-------
CONTENTS
Abstract iii
Figures vill
Tables ix
1. Introduction 1
Organization of the Report 3
2. Overview of Guidelines 4
Counties With Detailed Growth Analysis 4
Counties With Less Detailed Analysis 7
Counties Without an Analysis of Projected Air Quality But
With Monitoring of Air Quality 7
Counties Without an Analysis of Projected Air Quality
and Without Monitoring 9
Carbon Monoxide 11
References 13
3. Relationship of Guidelines to Other Air Quality Planning
Programs 14
Stationary Source Emission Surveillance 14
Preconstruction Review of New Stationary Sources 15
Prevention of Significant Deterioration 16
Motor Vehicle Source Surveillance 16
Consistency Review of Transportation Plans 17
Indirect Source Review 18
References 19
4. Guidelines for Implementing 40 CFR 51.12(h) 21
Definitions 21
Timing 22
Particulate Matter and Sulfur Oxides - Counties Without
Monitoring (Category 1) 23
Particulate Matter and Sulfur Oxides - Counties With
Monitoring (Category 2) 25
Particulate Matter and Sulfur Oxides - Counties With Con-
densed Analysis (Category 3) 27
Particulate Matter and Sulfur Oxides - Counties With De-
tailed Analysis (Category 4) 30
Carbon Monoxide - Counties With Detailed Analysis .... 31
Carbon Monoxide - Counties Without Detailed Analysis. . . 31
Oxidants - AQCRs Without Monitoring (Category 1) 33
Oxidants - AQCRs With Monitoring (Category 2) 36
Oxidants - AQCRs With Condensed Analysis (Category 3) . . 37
Oxidants - AQCRs With Detailed Analysis (Category 4)... 39
-------
CONTENTS (continued)
Nitrogen Oxides - Counties Without Monitoring
(Category 1) 40
Nitrogen Oxides - Counties With Monitoring (Category 2). 41
Nitrogen Oxides - Counties With Condensed Analysis
(Category 3) 43
Nitrogen Oxides - Counties With Detailed Analysis
(Category 4) 45
References 46
5. Illustration of Guidelines in Wisconsin 47
Summary 47
TSP and SOX 50
Oxidants 54
Nitrogen Oxides 56
Time Requirements 61
6. Illustration of Guidelines in Massachusetts 62
Summary 62
S02 and TSP 64
Oxidants 66
N02 68
CO 68
Time Requirements 70
Appendixes
A. Screening Methods for Projecting Emissions and Air Quality. . 71
Methods for Projecting Emissions 71
Modeling Air Quality Concentrations 74
B. Sources of Data 78
Parameters to Be Used in Counties With Detailed Analysis 78
Typical Sources of Data Items 82
Detailed Description of Prominent Sources 83
References 106
C. Geographic Information Systems 107
Introduction 107
Preliminary Reviews 110
New York State Land Use and Natural Resource Inventory . 118
Maryland Automated Geographic Information System .... 119
The Fairfax County Urban Development Information System. 120
Land-Use Mapping by Remote Sensing Techniques 121
Summary 123
References 124
D. Overview of the Process for Control of CO Hot Spots 128
Step 1: Preliminary Screening 128
Step 2: Verification Screening 128
Step 3: Detailed Modeling 128
Step 4: Identification of Alternative Improvements . . 128
vi
-------
CONTENTS (continued)
Step 5: Evaluation of Alternatives 130
Step 6: Selection of Control Measures 130
Step 7: Implementation 130
Step 8: Evaluation 130
Hot Spot Screening Guidelines . . . 130
References 132
E. Basis of Tables 1 and 2 133
vii
-------
FIGURES
Number Page
1 Schematic Diagram of Guideline Procedures With an Existing
Detailed Analysis of Growth 6
Schematic Diagram of Guideline Procedures for Areas With
an Existing Condensed Analysis of Growth
3 Schematic Diagram of Guideline Procedures for Areas Without
Analysis of Growth but With Monitoring 10
4 Schematic Diagram of Guideline Procedures for Areas Without
Monitoring 12
5 Comparison of Estimated Current Year Emissions With that
Forecast in the Condensed Analysis 28
D-l Decision-Making Process for Selection of CO Control Measures . . 129
viii
-------
