of tbe proposed
!««»«• Valfnuut t\l*t
a better use of limited resources would
be to focus VOC monitoring on days
when high Oj levels would be expected
or forecast. EPA has
fatd the
proposed optional sampling schedules,
considerod the economic impact of the
schedule, revisited tbe current stale of
the monitoring technology and has
concluded ft"** it is appropriate to make
a number of changee to the Ttitn»m»n»
sampling schedule for VOC To respond
to the data needs of the Agency ana the
State and local air pollution control
agencies, EPA has decided tbe
following: Sampling schedules for NO,
NO}, NOxi PI and surface
meteorological parameters remain
unchanged. EPA has determined that
sampling will continue to mirror those
for gaseous criteria pollutants, (i.
continuous measurements). The
*n{Ti
-------
j. ...— *
trtffMtaPg UM joist fMhrfttri fif MtvroxJc
* f^KAAstfQV |hi4 OptlC110 -
-- lincludea strategy far aa*uring a
coordinated. aetwotk-widr :e*poDse to
O> •venis&oaitorin'g.Siich e change in
•ocas to event anoanoring will ako
increase the feasibility of utilizing
manual sampling methods «s requested
far Mvenil frfMnn^^^T* •
Also in response iothesecencanj*
•nj jn m man/3 ina
are BO predominant high 0» day winds
which can be accurately identified,
Also, the Agency has » located the
upwind and downwind sites to
correspond more appropriately to the
data need* for photochemical grid
models and has added guidance en the
location of noniUss, •specially site .
alternate monitoring technologic for
the FAMS, stated that in lieu of
monitoring 1-hour avenges for VOC
monitoring, the sampling of HHninut*
. average for VOC equivalents or .
surrogates should be allowed. The
technology reconuaeaded by this
commanter is currently being
scrutinized by the AKEAL laboratory to
determine its utility in the SIP process
as noted in the discussion of $ 58.43.
EPA has otharwisa determined that VOC
monitoring at increments of 10 minutes
is not practical at this time.
Several other commenten suggested
the use of 24-hour and/or continuous
NMOC monitoring (with periodic
spedation) as an adjunct to or even as
a nplacamant for the PAMS speciatsd
VOC monitoring. They assart tbat the
technology fat NMOC mmttnrifig is
proven and that the subsequent data are
sufficient for the development and
tracking of control strategies. EPA has
considered thase arguments and has
determined t^t\ •Hh'M'Eh «"m« of the •
PAMS objectives may be fulfilled via
total NMOC data, the remainder require
the gathering of speciatad VOC
measurements. The Agency has .
therefore not adopted the use of NMOC
instead of spedated VOC as a national
requirement as discussed previously
under the public comments to $ 58.20.
The PAMS reauirements. however, do
not preclude the collection of additional
aabminaJ of aHasnativtjtftwadcs which
• propose elements of NMOC monitoring.
Two commentBri questioned the .
uttHry of gathering a 24-hour integrated
and spedated VOC sample to
sjupiussBBntths 1-hour frfciftt^ VOC
seraphs. EPA notes that given the
^•riabOBS inherent in continuous/I-
• hour VOCmaaturemant technology, the
addition of a periodic 24-hour sample
for purposes of quality assurance is a
prudent and aecasaary reality check.
Additionally, the yaar-round 24-hour
periodic sample will provide
information on emissions inventories,
RFP, and long-term VOC trends end
•One State commentar felt that the
guidance for regional network design.
provided by figure 2 of appendix D. is
too generic. This respondent suggests
specifically that EPA should develop
the PAMS monitoring network
description for the Northeast Oj
Transport Region. EPA rncogni7.es the
unique nature of the Oj problem
occurring in the northeastern United
States. Further, the Agency agrees with
the principle that a strong federal
contribution to the development of a
region-wide monitoring network is
critical to develop the needed
consistency, cohesiveness. and
comparability of the PAMS in the
Northeast. Accordingly, the Agency has
offered and is supplying both t«*-htitr«T
and financial assistance to coordinated
region-wide State and local efforts. EPA
does not agree, however, that the
Agency should, by rule, usurp the State
Implementation Flan process
established by section 110 of the dean
Air Act, aor shortcut the requirements
for the submittal of a network
description for PAMS. Failure of a State
to comply with the nquireaenls for
'submittal of a SIP could, however,
ultimately require EPA to promulgate
and implement a Federal
Implementation Plan for that State
pursuant to section 110.
Several agencies submitted a PAMS
monitoring plan which was
fundamentally different from the
proposed rule and requested that EPA
substitute those requirements as the
national requirements for PAMS
monitoring. EPA observes that these
.agendas,being proximate to one
another, would benefit greatly by
geographical region. On the contrary,
however, far the same reasons that the
requirements an .specifically tailored to
the <4<«T«u-i«rirt?r^ cf that particular
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8466 Federal Register / VoL 58, No.' 28 / Friday, February 12, 1993 / Rules and Regulations
regira. the Agency does not believe that
it would suffice as e national «nfa<»nm«
program.
18. Public Comments—Section 4J of
Appendix D—Transition Period
Six commenten responded to *^"«
section, with varying points of view,
although most were discussed as part of
the debate outlined in S 58.44.
Additionally, however, two commenten
suggested that the early years of the
program requirements should not be
overly prescriptive end that areas be.
allowed to build up their programs over
time, intimating that technology
changes and resource needs could be
phased in along with the monitoring
program. In response, EPA has
incorporated additional transition
period flexibility as iterated in the
discussion of S 58.44.
19. Public Comments—Section 4.6 of
Appendix D—Meteorological
Monitoring
Sixteen commenten provided
observations-regarding the
meteorological monitoring requirements
proposed by section 4.6 of appendix D
and further stipulated by reference 2 of
appendix C. Eleven of these respondents
indicated support for thecollection of
upper air meteorological data in each
area, especially if high quality upper air
data are not currently available. Several
supported this suggestion with'
notations that the photochemical grid
models demand such data. One
commenter, although recognizing the '
need for upper air monitoring, advised
caution and deferral of such
requirements due to the current state of
atmospheric sounding technology. EPA
has investigated the merits and
projected costs of upper air
meteorological monitoring and has
concluded that the benefits of
incorporating a requirement for upper
air measurements ere substantial In
response, therefore, the Agency has
amended section 4.6 to reflect these
requirements and has further indicated
its predisposition to allow adequate
time for securing data from this
network EPA also believes that States
should take advantage of existing upper
air monitoring programs and where
potable, substitute these data for the
FAMS rrquirements. EPA will provide
guidance for the collection of these data.
Several respondents provided specific
recommendations concerning the
particula: meteorological parameters
which should be monitored and those
for which they believed monitoring
should be limited. EPA notes that with
the exception of dew point
particular parameten ere incorporated
into reference Z of appendix C
rVmr^fnlnp dew point, ""f rnmm«t)ffy
stated that their meteorological staff find
dew point temperature measurements to
be much more useful than relative
humidity to the study and forecasting of
Oj episodes. The measurement
technique for dewpoint is
straightforward: State* ere encouraged
to include such measurements et PAMS.
if they find them useful The Agency
has not required the measurement of
this parameter since it may not be
essential for all locations and may be
derived from temperature and relative.
humidity measurements. As observed
by one commenter, barometric pressure
generally doe* act vary widely within e
large area, except in areas with complex
terrain features. EPA therefore indicates
its predisposition to allow approved
network designs which oner limited
measurements of barometric pressure
(or other parameten} if the State can
demonstrate that the area's topography
is not conducive to significant pressure
(or other) variations.
One respondent indicated that the
•rule should allow measurements at e
minimum height, or a range, above
ground rather than specify 10 meters.
For consistency, EPA has retained the
10-meter requirement The Agency has
determined that the lack of flexibility in
this requirement should not constitute
any hardship inasmuch as
measurements at 10 meters are
traditional as well as practical States
may institute additional monitoring at
other heights, at their own volition.
In the preamble to the March 4, 1992
proposal, EPA recognizeoVthe potential
difficulty in siting a 10-meter
meteorological monitoring tower at a
particular PAMS site. The Agency
therefore requested comments on
criteria to determine how such data
collected at a nearby site could be used •
to represent the meteorology at a PAMS
site where the tower and air monitoring
equipment could not be collocated. One
respondent agreed with the premise that
nearby data (such as collected at
airports or National Weather Service
stations) should be accepted, but
provided no suggestions for criteria to
judge the representativeness of those
data. EPA has consequently decided to
consider requests to use nearby existing
meteorological data, both surface and
upper air, on a case-by-case basis.
20. Public Comments— Appendix E —
Probe Siting Criteria for Ambient Air
Quality Monitoring
• Four respondents provided specific
comments regarding the placement of
measurements, the recommendations for- the probe and siting criteria for PAMS,
One was particularly concerned over the
description for the PAMS site to be
located downwind in the second-most
prevalent wind direction noting that the
probe siting criteria were based on the
primary wind direction. EPA recognize*
this deficiency, and notes that the rules
have been emended to eliminate this
PAMS type (5) site. Additional language
has been added to sections 10.2 and 12
of appendix E to correct this anomaly
One commenter. based on experience,
recommends that VOC samplers should
be located further from sources than
criteria pollutant moniton if they are to
measure area-emitted end-regionally*
transported VOC EPA notes that the
Tninirrmm network detailed in section 4
of appendix D, stipulates 3 site types
which are located to adequately
measure incoming transported
emissions (type (1)], maximum Oj
measurements (type (3}], and downwind
outgoing conditions (type (4)], all sited
as urban scale monitors.
Two agencies recommend the use of
a vertical manifold for the measurement
of ambient Oj precursor data rather than
a horizontal manifold. They further
recommend that a heated line from the
manifold to the GC be employed to
ensure the transmission of heavy
hydrocarbons through the line. EPA
notes no compelling reason to specify
the orientation of the sampling
manifold. The requirements published
in the technical assistance document
(Reference 2 of Appendix C) do not
preclude the use oil vertical sampling
manifold. Likewise, the Agency has not
specified nor prohibited the heating of
the manifold which may be necessary in
high humility areas.
One commenter believes that the
specifications for separation distance
between PAMS and roadways, trees and
obstacles appear to be lenient and
should be more stringent EPA believes
that the specifications are adequate
based on current best judgement As
more information becomes available, the
Agency will revisit this issue.
D. Public Comments Concerning Impact
on Small Entities
The U.S. Small Business
Administration (SBA) requested further
detail regarding the impact of these
regulations on rm*i\ entities which an
defined to include small businesses,
small organizations, and small
governmental jurisdictions (5 U.S.C. 601
et seq.). Since EPA is utilizing the State
Implementation Plan process as
outlined in section 110 of the dean Air
Act, the provisions of these regulations
promulgated today, apply directly only
to State Governments, and particularly,
-------
Federal Sagttter / VoL SB. Ko. 28 1 Friday. Fabnary 12.1093 / Roles «nd Regulations S467
•to the State air pa
• • • * •
fflnifc
ntml
8S Severe,
serious, or extreme. EPA therefore ha* .
concluded that no-small entities would '
Uaffeaedbytha proposal. At*be
request of the SBA's Chief Counsel for
Adroacy, this certification bis been
clarified. Therefore, pursuant to S I7.&C
eosfl>).lae Administrator certifies that
endments would, not have A
^Section 58JfcaaTOd*dbyievisiBg f58^ Atr^ueOtyeurveUenee:Ptan
flSU DeAnMone.
•«•••»
(f) NOa meaas aitegea dioxide. MO
"ip™*. no additional reviews are
wjuired. The rules wan submitted to
the Office of Management aad Budget
(OMB) for review (under Executive
Order 12291). This Is not a major ale
under ED. 12291 because it does not
• meet any of the fT^*r!* ^*fjr*^ in *^*
-------
8468 Federal Register / VoL:S8. No. 28 / Friday, February 12. 1993 / Rules and Regulation!
,S«c . .
58.44 PAMS network
68.45 PAMS data subm
51.46 System modification
(d) Identification of the sits type and
location within the PAMS network
i as defined in
Subptrt E—Photochemical
Assessment Monitoring Stations
(PAWS)
158*40 PAMSiietwoikestabllahmaiw.
(a) In addition to the plan revision, .
the State shall submit a photochemical
assessment monitoring network
description including a schedule for
implementation to the Administrator
within 6 months after;
(1) February 12,1993; or
(2) Date of redesignation or
^classification of any existing Oj
nonattainment area to serious, severe, or
extreme; or •
(3) The designation of a new area and
classification to serious, severe, or
extreme Os nonattainment
The network description will apply to
all serious, severe, and extreme Oj
nonattainment areas within the State.
Some Os nonattainment areas mey
extend beyond State or Regional
boundaries. In instances where PAMS
network design criteria as defined in
appendix D to this part require
monitoring stations located in different
States and/or Regions, the network
description and implementation
schedule should be submitted jointly by
the States involved. When appropriate.
such cooperation and joint network
design submittals are preferred.
Network descriptions shall be submitted
through the appropriate Regional
Office(s). Alternative networks,
schedules, periods, or methods,-may be
submitted, but they must include a '
demonstration that they satisfy the
monitoring data uses and fulfill the
PAMS monitoring objectives described
.in sections 4.1 and 4.2 of appendix D to
this part
(bj For purposes of plan development
and approval, the stations established or
designated as PAMS must be stations
from the SLAMS network or become
part of the SLAMS network required by
§53.20.
(c) The requirements of appendix D to
this part applicable to PAMS must be
met when designing the PAMS network.
§58.41 PAMS network description.
The PAMS network description
required by 5 58.40 must contain the
following: - " .
(a) Identification of the monitoring
area represented. . .
"(b) The AIRS site identification form
for existing stations.
(c) The proposed location for
scheduled stations.
appendix D to this part except that
during any year, a State may choose to
submit detailed information for the site
scheduled to begin operation during '
that year's PAMS monitoring season,
and ^tf*iT submittal of detailed •'
information on the remaining sites irnH1
succeeding years. Such deferred
network design phases should be
submitted to EPA for approval no later
than January 1 of the first year of
scheduled operation. As a »«<*<<«««*,
general information on each deferred'
site should be submitted each year until
final approval of the complete network
is obtained from the Administrator.
(e) The sampling and analysis method
for each of the measurements.
(f) The operating schedule for each of
the measurements.
(g) An Oj event forecasting scheme, if
appropriate. . - -•.
(h) A schedule for implementation.
This schedule should include the
following:
(1) A timetable for locating and
submitting the AIRS site identification
form for each scheduled FAMS that is
not located st the time of submittal of
•the network description;
(2) A timetable for phasing-in
operation of the required number and
type of sites as defined in appendix D
to this part; and
(3) A schedule for implementing the
quality assurance procedures of
appendix A to this part for each PAMS.
§58.42 PAMS approval
The PAMS network required by
S 58.40 is subject to the approval of the
Administrator. Such approval will be
contingent upon completion of each
phase of the network description as
outlined in § 58.41 and upon
conformanca to the PAMS network
design criteria contained in appendix D
to this part.
§58.43 PAHS methodology.
PAMS monitors must meet the
monitoring methodology requirements
of appendix C to this part applicable to
PAMS.
§58.44 PAMS network completion.
(a) The complete, operational PAMS
network will be phased in as described
in appendix D to this part over a period
of 5 yean after
(1) February 12.1993; or
(2) Date of redesignation or
xedassification of any existing 03
nonattainmeat area to serious, severe, or
extreme; or
(3) The designation of a new area and
classification to serious, severe, or
extreme 03 nonattainment.
(b) The quality assurance criteria of
appendix A to this part must be
. implemented for all PAMS.
§58.45 PAHS data eubmteal
(a) The requirements of this section
apply only to those stations designated
as PAMS by the network description
required by § 58.40.
(b} All data shall be submitted to the
Administntor in accordance with the
format, reporting periods, reporting
deadlines, and other requirements as
specified for NAMS in § 58.35.
(c) The State shall report NO and NOx
data consistent with the requirements of
S 58.35 for criteria pollutants.
• (d) The State shall report VOC data
and meteorological data within 6
months following the end of each
quarterly reporting period.
§58.48 System modification.
(a) Any proposed changes to the
PAMS network description will be
evaluated during the annual SLAMS
Network Review specified in S 58,20.
Changes proposed by the Slate must be
approved by the Administrator. The
State will be allowed 1 year (until the
next «Timi«l evaluation) to implement
the appropriate changes to the PAMS
network.
(b) PAMS network requirements are
mandatory only for serious, severe, end
extreme 63 nonattainment areas. When
any such ana is redesignated to
attainment, the State may revise its
PAMS monitoring program subject to
approval by the Administrator.
7. Two new sentences are added
before the last sentence in the first
paragraph of section.2.2 of appendix A
to read as follows:
Appendix A to Part 58—Quality
Assurance Requirements for State and
Local Air Monitoring Stations (SLAMS)
• • • • • •
2.2 ••• Quality assurance
guidance for meteorological systems at
PAMS is contained in reference 3.
Quality assurance procedures for VOC
NOX (including NO and NO]], Oj, and
carbonyl measurements at PAMS must
be consistent with EPA guidance.*. * •
• «.»-•« •
8. In the References section of
appendix A redesignata references 5, fr.
and 7 as references 6,7, and 8,
respectively, and a new reference 5 is
added to read as follows:
Refennca
••••••
5. Technical Assistance Document for
Sampling and Analysis of Ozone Precursors.
-------
Federal Register / VoJL SB. No. 28 > Fflaay. Yebruary 12. 1993 / Rules and Regulations 8469
Atmospheric Rs*eerch aad Expoauie
Assessment Laboratory, u.S- EnTirffti
Protection Agency. Research Triangle Park,
NC 27711. EPA 60078-91-215. October 1991.
• • • • •
9. Sections 4.0.5.0 tad 5.1 of appendix C
tn redesignated as sections 54, 84. tad 6.1,
respectively (renBeace S.1 wul ritff*flMf
nfoaaca.6.1 of nctioa 64). (actions 4.0.4£,
•ad 4J an added, and newly redesignated
section 6.0 is nvised to seed as fallows:
Appendix C—Ambient Air Quality
4JO Photochemical Assessment Mon&ozing
Stations (PAMS)
44'. Methods used fa O,monitoring at
PAMS mist be automated reference or
equivalent methods as defined in 5 50.1 of
this chapter.
. 44 Methods used far NO. NOa and NOx
monitoring at PAMS should be automated
reference or equivalent method* as defined
for NOa in S 50.1 of this chapter. If alternative
NO. NO] or NOx p"*"<*"'fag methodologies
an proposed, such techniques must be
detailed in the network description required
by S 58.40 aad subsequently approved by the
Administrator.
O Methods for meteorological
measurements and spedated VOC
monitoring are Included in the guidance
provided'in references 2 and 3. If alternative
VOC monitoring methodology (including the
use of aew or innovative technologies), .
which is not included in the guidance, is
proposed, it'must be detailed in the network •
description required by S 58.40 and
subsequently approved by the Administrator.
£.0 References
• • • • •
1. Pelton, D.). Guideline for Particulate
Episode Monitoring Methods, GEOMET
Technologies, Inc.. Rockville. MD. Prepared
far US. Environmental Protection Agency,
Research Triangle Park, NC EPA Contract
No. 68-02-35*4. EPA 450/4-43-005.
February 1983.
2. Technical Assistance Document For
Sampling and Analysis of Ozone Precursors.
Atmospheric Research aad Exposure •
Assessment Laboratory, ILS. Environmental
Protection Agency, Research Triangle Park,
NC 27711. EPA 600/8-91-215. October 1991.
"3. Quality Assurance Handbook far Air
Pollution Measurement Systems: Volume IV.
Meteorological Measurements. Atmospheric
Research and Exposure Assessment
Laboratory, U.S. ^""^r"1****11*^' Protection
Agency, Research Triangle Park, NC 27711.
EPA 600/4-90-0003. August 1989.
10. The heading of appendix!) is
revised to read as follows:
Appendix &-4*etwerfcDertgn for State «P»an
and Local Air UonHoring Stations ~ '
(SLAMS), National Air Monitoring
Station* (NAUS), and Photochemical
Aaaeaarnent Monitoring Statlona
(PAHS)
11. The second sentanca of the first
paragraph of section 1 of appendix D i*
nvised to seed as follows:
!.•• •ftalsoaeecrlbee criteria far
determining the number aad location of •
National Air Monitoring Stations (NAMS)
aad Photochemical Assessment Monitoring
.Stations (PAMS). These criteria will also be
used by EPA in evaluating the adequacy of
th«SLAMS/NAMS/PAMSnetwork- • •
itifiahle eetimi
itee of seeded
redactions; sad (3) the evahia^aaofuV
predictive capability of the models used.
Sections 4 aad 5 of Appendix D
fRedesignated as Sections S and 6]
12, Section 4 and section 5 of
appendix D an ^designated as section
5 and section 6, respectively, and a new
section 4 is added to read as follows:
4. Network Design for Photochemical
Assessment Monitorial Stations (PAMS)
la order to obtain more comprehensive and
representative data on Oj air pollution, the
1990 Dean AifAct Amendments require
enhanced monitoring far ozone (Oi), oxides
of nitrogen (N'O, NOa, aad NOx), and '
monitoring far VOC in Oj aonattainment
areas classified as serious, severe, or extreme.
This will be accomplished through the
establishment of a network of Photochemical
Assessment Monitoring Stations (PAMS).
4.1 PAMS Data Uses. Data from the
PAMS are intended to satisfy several
coincident needs related to attainment of the
National Ambient Air Quality Standards
(NAAQS), SIP control strategy development
aad evaluation, corroboration of emissions
tracking, preparation of trends appraisals,
and exposure assessment.
(a) NAAQS attainment and control strategy
development. Like SLAMS and NAMS data.
PAMS data will be used far monitoring Oj
exceedances and providing input far •
attaiament/nonattalnment decisions. In*
addition. PAMS data will help resolve the
roles of transported and locally emitted 0}
precursors in producing an observed •
exceedanca and may be utilized to identify
specific sources emitting excessive
concentrations of Oj precursors and
potentially contributing to observed
exceedances of the Oj NAAQS. The PAMS
data will enhance the characterization of Oj
concentration! and provide critical
information on the precursors which cause •'
Oj. therefore extending the database available
far furore attainment demonstrations. These
demonstrations will be based on
photochemical grid modeling and other
approved analytical methods and will
provide a basis for prospective mid-course
control strategy corrections.-PAMS data will
provide information concerning (1) which
areas and -episodes to model to develop
appropriate Luotiol strategies; (2) boundary
conditions required by the models to produce
•PAMS WO! provide data far SIP control
strategy evaluation. Long-term PAMS data
will be need to evaluate the effectiveness of
these control strategies. Data may be used to
evaluate the impact of VOC and NOx
emission reductions on air quality levels far
Oa if data is reviewed following the time
period during which control measures wen
implemented Spedatton of measured VOC
data will allow determination of which
• organic apedes an most afiected by the
•missions reductions and assist in
developing cost-effective, selective VOC
reductions and control strategies. A State or
local air pollution control agency can
therefore ensun that strategies which an
implemented la their p^^nilsT
t ana an those which an best
Mi ted far that area and achieve the most
iffective emissions reductions (aad therefore
largest impact) at the least cost.
. (c) finissons tracking. PAMS data will be
used to corroborate the quality of VOC aad
NOx emission inventories. Although a
perfect mathematical nlationship between
emission Inventories ud ambient
measurements does not yet exist a
qualitative assessment of the nlative
contributions of various compounds to the
ambient air r**T oe roughly compered to
current emission inventory estimates to
evaluate'the accuracy of the emission
Inventories. In addition, PAMS data which
an gathered year round wfll allow tracking
of VOC and NOx emission reductions,
provide additional information necessary to
support Reasonable Further Progress (RFP)
calculations, aad corroborate tri<««»>w««
trends analyses. While the regulatory
assessments of progress will be made la
terms of emission inventory estimates, the
ambient data can provide independent trends
analyses and corroboration of tnese
assessments which either verify or hffiHg>»«
possible ericas in emissions treads indicated
by inventories. The ambient assessments.
using spedated data, can gauge the accuracy
of estimated changes in emissions. The
spedated data can also be used to asset* the
quality of the VOC spedated and NOx
C^BiSOOfi uXYOfilQXlBS fOt ISIDUt QlBi&K
photochemical grid modeling exercises aad
identify potential urban air toxic pollutant
problems which deserve closer scrutiny.
The spedated VOC data will be used to
determine changes in the spedes profile,
resulting from the emission control program.
particularly those resulting from the
reformulation of fuels.
(d) Treads. Long-term PAMS data will be
used to establish spedated VOC. NOx. tad
United toxic air pollutant treads, and
supplement the Oj treads database. Multiple
statistical Indicators will be tracked,
including Oj and its precursors during the
events encompassing the days during each
year with the highest Oi concentrations, the
seasonal means far these pollutants, aad the
annual means at representative locations.
The men PAMS that an established ia'aa
near nonattalnment anas, the men effective
the trends data wfll became. As the spatial
-------
8470 Federal RegJriar / VoL 58, No. 2ft /Friday. February 12,1993 / Rules and Ragohttom
distribution. Bad aumber of Oj aad Oj
pncunot nonltoa Improve*, bind* analyse
nttia«> «» «4t«
•rill ha Ta« tt»H««Tu-«a fry i
T^T nQUXnaMQi ttrit
se*
aftecDoon wiad d&ecUos mar ^yrrft
t£f Utility Of th***
by comparisoaa with avtBOtologifial treads*
and transport mfiueace«.Th* meteorological
datatsrfned fttsm historical wind date
during tha period 7 us. to 10
day» or on those day* whka
Intel
(a) £rposon acsecsmeaLPAUS data will
b*usedtob*ttarcharacterix»O>andtoodcair
pollutant exposur* to popuknons living la
serious, sevare, at extreme ana*. Annual
HM«« tcnrV.?rpfJlMf™» rn*f~,*.H~.~fn .
be calculated to halpastimate tha avB*>*
risk to the population, associated with
Individual"
considered fo^'p.
which an
urban eDviroamanta.
the SLAMS and NA14S design ezitaria which
an pollutant specific. PAWS design criteria
im litn TTirrifir rnnnirriiTrt mmnrtimrnli rf~
Oj» NOx, spedatad VCC aad meteorology
an obtained at PAMS. Design criteria fiar th*
PAMSMtwork are based oa selection of aa
arny of site IccatioM relative taOs precursor
directions «*w*v«^ with high O» events.
Specific m/mi*"*-^* obj*ciivas> an associated
with aach location. Th* overall design should
enable fti«>« aad
its precursor* into aad out of tha ana. aad
the photochemical ptocassee nlated to O,
Boaattaiameat. as wall as develop h\a M*
pollutant rislabas*. Specific objectives thai
muitbetddres*.
i •TaatfrTna vrnVtAnl
tnnds ia O}. NO, NOi. NOjb VOC Oadudiag
cuboayU), and VOC ipecac*. «*«*«"^'"^
spatial sad diuntal wriabUily of O^ NO.
NOj, NOx. aad VOC spedM and asseniaf>
chaagM ia tha VOC tprp'** piofilac *h»t
t pazticulariy thota ftminrfM
mudmtna of five PAMS sites an required ia
•>«> afffftyfl &fi«Uitt*U&ffiftDl VM dftDilodim OD
tha populatica of th* Vtotropolitaa Statistical
jijM/fVift»0 j(4a»^ Metropolitan Statistical
Ana (MSA/CMSA) or noaattaiament area,
whichever is krgee. Specific zoceitoring
objectives associated with each of these site*
mult in four distinct sit* type*. Note thai
fjffg}i« (thia ate may coiadda witk
monitoring site).
aolssion
• Bstabllshniant of boundazT conditions
fix future photochemical grid modeling and
mid-course control strategy chaagw, lad
• • Derfllcpment of Incoming polhitjnt
tnnds.
Typt U) shea an estabtiahed to monitor
th* magnitude and lyp» of pncmscr
aiaissioas ia tr^ anft when ^*^^""^»*^
precursor emissions an expected to impact
aad an suited for tha monitoring of urban air
tadc pollutants. Type. (2) site* ax» located
immediaialy downwind of tha ana of
amlssioas ^TT^ an
modeling applications,
• Future development aad evaluation of
COBUUI straiegiee,
• DeTslopmant of pollutant tnnds. and
• ChanctariatioaofOiponutaat
•srposuns.
Type (4) sites anestablished to
charactanza the f **'ftih^ down wiad
transported Oj and Its precursor
concentrations »«tttii» the ana, t***^ wiD
identify those «nas which an potentially
near me downwind
bouadsry of me cestnl business district to
obtain; neighborhood sale measurements.
Tha ipproprtita downwind dinction should
be obtained similarly to that for type (1) sites.
Additionally, a second type (2) site may be
required depending on the size of the area.
•ad should be placed la ^m
predominant morning wind HtT^-tirm >j
noted previously. D*U measured at type
sites wiH ba used principally for the .
following purpose*:
other anas. Type- (4) site* an located cate
pndomiaaat aftemoom downwind direction.
as detarmined for the type (3) site, from the
local ana of maximum pcecucwc emJuiont
during tha Oj seasoa aad at a distance
sufficient ID obtain urban scale
appendix. Typically, type H) sftoe will be
located aaar th* dowawiad edge of tha
pbqtryKogir^i grid "^^*> famm'tn Altaoai*
scaetnee lor specifying the location of thia
sit* m«y be submitted aa a pan of tha
aetworx description required by S5 54.40 aad
55.41. Data'measured at type (4} sites will be
used principally for the following purposes: '
• Development cad evaluation of Oj
coatrot sUste^ies,
• Identifies tico of emissions »d
photochatnirai products leaviag the are*.
^j»} futun conbol stTttBgia*,
nf MfT^ «n^ VOT! JITTIIMI
inventories.
• Augmentation of RFP
• Verification of photoch
perfonna&ca.
pollutant exposures (appropriate site for
• Development of pollutant"tnods, '
particularly toxic air pollutants and annual
ambient speciated VOC trend* to compare
with tnods in annual VOC «»w«i«
estimates, and
• Determination of attainment wha tfae
NAAQSforNOjandO>
Typ* (3) sites an intended to monitor
TTHTmuim Oj canceatntioBS occurring
downwind from th* ana of maximum
. precursor emtesion*. Location* fc» type (3)
site* should b* cheeea so that nrbea seal*
saeaeunmeote an obtained. Typically, type
(3) sites will b* located 10 to 30 mile*
downwind from th* fri&g* of th* urban are*.
The downwind directioo ftn^iH ^lm be
determined bom historical wind data, bat
should be ideotifted as thoe* afteraooa winds
occurring during the period 1 pjB.to4pjn.
oa high Oj days or oa thoe* days which
•xhihit th* pnrenKal lac j-*v*«»<'*fl high Oj
levek. Alternate sesame* far specifying thW
for pKntcvX»fpw-ii rrift modeli&g,
• Development of pQl)"*itr>t bvodSv
• Background s*H upwind infon&atioo> fr^^
other downwind anas, and
• Evaluation of photochemical grid mode!
performance.
States choosing to submit an individual
- _ . network description for each effected
grid model nonattainment area, irrespective of its
proximity to other affected anas, must folfiU
the requirements for isolated anas a*
described in section 4 of appendix D. as IA
example, and illustrated by FIgun 1. States
containing areas which experience
significant impact from long-range uausput
or an proximate to other noaattainmeot areas
(even in other States) should coDective)y
submit a network description which moti'"?
altamativ* sites to thoee mat would be
required for aa isolated ana. Such a
suacaittal •h*^]M B a gn^^ff, b* based oo th*
exampl* provided i&Tigun 2, but must
iachide a A**mip*tr^ f TQJ* ^^y tf^f desioi
satisfies tha «««nttf
aonitrdng objectiro far a dlgeraat sit* la .
for one ana may «"*s^'« as as upwind site
for another. These alternative network
design* must also be reviewed aad appron
by tK* Ai^mmlt+Tf Ifrr
MLLX4Q COOC aHD*40^
-------
FIGURE 1 - ISOLATED AREA
NETWORK DESIGN
CENTRAL BUSINESS DISTRICT
URBANIZED FRINGE -^
NOTE: 1/7 AND U2 REPRESENT THE FIRST AND SECOND MOST
PREDOMINANT HIGH OZONE DAY MORNING WIND DIRECTION.
U3 REPRESENTS THE HIGH OZONE DAY AFTERNOON WIND DIRECTION.
112
-------
8472 Eedgil Begiiter / Vol 58, No. » / ftiagj. Febnaiy 12. 1893 / Rule* ami Regulations
FIGURE 2 ^MULTI-AREA AND
TRANSPORT AREA 0
NETWORK DESIGN
CITY Y
CENTRAL
BUSINESS DISTRICT
CITY Z
CITY X
(2)X ^C^ )
URBANIZED
FRINGE
_ uiA*DU2*0fssBn"me OUSTAtBstcem MOST
& f>fi£DGMWA»7 HIGH OZONE DAY MOftNINQ MWO DIRKTX)*.
^ V3 RSffSSBTTS THE HIGH OZONE 04 YAfTtmOOtt HWO OIRB
LWOCOM
-------
Federal Register / VoL 58, No. 28 / rhday, georuary 12. 1S93 / iuuea anu sxeguiauona
Alternative PAU
i site-bysita basis, provide
eeeary to enhance the attaii
onai .
aeceeiaiy to enhance I
those data
tharetes,then*eofi
imlts (such a* couatiee or i
transport. Tie alternative PAMS d
t uld
be usable for the conobaration sad
mjficition of Q> precursor emissions
inventories and fh"MM comprise •
Qualitative (If not quantitative) measun of
theaccuncyofRFP calculations. The dais
should ba suffidaot to evaluate the
efiectivenau of tha implemented 0» control
strategies and should provide data necessary
to establish photochemical arid modeling
nfHinrtary conditions a&d necessary inputs
xBooaing appiuyriata pataofpioy flal
O1SA) far monitoriiig network design
purpose* i» inappropriate. Various sampling
f^T^i of the ana to •*j««nm<«fat« fr* twip^-t
convection of Oipcecunccs.
• Tha type (1) site which oUueeiae the
«Bsct of incoming ncuaor amiaskjos aad
account for tha spatial variations inherent in
large anas, to satisfy the differing data needs
of urge versus small anas due to the
intractability of tha Oj nonattainment
problem, and to recognize the potential
-fflf^mmiff impact of implementation CTI State
and locil government Populaico figure*
- - -• -t *. fc _» t tVf S9
Thaaaeondtypa(2)ahi«h!chpre>ridM
eoeapraheasira data concerning 0» pracanor
which can serve as model evaluation tools.
(alternative or not), a State should be able to
draw condustons regarding popnlati
sustnflacttha
cansus
en
provided to
••rrmlrin* rm/
direction on high 0* dara,
• Note also that O» «r«at (paalt day)
— • -^ • • '
iwport. Specific yildinra
natworicnquinmanoi Is
networit
exporun and conduct t
•?>
nquinmants an outlinad inTabla 2.
TA8L£ 2.—PAMS M»flUUU MOfffTORWO
NETWORK REOUWEMEKTS1
Jdt
Overall, the PAMS network
one of several complementary means.
together with """^""g and analysis of other
data bases (e^. inventories) and availability
of control technology, etc, for State* to
jUSUijr 10V AUOUlUtj^ftUUB wl VAi*UJ2£ \AJDUWl
grams, design new programs, and evaluate
iron course* of actions for O» controL
t Period-PAMS precursor
* BmtiiA^y
throughout the months of June, July and
August (as a minimum) when peak Oj value*
an expected in each ana: however, precursor
y^fmifnrffig ^yririff the entin Oi season fry
the ana is preferred. Alternate precursor
Yyij^tfirjmft periods may be submitted fr
approval as a part of the PAMS network
description required by $ 58.40. Change* to
the PAMS monitoring period must be
identified ^"""g the annual SLAMS
Network Review specified in 5 5E.20, PAMS
O) monitors must adhere to the O)
mnaUnring season specified in section 2J of
appendix D. To ensun a degree of national
' [for tha 1993 season
PopuMonofMSA'
CMSAornaneoaln-
fnertarea*
Less »isn 500.000 -
600,000k)
MOCQJX6.
XOO&OOOto
2.000.000.
More t>en 2£00.000
Re-
quired
Kai*
B
O
s .
D
P)
P)
O
8
O
n
o
MnV
mum
'•aped-
eSd
voc
sUITV
fte-
^sp
AorC
AerC
AorC
B
AorC
AorC
B
B
AorC
AorC
B
B
AorC
AorC
MH-
•M1I
ceroonyt
earn-
y*jfl
quen-
DorF*
E
E
E
E
E
forecasting such high O» days
auani the stipulation of what
meeorological conditions constitute a
potential high 0» day; monitoring could then
be triggered only Tia meteorological
projections. The O» event fareeasting and
«B.flsiitoiinfl «/"itait»^ yVi».iti^ ^0 submitted as a
part of the network description nqaired by
i$ 5C.40 and M.41 and should ba reviewed
during each annual SUMS Network Review
specified in 5 M^X
4J TnuKnbnPariod. A variable period
of time is pioposed far phasing in the
operation of all nquted PAMS. Within 1
year after (1) February 12. 1993. (2) or data
of ndestanation or yf^^yt^ftt^.|H«iiQ Q£ any
existing Oj TMratialnmnnt ana to serious,
severe, or extreme, or (3} the designation of
ft new area yrd ^fa
One in 3-day sampling—June 3.1993.
One in 6-day sampling—June 6.1993.
These monitoring dates will thereby be
coincident with the preriouslyectablished.
'O) and NOz (IndUdng NO and NO])
atoutt bt eendnuouc measuremertts.
*WMef>«v«r arte It taroer.
»S«e Rggre 1.
'Fr*qu«ncy Regulremena are as teBowc A-SoM
at/note*
intermittent schedule ^nf peTti^ilttf matter*
States initiating sampling earlier (or later)
than June 3,1993 should adjust their
schedules to ^^^4+ with this national
schedule •
4.4 Minimum UoafaringNftmtt
jfajMtrmmmntf Tb* minimum nouired
number and type of monitoring sites mr"^
sampling requirement* an based on the
population of the affected MSA/O4SA or
• acmittihimimt ana (whlcherer is larger). The
MSA/OASA basis for monitoring network
requirements was choean because h typically
is the most npnsantathre of the ana which
contributing to ""T******™***"* Thf MSA/
GitSA emissions density can also be
affectively and conveniently portrayed by the
surrogate of population. Additionally, a
network which is adequate to characterize
tha ambient air of an MSA/QitSA often must
extend beyond tha boundaries of such an
evety twd day and on* addtonel
24-hour Mrrde ewry ebdh day during the mentoring
period: B— Eight 3-hour MmptM, ewry day during
fr» monittxing period and 004 addWontl 24-hour
aarnple every ttaoi day yeer-reund; C— Sgnt a^eur
eemptee on tne 9 peek Oj deys pk*
seven, or extreme Oi nonattainment a.
minimum of one type 12) site must be
operating. Operation Ot the remaining sites
must, at a minimunVbe pTiund in at tha rats
of one site per year during subsequent yean
as outlined in the approved PAMS network
description provided by the State. -
4.6 Meteorological MoaHatinf. In order to^
support monitoring objectives associated
with the need for various air quality analyses,
modal inputs and parfhrmanra evaluations.
meteorological monitoring t«*rf"«tinfl wind
measurements at 10 meters above ground is
required at each PAMS site. Monitoring
should begin with site establishment In
addition, upper air meteorologies!
monitoring is required for eecn PAMS are*.
Upper air monitoring should be initiated as
soon as possible, but no later man 2 yean
after (1) February 12.1993. (2) or data of
i of any
dey, eigtt 3-hour aampiM every »ian dey. and one
adpjttonal i<-ho*g aampte every ebtft d»y. during the
monaofing ptnoci O Eight 9^wur aarnpies every
turd dey during vw montortng period; E— Eight »•
hour «urp<«* every dey dumg ffw montortng parted;
F— Eight 3-hour larnpiee on V* 5 peak Oj days pba
eee* prwioue dey and eight 3-hour aanip.ee evwy
efatf) day during tne mentoring period (NOTE:
must* sample* taken on a dairy be** cruet beoki
at iriOrtgnt and coneM o. aequentlat, nor*-
overUpptng aunplng period*.)
*Careonyi eemoNng trequeney must matri ffte
eheeen apedead VOC frequency.
Note tut .ne ue* o( Frequende* C or F noubea
fte submBal of an ozone event torecasOng echame.
existing Oj nonattainment area to serious,
seven, or extreme, or (3) the designation of
a new area and rlsftlfiffit^1**1 to f^jQ.^
seven, or extreme Oj nnnarralTiTTumt The
upper air monitoring site may be located
separately from the type (1) through (4) sites,
but the location should be representative of
the upper air data in the nonattainment ana.
Upper air meteorological data must be
collected during those days specified for
monitoring by the sampling frequencies in
Table 2. of section 4.4 of this appendix D in
accordance with current EPA guidance.
For purpose* of network implementation * .. _ .. , _
andtrinsffl^mreccmmendsthe •StcUonSofAppndixD /AmencfeoJ
following priority order for the establishment 13. References 19 through 32 an added to
of sites: section 6 of appendix D to read as follows:
• The type (2) site which provides the ' - . .
most comprehensive data concernintOj e-fle/ereneei
precursor emissions and toxic air pollutants, '* * *
-------
8474 Federal Register /-Vol. SB. No. 28 / Friday. February 12,1993 / Rules and Regulation
19. Enhanced Ozone Monitoring Netwodc
Design ud Siting Criteria Guideline
Document Office of Air Quality Planning '
Protection Agency, Research Triangle Park,
NC 27711. EPA 450/4-91-033. November
1991.
20,Technical Anil*"***P''"^'"'"!!1^For
Sampling and Analysis of Ozone Precursors.
Atmospheric Rejeerch and Exposure
Assessment Laboratory, U.S. EuiUuinrutntal
PntactioB Agency. Research Triangle- Park,
NC 27711. EPA 600/8-41-215. October 1981.
21. Quality Assurance Handbook far Air
Pollution Measurement Systems: Volume IV.
Meteorological Measurements. Atmotpheric
Research and Exposure Aaaeaameat
Laboratory, U.S. Environmental Protection
Agency, Research Triangle Park. NC 27711.
EPA 600/4-90-0003. August 1989.
22. Criteria for Assessing the Role of
Transported OzoM/Precursars in Ozone
Non-attainment Areas. Office of Air Quality
Planning •T><^ Standards, VS, ^f^^mmnfii^i
Protection Agency, Research Triangle Park.
NC 27711. EPA-tSOM-91-015. May 1991.
23. Guideline for Regulatory Application of
the Urban Airshed Model Office of Air
Quality Planning and Standards, U.S.
Environmental Protection Agency, Research
Triangle Park. NC 27711. EPA-tSO/4-91-
013. Jury 1991.
24. Ambient Air Monitoring Data Quality
Objectives (DQOs) for the Photochemical
Assessment Monitoring Stations (PAMS)
Program. Guideline Document Office of Air
Quality planning and Standards, U.S.
Environmental Protection Agency, Research
Triangle Park. NC 27711. Draft Report July
1992.
25. Shao-Hung Chu. "Using Windrose Data
to Site Monitors of Osone and Its
Precursors", Office of Air Quality Planning
and Standards, U.S. Environmental
Protection Agency. Research Triangle Park,
NC 27711. Draft Report June 1992.
26. Lewis, Charles W., and Teri L Conner,
"Source Reconciliation of Ambient Volatile
Organic Compounds Measured in the Atlanta
1990 Summer Study. The Mobile Source
Component", Atmospheric Research and
Exposure Assessment Laboratory, U.S.
Environmental Protection Agency. Research
Triangle Park, NC 27711. September 1991.
27. Fujlu, Eric M.. Bart B. Croes. Charles
L. Bennett. Douglas R. Lawson. Frederick W.
Lurmann, and Hilary H. Main. "Comparison
of Emission Inventory and Ambient
Concentration Ratios of CO. NMOG. and NOx
in Californ! Vs South Coast Air Basin", I. Air
and Waste Management Association 42364-
276. March 1992.
28. Nelson, P. P., S. M. Quigley and M. Y.
Smith. "Sources of Atmospheric
Hydrocarbons in Sydney: A quantitative
Determination Using • Source Rfwt^^Vk"1
Technique", Atmospheric Environment Vol
17, No. 3.1983.
29. Mayrsolm. H. and L H. Cnbtree.
"Source Reconciliation of Atmospheric
Hydrocarbons", Atmospheric Environment
Vol 10.1976.
30. Maynohn, Henry, )amee H. Crabtree.
Mutsuo Knnmoto, Ray D. Sotbem. and
Henry Mano, "Source Reconciliation of
Atmospheric Hydrocarbons 1974",
Atmospheric Environment Vol 11. 1977.
31. Analysis of the Ambient VOC Data
Collected in the Southern California Air
Quality Study. State of California Air
Resource* Boerf-Reeearch Division, 1600
15th Street. Sacramento, CA 95814, Final
Report Contract No. A832-13a February,
1992.
32. Purdue, Larry L, "Summer 1990
'Atlanta Ozone Precursor Study, preeented at
the 64th Annual Meeting and Exhibition of
HI^ Air **"^ Waste Management Association.
Vancouver, British OM^^blai r*^"!^ June
1991.
14. Appendix B la amended by adding a
must be Included m the 270* arc. If the probe
is located on the ride of the. building, 180*
clearance Is required.
10J -Spacing /wra flood*, ft is Important
in the probe siting process to minlmia
destructive interferences from sources of
nitrogen oxide (NO) since NO readily reacts
with Ov Table 5 below provides the required
minimum separation distances between
roadways and PAMS (-^mting upper air
ff stations)!
TABLE 5.—SEPARATION DISTANCE
BETWEEN PAMS AND ROADWAYS
(Edge o( Nearest Tiaflc Lam]
paragraph after the first paragraph in
section 9, redetignating sections 10, 11, and
12 as sections 11, IX and 13, and adding a
new section 10, redesignating Table B as
Table 6 in newly redesignated section 12,
and adding a new Table 5 in new section 10,
minding the last sentence in newly .
redesignated section 11 to add reference to
PAMS, and amending newly redesignated
section 12 by adding an entry to the bottom
of Table 6 far VOC to read as fellows:
Appendix E-Probe Siting Criteria for
Ambient Air Quality Monitoring
For VOC monitoring at those SLAMS
designated as PAMS, FEP teflon is
unacceptable as the probe material because of
VOC adsorption and desorption reactions on
the FEP teflon. Borosilicate glass, stainless
steel, or its equivalent are the acceptable
probe materials for VOC and carbonyl
sampling. Care must be. taken to ensure that
the sample residence time is 20 seconds or
less.
10. Photochemical Assessment Monitoring
Stations (PAMS)
10.1 Horizontal and Vertical Probe
Placement The height of the probe inlet
must be located 3 to 15 meters above ground
level This range provide* e practical
compromise for finding suitable sites for the
multipollutant PAMS. The probe inlet must
also be located more than 1 meter vertically
or horizontally away from any supporting
structure.
10.2 Spacing jram.Obstructions. The
probe must be located away from obstacles
and buildings such that the distance between
the obstacles and the probe inlet is at least
twice the height that the obstacle protrudes
above the sampler. There must be
unrestricted airflow in an arc of at least 270*
•round the probe Inlet Additionally, the '
predominant wind direction for the period of
greatest pollutant concentration (as described
for each site in section 4.2 of appendix D)
Roadway average daty traffic
vehicles per oey
«10,000
1S£OQ ..
20 .000 ,
70X900 —
>110,OQO
VMreunaapera*
afldtMore
1
20
30
SO
100
>2SO
1 Dtstarcee should be htarpoMad teed en MBc
Row..
Type (i), (3) and (4) sites an intended to be
regionally representative and should not be
unduly influenced by nearby roadways.
Similarly, a nearby roadway should not act
as a local depressor of Oj concentrations for
type (2) and (3) sites.
10.4 Spacing ftmn Trees. Trees can
provide surfaces for adsorption and/or
reactions to occur and can obstruct tanas!
wind flow patterns. To mhitml** these
effects at PAMS, the probe inlet should be-
placed at least 20 meters from the drip line
of trees. Since the scavenging effect of t^es
is greater for Oi than for tie other criteria
pollutants, strong consideration of this effect
must be given in locating the PAMS probe
Inlet to avoid this problem. Therefore, the
samplers must be at least 10 meters from the
drip line of trees that are located between the
urban city core area and the sampler along
the-appropriate wind direction.
10.5 Meteorological Measurements. The
10-meter meteorological tower at each PAMS
site should be located so that measurements
can be obtained that ire not Immediately
influenced by surrounding structures ud
trees. It is important that the meteorological
data reflect the origins of, and the conditions
within, the air mass containing the pollutants
collected at the probe. Specific guidance on
siting of meteorological towers U provided in
references 31 and 32.
11. Waiver Provision*
• • » • •
For those SLAMS also designated as
NAMS or PAMS. the request will be
forwarded to the Administrator.
12. Discussion and Summary
-------
Federal Register / VoL 88. No. 28 / Friday, February 12.1993 / Rules and Regulations 8475
TABLE fe-Suutunr OP Paoee Snwo CRITERIA
km. Mian
Hortzonbl*
voc
9-15
>1
>1 1. Should be >» mmn torn tie drip** and muet b> 10 meien fcomtte drtpfc* »hen t»
cteaneflan _ . -
Iran prate InM ID obiiftdi nut te •! liutt^os thv
-
8. Uu« t** unrMtHetod air flow In an ire of at hut 2nr veund •» prate InM «nd M pr»-
Oomtant «M dnotan tar f» (wrtod e( «(MtMt pokMrt eoncwtttiton (M dMotMd fcr
Meh DM ki Mdton O of ippwidb 0) IBMI b* todud^ to v» 270* we. I pate baud en
tM ild* o( « buUng urvMMaad air low nu« to 1W.