TABLES
Number Page
1 Critical Gasoline Sales Density to Exceed 75 Percent of the
Hydrocarbon Standard 34
2 Critical VMT Density to Exceed 75 Percent of the Hydrocarbon
Standard 35
3 Initial Inclusion/Exclusion Summary 48
4 Air Quality Projections 49
5 Category 1 Analyses for TSP and S02 (Step 1) 51
6 Category 1 Analyses for TSP and SO (Step 2) 52
X
7 Category 2 Analyses for TSP and SO 53
8 Category 3 Analyses for TSP and SO 55
9 Category 1 Analyses for Oxidants 57
10 Category 2 Analyses for Oxidants 58
11 Category 3 Analyses for Oxidants 59
12 Category 2 Analyses for NO- 60
13 Categorization of Massachusetts Counties for Growth Monitoring
Analyses 63
14 Category 4 Analyses for TSP and SO 65
15 Comparison of 1972-1985 Projections 67
16 Oxidant Data and Calculation Results for Category 2 Counties in
Massachusetts 69
17 Category 2 Analyses for N0_ 69
IX
-------
TABLES (continued)
Number Page
A-l Emission Factor Ratios 73
B-l Typical Projection Parameters 79
B-2 Recommended Growth Tracking Indicators 81
B-3 Vehicle Mile Data Available in 1973 84
B-4 Contacts County Sales of Gasoline Data 87
B-5 Summary of National and Commercial Data Sources 88
B-6 Content of 1960 and 1970 Census 92
B-7 Federal-State Co-Op Program Contacts 94
B-8 Categories of Nonresidential Construction 100
B-9 Summary of Proposed Data Elements for the Urban Transportation
Reporting System 102
B-10 State Project Review Data Sources 104
C-l USGS Land Use and Land Cover Classification System
Characteristics 109
C-2 Selected Geographic Information System Characteristics .... Ill
C-3 Land-Use Coding Techniques 112
C-4 Uses of LUNR Inventory Products According to Types of
Respondents 114
-------
SECTION 1
INTRODUCTION
The U.S. Environmental Protection Agency regulations issued under section
301(a) of the Clean Air Act, Part 51 - Requirements for Preparation, Adoption,
and Submittal of Implementation Plans require that:
51.12 (h) (1). For all areas of the State, the State Implementation
Plan shall, by May 3, 1978, provide for a procedure for the continual
acquisition of information used in projecting emissions.
(2). The plan shall provide that at intervals of no more than 5 years,
all areas of the State shall be assessed to determine if any areas are
in need of plan revisions.
(3). The State shall retain the data gathered and the written assessment
made under paragraphs (h)(1) and (h)(2) of this section, and make them
available for public inspection and submit them to the Administrator at
his request.
(4). The State shall notify the Administrator if an area is undergoing
an amount of development such that it presents the potential for a
violation of national standards within a period of 20 years.
The goal of this report is to provide information useful to agencies
responsible for the development and use of a procedure for implementing these
regulations. The objective of the procedures described in the following pages
is to enable the identification of those areas where increases in emissions
may cause the national ambient air quality standards (NAAQS) to be violated.
The procedures described in this report should be viewed as a typical
approach to fulfilling the requirements of the cited regulations. The spe-
cific concerns and unique situations in every state or region may dictate
greater emphasis and a more detailed analysis in certain areas. For example,
areas with the potential of very rapid growth due to the proposed development
of a large energy facility can be more adequately assessed for the potential
of an NAAQS violation by a specific environmental assessment and, subsequently,
the tracking of actual growth versus that projected in the assessment. More-
over, for some areas the procedures outlined in this report may be invalid.
The procedures described below are based on air quality planning techniques
familiar to every state air pollution agency. Thus, the state agency should
be able to assess the validity of this approach in the context of their state
and their approach to previous air quality planning programs and modify it
-------
as necessary. The procedures are not intended to be a detailed analysis of
the air quality problem in an area; rather, they are intended to be a screen-
ing tool to identify potential problem areas for more detailed analysis.
The procedures outlined below are designed to be applied in stages. Only
a small amount of information is initially acquired. If that information
does not indicate a potential violation of standards, then nothing else need
to be done. Thus, many areas will only collect growth data on a regular
periodic basis and do nothing else. If the information suggests the possibi-
lity of emissions growth sufficient to violate the NAAQSs, additional infor-
mation is acquired. This may be additional analysis, the acquisition of more
detailed growth information, or the initiation of ambient air monitoring.
This analysis process continues to the point wherein the last stage, a detailed
analysis, as described in subpart D of the regulations, is conducted.
The procedures outlined below are also modular in nature. The nature
of the existing data bases, agency resources, and the current State Implemen-
tation Plan (SIP) will vary among states and areas of the state.
Some areas have been identified as having problems in maintaining NAAQSs,
once attained. This was determined through AQMA designation analysis and sub-
sequent analysis. This analysis included a detailed projection of emissions
and modeling of air quality. For these areas, the objective of the guidelines
is to determine if, in light of experienced growth and revised growth projec-
tions, the SIP is still adequate for maintaining the NAAQSs.
Other areas will not have conducted an analysis of potential future vio-
lations. The objective of the guidelines in these areas is to identify the
point when expected growth may threaten an NAAQS and when a detailed analysis
should be conducted. Further distinctions are made below between areas with
and without air quality monitoring and between the level of detail of the anal-
ysis of potential future violations (where it has been conducted). Different
procedures are outlined for each pollutant.
The growth tracking procedures should be performed on a frequent and peri-
odic basis. The reassessment of the potential of a NAAQS violation should be
performed at least once every 5 years. In the intervening years, current
growth estimates and projections are acquired and compared with the previous
projections. The frequency with which this is done would depend on the kind
of data used and how often it is updated, and the amount of growth occurring in
a county. If, for example, revised projections are available annually or bi-
anually, the use of the tracking procedures could be linked to the publications
of new projections. If current estimates of growth are utilized (with their
inevitable 6- to 18-month lag), it seems prudent for this to be done annually,
especially if it is a rapidly growing area.
Detailed emission projection and simulation modeling of future air quality,
as specified in Part 51, Appendix D and generally described in Volumes 7,
12 and 13 of the Guidelines for Air Quality Maintenance Planning and Analysis.
-------
The process of tracking growth trends and assessing their implications
on ambient air quality levels should be viewed as an information gathering
process which allows one to continually refine the assessment of the air
quality problem in an area. It should be part of an anticipatory planning
process whereby future air quality problems are identified before they are
critical so there is both time to assess the problem and develop or refine
a control strategy. It is the antithesis of a reactive process where incom-
plete information and limited time preclude the development of a comprehensive
approach to the problem and where recent events may limit the usefulness or
availability of the most effective control strategies. It can be a tool for
incorporating the air quality planning program with the plans and programs of
the other planning functions in a state; e.g., land use, economic, transpor-
tation, and water quality planning, among others.
ORGANIZATION OF THE REPORT
Section 2 presents a detailed introduction to the guidelines and their
technical background. Section 3 summarizes the relationship between the
subject of this report and other air quality planning programs that monitor
growth and its impact on air quality. The guidelines are presented in
Section 4. Finally, in Sections 5 and 6, the guidelines are illustrated by
application to two States, Wisconsin and Massachusetts. There are several
appendices. Appendix A is a suggested condensed emission projection and air
quality simulation technique that may be used to further define the air
quality impacts of growth before resorting to a detailed analysis such as
that required by subpart D. Appendix B is a description of the sources of
data required by the guidelines. Appendix C is a summary of existing geogra-
phic information systems; i.e., spatially defined data files and analysis and
presentation techniques. Where such systems currently exist, they may be used
to monitor growth for the purposes of maintaining air quality. In addition,
the rapidly advancing state-of-the-art in remote sensing, especially satellite
imagery, suggests that such techniques may find wide application for growth
tracking in the future. Appendix D is an overview of the planning procedure
for the control of CO hot spots. Appendix E describes the basis of certain
tables in Section 4.