4. 8|Mdng horn mdiw
ti In ntannM to Mil. p>np«^ or p««)ouMi toatad an tM raoL
• !S.R
-------
EPA-454/B-93/051
Appendix B
Revision No. 0
Date: March 1994
Page B-l
APPENDIX B
METEOROLOGICALLY ADJUSTED OZONE TRENDS IN URBAN AREAS
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MAX TEMPERATURE
TEAR
REL HUMIDITY
TEAR
CLOUO COVER
TEAR
WIND SPEED AM
TEAR
WIND SPEED PM
MIXING HEIGHT
TEAR
TEAR
FIGURE 1. Chicago Meteorological Data
220
200
180
160
140
120
100
80
60
CHICAGO OZONE TRENDS
99 TH PERCCNT1LE—DAILY MAXIMUM (JUNE-SEPT)
1981 1982 '1983 1984 1985 1986 1987 1988 1989 1990
YEAR
FIGURE 2. Ozone Trend Statistics with 95* Confidence Limits
-------
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-------
EPA-454/B-93/051
Appendix C
Revision No. 0
Date: March 1994
Page C-l
APPENDIX C
GUIDELINE FOR THE INTERPRETATION
OF OZONE AIR QUALITY STANDARDS
-------
United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park NC 27711
EPA-450/4-79-003
OAQPSNo. 1.2-108
January 1979
Air
Guideline Series
Guideline for the
Interpretation of
Ozone Air Quality
Standards
-------
EPA-450/4-79-00
OAQPS No. 1.2-i
Guideline for the
Interpretation of Ozone
Air Quality Standards
Monitoring and Data Analysis Division
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air, Noise, and Radiation
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
January 1979
-------
OAQPS GUIDELINE SERIES
The guideline series of reports is being issued by the Office of Air Quality
Planning and Standards (OAQPS) to provide information to state and local
air pollution control agencies, for example, to provide guidance on the
acquisition and processing of air quality data and on the planning and
analysis requisite for the maintenance of air quality. Reports published jn
this series will be available - as supplies permit - from the Library Services
Office (MD-35), U.S. Environmental Protection Agency, Research Triangle
Park, North Carolina 27711; or, for a nominal fee, from the National
Technical Information Service, 5285 Port Royal Road, Springfield, Virginia
22161. . X> .;,, . _ : 7- :
Publication No. EPA-450/4-79-003
(OAQPS No. 1.2-108
ii
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Table of Contents
— 1. INTRODUCTION .. 1
1.1. Background 2
1.2. Terminology 3
1.3. Basic Premises 4
2. 'ASSESSING COMPLIANCE 7
2.1. Interpretation of "Expected Number" 7
2.2. Estimating Exceedances for a Year 8
2.3. Extension to Multiple Years 12
2.4. Example Calculation 1"
3. ESTIMATING DESIGN VALUES 17
3.1. Discussion of Design Values 17
3.2. The Use of Statistical Distributions 18
3.3. Methodologies 20
3.4. Quick Test for Design Values 28
3.5. Discussion of Data Requirements 29
• 3.6. Example Design Value Computations 31
4. APPLICATIONS WITH LIMITED AMBIENT DATA 35
5. REFERENCES - . 37
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1. INTRODUCTION
The ozone National Ambient Air Quality Standards
(NAAQS) contain the phrase "expected number of days per
calendar year." [1] This differs from the previous
NAAQS for photochemical oxidants which simply state a
particular concentration "not to be exceeded more than
once per year." [21 The data analysis procedures to be
used in computing.the expected number are specified in
Appendix H to the ozone standard. The purpose of this
document is to amplify the discussions contained in
Appendix H dealing with compliance assessment and to
indicate the data analysis procedures necessary to de-
termine appropriate design values for use in developing
control strategies. Where possible, the approaches
discussed here are conceptually similar to the proce-
dures presented in the earlier "Guideline for
Interpreting Air Quality Data With Respect to the
Standards" (OAQPS 1.2-008, revised February, 1977). C31
However, the form of the ozone standards necessitates
certain modifications in two general areas: (1) ac-
counting for less than complete sampling and (2) incor-
porating data from more than one year.
Although "the interpretation of the proposed stan-
dards may initially appear complicated, the basic prin-
ciple is relatively straightforward. In general, the
average number of days per year above the level of the
standard must be less than or equal to 1. In its
simplest form, the number of exceedances each year
would be recorded and then averaged over the past three
years to determine if this average is less than or
equal to 1. Most of the complications that arise are
consequences of accounting for incomplete sampling or
changes in emissions.
Throughout the following discussion certain points
are assumed that are consistent with previous guidance
t3] but should be reiterated here for completeness.
The terms hour and day (daily) are interpreted respec-
tively as clock hour and calendar day. Air quality
data are examined on a site by site basis and each in-
dividual site must meet the standard. In general, data
from several different sites are not combined or aver-
aged when performing these analyses. These points are
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-discussed in more detail elsewhere. [33
This document is organized so that the remainder
of this introductory section presents the background of
the problem, terminology, and certain basic premises
that were-Used in developing this guidance. This is
followed by a section which examines methods for deter-
mining appropriate design, values. The final section
discusses approaches that might be employed in cases
without - ambient monitoring data. This last section is
brief and fairly general, because it treats .an... aspect
of the problem which would rbe*-expected to rapidly
evolve once these new forms of the NAAQS become
established. In several parts of this document the ma-
terial is developed in a conversational format in order
to highlight certain points.
1.1. Background
The previous National Ambient Air Quality Standard
(NAAQS) for oxidant stated that no more than one hourly
value per year should exceed 160 micrograms per cubic
meter (.08ppm). [2] With this type of standard, the se-
cond highest value for the year becomes the decision-
making value. If it is above 160 micrograms per cubic
meter then the standard was exceeded. This would ini-
tially appear to be an ideal type of standard. The
wording is simple and the interpretation is obvious-or
is it? Suppose the second highest value for the year
is less than 160 micrograms per cubic meter and the
question asked is, "Does this site meet the standard?"
An experienced air pollution analyst would almost
automatically first ask, "How many observations were
there?" This response reflects the obvious fact that
the second highest measured value can depend upon how
many measurements were made in the year. Carried to
the absurd, if only one measurement is made for the
year, it is impossible to exceed this type of standard.
Obviously, this extreme case could be remedied by re-
quiring some minimum number of measurements per year.
However, the basic point is that the probability of de-
tecting a violation would still be expected to increase
as the number of samples increased from the specified
minimum to the maximum possible number of observations
per year. Therefore, the present wording of this type
of standard inherently penalizes an area that performs
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more than the minimum acceptable amount of monitoring.
Furthermore, the specification of a minimum data com-
pleteness criterion still does not solve the problem of
what to do with those data sets that fail to meet this
criterion*
A second problem with the current wording of the
standard is not as .obvious but becomes more apparent
when considering what is involved in maintaining the
standard year after year. For example, suppose an area
meets the standard in the sense that only one value for
the year is above 160 mi crogr arcs' per cubic meter.
Because of the variability associated with air quality
data, the fact that one value is above the standard
level means that there is a chance that two values
could be above this -standard level the next year even
though there is no change in emissions. In other
words, any area with emissions and meteorology that can
produce one oxidant value above the standard has a de-
finite risk of sometime having at least two such values
occurring in the same year and thereby violating the
standard. This situation may be viewed as analogous to
the "10 year flood" and "100 year flood" concepts used
in hydrology; i.e., high values may occur .in the future
but the likelihood of such events is relatively low.
However, with respect to air pollution any rare viola-
tion poses distinct practical problems. From a control
agency viewpoint, the question arises as to what should
be done about such a violation if it is highly unlikely
to reoccur in the next few years. If the decision is
made to ignore such a violation then the obvious impli-
cation is that the standard can occasionally be
ignored. This is not only undesirable but produces a
state of ambiguity that must be resolved to intelli-
r.ently assess the risk of violating the standard. In
oti.er words, some quantification is needed to describe
what it means to maintain the standard year after year
in view of the variation associated with air quality
ciata. The wording of the ozone standard is intended to
alleviate these problems.
1.2. Terminology
The term 'daily maximum value' refers to the maxi-
mun hourly ozone value for a day. As defined in
Appendix H, a valid daily maximum means that at least
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75$ of the hourly values from 9:01 A.M. to 9:00 P.M.
-(•fcST) were measured or -at least one hourly value ex-
ceeded the level of the standard. This criterion is
intended to reflect adequate monitoring of the daylight
hours while allowing time for routine instrument
maintenance. The criterion also ensures that high
hourly values are not omitted merely because too few
values were measured. It should be noted that this is
intended, as a minimal criterion for completeness and
not as a recommended monitoring schedule.
A final point worth noting concerns terminology.
The term "exceedance" is used throughout this document
to describe a daily maximum ozone measurement that is
above the level of the standard. Therefore the phrase
"expected number of exceedances" is equivalent to "the
expected 'number of daily maximum ozone values above the
level of the standard."
1.3- Basic Premises
By its very nature, the existence of a guideline
document implies several things: (1) that there is a
problem, (2) that a solution is provided, and (3) that
there were several alternatives considered in reaching
the solution. Obviously, if there is no problem then
the guideline is of limited value, and if there were
not some alternative solutions then the guidance is
perhaps superfluous or at best educational. The third
point indicates that the "best" alternative, in some
sense, was selected. With this in mind, it is useful
to briefly discuss some of the key points that were
considered in judging the various options. The purpose
of this section is to briefly indicate the criteria
used in developing this particular guideline.
The most obvious criterion is simplicity. This
simplicity extends to several aspects of the problem.
When someone asks if a particular area meets the stan-
dard they expect either a "yes" or "no" as the answer
or even an occassional "I don't know". Secondly, this
simplicity should extend to the reason why the standard
was met or violated. If a panel of experts is required
to debate the probability that an area is in compliance
then the general public may rightly feel confused about
just what is being done to protect their health. Also,
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the more clear-cut the status of an area is (and the
reasons why) the more likely it is that all groups in-
volved can concentrate on the real problem of maintain-
ing clean air rather than arguing over minor side
issues.
While simplicity is desirable, if the problem is
complex the solution cannot be oversimplified. In oth-
er words, the goal is to develop a solution that is
simple, and yet not simple-minded. In order to do
this, the approach taken in.this document is to recog-
nize that there are two questions involved in determin-
ing compliance: (1) was the standard violated? and (2)
if so, by how much? The first question is the simpler
of the two in that a "yes/no" answer is expected. The
-second question implies both a quantification and a de-
termination of what to do about it. Therefore, it
seems reasonable to have a more complicated procedure
for determining the second answer.
In addition to the trade-offs between simplicity
and complexity another problem is to allow a certain
amount of flexibility without being vague. There are
several reasons for allowing some degree of
flexibility. Not only do available resources vary from
one area to another but the complexity of the air pol-
lution problems vary. An area with no pollution prob-
lem should not be required to do an extensive analysis
just because that level of detail is needed someplace
else. Conversely, an area with sufficient resources to
perform a detailed analysis of their pollution problem
to develop an optimum control strategy should not be
constrained from doing so simply because it is not war-
ranted elsewhere. Furthermore, a certain degree of
flexibility is essential to allow for modified monitor-
ing schedules that are used to make the best use of
available resources.
In addition to these points concerning simplicity
and flexibility, certain other considerations are of
course involved. In particular, the methodology em-
ployed cannot -nerely ignore high values for a particu-
lar year simply because they are unlikely to reoccur.
The purpose of the standard is to protect against high
values in a manner consistent with the likelihood of
their occurrence.
A final point is that the proposed interpretation
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should involve a framework that could eventually be ex-
tended to other pollutants, if necessary, and easily
modi-fled in the future as our. .knowledge and understand-
ing of air pollution increases.
It should be noted that no specific mention is
made of measurement error in the following discussions.
While it would be naive to assume that measurement er-
rors do not occur, at the present time it is difficult
to allow for measurement errors in a manner that is not
tantamount to re-defining the level of the standard.
Obviously there is no question that data values known
to be grossly in error should, be. corrected or
eliminated. In fact the use of multiple years of- data
for the ozone .standards should facilitate this process.
The more serious practical problem is with the level of
uncertainty associated with every individual
measurement.- The viewpoint taken here is that these
inherent accuracy limitations are accounted for in the
choice of the level of the standard and that equitable
risk from one area to another is assured by use of the
reference (or an equivalent) ambient monitoring method
and adherence to a required minimum quality assurance
program. It should be noted that the stated level of
the standard is taken as defining the number of signi-
ficant figures to be used in comparisons with the
standard. For example, a standard level of .12 ppm
means that measurements are to be rounded to two deci-
mal places (.005 rounds up), and, therefore, .125 ppm is
the smallest concentration value in excess of the level
of the standard.
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2. ASSESSING COMPLIANCE
This section examines the ozone standard with par-
ticular attention given to the evaluation of
compliance* This is done in several steps. The first
is a discussion of the . term "expected number." Once
this is defined it is possible to consider the in-
terpretation when applied to several years of data or
to less than complete sampling data. An example calcu-
lation is included at the end of this section to sum-
marize and illustrate the major points.
2.1".- Interpretation of "Expected Number"
The wording of the ozone standard states that the
"expected number of days per calendar year" must be
"equal to or less than 1." The statistical term
"expected number" is basically an arithmetic average.
Perhaps the simplest way to explain the intent of this
wording is to give an example of what it would mean for
an area to be in compliance with this type of standard.
Suppose an area has relatively constant emissions year
after year and its monitoring station records an ozone
value for every day of the year. At the end of each
year the number of daily values above the level of the
standard is determined and this is averaged with the
results of previous years. As long as this arithmetic
average remains "less than or equal to 1" the area is
in compliance. As far as rounding conventions are
concerned, it suffices to carry one decimal place when
computing the average. For example, the average of the
three numbers 1,1,2 is 1.3 which is greater than 1.
Two features in this example warrant additional
discussion to clearly define how this proposal would be
implemented. The example assumes that a daily ozone
measurement is available for each day of the year so
that the number of exceedances for the year is known.
On a practical basis this is highly unlikely and,
therefore, it will be necessary to estimate this
quantity. This is discussed in section 2.2. In the
example it is also assumed that several years of data
are available and there is relatively little change in
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-emissions. This is discussed in more detail in section
2.3.
The key point in the example is that as data from
additional years are incorporated into the average this
expected number of exceedances per year should
stabilize. If unusual meteorology contributes to a
high number of exceedances for a particular .year then
this will be averaged out by the values for other
"normal" years. It should be noted that these high
values would, therefore, not be -.ignored ^but ^rather
their relative contribution to the overall average is
in proportion to the likelihood of their occurrence.
This use of the average may be contrasted with an ap-
proach based upon the median. If the median were used
then the" •year with the greatest number of exceedances
could be ignored and there would be no guarantee of
protection against their periodic reoccurrence.
2.2. Estimating Exceedances for a Year
As discussed above, it is highly unlikely that an
ozone measurement will be available for each day of the
year. Therefore, it will be necessary to estimate the
number of exceedances in a year.. The formula to be
used for this estimation is contained in Appendix H of
the ozone standard. The purpose of this section is to
present the same basic formula but to expand upon the
rationale for choosing this approach and to provide il-
lustrations of certain points.
Throughout this discussion the term "missing
value" is used in the general sense to describe all
^ays that do not have an associated ozone measurement.
It. is recognized that in certain cases a so-called
"r.issing value" occurs because the sampling schedule
ci:.i not require a measurement for that particular day.
Such, nissing values, which can be'viewed as "scheduled
niissinR values," may be the result of planned instru-
ment -naintenance or, for ozone, may be a consequence of
a seasonal monitoring program. In order to estimate
the number of exceedances in a particular year it is
necessary to account for the possible effect of missing
values. Obviously, allowance for missing values can
only result in an estimated number of exceedances at
least as large as the observed number. From a practi-
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cal viewpoint, this means that any site that is in vio-
"lation of the standard based upon the observed number
of exceedances will not change status after this
adjustment. Thus, in a sense, this adjustment for
missing values is required to demonstrate attainment,
but may not be necessary to establish non-attainment.
In estimating the number of exceedances in cases
with missing data, certain practical considerations are
appropriate. In some areas, cold weather during the
winter makes it very unlikely that high ozone values
would occur. Therefore it is possible to discontinue
ozone monitoring in some localities for limited time
periods with little risk of incorrectly assessing the
status- of the area. As indicated in Appendix H, the
proposed monitoring regulations(CFR58) would permit the
appropriate Regional Administrator to waive any ozone
monitoring requirements during certain times of the
year. Although data for such a time period would be
technically missing, the estimation formula is struc-
tured in terms of the required number of monitoring
days and therefore these missing days would not affect
the computations.
Another point is that even though a daily ozone
value is missing, other data might indicate whether or
not the missing value would have been likely to exceed
the standard level. There are numerous ways additional
information such as solar radiation, temperature, or
other pollutants could be used but the final result
should be relatively easy to implement and not create
an additional burden. An analysis of 258 site-years of
ozone/oxidant data from the highest sites in the 90
largest Air Quality Control Hegions showed that only 1%
of the time did the high value for a day exceed .12 pprn
if the adjacent daily values were less than .09 ppm.
*itn this in mind the following exclusion criterion may
A missing daily ozone value may be assumed to
e less than the level of the standard if the daily
.axima on both the preceding uay and the following day
'o not exceed 75$ of the level of the standard.
It should be noted that to invoke this exclusion
criterion data must be available fron both adjacent
days. Thus it does not apply to consecutive missing
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—— .. -daiLy. values. Having defined the set of missing values
that may be assumed to be less than the standard it is
possible to present the computations required to adjust
for missing data.
Let z denote the number of missing values that may
be assumed to be less than the standard. Then the fol-
lowing formula shall be used to estimate the number of
exceedances for the year: "-
-^
- eVvV(v/n)«(N-fl-2T - -• TO -
(* indicates multiplication)
Where N = the number of required monitoring
days in the year
n = the number of valid daily maxima
v = the number of measured daily values above
the level of the standard
z - the number of days assumed to be less
than the standard level, and
e = the estimated number of exceedances for
the year.
This estimated number of exceedances shall be
rounded to one decimal place (fractional parts equal to
.05 round up).
Note that N is always equal to the number of days
in the year unless a monitoring waiver has been granted
by the appropriate Regional Administrator.
The above equation may be interpreted intuitively
in the following manner. The estimated number of ex-
ceedances is equal to the observed number plus an
increment that accounts for incomplete sampling. There
were (N-n) missing daily values for the year, but a
certain number of these, namely z, were assumed to be
below the standard. Therefore, (N-n-z) missing values
are considered to be potential exceedances. The frac-
tion of measured values that were above the level of
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the standard was v/n and it is assumed that the same
•--fraction of these candidate missing values would also
exceed tl«e level of the standard.
The estimation procedures presented are computa-
tionally simple. Some data processing complications
result when missing data are screened to ensure a
representative data base, but on a practical basis this
effort..is only required for sites that are marginal
with respect to compliance.- Because the exclusion
criterion for missing values does not differentiate be-
tween scheduled and non-scheduled missing values it is
possible to develop a computerized system to perform
the necessary calculations without requiring additional
informatio-n on why each particular value was missing.
In principle, if allowance is made for missing values
that are relatively certain to be less than the stan-
dard then it would seem reasonable to also account for
missing values that are relatively certain to be above
the standard. Although this is a possibility, it will
probably not be necessary initially because such a si-
tuation would, of necessity, have at least two values
greater than the standard level. Therefore, it is
quite likely that this would be an unnecessary compli-
cation in that it would not affect the assessment of
compliance.
One feature of these estimation procedures should
be noted. If an area does not record any values above
the standard, then the estimated number of exceedances
for the year is zero. An obvious consequence of this
is that any area that does not record a value above the
standard level will be in compliance. In most cases
this confidence is warranted. However, at least some
qualification is necessary to indicate that it is poss-
ible that the existing monitorinc data can be deemed
inadequate for use with these estimation formulas. In
p.eneral , data sets that are 75% complete for the peak
pollution potential seasons will be deemed adequate.
Although the ceneral 75% completeness rule has been
traditionally used as an air quality validity criterion
the key point is to ensure reasonably complete monitor-
in}1, of those time peViods with high pollution
potential. An additional word of caution is probably
required at this point concerninp. attainment status de-
terminations based upon limited data. If a particular
area has very limited data and shows no exceedances of
the standard it must be recognized that a more intense
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~~ monitoring program could-possibly result in a determ-
ination of non-attainment. Therefore, if it is criti-
cal to immediately determine the status of a particular
area and the ambient data base is not very complete,
the design value computations presented in section 3
may be employed as a guide to assess potential
problems. The point is, that as the monitoring data
base increases, the additional data may indicate, non-
i attainment. Therefore some caution should be used when
| viewing attainment status^esignations based upon in-
f compiete data.' /: *"iilL~!~.l":~ir*''"ir"':" "J° "'" '^"~™ ~ ~' -
2.3. Extension to Multiple Years
As discussed earlier, the major change in the
ozone standard is the use of the term "expected number"
rather than just "the number." The rationale for this
modification is to allow events to be weighted by the
probability of their occurrence. Up to this point,
only the estimation of the number of exceedances for a
single year has been discussed. This section discusses
the extension to multiple years.
Ideally, the expected number of exceedances for a
site would be compared by knowing the probability that
the site would record 0,1,2,3|... exceedances in a
year. Then each possible outcome could be weighted ac-
cording to its likelihood of occurrence, and the appro-
priate expected value or average could be computed. In
practice, this type of situation will not exist because
ambient data will only be available for a limited
number of years.
A period of three successive years is recommended
as the basis for determining attainment for two
reasons. First, increasing the number of years in-
creases the stabiity of the resulting average number of
exceedances. Stated differently, as more years are
used, there is a greater chance of minimizing the ef-
fects of an extreme year caused by unusual weather
conditions. The second factor is that extending the
number of successive years too far increases the risk
of averaging data during a period in which a real shift
in emissions and air quality has occurred. This would
penalize areas showing recent improvement and similarly
reward areas which are experiencing deteriorating ozone
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air quality. Three years is thought by EPA to repre-
sent a proper balance between these two considerations.
This specification of a three year time period for com-
pliance assessment also provides a firm basis for pur-
poses of decision-making. While additional flexibility
is possible for developing design values for control
strategy purposes, a more definitive framework seems
essential when judging compliance to eliminate possible
ambiguity and to clearly" identify the basis for the
decision. - . ^
Consequently, the expected number of exceedances
per year at a site should be computed by averaging the
estimated number of exceedances for each year of data
during the past three calendar years. In other words,
if the estimated number of exceedances has been com-
puted " for 1974, 1975, and 1976, then the expected
number of exceedances is estimated by averaging those
three numbers. If this estimate is greater than 1,
then the standard has been exceeded at this site. As
previously mentioned, it suffices to carry one decimal
place when computing this average. This averaging rule
requires the use of all ozone data collected at that
site during the past three calendar years. If no data
are available for a particular year then the average is
computed on the basis of the remaining years. If in
the previous example no data were available for 1971*,
then the average of the estimated number of exceedances
for 1975 and 1976 would be used. In other words, the
general rule is to use data from the most recent three
years if available, but a single season of monitoring
data may still suffice to establish non-attaimient.
Thus, this three year criterion does not mean that
non-attainment decisions must be delayed until three
years of data are -available. It should be noted that
to establish attainment by a particular date, allowance
will be permitted for emission reductions that are
known to have occurred.
One point worth commenting on is the possibility
that the very first year is "unusual." While this could
occur, in the case of ozone most urbanized areas
already have existing data bases so that some measure
of the normal number of exceedances per year is
available. Furthermore the nature of the ozone problem
makes it unlikely that areas currently well above the
standard would suddenly come into compliance.
Therefore, as these areas approach the standard addi-
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years of. data would be available to determine
the expected number of exceedances for a year.
2.4. Example Calculation
in order to illustrate the key points that have
been discussed in this section it is convenient to con-
sider the following example for ozone.
Suppose a site has the following data history
for 1973-1980:
1973: 365 daily values; 3 days above the
standard level.
1979: 285 daily values; 2 days above the
standard level; 21 missing days satisfying
the exclusion criterion.
1980: 287 daily values; 1 day above the stan-
dard level; 7 missing days satisfying the ex-
clusion criterion.
Suppose further that in 1980 measurements were not
taken during the months of January and February (a to-
tal of 60 days for a leap year) because the cold
weather minimizes any chance of recording exceedances
and a monitoring waiver had been granted by the appro-
priate Regional Administrator.
Because the three year average number of ex-
ceedances is clearly greater than 1, there is no compu-
tation required to determine that this site is not in
compliance. However, the expected number of ex-
ceedances may still be computed using equation 1 for
purposes of illustration.
For 1973, there were no missing daily values and
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15
Jtherefore there is no need to use the estimated ex-
ceedances formula. The number of exceedances for 1978
is 3.
For 1979, equation 1 applies and the estimated
number of exceedances is:
2 +(2/285)»(365 - 285 - 21) =
2 •»• 0.1 = 2.1
For 1980, the sane
due to . the monitoring
the number of required
therefore the estimated
estimation formula is used but
waiver for January and February
monitoring days is 306 and
number of exceedances is:
(1/287)*(306 - 287 -7) =
(1/287)*(12) = 1.0
Averaging these
gives 2.1 as the
ceedances per year
calculations.
three numbers (3> 2.1, and 1.0)
estimated expected number of ex-
and completes the required
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3. ESTIMATING DESIGN "VALUES
The previous section addressed compliance with the
standard. As discussed, it suffices to treat questions
concerning compliance as requiring a "yes/no" type
answer. This approach facilitates the use of relative-
ly simple computational formulas. It also makes it
unnecessary to define the type of statistical distribu-
tion that describes the behavior of air quality data.
The advantage of not invoking a particular statistical
distribution is that the key issue of whether or not
the .standard is exceeded is not obscured by which par-
ticular distribution best describes the data. However,
once it is established that an area exceeds the
standard, the next logical question is more quantita-
tive and requires an estimate of by how much the stan-
dard was exceeded. This is done by first examining the
definition of a design value for an "expected
exceedances" standard and then discussing various
procedures that may be used to estimate a design value.
A variety of approaches are considered such as fitting
a statistical distribution, the use of conditional
probabilities, graphical estimation, and even a table
look-up procedure. In a sense each of these approaches
should be viewed as a means to an end, i.e., meeting
the applicable air quality standard. As long as this
final goal is kept in mind any of these approaches are
satisfactory. As with the previous section discussing
corripl iance, this section concludes with example calcu-
lations illustrating the more important points.
3.1. Discussion of Design Values
In order to determine the amount by which the
standard is exceeded it is necessary to discuss the in-
terpretation of a design value for the proposed
standard. Conceptually the design value for a particu-
lar site is the value that should be reduced to the
standard level thereby ensuring that the site will meet
the standard. With the wording of the ozone standard
the appropriate design value is the concentration with
expected number of exceedances equal to 1. Although
this describes the design value in words it is useful
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18
to introduce certain notations to precisely define this
quantity.
Let P(x < c) denote the probability that an obser-
vation x is less than or equal to concentration c.
This is also denoted as F(c).
Let e denote the number of exceedances of the
standard level in the year, e.g., in the case of ozone
this would be the number of daily values above .12 ppm.
Then the expected value of e denoted as E(e) may be
written as:
E(e) = P.(x > .12) « 365 = II - F( .12)] » 365
For a site to be in compliance the expected number
of exceedances per year E(e), must be less than or
equal to 1. From the above equation it follows that
this is equivalent to saying that the probability of an
exceedance must be less than or equal to 1/365.
As indicated, the appropriate design value is that
concentration which is expected to be exceeded once per
year. Alternatively, the design value is chosen so
that the probability of exceeding this concentration is
1/365. If an equation is known for F(c) then the de-
sign value may be obtained by setting 1-F(c) equal to
1/365 and solving for c. If a graph of F(c) is known
then the design value may be determined graphically by
choosing the concentration value that corresponds to a
frequency of exceedance of 1/365. Obviously in prac-
tice the distribution F(c) is not really known. What
is known is a set of air quality measurements that may
be approximated by a statistical distribution to deter-
mine a design value as discussed in the following
section .
3.2. The Use of Statistical Distributions
The use of a statistical distribution to approxi-
mately describe the behavior of air quality data is
certainly not new. The initial work by Larsen [4] with
the log-normal distribution demonstrated how this type
-------
19
"oT statistical approximation could be used. The pro-
posed form of the ozone standard provides a framework
for the use of statistical distributions'to assess the
probability that the standard will be met. An impor-
tant point in dealing with air pollution problems is
that the main area of interest is the high values. The
National Ambient Air Quality Standards are intended to
limit exposure to high concentrations. This has a
direct impact on how statistical distributions are cho-
sen to describe the data. [5] If the intended applica-
tion is to approximate the data in the upper concentra-
tion ranges then obviously it must be required that any
statistical distribution selected for this purpose has
to fit the data in these higher concentration ranges.
Initially this would appear to be an obvious truism
but, in 'many cases, a particular distribution may
"reasonably approximate" the data in the sense that it
fits fairly well for the middle 801 of the values.
This may be satisfactory for some applications but if
the top 10J of the data is the range of interest it may
be inappropriate.
Over the years various statistical distributions
have been suggested for possible use in describing air
quality data. Example applications include the two-
parameter lognormalt1!], the three-parameter
lognormal[6], the Weibull[5,73, and the exponential
distribution[5,8].' Despite-certain theoretical reser-
vations concerning factors such as interdependence of
successive values these approaches have been proven
over time to be useful tools in air quality data
analysis. The appropriate choice of a distribution is
useful in determining the design value. Viewed in
perspective, however, the selection of the appropriate
statistical distribution is a secondary objective
the primary objective is to determine the appropriate
design value. In other words, the question of interest
is "what concentration has an expected number of ex-
cecdances per year equal to 1?" and not "which distri-
bution perfectly describes the data?" Therefore, it is
not necessary to require that any particular distribu-
tion be used. All that is necessary is to indicate the
characteristics that must be considered in determining
what is meant by a "reasonable fit". In fact it will
be seen later that a design value may be selected with-
out even knowing which particular distribution best de-
scribes the data.
-------
20
There are certain points that are implicit in the
above discussion which are worth commenting upon. One
possible approach in developing this type of guidance
is to specify a particular distribution to be used in
determining a design value. This approach is not taken
here for a variety of reasons. There is no guarantee
that one family of distributions would be adequate to
describe-ozone levels for all areas of the country, for
all weather conditions, etc.- It may well be -that
different distributions are needed for different areas.
Secondly, as control programs take effect and pollution
levels are reduced the so-called "best" distribution
may change. Another point that should be emphasized
involves the distinction between determining compliance
and determining a design value. Suppose, for example,
that a statistical distribution is selected and ade-
quately describes all but the highest five values each
year. However, these five values are always above the
standard and consequently the number of exceedances per
year is always five. Such a site is not in compliance
even if the design value predicted from the approximat-
ing distribution is below the standard level. In such
a case the expected number of exceedances per year is 5
(with complete sampling) and therefore the site is in
violation. .The design value is an aid in determining
the general reduction required, but it some cases it
may be necessary to further refine the estimate because
of inadequate fit for the high values.
Methodolog ies
The purpose of this section is to present some ac-
ceptable approaches to determine an appropriate design
vniue, i.e., the concentration with expected number of
exceedances per year equal to 1. As discussed, this
-iy be alternatively viewed as determining the concen-
tration that will be exceeded 1 time out of 365.
Throughout this discussion it is important to re-
c-Y^r.IZP that the number of measurements must be treated
properly. In particular, missing values that are known
to be less than the standard level should be accounted
for so that they do not incorrectly affect the empiri-
cal frequency distribution. For example, if an area
does not monitor ozone in December, January, and
February, because no values even approaching the stan-
-------
21
"dard level have ever been reported in these months then
these observations should not be considered missing but
should be assigned some value less than the standard.
The exact choice of the value is arbitary and is not
really important because the primary purpose is to fit
the upper tail of the distribution.
In discussing the various acceptable approaches
several different cases are presented. This is in-
tended to illustrate the general principles that should
be applied in determining the design value.. Throughout
these discussions it is generally assumed that more
than one year of data is available. The difficulty
with using a single year of data is that any effect due
to year.to year variations in meteorology is obviously
not accounted for. Therefore, any results based upon
only one year of data should be viewed as a guide that
may be subject to revision.
(1) Fitting One Statistical Distribution to
Several Years of Data
One of the simplest cases is when several years of
fairly complete data are available during a time of re-
latively constant emissions. In this situation the
data can be plotted to determine an empirical frequency
distribution. For example, all data for a site from a
3-5 year period could be ranked from smallest to larg-
est and the empirical frequency distribution plotted on
semi-log paper. This type of plot emphasizes the be-
havior of the upper tail of the data as shown in Figure
1. A discussion of this plotting is contained
elsewhere. [5] Figure 2 illustrates how different
types of distributions would appear on such a plot.
The data may also be plotted on other types of graph
paper, such as log-normal or Weibull. The ideal situa-
tion is when the data points lie approximately on a
straight line. The next step is to choose a statisti-
cal distribution that approximately describes the data
and to fit the distribution to the data. This may be
rjcne by least squares, maximum likelihood estimation,
or any method that aives a reasonable fit to the top
1CS of tne data. An obvious question is "what consti-
tutes a reasonable fit?11 This can be judged visually by
plotting the fitted distribution on the sane graph as
the data points. Because of the intended use of the
distribution the degree of approximation for the top
-------
22 *
10-t
\.
V
10-2
10-3
I
I
100 200 300
S02 CONCENTRATION, ppb
400
Figure 1. Sulfur dioxide measurements for 1968 (24-hour) at CAMP station
in Philadelphia, Pa., plotted on semi-log paper.
„.,- \
C 10-2
10-3
10-
III I
\
I I I I I I
i i i i i i
i
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70
CONCENTRATION, pphm
Figure 2. Examples of lognormal, exponential, and Weibull distributions
plotted on semi-log paper. A Weibull distribution may also curve upward
for certain parameter values.
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23
-~105, 5%, 1% and even .5%.of the data must be examined.
The mos* obvious check is to examine departures of the
actual data points from the fitted distribution. As a
general rule there should be no obvious pattern to the
lack of'fit in terms of under- or over-prediction for
trend. For example, if the fitted distribution un-
derestimates all of the last eight data points by more
than 5%, then it must be established that the fitted
distribution is reasonable..,..Such an argument might in-
volve showing that the majority of these data points
all occurred .in the same period, and that the meteorolo-
gy for these ~particular days was extremely unusual.
The-claim that this meteorology was unusual would also
have to be substantiated by examining historical me-
teorological data. It should be noted that this extra
effort -is not routinely required and would only be ne-
cessary when the fit appears inadequate. The design
value corresponds to a frequency of 1/365 and in some
cases the empirical frequency distribution function
will be plotted in this range. In such cases, the fit-
ted distribution should be consistent with the empiri-
cal distribution in this range. This can be examined
graphically by locating the concentration on the em-
pirical frequency distribution function corresponding
to a frequency of 1/365. By construction, there will
be measured data points on either side of this value.
The two measured concentrations below this value and
the two measured concentrations above this value will
be used as a constraint in fitting a distribution. If
the fitted distribution results in a design value that
differs by more than 5% from all four of these measured
concentrations, some explanation should be presented
indicating the reasons for this discrepancy. It should
be noted that in some cases there may be only one,
rather than two, measured values on the empirical fre-
quency distribution with frequencies less than 1/365.
In these cases the upper constraint would consist of
one rather than two data points.
(2) Usin& the Empirical Frequency Distribution of
Several Years of Data (Graphical Estimation)
It, should be noted that if several years of fairly
complete data are available it is not necessary to even
fit a statistical distribution. The concentration val-
ue corresponding to a frequency of 1/365 may be read
directly off the graph of the empirical distribution
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, 21*
Table 1
TABULAR ESTIMATION OF DESIGN VALUE
Number of Daily
Values
365
730
1095
1460
1825
to
to
to
to
to
729
1094
1459
1824
2189
Rank of Upper - _
Bound
1
2
3
4
5
; — * Rank of Lower Data Point Used
-- : " Bound for
2
3
4
5
6
Design Value
highest value
second highest
third highest
fourth highest
fifth highest
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25
function and used as the design value.
If the data records are not sufficiently complete
then the empirical distribution function will not be
plotted for the 1/365 frequency and it will be neces-
sary to fit a distribution to estimate the design
value. However, whenever sufficient data are
available, this technique provides a convenient means
of graphically estimating.the design value.
(3) Table Look-up ._. •:,-_. ..--•..' ,
' An obvious point that can initially be overlooked
in the discussion of these techniques is that the final
choice of a design value is primarily influenced by the
few highest values in the data set. With this in mind,
it is possible to construct a simple table look-up
procedure to determine a design value. Again, it is
important to treat the number of values properly to en-
sure that the data adequately reflects all portions of
the year.
To use this tabular approach it is only necessary
to know' the total number of daily values, and then de-
termine a few of the highest data values,. For
example, if there are 1,017 daily values then the ranks
of the lower and upper bounds obtained from Table 1 are
3 and 2. This means that an appropriate design value
would be between the third- highest and second-highest
observed values. In using this table the higher of the
two concentrations may be used as the design value.
Therefore in this particular case, it suffices to know
the three highest measured values during the time
period.
This look-up procedure is basically a tabular
technique for determining what point on the empirical
frequency distribution corresponds to a frequency of
1/365. By construction, the table look-up procedure
overestimates the design value. For instance, in the
example with 1,01? values an acceptable design value
would lie closer to the lower bound. This could be
handled by interpolation between the second and third
highest values. However, rather than introduce interpo-
lation formulas it would be simpler to merely use the
previously discussed graphical procedure.
-------
26
-——For the cases that are.755 complete but still have
less than 365 days the maximum observed concentration
may be used as a tentative design value as long as the
data set was 759 complete during the peak times of the
year. In this case it must be recognized that the de-
sign value is quite likely to require future revision.
In principle, if statistical independence applied, this
maximum observed concentration would .equal or exceed
the 1/365 concentration about half the time. However,
the failure to adequately account for yearly variations
in meteorology makes any estimate .based on a.single
year of data very tentative.
(iJ) Fitting a Separate Distribution for Each Year
of Data (Conditional Probability Approach)
The previous method required grouping data from
several years into a single frequency distribution. In
some cases data processing constraints may make this
cumbersome. Therefore, an alternate approach may be
used that allows each year to be treated individually.
In considering this alternate approach it is useful to
briefly indicate the underlying framework. This parti-
cular approach uses conditional probabilities and in
most cases it would probably be more convenient to use
one of the previous methods. However, the underlying
framework of this method has sufficient flexibility to
warrant its inclusion.
Suppose that the air quality data at a particular
site may be approximated by some statistical distribu-
tion F(x|9), where 6 denotes the fitted parameters.
Suppose further that the values of the fitted parame-
ters differ from year to year, but that the data may
still be approximated by the same type of distribution.
Intuitively this would mean that while the same type of
distribution describes each year of data, the values of
the parameters would change from year to year re-
flecting the prevailing meteorology for the year. In
theory it could be possible to define a set of meteoro-
logical classes, say rn(i), so that the distribution
function of the air quality data could be defined for
each one of these meteorological classes. Then for
each meteorological class, m(i), there would be an as-
sociated air quality distribution function denoted as
F(x|m(i)), the distribution function for x given the
meteorological class m(i). Using.the standard rules of
-------
27
^conditional probability the distribution function F(x)
may be written as:
F(x) = Z {F(x|m(i))} P[m(i)]
#
JL
where Pttn(i)] is the probability of meteorological
class ro(i) occurring.
** *
Continuing this approach the expected number of
exceedances may be written as:
E(e) = Z P[x > s |m(i)] » P[ro(i)]
where s denotes the standard level.
Initially the above framework may seem to be too
theoretical to have much practical use. However, it
will be seen in Section H that this approach may afford
a convenient means of determining the expected number
of exceedances per year when limited historical data is
available. For the present discussion it suffices to
indicate how this approach may be used when ambient
data sets are available.
Suppose that five years of ambient measurements
are available. An approximating statistical distribu-
tion may be determined as discussed previously for each
year, denoted as Fi(x). This would be analogous to the
F(x!m(i)) in the above discussion. Then the distribu-
tion function of F(x) may be written as:
5
F(x)= .1, Fi(x) « 1/5
^rmf I
where Fi is analogous to F[xjm(i)] and P[m(i)] is as-
sumed to be 1/5. The design value may then be deter-
r.ineo by setting 1-F(d) r 1/365 and solving for d, the
nesif,n value. This is equivalent to determining the
concentration d so that:
.Z,[1-Fi(d)3 * 1/5 = 1/365.
^.™ I
-------
28
In general it may not be possible to explicity
solve this equation for d, but the answer may be ob-
tained iteratively by first guessing an appropriate de-
sign value.
The use of this equation can perhaps best be .il-
lustrated by a simple example with two years of data.
Suppose the data for each year may be approximated by
an exponential distribution although the parameter is
different for the two years. In particular let
FUx) = 1 -EXP(-43.4x) and
F2(x) = 1 -EXP(-37.6x).
Using the previous equation, the design value (d) must
be determined so that
1/2 EXP(-'l3.4d) + 1/2 EXP(-37.6d) = 1/365 or
365 * {1/2 EXP(-43.4d) + 1/2 EXP(-37.6d)} = 1.
If .15 is used as an initial guess for d this
equation gives a value of .92 rather than 1. If .145
is used the resulting value is 1.12 indicating that the
design value is between .145 and .15. Guessing .148
gives a value of .99,i.e.
365H/2 EXPC-43.4 « .148) + 1/2 EXP(-37.6 * .148)} =
.99
This is sufficiently close to 1 and is a reas<
stopping place in determining the design value.
reason-
able
3.4. Suiek Test for Design Values
All of the approaches in the previous section have
one thing in common; namely, their purpose. Each tech-
nique is intended to select an appropriate design
value, i.e., a concentration with expected number of
-------
29
yearly exceedances equal to 1. With this in mind a
quick check may be made to determine how reasonable the
selected design value is. Tf.is may be done by counting
the number of observed daily values that exceed the se-
lected design value and computing the average number of
exceedances per year. For example, if the selected de-
sign value was exceeded 4 times in 3 years, then the
average number of exceedances per year is 1.3.
Ideally, this average should be less than or equal to
1, but for a variety of reasons somewhat higher values
_may occur. However, if this average is greater than
"2.0 the design value is questionable. In such cases
the design value should either be changed or, if not
changed, careful examination should be performed to
substantiate this choice of a design value.
3.5.. Discussion of Data Requirements
The use of the previous approaches presupposes the
existence of an adequate data base. Both approaches
were presented in the context of having several years
of ambient data. In many practical cases the available
data base may not be so extensive. Although these sta-
tistical approaches may be used with less data, some
caution is still required to ensure a minimally accept-
able data set. In general, statistical procedures per-
mit inferences to be made from limited data sets.
Nevertheless, the initial data set must be
representative. For example, if no data is available
from the peak season, then any extrapolations would re-
quire more than merely statistical procedures.
Therefore, the input data sets should be at least 505
complete for the peak season with no systematic pattern
of missing potential peak hours. This 505 completeness
criterion should be viewed in the context of the type
of .nonitoring performed. A continuous monitor that
fails to produce data sets meeting this criteria has in
effect a down-time of more than 305. With such a hijh
percentage of down-time for the instrument even the re-
corded values should be viewed with caution.
In employing approaches that r.roup data from all
years into one frequency distribution, it should be
verified that all years have approximately the same
pattern of missinp. values. Furthermore, if the number
of measurements during the oxidant season differs by
-------
30
more—than 20* from one year to another, then the condi-
tional probability approach should be used. The reason
for this constraint is to ensure that variations in
sample sizes do not result in disproportionate
weighting of data from different years.
Another point of concern is how many years of data
should be used. Intuitively it would be reasonable to
use as many years of data as possible as long as emis-
sions have not changed "appreciably". Obviously this
suggests that some guidance be provided on what percent
change in emissions is permissible. To some degree any
such specification is arbitrary. However, the more
relevant point is that the specified percentage be
reasonable. The reason for a cut-off is to ensure that
the impact" of increased emissions is not masked by the
use of air quality data occurring prior to these emis-
sion increases. If an area is in violation of the
standard, then emission changes should be expected as
control programs take effect. Also, the design value
serves as a guide to achieving the standard and is, in
a sense, merely the means to an end rather than an end
in itself. Therefore, no more than a 20% variation be-
tween the lowest and highest years is recommended. It
should be noted that a total variation of 20} may
translate into a + or - 10% variation around the
average.
If emissions have increased by more than 20J then
additional years should not be incorporated unless the
air quality values can be adjusted for the change in
emissions. For cases in which emissions have decreased
by more than 20J the earlier data may be used after ad-
justment or used without change knowing that the design
value will consequently be conservative. Although this
document does not discuss methods for performing this
adjustment, it is useful to mention the basic principle
involved. The selection of a design value inherently
implies the existence of an acceptable model for taking
an air quality value and determining the emission
reduction required to reduce this value to the
standard. In principle, then, this same model may be
used in reverse to take the emission change known to
have occurred and use the model to scale the previous
data sets. Attempting to adjust older historical data
may initially seem to be an unnecessary complication
but the more data that can be used to estimate the de-
sign value the more likely it is that a -proper design
-------
value is selected. Because considerable effort could
~be expended in revising a control strategy this addi-
tional effort may be warranted.
3.6. Example Design Value Computations
As in the previous discussion of compliance
assessment, it is convenient to conclude this section
with examples illustrating the main point involved in
applying these various techniques. For purposes of il-
lustration all four techniques are used on the same
data set. Figures 3,4, and 5 display semi-log plots of
daily ozone values for 197M, 1975 and 1976 at a sample
site. .These data are plotted using previously dis-
cussed conventions. [5] The horizontal axis is concen-
tration (in pprn) and the vertical axis is the fraction
of values exceeding this concentration. A horizontal
dotted line is shown at a frequency of 1/365 and the
dotted line represents a Weibull distribution approxi-
mating the data. This particular fit was done by
"eye-balling" the data, but suffices for the. purposes
of illustration. Figure 6 is a similar plot for all
three years of data grouped together. The high and se-
cond high values for the three years are: (.13 and
.12), (.16 and .16), and (.15 and .1U).
Method 1: Fitting
all three years.
a single distribution to data from
The Weibull distribution plotted in Figure 6 for
the three years of data is described by the equation:
F(x) = 1 - EXP[-(x/.0609)
2.011
Setting F(x) = 1 - 1/3^5 and solvinp, for x gives
. 1'17 which is the design value because it corresponds
to a frequency of exceedance of 1/365. Using this
quick check, there are three values above .147 so the
average number of yearly exceedarices is 1.
-------
32
s
10
0 - aD5 CONCENTRATION, »pn IL10 °'15
Figure 3. Semi-log plot of daily maximum ozone for 1975 (365 daily values).
19
0.05
0.15
0.10
CONCENTRATION, ffm
Figure 4. Semi-log plot of daily maximum ozone for 1976 (303 daily values).
120
-------
33
I US Ml
CONCENTRATION. pf«
Figure 5. Semi-log plot of daily maximum ozone for 1977 (349 daily values).
it
I I
1.11 1.15
CONCENTRATION, ppi
Figure 6. Semi-log plot of daily maximum ozone for three years: 1975,1976,1977
(1,017 daily values).
-------
Mefcbod 2: Graphical estimation
Referring to Figure 6 it may be seen that the em-
pirical frequency .distribution function crosses the
line plotted at 1/365 at a concentration of .\5 and,
therefore, this is the design value selected by this
method. .
Using the quick check there are only two data val-
ues above .15 and, therefore*, .the average number of
yearly exceedances of the design value is .67 which is
acceptable.
Method 3: Table look-up
A total of 1,017 data values were recorded during
the three year period. Using Table 1, this method says
that the second highest value may be used as the design
value. Therefore this method yields .16 as the design
value. The quick check gives 0 as the average number of
yearly exceedances of the design value although there
are two values exactly equal to this estimated design
value. As indicated earlier, this procedure is some-
what conservative in that it tends to overestimate the
design value.
Method 4: Conditional probabilities
Separate two parameter Weibull distributions were
fitted to each yearly data set as shown in the graphs.
Using the form of equation 5 gives the equation:
1.835
1/365 = 1/3 EXP{-(d/.OH67) > +
2.139
1/3 EXP{-(d/.0705) } +
2 1 &0
1/3 EXP{-(d/.0629)' }
Solving for d (by successive guesses) -gives .15 as the
design value. Using the quick check gives two values
above the .design value and therefore, an.average yearly
exceedance rate of 2/3.
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35
APPLICATIONS WITH LIMITED AMBIENT DATA
Virtually all of this discussion has focused upon
the use of ambient data. Historically, air quality
models have been quite useful in providing estimates of
air quality levels in the absence of ambient data. The
proposed wording of the standard does not preclude the
use of such models. As models that provide frequency
distributions of air quality are developed their use
with the proposed standard will be convenient.
Another potential means of estimating air quality
data involves the use of conditional probabilities.
While'the use of conditional probabilities was dis-
cussed earlier in terms of combining different years of
data, a more promising use of this technique would in-
volve the construction of historical air quality data
sets from relatively short monitoring studies. Very
limited ambient data or air quality models may be used
to develop frequency distributions for certain types of
days or meteorological conditions. Then past histori-
cal meteorological data may be used to determine the
frequency of occurrence associated with these meteoro-
logical conditions. This information may then be com-
bined using conditional probabilities to obtain a gen-
eral air quality distribution. This particular ap-
proach could even be expanded to allow for changes in
emissions.
No matter what approach is chosen the two quanti-
ties of interest are: (1) the expected number of ex-
ceedances per year and (2) the design value, i.e., that
concentration with expected number of yearly ex-
ceedances equal to 1. However, these modelling and
conditional probability constructions may make it poss-
ible to assess the risk of violating the standard in
the future based upon limited historical data.
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37
5. REFERENCES
1. 40CFR50.9
2. Fed. Reg.,36(8"O:8186(April 30,1971)
3t "Guidelines for Interpretation of Air Quality
Standards," Office of Air Quality Planning
............ and_ Standards Publ. _ U2-008 U.S.
Environmental* 'ProtectionAgency; ~ Research
Triangle Park, North Carolina, February,
1977.
4. Larsen, R.I. A Mathematical Model for
Relating Air Quality Measurements to Air
Quality Standards. U.S. Environmental
Protection Agency Research Triangle Park,
North Carolina Publication Number AP-89,
1971.
5. Curran, T.C. and N.H. Frank. Assessing the
Validity of the Lognormal Model When
Predicting Maximum Air Pollutant
Concentrations. Paper No. 75-51.3, 68th
Annual Meeting of the Air Pollution Control
Association, Boston, Massachusetts, 1975.
6. Mage, D.T. and W.R. Ott An Improved
Statistical Model for Analyzing Air Pollution
Concentration Data. Paper No. 75-51.4, 68th
Annual Meeting of the Air Pollution Control
Association, Boston, Massachusetts, 1975.
7. Johnson,T. A Comparison of the Two-Parameter
Weibull and Lognorrnal Distributions Fitted to
Ambient Ozone Data, Quality Assurance in Air
Pollution Measurement Conference, New
Orleans, Louisiana, March, 1979.
8- Breiman,L. et al. Statistical Analysis and
Interpretation of Peak Air Pollution
Measurements. Technolocy Service
Corporation, Santa Monica,California. 1978.
-------
m TECHNICAL REPORT DATA 1
(Pleate nod Inunctions OH the reverie before completing/ \
1. REPORT NO. 2.
EPA 450/4-79-003
4. TITLE AND SUBTITLE
Guideline for the Interpretation of Ozone
Air Quality Standards
7. AUTHOR(S)
ThomasjC. Curran, Ph.D
9. PERFORMING ORGANIZATION NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air, Noise and Radiation
Office of Air Quality Planning and Standards
Research Trianale Park, North Carolina 27711
12. SPONSORING AGENCY NAME AND ADDRESS
3. RECIPIENT'S ACCESSION-NO.
5. REPORT DATE J
.7sniiaT-yr 1 Q7Q •
6. PERFORMING ORGANIZATION CODE ^1
B. PERFORMING ORGANIZATION REPORT NO.
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES - - -
Special mention should be made of the contributions of William M. Cox,
Thomas B. Feagans, William F. Hunt, Jr. and Sherry L. Olson
16. ABSTRACT
This document discusses the interpretation of the National Ambient Air
Quality Standards (NAAQS) for ozone that were promulgated by the U.S.
Environmental Protection Agency in 1979. These standards differ from
previous NAAQS in that attainment decisions are based upon the expectej
number of days per year above the level of the standard. The data
analysis implications of this statistical formulation of an air
quality standard are presented for both compliance assessment and
design value estimation purposes. Example calculations are included.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
Air Pollution Standards
Design Values
Ozone
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
18. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (This Report)
TTncO acc-i -F-i
21. NO. OF PAGES
(This
20. SECURITY CLASS
Unclassified
22. PRICE
EPA Form 2220-1 (t-73)
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EPA-454/B-93/051
Appendix D
Revision No. 0
Date: March 1994
Page D-l
APPENDIX D
QUESTIONS AND ANSWERS ON THE
PHOTOCHEMICAL ASSESSMENT MONITORING STATIONS (PAMS)
NETWORK BASED ON THE APRIL 27-29,1993
TELECONFERENCE WORKSHOP
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TABLE OF CONTENTS
Section Page
INTRODUCTION 1
OVERVIEW 2
NETWORK DESIGN AND SITING 5
SAMPLING AND ANALYSIS 10
QUALITY ASSURANCE 27
MODELING AND METEOROLOGICAL MONITORING 33
DATA ANALYSIS 40
AIRS AND PAMS 43
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INTRODUCTION
The following questions and answers were compiled primarily from the Photochemical
Assessment Monitoring Stations (PAMS) Teleconference Workshop held April 27-29, 1993.
Supplemental questions and answers have been added in this document to address broader PAMS
issues and provide an overview of the regulations. The questions and answers have been
organized into the following categories: (1) Overview; (2) Network Design and Siting;
(3) Sampling and Analysis; (4) Quality Assurance; (5) Modeling and Meteorological Monitoring;
(6) Data Analysis; and (7) AIRS and PAMS.
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OVERVIEW
Question:
What are the PAMS program objectives?
Answer:
The PAMS program objectives, or data uses, include the following: National Ambient Air
Quality Standards (NAAQS) attainment and control strategies; State Implementation Plan
(SIP) control strategy evaluation; emissions tracking; exposure assessment; and support
for urban airshed modeling.
Question:
Who is affected by the 40 CFR Part 58 PAMS regulations?
Answer:
The regulations directly affect those air pollution control agencies with designated serious,
severe, or extreme ozone nonattainment areas. For the first time, States are required to
collect data, not only to determine compliance with the NAAQS but also to provide
fundamental data to aid in assessing the ozone problem.
Question:
What is the difference between standard and alternate network plans?
Answer:
The Part 58 PAMS regulations allow for two types of network plans: standard network
plans conform directly to the criteria for a network description' as described in Section
58.41 and Appendices A and D of the regulations, including all of the elements listed;
alternate network plans include one or more of the acceptable alternative network
elements, but otherwise comply with the criteria for a standard network.
Question:
What alternative elements are allowed under the alternative element provisions of the
regulations?
Answer:
The PAMS regulations contain provisions for alternative network elements in five areas:
(1) sites (number and arrangement); (2) methodology (sampling and analysis methods);
(3) monitoring season (months with the highest ozone); (4) sampling frequency; and (5)
meteorology (establishing wind directions for siting). States submitting plans containing
one or more of these alternative elements must state that the submittal is an alternative
PAMS network design. In order to be accepted, a network plan containing alternative
elements must demonstrate fulfillment of the PAMS monitoring and program objectives.
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Question:
What are the basic elements that must be included in a network plan?
Answer:
To be considered complete, a network plan must include the following elements, in
conformance with the criteria outlined in 40 CFR Part 58: (1) network overview, (2) site
identification, (3) sampling and analysis methods, (4) monitoring period, (5) sampling
frequency, (5) meteorological monitoring, (6) network implementation schedule, and (7)
quality assurance. Alternate network plans must also include the following
documentation: (1) narrative explanation of the alternative element(s); (2) justification of
the alternative element(s); and (3) demonstration of comparability.
Question:
Who will review and approve network design plans?
Answer:
Network plans are submitted first to the EPA Regional Office for preliminary review.
The plans are then forwarded to EPA's Monitoring and Reports Branch, Technical
Support Division, Research Triangle Park, NC, where they are reviewed by the PAMS
Network Review Committee, which will forward the plan along with its recommendations
to EPA Headquarters management for final approval.
Question:
Will States be able to meet in person with EPA's Office of Air Quality Planning and
Standards (OAQPS) and Regional staff to explain in detail an alternative regional plan?
Answer:
The monitoring program is envisioned as a three-way partnership between State, Regional
Office, and OAQPS staff, and communication and coordination between States and EPA
staff are encouraged in establishing alternative plans. Because of travel restrictions,
however, conference calls may be the best vehicle for such communication. Alternatively,
States are welcome to visit OAQPS staff in RTP, NC to discuss alternative plans in
person.
Question:
Where does the SEP get submitted, and what should it say?
Answer:
The SIP revision is submitted to the Regional Office, which then prepares the rulemaking.
EPA anticipates that the SIP revision covering the PAMS provisions will be a relatively
small part of the total SIP, basically, a commitment to design and install the network.
Though the revision is not regulatory in nature, it does have to go to public hearing, as
all SB? revisions do. EPA's Air Quality Management Division in conjunction with the
Technical Support Division has drafted suggested language that will be helpful to States
in developing their SIPs.
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Question:
Does an alternative plan based on a regional effort need to reference sites to specific
Metropolitan Statistical Areas/Consolidated Metropolitan Statistical Areas (MSAs/CMS As)
or can the sites be referenced to the region as a whole?
Answer:
For purposes of strategy development, if an area does have a regional network (for
instance, the northeast United States), such areas can use those monitors to develop
strategies which could be implemented region-wide. It is still important, however, that
each site be keyed to a particular MSA/CMSA. EPA would encourage even regional sites
to be keyed to one or more MSAs and not just to the region.
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NETWORK DESIGN AND SITING
Question:
How many and what type sites are required?
Answer:
A maximum of five PAMS sites is required in an affected ozone nonattainment area,
depending on the population of the MSA/CMSA. For the larger areas, EPA has
determined that the minimum network that will provide data sufficient to satisfy the
PAMS monitoring objectives should consist of five sites: (1) Site No. 1 - upwind and
background characterization site; (2) Site No. 2 - maximum representative ozone precursor
emissions impact site; (3) a second Site No. 2 in the second most prominent morning
wind direction; (4) Site No. 3 - maximum ozone concentration site; and (5) Site No. 4 -
extreme downwind monitoring site. The recommended order of implementation is Site
No. 2, No. 3, No. 1, No. 4, and last, the secondary No. 2.
Question:
What if a State does not want to use the recommended phase-in schedule?
Answer:
The regulation requires that five sites be established in five years, with Site No. 2
required as the first site to be established. But the phase-in schedule for years 2 through
5 can be in any order chosen by the State, allowing for a great deal of flexibility. For
a particular area, once Site No. 2 is in place the first year, as long as the one site per year
requirement is met, the choice of sites will be up to the particular State or local air
pollution control agency. Plans containing alternative numbers and types of sites would
be considered alternative plans and would have to be submitted in accordance with the
requirements in EPA's guidance on PAMS network plan and approval.
Question:
Does the rule provide for alternative phase-in schedules longer than 5 years?
Answer:
No, it does not. The network must be totally implemented by 1998. States that started
phase-in in 1993 get an extra year.
Question:
At the Region IV Air Monitoring Workshop, it was recommended that monitoring be
conducted at a background site. Is there a difference between Site No. 1 and the
background site referred to at the workshop?
Answer:
Site No. 1 is supposed to be the upwind background site; typically, it will be located near
the upwind edge of the photochemical modeling domain. That is the only requirement
for a background site for PAMS.
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Question:
How close should Site No. 2 be to the central business district for major point sources?
Answer:
The regulation states that Site No. 2 should be located immediately downwind of the area
of maximum precursor emissions. In an urban area, precursor emissions are expected to
come, in large part, from the central business district. In general, Site No. 2 should be
close enough to the central business district for major point sources to record higher
concentrations and get more sensitive and precise information but not so close to a
particular emission source that maximum ground level precursor concentration would be
expected. The site should be representative of the area's emissions, but should not be
unduly influenced by any particular emissions source.
Question:
What is the rationale for Site No. 2, Type "B" sampling frequency (eight 3-hour samples
every day during the monitoring period and one additional 24-hour sample every sixth
day year-round)? What will these data be used for?
Answer:
Site No. 2, as stated in the regulation, is to be located representative of the MSA's
downwind VOC emissions, to capture the "maximum precursor impact." Finding a site
which is appropriate and not unduly influenced by any particular source of emissions may
be very difficult Therefore, there is going to have to be a great deal of leeway in
looking at the particular arc in which Site No. 2 is located. Generally though, Site No.
2 should be located in that arc in the morning wind direction, downwind of the MSA,
such that it is not unduly influenced by any particular source of emissions.
Data from Site No. 2 will be used for (1) development and evaluation of imminent and
future control strategies, (2) corroboration of NOX and VOC emission inventories, (3)
augmentation of reasonable further progress (RFP) tracking, (4) verification of
photochemical grid model performance, (5) characterization of ozone and toxic air
pollutant exposures, (6) development of pollutant trends, particularly toxic air pollutants
and annual ambient speciated VOC trends to compare with trends in annual VOC
emission estimates, and (7) determination of attainment with the NAAQS for N02 and
ozone. The additional once every sixth day sampling is required for quality control
purposes and for determining annual averages of speciated VOC for air toxics
assessments.
Question:
Should Site No. 3 be the current ozone design value site?
Answer:
Site No. 3 should correspond to the maximum ozone site for the MSA/CMSA which is
located downwind. Site No. 3 may or may not be collocated with the ozone design value
site for a particular MSA/CMSA. In some cases, the design value site may be upwind
of the MSA itself and be influenced totally by long-range transport of ozone. Further,
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an existing site downwind, measuring the highest ozone levels in the area, may not be the
ideal location for Site No. 3. This determination will need to be made on a case-by-case
basis.
Question:
Regarding siting guidance, what does "undue source influence" mean?
Answer:
Criteria for dealing with undue influence from sources are covered in 40 CFR Part 58,
Appendix E. With regard to spacing from roadways, a minimum separation distance must
be maintained between roadways and PAMS monitoring sites, for example, to minimize
NO interference on ozone monitoring and minimize the influence from mobile sources.
Sites No. 1, No. 2, and No. 4, in particular, should avoid NOX interference from nearby
roadways. Generally, Site No. 2 should be placed at a location which is representative
of all the emissions of the area and not just indicate the signature of a particular source.
In terms of spatial scale of representativeness, it should be a neighborhood scale rather
than a micro or middle scale.
Question:
For submitting the network design plans, where can wind roses be obtained if they cannot
be produced by a given agency?
Answer:
Ideally, local/nearby meteorological information is used to develop wind roses. If current,
local information is not available, the wind roses produced by Headquarters can be used;
these can be obtained from Regional Offices. Two sets of roses were prepared, one for
ozone conducive days and the other for high ozone days, according to the following
criteria: for both sets of days the most recent 5- or 10-year data set for June, July and
August were used; ozone conducive criteria were used in which the temperature is greater
than 85°F, the 7 to 10 a.m. wind speeds are <10 knots, the 1 to 4 p.m. wind speeds are
<14 knots, and the 1 to 4 p.m. relative humidity is <60%; and for high ozone days in
which the criteria ozone concentration is >0.10 ppm.
The weakness in the high ozone day information is that it presumes that the current ozone
sites are located correctly. EPA has been encouraged by the fact that for most MSAs, the
wind roses for ozone conducive days correlate well with the wind roses for high ozone
days. In any case, the Agency feels that using either set of roses, the sites would be
located at least in the same quadrant, and most of the time probably within a 30° arc.
Question:
When discussing the site guidance criteria for using the wind data on high ozone days,
or on those days which exhibit the potential for producing high ozone levels (high ozone
conducive days) as in Site No. 1, which wind rose should be used? There are two
represented for each time period, categorized under the headings "conducive days" and
"observed highs."
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Answer:
If the cuirent ozone site is believed to be properly located, the wind rose based on
observed highs would probably be more appropriate. Otherwise, consideration should be
given to both.
Question:
Are AIRS Graphics printouts acceptable for emissions?
Answer:
EPA would prefer emission density maps in combination with AIRS Graphics printouts
(or equivalent) depicting the locations of the largest point emitters, if they can be
obtained. Your Regional modeler may be able to provide further assistance.
Question:
Regarding emission source information, what is the smallest point source for which
information is needed?
Answer:
For SIP inventory purposes, the VOC point source cutoff definition for VOC sources is
10 tons per year. EPA is requesting the same cutoff for PAMS network plans emissions
information.
Question:
Can episode sampling be used at Site No. 2?
Answer:
The rule allows for episodic sampling at Site Nos. 1, 3, and 4, but does not speak to it
as an allowable alternative for Site No. 2. The Agency's philosophy for criteria pollutants
is that around-the-clock sampling is required in order to capture the rare event. This same
philosophy of capturing the rare event applies to Site No. 2--as "an insurance policy,"
continuous sampling at Site No. 2 is desired. However, the Agency could consider plans
which propose less than complete or 24-hour per day sampling at Site No. 2, in those
situations where it could be demonstrated that data collected on an episodic basis or
collected at selected hours of the day are sufficient. Even if an episodic plan were to be
approved at Site No. 2, however, it would still be important to do additional intermittent
sampling to provide information on the concentration on nonepisode days, as it is equally
important to understand what is happening on the days of lower photochemical reactivity
as on the days that produce the highest ozone.
Question:
What data must be submitted to support a change to the required June, July, August
monitoring season?
Answer:
The intent of the regulation was to require at least three months of intensive sampling.
In most States, June, July, and August incorporate the periods when peak ozone values
8
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are likely to occur. Historical ozone data could be submitted to demonstrate that a
different three consecutive months (for example, July, August, and September) would
better serve the PAMS program. EPA encourages States to extend the PAMS monitoring
period whenever feasible to include the entire ozone season or perhaps the entire calendar
year. Again, plans containing alternate monitoring seasons would be considered alternate
network plans and would have to be submitted in accordance with the requirements
specified in EPA's guidance on PAMS network plan and approval.
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SAMPLING AND ANALYSIS
Question:
Should paniculate filters be used on the auto gas chromatograph (GC) system? If so, how
should they be configured and of what materials should they be constructed?
Answer:
Particulate filters should be used on the GC system. Most canisters use a stainless steel
10 micron filter which removes particles that would otherwise get into the canisters.
However, if paniculate filters are used, a maintenance program which includes periodic
checking of the filter is necessary.
Question:
What is the maximum allowable inlet line length for various auto GC systems?
Answer:
In general, there is no prescribed maximum allowable inlet line length. The concept is
that as gases are entering the system, they contact surfaces. The smaller the surface, the
less of a potential problem. Therefore, the rule-of-thumb is to minimize the surface
contact area. Silica material seems to be a good inert surface. If the tubing is coated
with the silica material to make it inert, then the larger surface may be acceptable, but
rule-of-thumb is to minimize surface areas. Further information may be found in 40 CFR
Part 58, Appendix E.
Question:
What is the shelf-life of an ambient air sample in a Summa® polished canister (without
significant hydrocarbon chemical reactions and alterations)? What is the shelf-life of a
calibration cylinder (e.g., 56 compound super-blend)?
Answer:
Generally, tests under typical conditions for ambient air samples collected in canisters
indicate a shelf-life of 14 to 30 days and probably longer (with the exception of a- and
|3-pinene, which have not been tested). However, ambient canister samples should be
analyzed as soon as practicable after collection to ensure that losses are minimized.
Calibration or retention time standards in high pressure cylinders containing the 56-
compound mixture (with the exception of a- and p-pinene) are generally stable for at
least 6 months to a year. However, problems with losses of olefinic compounds such as
2-methyl-l-pentene and isoprene have been observed.
Question:
What is the recommended frequency for the analysis of (a) the propane standard, and (b)
the qualitative multi-component retention time standard?
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Answer:
The frequency of calibration and analysis of the retention time standards will be left to
the judgement of the analyst and will be dependent on the stability of the system.
However, at least initially, the retention time standard should be analyzed daily. Further
guidance on this issue is provided in the Technical Assistance Document for Sampling and
Analysis of Ozone Precursors (TAD), Section 2.2.6 (EPA-600/8-91-215, October 1991).
Question:
Is EPA guidance available for the sampling and analysis of ozone precursors?
Answer:
Guidance is provided in the TAD. The Agency will be updating this manual in the near
future.
Question:
Given the following background information for Baton Rouge:
(1) It is a "serious" area
(2) It is Type "B" for sampling frequency requirements
(3) It has a January to December "ozone season"
(4) It has a population between 500,000 and 1,000,000; frequency type is "B"
or "E"
(5) Sampling frequency requirement "B" is daily part of the year/every sixth
day year-round
(6) Multiple-canister sampling (8, 3-hour samples) is to be run daily during
June, July, and August; and every sixth day per year, year-round
Does the Baton Rouge area's daily VOC sampling schedule run only from June through
August or will it run year-round to coincide with the ozone season?
Answer:
The ozone monitoring should be for the entire ozone season as every other ozone monitor
in the network is operated. The precursor monitoring, which includes the oxides of
nitrogen, the VOC and the carbonyls (except for any year-round component), would be
for June, July and August only. That presumes that Baton Rouge chooses June, July and
August for its monitoring season. The rule does allow for any MSA to choose a different
monitoring season if it captures the peak ozone days for that particular area. Assuming
June, July and August did encompass the peak ozone days, Baton Rouge would only be
required to operate the VOC and other precursor monitors during that time period (except
for the year-round component).
In addition, although only 3 months of precursor monitoring are required, State or local
agencies can extend that season to more than 3 months if they believe that those
additional months are critical to understanding the ozone problem in their area. However,
areas of the country with longer ozone seasons (i.e., 12 months) typically have the highest
ozone concentrations during the warmest months of the year, which usually are 3 to 6
months of that annual period.
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Question:
Why is it necessary to sample around-the-clock? Is it necessary to capture the diurnal
pattern whether by eight 3-hour samples per day or by the use of a continuous instrument
to collect hourly samples?
Answer:
Data collected "around-the-clock" will be useful for quality assurance, for establishing
trends, for evaluating control strategies, for photochemical model diagnostics, for
confirming emissions inventories, and for toxics assessments. Twenty-four hour a day
sampling refers not only to eight 3-hour samples a day, but also to the year-round 24-hour
canister component.
One of the real advantages of the PAMS network is that it provides much more data to
compare with emission inventories. It is important that the PAMS network shows data
from around-the-clock, because the inventories are around-the-clock representations,
especially for the VOC, where much of the emissions come from evaporation around-the-
clock.
The PAMS program and the ozone program in general are concerned with rare events.
Continuous sampling is preferable to try to capture the event that occurs just once or
twice a year. In terms of trying to identify the impact of certain emission changes, it may
be important to understand what changes actually occurred to the underlying diurnal
pattern. Will the diurnal pattern change when fuels are changed, for example? Will there
be a shift in the concentration observed at night? In previously collected data, higher
concentrations were recorded at night, when photochemical activity was at its lowest.
Continuous sampling provides additional sensitivity to follow data for determining trends.
Without continuous data, looking at a selected period of time during the night might mean
sampling during the wrong period of time. Some of the sites in Atlanta had very stable
patterns during the early morning hours; for example, 2:00 a.m. was particularly high.
Sampling only at that time and not continuously during the night might result in an
unrepresentative nighttime value. Thus, it is important to sample continuously throughout
these higher nighttime periods to arrive at a representative nighttime value.
Further, sampling in the evening would provide additional information on mobile source
emissions. Ozone planning has focused historically on morning emissions. Continuous
sampling would probably corroborate better the evening rush-hour emissions for mobile
sources.
In the past, the EPA has been criticized, in general, for not collecting enough data; the
National Science Academy's report addressed this issue. In the 1980s, data were
basically collected from 6 to 9 a.m. at a very limited number of sites. With such a
limited schedule, it was not possible to see what happened in the afternoon with the
biogenic factor, or with evaporative emissions. Since this is a long-term monitoring
program, it only makes sense to start off with as robust a database as possible in order
to track changes in the atmosphere over time, to answer questions which may arise in the
future.
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In addition, when reviewing ozone data, the data cycle may not be the same from day to
day, particularly at monitoring sites in areas with varying transport and stagnation types.
Transport may result in ozone peaks in the early morning or late afternoon. When
conditions are stagnant, the ozone peak may be more persistent and lingering.
Additionally, weekday emissions data differ from weekend data. Therefore, two fixed 3-
hour sampling periods may miss some of the data needed to evaluate these situations.
To summarize, continuous sampling is seen as "an insurance policy" to collect data over
the course of the entire day in order to capture the diurnal pattern and to be able to
answer the many different types of questions that could arise. In fact, in the ozone
nonattainment areas designated severe and extreme, between 1994 and 1995, fuels are
going to be reformulated and the atmosphere is going to change when this is
implemented. Continuous sampling will provide a picture of the diurnal patterns and
atmospheric constituents in those cities in 1994 and how they have changed in 1995.
>n:
Can sampling aloft be substituted for ground level monitoring of ozone and ozone
precursors?
Question:
G
precursors
Answer:
To the extent that States can assist in the model evaluation process, EPA would certainly
encourage the collection of air quality data aloft However, collecting air quality data
aloft must be balanced against some of the primary objectives of the PAMS program
which include tracking the progress of control programs and trends in emissions. If the
basic components of the PAMS program would not be jeopardized by such air monitoring
aloft, EPA would be open to complementing ground monitoring with this aloft
monitoring. However, questions remain regarding this issue, and the Agency would
consider such requests on a case-by-case basis.
Question:
Were there any interferences in the UV open path system such as weather conditions,
rain, etc.?
Answer:
The UV open path system may be vulnerable to dense fog conditions which can act as
optical obstructions in reducing the light transmission below the critical level necessary
for measuring gaseous pollutant concentrations. During these periods, however, the
OPSIS system is designed to flag the data as invalid. The ozone concentrations coming
from the UV open path system correlate very well with the ozone concentrations at a
fixed monitoring site. Since this is a photometric measurement, it is believed that those
measurements are very appropriate for ozone. Measurements of N02 and S02 have also
been made. An advantage of the system for N02 is that the measurements are direct
spectroscopic ones and not "difference-derived" as with the chemiluminescence
instruments. At the time of the Atlanta study, the measurements for hydrocarbons,
particularly benzene, toluene and xylene, were just emerging and the study found some
problems with the deconvolution software used by the differential optical absorption
13
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spectrometer to separate the interfering species from the species to be measured. The
company making the system used in Atlanta, OPSIS, is currently working to improve its
internal and data collection software, and while there are hopeful signs for future use, for
the moment, OPSIS is limited to those compounds that will absorb in the UV region of
the spectrum.
Question:
What are some suggestions about CO2 management? Any problems, solutions, or
expectations?
Answer:
CO2 is probably more of a problem in mass spectrometry work than in the case of
hydrocarbon analysis using the flame ionization detector (FED). When using narrow
internal diameter (ED) columns a problem could occur due to CO2 plugging the column.
In such cases, water removal is important and should be done. Whether or not there are
ways of taking CO2 out without taking out the VOC compounds remains to be seen.
Selective removal of particular compounds may affect the VOC. Therefore, it might be
better not to remove the CO2.
Question:
Why don't you use a Nation Dryer to eliminate water in the preconcentration direct flame
ionization detection (PDFED) method?
Answer:
About 10 years ago when the PDFDD method for estimating the total NMOC was
developed, the Nafion Dryer had not been tested adequately to be sure that it passed
NMOC without unacceptable losses. At the same time, correcting for water using the
operational baseline technique seemed to work quite well. The method was put into
service at that point The additional development work to test the performance of the
system with the Nafion Dryer was never carried out.
Question:
Define high and low VOC to NOX ratios.
Answer:
A high VOC to NOX ratio would be greater than 16-20 to 1 and a low VOC to NOX ratio
would be about 5 to 1. Most cities fall within the range of 20 to 1 to 5 to 1.
Question:
How can canisters be checked for contamination via NMOC analysis when VOC
sensitivity is 0.3 ppmC while with PAMS we are frequently looking at ambient
concentrations less than 1 ppb?
Answer:
The 0.2 or 0.3 ppmC number that is given for the detection limit is really based on
variability in background response from the canisters. The instrumental measurement
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capabilities are as much as an order of magnitude better. Contamination normally
involves several compounds so that there are several compounds included in total NMOC.
The PDFID method serves as an excellent screening tool to ensure that canisters are
cleaned properly. It is recommended that an occasional blank analysis be conducted with
the full GC system to make sure there is no single compound contamination that
constitutes a major contamination.
Question:
Can a surrogate for speciated VOC be used?
Answer:
The rule would allow for the proposal of a surrogate for speciated VOC, but the burden-
of-proof would be on the State to show that it can still provide enough information to
meet a set of balanced objectives. Currently, the Agency would consider surrogates for
speciated VOC at Site Nos. 1, 3, and 4, but feels strongly that continuous speciated VOC
at Site No. 2 is necessary.
Question:
In hindsight, regarding the Atlanta study, were hourly averages adequate for the study's
data analysis needs?
Answer:
The current automated GC systems require one hour to complete sample preconcentration
and analysis procedures. Consequently, sample frequency cannot be any greater than one
sample per hour. Hourly averages were adequate for the study's data analysis needs. The
regulations require a minimum of 3-hour sampling. The samples analyzed for the 1990
Atlanta Study were integrated over a 35-minute period with the assumption that this
period was representative of the one-hour average. It was thought that a period shorter
than 35 minutes might not be representative of an hour average.
Question:
What is meant by internal reference peaks in a gas chromatogram?
Answer:
Internal reference peaks are usually 3-4 gas chromatograph peaks used as retention time
and/or response factor references in processing the GC data. The peaks correspond to
individual compounds that are added to the sample during analysis or that are usually
present in ambient air (such as benzene, toluene, and the xylenes). If the retention times
of the internal standards shift, then adjustments to the expected retention times of all other
target compounds are made during processing to ensure correct identification. Similarly,
if the internal reference peaks are used as response factor references, they must be
compounds that are added to the system during sample collection at known amounts.
Changes in system response can be identified by comparing the response of the internal
standard to the response determined during calibration. The use of internal standards
allows for the adjustment of the analytical system for each analysis.
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Question:
We have received a canister mixture standard from a supplier of standards with certified
concentrations for propane and benzene. We saw nonlinear quantitative response between
propane and benzene (i.e., area versus ppbC). Is this likely to be caused by a collection
bias? The supplier is using a Chrompack FID measurement system or some other
method. How can this nonlinearity be adjusted when determining concentrations?
Answer:
A similar per carbon response has been seen in investigations comparing response factors
of nonmethane hydrocarbons, aromatics, paraffins and olefins. If a response is not within
5 percent, there must be something wrong with the system. There have been some
reports that a dry mix in the canister does not store well, but propane and benzene usually
store well in canisters with dry atmospheres; therefore, the problem could be the result
of a leak in the system, in the preconcentration, or some other part.
Also, some collection efficiency factors to consider when an adsorbent column is used for
sampling are trapping efficiencies and transfer of the sample to the columns. These
factors can affect the area count for carbon sensitivity as well as the linearity of the
response.
Question:
We have experienced large differences in hourly total NMOC values delivered by
collocated GC systems. The difference occurs because one system uses a serial column
arrangement while the other uses parallel columns. Differences have exceeded 100
percent and only occur on ambient air. Calibration standards are generally within 10
percent. How can this situation best be addressed?
Answer:
These differences are associated with how samples are being introduced into the system.
In this case, the different types of collection media (i.e., moisture in the sample versus
a standard mix in the dry atmosphere) may be affecting trapping efficiency or collection
efficiencies. Certainly the mixture in the atmosphere is more complicated than a
calibration standard and that may account for part of the problem. Compare the internal
compositions to see where the differences occur and try to reinvestigate the system.
These systems have all been evaluated and compared very well. The fact that they are
not comparing well suggests that there is a systematic problem (i.e., leaks in the system
or problems in the collection aspect of the system) that has to be evaluated.
In general, there is no conceptional reason why a series application versus a parallel
application would result in differences that large. Discuss those problems with the vendor
and review all the aspects of the system to see where the problem lies.
Question:
How many National Institute for Standards and Technology (NIST)-traceable standards
should be employed when determining detection levels of automated GC systems for the
list of over 50 targeted compounds?
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Answer:
The FID detector provides constant response for all compounds on a per carbon basis
requiring just one standard reference method (SRM) for detector response calibration.
Detection limits may be slightly different for each GC peak and can be determined with
the retention time standards. In some automated GC systems with dual FID serial and
parallel columns, propane will be used to calibrate one of those columns and benzene will
be used to calibrate the other FID. Since benzene SRMs are no longer available from
NIST, a certified benzene standard obtained from a cylinder gas manufacturer will be
required for calibration.
Question:
If a compound on the current targeted list of compounds is not found, can it be removed
from the list? If yes, at what detection level must this be demonstrated?
Answer:
More guidance on this may be provided as the Agency defines how to ascertain detection
limits. Certainly, compounds should not be indiscriminately removed from the list that
might play a role in the total estimate, in the chemistry, or in receptor modeling; on the
other hand, compounds which are seldom, if ever, detected should not be retained on the
target list. In addition, a number of compounds on the target lists, mostly the olefin
compounds, will be in the atmosphere at low concentrations. They usually will be at
higher concentrations in the morning; during the afternoon period they may be below
detectable limits. All of the compounds on the target list should be noticed, with the
possible exception of the natural hydrocarbons in an urban mix, at some of the sampling
periods, but not necessarily all of them.
Question:
For how many compounds should the States determine detection levels (40 CFR Part 136
Appendix B)? How many standards do States need to use?
Answer:
Detection limit is not deemed to be a critical parameter for this application because most
areas of concern will have reasonably high ambient air concentrations of VOC precursors
(particularly the ones on the target list). No requirements to determine definitive
detection limits (via 40 CFR Part 136 Appendix B) for all the listed species are planned
but it would be prudent to make this determination on at least one representative light
VOC species (e.g., propane or butane) and at least one heavy VOC species (e.g., toluene
or xylene).
Question:
The use of parallel analytical columns may result in unacceptable signal loss. How do
you compensate for this to maintain the required level of response?
Answer:
If the sample is split or if only a portion of the sample is used, signal response is reduced.
However, current automated GCs that use a splitter do have adequate sensitivity to
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monitor ambient air levels of ozone precursors down to concentrations of 0.5 ppb.
Additional sensitivity may be obtained by increasing the sample size during collection on
the primary trap provided breakthrough of target compounds does not occur and provided
unacceptable accumulations of water vapor or carbon dioxide do not occur.
Question:
Are procedures in place to allow for zero span gas challenge procedures using the field
sampling manifold systems?
Answer:
No. However, zero challenges are very important and the issue of whether or not they
are challenged through the manifold or challenged with zero canisters is going to be
discussed and addressed in the next version of the TAD. Zero samples allow the potential
for artifacts in concentrator traps within the whole system to be addressed.
Question:
How should the States calculate total NMOC? How many compounds should be
included? Should all measurable peaks be included?
Answer:
Total NMOC is generally considered as the sum of all the peaks in the chromatogram in
ppbC excluding methane. There is concern that some NMOC peaks are removed with
the water management system (e.g., Nafion, etc.). Consequently, true NMOC may not
be obtained by the sum of all GC peaks.
Question:
Can estimates be given for costs for procurement, operation and maintenance of the
various PAMS network configurations being discussed?
Answer:
Some cost estimates made by OAQPS are included in the Preamble to the proposal and
promulgation of the PAMS regulations. Cost estimates are also addressed in the EPA
report, Guidance for Estimating Ambient Air Monitoring Costs for Criteria Pollutants and
Selected Air Toxic Pollutants, EPA-454/R-93-042, October 1993.
Question:
Can you comment on the cost benefits of purchasing carbonyl cartridges versus making
them?
Answer:
Currently, the commercially available dinitrophenylhydrazine (DNPH) silica gel coated
cartridges cost about $10.00 each; uncoated blank cartridges cost about $2.00 each. The
cost of coating, quality assurance, etc. involved in cartridge preparation must be
considered, however. EPA did prepare cartridges as demonstrated in the April 1993
PAMS workshop video presentation, but now finds it more cost-effective to purchase
them. Agencies wishing to use the DNPH-coated CIS cartridges will have to make them
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since they are not commercially available. There may, however, be private contract labs
willing to prepare them. It is important that they can guarantee a specified background
level suitable to the application.
Question:
Current annual estimated costs for carbonyl sampling and analysis are substantial. What
new technologies are EPA or other sister Federal Agencies such as the National Oceanic
and Atmospheric Administration (NOAA) pursuing to automate carbonyl sampling and
analysis and bring down State costs? Can you comment on alternative technologies?
Answer:
Although there are no commercially available automated technologies for sampling and
analysis of speciated carbonyls, there are several methods that have been used to sample
just for formaldehyde, for example. There are some possible alternatives for
derivatization. Certain perfluoro compounds might be used to make an oxime, for
instance, which could then be analyzed by GC/ECD. That would probably provide
slightly cheaper analytical costs, but sampling would still involve some kind of trapping
on a cartridge. Using ECD might provide the sensitivity needed to compensate for the
difference in the amount of sample going on a column. For liquid chromatography (LC),
up to 25 microliters of sample are commonly injected. Less than one microliter of sample
would likely be used for GC analysis; there are a lot of tradeoffs to be considered.
A real-time formaldehyde analyzer was used in the Atlanta Ozone Precursor Study in
1990. It uses a diffusion scrubber to collect formaldehyde. Ambient air is sampled
through a tube along the walls of which water is flowing. The formaldehyde diffuses to
the wall and goes into solution in the water. The water is then separated from the air and
chemicals are added so that a new compound is formed by chemical reaction. This
derivatized compound is sensed with a fluorescence detector. The system is very
sensitive, detecting ambient background concentrations of formaldehyde in the sub-ppbV
range. Interference testing indicated no significant interference. The disadvantage of the
system is that it measures only formaldehyde.
For continuous carbonyl monitoring there is a reference in the literature to a procedure
where DNPH reagent solution and air flow through a glass coil scrubber. The reacted
reagent is then collected and analyzed by HPLC. This could be automated by using
sequential collection of sample and an auto injector. The method is only good for soluble
carbonyl compounds having solubilities similar to or greater than formaldehyde (see
Environmental Science & Technology, Vol. 27, No. 4, 1993, pp. 749-756). The
disadvantage is that liquid reagents and HPLC are worked with in the field, which could
contaminate other analyses (e.g., VOC).
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Question:
Which hydrophobia adsorbents are now being tested?
Answer:
Several companies make hydrophobic adsorbents including Supelco with their Carboxin
series. The Carboxin adsorbents are hydrophobic and therefore reduce the amount of
water vapor remaining after sampling. EPA has used the Carboxins in place of the
Carbosieve S-ffl adsorbent, which is typically the last and most retentive adsorbent in a
multisorbent trap. The breakthrough volume for water vapor is reduced using the
Carboxins. A neutral gas purge is used to eliminate additional water vapor from the
multisorbent. Additional information on multisorbents is presented as "Evaluation of a
Sorbent-Based Preconcentrator for Analysis of VOCs in Air Using Gas Chromatography-
Atomic Emission Detection" in the Proceedings of the 1992 U.S. EPAIA&WMA
International Symposium on Measurement of Toxic and Related Air Pollutants.
Question:
Do any of the continuous GC/FDD systems have an automatic shut-off for hydrogen
during a flame out? If not, what do you recommend to prevent explosions at field sites?
Answer:
The instrument manufacturers have addressed the safety problems with the use of
hydrogen. Vendors should be contacted to determine whether or not their systems have
automatic shut-off valves.
Question:
Since FID detection is not enough to confidently identify ambient air pollutants, why
wasn't mass spectrometry included in the federal regulation? If it is going to be a future
revision, when will this take place?
Answer:
EPA believes that the FID with modern analytical GC columns and associated hardware
and software is the most appropriate procedure to qualitatively identify and quantitatively
analyze the target species for the purposes delineated in the PAMS regulations and
detailed in the TAD.
Mass spectrometry is not recommended for primary monitoring for this purpose, and it
is not likely that it will be recommended in the future. Mass spectrometry does play an
important role in quality assurance/quality control (QA/QC) and in verifying and
identifying unknowns.
Question:
How well should PDFID (total concentrations) correlate with speciation concentrations
(taking into account that some compounds are not high enough in concentration for some
FIDs to detect) assuming good QA/QC?
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Answer:
Generally, PDFID estimates of total NMOC should agree with the GC/FID sum of peaks
estimates within 15 percent However, areas with significant concentrations of polar,
water soluble, and substituted species may not agree as well. The correlation with a total
measurement by photoionization detection (PID) would probably not be as good because
of the response variability of the PID to different compounds.
Question:
Will the TAD provide specific criteria for States to decide if PDFID will be an acceptable
substitute for speciated analysis?
Answer:
Decisions about the acceptability of plans is addressed in the regulations for submitting
alternate plans to EPA. Specific criteria will probably not be included in the TAD since
alternative plans will be considered and approved on a case-by-case basis.
Question:
If the only equipment currently available to an agency to analyze ozone precursors is an
Entech System interfaced to a Hewlett Packard GC with a mass spectrometer detector
(MSD), would the MS data be acceptable for participation in the PAMS program for the
summer of 1993?
Answer:
The use of MSDs is not encouraged because of problems in calibrating individual species
and difficulties in estimating the concentrations of unidentified species (and resultant
difficulties in estimating the total NMOC). However, data for a specific set of
compounds collected by MSD this summer would probably not be refused. States
proposing this kind of system as part of an alternative plan should contact Entech to
determine the cost of putting an FID detector on that system.
Question:
What degree of accuracy is expected or required for the 50 compounds monitored by the
automated GC procedure? Will it be necessary to routinely examine every chromatogram
to verify and identify the compounds using the automated GC procedure?
Answer:
EPA is currently reviewing this issue and hopes to provide more definitive guidance in
the next version of the TAD. For automated GC applications it will not be practical to
routinely examine every chromatogram. Users will have to rely on emerging software
techniques to process chromatographs that are now examined and validated manually.
(Initially, as many chromatograms as practical or possible should be examined manually.)
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Question:
How are data between different instruments having dissimilar detection limits for varying
compounds compared?
Answer:
Comparisons are appropriate if each of the instruments is measuring species
concentrations well above the detection limit Comparison of results for species at or near
detection is not advisable.
Question:
m.
Why is it necessary to monitor for Q and C3 compounds?
Answer:
This issue was addressed when the 1990 Atlanta study was designed. Users of the data
felt that the database would be incomplete without this information because the C,
compounds have too much potential for contributing a significant amount to the total
VOC. Also, some of the Q compounds are reactive.
The principal interest in monitoring the Q, and C3 compounds is to provide source
fingerprints. Acetylene is an excellent indicator for an exhaust component from mobile
sources. In addition, ethylene and propene are reactive compounds and important in the
photochemistry process.
Question:
How does EPA plan to address interferences in ozone measurement methodology such
as moisture in the chemiluminescence method and benzene and its derivatives in the UV
method?
Answer:
Some reports about interferences with the UV photometry technique have been based on
comparing UV photometry with the chemiluminescence technology. Substantial studies
have been conducted to ascertain whether or not moisture could be causing those
differences, but so far no definitive information has been found to indicate that moisture
is a serious problem in terms of the UV measurement. There is always the potential for
any hydrocarbon compound that is a strong UV absorber (usually aromatic type
compounds) that is not properly compensated for in the ozone scrubber in the UV
technique to be an interferant. It is very difficult to quantitate what those interferences
are because those studies can only be done with known compounds like benzene,
naphthalene, and toluene. There is always the possibility that some higher boiling
compound that has absorption characteristics in the same portion of the spectrum as ozone
will cause an interference. Currently, these are not creating major interferences, but the
Agency does have an ongoing program to look at this issue within the limits of the
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available resources. Contact the AREAL Equivalency and Methods Program at (919)
541-2622 for further information.
Question:
Could you explain the differences in the units of measurement between parts per billion
carbon (ppbC) and parts per billion volume (ppbV)?
Answer:
Both units are concentration measurements used particularly for hydrocarbon compounds.
Parts per billion carbon (ppbC) represent concentration in terms of carbon atoms in the
compound. Parts per billion volume (ppbV) represent compound concentration. For
example, a 1 ppbV hexane concentration would convert to a 6 ppbC concentration since
there are 6 carbon atoms in the hexane molecule. The FID response is reasonably
constant over the whole spectrum of PAMS compounds.
Question:
Since CO plays a role in ozone formation and will likely be included in ozone model
evaluation, what type of CO instrument(s) does EPA suggest the States use at the
different PAMS sites?
Answer:
States are encouraged but not required to make CO measurements at PAMS sites. EPA
has not developed definitive guidance for low level CO measurements for this purpose.
States that choose to make this measurement should consult with the research community
involved in low level CO measurements and follow their suggestions.
Question:
Can CO monitoring be part of the FAMS network?
Answer:
CO monitoring is not currently required; however, many data analysis studies involving
CO show that CO correlates extremely well with some of the VOC species, in particular,
for mobile sources. CO information can be very useful, particularly to photochemical
modelers, in identifying to what extent mobile sources are contributing to the total VOC
and may be unduly influencing a monitoring site. A CO monitor with a more sensitive
range than the CO monitors used for determining compliance with the CO standards
should be used. Such monitors have been used in several research studies for this
purpose, and interested State and local agencies would be encouraged to look into these.
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Question:
What factors should be considered for using ozone scrubbers for carbonyl sampling?
Commercially available cartridges have a copper grid to eliminate ozone interference.
Isn't this required for lab-prepared dinitrophenylhydrazine (DNPH) cartridges?
Answer:
Commercially available cartridges (DNPH-coated silica gel) do not incorporate a copper
grid to eliminate ozone interference. Both commercially or lab-prepared cartridges require
some form of ozone scrubber or denuder. One example of a denuder that worked
successfully for EPA has a coiled 3' length of 1/4" copper tubing treated with a solution
of potassium iodide; it had a lifetime of 80 hours for 700 ppb ozone at 2 liters/minute.
The carbonyls required to be monitored for PAMS showed no losses from use of the
denuder. Other types of scrubbers are possible, but would need to be validated.
While DNPH CIS type cartridges appear to be more immune to ozone interference than
DNPH-coated silica gel cartridges, there is evidence of degradation products that appear
during HPLC chromatography. Thus, use of the denuder for either DNPH-coated silica
gel or DNPH-coated CIS cartridges is recommended.
Question:
Is a heater needed for an ozone scrubber for carbonyl sampling?
Answer:
Yes, using a heater is recommended.
Question:
Is once every sixth day, 24-hour sampling also required for carbonyls?
Answer:
The regulations state that carbonyl sampling frequency must match the chosen speciated
VOC frequency. That means that at each Site No. 2, a 24-hour sample for VOC and also
a 24-hour sample for carbonyls should be collected concurrently with the 3-hour samples.
Question:
What time (daylight or standard) should be used for VOC and carbonyl sampling?
Answer:
As with the criteria pollutants, local time is used for sampling. Data should be reported
in accordance with the AIRS guidance indicating local standard time.
Question:
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Is the instrumentation associated with monitoring nitrogen compounds adequate to
characterize simple and slightly complex atmospheric chemistry and to provide useful
information for evaluating and validating models in both urban and rural areas?
Answer:
Actually, current chemiluminescence analyzers for oxides of nitrogen (NOy) only measure
NO accurately. The NOX channel measures NO, NO2, and PAN quantitatively and other
gas phase nitrogen oxides such as nitric acid less quantitatively. In the early stages of
the ambient air photooxidation process, the NOX results consist mainly of NO and N02.
As the photooxidation process proceeds, NO2 is further oxidized to PAN and nitric acid.
For model evaluation and validation, better information for the N0y is needed. Joe
Sickles (AREAL, 919-541-2446) is the contact person for additional information on this
issue.
Question:
Does NOX include N02? How does solar radiation correlate with ozone or hydrocarbons?
Answer:
NOX in its strictest sense is NO + NO2. Solar radiation is required to produce
photochemical ozone; consequently, there is a correlation between these two components.
There is no correlation between hydrocarbons and solar radiation.
Question:
Please elaborate on NOX measurements, carbonyl issues, and CO measurements?
Answer:
In promulgating the PAMS regulation, EPA considered using emerging technology to look
at more definitive NOy species and was faced with deciding whether or not to require
more definitive species measurements or to continue to use the chemiluminescence
reference method technologies that State and local agencies have used for N0:
measurements.
Over the past several years, the research community interested in background
measurements has been very concerned about measuring all NOy including nitric acid,
peroxyacetyl nitrate (PAN) and other oxides of nitrogen. Although research techniques
have been developed, they have not become routine. Consequently, no techniques for
measuring these additional oxides of nitrogen have been included in the 1991 version of
the TAD. When improved technology for measuring the nitrogen oxide compounds
becomes available, the TAD will be revised. A range problem exists because there are
high NOX concentrations in the morning compared to very low NOX concentrations in the
afternoon. Vendors of chemiluminescence instruments will be encouraged to provide
automatic range changes to address this issue.
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Consideration is being given to relocate the converter on the NOX chemiluminescence
analyzer to measure NOy. This technique will also be included in the revised TAD. In
addition, GC techniques for measuring PAN will be addressed. Although these
measurements will not be required, State and local agencies are encouraged to work with
the research community to make such NOX and NOy measurements.
For carbonyls, the regulation requires that the carbonyl measurement schedule be the same
as the VOC schedule so that modelers can make sense of the data; unfortunately, little
monitoring has been done with sequential carbonyl samplers. Therefore, there is a lot of
encouragement to, and a reasonable effort by, the manufacturing community to design
samplers that can take 3-hour sequential samples around-the-clock. These samplers
should be on the market by early 1994.
Question:
Can an open path instrument be used in lieu of GC or canister sampling?
Answer:
Open path technology is just emerging and does not currently measure all of the
compounds to be measured for PAMS. While open path technology will continue to be
evaluated, it will not apply to PAMS at this time.
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QUALITY ASSURANCE
Question:
How will proficiency cylinders be made available for testing in 1993?
Answer:
The cylinders will be shipped to a contact person in each agency as identified by OAQPS.
EPA will have a contract established with a national carrier to ship cylinders to and from
the contacts, at no cost to the agencies.
Question:
How can one obtain a copy of the PAMS northeast quality assurance plan?
Answer:
Copies are available by calling Avi Teitz, EPA Region n, at (908) 906-6160 or faxing
your request to (908) 321-6788.
Question:
How does one obtain the calibration and retention time standards?
Answer:
State or local agencies can obtain calibration and retention time standards from their EPA
Regional Office. Regional Offices can contact Geri Dorosz-Stargardt, OAQPS, at
(919) 541-5492, who will coordinate with AREAL to get calibration retention time
standards.
Question:
Who pays for the calibration and retention time standards?
Answer:
Arrangements have been made by EPA to cover the cost for 1994 by withholding §105
grant funds. In the future, grant dollars will likely be set aside for this purpose.
Question:
If we already have retention time standards, how many components should standards
contain, and which compounds should have certified concentrations?
Answer:
The calibration standards EPA is supplying are going to be certified for propane and
another compound, most likely benzene. The mixtures themselves, as ordered from the
vendor, were certified to be within ±10% of the values stated on the cylinders. All 25
of these mixtures will be analyzed by EPA and these values will be used to provide the
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average value for each compound in the mixture plus a standard deviation for each
compound.
Question:
Some EPA regional laboratories use SRM gases for their ambient air monitoring
programs, including certifying tanks for use in regional performance audit programs and
certifying State standards, usually certified reference materials (CRMs), to assure stability
and repeatability. What is EPA doing to make SRM gases, especially for the NO, NO2,
and NOX monitoring, more readily available since there is a lengthy certification process
for each cylinder and demand for these cylinders is likely to increase?
Answer:
EPA's Office of Research and Development (ORD) is concerned about the availability
of standards, and has instituted three new programs in the last year to make high quality
standards readily available.
(1) The first is a quality assurance program for the suppliers of protocol gases. The
results of these checks on the certification accuracy and documentation completeness of
certified protocol gases obtained from the suppliers of these gases are available on the
AMTIC bulletin board system (BBS). For instructions on accessing this information on
the AMTIC BBS, contact Ed Hanks at (919) 541-5475.
(2) EPA is also working with MIST to improve the availability of NO SRMs. Two new
programs have been started at NIST to supplement the SRM program. Copies of papers
presented at the EPA and Air & Waste Management Association (A&WMA) Conference
in Durham describing these programs are available by calling Bill Mitchell at (919)541-
2769.
(3) Finally, the NO certification accuracy of 8 vendors for a 50 ppm NO cylinder was
checked in January 1993. All 8 vendors were able to get within ±2 percent of the
certified value that is specified for protocol gases. EPA hopes to make high quality gases
available through the protocol gas program. By revising the guidance (procedures for
establishing traceability of gas mixtures to NIST SRMs), EPA hopes to make it simpler
and easier for the vendors to provide these gases, which should be more readily available,
more accurate, and less expensive than SRM gases. (Note: This guidance was issued in
revised form in October 1993. Copies were sent to all suppliers of protocol gases.)
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Question:
What concentration ranges of SRMs and CRMs are available for propane and benzene?
Answer:
A 3 ppm concentration level is used for propane and a 0.2 ppm concentration level is
used for benzene; each of them is adequate.
Question:
If methane can be detected, should it be reported or ignored? If this information is
important for modeling purposes, should some subset of the PAMS sites monitor methane
on a routine basis?
Answer:
Although methane has a rather high concentration (the background level is about 1.6
ppm), the hydroxyl radical (OH) reaction with methane is slow (about 1,000 to 10,000
times slower than most VOC). That being the case, very little ozone is produced in those
systems when NOX is added. Although it is important when talking about tropospheric
ozone (that is, background ozone), in general, methane is not considered because it
contributes very little to ozone formation in urban situations; therefore, EPA has not been
concerned with monitoring it.
Question:
Where can part per billion level certified VOC standards be purchased for calibrating
automated GCs, and at what cost?
Answer:
NIST sells an SRM containing about 18 compounds, 6 to 8 of which are PAMS
compounds that are also toxic orpanics. The standard sells for about $11,000. It is
certified to within 10 percent, and concentrations are about 5 ppbV. No specific NIST
SRM is currently available for the PAMS hydrocarbon mixture.
Scott Specialty Gases and Alpha Gas have also made high quality PAMS mixtures. The
retention time standards that EPA is supplying to agencies were bought from Scott.
Mantech is going to certify these mixtures for propane and for a second compound using
NIST SRMs; that second compound may be benzene or toluene. Certified mixtures are
available from several suppliers including Scott and Alpha Gas. Perhaps the retention
time standards along with the certification that could be given for the values on the
standards, and the proficiency sample testing results, will provide adequate information.
Calibrated standards can be purchased from Scott Specialty Gases for $5,000 to $7,000,
depending on the desired certification. However, the desired certification may not
necessarily agree with what is being used as a reference for PAMS, and that would have
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to be taken into account. The particular mixture purchased would have to be somehow
referenced back to the standard being used for PAMS. That is an important consideration
when buying calibration standards "on the outside."
Question:
Will VOC gas mixtures need to be diluted when added to canisters? What concentration
will the tanks contain? Will EPA have a proficiency program in 1993?
Answer:
All compounds in the retention time standard cylinders will be at 30 ppbC concentration
and will not require dilution. A proficiency program was begun in 1993. EPA has a new
gas transfer system that allows stock gases to be put into smaller cylinders and
pressurized to the pressure needed to obtain a specified volume. Stability tests have been
started to make sure that the PAMS compounds are stable in the compressed gas
cylinders.