-------
SECTION 2
OVERVIEW OF GUIDELINES
The basic area considered in these guidelines is the county. This is
due principally to the general lack of availability of growth indicators for
smaller areas. If indicators are available, a smaller geographical unit may
be used. For oxidants, the AQCR is used as the basic geographical unit.
In the suggested procedures, counties with an existing detailed analysis
of the effects of emissions growth on air quality acquire current estimates or
projections of population, employment, or other appropriate indicators on a
regular and periodic basis. If the growth in any of the selected indicators is
beginning to significantly exceed the projections in the SIP, a more detailed
analysis of emissions growth is required. If this growth is in excess of that
projected in the SIP, a definite potential for violating NAAQS may exist. At
this point, the existing subpart D analysis is revised to reflect the growth
rate experienced to date and to incorporate new projections. Regardless of
experienced growth, the subpart D analysis must be revised at least every 5
years to incorporate new 10-year projections of growth indicators.
Counties without a detailed analysis of projected air quality acquire
current estimates or projections of population or other readily available
parameters on a regular and periodic basis. If the growth rates or absolute
values of these parameters exceed certain threshold values, a simplified anal-
ysis of projected air quality (a modification of the AQMA designation analysis)
is conducted. If this analysis indicates the potential for the violation of an
NAAQS exists, a subpart D analysis of projected air quality is recommended.
In the remainder of this section, the guidelines are explained in more
detail and the assumptions and limitations cited. Geographic areas of anal-
ysis for all pollutants except CO are delineated into four categories:
(1) those with an existing detailed projection of emissions and simulation
of air quality (such as that required in subpart D of the SIP regulations,
the AQMA analysis), (2) those with a less detailed or condensed analysis of
projected air quality, (3) those with no current analysis of projected air
quality but with air quality monitoring for the pollutant of concern, and
(4) those without an anlaysis and without monitoring. The guidelines for
carbon monoxide (CO) are explained separately below.
COUNTIES WITH DETAILED GROWTH ANALYSIS
A detailed projection of emissions and simulation of air quality will
have been prepared for many counties, most often as part of a nonattainment
study or in preparation of an AQMA plan. Detailed projection and simulation
-------
are defined, for the purposes of this report, as the procedures outlined in
subpart D of the SIP regulations,1 and generally described in Volumes 7, 12,
and 13 of the AQMA guidelines.2 ^ Typically, a new or updated county area
source emission inventory would be prepared, the point source inventory may
have been validated, and the emission inventory would be projected by using
population and employment forecasts or other growth indicators. The particu-
late matter and sulfur oxide emission inventories would typically be allocated
to a subcounty grid system and modeled using the Air Quality Display Model
(AQDM). The hydrocarbon and nitrogen oxide emission inventories probably
would not have been allocated and air quality would be modeled using, respec-
tively, Appendix J and linear rollback. The outcome of this process will be
either a determination that the NAAQSs will not be violated or that they will,
in which case control strategies will be developed and implemented.
If population or employment growth (or whatever else was used to project
emissions) does not exceed the forecast amount for which control strategies
have been developed, theoretically one can assume that the nitrogen oxide and
oxidant NAAQSs will not be violated. The guidelines in this report recommend
a collection of the estimated value of the parameters used to project emis-
sions and a comparison with the forecast value. A schematic diagram of the
guidelines is shown in Figure 1. If all the parameters are less than forecast,
no further action is recommended. If one or more of the parameters is greater
than forecast (when more than one parameter was used to project emissions),
a rough estimate of the county emissions is prepared. This is compared with
the forecast emissions for the year the analysis is being conducted. If the
current estimate of emissions is greater than forecast, the next step is to
reassess the validity of the forecasted value of the projection parameters
for the final year of the detailed growth analysis. (For example, assume a
1975 emission inventory was projected to 1985 using population and employment.
In 1978 current estimates of population, employment, and emissions are in
excess of what was forecasted for 1978. One must now reassess the validity
of the forecasted values of population and employment for 1985.) If indeed
the forecasts of the emission projection parameters are invalid, the emission
The guidelines for particulate matter and sulfur oxides follow the same pro-
cedure as that outlined above for nitrogen oxides and oxidants. However, the
growth in the emission projection parameters may be less than forecast and the
NAAQSs may still be violated if the growth occurs in a portion of the county
where it was unanticipated when the subcounty allocation was performed. To an
extent this is also true of growth in hydrocarbon and nitrogen oxide emission
inventories even though the detailed emission projection and simulation model-
ing techniques are insensitive to the location of emissions growth within a
county. It is assumed that this situation will not be so severe as to violate
the NAAQSs within the 5-year time period between the preparation of new sub-
county inventories. Since all new major sources will be subject to the new
source review process, this assumption is considered to be reasonable. State
or local agencies not willing to make this assumption would then need to keep
track of growth on a subcounty basis and maintain a source-receptor file of
coefficients to continually assess the effects of both the amount and location
of growth on ambient air quality. The availability of information systems for
doing so is discussed in Appendix C.
-------
COLLECTION OF
CURRENT ESTIMATES
OE CROWTH PARAMETERS
PREPARE NEW FORECAST
OF GROWTH PARAMETERS
FOR LAST YEAR OF SIP
Figure 1. Schematic diagram of guideline procedures with an existing
detailed analysis of growth.
-------
projection and air quality simulation should be revised. Notwithstanding the
results of the process described above, the detailed projection of emissions
should be revised at least every 5 years.
COUNTIES WITH LESS DETAILED ANALYSIS
Growth trends and projected ambient air quality may have been analyzed
in some counties with less detail than the process outlined in subpart D.
For example, this analysis may have been conducted as part of the AQMA desig-
nation analysis. This condensed analysis will most often consist of an update
and projection of the county emission inventory using population, total em-
ployment (or earnings), and manufacturing employment (or earnings). No sub-
county allocation of emissions will have been performed. Air quality will
have been forecasted using linear roll-forward, Hanna-Gifford, or Miller-
Holtzworth and, in the dase of oxidants, Appendix J.
The procedures suggested in this guideline for this type of county, shown
in Figure 2, are very similar to the guideline for counties with a detailed
growth analysis. The principal difference is that instead of comparing current
estimates of growth parameters with the values forecasted in the subpart D
analysis, they are compared with the values for these parameters forecast in
the simpler growth analysis that was conducted. Counties for which frequent
revisions of demographic and economic projections are made may simply compare
the new projections with the old projections instead of keeping track of
current estimates. Again, the potential of a future violation of an NAAQS
must be reassessed at least every 5 years. Therefore, the condensed analysis
should be revised at least every 5 years.* If this analysis indicates a po-
tential violation, the EPA administrator should be notified.
COUNTIES WITHOUT AN ANALYSIS OF PROJECTED AIR QUALITY BUT WITH MONITORING
OF AIR QUALITY
In many counties no projection of future air quality will have been con-
ducted. Those that do have monitoring for the pollutant of interest are
considered in this subsection while those that do not are considered in the
subsequent subsection.
Despite the fact that no analysis has been conducted, the data necessary
to do at least a condensed analysis does exist - it remains to be collected
and analyzed. The objective of the guidelines in this instance is to suggest
a methodology that entials the minimal collection of data necess'ary to iden-
tify areas where the threat of a potential future violation of the NAAQSs is
great enough that a condensed analysis of projected air quality is warranted.