Question:
Will the VOC performance audit gases be humidified by an external system?
Answer:
Note that these are proficiency samples, not audit samples. To answer the question
directly, these mixtures will not be humidified initially, because the effect of humidity on
a mixture that might be pressurized to 1000 psi is unknown. However, the possible effect
is to be studied.
Question:
Based on past experience, what level of comparability do you expect to see for VOC and
carbonyls (a) within a monitoring organization, and (b) between monitoring organizations?
Answer:
It has been EPA's experience that at low concentration levels, monitoring organizations
can disagree by more than a factor of two. At concentration levels that can be measured
quantitatively, comparability improves to 10 to 25 percent. It is generally the case that
agreement between monitoring groups within an organization is better than that between
organizations.
Question:
In the past, where has the variability among organizations been most likely to occur?
Answer:
The differences among organizations have generally been at the analytical level. Great
differences were not found when different organizations conducted the sampling but sent
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the samples to the same laboratory. This is probably because the organizations are
already proficient in the technique of setting timers, doing automated sampling, and other
tasks associated with sampling.
Question:
What will EPA be doing to quality assure the performance of those commercial
laboratories performing analyses for States?
Answer:
For some EPA Regions (such as Regions I, II, and HI) this is hypothetical, but other
Regions may have different plans or experiences with the use of commercial laboratories.
If commercial laboratories get more involved, EPA will expand and support regional
efforts to the States to enable them to perform adequate quality assurance oversight,
whether this involves performance evaluations, monitor collocations, etc. EPA will work
with the States to ensure that they have the capacity to do the proper quality assurance
oversight.
Question:
For carbonyl proficiency studies, will AREAL use tubes supplied by each agency?
Answer:
Yes. The tubes are to be prepared by each agency and sent to AREAL. For proficiency
testing, representative tubes (i.e., tubes that represent the cleanup and extraction
procedures that the agency would use) have to be provided. Tubes provided from
AREAL's own inventory would not necessarily reflect the agency's proficiency at
recovering aldehydes.
The details still need to be worked out. EPA Regional Offices have been contacted and
are aware that some procedures will have to be developed for making these tubes
available to AREAL to spike on a routine basis. Only a limited number of agencies are
expected to start sampling for aldehydes on a regular basis in the first few months of
summer. The majority of agencies contacted will not conduct carbonyl sampling before
the summer of 1994, giving AREAL time to develop these materials.
Question:
What about the effects of different flow rates used by the agencies?
Answer:
If an agency uses a different flow rate than the standard, it should show up at some point
in the proficiency samples. In general, proficiency samples do not have to be checked
for flow because they are going to be recovered as an analytical sample. The details still
need to be worked out.
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Question:
During previous National Performance Audit Program (NPAP) audits conducted against
our standard reference photometer (NIST SRP) for ozone, changes have been observed
in the ozone output from the TECO 165 of as much as 38 percent. Does the new TECO
175 have the capability to monitor line voltage, which seems to be the major concern?
Answer:
The TECO 175 will not have the capability to monitor line voltage. The first version of
the TECO 165, which was pilot tested in 1990-91 and first used in 1992, had some
problems with circuit boards that were not adequately stabilized, and some breaks in
solder. EPA has not seen this 30 percent difference in its own laboratory. Generally,
results are repeatable within ±2 percent on a daily basis. (EPA will check into that 30
percent difference to see what caused it.) AREAL keeps a record of every problem and
how it was solved, along with a logbook of equipment maintenance. EPA has adjusted
its certification procedures as it has found problems. The 175 has essentially the same
circuitry as the 165 now does, and EPA is putting it through acceptance testing.
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MODELING AND METEOROLOGICAL MONITORING
Question:
The PAMS regulation requires intensive monitoring at one site, starting in the summer
of 1994. This will provide some limited data by the end of 1994; the PAMS data will
increase in future years. Since modeling for the 1994 nonattainment plans must be
completed in late 1993 or early 1994, how will the PAMS data help air pollution control
agencies make control measure evaluations and decisions, and perform attainment
demonstrations for the 1994 nonattainment plans?
Answer:
The modeling must be completed by November 1994. Obviously, the PAMS data are not
going to be on-line to assist in that modeling process for either the model inputs or for
evaluating model performance for the base case. However, the PAMS data that come on-
line from 1994 throughout the next several years will be useful for tracking model
performance over time for the future. Certain assumptions about control strategies and
the PAMS data will be used to track how well the model predicts future events. In short,
the PAMS data at this time will not complement the upcoming modeling; however, the
PAMS data will be very useful for future interim modeling.
Question:
When using the Urban Airshed Model (UAM) to predict future ozone concentrations, is
the worst case or average used for the weather input? How is the prediction of the
weather made for a given time period? What weather parameters are used
(i.e., temperature, humidity, etc.)?
Answer:
An underlying assumption in the regulatory modeling approach is that historical
meteorological episodes will repeat themselves in the future. When applying the model
to future years, such as projections to the year 1999 or 2005, the same meteorological
inputs (from actual meteorological data) in the base case are used, adjusting emissions and
boundary conditions to reflect, as much as possible, the future year scenario. These
meteorological fields are usually obtained from National Weather Service data and include
3-dimensional wind fields, wind speed and wind direction, temperature fields, mixing
heights, atmospheric pressure, relative humidity, and some other variables.
EPA guidance requires that the most severe ozone episodes from the last several years
of data available, roughly the late 1980s and early 1990s, be considered for the modeling
process. The following factors are generally considered when selecting episodes to
model: the severity of the ozone episode in terms of maximum ozone, the persistence of
ozone during the period of interest, and the likelihood that the episode meteorology will
recur.
33
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Question:
How important are actual N0y measurements for the UAM and other models? Is some
confirmatory monitoring necessary or are default values for NOy available for the model?
Answer:
NOy data are useful in drawing inferences about the types of control strategies that might
be beneficial, and in determining whether an area is NOX or hydrocarbon limited. To a
certain extent, the model is capable of adding up the number of the oxidized nitrogen
species and determining roughly what the N0y simulated values would be since NOy is
an accumulation of many of the oxidized nitrogen species (e.g., nitric acid, PAN, and
NOX). Since some of the emerging ambient techniques (e.g., incremental emission rate
algorithms, smog production algorithms, "Airtrak mechanism," etc.) rely heavily on
nitrogen measurements, it becomes important to be able to separate N0y and NO when
using these ambient measurements. N0y is useful in the overall context of model
application because it represents a cumulative group of species that can indicate model
performance.
Question:
Given the different UAM data needs for areas with special conditions (for example, the
Great Lake environments), how will EPA handle deviations from the basic PAMS
program to meet these varied special needs? For example, for the Lake Michigan region,
modelers are requesting ozone measurements aloft; will EPA consider a reduction in
ground level measurements for VOC so that the available funds can be spent differently?
For States and regions which have already collected databases for modeling and have
been developing models appropriate for special regions (such as the Lake Michigan Ozone
Study), would a reduced VOC sampling program be adequate?
Answer:
It is important to be able to account for what occurs vertically in the model process and
the whole atmospheric chemistry process. When considering mass balances for the
overall volume of the model, a lot is happening vertically for which little information
exists and for which more information is needed. For alternative plans, there are certain
minimum requirements which must be met with respect to surface monitoring for a
number of purposes beyond modeling. In addition to modeling, PAMS data are crucial
for tracking emission trends and the success of control implementation programs. The
ability of the PAMS programs to accomplish these objectives must not be jeopardized by
tradeoffs for modeling purposes.
Question:
How can the Chemical Mass Balance (CMB) be used since VOC react in the atmosphere
over time, creating secondary products?
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Answer:
The fitting species must be restricted to relatively stable species whose reaction rates are
slow (i.e., species which do not transform appreciably in 10 hours or so, or a large
fraction of a full day), a small subset of the VOC that have been targeted.
Question:
The CMB type of receptor modeling seems to require a lot of ambient data. Will there
be enough data generated by a PAMS station to be able to use the CMB model approach?
Answer:
There are two aspects to how the data are used. If the source profiles are already
available, then the CMB approach can be used for a single sample and provide an
estimate of what sources are contributing to the measured VOC. However, large
quantities of data are required to extract source profiles from the ambient data. Several
hundred individual measurements are estimated to be required to perform this data-
intensive, multivariate procedure. If one is willing to use profiles compiled by others
(and more accurate profiles are likely to be obtained as the PAMS network goes on), then
data requirements become small. Only in the initial stages, while trying to construct these
reliable profiles, are large amounts of data necessary.
Question:
What has to be done to adapt the CMB-7 program for receptor modeling of VOC data
instead of aerosol data?
Answer:
The CMB-7 program was originally used for aerosol data, and all the documentation
references this application, but it is perfectly adaptable to VOC simply by changing what
is specified in the input. No changes to the internal workings of the program are
necessary.
Question:
Would it be wise to conduct source receptor analyses periodically to see how the
inventory is changing over time as the control program reduces ozone precursors over
time? Should source receptor analyses be conducted before and after the fuel
reformulation program?
Answer:
Yes to both of those questions. The PAMS network will accumulate data over several
years to track the relative contributions of the source categories that can be quantified
over time.
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Question:
What about receptor modeling for sources other than those that are vehicle-related (such
as tailpipe emissions and gasoline evaporation)?
Answer:
Vehicle-related sources probably represent the majority of the VOC in the atmosphere in
any urban center. There are other sources that can be quantified such as industrial solvent
sources or leakage of natural gas in areas where natural gas is used. Biogenic emissions
is another source which many feel is important. There has been lots of discussion in the
past few years suggesting that the biogenic contribution of VOC has been underestimated
in comparison to anthropogenic sources. The difficulty in quantifying the biogenic
contribution by the CMB approach is that stable VOC must be included in a given source
to make the CMB procedure reliable. Practically all species that would be connected with
a biogenic source (e.g., isoprene and a- and p-pinene) are very rapidly reacting species.
Thus, there is no acceptable way of treating biogenic emissions through the CMB
approach. Work is in progress to assess the biogenic contribution by using carbon-14
dating techniques.
Question:
Urban receptor modeling has previously used data for hydrocarbons and halogenated
species to quantify urban sources. Will the hydrocarbon species measured at PAMS sites
be sufficient to quantify urban sources?
Answer:
With receptor models, sites should be located all over the city, with definitive speciation
available anywhere there is likely to be a source to be quantified. The receptor modeling
technique is currently being applied to ambient VOC species with the intent of
apportioning the sources of VOC among the various sources in the city. In addition,
receptor modeling is being combined with a "hybrid" dispersion model to estimate
emission rates from a given source and then to compare rate estimates directly with
emission inventory information. EPA is very excited about this application of the
speciated data.
Question:
Where can one obtain the most recent copy of the photochemical grid model domain for
the areas to be included in a given network design?
Answer:
Ellen Baldridge of the Source Receptor Analysis Branch is responsible for tracking all of
the UAM applications and recording all the domain coordinates throughout the country;
she can be contacted at (919) 541-5684.
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Question:
Is on-site meteorological monitoring necessary if nearby National Weather Service (NWS)
data are available?
Answer:
The PAMS regulations require that surface monitoring be representative of the PAMS site
itself, and that upper air monitoring be representative of the MSA being monitored. If
NWS data are complete and provide one of those representativeness options then those
data may be satisfactory for either a PAMS surface monitoring site or for the upper air
station for the MSA. EPA will consider each proposal on a case-by-case basis to ensure
that NWS data are representative.
Question:
Do the meteorological data need to be collected at the monitoring site itself?
Answer:
According to the regulation, meteorological data must be collected with the monitoring
data. However, it depends on whether it is a big urban area or a small urban area, as well
as on the complexity of the area. Where the distance between the monitor Site No. 1 and
Site No. 4 is within 100 miles and the terrain is not complex, the difference in
meteorological measurements is very small. In such situations, one might be able to use
the local weather service meteorological data. On the other hand, if there is complex
terrain or blocking by physical obstructions, collocated monitoring would be necessary
in order to accurately depict the meteorological data at the monitoring sites.
Question:
For No. 2 sites, why can't mini-Sodar systems be used instead of the 10-meter tower?
Good wind speed and wind direction data in the range of 10 to 200 meters can be
collected with these Sodar systems.
Answer:
The No. 2 sites are typically located immediately downwind of downtown areas or other
areas of maximum VOC concentrations. Siting a Sodar downtown causes problems with
noise interference from cars and planes. There is no problem with using a Sodar if it is
sited properly to eliminate a lot of the noise. If a Sodar is located on top of a building,
however, it will be several tens of meters above ground level. In addition, Sodar and
Rass systems emit irritating sounds and, thus, cannot be sited in residential areas.
37
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Question:
Is a mini-Sodar system less expensive than a regular Sodar system?
Answer:
A mini-Sodar system typically costs $12,000 compared to a regular Sodar which costs
$50,000 to $100,000. The problem with mini-Sodar systems is that they only go up to
about 200 meters while the mixing height can vary from near ground level to 2
kilometers. The mini-Sodar provides very good wind structure near the ground and is
valuable for calculating maximum concentrations which typically occur when the
boundary layers are near the surface. However, some data will be missed using the mini-
Sodar alone. Thus, both systems should be purchased, using the mini-Sodar to get the
lower winds and the regular Sodar or Rass system to get the upper winds.
Question:
How many low level and upper level meteorological stations are required for a typical
PAMS area?
Answer:
A 10-meter meteorological tower at every PAMS station and a minimum of one upper
air radar sodar profiler in every city is recommended.
Question:
Why are temperature measurements indicated at the 2 and 10 meter levels of the 10-meter
meteorological tower?
Answer:
The two height requirement was included because that information is needed for the
model. The configuration of 2 and 10 meters gives a lot of information for calculating
mixing heights using equations instead of using a Sodar or Rass system and will permit
checks that the Sodar or Rass system is working properly. Boundary layer conditions
(i.e., temperature, relative humidity) at the surface and at the mixing height are needed
for the model.
Question:
Is temperature accuracy 0.1 or 0.01°C?
Answer:
With the delta T approach, the best temperature accuracy that can be expected with a IO-
meter tower is about 0.2°C. EPA guidance is being updated to include this and other new
technology.
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Question:
What time (daylight or standard) should be used for meteorological data?
Answer:
For VOC, carbonyl, and criteria pollutant sampling, local time should be used in
developing wind roses and summarizing other meteorological data. Data should, however,
be reported to AIRS in local standard time.
Question:
In volume IV of the Quality Assurance Handbook for Air Pollution Measurement Systems,
the problems of siting meteorological towers in urban environments are not addressed.
In the future updated version of this quality assurance handbook, will EPA address the
urban meteorological No. 2 sites?
Answer:
EPA is in the process of gathering information on meteorological equipment and what
must be done regarding quality assurance. Volume IV deals mainly with the installation
and calibration of meteorological towers located for rural monitoring networks.
Obviously, siting a meteorological tower in an urban area is more complicated. Volume
IV will be revised to address the PAMS meteorological situation and the problems of
siting meteorological towers in urban environments.
Question:
Has the 915 megahertz wavelength been included by the FCC?
Answer:
The 915 megahertz wavelength has been cleared by the FCC. Efforts are being made to
get several more frequencies cleared.
Question:
Why are temperatures measured at 2 meters?
Answer:
They are needed to determine "delta," which is the temperature difference between 2 and
10 meters which is used to infer stability near the surface. That has been used to aid in
processing the Pasquill stability curve, estimating which one to use along with the solar
radiation measurements. As the solar technology advances, we are hoping to eliminate
that sort of instrumentation completely if we can measure the mixing height accurately.
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DATA ANALYSIS
Question:
A day of the week versus ozone dependence has been noted in our data. Are there other
researchers or studies with similar results?
Answer:
In the 1970s, analyses were done using data from Los Angeles which compared weekends
to weekdays, and higher ozone concentrations were noted on Sundays in some locations.
This type of analysis will be possible with PAMS data to provide insight into the
potential benefits of VOC versus NO, control strategies, for example, by looking at ozone
and NOX levels on the weekends versus weekdays.
In some of the air quality trends analysis work involving meteorology, a variable has been
included to account for weekend versus weekday differences. Very distinct patterns can
be seen in terms of the weekend effect, depending on the geographic area when looking
at a number of urban areas. There is no question that such an indicator would be used
in future analysis involving PAMS data, and perhaps even in looking at the national
ozone network, which is in place and has a large database.
There have been some studies where monitoring was only conducted on the weekdays as
an economy measure. As soon as one considers a day-of-the-week effect or
weekend/weekday differences, monitoring must occur every day of the week.
Question:
What is the biggest problem in trends analysis?
Answer:
In terms of ozone, the biggest problem in trends analysis is cleaiiy the confounding effect
of meteorology. For example, east of the Mississippi between 1987 and 1988, ozone
levels in many areas increased an average of 10 percent, although emissions did not
actually change that much. One of the challenges in trends analysis is how to remove,
or at least reduce, the effect of meteorology on ozone levels. Some of the work that EPA
has done looks promising, in terms of attempting to remove the effect of meteorology.
Another possibility is that precursors, particularly in early morning hours or times when
there is greater stability, are not going to be as influenced by meteorology as ozone
levels. Therefore, PAMS data may be used to gain more insight into trends, and to help
eliminate or at least qualitatively eliminate some of the effects of meteorology.
40
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Question:
Why was the use of specific techniques for data analysis not required?
Answer:
A prescribed approach might drive analysis efforts to the lowest common denominator.
The PAMS network data are going to be a veritable gold mine of information. The data
must be analyzed with the best and most sophisticated tools available to get the most out
of the data. The hope is that by not requiring specific techniques, creativity will be
encouraged and innovative approaches will be used. Obviously, a minimum or
standardized set of analyses may evolve over time, but for right now, the current approach
seems to be most reasonable.
Question:
Can standard statistical approaches, such as regression analysis, be used?
Answer:
Standard statistical techniques would be acceptable in some cases. Exploratory techniques
provide more insight into the data and help to get more out of the data initially. The
problem with linear regression is that it assumes a linear dependence on the independent
variables which may not be appropriate for complex photochemical relationships. There
is no consistent linear trend in ozone data over time, particularly in the 1980s; it is a mix
of good and bad years. For the EPA trends report, a classic statistical approach, more
like general linear models, is used in which a year effect term is fit into the trend display
as a better way of determining trends.
Question:
What statistics should be considered for determining VOC trends?
Answer:
The morning traffic peak (6:00 a.m. to 9:00 a.m.), on high ozone days, as well as other
days, should be considered for determining VOC trends.
Question:
How should trends be adjusted for meteorology?
Answer:
Work has been done involving adjusting ozone for meteorological influences. The
techniques, which have been documented and are available to interested agencies, could
be adapted and applied to adjusting trends in VOC and VOC species. It is not clear
whether the same success rate achieved with ozone can be achieved for VOC. Obviously.
there will not be enough data for 2 to 6 years to make meaningful adjustments to annual
trends; nevertheless, this is a worthwhile option to consider. By using some of the
41
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exploratory data analysis techniques that have been talked about, the basic relationships
between meteorology and some of these VOC species can begin to be investigated, with
the idea that those relationships could be used to make the adjustments in the VOC
trends, giving a more precise, less biased estimate of those trends.
Question:
Please describe the SAS package used in the demonstration. In particular, what is
required to run it and where is it available?
Answer:
The SAS package, Insight, runs on a variety of platforms, including Avion and General
workstations, and some SPARC workstations. It is also available on a PC platform with
a minimum number of megabytes in size. The EPA has a contract with the SAS Institute
to acquire SAS products. To acquire software through that contract, contact Ron
Scarborough at (919) 541-1369. For more specific information about SAS products,
contact the SAS Institute in Gary, NC at (919) 677-8000.
Question:
Exploratory data analysis can provide insight into the data. How long does it take to
learn the exploratory data analysis methods that SAS Insight offers? Are there any other
software packages that could be used besides SAS Insight?
Answer:
Based on personal experience, it took about 1-1 Vi months to become reasonably proficient
at using that database and package. It is a very easy interface to use and a very easy tool
with which to become proficient fairly quickly.
Other software packages could also be used for these analyses. One possibility would be
S-Plus, manufactured by Stat-Sci in Seattle, Washington. This package has many of the
features that SAS Insight has; however, S-Plus is more of a programming language and
the learning curve for that package would be somewhat higher. S-PIus and other similar
packages offer the same kind of functionality available with Insight, and certainly could
also be considered.
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AIRS AND PAMS
Question:
Describe the hardware and software requirements necessary to access AIRS Graphics via
a PC-based system, and the status of the AIRS Graphics access for direct AIRS users.
Will separate screening files be required for loading the PAMS data onto NCC AIRS?
Answer:
To access AIRS Graphics, a graphics terminal and graphics interpretation card are needed
on your PC. You can then call via modem to the NCC mainframe. In order to access
AIRS Graphics, a valid time sharing option (TSO) NCC user ID is needed.
The easiest and most popular way to access AIRS is to sign on through TSO. At the
TSO ready prompt from the NCC mainframe, type in AIRSG (one word) to log directly
into AIRS Graphics. Another way to log into AIRS Graphics is by typing the command
AIRSX at the NCC main menu. A third way to access AIRS Graphics is directly through
the AIRS main menu screen.
Separate files are not needed to submit PAMS data into the AIRS Air Quality Subsystem
(AQS). The PAMS data can be entered into AIRS just like any other data. Regions may,
but are not required to, build new screen files specifically to handle PAMS data. To set
up a new screen file, contact Gary Wilder, NADB, at (919) 541-5447.
Question:
Is it possible to download an AIRS Graphic file using the phone line and modem? If so,
how?
Answer:
It is possible to download any TSO file through a modem and telephone line. Contact
Tom Link, NADB, at (919) 541-5456 for specifics on downloading AIRS files.
Question:
Is the AIRS Graphics package available as separate software for use on a PC? If yes,
how can it be obtained? Is it available through EPA's BBS?
Answer:
There is not a PC-version of AIRS Graphics. A software program called AIRS Executive
is available, however. AIRS Executive is a managerial tool that houses canned data and
prints a variety of fixed preset reports (for example, top 30 source emitters for point
sources). AIRS Executive is geared more towards point source data, although it does
contain some ambient data. For more information, contact Tom Link, NADB, at
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(919) 541-5456. [AIRS Executive, along with current data files, may be downloaded
from the AIRS BBS, which is part of the OAQPS Technology Transfer Network (TTN).]
Question:
In AIRS Graphics, is there any way to alter the AIRS Graphics, line charts or maps?
Answer:
The line graphs in AIRS Graphics are generated from the raw data listing the AMP 350
work files. The only way to alter AIRS Graphics is to edit what is going into AIRS
Graphics (i.e., the TSO data set where the work files for the AMP 350 reside). AIRS
Graphics can be exported as metafiles or printed directly at the NCC; manipulation of the
graphs, maps, or charts once they have been generated in AIRS Graphics is not possible.
Question:
What types of AIRS reports and AIRS Graphics in AQS are projected to be available in
the future for PAMS related data?
Answer:
AIRS has two types of PAMS specific reports: the AMP 225, which is the PAMS
network report, and the PAMS raw data summary report, which is currently under
development. User input is requested with regard to future types of batch reports both
in AIRS Graphics and in AQS. If you have any suggestions on what kinds of AIRS
Graphics or AQS would be useful, please contact Jonathan Miller at (919) 541-3330.
Question:
Does AIRS have a method code for a 6-hour sampling period for carbonyls or should the
3-hour method code be used and two identical values be reported?
Answer:
AIRS has the ability to generate new method codes at any time it is deemed appropriate.
In this situation, the best thing to do would be to use a separate (new) method code to
indicate a 6-hour sampling period to differentiate that from two consecutive 3-hour time
periods.
Question:
If the intermittent sampling is collected on local time at one of the PAMS sites, is it
appropriate to report that data to AIRS on local standard time?
Answer:
Yes, the time frame used in AIRS is local standard time.
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Question:
Since the AIRS reporting format includes parts per billion per unit, can VOC data be
submitted as parts per billion volume (ppbV)?
Answer:
Currently, data submitted in ppbV would be accepted; however, it is not the preferred
format. It is recommended that data be submitted in parts per billion carbon (ppbC).
There is currently discussion as to whether AIRS should have an edit check to screen out
data not reported in ppbC.
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EPA-454/B-93/051
Appendix E
Revision No. 0
Date: March 1994
Page E-l
APPENDIX E
UPDATED ESTIMATED CANCER INCIDENCE
FOR SELECTED TOXIC AIR POLLUTANTS
-------
Updated Estimated Cancer Incidence For Selected
Toxic Air Pollutants Based on Ambient Air Pollution Data
Robert B. Faoro, Thomas C. Curran and
William F. Hunt, Jr.
U. S. Environmental Protection Agency
Office of Air Quality .Planning and Standards
Technical Support Division
Monitoring and Reports Branch
Research Triangle Park, North Carolina 27711
August 1989
-------
Acknowledgment
The authors would like to acknowledge the technical support they
• *
received from Alison Pollack and Belle Hudischewskyj of Systems Applications
Inc., J. J. Mind of American Management Systems, John Bachmann, Larry Cupitt,
Fred Gimmick, Tom Lahre, and Joe Padgett of EPA and finally Helen Hinton of
EPA for the typing and retyping of this report.
-------
UPDATED ESTIMATED CANCER INCIDENCE FOR SELECTED TOXIC
AIR POLLUTANTS BASED ON AMBIENT AIR POLLUTION DATA
1. INTRODUCTION
In 1985 a major study assessed the cancer risks from selected air toxics
In the United States. The use of ambient air toxic data to determine these
risks was a major portion of the overall air toxic assessment. This report
1s an update to the 1985 study and It estimates Individual cancer risk and
number of cancer cases or Incidence for three major classes of air toxics: the
volatile organic compounds (VOC), trace metals, and benzo(a)pyrene (BaP), the
last belonging to the large class of pollutants called the products of
Incomplete combustion (PIC). The VOC data have been obtained from either the
updated National Ambient Volatile Organic Compound Data Base^ or the Interim
Data Base for State and Local Air Toxic Volatile Organic Chemical
Measurements^ The trace metal data were obtained from the National Aerometric
Data Bank's new Aerometrlc Information Retrieval System5 (AIRS) while the
*
•
benzo(a)pyrene data came from U.S. Environmental Protection Agency's (EPA)
Atmospheric Research and Exposure Assessment Laboratory (AREAL).
This report is organized basically into'three sections: estimated
national cancer incidence for trace metals and BaP; estimated national
incidence for VOC; and lifetime additive and highest observed indqVrdual
risks. Cancer incidence are determined with unit risk values currently used
by EPA in analyses of cancer risks associated with air toxic pollutants.
Table 1 presents the 28 pollutants which are thought to be present in the
ambient air in sufficient quantities to pose a cancer risk to the general
population. Also included are the current risk values and those used in the
previous study. Of the 15 pollutants considered in both studies, ten had
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4
changes in their unit risk values. Beryllium showed the largest difference
for these pollutants with the unit risk value .increasing from 4.0 x 10"4 to
2.4 x 10"3 a six-fold increase. However, 1,3 butadiene, which was not
considered in the previous study because ambient data was not available,- shows
the largest difference in unit risk values changing from 4.6 x 10"7 to a
current value of 2.8 x 10"*.
The number of estimated cancer cases or incidence 1s found by applying a
factor which represents the chance of contracting cancer 1f an Individual is
exposed to a concentration of 1 /tg/n3 of a toxic pollutant for 70 years
(lifetime). This factor is called the unit risk. Generally,-the unit risk
value represents the probability of cancer cases, not deaths. However, since
the epidemiological studies that generated the potency number for PIC
(products of incomplete combustion).are based on lung cancer mortality, the
PIC estimates used in this study imply lung cancer deaths. The potency
factors or unit risk values represent plausible upper bounds -?' i.e. they are
unlikely to be higher, and could be substantially lower. As will be seen
later the estimation of incidence for all pollutants will be the product of
three numbers: 1) the unit risk, 2) an estimate of exposure usually an
average of annual averages across some geographical area, and 3) the exposed
' •<. —
.-*. — -
population of the geographical area. The size of the geographical area for
which incidence are estimated will vary depending upon the number of estimates
of exposures represented by the available ambient data. In this study,
incidence for the trace metals are estimated on a county basis while for the
VOCs, because of the much smaller data base, incidence estimates could only be
determined for the urban and non-urban segments of the National population.
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5
In the 1985 study, national incidence derived from ambient data were
estimated for 16 pollutants, while highest observed individual lifetime risks
*
were calculated for 21 pollutants. Also the additive lifetime individual
risks were estimated by summing together lifetime individual risks for metals,
BaP, PIC and VOC. These additive lifetime risks were estimated at two
monitoring locations, generally those With the highest pollutant levels, in
each of four metropolitan areas. Similar types of analysis will be shown in
this updated study, which addresses all of the pollutants shown In Table 1;
except as noted there.
2. 'OBJECTIVE
The objective of this report is to utilize available ambient monitoring
data for air toxics to present estimates of: national cancer incidence;
additive individual lifetime risks .in metropolitan areas, where possible; and
highest observed Individual lifetime risks for as many pollutants as possible.
3. DEVELOPING NATIONAL INCIDENCE ESTIMATES FOR TRACE METALS/
BENZO(A)PYRENE, AND VOLATILE ORGANIC COMPOUNDS
The following discusses how National estimates of incidence using
ambient data for selected trace metals BaP, and the VOCs are developed. Five
trace metals are considered: arsenic, beryllium, cadmium, chromium, and
•* • •." -.<'•—'•"
nickel. The ambient data available for these pollutants pose a problem when
national estimates are to be developed. The available ambient data is always
inadequate for the purpose of defining true population exposure especially
that portion of the population receiving the highest dose. The aim here is to
derive reasonable estimates of typical exposures in terms of long-term
averages. The number of monitoring sites and their geographic coverage for
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6
the trace metals make it more feasible to attempt estimations for the trace
metals than for volatile organic compounds. However, a major problem with the
trace metal data Is that ambient chromium and nickel concentrations reflect
the total of all particulate species, while only specific species like
chromium +6 and nickel subsulfide are thought to be carcinogenic. The
available ambient data for volatile organic compounds are typically the
results of short term special studies in selected areas. In contrast hi-vol
filters from the old National Air Surveillance Network (HASH) going back to
the early 1960s were routinely analyzed for certain metals. This original
network and the continued operation of some of these sites over the years
provide a data base that reflects year-round monitoring efforts and minimizes
the effect of seasonality on the estimates of annual averages.
For the most part, these NASN sites were located in the center city
business area. In developing these national estimates, two different
geographical extrapolations are made. The first assumes that monitoring data
from a specific site or sites are representative of concentrations over as
broad a geographical area, as a county. The second involves estimating the
average concentrations for those counties with no monitoring data. Although
obviously legitimate concerns may be raised about both of these steps, this
•« - •;. ^-t(.~T\-
discussion attempts not to assess the potential error in estimates resulting
from these extrapolations but merely to provide some perspective on the
assumptions.
Beryllium and nickel are often associated with fuel combustion
o
emissions, primarily from coal. Cadmium and chromium are more closely
associated with industrial uses, such as making steel or other alloys or
-------
7
fabricating them into end products.8 Arsenic emissions are associated with
industry (e.g. primary copper smelters) and a-lso with pesticide use. BaP
emissions are primarily associated with the emissions from coke ovens.10 In
recent years, wood burning has become a major source of BaP in some areas, but
a national data base 1s not available to measure this source. With these
emission sources involved, it is possible that a center city site could either
over- or underestimate long term average exposure for a county.
3.1 METHODOLOGY FOR TRACE METALS AND BaP
The methodology used in developing these national estimates is discussed
in terms of the various steps involved: data base selection, 'estimated county
averages, and estimation of concentrations for counties without data.
Ambient air quality data from AIRS was used for the five-trace metals,
while the BaP data.came from AREAL. For the"trace metals, all annual averages
-• . -^f
with at least 20 daily values from 1985 to 1986 were used, because they
represent the latest and best estimates of ambient concentrations. The BaP
data used were from 1986 and 1987 since earlier data (1982-85) which were to
be used were found to have a positive bias because of some unknown
contamination. Annual averages were used if there were a minimum of.twenty
24-hour samples. 1986 and 1987 BaP levels were higher (1.0 ng/ra?,v.s. 0.3
• • •. ^ -•-.
ng/m3) than those reported in 1977-80 but significantly lower than 1981-82
levels. The 1985 study on BaP and PIC incidences used data from the 1977-82
period.
For the trace metals, the valid annual averages for each site were
averaged for all available years (1985-86). Then the average of all sites in
a county was computed to determine a county wide air quality value. As
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8
discussed earlier, this temporal and spatial average estimate is assumed to
representjthe average for the county. The methodology used for BaP was
similar to that used for the trace metals but because of the relative
sparseness of the BaP data a larger geographic area than counties was used.
Two different approaches were used to extrapolate to counties without
data in order to compute national estimates. The approach used for the metals
and that used for BaP differ because of the sparseness of the available BaP
data and the apparent BaP network emphasis on eastern Industrial areas.
The approach'used to estimate county average concentrations for the
trace metals also differs slightly from that used in the 1985 study. The
earlier study used available ambient data to extrapolate to those counties
without data. Because of observed differences in ambient levels for some of
the trace metals, the data from the. counties"with, data were categorized in one
of four ways. The counties with data were categorized as being from either
"smelter" or "non-smelter", "Texas", or "non-Texas" counties. -This resulted
in four categories of county averages from which composite averages were
computed. Those counties without data were classified by the same scheme and
the appropriate average from those counties with data was assumed to apply.
As a refinement this study used estimated .county trace metal emissions
i • •. ,-f. — •
categories for those counties with data to extrapolate to the counties without
ambient data. It is assumed that the relationship between ambient trace metal
concentrations and emissions in those counties with ambient monitoring results
is the same for the counties without ambient data. All annual averages
satisfying the minimum data completeness criteria stated above were
categorized into six emission strength classes based on the estimated county
-------
9
emissions. The composite average concentration was then computed for each of
the emission classes. For counties without ambient data, the composite
average for the emission class corresponding to the estimated county emissions
was then used to represent average trace metal concentrations.
In summary, the estimate of the county trace metal average was obtained
from either monitored data, if available, or from the averages based on the
estimated trace metal emissions for the counties not having ambient monitoring
results. These average county concentration estimates were then used with the
unit risk and county population figures to estimate cancer incidence. After
either the observed or estimated average concentration was assigned to each
county, the incidence was computed for each county by multiplying the average
ambient concentration by the unit risk and population, and then dividing by 70
years in order to present the incidence on an annual basis. The national
incidence estimate was obtained by summing over all counties in the country.
County emission estimates for the trace metals were obtained by applying
speciation factors to total emissions (area + point sources) of particulates
from the most recent (1985) National Emission Data System (NEDS) summary.H**2
i^
The speciation factors used here also represent the latest estimates.
Special efforts were made to extrapolate BaP exposures.for the..entire
• • •. --f. —•
country. In this study, BaP is considered not only as a carcinogen but also
as a surrogate for a wide variety of air pollutants, produced by incomplete
combustion of fossil fuels. The national data base for BaP is much less
extensive than for the metals, and most of the network is concentrated in
eastern industrial areas. Seventy-seven site-years of data from 35 counties,
having at least twenty observations in 1986 or 1987 are included in this
analysis, and 23 of the site-years were from sites west of the Mississippi
-------
10
River. Fortunately, the BaP sites represent many of the largest urban areas
in the country, e.g. New York City, Los Angeles, and Chicago.
To avoid assuming that this data base is representative of the nation,
and to avoid the other extreme of assuming that there is no BaP problem in
areas without data, a compromise approach was developed to attempt to make the
best use of the limited available data. The basic approach was to divide the
nation into broad geographical areas patterned after the U.S. Census Division
and Regions. Because BaP levels would likely be higher in colder* climates,
some of these areas were further subdivided into the 11 areas shown in Figure
1. * this was also done for convenience to make use of census data for these 11
regions. Within each, urban and rural populations were determined, as well as
urban and rural BaP annual averages for 1986, which are also shown in Figure
1. .
Ten of the 11 regions had BaP data in the urban areas. Region III
(Florida) had no BaP data, so the urban area BaP average for the adjacent
Region II is used to represent Florida.
Current BaP data were not available for any nonurban site.
Consequently, nonurban BaP averages from the earlier study are used. The
reader should consult the earlier study fpr details on how .the nonurban
. • •. .-< —
averages were obtained.
Once these air quality values were determined, the incidence was
determined for each of the 11 geographical areas, for both urban and nonurban
segments of the population, and then the total incidence computed as the sum
of the individual area incidence.
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11
3.2 Methodology for the Volatile Organic Compounds
Because of the sparsity of available VOC.data, only a limited number of
metropolitan areas had air pollution data which satisfied the completeness
criteria of any site having a minimum of 5 observations in one quarter and at
least 10 observations for the year. The VOC data used in this analysis
represents primarily the years 1985-1987; however, in a few cases earlier data
(1980-83) was used. The California VOC data generally is from 1986 and 1987.
Other criteria requiring more complete data essentially limited the data
available for analysis to the California sites and thereby it would have been
difficult to extrapolate these data to the entire nation. It 'is recognized
that this criteria could include sites with an imbalanced representation of
samples throughout the year and could result in biased annual averages where
the data exhibit a seasonal pattern. This criterion is used to maximize the
number of valid sites, thence the geographic coverage of the available VOC
data. It is consistent with the approach used in the previous-'sttidy.
The urban areas with VOC data satisfying all the criteria varied from
four areas for styrene to 43 areas for benzene. Table 2 shows the urban areas
represented for each of the VOCs with data. Several pollutants having unit
risk values did not have any data on which to make an assessment, ..These
• " " • **?^ *"*"
pollutants include: acetaldehyde; acrylonitrile; asbestos; epichlorodhydrin;
ethylene oxide; hexachlorobenzene; propylene oxide; and 2,3,7,8-
tetrachlorodibenzo-p-dioxin. Metropolitan area population figures were used
to calculate a population-weighted VOC grand mean concentration across the
metropolitan areas represented for each pollutant (Table 3). The VOC grand
-------
12
mean concentrations are assumed to be the "best" available estimate of urban
area VOC concentrations.
• *
The same simple formula used in the earlier study was used to calculate
the cancer incidence for the VOC:
/•_ ~
Cancer Incidence r. I VOC . pop + VOC . pop
Per Mil lion \ UA UA NUA NUA,
Population
70 . 240
where r « unit risk value
VOC UA = estimated VOC grand mean concentration for urban areas
from Table 3.
pop UA = urban area U.S. population (185 million).
VOC NUA «= estimated VOC grand mean concentration for nonurban
areas from Table 3.
pop NUA « nonurban area population of the U.S. (55 million).
70 = the number of years in a lifetime.
240 - the number of millions of people in the U.S.
(used so that the rate can also be expressed as the
incidence per million population)
A slight modification in the calculations was made for the following
• • '. • '. • ,*f**~r?-
chemicals involving a large number of California areas so that the California
data would not be used to characterize non-California: benzene, carbon
tetrachloride, chloroform, ethylene dibromide, methylene chloride,
tetrachloroethylene, and trichloroethylene. For each of these pollutants, a
total of 15 urban California areas are involved. Separate incidences were
computed for California and for the remainder of the country, then they were
-------
13
added together to get the urban contribution, which was then added to the
nonurban incidences to derive the incidence total for the nation.
The urban, nonurban and total population estimate of the United States
are estimates for 1986 and are taken from the Statistical Abstract of the
United States. 1988.** The estimated VOC urban and nonurban area grand mean
concentrations are shown In Table 3. The nonurban area means are calculated
for all remote and rural sites in Reference 3. Of the 13 VOC areas in Table
3, all had urban area means, and 10 had nonurban area means. For the three
VOCs for which there are no nonurban data (formaldehyde, tetrachloroethylene
and vinylidene chloride) nonurban averages were obtained from Reference 15.
4. ESTIMATION OF NATIONAL INCIDENCE FOR TRACE METALS, BENZO(A)PYRENE, AND
THE VOLATILE ORGANIC COMPOUNDS
The national estimates of incidence for"the five trace metals and BaP
are shown in Table 4. These rates assume that values less than the minimum
detectable limit are equal to 1/2 of the minimum detectable limit, which is a
fairly standard practice in air pollution data analysis.^ A factor of 0.4
was used to adjust the total chromium (Cr) incidences to Cr+6.17 This factor
represents the average of hexavalent to total chromium concentrations
estimated from modeling done in five U.S.,cities. In subsequent,tables, only
* - •/ -•<"—
the estimated chromium +6 incidence are shown. No such factor was available
for nickel. The unit risk factor for nickel, 4.8 x 10~4, shown in the table
represents nickel subsulfide. However, because there are no known emissions
of nickel subsulfide in the county; the incidence from nickel subsulfide is
assumed to be zero. Table 4 also indicates both the extent of coverage of the
ambient data (the number of counties with data) and the relative sparseness of
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14
the BaP data. One additional point that should be made concerning BaP is that
most of these sites are located to reflect industrial sources of BaP. The
current concern with respect to the effect of wood stoves on BaP emissions
suggests the existing data base is quite limited, in that monitors generally
are not situated in areas with wood smoke problems. Table 5 provides the
pollutant specific incidence for the VOCs having both some ambient monitoring
data and unit risk values. Some discussion of these Incidence will follow in
the next two sections.
4.1 National Incidence Totals
'National incidence are summarized In Table 6 for all 20 a'ir toxic
pollutants considered. The national incidence for trace metals, BaP and PIC
and number of incidence per million population are based on the number of
incidence from Table 4. Chromium +6 is shown here because it is the species
associated with cancer risk. The formaldehyde data are primarily taken from a
recent 1987-88 study done in 17 urban areas.*8 The incidence rates for the 10
VOCs were estimated using the formula given in Section 3.2 above. The total
incidence for all 20 pollutants was 1924, or approximately 8.0 per million
people. Eight pollutants account for over 90 percent of the risk: PIC,
formaldehyde, 1,3 butadiene, benzene, chloroform, chromium +6, arsenic, and
* • -^» •**"* *
* " *• **T^* ^*"
ethylene dibromide. As discussed below, some caution is necessary in
interpreting these results, particularly for 1,3 butadiene.
4.2 Comparison of Previous and Current Cancer Incidence Studies
In the 1985 study, 1562 excess cancer cases, or 6.8 cases per million
people, were reported based on a U.S. population estimate of 230 million.
This figure represented 16 pollutants, however, the unit risk values for 10 of
-------
15
these pollutants have since changed. Correcting the earlier incidence figures
by using the new unit risk values increases the total incidence rates from
1562 to 1686 cases, or 7.3 per million population. This compares with
approximately the same number of cases (1597) and rate per million (6.7) for
the current assessment for the pollutants in common. Table 7 compares the
incidence In the old and new studies, using the same unit risk numbers. It is
Indeed quite unexpected that the totals are so close, owing to the many
sizeable differences for certain pollutants for example benzene or chloroform.
One pollutant, methyl chloride, which accounted for only one Incidence, was
included in the earlier study but not in the current one because it no longer
is on the 11st of pollutants with unit risk factors. So, for the pollutants
in common between the two studies.there really is no significant difference in
the number of excess cancer cases estimated"
However, as was shown above, the current study estimates 1924 excess
cancer cases per year. The main differences between this figure and the 1597
cases based on 16 pollutants are the incidence attributed to 1,3 butadiene
(244). In the case of 1,3 butadiene, urban concentration estimates are based
solely on 12 urban areas situated in northern California representing such
urban areas as: San Francisco, San Jose,, and Sacramento. These, aje the only
--*'—•
1,3 butadiene data representing 24-hour sampling that were available. Using
1,3 butadiene from 20 urban areas which measured 6 to 9 a.m. average
concentrations at one monitoring site in the area, the incidence would be much
higher (1055). Since 1,3 butadiene is emitted by automobiles, the 6 to 9 a.m.
average undoubtedly would overestimate a long term average based on all hours
in the day. For example, 6-9 a.m. carbon monoxide concentrations are on the
-------
16
average 30 percent times higher than levels representing an entire day.
Adjusting the 1,3 butadiene in the 20 cities by this factor would result in an
incidence of about 800 -- or over three times the estimate using the
California data. In the case of vinylidene chloride, the 10 excess case
figure is based on ten urban areas. Data from eight of these areas came from
a study done in 1980 by Singh et. al.19 The two other areas included are
Sacramento, CA and Charleston (Institute) WV. Two New Jersey areas (Camden
and Newark) were excluded from this analysis because their vinylidene chloride
levels were more than an order of magnitude higher than the other results.
Although there is significant concern about the accuracy of all of the
national estimates, it is clear that for 1,3 butadiene and vinylidene
chloride, the concern is even greater. In the assessment of ethylene
dibromide, a very high annual average of 2.12 /tg/m3 was not used because it
was more than an order of magnitude larger than the next highest average
available. The next largest average was 0.2 0g/m3, while most'of the averages
were less than 0.1 /tfj/m3.
5. INDIVIDUAL LIFETIME RISKS
Individual lifetime risks are examined in two ways, as additive
individual lifetime risks and as the highest observed individual lifetime
« '. " -T*. --• *
• •, ""^ ""* "
risks. Additive raultipollutant individual lifetime risks are defined as the
sum of lifetime individual risks for metals, BaP, VOC and PIC at a monitoring
site within a city where a battery of air toxic pollutants is being monitored.
These are summarized in Table 8 for four metropolitan areas, Baton Rouge,
Boston, Chicago, and Los Angeles. For the most part, the data shown represent
the year given alongside the city name; for the cases footnoted, data from
-------
17
other years were used. The added individual risks are influenced by the
number of pollutants for which there are available data at the given
monitoring locations. Note that 1,3 butadiene is not included for any of
these cities. Boston had the fewest number of pollutants represented, 11, out
of the 20 pollutants investigated. Given the limitations in the available
data, it can be seen from Table 8 that additive individual risks on the order
of 10"* are not uncommon.
Highest observed Individual lifetime risks are calculated for 20
pollutants. The calculations are made by using the simple formula:
Highest
Observed Highest arithmetic Unit
Individual - mean concentration X Risk
Lifetime Risk observed
The air pollution data base varies considerably. Table 9 gives, the
highest observed individual risks for the trace metals and benzo(a)pyrene,
including PIC. This risk, based on monitoring data, represents the highest
*
observed risk in the nation. Since monitoring data generally would be
expected to underestimate the "true" maximum, these results should be viewed
as approximations. Also, generally speaking, the larger the number of sites
represented, the better the chances are of hitting the "true" maximum . In
this light, the data base for BaP (44 site years) should not provide as good
an approximation as the more nearly complete trace metal data. The maximum
individual risks range from a low of 1.7xlO"5 for beryllium to a high of
8.4xlO"3 for PIC. Arsenic has the next highest risk of 3.9xlO"4.
Table 10 gives the highest observed individual lifetime risks for the
VOC pollutants studied. Once again, the number of site years of data varies
widely, with benzene having the most data (108 site years) and styrene the
-------
18
least (6 site years). The highest observed individual lifetime risks range
from a low of l.SxlO"6 for styrene to a high .of 3.0xlO~4 for formaldehyde.
Several of the VOC have risks in the IxlO"4 to 9.9xlO~4 range. These include
chloroform (2.1xlO~4) benzene (1.7xlO~4), 1,3 butadiene (1.3xlO'4) ethylene
dichloride (l.lxltT4), and formaldehyde (3.0xl(T4).
6. SUMMARY
/ The reader 1s cautioned, when Interpreting this Information, that the
national cancer Incidence are based on very spotty VOC and BaP air quality
data, as well as on uncertain unit risk factors. In the opinion of the
authors of this report, eventually some measure of Imprecision in the unit
risk rates should be introduced to provide upper and lower bounds to the
national cancer incidence rates. It may also be appropriate to view these
estimates as only one approach, and to consider the results in the context of
estimates obtained from alternative methods.
When interpreting the combined national incidence rate for all 20
pollutants, the reader should keep in mind that all the individual incidence
rates are added together, under the assumption that their combined effects are
additive. People can be exposed to not one but several of these pollutants
simultaneously, and there could be synergistic effects associated .with these
. - •." --*"'••
pollutants which could increase or decrease the national incidence rates.
More and better monitoring data are needed to provide better estimates
of the rates of true national cancer incidence due to air toxic pollution.
This should be coupled with some measure of uncertainty for the unit risks.
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19
REFERENCES
1. Elaine Haemisegger, et al., The Air Toxics Problem in the United States:
—-An-^nalvsis of Cancer Risks for Selected Pollutants. EPA-450/1-85-001,
U. S. Environmental Protection Agency, Research Triangle Park, NC, May
1985.
2. William F. Hunt, Jr., et al., Estimated Cancer Incidence Rates for
Selected Toxic Air Pollutants Using Ambient Air Pollution Data.
Unpublished Report, April 1985.
3. J. J. Shah and E. K. Heyerdahl, National Ambient Volatile Organic
Compounds fVOC/s) Data Base Update. U. S. Environmental Protection
Agency, Atmospheric Sciences Research Laboratory, Research Triangle
Park, NC, February 1988.
4. A. Pollack, Systems Applications, Inc., Updated Report on the Interim
Data Base for State and Local Air Toxic Volatile Organic Chemical
Measurements. Prepared for Robert B. Faoro, U. S. Environmental
Protection Agency, Office of Air Quality Planning and Standards,
Research Triangle Park, NC, August 1988.
5. Aerometric Information Retrieval System, Office of Air Quality Planning
and Standards, U. S. Environmental Protection Agency, Research Triangle
Park, NC, March 1988. . " ,
6. J. Bumgamer, Atmospheric Research and Exposure Assessment Laboratory,
U. S. Environmental Protection Agency, Research Triangle Park, NC,
September 1988.
7. F. S. Hauchman, Memorandum on Air Toxics Unit Risk Estimates, Office of
Air Quality Planning and Standards, U. S. Environmental Protection
Agency, Research Triangle Park, NC, June 1988.
8. R. B. Faoro and T. B. McMullen, National Trends in Trace Metals in
Ambient Air. 1965-1974. EPA-450/1-77-003, U. S. Environmental Protection
Agency, Research Triangle Park, NC, February 1977.
• " *- . *"?^ '*""" *
9. B. E. Suta, Human Exposures to Atmospheric Arsenict SRI International,
Prepared for A. P. Carl in and J. D. Cirvello, U. S. Environmental
Protection Agency, Offices of Research and Development and Air Quality
Planning and Standards, September 1978.
10. R. B. Faoro, and J. A. Manning, Trends in Benzo(a)Pyrene, 1966-77
Journal of the Air Pollution Control Association Volume 31, No. 1,
January 1981.
11. J. J. Wind, "Gateway to EPA Program Systems," American Management
Systems, October 1987.
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20
12. Aerometric Information Retrieval System - National Emissions Data
Systems National Emissions Summary (1985), U. S. Environmental
—Protection Agency, Office of Air Quality Planning and Standards,
Research Triangle Park, NC, August 1987.
13. Air Emissions Species Manual - Volume II Particulate Matter Species
Profiles, EPA-450/2-88-036, U. S. Environmental Protection Agency,
Research Triangle Park, NC, April 1988.
14. Statistical Abstract of the United States, 1988, National Data Book and
Guide to Sources, U. S. Department of Commerce, Bureau of the Census,
Washington, DC, December 1987.