One of the simplest air quality simulation techniques is linear roll-forward.
*
A suggested procedure for conducting such an analysis is described in Appen-
dix A.
-------
FREQUENT REVISIONS
OF (,ROWTH
PROJECTIONS AVAILABLE
COLLECT-TON OF
REVISED PRO H'.CTIONS
COLLEt TION OF CUk.,,,M'
[STTNATES OF CROW, i
1'ARAME'I KRS
1
NO
PREPARE NRW FORECAST OF
GROWTH PARAMETERS FOR
LAST YEAR OF FORECAST
PERIOD
REVISE THE GROWTH ANALYSIS
(APPENDIX A)
Figure 2. Schematic diagram of guideline procedures for areas
with an existing condensed analysis of growth.
-------
This technique is utilized with a crude but conservative 10-year forecast of
emissions to identify areas where additional anlaysis is recommended to assess
the potential of a violation of an NAAQS. This methodology is admittedly sub-
ject to error; i.e., the situation where no violation is indicated in 10 years,
but a more sophisticated analysis would indicate such a violation.
There are two types of error that are of concern. First, the situation
where a violation will occur in 10 years at the monitoring site. This situa-
tion is not troublesome, as the potential of a violation will eventually be
indicated as the analysis (linear roll-forward) is reconducted in subsequent
years. The second type of error is where the violation will occur somewhere
else in the region; i.e., not at the monitoring station. This situation can
only be discovered through the subcounty allocation of emissions and the use
of a regional simulation model such as AQDM. State agency personnel perform-
ing the analysis should be aware of this limitation and in situations where
the monitoring station is unrepresentative, take appropriate action. Note
that to the extent new major sources contribute to the violation, the new
source review program will help to identify the locations in the county where
ambient concentrations are higher than at the monitoring stations.
An schematic diagram of the guideline procedures is shown in Figure 3.
The procedure is straightforward. Every 5 years a linear roll-forward pro-
jection of air quality is made (described in detail in Section IV). In the
intervening years, current estimates or new projections of population and em-
ployment are collected. If the current estimates or projections are greater
than previous values, a new linear roll-forward must be executed. If the 10-
year linear roll-forward forecast of air quality exceeds an NAAQS, a con-
densed analysis of growth and air quality is prepared (described in Appendix A).
COUNTIES WITHOUT AN ANALYSIS OF PROJECTED AIR QUALITY AND WITHOUT MONITORING
Some counties will have no existing air quality data base and no analysis
of growth. Since an accurate determination of the potential of a future vio-
lation of an NAAQS requires monitoring and since monitoring is prudent before
a SIP revision is called for, the objective of the guidelines for counties in
this category is the identification of when monitoring should begin.
Threshold levels of population, employment, and other economic indicators
are identified, above which there is a substantial possibility that a violation
of an NAAQS may occur in the future. Once a threshold has been exceeded, a
condensed analysis of growth and air quality (described in Appendix A) is re-
commended for particulate matter or sulfur oxides. If the condensed analysis
indicates a potential violation, the guidelines recommend initiating monitoring.
Since the air quality simulation procedures in the condensed analysis for
*
It is conservative in that emission reductions at existing sources are not
considered. If a linear roll-forward projections of air quality indicates a
potential NAAQS violation, the next step recommended in the guidelines is
essentially repeating the roll-forward analysis with an emission projection
that does consider the future emission reductions.
-------
COLIECTTON OF CURRENT
ESTIMATES OF GROWIII
INDICATORS
FREQUENT REVISIONS
OF GROWTH
KOJECriONS AVAILABLE
COLLECTION OF NEW
PROJECTIONS
COLLECTION OK
NEW PROJECTIONS
PROJECT AIR QUALI1Y
USING LINEAR
ROLL-FORWARD
POTENT[AL NAAOS
VIOLATION
PREPARE A CONDLNSEE
ANALYSIS OF GROWTH
(APPENDIX A)
POTENTIAL NAAQS
VIOLA!ION
NOTIFY THE EPA ADMINISTRATOR
Figure 3. Schematic diagram of guideline procedures for areas
without analysis of growth but with monitoring.
10
-------
nitrogen oxides and oxidants (roll-forward and Appendix J, respectively) re-
quire an air quality baseline concentration, the guidelines recommend ini-
tiating monitoring for these pollutants once the thresholds have been exceeded.
A schematic diagram of this process is shown in Figure 4.
CARBON MONOXIDE
Some counties will have had a detailed analysis of growth and air quality
prepared. Typically, CO will have been modeled at existing monitoring stations
by rollback based on projected regional vehicles miles traveled (VMT). A de-
tailed projection of average daily traffic (ADT) on major traffic links, in
conjunction with area source estimates of VMT on local streets and CO emis-
sions from stationary sources may have been made. Projected CO concentrations
will then have been modeled using APRAC-la5 or a combination of HIWAY6 and
Hanna-Gifford.7 While such procedures have limitations in identifying lo-
calized CO violations, for the purposes of these guidelines, they are assumed
to be sufficiently accurate. Thus, the recommended guideline for counties
with a detailed CO analysis is similar to the procedures for counties with a
detailed analysis for other pollutants; i.e., the annual collection of the
current estimates of the indicators used to project emissions and comparison
with their forecasted value.
Most counties will not have had a detailed analysis conducted recently.
The annual consistency review of transportation plans in urbanized areas8 is
assumed to identify potential new CO violations associated with planned changes
in the highway network. However, this process will not identify all potential
CO violations, since many source configurations (e.g., indirect sources) are
not encompassed in the 109(j) consistency review. States may wish to institute
an annual program for screening promising locations for potential CO viola-
tions (as described in Section 4 and Appendix D).
11
-------
COLLECTION
OF GROWTH INDICATORS
ARE THRESHOLDS
EXCEEDED?
NO AND HC
YES
PERFORM CONDENSED
ANALYSIS OF GROWTH
(PM & SOX ONLY)
POTENTIAL NAAQS
VIOLATION
NOTIFY ADMINISTRATOR
AND INITIATE
MONITORING
Figure 4. Schematic diagram of guideline procedures for
areas without monitoring.
12
-------
REFERENCES
1. 40 CFR 51.42 through 40 CFR 51.51.
2. Guidelines for Air Quality Maintenance Planning and Analysis, Volume 7:
Projecting County Emissions. U.S. Environmental Protection Agency,
Research Triangle Park, N.C.
3. Guidelines for Air Quality Maintenance Planning and Analysis, Volume 12:
Applying Atmospheric Simulation Models to Air Quality Maintenance Areas.
U.S. Environmental Protection Agency, Research Triangle Park, N.C.
4. Guidelines for Air Quality Maintenance Planning and Analysis, Volume 13:
Allocating Projected Emissions to Subcounty Areas. U.S. Environmental
Protection Agency, Research Triangle Park, N.C.
5. Mancuso, R. L., and F. L. Ludwig. User's Manual for the APRAC-1A Urban
Diffusion Model Computer Program. Ecological Research Series, EPA-650/
3-73-011, Technical Publications Branch, Environmental Protection Agency,
Research Triangle Park, North Carolina, 1972.
6. Zimmerman, J. R. and R. S. Thompson. User's Guide for HIWAY: A Highway
Air Pollution Model. EPA-650/4-74-008, U.S. Environmental Protection
Agency, National Environmental Research Center, Research Triangle Park,
North Carolina, 1975.
7. Hanna, S. R. A Simple Method of Calculating Dispersion From Urban Area
Sources. J Air Pollut Control Assoc. 21(12):774-777, 1971.
8. 23 CFR 770.2.