15. Personal Communication, William Lonneman, U. S. Environmental Protection
Agency to Robert 8. Faoro, U. S. Environmental Protection Agency,
Research Triangle Park, NC, June 1984.
16."Guidelines for the Evaluation of Air Quality Data, U. S. 'Environmental
Protection Agency, Office of Air Quality Planning and Standards,
Research Triangle Park, NC, Publication No. OAQPS 1.2-015, February
1974.
17. Personal communication, Tom Lahr, U. S. Environmental Protection Agency
to Robert Faoro, U. S. Environmental Protection Agency, October 1, 1988.
18. R. A. McAllister, et a!., 1988 Nonmethane Organic Compound Monitoring
Program Volume lit Urban Air Toxics Monitoring Program. EPA-450/4-89-
005, Office of Air Quality Planning and Standards, U. S. .Environmental
Protection Agency, Research Triangle Park, NC 27711.
19. H. B. Singh, et al., Measurements of Hazardous Organic Chemicals in the
Ambient Atmosphere. EPA-600/53-83-002, U. S. Environmental Protection
Agency, Research Triangle Park, NC 27711.
-------
TABLE 1
POLLUTANTS "CONSIDERED IN UPDATED. AIR TOXIC ASESSMENT
WITH THE OLD AND CURRENT UNIT RISK VALUES.
PREVIOUSLY USED UNIT
POLLUTANT RISK ESTIMATES
(ug/ra3)-l
Acet aldehyde a
Acrylonitrile3
Arsenic^
Asbestos3
Benzene1*
Benzofrlpyrene (BaP)b
Beryl liuinP
1,3-butadieneP
.Cadmium5
"Caroon tetrachloride5
Chloroform5
Chromium (VI )b
Ethyl ene dichloride5
Epichlorohydrin3
^Ijiylene di bromide0
^Ptylene oxide3 • .- . •
Formaldehyde5
Hexachlorobenzene. (HBC)3 -
Methyl ene chloride5
Nickel - SubsulfideP
Products Incomplete Combustion (PIC)b
Propylene oxide3
Styrene0
2 ,3,7 ,8-tetrachl orodi benzo-rp-di oxi n3
Tetrachl oroethyl ene5
Trichl oroethyl ene5
Vinyl chloride0
Vinyl idene chloride5
Not available
Same as current value
Same as current value
Not available
6.9 x 10-fr '
3.-3 x 10-3
4.0 x 10-4
4.6 x 10-7
2.3 x 10-3
Sane as current value
1.0 x 10-5.
Same as current value .
Same as current value
2.2 x 10-7
5.1 x 10-4
3.6 x 10-4 """. .
6,1 x 10-6
Not available
1.8-x 10-7 •
3.3 x 10-4
Same as current value
1.2 x-10-4
2.9 x 10-7
Not available
1.7 x 10-6
4.1 x 10-6
2.6 x 10-6
4.2 x 10-5
*
CURRENT
UNIT RISK ESTIMATE
(ug/m3)-l
2.2 x lO-6
6.8 x 10-5
4.3 x 10-3
2.3 x 10-1
8.3 x 10-6
1.7 x 10-3
2.4 x 10-3
2.8 x 10-4
1 .8 x 10-3
1.5 x 10-5
2.3 x 10-5
1 .2 x 10-2
2.6 x 10-5
1 .2 x lO-6
. . 2.2.x 10-4
1.0-x 10r4
1.3x10-5
4.9 x 10-4
4.7 x lO-7
•' 4.8 x 10-4
4.2 X lO-1
3.7 x 10-6
5.7 x 10-7
(fibers/ml
3.3 x 10-5 (pg/n»3)-l
5.8 x lO-7
1.7 x 10-6
4.1 x lO-6
'5.0 x 10-5
a These pollutants did not have data and were not included in the
Study.
b These pollutants were included in previous assessment. Methyl
chloride considered in earlier study was omitted from this study
because it was not on the current list of pollutants with unit risk
values.
These pollutants were not considered in the previous study.
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EPA-454/B-93/051
Appendix F
Revision No. 0
Date: March 1994
Page F-l
APPENDIX F
SAMPLE WIND ROSES FOR THE PAMS PROGRAM
-------
conducive days
Atlanta GA
10 years
AM
observed highs
PM
5 years
AM
-------
conducive days
Chicago IL
10 years
AM
observed highs
PM
5 years
AM
PM
-------
conducive days
SE Desert (Daggett)
10 years
observed highs
PM
PM
1-6 7-16 17-27 >= 28
ok"
-------
conducive days
San Diego CA
10 years
AM
observed highs
PM
5 years
AM
2C1
-------
conducive days
Washington DC
10 years
AM
observed highs
PM
5 years
.AM
PM
1-6 7-16 17-27 >= 28
knots
-------
conducive days
Philadelphia PA
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27 >» 28
knots
-------
conducive days
New York, NY
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27>s28
calrrt I I LZZ3
knots
-------
conducive days
Los Angeles CA
10 years
AM
observed highs
5 years
AM
U
-------
conducive days
Houston TX
10 years
AM
observed highs
PM
5 years
AM
-------
conducive days
Hartford Ct
10 years
AM
observed highs
PM
5 years
AM
PM
ofc
-------
conducive days
Boston MA
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27>=28
I I I I
knots
n«r
"TW5 5t!%
-------
conducive days
Baltimore MD
10 years
AM
observed highs
PM
5 years
AM
PM
-------
conducive days
Sacramento CA
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27 >= 28
ealfTJ 1 I I 1
0%
-------
conducive days
Providence Rl
10 years
AM
observed highs
PM
5 years
AM
PM
-------
conducive days
Milwaukee Wl
10 years
AM
observed highs
PM
5 years
AM
PM
knots
-------
conducive days
Baton Rouge LA
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27 >s 28
Knots
-------
conducive days
San Joaquin (Bakersfield)
10 years
AM
observed highs
PM
5 years
AM
1-6 7-16 17-27>=28
1 1 1 1
-------
conducive days
San Joaquin (Fresno)
10 years
AM
observed highs
PM
5 years
AM
H7*
-------
conducive days Springfield (Worcester met data) observed highs
10 years
AM |
PM
5 years
AM *
PM
1-6 7-16 17-27 >= 28
calrrj I I HI
-------
conducive days Portsmouth with Portland Met data
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27 >= 28
1 1 1 1
ok
-------
conducive days Portsmouth with Concord Met data observed highs
10 years
AM
PM
5 years
AM
PM
1-6 7-16 17-27 >» 28
calmf I I LIT"
ok
-------
conducive days
Beaumont-Port Arthur TX
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27 >= 28
knots
-------
conducive days Ventura (Santa Barbara)
10 years
observed highs
AM
PM
-------
conducive days
3 Paso, TX
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27 >* 28
-L
-L
knots
-------
conducive days
Raleigh-Durtiam NC
10 years
AM
observed highs
PM
5 years
AM
PM
1-6 7-16 17-27>=28
I I 1 1
-------
conducive days Greensboro-Winston-Salem observed highs
10 years
AM
PM
5 years
AM
PM
1-6 7-16 17-27>s28
caln) I I =CZ3
-------
conducive days
Charlotte NC
10 years
AM
observed highs
PM
5 years
AM
PM
7-16 17-27>=28
1 » 1 1
ok-
-------
EPA-454/B-93/051
Appendix G
Revision No. 0
Date: March 1994
Page G-l
APPENDIX G
OUTPUTS FROM THE SCREEN MODEL
-------
02/23/94
13:59:49
*** SCREEN2 MODEL RUN ***
*** VERSION DATED 92245 ***
INT SOURCE EFFECT ON URBAN PAMS SITE
SIMPLE TERRAIN INPUTS:
SOURCE TYPE
EMISSION RATE (G/S)
STACK HEIGHT (M)
STK INSIDE DIAM (M)
STK EXIT VELOCITY (M/S)>
STK GAS EXIT TEMP (K) •
AMBIENT AIR TEMP (K)
RECEPTOR HEIGHT (M)
URBAN/RURAL OPTION
BUILDING HEIGHT (M)
MIN HORIZ BLDG DIM (M) '
MAX HORIZ BLDG DIM (M) ••
POINT
1.00000
12.0000
.5000
10.0000
298.0000
298.0000
2.0000
URBAN
10.0000
50.0000
100.0000
BUOY. FLUX = .000 M**4/S**3; MOM. FLUX
*** FULL METEOROLOGY ***
**********************************
*** SCREEN AUTOMATED DISTANCES ***
6.250 M**4/S**2.
*** TERRAIN HEIGHT OF
0. M ABOVE STACK BASE USED FOR FOLLOWING DISTANCES ***
DIST
|(M)
50.
100.
200.
300.
400.
500.
600.
700.
800.
900.
1000.
1100.
1200.
1300.
1400.
1500.
1600.
1700.
1800.
1900.
2000.
2100.
2200.
2300.
2400.
£500.
•600.
5700.
2800.
2900.
CONC
(UG/M**3)
822.6
610.6
378.8
282.9
208.4
156.9
122.2
98.32
81.21
68.54
58.89
51.35
45.34
40.45
36.43
33.06
30.20
27.76
25.66
23.82
22.21
20.79
19.52
18.39
17.38
16.46
15.63
14.87
14.18
13.55
STAB
3
4
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
U10M
(M/S)
1.0
1.0
1.5
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
USTK
(M/S)
1.0
1.0
1.6
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
MIX :
(M
320
320
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
10000
HT
) I
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0 -
.0
.0
.0
.0
.0
.0
.0
.0
.0
PLUME
HT (M)
15.88
17.89
15.13
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
20.70
SIGMA
Y (M)
10.89
15.69
21.17
31.18
40.85
50.21
59.27
68.06
76.59
84.89
92.97
100.83
108.50
115.99
123.30
130.44
137.43
144.27
150.97
157.54
163.98
170.30
176.50
182.59
188.57
194.45
200.24
205.93
211.54
217.05
SI
Z
10
13
14
19
25
30
34
39
43
46
50
54
57
60
63
66
69
72
74
77
80
82
84
87
89
91
93
96
98
100
GMA
(M)
.00
.79
.03
.93
.30
.24
.82
.11
.15
.97
.60
.06
.37
.55
.61
.56
.42
.18
.86
.47
.00
.47
.87
.22
.52
.77
.96
.12
.23
.30
DWASH
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
-------
*** SCREEN2 MODEL RUN ***
*** VERSION DATED 92245 ***
POINT SOURCE EFFECT ON RURAL PAMS SITE
02/23/94
14:14:23
SIMPLE TERRAIN INPUTS:
SOURCE TYPE
EMISSION RATE (G/S)
STACK HEIGHT (M)
STK INSIDE DIAM (M)
STK EXIT VELOCITY (M/S)<
STK GAS EXIT TEMP (K) •
AMBIENT AIR TEMP (K)
RECEPTOR HEIGHT (M)
URBAN/RURAL OPTION
BUILDING HEIGHT (M)
MIN HORIZ BLDG DIM (M) •
MAX HORIZ BLDG DIM (M)
POINT
1.00000
12.0000
.5000
10.0000
298.0000
298.0000
2.0000
RURAL
10.0000
50.0000
100.0000
BUOY. FLUX = .000 M**4/S**3; MOM. FLUX
*** FULL METEOROLOGY ***
6.250 M**4/S**2.
*** SCREEN AUTOMATED DISTANCES ***
**********************************
*** TERRAIN HEIGHT OF
0. M ABOVE STACK BASE USED FOR FOLLOWING DISTANCES ***
DIST
(M)
50.
100.
200.
300.
400.
500.
600.
700.
800.
900.
1000.
1100.
1200.
1300.
1400.
1500.
1600.
1700.
1800.
1900.
2000.
2100.
2200.
2300.
2400.
2500.
2600.
2700.
2800.
2900.
CONG
(UG/M**3)
976.5
1058.
694.2
546.2
452.9
396.3
355.8
318.5
285.7
257.3
233.1
212.2
200.7
191.4
182.1
173.0
164.2
155.9
148.1
140.8
134.1
127.8
122.0
116.5
111.4
106.7
102.3
98.13
94.25
90.61
STAB
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
U10M
(M/S)
3.0
2.5
2.0
2.0
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
USTK
(M/S)
3.3
2.8
2.2
2.2
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.7
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
MIX HT
(M) 1
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0 .
10000.0
10000.0
10000.0
10000.0
PLUME
HT (M)
12.23
12.45
13.00
13.00
14.71
14.71
14.71
14.71
14.71
14.71
14.71
14.71
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
20.37
SIGMA
Y (M)
2.14
4.07
7.73
11.23
14.64
17.97
21.24
24.46
27.63
30.78
33.88
36.96
40.01
43.04
46.05
49.03
51.99
54.94
57.87
60.78
63.68
66.56
69.42
72.28
75.12
77.95
80.76
83.57
86.36
89.15
SIGMA
Z (M)
5.74
7.75
8.39
9.68
9.96
10.77
11.84
12.85
13.83
14.47
15.32
16.14
15.97
16.77
17.56
18.32
19.06
19.79
20.50
21.20
21.63
22.21
22.78
23.34
23.89
24.42
24.95
25.47
25.98
26.48
r^Tjj^ ^^^i
t' *>*AW^H
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
SS
ssf
s^
SS
SS
SS
-------
3000.
12.97
1.0
1.1 10000.0
KAXIMUM 1-HR CONCENTRATION AT OR BEYOND
50. 822.6 3 1.0 1.0
50. M:
320.0 15.88
20.70 222.49
10.89
102.34
10.00
SS
SS
MEANS NO CALC MADE (CONC - 0.0)
MEANS NO BUILDING DOWNWASH USED
DWASH=HS MEANS HUBER-SNYDER DOWNWASH USED
DWASH=SS MEANS SCHULMAN-SCIRE DOWNWASH USED
DWASH=NA MEANS DOWNWASH NOT APPLICABLE, X<3*LB
*** CAVITY CALCULATION - 1 ***
CONC (UG/M**3) = .0000
CRIT WS @10M (M/S) = 99.99
CRIT WS 6 HS (M/S) = 99.99
DILUTION WS (M/S) «= 99.99
CAVITY HT (M) = 10.02
CAVITY LENGTH (M) = 50.00
ALONGWIND DIM (M) = 50.00
*** CAVITY CALCULATION - 2 ***
CONC (UG/M**3) = .0000
CRIT WS glOM (M/S) = 99.99
CRIT WS § HS (M/S) = 99.99
DILUTION WS (M/S) = 99.99
CAVITY HT (M) = 10.00
CAVITY LENGTH (M) = 38.89
ALONGWIND DIM (M) = 100.00
CAVITY CONC NOT CALCULATED FOR CRIT WS > 20.0 M/S. CONC SET =0.0
*** SUMMARY OF SCREEN MODEL RESULTS ***
***************************************
CALCULATION
PROCEDURE
SIMPLE TERRAIN
MAX CONC
(UG/M**3)
DIST TO
MAX (M)
TERRAIN
HT (M)
822.6
50.
0.
***************************************************
BER TO INCLUDE BACKGROUND CONCENTRATIONS **
***********************************************
-------
*** SCREEN2 MODEL RUN ***
*** VERSION DATED 92245 ***
AREA SOURCE EFFECT ON RURAL PAMS SITE
SIMPLE TERRAIN INPUTS:
SOURCE TYPE
EMISSION RATE (G/(S-M**2)) -
SOURCE HEIGHT (M)
LENGTH OF SIDE (M)
RECEPTOR HEIGHT (M)
URBAN/RURAL OPTION
02/24/94
15:30:23
AREA
.400000E-03
12.0000
50.0000
2.0000
RURAL
BUOY. FLUX = .000 M**4/S**3; MOM. FLUX =
*** FULL METEOROLOGY ***
.000 M**4/S**2
*** SCREEN AUTOMATED DISTANCES ***
**********************************
*** TERRAIN HEIGHT OF
0. M ABOVE STACK BASE USED FOR FOLLOWING DISTANCES ***
DIST
(M)
50.
100.
200.
300.
400.
500.
600.
700.
800.
900.
1000.
1100.
1200.
1300.
1400.
1500.
1600.
1700.
1800.
1900.
2000.
2100.
2200.
2300.
2400.
2500.
2600.
2700.
2800.
2900.
3000.
CONG
(UG/M**3)
690.
668.
629.
582.
555.
523.
523.
495.
457.
418.
382.
349.
319.
293.
269.
249.
230.
214.
199.
186.
174.
164.
154.
146.
138.
131.
125.
119.
113.
108.
103.
1
8
0
7
0
5
6
7
8
9
1
0
4
1
7
0
6
1
4
2
4
2
9
5
7
7
2
2
7
6
9
STAB
1
2
4
5
5
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
6
U10M
(M/S)
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
USTK
(M/S)
1.0
1.0
1.0
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
MIX HT PLUME
(M) HT (M)
320.0
320.0
320.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0 .
10000.0
10000.0
10000.0
10000.0
10000.0
10000.0
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
SIGMA
Y (M)
6.80
14.24
13.53
15.43
20.58
17.03
20.32
23.55
26.74
29.89
33.01
36.10
39.16
42.19
45.20
48.19
51.16
54.11
57.04
59.96
62.86
65.75
68.62
71.47
74.32
77.15
79.97
82.78
85.58
88.36
91.14
SIGMA
Z (M)
10
12
9
9
11
8
9
11
12
13
14
15
15
16
17
18
18
19
20
21
21
22
22
23
24
24
25
25
26
26
27
.20
.74
.30
.17
.26
.68
.96
.16
.20
.20
.14
.00
.84
.64
.43
.20
.94
.67
.39
.09
.76
.34
.90
.46
.01
.54
.07
.58
.09
.59
.07
DWASH
NO
NO
NO g
NO^
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
N0|
MAXIMUM 1-HR CONCENTRATION AT OR BEYOND
59. 703.2 1 1.0 1.0
50. M:
320.0 12.00
9.57 11.54
NO
DWASH= MEANS NO CALC MADE (CONC =0.0)
-------
DWASH=NO MEANS NO BUILDING DOWNWASH USED
DWASH=HS MEANS HUBER-SNYDER DOWNWASH USED
DWASH=SS MEANS SCHULMAN-SCIRE DOWNWASH USED
DWASH=NA MEANS DOWNWASH NOT APPLICABLE, X<3*LB
***************************************
*** SUMMARY OF SCREEN MODEL RESULTS ***
***************************************
CALCULATION MAX CONG DIST TO TERRAIN
PROCEDURE (UG/M**3) MAX (M) HT (M-)
SIMPLE TERRAIN 703.2 59. 0.
***************************************************
** REMEMBER TO INCLUDE BACKGROUND CONCENTRATIONS **
***************************************************
-------
*** SCREEN2 MODEL RUN ***
*** VERSION DATED 92245 ***
AREA SOURCE EFFECT ON URBAN PAMS SITE
SIMPLE TERRAIN INPUTS:
SOURCE TYPE
EMISSION RATE (G/(S-M**2)) =
SOURCE HEIGHT (M)
LENGTH OF SIDE (M)
RECEPTOR HEIGHT (M)
URBAN/RURAL OPTION
02/24/94
15:33:02
AREA
.400000E-03
12.0000
50.0000
2.0000
URBAN
BUOY. FLUX = .000 M**4/S**3; MOM. FLUX =
*** FULL METEOROLOGY ***
.000 M**4/S**2
*** SCREEN AUTOMATED DISTANCES ***
**********************************
*** TERRAIN HEIGHT OF
0. M ABOVE STACK BASE USED FOR FOLLOWING DISTANCES ***
DIST
(M)
50.
100.
200.
300.
400.
500.
600.
700.
800.
900.
1000.
1100.
1200.
1300.
1400.
1500.
1600.
1700.
1800.
1900.
2000.
2100.
2200.
2300.
2400.
2500.
2600.
2700.
2800.
2900.
3000.
CONC
(UG/M**3)
667
621
561
365
246
177
134
106
86.
72.
61.
53.
47.
41.
37.
34.
31.
28.
26.
24.
22.
21.
19.
18.
17.
16.
15.
15.
14.
13.
13.
.8
.0
.6
.2
.5
.4
.6
.3
75
55
90
67
18
94
65
08
07
50
29
37
70
22
90
73
68
74
88
10
39
74
14
STAB
3
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
U10M
(M/S)
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
USTK
(M/S)
1.0
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
1.1
MIX HT PLUME
(M) HT (M)
320.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
10000.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 .
0
0
0
0
0
0
0
0
0
0
0
0
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
12.00
SIGMA
Y (M)
4.77
7.79
18.28
28.39
38.16
47.60
56.74
65.61
74.21
82.57
90.71
98.63
106.36
113.89
121.25
128.44
135.48
142.36
149.10
155.70
162.17
168.53
174.76
180.88
186.89
192.80
198.62
204.34
209.96
215.50
220.96
SIGMA
Z (M) DWASH
14.36
8.96
15.37
21.14
26.41
31.26
35.78
40.01
44.00
47.77
51.36
54.79
58.07
61.23
64.26
67.19
70.03
72.77
75.44
78.02
80.54
83.00
85.39
87.73
90.01
92.25
94.44
96.58
98.69
100.75
102.77
NO
NO
NO.-
N<4
NC«
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NO
NQtf
MAXIMUM 1-HR CONCENTRATION AT OR BEYOND
64. 683.0 4 1.0 1.0
50. M:
320.0 12.00
5.84
12.00
NO
DWASH= MEANS NO CALC MADE (CONC =0.0)
-------
3000.
87.20
1.0
1.1 10000.0 20.37
MAXIMUM 1-HR CONCENTRATION AT OR BEYOND 50. M:
100. 1058. 6 2.5 2.8 10000.0 12.45
MEANS NO CALC MADE (CONC =0.0)
MEANS NO BUILDING DOWNWASH USED
DWASH=HS MEANS HUBER-SNYDER DOWNWASH USED
DWASH=SS MEANS SCHULMAN-SCIRE DOWNWASH USED
DWASH=NA MEANS DOWNWASH NOT APPLICABLE, X<3*LB
*********************************
*** SCREEN DISCRETE DISTANCES ***
*********************************
91.92
4.07
26.98
7.75
SS
SS
*** TERRAIN HEIGHT OF 0. M ABOVE STACK BASE USED FOR FOLLOWING DISTANCES ***
U10M USTK MIX HT PLUME SIGMA SIGMA
STAB (M/S) (M/S) (M) ' HT (M) Y (M) Z (M) DWASH
DIST
(M)
CONC
(UG/M**3)
DWASH= MEANS NO CALC MADE (CONC =0.0)
DWASH=NO MEANS NO BUILDING DOWNWASH USED
DWASH=HS MEANS HUBER-SNYDER DOWNWASH USED
DWASH=SS MEANS SCHULMAN-SCIRE DOWNWASH USED
DWASH=NA MEANS DOWNWASH NOT APPLICABLE, X<3*LB
*** CAVITY CALCULATION - 1 ***
CONC (UG/M**3) = .0000
CRIT WS @10M (M/S) = 99.99
CRIT WS 6 HS (M/S) = 99.99
DILUTION WS (M/S) = 99.99
_CAVITY HT (M) = 10.02
WITY LENGTH (M) = 50.00
JONGWIND DIM (M) = 50.00
***
CAVITY CALCULATION - 2 ***
CONC (UG/M**3) = .0000
CRIT WS §10M (M/S) = 99.99
CRIT WS 6 HS (M/S) = 99.99
DILUTION WS (M/S) = 99.99
CAVITY HT (M) = 10.00
CAVITY LENGTH (M) = 38.89
ALONGWIND DIM (M) = 100.00
CAVITY CONC NOT CALCULATED FOR CRIT WS > 20.0 M/S. CONC SET =0.0
***************************************
*** SUMMARY OF SCREEN MODEL RESULTS ***
***************************************
CALCULATION
PROCEDURE
SIMPLE TERRAIN
MAX CONC
(UG/M**3)
DIST TO
MAX (M)
TERRAIN
HT (M)
1058.
100.
0.
***************************************************
** REMEMBER TO INCLUDE BACKGROUND CONCENTRATIONS **
***************************************************
-------
DWASH=NO MEANS NO BUILDING DOWNWASH USED
DWASH-HS MEANS HUBER-SNYDER DOWNWASH USED
DWASH-SS MEANS SCHULMAN-SCIRE DOWNWASH USED
DWASH-NA MEANS DOWNWASH NOT APPLICABLE, X<3*LB
***************************************
*** SUMMARY OF SCREEN MODEL RESULTS ***
***************************************
CALCULATION MAX CONC DIST TO TERRAIN
PROCEDURE (UG/M**3) MAX (M) HT (M)
SIMPLE TERRAIN 683.0 64. 0.
***************************************************
** REMEMBER TO INCLUDE BACKGROUND CONCENTRATIONS **
***************************************************
-------
EPA-454/B-93/051
Appendix H
Revision No. 0
Date: March 1994
Page H-l
APPENDIX H
LIST OF DESIGNATED REFERENCE AND EQUIVALENT METHODS
-------
*
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METHOD CODES
Method
al Methods
Ref. method (panrosanOine)
TechnicoD I (jpararosaniline)
Techaieon D (Panroaaniline)
Advanced Pollution Inatr. 100
AutcoSOO
Beekman953
Bendu8303
Dasibi 4108
EovironoemeotS.A. AF21M
Lev Sicgier AM2020
Lear Siegler SMI 000
Lear Siegler ML9850
Meloy SA185-2A
Meloy SA285E
Meloy SA700
Monitor Ltbt 8450
Monitor L»b» 8850
Monitor Labs 8850S
Philip. PW9700
Philips PW9755
Thermo Electron 43
Thermo Electron 43 A
Advanced Pollution Instr. 400
Beckman 950A
Bendu8002
CS12000
Dasibi 1003-AH.-PC.-RS
Dttibi 1008-AH
Environici 300
Lear Siegler ML98 10
McMillan 1100-1
McMillan 1100-2
McMillan 1100-3
Meloy OA325-2R
Meloy OA3SO-2R
Monitor Labs 841 OE
Monitor Labs 88 10
PCI Ozone Corp. LC-12
Philip. PW9771
Thermo Electron 49
CO Analvzm
Advanced Pollution lostr. 300
Beckman 866
Bendix 850I-5CA
Dutbi 3003
Dasibi 3008
Horib. AQM-10,-11,-12
Horiba 300E/300SE
Le4r Siegier ML 9830
MASS - CO 1 (Massachusetts)
Monitor Labs 83 10
Monitor Labs 8830
MSA 2025
Thermo Electron 48
Designation
Nirmh*r
Method
Code
097
EQS-0775-001 097
EQS-0775-002 097
EQSA-0990-077 077
EQSA-0877-024 024
EQSA-067S-029 029
EQSA-1078-030 030
EQSA-10S6-061 061
EQSA-0292-084 084
EQSA-1280-049 049
EQSA-1275-005 005
EQSA-0193-092 092
EQSA-1275-006 006
EQSA-1078-032 032
EQSA-0580-046 046
EQSA-0876-013 513
EQSA-0779-039 039
EQSA-0390-075 075
EQSA-0876-011 511
EQSA-0676-010 010
EQSA-0276-009 009
EQSA-0486-060 060
EQOA-0992-087 087
RFOA-0577-020 020
RFOA-0176-007 007
RFOA-0279-036 036
EQOA-0577-019 019
EQOA-0383-056 056
EQOA-0990-078 078
EQOA-0193-091 091
RFOA-1076-014 514
RFOA-1076-015 515
RFOA-1076-016 016
RFOA-1075-003 003
RFOA-1075-004 004
RFOA-1176-017 017
EQOA-0881-053 053
EQOA-0382-055 055
EQOA-0777^23 023
EQOA-0880-047 047
RFCA-1093-093 093
RFCA-0876-012 012
RFCA-0276-008 008
RFCA-0381-051 051
RFCA-0488-067 067
RFCA-1278-033 033
RFCA-1180-048 048
RFCA-0992-088 088
RFCA-1280-050 050
RFCA-0979-041 041
RfCA-0388-066 066
RFCA-0177-018 018
RFCA-0981-054 054
Method
NO, Manual Methods
Sodium arsenite (orifice)
Sodium anenite/Technicon II
TCS-ANSA (orifice)
Advanced Pollution loar. 200
Beckmtn952A
Bendtx 8101-B
Bendix8101-C
Dasibi 2108
CSI1600
LearSieflerML9841
Meloy NA530R
Monitor Labs 8440E
Monitor Lab. 8840
Monitor Labs 8841
Philips PW9762/02
Thermo Electron 14B/E
Thermo Electron 14D/E
Thermo Environmental Inst. 42
Pb Manual Methods
Ref. method (hi-voI/AA spect.)
Hi-vol/AA spect. (alt. extr.)
Hi-vol/Energy-dispXRF (TX ACB)
Hi-vol/Enerjy-disp XRF (KEA)
Ki-vol/Flameless AA (EMSL/EPA)
Hi-vol/Fltmelexs AA (Omaha)
Hi-vol/lCAP spect. (EMSUEPA)
Hi-vol/lCAP spect. (Kansas)
Hi-vol/ICAP spect. (Montana)
Hi-vol/]CAP spect. (NEiT)
Hi-vol/ICAP tpect. (N. Hampshr)
Hi-vol/lCAP spect. (Penniylva)
Hi-vol/lCAP spect. (Rhode Is.)
Hi-vol/lCAP sped. (S.V. Labs)
Hi-volAVL-disp. XRF (CA A&IHL)
PNl,. Samplers
Oregon DEQ Med. vol. sampler
Siem-Andenen/GMW 1200
Siem-Andersen/CMW 321-B
Siem-Andersen/CMW 321-C
Siem-Andenea/CMW241 Dichot
Wedding & Auoc. high volume
Andersen Instr. Beta FH62I-N
R&PTEOM 1400,1400*
Wedding & AMOC. Beta Gauge
TSP Manual Method
Reference method (high-volume)
Februa^ 8, 1993
Designation Method
Number Code
EQN-1277-026
EQN-1277.027
EQN-1277-028
EQL-03 80-043
EQW)783-058
EQLX)589-072
EQL-0380-044
EQ1X)785X)59
EQU)38CV045
EQL-0592-085
EQL-0483-057
EQL-1188069
EQL-1290-080
EQL-0592-086
EQL-0888-068
EQL-1288-070
EQLXJ581-052
RFPS-0389-071
RFPS-1287-063
RFPS-1287-064
RFPS-1287-065
RFPS-0789-073
RFPS-1087-062
084
084
098
RFNA-0691-082 082
RFNA-0179-034 034
RFNA-0479-038 038
RFNA-0777-022 022
RFNA-1192-089 089
RFNA-0977-025 025
RFNA-1292-090 090
RFNA-1078-031 031
RFNA-0677-021 021
RFNA-0280-042 042
RFNA-0991O83 083
RFNA-0879-040 040
RFNA-0179-035 035
R5NA-C279-037 037
RFNA-1289-074 074
803
043
058
072
044
059
045
085
057
069
080
086
068
070
052
071
063
064
065
073
062
EQPM-0990-076 076
EQPM-1090-079 079
EQPM-0391-081 081
802
-------
APPROVED METHODS AS OF NOVEMBER 12, 1993
CO
N02
°3
Pb
PM10
SO2
TSP
MANUAL
REFERENCE
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EQUIVALENT
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3. HV/ICAP (EPA)
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5. HV/ICAP (MT)
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7. HV/FhBBfcM AA
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1. Mtloy OA323-2R (J)
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3. CE (Bead) K02 (J)
4. McMUlu 1100-1 U)
3. McMUlu 1100-2 (J)
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7. Mcniier Ut> WIOE (J)
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PM-10 Manilon
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Piflkh Sicvkr
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i. Mcnhor Ubi M» (A IjO)
7. ASAJtco 300 (J), em pjo)
1. BictaBB 9S3 (J, 1J5)
9. Bala 1303 (J. IJO)
10. Mcky SA2S5E (J15,.l,J,lJ3)
11. Mooiior Ute 830 (.3, 1 J)
12. Mcky SA700 (ii, J, IJO)
13. Uw n^kr AM3320 (J.1JO)
14. TED 43A (.1, i J. 1 JO)
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16. MaBhar Uta «30S (J, US)
17. APD 100 (J)
It. Esnraenma SA. AR1M (J)
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-------
EPA-454/B-93/051
Appendix I
Revision No. 0
Date: March 1994
Page 1-1
APPENDIX I
SAMPLE SUBMTTTAL MATERIALS AND ADDITIONAL GUIDANCE
-------
ATTACHMENT A - SAMPLE SUBMTTTAL MATERIALS
Including the following:
AMP380 report
Site ID forms
Monitor ID form
Sample MSA monitoring network design map
Sample 2km radius map
Sample 1/4 mile radius map
Land use information
CH-93-58
A-l
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12
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Figure A-2. Sample 2 Km Radius Map
A-12
-------
Sketch a map to document the environment within a 1/4 mile radius of the site.
Include the following information on the drawing where applicable.
PAMS Location on Drawing
Roadways with Names (paved and unpaved)
Parking Areas (paved and unpaved)
Stationary Sources
Buildings (number of stories)
Undeveloped Land (ground cover)
Tree Lines or Clusters
Small Area Sources (dry cleaners, gas stations, etc.)
Residences
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Recreation Parks
Recreation Fields
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Bodies of Water
Norm Direction
3. Sample 1/4 Mile Radius Map
A-13
-------
LAND USE INFORMATION
As noted in Section 2 of this document, land use information is quite useful in
determining the appropriate locations for ambient monitoring stations.
._Land use information availability.varies across the country. Differing State and local
land use regulations generate similar differences in land use data. Federal data sources also vary
in the availability of detailed data on electronic media.
Land use is defined differently by the many public and private data vendors, as well as
data customers. Land use can simply describe the degree of urbanization of an area and the
nature of this man-made development, or it can describe the purpose served by the development
(e.g., residential, commercial, institutional, open space) as well as the transportation systems
serving these areas.
The primary land use data sources in the federal government are the United States
Geological Survey (USGS) and the Bureau of the Census. The USGS produces topographic
maps on paper, electronic tape/disk, and optical disk. These maps are relatively inexpensive and
dense with information, but land use information must be distilled from the maps' structure
types, development densities, and transportation networks rather than simply being read as
pre-marked zones. Topographic maps are available in a variety of scales and media for many
areas of the country. Aerial photographs are available at 1:24,000 scale. These photographs
offer literal images of the surface features photographed from aircraft. Trained readers can
classify types of development and vegetation from these monochrome prints. Pilot projects have
yielded orthophotoquad maps on optical disk for a few areas. The Bureau of the Census
provides demographic and socioeconomic data capable of supporting land use analysis.
State, regional, and local governments maintain varying amounts of land use data. Data
maintained often vary with the planning requirements mandated by State or local legislation.
An advantage of sub-state level data is the presence of projected land use maps. Comprehensive
development plans often include current land use and projected land use, the latter typically
being in the form of zoning maps which reflect policies steering development.
With the development of satellite technology and image processing computer systems,
remote sensing has become a viable source of land cover, topographic, and interpretive data such
CH-93-J8 A-14
-------
as land use. Remote sensing is the process of deriving information through systems not in direct
contact with the objects or phenomena of interest: image processing describes the manipulation
of this raw data yielded by remote sensing systems. The combination of these technologies can
yield a variety of spatial data.
'- There are two main providers of primary remote sensing data. The Earth Observation
Satellite Observation Company (EOS AT) is the operator of the Landsat remote sensing satellite
system and the distributors of the primary data (and some interpreted data) from this system.
The information from this system is read with a pixel size of 30m x 30m. The French company
Systeme Probatoire de la Observation de la Terre (SPOT) has a satellite in orbit and a
distribution office in the United States. SPOT data are available with a 20m x 20m pixel size
for color data and a 10m x 10m black and white pixel size. SPOT is also the only supplier of
global Digital Terrain Modeling information. Both companies offer data for a variety of sizes
of databases and a variety of media (digital/tape, paper, or film/transparency). The cost for
digital system corrected map sheet information is $0.49 per square km for EOSAT data and
$0.68 per square km for SPOT data.
The National Oceanic and Atmospheric Administration (NOAA) has used the Nimbus
series of satellites to gather Advanced Very High Resolution Radiometer (AVHRR) data since
1978. AVHRR data are only sensed at 1.1 kilometer resolution, but offer the advantage of
semidiurnal readings. The private vendor handling public access to AVHRR data notes that this
information is not archived and contains encoded meteorological data; no land cover/land use
information is available through AVHRR.
Remote sensing data can directly provide information on land use and land cover. Digital
processing can enhance the satellite data to interpret this physical evidence to describe physical
and cultural processes.
CH-93-J8 A-15
-------
ATTACHMENT B - SAMPLE WIND ROSES
(Prepared by OAQPS/MRB)
CH-93-58 B-l
-------
conducive days
observed highs
10 years
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PM
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PM
1-6 7-16 17-27 >« 28
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0% 10% 20%
Figure B-l. Sample Wind Roses
B-2
-------
ATTACHMENT C - GUIDANCE FOR SUBMITTAL OF EMISSIONS INFORMATION
• Introduction
• Point Source Emissions
• Area Source Emissions
• Mobile Source Emissions
CH-93-58 C-l
-------
ATTACHMENT C
PAMS MONITOR SITING - USE OF EMISSIONS RELATED DATA AND
r SURROGATES
1.0 INTRODUCTION
Presentation of a summary of the available SIP base year (1990) VOC and NO, emissions
by the predominant major source categories will provide an initial indication of the relative
magnitudes of the source categories for which geographic distribution may be relevant to the
selection of PAMS Site #1. Appropriate data for this highly aggregated level of summary should
exist in the documentation of current SIP inventory submittals for the nonattainment area of
concern and should be available directly from State personnel responsible for inventory
preparation.
The primary purpose of obtaining and presenting emissions data summaries is to provide
perspective on the relative distribution of the area's emissions across source types. This
information will make it possible to develop priorities as to the sources for which geographical
distributions are important in the process of locating PAMS Site #2. At a minimum, VOC and
NOX emissions totals should be presented for the following categories: (1) point sources, broken
down into combustion and non-combustion sources; (2) area sources, broken down into
population-related and industrial source types; and (3) mobile sources, with separate totals for
highway and non-road sources (see Table C-l).
For most purposes related to PAMS station siting, the ideal form of geographic emissions
information is a set of emissions density displays at a small grid scale, such as that which can
be produced by emissions preprocessors for urban scale photochemical models. Where these
types of presentations of emissions data are not available or where the resolution provided is not
adequate for specific monitor siting considerations, alternatives are discussed below.
CH-93-5S C-2
-------
TABLE C-l. EXAMPLE AREA-WIDE EMISSIONS SUMMARY
Ozone Season Weekday Emissions
(tons/day)
VOC NOX
POINT SOURCE
Combustion
Non-combustion
AREA SOURCE
Population-related
Industry-related
MOBILE SOURCE
Highway vehicles
Non-road
BIOGENICS
TOTALS
* Due to rounding percentages
tons/day
1
9
115
160
•
195
22
100
602
do not total
percentage
< 0.1
1.5
19.1
26.6
32.4
3.7
16.6
100*
100.
tons/day
78
1
16
14
231
8
348
percentage
22.4
< 0.1
4.6
4.0
66.4
2.3
100*
2.0 POINT SOURCE EMISSIONS
Site #2 monitoring sites should be selected in areas that will allow accurate assessment
of representative amounts of point source emissions (i.e., emissions from facilities that generate
10 tons per year (tpy) VOC emissions or greater, or from facilities that generate 100 tpy or
greater NOX emissions. Smaller sources should be included if such data are available. A map
identifying point emissions sources and monitoring sites is the best way to concisely present the
required data. Maps should be generated at two levels of resolution: (1) a macro level, showing
the entire SIP and monitoring area; and (2) a micro level, representing a neighborhood-level
view of the monitoring sites and nearby point sources. VOC emissions are generated from many
point source mechanisms (e.g., combustion, evaporation, waste disposal) and therefore are
CH-93-38
C-3
-------
generated at many emissions points. In comparison, NOX is primarily a combustion byproduct,
generated at a smaller number of emissions points. This fundamental difference in emission
generation, coupled with the tendency of NO, emission sources to mask VOC emissions, results
in the need for separate maps identifying VOC and NOZ point emission sources.
2.1 MACRO-LEVEL MAPPING
Two macro-level maps should be submitted supporting Site #2 monitoring sites. One
map will summarize the monitoring locations and VOC emissions levels, the other will relate
monitoring sites to NO, emission points.
2.1.1 VOC Map
Point source emissions should be presented on a map that indicates VOC emissions on
a zip code level (see Figure C-l). In areas where the geographic areas represented by zip codes
are too small to be clearly represented on a macro-level map, the sources could be identified by
latitude/longitude. VOC emissions in each zip code may be identified by cross-hatching, color,
or gray scale, and should be resolved into quartiles or higher resolution. VOC emissions for
each facility in the SIP area should be available from EPA's Aerometric Information Retrieval
System (AIRS) Facility Subsystem (AFS). Zip codes are typically included for AFS facilities1;
in absence of zip codes, an approximation may be made using the latitude/longitude or .Universal
Transverse Mercator (UTM) data typical in AFS. Wind roses should be presented on the same
page, in the same orientation, as the emissions map. Including wind roses will make evaluating
potential site locations easier and more consistent. Software and climatological data for
generating wind roses are available in the Support Center for Regulatory Air Models (SCRAM)
on EPA's Technology Transfer Network bulletin board service (TTN).
'AFS includes zip codes for both street and mailing addresses. Care should be taken to use street addresses.
This avoids inaccuracies caused when a facility submits the mailing address of a remotely located home office
or when a rural facility maintains an in-city post office box.
CH-93-58 C-4
-------
IS
<*%*
Ix*
8^g
s
c_>
O
u
U
o
6
c
U.
-------
2.1.2 NO, Map
As stated earlier in this section, NO, is a combustion byproduct and therefore is produced
in a number of sources. Because the NOX resulting from a source may react with, and therefore
maskpambient .VOC levels, NO, emissions points should'be located and identified individually
rather than aggregated to a zip code level so that the VOC measurements are not unduly
influenced by a single source. NO, emissions may be identified from AFS; facility location is
typically reported using latitude/longitude or UTM data. The relative emissions from each
source may be reported on the map by indicating the location of each facility with an indicator
(circle, dot or spike) sized in proportion to its NO, emissions. As in the case of the VOC maps,
wind roses should be presented along with the maps.
2.2 MICRO-LEVEL MAPS
Micro-level maps show, on a neighborhood level, the location of the monitoring sites.
Micro-level maps generally show a 4-5 km radius around the monitoring station (see Figure C-
2). One micro-level map should be submitted for each monitoring location to be implemented
within the next ozone monitoring season.
All point sources in the neighborhood of the monitoring site should be indicated on this
map. As suggested for the NO, macro map, the relative emissions from each source may be
reported on the map by indicating the location of each facility with an indicator (circle, dot or
spike) sized in proportion to its NO, emissions. Color or shape may be used to indicate
pollutant (VOC or NOJ. AFS may be consulted to determine emissions, pollutant and location
(using plant address, latitude/longitude, or UTM code).
Wind roses should be printed on the same sheet as the map, oriented consistently with
the map to facilitate evaluation.
CH-93-58 C-6
-------
55 *
S2 CC *
C/9
V
,0
"53
in
U
O
3
O
1/3
3
C-7
-------
3.0 AREA SOURCE EMISSIONS
Many types of emission sources are too small or too prevalent to be inventoried as point
sources. Area source classifications allow estimation of emissions from such sources by using
emission .factors based upon substituting data descriptive of activity throughout a neighborhood
or county for facility-specific data. While indicators of the distribution of area sources include
varied data such as population, housing, land cover, land use, and sales of relevant commodities
or products, surrogates for the area sources responsible for VOC emissions are most closely
paralleled with population distribution. Therefore, maps representing the population distribution
of a nonattainment region will indicate neighborhoods with the highest area source emission
potential. . - - -.- •- - ~v -•'-- ^
A work of caution is given, however, because the use of population as a surrogate
activity level indicator is true for activities such as dry cleaning, architectural surface coating,
small degreasing operations, and solvent evaporation from household and commercial products.
However, per capita factors should not be used for sources whose emissions do not correlate
well with population. In some instances, it might be better to use employment rather than
population as a surrogate activity level indicator. Such factors are usually appropriate to
estimate emissions for source categories which have an SIC code and for which employment data
at the local level are available. Because large fractions of VOC emissions are covered by point
source procedures, the emissions-per-employee factor is a secondary procedure to cover
emissions from sources that are below the point source cutoff level.
There are several public sources of population and demographic data. The U.S.
Department of Commerce, Bureau of the Census provides population data on paper, magnetic
tape/disk, and optical disk. The data may be resolved to a variety of levels down to the size of
the typical city block. Data at the census tract level, a region containing approximately 2,500
to 8,000 people, is sufficient for most area source estimates. Local and regional planning
departments also maintain population data. Though the source of this data may also be the
federal census, it may be aggregated into regions more relevant to the development and
urbanization patterns of the metropolitan area.
CH-93-58 C-8
-------
4.0 MOBILE SOURCE EMISSIONS
Mobile sources consist of on-road sources (often referred to as "highway vehicles") and
off-road sources, which include aircraft, railroads, vessels, and "non-road" sources such as farm
and construction equipment,.utility engines, lawnmowers, etc. 'While on-road mobile sources
are expected to be a dominant source category in all PAMS areas, the importance of off-road
sources may vary.
4.1 ON-ROAD MOBILE SOURCES
Potential sources of information on the geographic distribution of on-road mobile source
emissions include:
• Highly resolved grid-based on-road mobile source emissions data such as that which
would be prepared for photochemical oxidant model input (gridded emission densities)
(see Figure C-3)
• Emissions .estimates by road system links and traffic generation and destination areas,
resulting from the use of a calibrated travel demand model in combination with the EPA
MOBILE on-road mobile source emission factor model
• Link- and area-based transportation activity estimates (vehicle miles travelled, trip starts
and trip ends) from a calibrated travel demand model
• Traffic count maps indicating the level of traffic on the area's road system, (see Figure
C-4)
Traffic flow maps may be available from the local organization(s) charged with
performing traffic counts. Some of these maps use bandwidths to indicate the relative level of
traffic on individual roads, while others feature the transportation grid system with actual traffic
counts written in numerically at the counted locations. The level of detail of these maps will
vary with the intensity of the local counting program, but typically includes only the larger roads
in the area (such as major arterials and expressways).
CH-93-58 C-9
-------
4.2 OFF-ROAD MOBILE SOURCES
The level of effort and detail appropriate for development of geographic distributions for
off-road mobile sources is a function of the magnitude of these emissions in the area of concern,
whiclrwould be shown, by emissions summaries. The highly disparate nature of the individual
off-road source types complicates geographical allocation of this category. If the off-road
category represents a critical or significant portion of the overall emissions of a given pollutant,
and locations of these emissions have not already been characterized for air quality modeling,
investment of some effort in geographical allocation for PAMS purposes may be justified. The
basic steps would include (1) obtaining a detailed listing of emissions from individual off-road
source types, (2) assigning priorities based on their emission levels, (3) developing reasonable
surrogates or logical locational characteristics for each source type, and (4) graphically depicting
the distribution of emissions represented by these surrogates or characteristics.
CH-93-H C-10
-------
Max T?ilu«: 9379.1 (kg/day) at ( 22. 24)
value: 123.9 (leg/day), non—*ero c«lls only.
440
520
600
^5024
34944
4864
20
11 .'-i 4704
3 4824
r*i
:;;:-.:.:3:;i
• •••»>• *
::^.::\
iff'UMIfff tllilllJM
i-.^T-::-::-:::::
•S
•.:•.:§:•.:::::::::::••:.• •":.-:-::::-"3
_i|[iur>.mi}iit[(iiriLi'caiit)|iiitii|;cL-i]^|
20
40
60
^4544
4 km, 68 x 120, 6/26 Motor Vehicle emissions (Re-rised inventory)
RHC
Total: 654668 (Kg/day)
Figure C-3 Grid-based mobile emissions data map
C-ll
-------
• ••• PWOJtCT •OUNOAKT'
Figure C-4 Sample traffic density map for a downtown area
C-12
-------
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
ATMOSPHERIC RESEARCKAND EXPOSURE ASSESSMENT LABORATORY
RESEARCH TRIANGLE PARK
NORTH CAROLINA 277 11
September 15, 1993
MEMORANDUM
SUBJECT: Requirements and Guidance for PAMS Meteorological Station in New
Brunswick, New Jersey
FROM: Jerry H. Crescemi, Physical Scientist W*U
Human Exposure Modeling Branch (MD/36) /
TO: N. Ogden Gerald
Office of Air Quality and Planning Standards (MD-14)
This memo is in response to your request for information about the requirements and
incorporation of a 30 meter meteorological tower and upper air profilers into the Photochemical
Assessment Monitoring System (PAMS) which will be located at Rutgers University in New
Brunswick, New Jersey. There are two categories of data needed to fulfill PAMS meteorological
requirements - surface and upper air.
The variables which are required from a ground-based system include wind speed, wind
direction, air temperature, relative humidity, barometric pressure and incident solar radiation.
Most of the guidance summarized below is taken from the Quality Assurance Handbook for Air
Pollution Measurement Systems, Volume IV: Meteorological Measurements (1983, revised
1989, EPA-600/4-82-060) and the On-Site Meteorological Program Guidance for Regulatory
Modeling Applications (1987, EPA-450/4-87-013).
The primary objective of instrument siting (horizontal and vertical probe placement) and
exposure (spacing from obstructions) is to place the sensor in a location where it can make
precise measurements that are representative of the general state of the atmosphere in that region
under study. The choice of a site must be made with a complete understanding of the regional
geography, the sources being investigated, and the potential uses of the data being collected.
Ideally, the 30 meter tower should be located in an open level area. In terrain with significant
topographic features, different levels of the tower may be under the influence of different
meteorological regimes at the same time. If this is the case, such conditions should be well
documented.
The standard exposure of a wind sensor over level, open terrain is 10 meters above the
ground. Open terrain is defined as an area where the horizontal distance between the instrument
-------
and any obstruction is at least ten times the height of that obstruction. An obstruction may to-
man-made (e.g., building) or natural (e.g., trees). The wind sensor should be mounted on aaasi
at the top of the tower or on a boom projecting horizontally out from the tower. If the sensor
is mounted on a boom, then it should be located at a horizontal distance at a minimum of twice
the maximum diameter or diagonal of the tower away from the nearest point on the tower. • The
boom should project in the direction which provides the least distortion for the predominant wind
direction. For example, the boom should be aligned in a northwesterly or southeastetly^direction
if the predominant wind is from the southwest. ""'"'%v'
"t.-'
Air temperature and humidity sensors should be mounted over a plot of open level ground
at least 9 meters in diameter. The ground surface should be covered with non-irrigated or
unwatered short grass or, in areas which lack a vegetation cover, natural earth. The surface
must not be concrete, asphalt or oil-soaked. If there is a large paved area nearby, these sensors
should be at least 30 meters away from it. These sensors should be located at a distance from
any obstructions of at least four times their height. Areas of standing water should also be
avoided as well as steep slopes, ridges or hollows. The standard heights are 2 and 10 meters,
but additional levels may frequently be required in air quality studies. These sensors must be
housed in well ventilated solar radiation shields (forced aspiration is preferable) at a horizontal
distance from the nearest point on the tower of at least the diameter of the tower.
As for the barometric pressure sensor, there is no particular siting guidance available
since the data is seldom utilized in EPA studies. However, the barometric pressure is needed
when computing variables such as specific humidity, potential temperature and air density. I
would suggest that the sensor be place indoors with the data acquisition system. One end of a
rubber tube should be attached to the sensor's pressure port and the other ended vented to the
outside of the trailer or shelter so that pressurization due to the air conditioning or heating system
is avoided.
Solar radiation measurements should be taken in a location free from any obstruction
which can either cast shadows or reflect sunlight on to sensor. This means that there should be
no object above the horizontal plane of the sensing element that could possibly cast a shadow on
it (including the tower). In addition, the pyranometer should not be placed near light colored
walls or artificial sources of radiation. Usually, a tall platform or a roof make suitable locations
for sensor placement. However, since it is not desirable to have a large obstruction such as a
building in the vicinity of the tower, then the best strategy is to place the pyranometer directly
south of the tower and its guy wires. There is no height requirement for this sensor.
The variables required for upper air monitoring to support PAMS include profiles of
horizontal wind velocity, vertical wind velocity, and air temperature. Also needed is an estimate
of the mixing layer height and stability class of the atmospheric boundary layer. However,
temporal and spatial density of these variables have not been clearly defined. Rather, the amount
of data to be acquired is a function of the field study objectives and numerical model input
requirements.
-------
There are two types of wind profiling systems. The first type is a RADAR which
transmits a 915 MHz electromagnetic signal and has a range of approximately 90 to 3000 meters.
The second type is a SODAR which transmits a 2 to 5 KHz acoustic signal and has a range of
about 60 to 600 meters. Both systems transmit their respective signals in pulses. Each pulse is
both reflected and absorbed by the atmosphere as it moves upwards. The height range of each
pulse is determined by how high it can go before the signal becomes so weak that the energy
reflected back to the antenna can no longer be detected. That is, as long as the reflected pulses
can be discerned from background noise, meaningful wind velocities can be obtained. The
attenuation of the pulses are functions of signal type, signal power, and atmospheric conditions.
A Radio Acoustic Sounding System (RASS) utilizes a combination of electromagnetic and
acoustic pulses to derive an air temperature profile in the range of about 90 to 1200 meters.
For upper air monitoring, remote sensing is quickly becoming the method of choice.
However, while these profiling systems have been approved and used to develop meteorological
databases required as input for dispersion models, there is a distinct void in terms of guidance
needed to help potential users and the regulatory community. Because of their unique nature and
constant evolution, the available EPA guidance for SODARs is more generic than that which
already exists for many well established in-situ meteorological sensors. Almost no guidance is
currently available on RADAR and RASS systems.
Since SODARs utilize sound transmission and reception to determine the overlying wind
field, a clear return signal with a sharply defined atmospheric peak frequency is required. Thus,
consideration of background noise may put limitations on where a SODAR can be located.
External noise sources can be classified as active or passive, and as broad-band (random
frequency) or narrow-band (fixed frequency). General background noise is considered active and
is broad-band., If loud enough, it can cause the SODAR software to reject data because it can
not find a peak or because the signal-to-noise ratio is too low. The net effect is to lower the
effective sampling rate due to the loss of many transmission pulses. Radian (assuming that this
company is providing the profiling systems) should be consulted as to what noise level would be
acceptable for the SODAR. A qualitative survey should be conducted to identify any potential
noise sources. A quantitative noise survey may be necessary to determine if noise levels are
within the instrument's minimum requirements.
Examples of active, broad-band noise sources include highways, industrial facilities,
power plants, and heavy machinery. Some of these noise sources have a pronounced diurnal,
weekly or even seasonal pattern. A noise survey should at least cover diurnal and weekly
patterns. Examination of land-use patterns and other sources of information may be necessary
to determine if any seasonal activities may present problems.
Examples of active, fixed-frequency noise sources include rotating fans, a back-up beeper
on a piece of heavy equipment, birds and insects. If these noise sources have a frequency
component in the SODAR operating range, they may be misinterpreted as good data by the
SODAR. Some of these sources can be identified during the site selection process. One
approach to reducing the problem of fixed frequency noise sources is to use a coded pulse, i.e.,
-------
the transmit pulse has more than one peak frequency. A return pulse would not be identified as
data unless peak frequencies were found in the return signal the same distance apart as the
transmit frequencies. Radian can provide information on whether or not the SODAR is capable
of such a task.
Passive noise sources are objects either on or above the ground (e.g., tall towers, power
transmission lines, buildings, trees) that can reflect a transmitted pulse back to the SODAR
antenna. While most of the acoustic energy is focused in a narrow beam, side-lobes do exist and
are a particular concern when antenna enclosures have degraded substantially. Side-lobes
reflecting off stationary objects and returning at the same frequency as the transmit pulse may
be interpreted by the SODAR as a valid atmospheric return with a speed of zero. It is not
possible to predict precisely which objects may be a problem. Anything in the same general
direction hi which the antenna is pointing and is higher than 5 to 10 meters may be a potential
reflector. It is therefore important to construct an "obstacle vista diagram" prior to SODAR
installation that identifies the direction and height of potential reflectors hi relation to the
SODAR. This diagram can be used after some data have been collected to assess whether or not
reflections are of concern at some SODAR height ranges. Note that reflections from an object
at distance X from an antenna will show up at height Xcos(oc), where a is the tilt angle of the
antenna from the vertical.
The RADAR, SODAR and RASS antennas should be aligned and tilted carefully as small
errors in orientation or tilt angle can produce unwanted biases hi the data. True North should
also be established for antenna alignment. Installation of the antennas should not be permanent
since problems are very likely to arise hi siting the profilers hi relation to the tower and other
objects that may be in the area. One final consideration is the effect of the instrument on its
surroundings. The sound pulse from a SODAR and RASS is quite audible and could become a
nuisance to residents who might happen to live near the installation site.
A joint effort is currently underway between EPA's Atmospheric Research and Exposure
Assessment Laboratory in Research Triangle Park, North Carolina and NOAA's Wave
Propagation Laboratory in Boulder, Colorado to further develop QA and QC guidance for wind
and temperature profiling systems. Once established, this information will provide standard and
consistent operating procedures which will lead to the acquisition of high quality, interpretable,
and scientifically defensible data sets.
cc: Alan H. Huber
William F. Hunt
Robert G. Kellam
Dale A. Pahl
Larry J. Purdue
Brian D. Templeman
-------
EPA-454/B-93/051
Appendix J
Revision No. 0
Date: March 1994
Page J-l
APPENDIX J
AIR QUALITY INDICATORS
-------
United States
Environmental Protection
Agency
Office of Air Quality
Planning and Standards
Research Triangle Park, NC 27711
EPA-450/4-81-015
February 1981
Air
EPA
U.S. ENVIRONMENTAL PROTECTION
AGENCY INTRA-AGENCY TASK
FORCE REPORT ON AIR
QUALITY INDICATORS
-------
EPA-450/4-81-015
February 1981
U.S. Environmental Protection Agency
Intra-Agency Task Force Report
on Air Quality Indicators
by
W.F. Hunt Jr. (chairman). G. Akland. W. Cox. T. Curran,
N. Frank, S. Goranson, P. ROM. H. Sauls, and J. Suggs
U.S. Environmental Protection Agency
Office of Air, Noise, and Radiation
Office of Research and Development
Office of Planning and Management
Region 5
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air, Noise, and Radiation
Office of Air Quality Planning and Standards
Research Triangle Park. NC 27711
February 1981
-------
This report is issued by the Environmental Protection Agency to report technical data of
interest to a limited number of readers. Copies are available - in limited quantities - from
the Library Services Office (MD-35), U.S. Environmental Protection Agency, Research
Triangle Park. North Carolina 27711; or, for a fee, from the National Technical Infor-
mation Service, 5285 Port Royal Road, Springfield, Virginia 22161:*
Publication No. EPA-450/4-81-Q15
-------
CONTENTS
Figures
Tables
1. Overview 1-1
1.1 Recommendations ' " 1-1
1.2 Future work 1-4 -
2. Known Measures of Data Uncertainty (Precision and
Accuracy) 2-1
2.1 Need for qualifying air pollution data 2-1
2.2 Schedule for implementing the precision and
accuracy program 2-3
2.3 Uses of precision and accuracy data 2-3
2.4 References 2-4
3. Detecting and Removing Outliers 3-1
3.1 Causes of outliers 3-1
3.2 Statistical procedures for identifying outliers 3-2
3.3 Recommended treatment of outliers 3-6
3.4 Conclusions 3-7
3.5 References 3-7
4. Area of Coverage and Representativeness 4-1
4.1 Background 4-1
4.2 Network description 4-3
4.3 Representativeness 4-4
4.4 References ' 4-6
5. Data Completeness and Historical Continuity 5-1 -
5.1 Data completeness 5-1
5.2 Historical completeness 5-9
5.3 References 5-15
6. Statistical Indicators and Trend Techniques 6-1
6.1 Statistical indicators 6-1
6.2 Trend techniques - 6-7
6.3 References 6-12
111
-------
CONTENTS (continued)
7. Inferences and Conclusions
7.1 Background
7.2 Case studies
7.3 Long-term solutions
7.4 References
8. Data Presentation 8-1
8.1 Concepts to be displayed .. 8-1
8.2 Chart types and uses 8-2
8.3 Classification of data " 8-29
8.4 Input parameters, data transformations, and
statistical comparisons 8-30
8.5 Audience applicability 8-30
8.6 Caveats and suggestions 8-32
8.7 Available plotting resources 8-33
8.8 Guidance"for selection of charts 8-33
8.9 Summary and recommendations 8-34
8.10 Future issues 8-34
8..11 References 8-35
9. Continuity of Year-To-Yeer Reports 9-1
9.1 Method changes 9-1
9'.2 NAMS network changes 9-1
1v
-------
FIGURES
Number ' Page
1 Empirical Histograms of All Possible Annual
Averages Based on One or Two Months of Data
Per Quarter Compared With Theoretical Fre-
quency Distributions Defined by Statistical
Model for 1973 S02 at the New York City
Laboratory Site "' 5-8
2 Theoretical Probability Distribution of Annual
Mean SO2 With 10 Sites in Each Year 1974-1976
and 15 Sites in 1977 and 1978 5-13
3 Comparison of SO2 Trends at Bayonne, N.J.,
With Regulations Governing % Sulfur Content
in Fuel 7-3
4 Weekly Average CO and Wind Speed in Richmond,
VA From January 4 to February 28, 1974 7-5
5 CO Air Quality From 18 Monitoring Sites and
Motor-Vehicle Gasoline Consumption for N.J.
From 1972 Through 1976 7-7
6 Quarterly TSP Maximum Values in Region VI
From 1972 to 1977 Illustrating the Effect
of the 1977 Dustorm 7-9
7 Satellite Views of February 23-25, 1977, Dust-
storm at Succeeding Time Periods 7-10
8 Status and Trends in Air Quality in Colorado 8-4
9 Intersite Correlation Test Data 8-5
10 Magna, Utah, Day 3, 0.50 Probability Ellipses
of the West-East and South-North Wind Com-
ponents for Three Cluster Types. Winds From
the West and South are Positive 8-6
11 Twenty-Four Hour TSP Values, 1972 8-7
12 Air Quality Data, 24-h TSP Concentration
Values, October 15, 1976 8-9
-------
FIGURES (continued)
Number . .- > - Page
-->- 13 Maximum 1-h 03 Values/Day, L977 (SAROAD
Site 141220002P10) 8-10
14 Oxidant Trends Adjusted for Meteorology 8-11
15 Annual Average and Second-High Day TSP
Values, 1970-75 - 8-12
16 Population Exposure Distributions of Annual
Mean TSP for 1970 and 1976 in City of
Chicago " 8-13
17 Ambient CO Concentration and Gasoline
Consumption, 1972-77 8-14
18 Comparison of Monthly GM, 12-mo Running GM,
and Predicted Monthly Means (By Double
Moving Average Method), 1964-74 8-15
19 Trends in CC Levels in New York's 45th Street
Station, April-January, 1975-77 8-16
20 Trends in PSI Levels, 16 Cities, 1973-76 8-17
21 Actual vs. Potential Emissions for Illinois,
Tons/Year 8-19
22 Number of Days Per Year That the TSP Primary
Standard or Alert Level was Exceeded,
Colorado . 8-20
23 Regional Changes in Metropolitan Population
Exposures to Excess TSP Levels, 1972-1977
(Width of Each Regional Column is Propor-
tional to its Metropolitan Population) 8-21
24 Trends of Annual Mean TSP Concentrations
From 1970 to 1976 at 2350 Sampling Sites 8-22
25 Wind Rose Pattern 8-23
26 Source Category Contributions to Particulate
Air Pollutants 8-24
27 Air Quality Status (TSP) and Trends in 25
Largest Urban Areas in EPA Region 5 8-25
vi
-------
FIGURES (continued)
Number • -• - ' - Page
~2§"Isopleths of TSP Concentrations (yg/m3) in
EPA Region V and Iowa for October 15, 1976 8-26
29 Air Quality Status, Colorado, 1972 8-27
30 Three Dimensional Plot of NO, Concentrations,
yg/ro3, November 1973 8-28
-------
TABLES
Number Page
1 Special Checks and Audits for Estimation
of Precision and Accuracy 2-2
2 Concentration Ranges for Automated Analyzer
Audits 2-2
3 Outlier Tests 3-9
4 NADB Validity Criteria 5-2
5 Continuous Measurement Summary Criteria 5-3
6 Data Completeness for Continuous SO,
Monitoring, 1973 5-4
7 Accuracy of Particulate Sampling Frequencies
and Averaging Intervals 5-6
8 Deviation of Observed Annual Mean and Maximum
From True Values Among 42 TSP Sites,
1976-78 5-6
9 Annual Means 5-14
10 Weekly Average CO Concentrations (ppm) and
Windspeeds (mph) in Richmond, VA, January
4-February 28, 1974 7-4
11 Multiple Parameter Listing, 1979, ug/m3 8-3
12 Weekly TSP Maximums at City Sites, 1979,
ug/m3 8-3
13 Region 5 Monthly Averages by Site Type, 1979,
ug/m3 8-3
14 Outline of Input Parameters, Data Transforma-
tions, and Statistical Comparisons 8-31
-------
1. OVERVIEW
The Intra-Agency Task Force on Air Quality Indicators was established to
reconmend standardized air quality indicators and statistical methodologies, for
presenting air quality status and trends in national publications. As a first
step, the members of the task force identified topics of concern and prepared a
series of issue papers on these topics; these papers discuss the background and
current status of each issue, develop recommendations, and identify areas that
need additional work. These individual papers make up the remaining sections
of this document.
To put the activities of the task force in perspective, it should be no-
ted that on May 10, 1979, EPA promulgated regulations for ambient air quality
monitoring and data reporting. These regulations were a result of the ground-
work of the Standing Air Monitoring Work Group (SAMWG), and reflect EPA's con-
cerns about data quality, timeliness, and consistency from one area to another.
Specific provisions in these regulations instituted the routine reporting of
precision and accuracy information to aid in characterizing data quality, the
designation of specific sites in state- and- local agency monitoring networks to
be used in national trends analyses, and the increased standardization of sit-
ing criteria to ensure greater uniformity. All ambient air quality data re-
ceived by EPA should reflect these changes by 1981; the data bases currently
used in EPA's analyses are in transition. In a sense, the monitoring communi-
ty has identified and begun to implement improvements in the air quality data
bases, and now those responsible for analyzing the data must ensure that the
best use is made of these improvements.
1.1 RECOMMENDATIONS
In developing recommendations, two common concerns were apparent. The
first involved data bases that do not yet exist (e.g., precision and accuracy
information). Since it is premature to recommend how these data should be
used in reporting air quality, the Task Force has simply identified the group
1-1
-------
that should take the initiative in developing methods for using the informa-
tion-. The second concern involved the relative merits of standardization.
The data from a given air quality study can be analyzed by a wide variety of
statistical "techniques. In many cases,'different approaches are equally ac-
ceptable. In fact, in certain cases, there are statistical techniques that
are recommended but seldom .applied. The important point here is that an em-
phasis on standardization should not discourage the development and applica-
tion of new techniques. Consequently, these recommendations should be view-
ed as a set of general principles rather than a set of inflexible rules. If
a particular approach satisfies the intent of these recommendations, it is
satisfactory; 1f it does not, an explanation should be included in the analy-
sis to say why alternative techniques were used.
The recommendations are grouped in four categories: data base, data
analysis, data interpretation, and data presentation. In each category, both
general and specific points are presented.
1.1.1 Data Base
In general, each analysis should indicate what data were used. For small
studies, specific sites can be named; for large studies, it will suffice to in-
dicate the data source (e.g., the National Air Data Branch, NADB) and the se-
lection criteria used to choose sites. Specific recommendations are listed-be-
low.
1. Precision and Accuracy (Section 2) - EPA does not require the sub-
mission of precision and accuracy information until 1981; therefore
no guidance on its use will be given at this time. It is recommend-
ed that ORD/EMSL take the lead in developing procedures for using
this information.
2. Data Scree'ning (Section 3) - Statistical procedures for detecting
outliers are available, and some have been incorporated into SAROAD.
Under the new monitoring regulations and management plan for the
National Air Monitoring Stations (NAMS), users will eventually be
able to assume that NAMS data quality has been verified. In the in-
terim, however, the user should apply appropriate screening proce-
dures to the data for any small-scale analysis; for large-scale
analyses, the user may rely on robust statistical techniques that
will minimize the potential impact of anomalous data.
3. Site Selection (Sections 4 & 5) - The NAMS will provide a usable,
quality assured, standardized data base for trends—particularly
national trends. Composite values of NAMS data will provide a -
1-2
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useful Index for national trends assessment. In the interim, the
user must select sites on the basis of specific criteria which en-
sure, adequate completeness and seasonal balance. The criteria
should be stated clearly in the analysis.
1.1.2 Data Analysis
The analysis should be structured so that results are stated in terms of
statistical significance. Analyses that have no statistical basis should in-
dicate that they do not and why they do not. Those analyses with a statisti-
cal basis should Indicate the statistical approach used. More specific recom-
mendations concerning data analysis follow.
1. Choice of Summary Statistics (Section 6) - Summary statistics should
reflect the appropriate air quality standard and not be biased due -
to sample size. If an analysis requires the use of a statistic that
is biased with sample size, care must be taken to ensure that compar-
isons over time or across sites are not affected by differences in
sample sizes.
2. Comparability of the Data Base (Sections 5 & 6) - Any trends analy-
sis should be structured so that results are not attributable to the
data base varying with time. Interpolated data may be used for the
visual presentation of trends, but trend statistics should be based
on actual data unless the effect of interpolation can be quantified.
3. Trend Techniques (Section 6) - Standard statistical techniques such
as Chi-square, nonparametric regression, aligned-rank tests, analy-
sis of variance, and time series are all acceptable means of assign-
ing probability statements to- trends analyses. The primary concern
is that the tests used are statistical In nature, not which tests
are used. However, EPA groups need to take a more active role in
applying various techniques to air data to assess the relative mer-
its of different procedures.
1.1.3 Data Interpretation
An analystxan facilitate the interpretation of air quality monitoring
data from the existing NAMS network by using other sources of information that
help explain why an air quality trend has or has not taken place or why there -
are significant differences between sets of air quality data. To better assess
the effectiveness of EPA's emission control program, the agency should collect
data on all variables that impact air quality in at least two major urban areas,
1.1.4 Data Presentations
Data presentations should be consistent with the analysis, and should be
adequately labeled so that they can stand alone.
1-3
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1. Choice of Scales - Distortion of scales should be avoided. In gen-
eral , the pollutant concentration axis should start at zero concen-
tration.
2. Distinguish No-Data Cases - Presentations involving shading (e.g.,
maps) should clearly indicate cases with no data as a distinct cate-
gory.
1.2 FUTURE WORK
In view of the transition occurring in the air quality data bases, it is
recommended that this task force be continued during 1981, when NAMS data and
precision and accuracy data will be received initially by EPA. During this
time, the following tasks should be performed:
1. Assessment of Statistical Manpower - To ensure that the task force
recommendations can actually be implemented and are not merely idealized
goals, it will be necessary to appraise the available and planned techni-
cal resources. A breakdown of resources needed should be provided, with
particular attention to the in-house resources needed to provide continu-
ity and technical guidance.
Lead Group: 0PM
Target Date: March 81
2. Use of Precision and Accuracy Information - The eventual use of •
precision and accuracy information needs to be better defined. Although
these data are not currently being received by EPA, similar preliminary
information is available to EMSL. These data should be examined, and a
plan should be developed on how this type of information can be incorpo-
rated into EPA's use of air quality data. Consideration should be given
to the feasibility of eventually establishing national performance stand-
ards for precision and accuracy data.
Lead Group: ORD/EMSL
Target Date: July 81
3. Use of Site Information in Trends Analyses - An important feature of
the NAMS data base is the detailed information available describing indi-
vidual sites. To routinely make efficient use of this information, it
will be necessary to identify the relevant site parameters and to develop
computer software to link the site information with the air quality in-
formation. Attention should be given to stratifying the data into broad
classifications needed for more refined data analysis.
Lead Group: OAQPS/MDAD
Target Date: September 81
1-4
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4. Assessment of Statistical Software - Several statistical software
packages are available that could be used for air quality data analysis.
To ensure-that EPA statistical manpower is "efficiently utilized an as-'
^sessment should be made of what statistical software is applicable. In
" particular, this assessment should determine: (1) what statistical pack-
ages are being used and to what extent and (2) if the best statistical
packages are being employed and if not, why not.
Lead Group: ORD/EMSL/RTP
Target Date: September 81
5. Presentation of Data - Because the Task Force is recommending specif-
ic types of data presentations a pilot study should be initiated to ensure
that these recommendations are feasible to implement on a routine basis.
Attention should be given to identifying computer programs that would
facilitate these presentations and if gaps exist"to develop the necessary
programs to the extent possible with existing resources.
Lead Group: Region V
Target Date: September 81
1-5
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2. KNOWN MEASURES OF DATA UNCERTAINTY (Precision and Accuracy)
Concepts of precision and accuracy have been the subject matter for many
presentations and publications. ASTM Committee E-ll on quality control of ma-
terials discussed definitions and implications of these two ideas over a 10-
year period. Complete agreement on the meanings of precision and accuracy is
unlikely to be found in the literature on scientific measurement systems. In
assessments of the quality of ambient air data, EPA uses estimates of preci- ..
•
sion to characterize the relative capability of the monitoring system to re-
peat its results when measuring the same thing and estimates of accuracy to
2
characterize the closeness of an observation to the "truth."
Beginning January 1, 1981, EPA will require all state and local report-
ing agencies to calculate precision and accuracy estimates in a prescribed man-
ner and to qualify all data entered into the EPA data bank with quarterly pre-
cision and accuracy estimates. Some, but not all, of the components necessary
for estimating precision and accuracy (Appendix A, 40-CFR-58) are available.
Currently, collocated samplers and single concentration precision checks provide
data which can be used to. estimate the precision of manual and automated sam-
plers, while audits of flew rates and laboratory analytical measurements provide
data which can be used for estimating accuracy. Perhaps improved methods for
estimating these parameters will be developed as a result of the increased at-
tention to assessing air quality data.
Table 1 presents the types and frequencies of special checks for precision
and accuracy by pollutant measurement method; Table 2 displays the concentration
range for each audit level.
2.1 NEED FOR QUALIFYING AIR POLLUTION DATA
Over many years, the air pollution data bank has grown into a gigantic
body of computerized records of concentrations of pollutants measured at sites
across the Nation at points in time. Necessarily, great amounts of attention
and expense have been devoted to devising systems to process the data into a
2-1
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TABLE 1. SPECIAL CHECKS AND AUDITS FOR ESTIMATION OF
PRECISION AND ACCURACY
Precision
Accuracy (local audit)*
Automated analyzers
(S02, CO, N02, 03)
Type check
Frequency
Scope
One concentration
Biweekly
All monitoring instruments
Manual methods
Type check
S02
N02
TSP
Frequency
Scope
Collocated samplers at two
sites
Each monitoring day
Two sites (of high concen-
tration)
Three or four concentrations
251 of the analyzers each quar-
ter; at least one per quarter
All analyzers each year
Type of audit
Flow
NA
HA
One level
25£ of the sites
each quarter; at
least once per
quarter
All sites each
year
Analytical
Three levels
Three levels
NA
Each analysis-
day; at least
twice per
quarter
NA
*See Table 2 for audit levels.
TABLE 2. CONCENTRATION RANGES FOR AUTOMATED ANALYZER AUDITS
Concentration range, ppm
Audit level
1
2
3
4
S02, N02, 03
0.03-0.08
0.15-0.20
0.40-0.45
0.80-0.90
CO
3-8
15-20
40-45
80-90
2-2
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computerized retrievable form. 'Also, high priority has been given to the de-
velopment and refinement of a system for collecting data-from state and local
agencies and sending the data through EPA Regional Offices to the NAOB com-
puter system. Inevitably, air pollution control administrators and affected
industries are concerned about the quality of the data that result from this
great expenditure of resources, especially pollutant measurements that may
represent exceedances of National Ambient Air Quality Standards (NAAQS) or
that have other serious implications. ,
As a result of continued programs of quality assurance and technological
improvements in monitoring and analysis, today's ambient air data are doubt-
lessly more representative of true concentrations than those of some years ago.
However, these improvements in data quality cannot be quantified because no
routine, standardized data assessment program has been in effect. Implementa-
tion of the program described above should provide the means to evaluate prog-
ress in measuring and recording ambient air data and should give managers a
higher level of confidence in making decisions based on air pollutant measure-
ments.
2.2 SCHEDULE FOR IMPLEMENTING THE PRECISION AND ACCURACY PROGRAM
All designated HAMS sites are to begin operation January 1, 1981 (Appen-
dixes A and E, 40-CFR-58). On July 1, 1981, the first quarterly report is due
into EMSL; the first quarterly sunroary- report from EMSL to the EPA Regional
Offices is due September 1, 1981; and the first annual report is scheduled for
July 1, 1982. The remaining State and Local Air Monitoring Stations (SLAMS)
are to be phased into the Precision and Accuracy Reporting System as soon as
possible after January 1, 1981. The distinction of SLAMS and NAMS is of lit-
tle relevance here, since precision and accuracy data relate only to agencies.
2.3 USES OF PRECISION AND ACCURACY DATA
Confidence in conclusions concerning air quality trends will be more
scientifically defensible with the precision and accuracy data because of the
increased capability to test for statistical significance in trends analyses.
Also, additional interpretive insights may be gained; for example, if accuracy
does not change significantly, the quality assurance program may be ruled out
as a factor affecting trends.
2-3
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For many trends study purposes, the analyst must set an arbitrary limit
(e.g-., ±15*).on sites to be included in an analysis. The analyst must make
judgments in light of the purpose and the user requirements." In all cases,
the ana1ysT~should test to determine any effect of precision and accuracy in-
formation on conclusions.
It is premature at this time to attempt to develop definitive criteria
for using precision and accuracy data in determining trends, nonattainment
status, and so forth. Inclusion of precision and accuracy data in analyses
may appear to add to the overall levels of uncertainty, but experience over
time is needed to establish criteria for setting limits on the data to be
used in a particular situation. " ''"-' ;"
Precision and accuracy data will permit comparisons of data quality
within and between monitoring networks and within and between States and re-
gions. Also, precision and accuracy data together with data from EPA's Am-
bient Air Performance Audit Program should provide the means for effective
evaluations of analytical laboratories hired by State and local agencies.
A great deal of interest centers on the possible uses of precision and
accuracy data to report probability intervals about peak and mean estimates
of air quality data. If the peak value is not an outlier, there is no prob-
lem with the probability interval. Long-term (3 years) studies may be re-
quired to verify the assumptions that the sample of precision and accuracy
information is representative and that extreme values are within the popula-
tion. There should be no problem in reporting probability intervals for
mean values. In any case, the assessed quality of air pollution measurements
should be included in all relevant reports and publications.
2.4 REFERENCES
1. Precision Measurement and Calibration, Statistical Concepts and Proce-
dures. National Bureau of Standards Special Publication 300. Volume 1.
February 1969.
2. Rhodes, R. C. Precision and Accuracy Data for State and Local Air Moni-
toring Networks: Meaning and Usefulness. Paper presented at the 73rd
APCA Annual Meeting, Montreal, Canada, Oune 1980.
3. Appendix A. Quality Assurance Requirements for State and Local Air Moni-
toring Stations (SLAMS). FR Vol. 44, No. 92, pp. 24574-27581, May 10,
1979.
2-4
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3. DETECTING AND REMOVING OUTLIERS
An outlier is an observation that does not conform to the pattern estab-
lished by other observations. This pattern may be a scatter plot, frequency
histogram, time series, or simple listing. The parent population from which
the observations are drawn is usually assumed to behave according to a certain
probabilistic model, and the observations are usually assumed to be drawn at
random or at least independently. The agreement between the observations and
the parent population depends both on the correctness of the underlying assump-
tions and on certain aspects governing the selection process. Outliers should
not be isolated from other problems of statistical analysis; they should be in-
cluded among anomalies such as nonadditivity, nonconstant variance, bias, tem-
poral drift, or wrong model specification. A correction in another problem
can often solve the outlier problem.
3.1 CAUSES OF OUTLIERS
Three basic ways an outlier can occur are (1) mistakes in readings, (2)
wrong model specification, and (3) rare deviation.
- Mistakes in readings can occur during any stage of data processing, but
the more common mistakes (e.g., transcription errors) usually occur early in
the processing; during data coding or key punching, transcription errors often
go unnoticed. Unusual readings from instruments m&y be caused by power fail-
ure or surges, improper calibration, breakdowns, torn filters, contamination,
chemical interaction, leaks, and so forth. Not adhering to an experimental
plan or design can affect recorded data. Mistakes occur both in totally auto-
mated data gathering processes and in those that rely on human consideration
or intervention.
With the exception of glaring mistakes that have obvious explanations,
model specification usually is the basis for deciding if a discordant observa-
tion is an outlier. In fact, most tests currently being used routinely by EPA
2
to detect outliers are actually testing some type of nonnormality. For ex-
ample, the null hypothesis of all the tests listed in Table 3, with the
3-1
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exception of the gap test, is that the population from which the observations
are being drawn is specified by a normal distribution model. References 3 and
4 describe additional tests which specify normal, lognormal, or Weibull models.
Detection of an outlier by any one of these tests is paramount to declaring
the parent population has a different distribution than was originally assumed.
Of course, the final conclusion would be that the observation is an outlier.
In any parent population, some observable events have a low probability
of occurring. These events are usually associated with the extremes (tails)
of the distribution. Although the probability of obtaining one of these ob-
servations is small, it is possible for such an event to occur. Being a rare
occurrence, the observation is almost always treated as an outlier.
3.2 STATISTICAL PROCEDURES FOR IDENTIFYING OUTLIERS
Statistical procedures for identifying outliers are used for different
reasons. One reason is to justify what would have been done anyway (i.e., to
reject observations that an experienced investigator would intuitively reject).
Another reason for using statistical tests is to provide algorithms to the
2 5
computer ' for scanning large sets of data that would be impractical to scan
by visual inspection. At present, 5122 SLAMS, 1269 NANS, and 68 Inhalable
Particulate Network (IPN) sites are producing data which require validation.
In addition, special studies such as the Philadelphia IP Study, the National
Forest Ozone study, and the. Across Freeway Study (LACS) are collecting large
quantities of continuous and 24-hour data. Whether the data are collected
routinely or for special studies, a procedure for detecting outliers is neces-
sary to strengthen the validity of conclusions reached during data analysis.
Table 3 lists several statistical tests for objectively screening a set
of data and identifying possible outliers. These tests are currently being
applied to routine data storage systems within EPA. These tests, except for
the studentized range, the studentized t-test, and the Shewhart control chart
require no external or independent parameter estimates; conclusions are based
2
solely on the data at hand. Except for the Gap Test, these tests for out-
liers are tests for normality. All tests are aimed at high values relative
to some measure of spread based on the sample. Where routine screening of
data is necessary, a battery of several tests is advisable.
The Oixon ratio test was the first of many standard statistical procedures
which have been found to work well in air data screening. Some work better
3-2
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than others, depending on sampling frequencies and durations. For example,
the Shewhart control chart was found superior to. the Dixon ratio in screening
24-hetHp-measurements. These and other screening procedures constitute the
Air Data Screening System (ADSS), which is now being implemented in 27 States
through the Air Quality Data Handling System.
In another screening program, several statistical procedures are current-
ly being applied to SAROAD data. With the exception of the gap test, these
tests have one thing in common—they all assume that the observations are sam-
ples from a single normal population with specific location and shape parame-
ters. Tables and charts are used to identify values that have a low probabili-
ty of occurring if all observations were taken from the same population; these
values are flagged for further investigation.
To demonstrate how outliers can be identified, several tests, in Table 3
are applied to the following set of mass data in the 0-15 micron size range
gathered over a 5-month period in Birmingham, Alabama, using a dlchotomous sam-
pler.
24 -hour samples
Date
08/01/79
08/07/79
08/25/79"
08/31/79
09/06/79
09/12/79
09/30/79
10/06/79
10/12/79
10/18/79
10/24/79
10/30/79
11/05/79
11/23/79
12/05/79
12/11/79
yg/m3
43.8
66.7
17.8
45.3
92.6
34.8
38.4
47.5
64.7
36.2
30.6
16.9
36.6
15.3
101.8
35.0
Monthly values
Average (x)
43.4
55.3
39.2
26.0
68.4
Range (R)
48.9
57.8
47.8
21.3
66.8
3-3
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Dixon Ratio2*3
Calculated:
—~~~
Tabulated: rQ gQ (I.e., o * 0.10) * 0'.454 for n = 16.
Thus: 1*22 < rQi9o;
Shewhart Control Chart2*3
Range: LCLR « D3R « (0)(43.95) « 0. --.
UCLR - D4R - (2.57)(53.95) = 112.95. ' - -
In this example, the largest integer less than the average was used (n = 3).
Average: LCLo » J - A^R * 40.95 - (1.02) (43. 95) < 0 (use LCL? * 0 in this
AW A
case).
UCLX « + A2R * 40.95 + (1.02)(43.95) » 85.78.
Thus the monthly average (68.4) and range (66.8) for December are not consid-
ered outliers.
Chauvenet's Criterion^
X - 45.25
S = 25.00
r - X" ' * « 101.8-45.25 . ? ?fi
c -- T~ 2T5C - 2'26'
The critical value of C for sample size n = 16 is 2.154 with an a-level of
0.016 for a one-tailed test, thus 101.8 is an outlier. Chauvenet's criterion
is not reconmended for samples of n < 7 for a two-tailed test and for samples
of n < 4 for a one- tailed test because it tends to flag too many valid obser-
vations.
Grubbs Test7'8
Calculated: SS = 9372.26, SSlg = 5961.16, and SS15>16 • 3161.25.
ssifi ssm ifi
Thus: Lj_ - -S. = Q.64 and L - *1P - 0.34
Tabulated: LI « 0.576 and L2 « 0.405 for n = 16.
3-4
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Therefore, at the a * 0.05 significance level, only the highest value (101.8)
can be rejected-as-an outlier.
Coefficient of Skewness10
n -
n I (X. - Xr
Calculated: B « —~ = 1.0
_z (x.-X)2 3/2
Normally, this test for skewness is not used for n small (say < 25); however,
the value of B exceeds the tabulated value 0.71 for n » 25 (the tabulated val-
ue for n = 16 will be < 0.71) and therefore, normality is rejected at the a =_
0.05 significance level.
After excising 101.8 and 92.6, normality can no longer be rejected; both
values are outliers based on this test.
Studentized T-Test9
The standard deviation (S) required for testing Studentized deviates was
estimated from the August, September, and October data to be 21.52. November
and December data are grouped together because there are only two observations
in each month. The suspected outlier is 101.8 ug/m .
T ». X" ' X 101.8 - 47.18 , CA
1 S 2TT52*'**' •
The critical value (o = 0.05) for examining one outlier among four samples,
relative to the prior S based on 11 degrees of freedom, is tQ Q5(4»H) = 2.24.
Thus 101.8 ug/m is an outlier.
q
Studentized Range
The S required for the Studentized range test was estimated from the same
set of data as the Studentized t-test. November and December data are grouped
together as before, and the suspected outlier is again 101.8 ug/m .
Calculated: W = Xn - X, = 101.8 - 15.3 = 86.5.
Tabulated: W = qQ Q5(4,11)S = 4.26(21.52) = 91.68
Thus: 101.8 is not an outlier.
Some tests are more suited to hourly than to 24-hour data. Table 3 summarizes
the recommended applications of the commonly used tests. For examples of how
other tests are applied, consult the references.
3-5
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References 3 and 4 describe nonparametric tests for comparing two or more
•
data- sets to aid in identifying a data set that does not conform to the pattern
established by the other data sets. Reference 4 also discusses the use of non-
parametric tests for a single sample. However, identifying an outlier by a non-
parametric test is inconsistent with our definition of an outlier; an outlier
is an atypical observation because it does not conform to a model which we hypo-
thesize to describe the data. If we have no mode.1 in mind, it is difficult to
describe what we mean by an outlier. Hence, nonparametric techniques are recom-
mended only for the comparison of data sets.
3.3 RECOMMENDED TREATMENT OF OUTLIERS "
No observation should be rejected solely on the basis of statistical tests,
since there is always a predictable risk (i.e., the a-level) of rejecting "per-
fectly good" data. Compromises and tradeoffs are sometimes necessary, especial-
ly in routinely scanning large amounts of data; in these situations, no statis-
tical rule can substitute for the knowledge and judgement of an experienced
analyst who is thoroughly familiar with the measurement process.
In any data-collecting activity, all data must be recorded along with any
notes that may aid in statistical analysis. Gross mistakes should be corrected
if possible before performing calculations in the final analysis; if a mistake
cannot be explained or corrected, it is not always- wise to discard the reading
as though it had never occurred. Further experimental work may be needed, since
a gross error in the observations can bias the analysis in all but the most ro-
bust statistical procedures. In addition, data collected under differing condi-
tions should not be combined for identifying outliers unless the experiment was
designed (e.g., factorial design) to handle such data with an appropriate model
during final analysts.
In performing the calculations in the final statistical analysis, the
question of what weight* 1f any, to assign a discordant value is difficult to
answer in general terms. An acceptable explanation for an outlier should pre-
clude any further use of the value. Sometimes it is obvious that an observa-
tion does not belong even though there is no explanation for its existence.
Although the value should not be used in further calculations, it should be
mentioned in the final report.
Q
Experienced investigators differ greatly on these matters. Excluding
"good" data may not be as serious as including "bad" data and then excluding
3-6
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any questionable observations in further calculations at the risk of losing
information on estimates and introducing some bias. Reducing sample variation
(ifl««asing precision) may be preferred over introducing a slight bias, es-
pecially if the bias is theoretically estimable. Using robust air quality
indicators that are not strongly influenced by outliers may avoid many argumen-
tive, subjective decisions.
3.4 CONCLUSIONS
The data analyst should not assume that all outliers represent erroneous
values. Some outliers occur because the analyst has used the wrong probabilis-
tic model to characterize the data. For example, outlier tests based on as-
sumptions of normality may be inappropriate for nonnormal data sets. In addi-
tion, there is always a finite chance that an extreme value will occur natural-
ly. The analyst should carefully investigate these possibilities before dis-
carding outliers. The use of robust air quality indicators is recommended
since they decrease the need for detecting outliers. Reference 4 discusses
several outlier tests, their performance, and provides a brief summary of com-
parative information for each test, including pertinent references.
3.5 REFERENCES
1. International Encyclopedia of Statistics. Vol. 2. The Free Press, New
York, 1978. pp. 1039-1043.
2. Guideline Series. Screening Procedures for Ambient Air Quality Data.
EPA-450/2-78-037, July 19?S.
3. Nelson, A. C., D. W. Armentrout, and T. R. Johnson. Validation of Air Mon-
itoring Data. EPA-450/2-78-037, August 1980.
4. Barnett, Vic and Toby Lewis. Outliers in Statistical Data. John Wiley
and Sons, Inc. New York, New York, 1978.
5. Northrop Services, Inc. A Data Validation Program for SAROAD. Cont. No.
68-02-2566. ESG-TN-78-09, December 1978.
6. Dixon, W. J. Processing Data for Outliers. Biometrics. 9(l):74-89,
March 1953.
7. Grubbs, F. E., and G. Beck. Extension of Samples, Sizes and Percentage
Points for Significance Tests of Outlying Observations. Technometrics
14(4):847-854, November 1972.
3-7
-------
8. Tietjen, 6. L., and R. H. Moore. Some Grubbs-Type Statistics for the Oe-
. tection. of Several Outliers. Technometrics 14(3):583-597, 1972.
9. Natrella, M. £.. Experimental Statistics. Chap. 17. National Bureau of
~~ Standards Handbook 91, 1963. ~
10. Duncan, A. 0. Quality Control and Industrial Statistics. Richard D.
Irwin, Inc., 1965.
11. Quality Assurance Handbook for Air Pollution Measurement Systems. Volume I,
EPA-60Q/9-76-005. U.S. Environmental Protection Agency, Environmental Moni-
toring and Systems Laboratory, Research Triangle Park, N.C., January 1976.
3-8
-------
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4. AREA OF COVERAGE AND REPRESENTATIVENESS
4.1 BACKGROUND
Over the decade of the 1970*s the number of ambient air pollutant moni-
tors Increased dramatically from approximately 1800 In 1970 to approximately
8000 In 1979. The lack of uniform criteria for station locations, probe
siting, sampling methodology, quality assurance practices, and data handling
procedures resulted in data of unknown quality. In preparing "national" air -
quality trends data bases for the major pollutants, the number of monitoring
sites changed constantly, reflecting the growth in State monitoring networks
during this period. A conglomeration of different types of sites—rural, in-
dustrial, residential, commercial, etc—evolved with no national plan. Some
urban areas of the country had extensive monitoring while others did not.
In October 1975, at the request of the Deputy Administrator of EPA, a
Standing Air Monitoring Work Group (SAMWG) was established. The Work Group
was to critically review and evaluate current air monitoring activities and
to develop air monitoring strategies which would be more cost effective,
would help to correct identified problems, would improve overall current op-
erations, and would adequately meet projected air monitoring goals. Members
of the Work Group represent State and local air pollution control agencies
and EPA program and regional offices.
SAMWG1s review indicated that the current ambient monitoring program is
basically effective in providing information for support of State Implementa-
tion Plan (SIP) activities. Several areas were identified where deficiencies
existed, however. The principal areas where corrections are needed are sum-_
marized below.
1. Lack of uniformity in station location and probe siting, sampling
methodology, quality assurance practices, and data handling proce-
dures have resulted in data of unknown quality.
2. Existing regulations coupled with resource constraints do not allow
State and local agencies sufficient flexibility to conduct special
purpose monitoring studies. -
4-1
-------
3. Resource constraints and the diversity of data needs frequently re-
sult in untimely or incomplete reporting of air quality data. Ade-
. quate air quality data for national problem assessments and routine *
—_ -trend analyses are in some cases not available to agency headquar-
ters until 12-18 months after each calendar quarter.
4. In some cases, data are being reported to the EPA central data bank
from more stations than are absolutely necessary for adequate assess-
ment of national control programs and analysis of pollutant trends.
The recommendations of SAMWG later became the basis for the Federal moni-
2
toring regulations promulgated on May 10, 1979. These regulations require EPA
to: ' ..
o set stringent requirements for a refined national monitoring network
in areas with high population and pollutant concentrations to provide
a sound data base for assessing national trends;
o give the States flexibility to use resources freed from SIP monitor-
ing work to meet their own needs;
o establish uniform criteria for siting, quality assurance, equivalent
analytical methodology, sampling intervals, and instrument selection
to assure consistent data reporting among the States;
o establish a standard national pollutant reporting index and require
its use for major metropolitan areas; and
o require the submission of precision and accuracy estimates with air
quality data to enable better interpretation of data quality.
These regulations should produce a streamlined, high-quality, more cost-effec-
tive national air monitoring program.
The States are required to establish a network of stations to monitor
pollutants for which National Ambient Air Quality Standards (NAAQS) have been
established. Each network is to be designed so that stations are located in
all areas where the State and the EPA Regional Office decide that monitoring
is necessary. The stations in the network are termed State and Local Air
Monitoring Stations (SLAMS),
Data summaries from the network are to be reported annually to EPA. Data
from a subset of SLAMS to be designated as National Air Monitoring Stations
(NAMS) are to be reported quarterly to EPA.
4-2
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4.2 NETWORK DESCRIPTION
4.2.1 The SLAMS-Network
Tfie SLAMS network should be designed to meet a minimum of four objectives:
1. To determine the highest concentrations expected in each area covered
by the network;
2. To determine representative concentrations in areas of high popula-
tion density;
3. To determine the Impact of ambient pollution levels from significant
sources or source categories; and
4. To determine background concentrations.
Each monitoring site 1s required to be identified by location and type of sur-
roundings as well as by monitoring objective and spatial scale of representa-
tiveness. The spatial scale of representativeness is described in terms of the
physical dimensions of the air parcel sampled by the monitoring station through-
out which actual pollutant concentrations are reasonably similar; the scale
adjectives are micro, middle, neighborhood, urban, regional, national, and glob-
al.
4.2.2 The NAMS Network
The NAMS stations are selected from the SLAMS network to emphasize urban
and multisource areas. The prfmary objective for NAMS is to monitor areas where
pollutant levels and population exposure are expected to be highest, consistent
with the averaging time of the NAAQS. Accordingly, NAMS fall into two catego-
ries:
1. Stations in area(s) of expected maximum concentrations; and
2. Stations with poor air quality and high population density but not
necessarily in area(s) of expected maximum concentrations.
For each urban area where NAMS are required, both categories of stations must
be established. If only one NAMS is needed to monitor suspended particulates
(TSP) and sulfur dioxide (S02), the first category must be used. The NAMS are
expected to provide superior data for national policy analyses, for trends, and
for reporting to the public on major metropolitan areas. Only continuous in-
struments will be used at NAMS to monitor gaseous pollutants.
4-3
-------
Siting requirements and definitions vary with pollutant, but MAMS are re-
quired only in urban'areas with populations of at least 50,000 where pollutant •
—eoncentr-a-tions are known to exceed the secondary NAAQS. The number of urban
areas monitored will vary with pollutant, as indicated below.
Pollutant
Total suspended parti culates (TSP)
Sulfur dioxide (S02)
Carbon monoxide (CO)
Ozone (03)
Nitrogen dioxide (N02)
Urban
areas
.212
160
77
85
33
NAMS
monitors
636
244
121
208
65
The NAMS network is being selected on the basis of experience with past
monitoring data and primarily attempts to measure the highest pollutant levels
associated with each urban area. The word "associated" indicates that, with
transport-effected pollutants such as 03 or TSP, the highest levels may occur
in areas of low population densities. The location selection should be periodi-
cally reviewed, based on historical monitoring data, meteorological conditions,
and changes in emission patterns. For example, there is definite evidence that
the highest 0, levels in the Los Angeles basin have been moving upwind in the
last few years, probably because of the changing composition of tailpipe pollu-
tants. Changing fuel usage and new construction may have also contributed to
this shift.
4.3 REPRESENTATIVENESS
The question has often been asked as to what constitutes a "national"
trend? In previous National Air Quality. Monitoring and Emission Trends Re-
ports. '* all sites with data available in the National Aeromatic Data Bank
(NADB), that could meet an historical data completeness criteria, were select-
ed for the national trend. In the case of total suspended particulate (TSP)
as many as 3000 sites could meet an historical completeness criteria. These
sites come from a variety of networks representing urban areas, rural areas,
and large point sources. Geographical coverage was largely weighted by popu-
lation; that is, the more populated areas generally had more monitoring sites.
In analyzing the national trend each site was weighted equally.
In contrast to TSP, the automotive related pollutants—carbon monoxide
(CO) and ozone (03)—had less than 250 trend sites meeting historical complete-
ness criteria as late as 1977.
Although California had a disproportionate
4-4
-------
number of these trend sites, each site was weighted equally In developing the
national trend.- -
—-In-each of the three cases, the.sites used for analyzing the national
trend represented a mixture of siting'criteria. Consequently, it was difficult
to determine what the resulting trend really represented.
The major difficulty in selecting sites that define a "national" trend is
determining what mix of sites represents national air quality. How should geo-
graphic distribution be determined—by population or by land mass? What types
of sites—center city, suburban, residential, commercial, Industrial, rural,
remote, etc.—should be 1n the national trend and what proportions are appro-
priate?
4.3.1 The NAMS Solution
A partial solution to this dilemma lies in the NAMS network. Part of
the problem with a "national" trend is a semantic one—how is it defined? The
NAMS can resolve this problem because they can be defined. For each of the cri-
teria pollutants, NAMS are located in either the areas of expected maximum con-
centration or the areas of high population density. Consequently, the NAMS lend
themselves to stratification into these two site populations. Additional siting
information is available through the NAMS management information system, which
will allow for the use of covariate data (such as traffic counts in the case of
CO) for the first time.
The NAMS are particularly appropriate for characterizing national trends
for urban sites located in areas of expected maximum concentration or high popu-
lation density. For example, the CO NAMS located in areas of expected maximum
concentration make up a clearly defined population and could serve as a good in-
dicator of the success (or failure) of the automotive emission control program.
4.3.2 The SLAMS and Detailed Urban Area Analyses
While the NAMS can be used to define national urban trends in areas of
expected maximums or high population density, the SLAMS can be used for detail-
ed urban area analyses. If one is trying to determine changes in air quality
in an urban area, then an examination of both spatial and temporal change is in
order. The SLAMS networks lend themselves to these types of analyses. EPA has
published several guidelines useful in determining spatial and temporal trends;
they should be consulted before initiating these types of analyses. '
4-5
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4.4 REFERENCES
1. Monitoring and'Air Quality Trends Report, 1974. U.S. Environmental Pro-'
tection Agency, Office of Air Quality Planning and Standards. Research
Triangle Park, N.C. Publication No. EPA-450/1-76-001. February 1976.
2. Federal Register. Vol. 44, February 8, 1979, pp. 8202-8237.
3. National Air Quality and Emission Trends Report, 1975. U.S. Environmental
Protection Agency, Office of Air Quality Planning and Standards. Research
Triangle Park, N.C. Publication No. EPA-450/1-76-002. November 1976.
4. National Air Quality and Emissions Trends Report, 1976. U.S. Environmen-
tal Protection Agency, Office of Air Quality Planning and Standards, Re-
search Triangle Park, N.C. Publication No. EPA-450/1-77-002.
5. National Air Quality, Monitoring and Emissions Trends Report, 1977. U.S.
Environmental Protection Agency, Office of Air Quality Planning and Stand-
ards, Research Triangle Park, N.C. Publication No. EPA-450/2-78-052.
December 1978.
6. Guideline on Procedures for Constructing Air Pollution Isopleth Profiles
and Population Exposure Analysis. U.S. Environmental Protection Agency,
Office of Air Quality Planning and Standards, Research Triangle Park,
N.C. Publication No. EPA-450/2-77-024a. October 1977.
7. Users Manual for Preparation of Air Pollution Isopleth Profiles and Popu-
lation Exposure Analysis. U.S. Environmental Protection Agency, Office
of Air Quality Planning and Standards, Research Triangle Park, N.C.
Publication No. EPA-450/2-77-024b. October 1977.
4-6
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5. DATA COMPLETENESS AND HISTORICAL CONTINUITY
Data completeness for sunmary statistics and historical continuity for
trend data are two concerns of the data analyst. In both cases» the quantity
of data available affects the uncertainty of the analytical results. In cur-
rent practice, criteria are invoked in the data screening steps to select min-
imally acceptable data sets. This section explores the effect of missing data
on the uncertainty of analytical results, and discusses criteria for ensuring"
adequate data completeness and historical continuity.
5.1 DATA COMPLETENESS
5.1.1 Background and Purpose
The number of air quality values produced by ambient monitors is usually
fewer than the maximum number possible. Missing values result from the inter-
mittent sampling schedules for manual methods, instrument failure, downtime for
calibration, or human error. The temporal balance and the sample size of the
resultant data set can seriously affect the validity of the sample and the un-
certainty of its summary st3tfs~trcs".
Published criteria have been used by EPA to establish the validity of data
sets for summarizing and analyzing air quality data. Such criteria should mini-
mize the uncertainty associated with air quality summary statistics. Unfortu-
nately, for each pollutant the same completeness criteria are used for all sum-
mary statistics-, despite the fact that the uncertainty associated with a summa-
ry statistic varies with the type of statistic and its variance properties.
In a sense, validity criteria provide a capability for identifying data _
produced by poorly operating instruments and for screening data samples that
may otherwise yield misleading or incorrect estimates of air quality levels.
Data requirements defined by the criteria should involve the type of summary
statistic (e.g., annual mean or maximum daily average) as well as its intended
application (e.g., trends analysis or status assessment with respect to the
standard). In general, fewer data are needed to determine an annual average
5-1
-------
than a short-term statistic, and fewer data per year are needed to estimate a
long-term trend than a -yearly status.
— Currently, the NADB uses different validity criteria for different time
periods and sampling approaches, as shown in Table 4. The criteria for each
sampling approach are intended to consider both the characteristics in the data
collection and the primary objective of the monitoring; however, for specific
applications there are inconsistencies in the criteria for different approaches.
This section discusses only the criteria for summary statistics for periods of
3 to 12 months.
TABLE 4. NADB VALIDITY CRITERIA1
Continuous Sampling (l-\\, 2-h, and 4-h data)
Quarterly statistics - 75% or 1642 hours
Annual statistics - 752 or 6570 hours
Intermittent Sampling (24-h data)
Quarterly statistics
Five samples per quarter
If 1 month has no values, at least two
values in other months
Annual statistics - four valid quarters
5.1.2 Origin of NADB Criteria
Criteria for intermittent sampling were formulated on the basis of a bi-
weekly sampling schedule which was used by the National Air Surveillance Net-
work (NASN) up to 1972. Nehls and Akland recommended that more stringent cri-
2
teria be applied when the sampling schedule is every 3rd or 6th day.
For continuous sampling, the origin of the 75 percent criteria is not
clear. Early Federal Air Quality Publications used a 50 percent criterion to
report summary statistics. Nehls and Akland suggested 75 percent completeness
and a more structured basis for summary statistics, as shown in Table 5; these
criteria require as few as 3402 hourly observations, or 39 percent of the pos-
sible hours.
5-2
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TABLE 5. CONTINUOUS MEASUREMENT SUMMARY CRITERIA2
Time interval
3-h running average
8-h running average
24-h
Monthly
Quarterly
Yearly
Minimum requirement
3 consecutive hourly values
6 hourly values
18 hourly values
21 daily averages
3 consecutive monthly averages
9 monthly averages with at least
2 monthly averages per quarter
5.1.3 Characteristics of Air Quality Sampling
Intermittent 24-hour sampling generally follows a fixed systematic or
pseudo-random schedule which is intended to provide representative coverage of
a time period with only a fraction of the total possible observations. By de-
sign, data from intermittent sampling can provide good estimates of an annual
mean, but may severely underestimate the peak values. Trying to improve the
estimate of the peak observation by intensifying the sampling during periods
of high pollution levels is known as episode monitoring. When these unsched-
uled episode data are combined with the scheduled data, bias can be intro-
duced into summary statistics.
Early intermittent sampling for TSP and other pollutants by the NASN was
biweekly on a modified random schedule which yielded 20 samples a year. Later
the schedule was modified to ensure equal representation for each day of the
week. After 1972, samples were collected every 12th day yielding a maximum of
30 to 31 samples a year. EPA's current recommended sampling schedule for TSP
is once every 6 days. Most agencies seem to follow this schedule. Among 2882
sites with 1978 data that meet the NADB validity criteria, over 60 percent pro-
duced 40 to 60 samples, and less than 10 percent sample more often than 1 in 3
days.
Continuous hourly monitoring, by providing a more complete representation
of air quality, should provide much better estimates of the true annual mean
and short-term peak values. In reality, continuous monitoring is often incom-
plete, and can yield biased estimates of long-term behavior. Missing data of-
ten occur in blocks of consecutive days or weeks. Sometimes a pollutant such
as 03 is monitored during only part of the year; only seasonal statistics are
appropriate in these cases.
5-3
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TABLE 6.
DATA COMPLETENESS FOR CONTINUOUS S02 MONITORING, 1973
Minimum quarterly
completeness (•)
25
26-32
33-49
50-66
67-74
75-100
Total
Number of sites
Annual completeness
<75£
41
11
40
14
2
108
>755
4
18
10
84
116
Total
41
11
44
32
12
84 "
224
As an example of actual monitoring performance, data completeness for
1973 SO- data is presented in Table 6. Of 224 sites, only 116 reported 75
percent of the total hourly observations. According to the percentage of com-
pleteness for 1973, 56 of the 108 sites not meeting the 75 percent annual com-
pleteness criterion had at least one-third of the total observations in eacn
calendar quarter.
5.1.4 Characteristics of Air Quality Data
Air quality data are known to exhibit temporal components generally in
the form of diurnal, weekly, or seasonal cycles. The variances for each com-
ponent may be different, thus an arbitrarily selected sample of the entire
series may not yield unbiased, minimum variance statistical estimates if the
sample does not represent each portion of each time component equally.
For example if-a diurnal pattern always shows the highest concentrations
between 0800-1200 hours, but the sampling does not include any observations
during these hours, simple sample statistics will have a negative bias. A sam-
ple requires temporal balance to be representative.
With a seasonal pattern of nonuniformly distributed data, the more extreme
the seasonal variation, the larger the potential bias. In addition, the larger
the sampling imbalance across the seasons, the larger the potential bias. If a
seasonal pattern shows one quarter with concentrations twice those of the other
three quarters, the range of possible bias in a mean is 88 percent to 136 per-
cent if one-tenth of the total observations are in a single quarter.
5-4
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Temporal balance is essential only if simple unweighted statistics are
used. Unbiased estimates can be obtained from unbalanced samples by using ap-
proprtate sample stratification and.by applying weighting factors. This method
is particularly effective in determining unbiased estimates for a given sample
size when the variance components are different within sampling strata.
The problems of unbalanced samples were considered in the establishment
of the original validity criteria for TSP and other 24-hour data. The recom-
mendations of Nehls and Akland for continuous data also considered these prob-
lems. Unfortunately, the current criteria for intermittent sampling do not
ensure balance when sampling more frequently than once in 2 weeks; more strin-
gent criteria or weighting factors need to be considered. In addition, the
current NADB criteria for continuous sampling may not ensure balance while re-
quiring more observations than necessary. Fewer observations could provide
2
better estimates if the sampling recommendations were adopted.
5.1.5 Estimates of Air Quality
The variation in a statistical estimate of air quality depends on the
temporal variation of the data, the size of the data sample, the temporal dis-
tribution of the sample within the year, and how the data are combined in de-
veloping the estimate.
Data completeness has varying impacts on different sample statistics. In
general, the more data available,- the, better the estimate. For a given level
of uncertainty, however, fewer observations will be needed to estimate a mean
than, say, a maximum value. For data with cyclical components, temporally bal-
anced samples with less data will yield better estimates than unbalanced samples
with more data. With the use of weighted averages, more data will usually yield
better estimates-, even if they are not balanced.
Intermittent Data - Nehls and Akland investigated the accuracy of annual
means estimated from systematic samples. Table 7 shows how accuracy degrades-
with decreasing sampling frequency based on particulate data collected almost
continuously in Philadelphia over 9 years. As expected, the percent error in-
creases with decreasing sampling frequency. For a given sampling frequency,
the error for a quarterly mean is approximately twice that for the annual mean.
5-5
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TABLE 7. ACCURACY OF PARTICULATE SAMPLING FREQUENCIES AND
AVERAGING INTERVALS
Sampling
frequency
(k) days
2
3
4
5
6
7
8
9
Percent error compared to daily sampling
Yearly
1.4
1.7
2.3
2.7
3.2
8.7
3.8
5.0
Quarterly
2.3
3.2
4.6
6.0
6.5
10.7
8.1
8.9
Monthly
3.9
6.5
8.7
10.3
12.0
- 15.1
14.9 '
16.0
Empirical evidence of the effect of sample frequency on summary statistics
is presented in Table 8, based on TSP data from 14 sites monitoring continuous-
ly for 3 years, 1976-78. Estimates of annual averages and annual maxlmums when
sampling every other day, every 3rd day, every 6th day, and every 12th day are
compared with the averages and maximums obtained from daily sampling. Errors
of the estimates for the annual maximum are typically 4 to 6 times larger than
the errors in the mean. Even sampling every other day, the sample maximum un-
derestimates the annual maximum by 9 percent.
TABLE 8.
DEVIATION OF OBSERVED ANNUAL MEAN AND MAXIMUM FROM TRUE VALUES
AMONG 42 TSP SITES, 1976-78
Sampling
frequency
1 in 12
1 in 6
1 in 3
1 in 2
Average percentage error, (*)
Mean
7.1
4.1
2.1
1.9
Maximum
30.1
22.0
13.6
8.9
Continuous Data - The variability of an annual mean derived from continu-
ous data can be examined by assuming that the data consist of 1 or 2 months of
complete data in each calendar quarter. This assumption corresponds to the ex-
treme situations in which the quarterly completeness is 33 percent or 67.per-
cent.
S-6
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Variance of the annual mean Var(x) based on complete months of data is
expressed as - - •
Var(x) -fc (1-f) -fi(I-I), (1)
where f is the fraction of months sampled in each quarter (f * n/3 and l-f is
the finite population correction), n is the number of months in a quarter, and
o
c is the variance among true monthly means within a quarter. For simplicity,
the number of days in a month and the number of months sampled per quarter are
assumed to be equal. To generalize this approach* this model could be con-
structed to consider subsamples of any number of discrete blocks of consecutive
days within each calendar quarter.
The variance of an annual mean based on monthly data defined by Equation"!
depends on the variability among monthly means within a quarter and on the num-
ber of months sampled in a quarter. Thus, for 1 month of data per quarter, the
standard deviation (SO) of the mean is 0.41 times the SD of monthly means. For
2 months of data per quarter, the SD of the mean is 0.2 times the SD of monthly
means.
The model based on monthly data was evaluated by comparing the empirical
distribution of annual means (based on 1 or 2 months of actual data) with the
theoretical distribution defined by Equation 1. Complete S0~ measurements ob-
served at the NYC laboratory site during 1973 were used to generate all 81
possible subsamples and corresponding armua-1 means. Using the average quarter-
2
ly estimate of variance among months equal to (21.4) , the estimates of vari-
ance for the sample means using 1 month or 2 months of data per quarter are
2 2
(8.8) and (4.4) respectively. Normal distributions corresponding to these
variance estimates were compared to the histogram based on all 81 possible
annual averagesr there was good agreement, as indicated in Figure 1. This ex-
ample demonstrates that data with one-third of the observations in each calen-
dar quarter can produce reasonable sample estimates.
The analysis above assumes that the variance is the same in each sampling
strata (quarter). If variances are different, the sampling period with the
highest variability should have the best sampling representation.
5.1.6 Summary and Recommendations
Data completeness criteria for producing summary statistics are desirable
to ensure representative estimates of air quality. Ideally, different criteria
5-7
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>-
u
UJ
Or
UJ
ts.
u_
0.1
0.05
TWO MONTHS PER QUARTER
60
70
80
90
100
110 120
UJ
C£
ONE MONTH PER QUARTER
70 80 90 100
S02 CONCENTRATION (ug/m3)
Figure 1. Empirical histograms of all possible annual averages based on
one or two months of data per quarter compared with theoretical
frequency distributions defined by statistical model for 1973
S02 at the New York City laboratory site.
5-8
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should be used to screen data for different uses; however from a practical
point of view, .a..single criterion specifying minimum data completeness for one
statistic (e.g., a mean) will probably be used for all applications. The cur-
rent NADB criteria for summarizing data need to be revised. The recommenda- •
tions of Nehls and Akland appear reasonable for intermittent data; the existing
criteria are reasonable as long as weighted statistics are used to correct for
the potential sampling Imbalance. Methods for specifying the required strata
and numbers of observations should be resolved in future work.
5.2 HISTORICAL COMPLETENESS
5.2.1 Background and Purpose
Important to trend analysis is data base preparation. If one is analyz- ~
ing the trend at only one monitoring site, all data from that monitor can be
considered. When analyzing a group of monitors, a specific time frame repre-
sented by the group should be used, and the historical data completeness of
each candidate monitoring site should be examined to determine suitability for
trends analysis within the time frame.
Since air quality trend analysis focuses on year-to-year variation (as
opposed to within-year variation), emphasis is usually on comparison of annual
statistical indicators derived from complete or "valid" data sets. Thus, the
number and temporal distributions of the annual statistical indicators are im-
portant; this characteristfc is termed "historical completeness."
The data series should be as complete as possible, but missing values are
permissible. Air quality monitoring does not always produce complete data
records. Instrument failure and data processing problems are two of the many
reasons for missing data. In many cases, emphasis is on compliance assessment
rather than long-term monitoring. Historical completeness criteria are used
during the data screening process to identify the largest possible data base
from which a representative sample can be drawn for trend analysis.
5.2.2 Characteristics of Missing Data in Trend Analysis
The number of missing values permitted depends on the objective of the
trend analysis, the trend technique, and the-variance components of the data.
In this context, variance components include error due to incomplete sampling,
instrument error, meteorological fluctuations, and departures of the observed
5-9
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trend from an assumed underlying pattern. The sensitivity of a trend tech-
nique improves with-more data; thus the anaTyst desires the maximum amount of .
..data at_thfi_JLargest number of sites. The sensitivity also depends on the vari-
ability of the trend. If, for example, a monotonic trend were to exist at a
group of sites, a minimum of two observations selected at random from each site
would be sufficient to categorize the trend. Similarly, if the analysis objec-
tive were to detect a long-term shift without the need to categorize the year-
to-year pattern, a few widely spaced data points would be adequate. If, how-
ever, the temporal patterns were more complex or were masked by high data vari-
ability, more data would be needed to separate the trend from other variance
" r- ** *
components, and more complete temporal records would be needed to obtain an ac-
curate year-by-year trend.
5.2.3 Historical Completeness Criteria
At a minimum, each site in the trend analysis must have two data points
representing the time series. To ensure that these data points are widely
spaced, the time period may be divided into two segments. For example, if the
6-year period 1972-77 were divided into 1972-74 and 1975-77, a site could be
selected if it produced one valid year of data in the first and in the second
time segments; this procedure ensures that data from the start and end of the
time period are represented.
A data selection approach often used by EPA is based on the historical
completeness of quarterly data. A criterion commonly used in the analysis of
national trends is four consecutive calendar quarters with valid data in each
of 2 time segments. Because the last one or two quarters of data can be miss-
ing from the most recent years due to late reporting, this approach can yield
more current estimates than the approach based on complete annual data. In
addition, using quarterly data to derive annual summary statistics minimizes
the bias caused by within-year sampling imbalance (Section 5.1).
Using historical completeness criteria can increase the number of candi-
date monitors many fold, and thus help obtain a more geographically representa-
tive sample. Of the 4000 TSP monitors reporting data to the NADB between 1972
and 1977, 2661 met the aforementioned criteria based on valid annual data, and
2737 met the criteria based on valid quarterly data. The trend period was di-
vided into two time segments—1972-74 and 1975-77. Using three 2-year time
5-10
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segments and valid annual estimates, 1737 would qualify, but only 417 had valid
annual data in each year between 1972 and 1977..
If_a representative sample.of stations with valid data for all years is
available, additional sites with missing data may not be needed or may only be
needed to improve the detectability of trends or to confirm the existence of
trends by using a larger population.
5.2.4 Historical Completeness in Data Presentation
Historical completeness of data is particularly important for graphical
presentations of trend results. Trend lines based on a group of monitoring
stations are commonly used in air quality analysis. Such an aggregate trend
line must be based on the same number of sites for each data point (e.g., year)
to minimize bias caused by a changing data base; this requirement is satisfied
by using every-year stations or by estimating all missing values. Estimating
missing values is not necessary for trend assessment, but it is for data pres-
entation.
In general, EPA characterizes the air quality trend in a defined geograph-
ic region using data for n years from m monitors. These data can be arranged
in the matrix:
Monitor 1
Monitor 2
Monitor m
Year 1 Year 2 ...
V Y
11. 12 * ' *
X« ^ 92 * * *
X
xml *m2 * * *
Year n
xln
X2n
xmn
where value x.. occurs at monitor i in year j. The presentation of trends re-
quires an average regional value of x for each year. If the matrix is complete,
a reasonable estimate of the average value for year j is the arithmetic mean
of each column,
«. •< m
^ - i £ V
However, this estimate may be biased if the matrix has missing values.
Two methods have proved useful in estimating yearly means when the data
matrix is incomplete. In the one method, missing values are estimated by
linear interpolation before the column means are calculated. This method
5-11
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produces reasonable estimates when the underlying trend is linear. The other
method assumes each.cel.l in the matrix can be characterized by a general linear
model:
where
u is a constant—the grand mean of all the responses which would be
obtained if there were no errors;
M^ 1s a term peculiar to the ith monitor, and is independent of year;
Y. is a term peculiar to the jth year, and is independent of monitor;
J and •. •'•
e^ denotes the experimental error associated with xij, and it is as-
J sumed to be a normal random variable with standard deviation oe.
Computer programs can be used to generate least squares estimates of these
parameters regardless of the number of missing values in the data matrix.
Each yearly mean is estimated as
*K ^ A
u. « u + Y.. (4)
Statistical methods are available for determining confidence intervals for the
yearly means and for the differences between yearly means.
One advantage of the generalized linear model is that it explicitly re-
lates the number of missing yearly values to the uncertainty of the estimates
of the yearly means. Working backwards through the model, the analyst can
specify a desired confidence interval, calculate the number of permissible
missing values, and adjust the data base accordingly.
5.2.5 Effect of Historical Completeness on Trends Analysis^
The impact of missing data on trends analysis is empirically examined by
sampling from a group of 30 S02 sites with 75 percent complete data each year -
of 1974-78. Theoretical 90 percent and 50 percent probability intervals based
on sampling one-third of the annual means in each of the first 3 years and one-
half in each of the last 2 years are shown in Figure 2. This method of sampling
is analogous to selecting sites independently for each year, and the intervals
show the distribution of means in each year.
The smallest variability is in the last 2 years because of the larger num-
ber of observations used to calculate those means. The distribution of means
5-12
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42
40
38
36
34
32
30
28
26
24
22
20
18
16
14
12.
10
8
6
4
2
•
•
4
M
m
m
«
•
*m
I
4
m
!•
•
m "
n P
fr
* L
• <
•
•
T T
114,
* I
. i I
•
; 95th % ile
; 1 75th % ile
; » MEAN (50th S ile)
m
I " U25th X ile
I 5th X ile
^
-
, , i ^L^ 1
1974 1975 1976 1977 1978
YEAR
Figure 2. Theoretical probability distribution of annual mean
SO, with 10 sites in each year 1974-1976 and 15 sites
in 1977 and 1978.
5-13
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is sufficiently variable for a subsample of means to show an incorrect upward
•
trend. The extremes-occur when a site effect exists and when different sites.
-are used_a±. the start and end of the time period. The highest and. lowest an-
nual means from the aforementioned subsamples are shown in Table 9.
TABLE 9. ANNUAL MEANS
1974 1975 1976 1977 1978
Lowest
Highest
14.5 21.4 11.3 12.9 14.5
56.9 56.8 58.7 35.5 37.3
The situation is less ominous if an additional constraint—that the same sites -
be used in the first 3 years and in the last 2 years—is imposed as a require-
ment for historical continuity.
Sampling from a finite population dictates that the distribution of means
for each year of the first 3 years will be independent of the distribution of
means for 1 of the last 2 years. If there is a site effect, other combinations
will be dependent. The most extreme results will occur if the distribution of
means in the first and last years are independent; for example, there is a 25
percent chance that the subsample-derived mean of the first year will be less
than the true value and that the subsample-derived mean for the last year will
be greater than the true value. The extreme value for the first year could be
14.5 and that for the last year could be 37.3, but values for the intermediate
years would counterbalance the extremes at the end years because of the site
effect. Example values for the three intermediate years are 33.7, 42.2, and
14.9, respectively. Thus, historical continuity minimizes the chances of an
incorrect result, b'ut this rare combination of missing values may still pre-
vent the detection of the true downward trend.
5.2.6 Conclusions and Recommendations
Historical completeness criteria are useful screening tools for selecting
sites for trend analysis. Historical data should be as complete as the environ-
mental data base will permit in order to establish a representative sample which
is large enough to detect trends. Trend analysis should keep track of the ex-
tent of the historical completeness, and should report separate findings accord-
ingly. Techniques such as linear interpolation and the generalized linear model
5-14
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should be applied to trend data with missing values to minimize bias due to site
effects for the purpose of displaying graphical-results.
5 .IRREVERENCES
1. Aeros Manual Series, Volume III. Summary and Retrieval. EPA-450/2-76-009a,
July 1977.
2. G. J. Nehls and 6. G. Akland. Procedure for Handling Aerometric Data. J.
of Air Pollution Control Association. 23:180 (1973).
3. Air Quality Data from the National Air Sampling Networks and Contributing
State and Local Networks, 1964-1965. United States Department of HEW, 1966.
5-15
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6. STATISTICAL INDICATORS AND TREND TECHNIQUES
This section attempts to answer two commonly asked questions:' What Is
the air quality? How is it changing? Throughout the section, it is assumed
that the principles and procedures of the previous sections have been follow-
ed; that is, the data sets have been screened for outliers and the sites have
been examined to ensure representativeness. Separate subsections are devoted
to each topic—statistical indicators and trend techniques, but a certain
amount of interplay is involved between the two. For example, when a partic-
ular statistical indicator is used to summarize the data, a natural followup
concern is how this indicator has changed over time.
6.1 STATISTICAL INDICATORS
The term "statistical indicator" is used in this section in a fairly gen-
eral sense to include any statistic which summarizes air quality data for a
particular time period. Technically, a statistic is a "summary value calculat-
ed from a sample of observations." For some air quality applications, we may
have not merely a sample but also the entire population; therefore, the comput-
ed value is not technically a statistic. For the purposes of this section,
statistical indicator is used in either case.
This subsection discusses the background and purpose of statistical indi-
cators for air quality, the types of indicators frequently used, what proper-
ties are desirable, and the relative merits of various indicators as well as
future needs.
6.1.1 Background and Purpose
A continuous air quality monitor can produce a pollutant measurement for
each hour of the day every day of the year. This means as many as 8760 con-
centration values for a single pollutant at a single site. The volume of data
is further increased by the number of pollutants measured at a site and by the
number of sites within an area. Such a quantity of data requires some type of
data reduction to conveniently summarize the data. A wide variety of-summary
6-1
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statistics could be used. The proper choice depends on the intended purpose
of the information.anoLon an awareness of the characteristics of the data.
WhUejnany specific purposes could be listed for air quality statistical
indicators, for most practical applications there are basically two: (1) in-
dicating status with respect to standards and (2) evaluating trends. An air
quality standard is an absolute frame of reference for an indicator. If an
air quality statistic is not compared to a standard, it is usually compared to
a value from some other time period under the general heading of trend analy-
sis. A third purpose Is using the statistic as a basis of comparison with data
from other sites or cities; however, most remarks that apply to choosing an in-.
dicator for trend analysis also apply to these comparisons.
An important point in any discussion of statistical indicators is that
many air quality standards are structured in terms of concentration limits not
to be exceeded more than once a year. This places a premium on information in
the upper tail of the distribution. Accordingly, the average and median val-
ues commonly used as summary statistics in many fields are often of little in-
terest in air quality data analyses. In fact, only the extreme values may be
of interest for comparisons with standards.
6.1.2 Types of Statistical Indicators
A wide variety'of statistical indicators are being used in air quality
data analyses. Some reflect standard statistical choices such as means or
percentiles. The highest or second highest value or the number of times the
level of the standard is exceeded is often used due to the importance of the
higher concentration values in air quality management. For example, the 1-hour
NAAQS for CO specifies a level of 9 ppm not to be exceeded more than once a
year. Thus, the second highest hourly value or the number of hourly values
greater than 9 ppm would equivalently indicate whether or not the site meets
the standard.
Other statistical indicators represent a compromise between focusing on
the peak concentrations and introducing more stability into the indicator.
These indicators may use either upper percentiles or knowledge of typical pol-
lutant patterns to construct a useful index for trends. Examples include the
average of daily maximum 03 measurements for the 0- season or the number of
times a level (other than the standard) is exceeded.
6-2
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Although the previously discussed indicators are typically used to sum-
marize data for.one pollutant at one site, they-can be adapted to accommodate
data-far one pollutant at several sites within an area. A further generaliza-
tion is to incorporate data for several pollutants into a single index. To do
this requires some method of normalizing the individual pollutant measurements
so that there is some basis for scaling their relative contributions to the in-
2 ^
dex value. The Pollutant Standards Index (PSI) is a method for doing this.
An ideal indicator would incorporate both air quality data and population
data to provide a measure of population exposure to various air pollution lev-
els. Efforts have been made in developing such measures, but the degree of
spatial and temporal resolution required for both data sets makes these beyond
the current state of'the art. However, simplifying assumptions may be intro- '
4
duced to obtain rough approximations for these types of measures.
6.1.3 Desirable Properties
Certain properties are desirable for a statistical air quality indicator.
Some properties are desirable on a purely intuitive basis; others involve tech-
nical or practical considerations.
Clarity - Because the purpose of an indicator is to convey information,
there is an advantage in using an indicator that is easily understood. Although
understanding is partially a function of the intended audience, simple data pre-
sentations should use mare,easily understood indicators than those appropriate
for a detailed examination of alternative control strategies if the more detail-
ed analysis requires a more complicated indicator. Clarity does not necessari-
ly mean that the indicator is simple to compute. For example, the computations
for evaluating the PSI require linear segmented functions, but the final result
is relatively easy to comprehend.
Independence of Sample Size - Another desirable property, on an intuitive
basis, is that the indicator be independent of sample size. For example, sam-
pling TSP every 6th day commonly results in approximately 60 measurements a
year. Sampling every day of the year may result in 365 (or 366) measurements.
Use of the maximum value, the second maximum, or the number of times the stand-
ard level is exceeded creates a problem with different sample sizes. A site
that samples once every 6th day has only a l-in-6 chance of measuring the an-
nual maximum; a site that samples every day obviously measures the maximum.
Any indicator that does not account for varying sample sizes can be misleading.
6-3
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Robustness - A property that should be mentioned is robustness—that is,
the indicator is not unduly influenced by a few outliers. How desirable this "
""propertyts—for air quality data analysis depends on the type of study. In
air pollution work, the higher concentrations are often the most important;
therefore, the median concentration may be robust but irrelevant. If the pur-
pose of the study is to examine trends resulting from an overall emission re-
duction, the robustness of the indicator may be desirable.
Precision and Accuracy - A statistical indicator can have all of the
above properties and yet fail to adequately summarize the data. Therefore,
precision and accuracy must be included as desirable properties. Accuracy im-
plies that the indicator is unbiased; precision measures the variability of
the estimate. A recent paper by Johnson discusses these properties for cer-
tain air quality indicators.
Feasibility - A practical evaluation of potential indicators must con-
sider the feasibility of implementing a particular choice. An indicator may
be highly desirable but not feasible to implement due to the present state of
the art or to lack of information in the air quality data bases. This does
not mean that a promising indicator should be ignored because it is difficult
to implement; such a situation can highlight where additional work is needed.
Relevance - After all of the above properties have been considered, the
final test of an air quality indicator is its relevance to the purpose of the
study. Does the indicator sufficiently characterize the data so that the re-
sults may be easily translated into a clear statement of the information in
the air quality data?
6.1.4 Discussion of Candidate Indicators
Consideration of all possibilities is not practical when discussing can-
didate indicators. It is more convenient to delineate certain classes of in-
dicators: peak values (highest and second highest measurements), mean values
(arithmetic and geometric), percentiles, exceedance statistics, design value
statistics, multisite indicators, multipollutant indicators, and seasonal in-
dicators.
Peak Value Statistics - This class includes indicators such as the maxi-
mum and the second highest concentrations which have been used because they
are consistent with the "once per year" type of air quality standard. These
-------
are not independent of sample size. For less than everyday sampling, they
have a negative-bias because they underestimate-the true value. Therefore -
it-fs-difficult to recommend this class of statistics unless an adjustment
is made for sample size. A possible alternative approach is the use of ex-
pected peak values estimated by fitting distributions to the data; this ap-
proach yields statistics independent of sample size.
Mean Values - TSP, S02» and N02 have NAAQS's involving annual means (ar-
ithmetic for SOg and NOg; geometric for TSP), so the use of an annual mean for
these pollutants is fairly natural. For CO and Oj, the annual mean is not par-
ticularly useful for assessing status. Because the primary CO control strategy
involves motor vehicle emission reductions, the annual mean may be adequate for
trend analyses; nevertheless, changes in higher concentrations, should be exam-
ined. The typical diurnal and seasonal patterns for 0, suggest that the an-
nual mean is of little value.
Percentiles - Use of percentiles is one means of adjusting for differ-
ences in sample sizes and affording a degree of protection against a few ex-
treme values. If higher concentrations are of interest, little will be gained
by using lower or midrange percentiles. Upper percentiles are more useful;
the 90th, 95th, and 99th percentiles provide an adequate range for trends analy-
ses.
Exceedance Statistics - This class of statistics includes both the fre-
quency and the relative frequency that an air quality level (NAAQS or other)
was exceeded. This type of statistic is intuitively appealing, and is rela-
tively easy to understand. If the level of the standard is used, the results
relate directly to status assessment. Statistics involving the recorded num-
ber of exceedances (rather than the percentage of exceedances) depend on the
sample size; with less than complete sampling, they underestimate the true val-
ue. As with peak value statistics, it would be advisable to use an adjustment
to account for incomplete sampling. This type of correction was incorporated"
7 8
into EPA's recently revised 03 standard. *
A change from one to two exceedances does not mean that the air quality
has become 100 percent worse. Caution is needed in interpreting this type of
statistic because it exaggerates percentage changes. Johnson5 considered the
relative precision of exceedances and the 90th percentile for 03 data, and
concluded that the 90th percentile was more desirable for trend analyses.
6-5
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Design Value Statistics - For a site that fails to meet a standard, the
design value is the. concentration that must be reduced to the level of the
^standardjfgr^site compliance. Design values computed for sites that meet the
standard would be less than or equal to the standard. The design value is a
convenient summary statistic, but it is not easy to compute because it may in-
8
volve factors other'than the actual air quality concentrations. Although in-
formative, these statistics are difficult to recommend for general use because
of the complexities of their estimations. "
Hultisite Indicators - An indicator that combines data from several sites
___^_«___———_.
(e.g., PSI) can be useful. A recent paper by Cox and Clark suggests areawide
indicators .for examining trends for regional-scale pollutants such as 0^. A
potential problem with multisite indicators is that data from cleaner sites can
mask higher concentrations at other sites. The seriousness of this problem de-
pends on the purpose of the study.
Multipollutant Indicators - An indicator that combines data for several
pollutants should scale the measurements so that the contribution of each pol-
lutant is appropriate. The PSI was developed for this purpose, and is recom-
2 3
mended as the standard indicator for these types of applications. It pro-
vides a convenient air quality indicator for daily reporting. A multipollutant
indicator is not recommended for characterizing trends because of the difficul-
ty of interpreting the results; for example, improvement in one pollutant may
mask degradation in another. The logical step in interpreting the results is
to examine trends for each pollutant.
6.1.5 Conclusions
When the purpose of the analysis is to compare standards, an indicator
that relates directly to the standard is needed. For pollutants with annual
mean standards, the annual mean also suffices for trend analyses. For pollu-
tants with only peak value standards, peak value and exceedance statistics
are acceptable for trends if adjusted for sample size; upper percentiles (90th-,
95th, and 99th) should also be considered. For pollutants (e.g., OO with
clear seasonal peaks, statistics based on data for only the peak season are
acceptable. In all cases, the data should be summarized for an averaging time
that corresponds to the averaging time of the standard.
Multisite indicators may warrant further study, particularly for areawide
pollutants. In national trend assessments, data are available for hundreds of
6-6
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sites; but because many subsets of these sites are correlated, interpretation
of the results-is complicated. Multisite indicators could be used to aggre-
-gate_the data for appropriate subregions as an intermediate step in evaluating
trends.
Another area that warrants further attention is the development of popu-
lation exposure indicators. Such indicators could provide not only a useful
technical tool but also an effective means of conveying information to the
general public.
6.2 TREND TECHNIQUES
A question of interest is whether air quality has changed over time. The
search for the answer results in a variety of analyses categorized as trend 'as-
sessment. Air quality trends analyses can vary in complexity from a simple nu-
merical comparison of statistics from two time periods to a detailed time-series
analysis incorporating the effects of meteorology and emission control programs.
This subsection is a general discussion of trend techniques for air quali-
ty data. More detailed information on certain techniques is contained in EPA's
Guidelines for the Evaluation of Air Quality Trends. Another useful report,
Methods for Classifying Changes in Environmental Conditions; has recently been
prepared in conjunction with the development of EPA's environmental profiles
effort.11
6.2.1 Background and Purpose
Because of the general public's interest in air pollution, questions con-
cerning air quality are fairly common. Air pollution summaries in units such
as micrograms per cubic meter need a useful, frame of reference to make the re-
sult more meaningful. The NAAQS's are one basis of comparison; another is how
air quality values have changed over time, which is a convenient practical way
to provide a perspective on what the numbers mean.
Both the general public and the technical community have a vested interest
in air pollution control programs, and trends analyses are frequently used to
evaluate the effectiveness of these programs. These analyses can be quite so-
phisticated. For example, ambient CO trends during the mid-1970's in New Jersey
were the result of both the Federal Motor Vehicle Control Program (FMVCP) and
an Inspection/Maintenance (I/M) Program instituted by the State; this result was
further complicated by the residual impact of the gasoline shortage in 1974-75.
6-7
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These factors, in addition to the possible influence of varying meteorology,
rapidly escalated the-level of detail needed in an analysis-rnot only with re-.
.Aspect to-the.trend techniques used but also with respect to the types of data
needed.
Another consideration in air quality trends analyses is the scope of the
study. The study may involve data from a single site, or it may involve a na-
tional data sample from hundreds or thousands of sites. A technique that may
be reasonable for an individual site may not be feasible for a more extensive
data set.
6.2.2 Types of Trend Techniques
A wide variety of trend techniques have been used for air quality trends
analyses. This section briefly discusses nonstatistical and statistical ap-
proaches.
Nonstatlstical - The usefulness of graphs (discussed in more detail in
Section 8) in any data analysis should not be underrated. At its simplest lev-
el , the purpose of a trend analysis is to determine what patterns are present
12
in the data. Box-plots, time-series plots, histograms, and so forth—all
serve as convenient guides to the data analyst. In many cases, a careful choice
of the proper graphical technique suffices to indicate trends.(e.g. Whittaker
Henderson,13 Box-plots,14'15 and two-way tables16'17'18).
A second nonstatistical approach is a simple numerical comparison between
summary statistics for two time periods. This is sometimes modified so that
trends are categorized as "no change" if the change fails to exceed some speci-
fied limit. This seemingly arbitrary cutoff may involve an underlying stati-
stical rationale and an assumed variance component.
Statistical - The statistical technique may merely be a comparison of two
annual means by using a standard t-test. When a sequence of data values is
19
available, regression analysis may be used. This may be either parametric or-
nonparametric. ' Trends analysis using regression basically assumes a linear
trend over time. In many practical situations, this assumption may not be rea-
sonable, so alternative procedures (e.g., analysis of variance (ANOVA)) may pro-
vide a more flexible framework for indicating change. Because of the time de-
pendencies in sequences of air pollution data, time-series models have been used
for air quality trends analyses. Intervention analysis is one of the techniques
20
used to examine control strategies.
6-8
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The above techniques apply to a single series of data points.. For analy-
ses of data from several sites, the results at each site may be summarized^as
eithex_up or down, and then analyzed as a contingency table; this technique as-
sumes that the sites are independent.
6.2.3 Desirable Properties
From a practical viewpoint, a desirable trend technique would be one which
is intuitively easy to understand, feasible to implement, based on reasonable
assumptions, and capable of providing results that are easily interpreted.
Intuitively Easy to Understand - People are more comfortable if the
rationale for the analytical technique is intuitively understandable. A tech-
nique may always be implemented on a "black box" basis: the user submits the-
required input data, and the answer appears as the output. For the result to
be useful, however, the user must be confident that the technique will work.
This does not necessarily mean that the technique itself must be simple; it
means that the underlying concepts must be easily explained. For example, an
autoregressive, integrated, moving average model can be presented with a bar-
rage of notations involving forward and backward difference operators. Yet,
the need for a model that incorporates seasonal and diurnal patterns and depend-
encies from one hour to the next is more easily understood.
Feasible to Implement - It is a truism to state that the best trend tech-
nique available will be ignored-unless it is feasible to implement. For air
quality analyses, several considerations are involved in evaluating feasibili-
ty. Because there are limited data histories in many practical situations, the
technique must be applicable to relatively short time periods (e.g., 2 to 5
years). For an analysis of data from a few sites, one may compute many types
of summary statistics; for national analyses, choices must be limited to those
readily available from NADB, which essentially limits the selection to certain
standard quarterly or annual statistics. (Monthly statistics are not stored,
and would have to be computed from raw data.) The number of sites involved
also places practical constraints on the amount of computer time and analyst
time available per site.
Based on Reasonable Assumptions - Every statistical procedure has an un-
derlying model requiring that certain assumptions be satisfied. These assump-
tions should be met by the air quality data for a test to be useful; therefore,
6-9
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the stipulations should be structured so that the air quality data can reasona-
bly be expected to meet them.
Results Easily'In'terpreted - After the analysis is complete, the success*
"of a recfmfque depends on whether the results can be easily interpreted. This
is one advantage of a statistical technique, as opposed to a nonstatistical
technique, for assessing change. The probability assigned by the statistical
procedure is an aid in interpreting the results; it also affects the type of
statistical technique that should be used. For instance, if the annual rate
of change is the variable of practical interest, a procedure such as regres-
sion should be used since this is the type of information it .produces.
6.2.4 Discussion of Candidate Techniques
Important in any discussion of candidate trend techniques for air quality
data is the interpretation of the final result. Because of the strong season-
al ity of certain pollutants (e.g., Q~)t the question of interest often involves
trends for a particular season. From a practical viewpoint, if the effective-
ness of a control strategy is of concern, only the peak months of the year may
be of interest. Because the NAAQS's are stated in terms of annual status as-
sessments (with the exception of Pb, which is quarterly), analyses are often in
terms of annual summary statistics. Use of an annual summary statistic reduces
the number of data points available for the analysis; but if the trend in this
summary statistic is the item of interest, the analysis should be structured
around the statistic.
The remainder of this subsection briefly discusses broad classes of trend
techniques, and indicates comparative strengths or weaknesses.
Graphical Procedures - Graphical presentations (discussed in more detail
in Section 8) are included here to emphasize that they are a useful first step
in any data analysis, not merely a final step for presentation purposes.
Numerical Comparisons - A simple comparison of summary statistics from two
time periods is of minimal use in most cases because it provides no frame of
reference for what is a normal change from one year to the next. Any underly-
ing statistical rationale for categorizing changes as up, down, or as no change
should be stated in the analysis. If the results of these comparisons are ag-
gregated over many sites for a contingency table analysis, they are acceptable.
Statistical Comparisons - Statistical comparisons may be made using
either parametric or nonparametric techniques. A typical parametric technique
6-10
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would be a t-test to compare 2 years of data, although the presence of sea-
sonallty may artificially inflate the error term and reduce the sensitivity of
the-feest. Nonparametric tests may.be used to avoid the assumptions that the
errors are normally distributed. The Wilcoxon signed-rank test allows for sea-
sonal ity, and is therefore a useful nonparametric technique. Aligned-rank
tests have been suggested for assessing changes in environmental data; how-
ever, experience with these tests for ambient air quality trends is limited at
this time.
Regression - Both parametric and nonparametric regressions provide an es-
timate of the rate of change as well as a statistical significance test. In
assessing air quality trends, the rate of change is often important because it
relates directly to the effectiveness of a control strategy rather than simply
stating whether an increase or decrease has occurred. Because of seasonal pat-
terns in the data, regression is normally applied to an annual statistic or a
summary statistic for the peak season; this is a disadvantage since only one
value a year is used. Regression also tests for a linear trend, which is use-
ful either when the user is interested in a linear trend or in a relative mea-
sure of net change over the time period; but if a finer resolution of the pat-
tern is desired, regression may not be adequate.
Analysis of Variance - The general class of analysis of variance (ANOVA)
models offers considerable flexibility for trends analysis. The user can in-
troduce month, season, and year terms into the model if a single site is being
examined. For an areawide analysis, a site-effect term can be added as well as
interactions and even covariates. ANOVA is not restricted to linear trend as-
sumptions, and multiple comparison tests are available to test for significant
differences among effects of interest.
Time-Series Analysis - A basic assumption in many statistical techniques
is that successive measurements are independent—that is, the value of a par-
ticular measurement does not depend on past measurements. In view of the
diurnal and seasonal patterns often present in air quality data, one may use
time-series techniques for these problems. Applications of time-series tech-
20
niques for air quality analyses have used Box-Jenkins techniques, Fourier
21 22
analysis, and polynomials to remove the seasonal components. Intervention
analysis techniques seem appropriate for examining control strategies and other
20
types of intervention. While these techniques have the advantage of produc-
ing more information, they are also more difficult to apply; consequently, it
6-11
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is difficult to reconinend them for routine large-scale analyses.
6.2-. 5 Conclusions
__ At_the_present time, it does not seem feasible to recommend specific trend
techniques. Since trends analyses are done for different purposes, the level
of resolution required in the answer may vary from a simple up-down classifica-
tion to an actual determination of the percentage improvement associated with
a specific control strategy. However, it does seem advisable to encourage the
use of statistical tests as an objective means of classifying trends.
Areas that warrant further examination Include the intervention/time-series
approach to see if the. implementation of this type of analysis can be simplified
so that its use can become more routine. Also, more experience is needed in ap-
plying the aligned-rank test to air quality data.
6.3 REFERENCES
1. Kendall, M. 6., and W. R. Buck!and. A Dictionary of Statistical Terms.
Hafner Publishing Company, Inc., New York, N.Y., 1971.
2. Guideline for Public Reporting of Daily Air Quality Data - Pollutant
Standards. Index (PSI). No. 1-2-044. Office of Afr Quality Planning and
Standards, U. S. Environmental Protection Agency, Research Triangle Park,
N.C., August 1976.
3. Federal Register 44(92):27598, May 10, 1979.
4. Frank, N. H., et al. Population- Exposure: An Indicator of Air Quality
Improvement. 70th Annual Meeting of the Air Pollution Control Association,
Toronto, Canada, June 1977.
5. Johnson, Ted. Precision of Quantile and Exceedance Statistics. American
Society of Quality Control Technical Conference Transactions, Atlanta, Ga.,
1980.
6. Johnson, T., a*nd M. Symons. Extreme Values of Wei bull and Lognorma-1 Dis-
tributions Fitted to Ambient Air Quality Data, Paper No. 80-71.4, Annual
Meeting of the A1r Pollution Control Association, Montreal, Canada, June
1980.
7. Federal Register 44(28):8282, February 8, 1979.
S. Curran, T. C., and W. M. Cox. Data Analysis Procedures for the Ozone
NAAQS Statistical Format. Journal of the Air Pollution Control Associa-
tion 29(5):532, May 1979.
9. Cox, W. M., and J. B. Clark. An Analysis of Ozone Concentration Patterns
Among Eastern U.S. Urban Areas (draft).
6-12
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10. Guidelines for the Evaluation of Air Quality Trends, OAQPS No. 1.2-015.
U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards,.Research Triangle Park, N.C., February 1974.
11. Methods for Classifying Changes in Environmental Conditions. VRI-EPA
7.4-FR3 0-1 (draft). Vector Research, Inc., Ann Arbor, Michigan,
February 1980.
12. Tukey, 0. W. Exploratory Data Analysis. Addison-Wesley Publishing Com-
pany, Reading, Mass., 1977.
13. Spirtas, R., and H. J. Levin. Characteristics of Particulate Patterns
1957-1966. U.S. Department of Health, Education, and Welfare, National
Air Pollution Control Administration, Raleigh, N.C., March 1970.
14. National Air Quality and Emissions Trends Report, 1976. Publication No.
EPA-450/1-77-002. U.S. Environmental Protection Agency, Office of Air -
Quality Planning and Standards, Research Triangle Park, N.C., December
1977.
15. National Air Quality and Emissions Trends Report, 1977. EPA-450/2-78-052.
U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, Research Triangle Park, N.C., December 1978.
16. Phadke, M. S., et al. Los Angeles Aerometric Data on Oxides of Nitrogen
1957-72. Technical Report No. 395. Department of Statistics, University
of Wisconsin, Madison, Wise., 1974.
17. Tiao, G. C., et al. Los Angeles Aerometric Ozone Data. Tech. Report No.
346. Department of Statistics, University of Wisconsin, Madison, Wise.,
1973.
18. Tiao, G. C., et al. Los Angeles Aerometric Carbon Monoxide Data. Tech.
Report No. 377. Department of Statistics, University of Wisconsin, Madi-
son, Wise., 1974.
19. The National Air Monitoring Program: Air Quality and Emissions Trends.
Annual Report Volume 1. Pub. No. EPA-450/l-73-001a. U.S. Environmental
Protection. Agency, Office of Air Quality Planning and Standards, Research
Triangle Park, N.C., July 1973.
20. Box, G. E. P., and G. C. Tiao. Intervention Analysis with Applications to
Economic and Environmental Problems. Journal of the American Statistical ' -
Association 70:708-79, 1975.
21. Phadke, M. S., M. R. Grupe, and G. C. Tiao. Statistical Evaluation of
Trends in Ambient Concentrations of Nitric Oxide in Los Angeles. Environ-.
mental Science and Technology, Vol. 12, No. 4, April 1978.
22. Horowitz, 0., and S. Barakat. Statistical Analysis of the Maximum Concen-
tration of an Air Pollutant: Effects of Autocorrelation and Non-stationarity.
Atmospheric Environment 13:811-818, 1979.
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7. INFERENCES AND CONCLUSIONS
This section focuses on the problem of identifying cause-and-effect rela-
tionships after a statistically significant trend or difference between data
sets has been*determined. Previous sections have discussed the problems of
data completeness, historical trends criteria, precision and accuracy of data,
screening data for outliers, siting and representativeness, statistics for
analyzing air quality data, and trend techniques. Assuming that all of these*
problems can be resolved in a particular analysis, the problem of interpreta-
tion remains.
7.1 BACKGROUND
At the present time, most air quality data available for analysis are
submitted to NADB. The major enhancement to this system is the current de-
signation of NAMS—a refined national monitoring network in areas with large
populations and high pollutant concentrations. Each NAMS will meet uniform
criteria for siting, quality assurance, equivalent analytical methodology,
sampling intervals, and instrument selection to assure consistent data report-
ing among the States. Precision and accuracy data will be available with the
air quality data for the first time.
Though the enhancements achieved through the monitoring regulations will
provide a much sounder national air quality data base for decisionmakers, the
data are still .seriously deficient in determining cause-and-effect relation-
ships between air quality, emission changes, meteorology, and the impact of un-
anticipated events such as fuel shortages. Explaining the causes of air quali-
ty changes is difficult without information to supplement basic "air quality
data. For example, what is the impact of a local, regional, or national gaso-
line shortage on ambient air pollution levels? What is the probable impact of
fuel switching or tampering with automotive emission control devices on air
quality levels?
A case in point is the recent controversy over 03 trends in Los Angeles.
A significant increase was observed in 03 levels between 1977 and 1978. An
7-1
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2
attempt was made by the South Coast Air Quality Management District lo deter-
mine how much of the .increase was due to meteorology; they used a meteorologi-
3
^cal index_cleyeloped by Zeldin; stated that a significant increase in 03 levels
remained after they had adjusted the data for meteorology; and speculatively
attributed it to the breakdown of catalytic control devices. What was needed
was concomitant information on emission changes; independent estimates of fuel
switching, tampering, and so forth; and more complete meteorological data.
The problem in making inferences and conclusions is largely the lack of
supplemental information needed to interpret air quality data analysis and
trends. This lack could be improved in two ways: (1) the data analyst could
try to find concomitant information (e.g., weather data collected at airports
by the National Oceanic and Atmospheric Administration), or (2) a long-term
solution would be to apply the principles of experimental design and enhance
the NAMS in two or more major urban areas with supplemental information on
meteorology and emission changes. The first approach is discussed in the fol-
lowing section on case studies, and the second is discussed in the section on
long-term solutions.
7.2 CASE STUDIES
Over the years, a number of attempts have been made to explain ambient
air quality trends in terms of changes in emissions, meteorological conditions,
or instrument measurement practices (e.g., changes in laboratory procedures or
calibration). The approach can best be illustrated by examples, as in the fol-
lowing four case studies.
7.2.1 Comparison of SO? Trends and the %3 Content Regulations in Distillate
and Residual Fuel Oil in Bayonne, N.JT
The impact of regulations for controlling the sulfur content of fuels on
ambient SO, levels was illustrated in Bayonne, N.J., by comparing ambient S00
4
levels with the effective dates of regulations limiting the sulfur content
(Figure 3). The EPA report which presented the analysis stated that the im-
provement in SO- air quality at this site can be attributed primarily to regu-
lations which became effective in New Jersey and New York during 1968-72. The
trend at the Bayonne site is consistent with the national trend in SO, during
4, t-
this time period, and is probably due to changes in the allowable sulfur con-
tent of fuel.
7-2
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I • • • I
•AHUM 24-HOUR CONCEXnuTBM
QUARTERLY UHE
•TKEHDUHE
ANNUAL PROMT STAKBAROS 00)
. , .llf.ltl.lt _ L 4 I _ ! _ I _ itJ - ! - 1 - « - ! - 1 - 1
10/1/nAU.OlL-O^S
RESIDUAL on.-us:
Figure 3. Comparison of S02 trends at Bayonne, N.J., with regulations
governing % sulfur content in fuel.
7-3
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The analysis could have been improved, and the conclusions strengthened
if appropriate meteorological data had been available to be treated as a co-
variate. As it stands," however, the graphical presentation "suggests a reason-"
-able ca-use-and-effect relationship between the decreasing levels of SO- and
the increasing restrictiveness of regulations limiting the sulfur content of
fuel.
7.2.2 Impact of Gasoline Shortage on CO in Richmond. Va.
An analysis of CO data 1n Richmond, Va., illustrates the problem of in-
terpreting ambient data. In 1974, an EPA analysis was undertaken to evaluate
the effect, if any, of the energy crisis on CO levels. The CO monitoring site
in downtown Richmond was representative of the influence of commuter traffic
patterns.
The period of time chosen for the analysis was the last 4 weeks (28 days)
of January and the 4 weeks of February. This time period was expected to re-
flect the most severe period of the gasoline shortage and to minimize the po-
tential anomalies in traffic patterns associated with the Thanksgiving, Christ-
mas, and New Year's holidays. The windspeed data recorded at the R. E. Byrd
International Airport served as an approximate indicator of the windspeed at
the site. The data were presented as weekly averages to compensate for the
differences in daily traffic patterns (Table 10).
TABLE 10. WEEKLY AVERAGE CO CONCENTRATIONS (ppm) AND WINDSPEEDS (mph)
IN RICHMOND, VA, JANUARY 4-FEBRUARY 28i 1974
Week
1/04-1/10
1/11-1/17
1/18-1/24
1/26-1/31
2/01-2/07
2/08-2/14
2/15-2/21
2/22-2/28
Hourly
average
2.92
1.94
3.07
2.88
2.28
2.31
2.08
1.73
Daily
8-h max.
4.45
3.13
4.79
4.56
3.54
3.76
3.09
2.81
6 to 9 a.m.
and
4 to 7 p.m.
average
4.50
3.18
4.52
4.20
3.56
3.40
3.00
2.82
Average
daily
windspeed
5.90
7.87
6.63
6.21
7.24
8.06
9.13
9.67
The CO data showed a downward trend during this 8-week period; however,
the average windspeed increased during this period (Figure 4). The decline
7-4
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3.0
2.0
o
o
1.0
T i—rn—i—r—r
AVERAGE CO
" —*'TTlNtTsPEED
I I 1 I
I
I
1 2 3
JANUARY 1974
678
FEBRUARY 1974
WEEK
30
£
O
20
10
Figure 4. Weekly average CO and wind speed in Richmond, VA
from January 4 to February 28, 1974.
7-5
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in CO levels may, therefore, have been due to the increase in average wind-
speeds, which is indicative of greater dilution.
The interdependence was seen in the statistical analysis of the data. If"
the change~~Tn windspeed was ignored, four parameters—daily average, maximum 8-
hour average, rush-hour average, and nonrush-hour average—showed statistically
significant decreases, although the rush-hour decrease was less apparent in the
averages. These findings were based on ANOVA. When windspeed was introduced
into the analysis as a covariate, using analysis of covariance, none of the
changes in the above parameters were significant. Therefore, although the data
at this site indicated a decline in CO levels during this period, the associat-
ed increase in windspeeds made the cause of the decline difficult to assess.
Failure to detect significant trends after adjusting for windspeed is not
entirely unexpected. The variability associated with CO measurements and the
relatively brief duration of the gasoline shortage make it possible for the ef-
fect to go unnoticed, unless the monitoring site itself was in precisely the
right location to detect changes due to alterations in traffic patterns.
This example illustrates one problem in trying to use data collected for
one purpose for yet another purpose. The assumption that the windspeed at the
airport reflects the windspeed at the downtown Richmond site may not be cor-
rect. Ideally, the windspeed should be measured at the CO monitor so the ana-
lyst could be more confident in interpreting the results.
7.2.3 Trends in CO in New Jersey
An analysis of CO data in New Jersey illustrates an attempt to relate
statewide CO trends to gasoline consumption. Figure 5 was prepared by the N.J.
Department of Environmental Protection to illustrate the progress made in re-
ducing State CO levels from 1972 through 1976. The dates for the initiation
of the two phases of their inspection/maintenance (I/M) program are shown.
New Jersey indicated that CO levels continued to improve despite an overall in-
crease in gasoline consumption.
While progress in CO levels is clearly evident, the effectiveness of the
New Jersey I/M program is confounded with the overall effectiveness of the CO
emission reductions attributed to the Federal Motor Vehicle Control Program
(FMVCP). Ideally, it would be desireable to separate the effects of the two
control programs; this could be accomplished with a designed experiment. Con-
comitant meteorological data would be desirable to determine if changes in
meteorology would aid in explaining the statewide CO trend.
7-6
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Is
i 4
8
LU 3
•M4
OQ
I
IMPLEMENT
PHASE I
I/M PROGRAM
AMBIENT
CO
GASOLINE
CONSUMPTION
300
IMPLEMENT
PHASE II
I/M PROGRAM
en
w
O
275
250 o
225
I
CM
o
t—
o.
o
o
UJ
o
-------
7.2.4 The Central Plains Drought
• On February 24, 1977, the extremely dry soil conditions in the Central
*" •
Plains and a strong frontal system resulted in dust being stirred up and trans-
ported east. Figure 6, a modified box-plot, shows peak TSP levels in Region VI
(Central Plains) by quarter from 1972 through 1977; the dramatic increase in
the first quarter of 1977 is obvious on this graph. Monitoring sites through-
out Texas, Oklahoma, and Arkansas reported high TSP levels during this February
duststorm. Several sites recorded daily values of'more than 1000 ug/m ; a sin-
gle value of this magnitude would increase the annual geometric mean at a site
by 10 percent.
In this example, the high TSP levels reported throughout Texas, Oklahoma,
and Arkansas are substantiated by satellite pictures taken February 23-25, 1977 "
(Figure 7).
7.2..5 Conclusions and Recommendations
With the existing NAMS network, the best an analyst can do to facilitate
the interpretation of air quality monitoring data is to seek other sources of
information to help explain why an air quality trend has or has not taken place
or why there is a significant difference between sets of data. The four case
studies illustrate the importance of meteorology, emission changes resulting
from control programs, and the impact of extraordinary events (e.g., the dust-
bowl of February 1977). A long-term solution is application of the principles
of experimental design to the collection of air quality and appropriate con-
comitant meteorological data. Such a'solution is discussed in the following
section.
7.3 LONG-TERM SOLUTIONS
One solution to the problem of trying to assess the effectiveness of EPA's
control programs would be to select two or more urban areas and to collect con-
comitant information on a continuing basis to aid in answering both anticipated
and unanticipated questions about effectiveness. The objective would be to de-
termine cause-and-effect relationships between air quality and emissions after
isolating the effects of meteorology, these relationships could be determined
if data could be collected to estimate the impact of gasoline shortages, fuel
switching, automobile control device tampering, contributions of various sources,
7-8
-------
I r
_ CM
i*»
o
*J
CM
I
c -o
o
O
0)
(O *J
> o
3 «4-
E u
•*—
X 0)
IQ .C
E 4->
O. O
to c
(O i
3 •
o-
0}
3
en
8
1
,u/6n 'NOIiWiN30HOO dSl
7-9
-------
Ol
c
•o
ft)
l
VI
CM V)
I -O
<*) O
CM f
-------
changes in Instrument calibration, degree of human exposure, extent of fugitive
dust, and so forth.
Air quality, monitoring, and emissions data would be collected according
to 7n~experimental design to test stated hypotheses. Each of the criteria pol-
lutants—TSP, S02» CO, 03, and NOg—would be measured in the two or more urban
areas along with IP and sulfates. Sources of emission changes to be consider-
ed in developing the experimental design include but are not limited to: (1)
changing economic conditions; (2) increased or decreased refinery capacity; (3)
fuel switching; and (4) growth patterns (e.g., the number of dry cleaning estab
lishments).
At a minimum, experimental designs would use analysis of variance (ANOVA)
and the analysis of covariance (COVA) to test hypotheses, and would use confi-
dence intervals about means in question to display significant findings. Other
appropriate statistical techniques would also be used to test hypotheses.
A contract has been let to explore this long-term solution in greater de-
tail. The objective is to pose policy questions and then to determine what
supplemental information would be needed to answer the questions in two or more
urban areas. The associated costs are also to be determined. When the report
on this contract is completed, its principal findings will be summarized and
appended to this report.
7.4 REFERENCES
1. Federal Register. Vol. 44, May 10, 1979, pp 27588-27604.
2. Davidson, A. et. al.. Air Quality Trends in the South Coast Air Basin.
South Coast Air Quality Management District, El Monte, Calif. June 1979.
3. Zeldin, M. D., and D. M. Thomas, Ozone Trends in the Eastern Los Angeles
Basin Corrected for Meteorological Variations. Presented at the Inter-
national Conference on Environmental Sensing and Assessment, Las Vegas,
Nevada, 1975.
4. Monitoring and Air Quality Trends Report, 1972. Pub. No. EPA-450/1-73-.004.
U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, Research Triangle Park, N.C. December 1973.
5. Monitoring and Air Quality Trends Report, 1973. Pub. No. EPA-450/1-73-007.
U.S. Environmental Protection Agency, Office of Air Quality Planning and
Standards, Research Triangle Park, N.C. October 1974.
6. New Jersey Department of Environmental Protection Annual Report: July 1,
1976-June 30, 1977. New Jersey Department of Environmental Protection,
Trenton, N. J. (in preparation).
7-11
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, Research.Triangle Park, N.C. May
7-12
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8. DATA PRESENTATION
The purpose of this section 1s to review well-established data presenta-
tion techniques applicable to acrcmstric measurements and to provide guidance
on selection of the forms most suitable to the scope of the problems to be
analyzed. Selection is based on criteria such as audience applicability,
spatial and temporal classification, and availability of computerized statis-
tical and graphical resources. Therefore the discussion is focused on (1)
the fundamental concepts to be displayed, (2) chart types, (3) input data
forms, (4) statistical classifications, (5) audiences, (6) caveats/enhance-
ments, and (7) available plotting resources. Finally, displays that meet
these requirements are included.
8.1 CONCEPTS TO BE DISPLAYED
A simple but accurate presentation of statistical measures of large data
bases or parametric relationships contributes greatly to the reader's under-
standing of the data. The most common displays of data on air quality and •
source emissions include (1) current status of the pollution problem, (2) sta-
tistical or descriptive trend, (3) impact of one or more parameters on another,
(4) comparison of two or more groups or classes for a specific parameter, (5)
relation of component parts to the whole, and (6) spatial and temporal patterns.
Statistical measures may be chosen not only from individual monitoring-site
or emission point-source populations of averages, medians, percentiles, maximums
or standards exceedances but also from aggregates (weighted or unweighted) of
these sites on a city, county, region, state, national, or global scale.
Data presentation should be carefully planned. The charts or graphs, as"
well as the statistical displays, may be easily distorted (intentionally or
unintentionally) by compression or expansion of scales, by nonuniform or broken
gridding, by line and shading optical illusions, and by cluttered or complex in-
formation. The following subsection introduces the most frequently used dis-
plays.
8-1
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S.2 CHART TYPES AND USES
.1 Tabular Suirwari.es
•-> . £. . A
—— Surnnase-iiing data in tabular format is an Important first step in data
analysis. The validity and accuracy of the data should be certified before
applying summary techniques. The tabular summary provides a permanent record
of the individual data items which can be further analyzed in future research
projects.
Aerometric examples of this form are MADB's monthly listings of hourly
**•""" *; "
air quality values and yearly listings of intermittent (daily or composite)
values. These data are also summarized by NADS in the yearly and quarterly
frequency distribution listings. Similarly, point-source emissions cats ara
submitted to MADS by-the National Emissions Data System (NEDS).
Tabular summaries provide comparisons of several parameters categorized
at one or more levels. Examples are listings of TSP, SO-, and N02 by day of
the year (Table 11), weekly TSP/maximum values at several monitoring sites
(Table 12), and TSP monthly averages by site type (Table 13).
Finally, either certain qualitative measures may not be readily applica-
ble to graphing or more information is provided in a smaller document. One
example is a display of current attainment status and trends using a variety
of symbols and colors, as shown in Figure 8.
Tabular listings or summaries should be limited in most cases to technical
support documents. For regional or national publications, these summaries
should be limited to comparisons of one or two parameters and about five class-
es or categories. Tedious or complex tables often contribute to the reader's
confusion and misunderstanding; moreover, descriptions of statistical tech-
niques used in producing these tables are often either left out or limited in
the text, discussion.
8.2.2 Point Charts
Point charts are used primarily to describe situations where scatter or
clustering are important. Since these displays for large data bases would be
almost impossible to draw manually, computerized techniques have been applied.
Rapid display of data to detect outliers, parametric relationships, or data
distribution is clearly a benefit to the statistician. Common uses are corre-
lation or cluster analysis (Figures 9 and 10), plotting air quality concen-
trations by year (Figure 11), and comparison of air quality for several
8-2
-------
TABLE 11. MULTIPLE PARAMETER LISTING, 1979, yg/m3
Yr/mo/day
79/01/01
79/01/02
79/01/04
*
•
79/12/31
TSP
125
86
•
•
145
SO-2
35
43
50
83
N02
45
52
•
•
96
TABLE 12. WEEKLY TSP MAXIMUMS AT CITY SITES, 1979, ug/m3
Week
beginning
Jan 7
Jan 14
•
•
Dec" 29
1979 Max
1979 Avg
4th & Market
120
163
•
•
103
236
125
Sites
6th & Vine
50
No sampling
•
•
52
99
55
18th Jackson
70
99
•
•
63
136
86
City
max
120
163
•
•
103
236
125
City
avg
80
131
•
•
•
73
187
77
TABLE 13. REGION 5 MONTHLY AVERAGES BY SITE TYPE, 1979, ug/m3
Month
Jan
Feb
•
•
Dec
Total
Commercial
Sites
Obs
Avg
Industrial
Sites
Obs
Avg
'
Residential
Sites
Obs
Avg
Remote
Sites
Obs
Avg
-
8-3
-------
County
Jefferson
IPrTata
Larimer
Las Aniws
Logan
Mesa
Moffat
Montasuna
Hontrose
Morgan
Otero
PUkin
Pi-owe rs
Pueblo
tour:
Weld
TSP | SO,
tsT
O
__ m
b
P
o
C0
o
o
o
lO*
^
^
@2
0,
a^-
O
NO,
CO
o
[•N
Ox Countv
(•"> Acars
Alaaasa
Arapahoe
Archuleta
Boulder
Clear Creek
Delta
Denver
Douglas
Eagle
El Paso
Fremont
Sarfield
Sunnison
Huerfano
O
TS»
0'
0,
E>
E>"
D
n£>
t,
B
0,
s>4
Cf
^
£>
0
so-
p
0
KO-
0
i
-
0
o
CO
— 1
\s '
t
^
i
OT
O
s>
O
a/ Status based on annual
mean only
II No evidence standare excesaed
{¥] Exceeds primary stanoartf
| Exce«4s alert level
| [ Increasing trend (deterioration)
| '^ Ho apparent trend
Decreasing trend (improvenent)
Figure 8. Status and trends in air quality in Colorado.
8-4
-------
LU VI
-------
1.7J |*-
t.o U.
MM
tlM
mime
on f«i«>
••
otrmu
u~' 3
»r=g
.8S tc-w
1::-,
B.M e.as
4.12
C-TJ 18.71
— te.8j
S.1J Ul.M
ll!^
t i~?tiT •>
n uiflii *na •
UtTO. t ».M
Figure 10. Magna, Utah, day 3, 0.50 probability ellipses of the west-east and
south-north wind components for three cluster types. Winds from the west and
south are positive.
8-6
-------
600
500
400
300
200
100
I T
PRI
SEC
TSP
O O O
0° O
o
o o
o o
FEB
APR JUN AUG OCT
MONTH"
Figure 11. Twenty-four hour TSP values, 1972.
8-7
-------
categories (Figure 12)-.
Point charts usually are accompanied by some "best-fitting" solid line to
describe annual trend-or diurnal or seasonal pattern. The integrity of the in-
.««djvidual_p_p_ints is the foremost reason for displaying data in this way.
8.2.3 Line or Curve Charts
The line or curve chart is perhaps the most widely used method of present-
ing summarized data graphically. The chart is also the most easily constructed
manually. The most common uses in displaying air quality or emissions data are:
1. Data coverage over a long time period (Figure 13).
2. Emphasis on movement rather than on actual amount (Figure li).
2. Comparison of several series, (same measurement unit) en same chart
(Figure 15).
4. Trends in frequency distribution; e.g., population exposure
(Figure 16).
5. Use of the multiple amount scale (Figure 17).
6. Estimates, forecasts, interpolation, or extrapolation (Figure 18).
3.2.-1 Surface Charts
The simple surface or band chart depicts a single trendline with shading
or crosshatching filling in the area between trend and base lines to enhance
the picture of the trend. Thus, in this chart type:
1. The magnitude of the trend is emphasized,
2. A cumulative series of components of a total trend is depicted, and
3. Certain portions of the chart are accented for a specific purpose.
Figure 19 exemplifies classification of CO data by concentration level and by
number of monitored days.
8.2.5 Column/Bar Charts
Column/bar charts are intuitively simple for most readers to follow since
they accent discrete dates or categories with comparative heights of the columns/
•
bars for one main statistic. The primary purpose is to depict numerical values
of the same type over a given time period (i.e., multiple years), as shown in
Figure 20. Other uses are:
8-8
-------
XL IA
Figure 12. Air quality data, 24-h TSP concentration values,
October 15, 1976.
8-9
-------
FES
APR
JUN
AUG
OCT
Figure 13. Maximum 1-h 03 values/day, 1977
(SAROAD site 141220002P10).
8-10
-------
-------
c_
l/J
100
ANNUAL STANDARD
PRIMARY 24-H
ALERT 24-H
SECONDARY 24-H
ANNUAL AVERAGE
2ND MAX DAY
1970
1971
1972
YEAR
1973
1974
1975
Figure 15. Annual average and second-high dav TSP values,
1970-75.
8-12
-------
C9 -t->
*- 0>
a u
UJ i-
LU 0)
U 0.
X
UJ »
«/» o
M UJ
-
o
Q.
40 —
20 —
40
fin
75 80
100
120
ANNUAL TSP CONCENTRATIONS, vg/m3
Figure 16. Population exposure distributions of annual mean TSP for 1970
and 1976 1n city of Chicago.
8-13
-------
LU
C3
a.
LU
C3
o
o
«Mtt(NT
UKtON
MONOXIO£
300
275
ee.
UJ
O
250 i
i
CM
C.
225
o
I/I
200
1972 1973
1974 1975
YEAR
1976
1977
Figure 17. Ambient CO concentration and gasoline
consumption, 1972-77.
8-14
-------
MONTHLY ClOMHtlC MEAN
H-MONTH IUNNINC GEOMCTUC MIAN
1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974
Figure 18. Comparison of monthly GM, 12-mo running GM, and
predicted monthly means (by double moving average method),
1964-74.
8-15
-------
200
£ 150
»—
UJ
100
o
o
C3
t/1
I 50
U-
o
UJ
CC
1975
1976
1977
TOTAL
9-13 ppm
13-17 porn
>17 oom
Figure 19. Trends in CO levels in New York's 45th Street Station,
April-January, 1975-77.
8-16
-------
o
C8
no
no
in
so
1 ,
UJ
co no
O.
•- ISO
01
Q too
u_
O
ca
z Q
200
ISO
100
U
a
rsifc
00-2
M
1
-
-
rttrml
00
•M^H
Itlllt
il^
Ilillillja
limn
ttadawll
tamr
H
Wiml
•300
^PSII.
ttsjiii &30C
so
200
ISO
100
SO
0
200
ISO
100
SO
0
200
ISO
100
so
0
tin
-
*\
Oti
HM
mvk
Ctto
HII II j
filn
JiPSltal
1-300 im
0«
•
Oiftpo. Ohto
mils
1.300
fflBM
_
Illllll
1873 1974 1975 197S
Figure 20. Trends in PSJ levels, 16 cities, 1973-76.
8-17
-------
1. Comparison of numerical values of the same type for several cate-
gories. (Figure 21),
__ 2._.^Comparison of two or three independent series over time such as
" grouped columns, subdivided columns, and three dimensions (Fig-
ure 22),
3. Display of increases or decreases, losses or gains, or deviation
from requirement or norm (Figure 23),
4. Display of ranges of maximal and minimal values for a series (Fig-
gure 24).
The wind rose is a familiar application of the bar graph in circular form
(Figure 25).
Caveats to be considered in preparation of these charts are irregular
time sequences, spacing between columns/bars, scale breaks, shading, and the
ordering or sequencing of items represented by the columns/bars.
8.2.6 Pie/Sector Charts
The familar pie/sector chart in the form of a circle compares component
parts, and shows their relation to the whole. Source emission categorization
lends itself well to this chart type (Figure 26), as does population exposure
(Figure 27). The pie chart is often used with line, column, bar, or map dis-
plays to exhibit geographic or categorical components of trends.
8.2.7 Map Charts
Map charts are attention-getters, and they are most applicable to en-
vironmental statistics, especially air quality. National, regional, State,
county, and city maps may depict formation and transport of air pollutants in
a real-time, dynamic sense. Moreover, within boundaries, current year-of-
record and trends may be shown through isopleths, symbols, or shading. Fig-
ures 28 and 29 demonstrate two applications of the treatment of data in the
dynamic (isopleth) and static modes.
8.2.8 Three-Dimensional Charts
Advanced computerized graphic techniques have made the three-dimensional
chart type a viable alternative to three-way tables and to restrictive two-
dimensional plane representations. The most significant applications have been
to dispersion modeling and contour mapping (Figure 30).
8-18
-------
10
2 5
ca
LU
o.
= 3
o
2
1
0
_ ACTUAL (NEDS) AND ILLEI (IEPA DATA) —
• ACTUAL
H POTENTIAL
D ILLEI
Figure 21.- Actual vs. potential emissions for Illinois, tons/year.
8-19
-------
Cfluntv feltvl
Arcnultta (Ptoo** Springs)
Boulder Uononont)
Denver (Denver)
1976
1977
1978
rren»nt (Cinon City)
ttr".t\i (Rifle)
Jtoffat (Cnig)
Ottro (Rocky Fort)
(Asotn)
Pnjwtrs (Uotr)
Pueblo (Pueblo)
Routt (Suimoat Sorinjs)
Held (U S4l1e)
Prlmtry level txct*o*d
Alert level
Figure 22. Number of days per year that the TSP primary
standard or alert level was -exceeded, Colorado.
8-20
-------
V
o
QJ
CL
LU
OO
O
o.
x
Ui
O
*-^-
t—
C_
O
100
90
80
70
60
50
40
30
20
10
0
r
10
CD MCnMIMtVHM
•I mem MI m urattt
IfTJ
I IT?
87 6
WEST
5 4321
REGION EAST
Figure 23. Regional changes in metropolitan population exposures to
excess TSP levels, 1972-1977 (width of each regional column is
proportional to its metropolitan population).
8-21
-------
T-— 90
1 — 7C
90TH PERCENTILE
75TH PERCENTILE
COMPOSITE AVERAGE
•— MEDIAN
-T—— 25TH PERCENTILE
1-— 10TH PERCENTILE
o
I—
H-
LU
O
o
LJ
h-
O.
a
UJ
C_
co
no
100
90
80
70
60
50
40
30
20
10
0
1
—
—
m
— 4
4
•M
1
1
| |
B
k
)>
mt*
A
•+
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wm
1
•
A
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T 1
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A
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i
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A
i
—
•
•
.
••
i
—
—
M
•
J
—
—
—
1970 1971 1972 1973 1974 1975 1976
YEAR
Figure 24. Trends of annual mean TSP concentrations from 1970 to 1976 at
2350 sampling sites.
8-22
-------
0-3 4-7 8-12 13-18 19-24
SPEED CLASSES (mph)a
012 3 45 6 789 10
SCALE, *
aB1as removed and calms distributed.
Figure 25. Wind rose pattern.
8-23
-------
-------
TOTAL SUSPENDED PARTICULATES (TSP)
OF PEOPLE AFFECTED
01 234 567
ILLINOIS
INDIANA
MICHIGAN
MINNESOTA
OHIO
WISCONSIN
9 10
Figure 27. Air quality status (TSP) and trends in 25 largest urban areas in
EPA Region 5. Pie chart depicts the percent of population exposed to levels
greater than NAAQS for TSP in Region 5. Bar chart is estimated number of
people exposed to these exceedances on a state-by-state basis.
8-25
-------
100
100
ISO*
Figure 28. Isopleths of TSP concentrations (yg/m3)
in EPA Region V and Iowa for October 15, 1976.
8-26
-------
Insufficient data (<755 of maximum possible observa-
tions)
No evidence primary standard exceeded
Primary standard exceeded
Alert standard exceeded
Figure 29. Air quality status, Colorado, 1972.
8-27
-------
O»
o
1C
4-1
c
O)
u
o
o
O S-
^- flj
C..C
(— O)
«o >
c o
o z
(/I
c
0)
2!
8-28
-------
8.3 CLASSIFICATION OF DATA
One of the early goals for standardizing the codes to be applied national-
lyjtfijilr quality monitoring sites was selectivity for analysis. The SAROAD
codes provide time classification, general geographic classification, and site/
neighborhood classification. However, only the first two are currently avail-
able at NADB for user applications. A profile of environmental quality on any
geographic basis will require more unique ways of data classification and
analysis in the future.
8.3.1 Time Categories
Overall, the NAAQS's dictate the following categories as most important:
year (TSP, S02> N02), quarter (Pb), day (TSP, S02), 8 hours (CO), 3 hours (S02.),
and 1 hour (Oj, CO). However, trends analysis techniques could require classi-
fication by hour of the day; day of the week; week; and month for multiple year
comparisons. Autocorrelation techniques may require other nonstandard time in-
tervals and hence a more flexible data base retrieval system. Research needs
will require further analysis of long- and short-range transport, and time se-
lection will be critical for trajectory analysis.
8.3.2 Geographic Categories
Summary statistics are usually retrieved from NADB on a monitoring or
site point-source basis. All individual sites may be retrieved for a city,
county, Air Quality Control Region (AQCR), arid State for a given time span.
Aggregation statistics are not yet standard selection options, except in
special computer routines not available to all users. Nationwide reports
either summarize individual site statistics for all States or select certain
geographic regions, urban areas, or special interstate areas. Likewise, re-
gional and state reports aggregate individual site statistics from all sites
or from selected counties or cities. Multlcounty, county, and city agencies
have more opportunity to deal with specific subcounty areas in annual quali- "
ty reports.
8.3.3 Site/Neighborhood Categories
This largely unexplored categorization has the potential to be a most in-
teresting summary in future regional and national reports. It is now a part
of the National and Regional Environmental Profile (NREP) effort. The. new
8-29
-------
monitoring regulation's require that sites be classified according to neighbor-
hood and monitoring objective. Site types published previously were industrial,
commercial, residential, and agricultural within center city, suburban, near
-urban ,~nira-l, and remote areas. The new classifications are microscale, middle
scale, neighborhood scale, and urban scale. Once established, NAMS will be
categorized and summarized in any of the classification schemes.
8.4 INPUT PARAMETERS, DATA TRANSFORMATIONS, AND STATISTICAL COMPARISONS
Table 14 outlines the details of data types which could be summarized.
Note that effort was made to delineate individual air quality and emissions
statistics from aggregate statistics and counting summaries. Counting sum-
maries are generally used internally as management tools. Only a few such
summaries should be related in RNEP's or in reports to the Administrator. Much
work remains on standardizing data transformation techniques. In addition,
the techniques of maximum-likelihood estimation, application of the general
linear model (GLM) regression and analyses of variance, and spectral (time-
series) analysis could be applied in more cases than they are presently.
8.5 AUDIENCE APPLICABILITY
The most important consideration in data presentation is applicability
to a specific audience. For example, the report to the Administrator may
cover not only air quality assessment but also the end results of EPA pro-
grams and regulatory policies. The data needs are national in scope for the
environmental assessment, perhaps with highlighted urban areas on criteria
and noncriteria pollutant issues. Both air quality and emissions data, cur-
rent status and trends, would be given on a national and possibly a region
basis; this level would require more graphic presentation than a technical/
management report—for example, a graphical summarization of data resulting
from singular national events (volcanic eruptions or widespread duststorms).
A report to the Regional Administrator may be merely a subset of the re-
port to the national Administrator, but with emphasis on regional policies.
The summary statistics are usually given state by state, by selected major ur-
ban areas and by regions.
Reports to other government agencies and in response to congressional and
(to a large extent) public inquiries are usually limited to specific areas
throughout a State. Environmental profiles provide an easily understandable
8-30
-------
TABLE 14. OUTLINE OF INPUT PARAMETERS, DATA TRANSFORMATIONS, AND
.... STATISTICAL COMPARISONS
•
""Individual ("raw") air quality data
All hourly concentration values
All daily concentration or "index" values
Maximum/minimum site values
Average/median site values
Quantiles by site
Individual emissions data
Process
Stack
Plant
Aggregate air quality data for given category
Maximum/minimum values " —
Average or median of maximum/minimum data values
Weighted average/median of averages/medians
Maximum/minimum quantiles (e.g., max all 90th percentiles)
Average/median quantile of like quantiles
Aggregate emissions data for given category
Maximum/minimum process
Maximum/minimum stack
Maximum/minimum plant
Average/median process
Average/median stack
Average/median plant
Counting summaries for given statistic
Number of sites, cities, counties, States, regions
Number of processes, stacks, plants, cities, etc.
Data transformations
Distributional (e.g., Weibull, logarithmic)
Regression
Analysis of variance (ANGYA)
Spectral analysis and smoothing techniques
Example statistical comparisons by site, geographic, and time categories
Total number of pollutant sites
Number of sites exceeding annual standard
Number of sites exceeding short-term standards
Counties with data
Counties exceeding standards
Days exceeding primary standard
PSI class distribution
Site averages by year
City averages by year
Counties (urban areas, etc.) with significant pollutant trends up,
down, no change
Emission estimates by major source category
Emission density vs. population and land use
8-31
-------
graphic summary of environmental status and trends, and solve the problem of
repetitive requests.
Air quality standards "violations" and trends on a pollutant/county or
urban areaT~basis (using colored maps) are the main tools of the RNEP effort.
The most common question—Where are the least polluted areas of the United
States?~has not been addressed directly in EPA reports because of the com-
plexity of issues regarding sufficiency, representativeness, and comparability
of data. However, profiles with an added impetus to incorporate the PSI will
at least indirectly address this issue.
Scientific and technical audiences may have stringent requirements for
level of data summary and documentation of the statistical' analysis techniques.
8.6 CAVEATS AND SUGGESTIONS
The following should be considered in planning graphics displays:
1. Descriptive or statistical parameters required?
2. Time to develop a summary from individual data?
3. Cost for preparation of graphics?
4. Data quality assured, valid, and carefully analyzed?
5. Proper emphasis on purpose of chart?
6. Chart not too light, heavy, confusing, complex?
7. Color/shading required?
8. Lettering styling and size appropriate?
9. Scale heights distorted?
10. Data gaps in chart treated correctly?
11. Too much gridding and/or lettering?
12. Grid units appropriate?
13. Grid points clearly identified?
14. Use of pictorial symbols and descriptive titles?
15. Chart self-explanatory?
8-32
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8.7 AVAILABLE PLOTTING RESOURCES
Graphic display packages are available at both the USEPA National Com-
. - - - 2 " • •
outer Center (NCC), Research Triangle Park, N.C., and the Washington Computer
Center (WCC) Washington, D.C. "Stand-alone" systems include Integrated Plotting
Package (IPP), Earvard Graphic, Tektronix, Calcomp, and Statistical Analysis Sys-
tem (SAS). Subroutines are available for user program interface under most of
these systems. Currently, statistical analysis and graphics programs developed
in some EPA Regional Offices are being documented for use by other regions;
these Include PSI, box-plot, and pollution/wind roses.
8.8 GUIDANCE FOR SELECTION OF CHARTS
No single standardized list of charts should be mandatory for displayins
aerometric data; however, the following steps should be used to guide the selec-
tion of the most relevant charts.
1. Will the audience be interested in technical details and require
follow-up documentation concerning both data base and data analysis
methodology? If so, individual data or tabular summary may be suf-
ficient. If graphics are needed, see steps 2-12 below.
2. Select the geographic scale of the summary: national, regional,
AQCR, SMSA, county, urban area, city, township, or monitoring
site/source.
3. Select concept to be charted: trend, current status, parameter(s)
vs. parameterU^v one parameter vs. several categories, composi-
tion of components, or maps.
4. Select time class: hour of day; day of week; month; calendar
quarter; season; year; or multiple year.
5. Select period of analysis: start year/month/day/hour and end year/
month/day/hour.
6. Select statistical summaries: individual, summation, or aggregation.
7. Select statistical analysis technique: descriptive statistics; dis-
tributional; regression; ANOVA; spectral analysis; or trend analysis.
8. Select site type, if desired: industrial, commercial, residential,
and so forth.
9. How can the analysis be accomplished? Manually (small data base),
hand calculator/computer, or large computer.
10. If a computer 1s necessary, are there statistical analysis and/or
graphics systems available? Check NCC, WCC, and Regional Office.
8-33
-------
11. Retrieve data according to selection criteria above.
12. In preparation of ..the chart, follow Section 8.7 caveats.
-8.9 SUMMARY AND RECOMMENDATIONS
This section discussed established data display techniques applicable to
aerometric measurements, and provided guidance for determining the formats most
suitable for the concepts to be displayed, the audience applicability, the in-
put data classification and analysis, and the plotting resources. The discus-
sion was limited to data resulting from the air monitoring and emissions inven-
tory processes. The purpose of such data is to provide quantitative insights
to help abate air pollution, manage natural resources, plan environmental
programs, and inform'the public.
The discussion did not consider topics such as sufficiency, representa-
tiveness, and data validity, and it assumed data to be efficiently accessible.
Since new statistical analysis techniques are covered in preceding sections,
this section discusses only analysis by currently available techniques.
Finally, the section did not attempt to standardize graphic formats; it
merely provided guidance and criteria, and gave example displays of suitable
data presentations. Graphics must accurately portray the data, help readers
understand the data, and help captivate interest. The guidance and criteria
in this section are not meant to stifle the innovation and creativity of
those preparing these artforas.
8.10 FUTURE ISSUES
Section 8 will be modified as new statistical techniques are used to
yield different parametric relationships and thus different graphics. Manda-
tory standardized analysis techniques may result in standardized computer
graphics programs. Questions to be addressed in the future are:
1. How stringent will USEPA be on data completeness and "representative--
ness"? Should we display quality assurance data? If so, should we
exclude source-impacted monitoring sites, or restrict analysis to
NAMS?
2. How can special "success stories," nonattainment status, or other
policy/regulatory issues be displayed in environmental assessment
documents? Should they be included?
3. Will population exposure analysis be used in future reports to-the
Administrator? Will population exposure software be easily used by
Regional Offices?
8-34
-------
4. How frequently will the RNEP's be published? How do the profiles
relate to the report to the Administrator, to Congress, and to the
National Air Quality and Emissions Trends Report"! Should the pro-
file format change from year to year and perhaps cover selected *
urban areas or regions in "off" years?
8.11 REFERENCES
1. Spear, Mary E. Practical Charting Techniques. McGraw-Hill, Inc., New
York, N.Y., 1969.
2. NCC User Reference Manual.
8-35
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9.0 CONTINUITY OF YEAR-TO-YEAR REPORTS
This section focuses on two major topics which can seriously affect the
continuity of data reported throughout time. First are changes in the opera-
tional definitions for measurements of pollutants and in the statistical in-
dicators or techniques. Second are shifts in the data base.
The discussion assumes that detailed data, as opposed to summary values,
will continue to be available from NAMS. It also assumes that as data needs
change with time, published reports will reflect the new priorities rather
than maintain format merely for historical continuity.
9.1 METHOD CHANGES
Data analysts preparing air quality reports should continually check
for changes in measurement techniques. These changes may require the adjust-
ment of the raw data for past years to maintain consistency in the data base.
The data base should not prevent the adoption of a new statistical indi-
cator (for example, a change from the median to the mean as an indicator of
the central tendency of a distribution). Availability of detailed data for
past years should make it possible to compute values of the new indicator for
data of the past. There should be no reason for presenting trend tables with
old indicator values for past years and new indicator values for the present
year. Similarly, introduction of a different statistical method should be
accompanied by.a presentation of its applicability to data of the past.
9.2 NAMS NETWORK CHANGES
•
The discussion above assumes that the number and location of monitors
providing data is held constant over the years for which the trend is studied.
However, the NAMS network will probably undergo many changes in years to come
as more is learned about the nature and effects of the various pollutants, as
funding levels change, and as source configurations are altered. If summari-
zation of data is carried out on the urban level (as recommended in Section 4
instead of by monitoring site, effects of changes in the network will be
9-1
-------
minimized. If an index of air quality is adopted, it is recommended that the
subset of NAMS used for index determination remain unchanged over a relatively
long period.
^_ There are a number of ways in which changes in the MAMS network could'oc-
cur; each would have a distinct effect on the continuity across years. In par-
ticular, there are three changes that could occur even if the subset of NAMS
used for index determination remains fixed.
1. The stations could be resited within an urban area,
2. The network in an urban area could be expanded, or
3. The network in an urban area could be contracted.
Effects of these changes can be minimized by the procedures given below,
A station should be resited only if there is hard evidence to justify it.
If resiting occurs, data from both the old and new sites should be gathered con-
currently for one year to firmly establish the differences between the two sites
and to assist in correcting any misleading conclusions formed using data from
the old site.
A change in location for a station used to report the maximum concentration
for an area should not affect the continuity of the data base; in fact, the maxi-^
mum monitoring site should be reviewed periodically to assure a reasonable ap-
proximation of the maximum concentration associated with the urban area.
It is difficult to foresee plausible reasons for resiting those stations
located according to the crittria of high population density and poor air quali-
ty, unless there is a considerable change in air quality patterns over the urban
area. In this case, the resulting "discontinuity" of the data base would re-
flect a discontinuity in the measured phenomenon and should be noted.
If the NAMS network in an urban area is expanded, past values of indices
and trend analyses can be adjusted by relating concurrent values from the old
network stations to those from the new combined network.
If the NAMS network in an urban area is contracted, all indices and trend
computations for past years should be redone using only the data from the small-
er network.
9-2
-------
TECHNICAL REPORT DATA
(Please read Imumctions on the rc*ene be fan completing)
i. REPORT NO.
EPA-450-4/81-015
. RECIPIENT'S ACCESSIO»*NO.
February 1981
A. TITLE AND SUBTITLE
U.S. Environmental Protection Agency
Lntra-Agenc^JTask Force Report on Air Quality Indicators
5. REPORT DATE
6. PERFORMING ORGANIZATION CODE
7. AUTMORtS)
J.F. Hunt, Jr., (Chairman), G. Akland, W. Cox, T. Curran
L Frank, S. Goranson, P. Ross. H. Sauls and J. Suaas
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
J.S. Environmental Protection Agency
Dffices of: Air, Noise and Radiation, Research and
Development and Planning and Management
EPA Region 5
10. PROGRAM ELEMENT NO.
ILCONfRAfirVGRANTNO.
12. SPONSORING AGENCY NAME AND ADDRESS
13. TYPE Of REPORT AND PERlfiO COVERED
J.S. Environmental Protection Agency
)ffice of Air, Noise and Radiation
Dffice of Air Quality Planning and Standards
Research Triangle Park, N.C. 27711
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
The Intra-Agency Task Force on Air Quality Indicators was established to recommend
standardized air quality indicators and statistical methodologies for presenting air
quality status and trends in national publications. This report summarizes the
•ecommendations of the Task Force grouped into four categories: data base, data analysi
Jata interpretation and data presentation. The report includes the position papers
)repared by the Task Force members dealing with precision and accuracy data, detecting
nd removing outliers, area of coverage and representativeness, data completeness and
listorical continuity, statistical indicators and trend techniques, inference and
:onclusion, data presentation, and continuity of year-to-year reports.
7.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
ntra-Agency Task Force on Ai
ir Quality Indicators
tatistical Methodologies
Jata Base
Jata Analysis .
Jata Interpretation
)ata Presentation
'recislon and Arrnrary Hata
r Quality Indieitors
Outliers
Representativeness.
Data Completeness
Statistical Indicators
Trend Techniqu
Continuity of
*ar-to-year reports
18. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (This Report)
Unclassified
21. NO. OF PAGES
20. SECURITY CLASS
Unclassified
22. PRICE
CPA Perm 222O-1 (»>73)
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5251
-------
EPA-454/B-93/051
Appendix K
Revision No. 0
Date: March 1994
Page K-l
APPENDIX K
SAMPLE OUTPUTS FROM AIRS GRAPHICS
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-------
EPA-454/B-93/051
Appendix L
Revision No. 0
Date: March 1994
Page L-l
APPENDIX L
BIBLIOGRAPHY
-------
EPA-454/B-93/051
Appendix L
Revision No. 0
Date: March 1994
Page L-2
BIBLIOGRAPHY
1. AIRS Users Guide, Volume AQ2, "Air Quality Data Coding," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, 1993.
2. AIRS Users Guide, Volume AQ3, "Air Quality Data Storage," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, 1993.
3. AIRS Users Guide, Volume AQ4, "Air Quality Data Retrieval," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, 1993.
4. AIRS Users Guide, Volume AQ5, "AIRS Ad Hoc Retrieval," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, 1993.
5. Ambient Monitoring Guidelines for Prevention of Significant Deterioration (PSD), EPA-450/4-87-
007, U.S. Environmental Protection Agency, Research Triangle Park, May 1987.
6. Berg, Neil J., et al., Enhanced Ozone Monitoring Network Design and Siting Criteria Guidance
Document, EPA-450/4-91-033, U.S. Environmental Protection Agency, Research Triangle Park,
North Carolina, November 1991.
7. Clean Air Act Ozone Design Value Study, Preliminary Draft, U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, April 1993.
8. Code of Federal Regulations, Title 40, Part 50, U.S. Government Printing Office, 1992.
9. Code of Federal Regulations, Title 40, Part 51, U.S. Government Printing Office, 1992.
10. Code of Federal Regulations, Tide 40, Part 53, U.S. Government Printing Office, 1992.
11. Code of Federal Regulations, Title 40, Part 58, U.S. Government Printing Office, 1992.
12. Cox, William M. and Shao-Hang Chu, "Meteorologically Adjusted Ozone Trends in Urban Areas:
A Probabilistic Approach," Tropospheric Ozone and the Environment II, Air and Waste
Management Association, Pittsburgh, Pennsylvania, 1992.
-------
EPA-454/B-93/051
Appendix L
Revision No. 0
Date: March 1994
Page L-3
13. Criteria For Assessing The Role of Transported Ozone/Precursors in Ozone Nonattainment
Areas, EPA-450/4-91-015, U.S. Environmental Protection Agency, Research Triangle Park, North
Carolina, May 1991.
14. Dorosz-Stargardt, Geri, "Initial Implementation of the Photochemical Assessment Monitoring
Stations (PAMS) Network," U.S. Environmental Protection Agency, Research Triangle Park,
North Carolina, 1993.
15. Federal Register, (57 FR 7687), "Ambient Air Quality Surveillance - Proposed Rule," March 4,
1992.
16. Federal Register, (58 FR 8452), "Ambient Air Quality Surveillance - Final Rule," February 12,
1993.
17. Gerald, Nash O., William F. Hunt, Jr., Geri Dorosz-Stargardt, and Neil H. Frank, "Requirements
for the Establishment of Enhanced Ozone Monitoring Networks," presented at the Air and Waste
Management/EPA Symposium "Measurement of Toxic and Related Air Pollutants," Durham,
North Carolina, May 4-7, 1993.
18. "Guidance for the Development and Approval of Photochemical Assessment Monitoring Stations
• Network Plans," Preliminary Draft, U.S. Environmental Protection Agency, Research Triangle
Park, North Carolina, June 1993.
19. Guideline for the Implementation of the Ambient Air Monitoring Regulations 40 CFR Part 58,
EPA-450/4-79-038, U.S. Environmental Protection Agency, Research Triangle Park, North
Carolina, November 1979.
20. Guideline for the Interpretation of Ozone Air Quality Standards, EPA-450/4-79-003, U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina, January 1979.
21. "Guideline on Modification to Monitoring Seasons for Ozone," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, March 1990.
22. Hunt, William F., Jr. and Nash O. Gerald, "The Enhanced Ozone Monitoring Network Required
by the New Clean Air Act Amendments," 91-160.3, Air and Waste Management Association,
Vancouver, 1991.
-------
EPA-454/B-93/051
Appendix L
Revision No. 0
Date: March 1994
Page L-4
23. Koutrakis, Petros, Jack M. Wolfson, Arnold Bunyaviroch, Susan E. Froehlich, Koichiro Hirano,
and James D. Mulik, "Measurement of Ambient Ozone Using a Nitrite-Coated Filter," Analytical
Chemistry, Vol. 65, 1993.
24. Lewis, Charles W. and Teri L. Conner, "Source Reconciliation of Ambient Volatile Organic
Compounds Measured in the Atlanta 1990 Summer Study: The Mobile Source Component," U.S.
Environmental Protection Agency, Atmospheric Research and Exposure Assessment Laboratory,
Research Triangle Park, North Carolina, September 1991.
25. "List of Designated Reference and Equivalent Methods," U.S. Environmental Protection Agency,
Atmospheric Research and Exposure Assessment Laboratory, Research Triangle Park, North
Carolina, November 12, 1993.
26. Liu, L.-J. Sally, Petros Koutrakis, Helen H. Suh, James D. Mulik, and Robert M. Burton, "Use
of Personal Measurements for Ozone Exposure Assessment: A Pilot Study," "Environmental
Health Perspectives," Journal of the National Institute of Environmental Health Sciences, Vol.
101, No. 4, September 1993.
27. Ludwig, F.L. and E. Shelar, Site Selection for the Monitoring of Photochemical Air Pollutants,
EPA-450/3-78-013, U.S. Environmental Protection Agency, Research Triangle Park, North
Carolina, April 1978.
28. McClenney, William A., "Instrumentation to Meet Requirements for Measurement of Ozone
Precursor Hydrocarbons in the U.S.A.," U.S. Environmental Protection Agency, Atmospheric
Research and Exposure Assessment Laboratory, Research Triangle Park, North Carolina, 1993.
29. Mulik, James D., Jerry L. Vams, Petros Koutrakis, Mike Wolfson, Dennis Williams, William
Ellenson, and Keith Kronmiller, "The Passive Sampling Device as a Simple Tool for Assessing
Ecological Change - An Extended Monitoring Study in Ambient Air," presented at the
Measurement of Toxic and Related Air Pollutants symposium, Durham, North Carolina, May
1992.
30. On-Site Meteorological Instrumentation Requirements to Characterize Diffusion from Point
Sources, EPA-600/9-81-020, U.S. Environmental Protection Agency,-Research Triangle Park,
North Carolina, 1981.
31. On-Site Meteorological Program Guidance for Regulatory Modeling Applications, EPA-450/4-87-
013, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, 1987.
-------
EPA^54/B-93/051
Appendix L
. ; Revision No. 0
Date: March 1994
Page L-5
32. "Ozone and Carbon Monoxide Areas Designated Nonattainment," U.S. Environmental Protection
Agency, Research Triangle Park, North Carolina, October 26, 1991.
33. Purdue, Larry J., "Continuous Monitoring of VOC Precursors," presented at the VOC Workshop
Assessment and Evaluation, Amersfoort, The Netherlands, January 26-27, 1993.
34. Purdue, Larry J., "Summer 1990 Atlanta Ozone Precursor Study," presented at the VOC
Workshop Assessment and Evaluation, Amersfoort, The Netherlands, January 26-28, 1993.
35. Purdue, Larry J., Dave-Paul Dayton, Joann Rice and Joan Bursey, Technical Assistance Document
for Sampling and Analysis of Ozone Precursors, EPA-600/8-91-215, U.S. Environmental
Protection Agency, Atmospheric Research and Exposure Assessment Laboratory, Research
Triangle Park, North Carolina, October 1991.
36. Purdue, Larry J., J. A. Reagan, W. A. Lonneman, T. C. Lawless, R. J. Drago, G. Zalaquet, M.
Holdren, D. Smith, C. Spicer and A. Pate, Atlanta Ozone Precursor Monitoring Study, U.S.
Environmental Protection Agency, Atmospheric Research and Exposure Assessment Laboratory,
Research Triangle Park, North Carolina, April 3, 1992.
37. Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV:
Meteorological Measurements, EPA-600/4-82-060, U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina, 1989.
38. Rethinking The Ozone Problem In Urban And Regional Air Pollution, National Research Council,
National Academy Press, Washington, D.C., 1991.
39. Rice, Joann and Dave-Paul Dayton, Enhanced Ozone Monitoring Methodology Evaluation, Radian
Corporation, Research Triangle Park, North Carolina, October 1992.
40. The Role of Ozone Precursors in Tropospheric Ozone Formation and Control, "A Report to
Congress," EPA-454/R-93-024, U.S. Environmental Protection Agency, Research Triangle Park,
North Carolina, July 1993.
41. Schweiss, Jon, "Draft Guidance for the Use of Portable Samplers," U.S. Environmental Protection
Agency, Seattle, Washington, February 1991.
42. Screening Procedures for Estimating the Air Quality Impact of Stationary Sources, Revised, EPA-
454/R-92-019, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina,
October 1992.
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EPA-454/B-93/051
Appendix L
Revision No. 0
Date: March 1994
Page L-6
43. Shao-Hang Chu, "Meteorological Considerations in Siting Monitors of Photochemical Pollutants,"
presented at the Regional Photochemical Measurement and Modeling Study Conference, San
Diego, California, November 1993.
44. Technical Support for Enhanced Air Quality Modeling Analysis for the Purpose of Development
of the 1994 Ozone State Implementation Plan Guidance, U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina, Draft, April 1993.
-------
TECHNICAL REPORT DATA
(Please read taUructions on the reverse before completing)
1. REPORT NO
EPA-454/B-93-051
2.
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
Photochemical Assessment Monitoring Stations
Implementation Manual
5. REPORT DATE
March 1994
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
TRC Environmental Corporation
Chapel Hill, NC
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
EPA Contract 68D30029
12. SPONSORING AGENCY NAME AND ADDRESS
13. TYPE OF REPORT AND PERIOD COVERED
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Technical Support Division, Monitoring & Reports Branch
Research Triangle Par, NC 27711
Final Report
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
EPA Work Assignment Manager: N. 0. Gerald
16. ABSTRACT
This document is designed to familiarize State and local air authorities with
the Photochemical Assessment Monitoring Stations (PAMS) program and to provide
guidance for designing PAMS monitoring networks. The document provides an
explanation of the requirements of 40 CFR 58 pertaining to PAMS, specific
guidance on network design and monitor siting, operational requirements, planning
and approval processes, and data storage and communications systems.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
Ambient Air Monitoring
Photochemical Assessment Monitoring
Stations (PAMS)
Air Toxics Monitoring
18. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (This Report)
Unclassified
21. NO. OF PAGES
548
20. SECURITY CLASS (This page)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
------- |