13
-------
SECTION 3
RELATIONSHIP OF GUIDELINES TO OTHER AIR QUALITY PLANNING PROGRAMS
The guidance offered in this report is intended to suggest possible pro-
cedures for identifying those areas for which expected growth may cause a
NAAQS to be violated. There are, of course, reasons other than growth which
may contribute to a violation of a NAAQS (or continuation of a violation);
e.g., changes in the Federal Motor Vehicle Control Program (FMVCP), the non-
compliance of stationary sources with compliance schedules, and other situa-
tions which may be categorized as nonattainment problems. Such situations
are more readily addressed through other components of a comprehensive air
quality planning process. Nevertheless, since continuing growth will, at
least, exacerbate a violation that is principally a result of another situa-
tion, this guidance does consider many of these problems.
There are also several components of the air quality planning process
that directly consider the effects of growth; e.g., new source review. The
effects on air quality of large new point sources are more expeditiously
considered in such programs. The cumulative impact of these sources and other
types of growth are necessarily considered in this guidance. The relationship
between other components of the air quality planning process and the subject
of this report are reviewed below.
STATIONARY SOURCE EMISSION SURVEILLANCE
Each SIP is required to provide for monitoring the status of compliance
of stationary sources; viz, "legally enforceable procedures for requiring
owners or operators of stationary sources to maintain records of, and peri-
odically report to the State information ... as may be necessary to enable
the State to determine whether such sources are in compliance with applicable
portions of the control strategy."! Thus a state should have the necessary
data to monitor the compliance status of stationary sources. EPA has developed
the Enforcement Management Subsystem (EMS), an information processing system
to aid State agencies in performing this monitoring task.
Whether or not stationary sources are meeting compliance schedules is of
importance in making the determination of the potential for a future viola-
tion of a NAAQS. For example, slower progress towards compliance by stationary
14
-------
&
sources than was anticipated during preparation of a subpart D analysis may
now contribute to a future violation that otherwise would not have occurred.
The guidelines in this report do not consider the compliance status of an
individual source. Such concerns are properly handled in the enforcement
division of the state agency. The guidelines do, at several points, consider
the total emission loading in a county due to point sources. For counties
for which an analysis of future air quality, such as subpart D, has been con-
ducted, the current estimate of total emissions from point sources is compared
with the value forecast in the emissions projection. Thus, in a crude way the
projection of emissions from point sources is verified, which includes both
growth (new sources and capacity expansion) as well as compliance schedule
progress.
PRECONSTRUCTION REVIEW OF NEW STATIONARY SOURCES
Stationary source review (SSR) is one component of new source review
(NSR) which, besides SSR, encompasses prevention of significant deterioration
(PSD), emission standards for hazardous pollutants (NESHAP), and standards of
performance for new sources (NSPS) for selected source categories. Each State
is required to establish procedures that will "enable the State or local agency
to determine whether the construction or modification of a facility, building,
structure, or installation, or combination thereof, will result in violation
of applicable portions of the control strategy or will interfere with attain-
ment or maintenance of a national standard either directly because of emis-
sions from it, or indirectly, because of emissions from mobile source activi-
ties associated with it."5 Most states have SSR procedures in their SIP6 -
though in six SIP's EPA has promulgated SSR regulations.7
An interpretive ruling to 40 CFR 51.187 has indicated that only major
sources are required to be reviewed to determine if the proposed source will
cause or exacerbate a violation of a NAAQS. A major source is defined as
having an allowable emission rate of 100 or more tons per year of particulate
matter, sulfur oxides, nitrogen oxides, or nonmethane hydrocarbons and 1000
or more tons per year of carbon monoxide. Thus every large new point source
(or modification) should be reviewed to determine if it will interfere with
the attainment or maintenance of a NAAQS. The air quality analysis should
take into account emissions from other previously approved new sources.8
The emissions of a new source include the secondary or indirect emissions
resulting from the facility when they can be accurately quantified and are
well defined.9 For a new source which would exacerbate an existing violation
of a NAAQS, approval may be granted only if the source meets the lowest
*
The emissions projection techniques and air quality simulation procedures
specified in subpart D, sections 51.42 through 51.51, and generally described
in Volumes 7, 12, and 13 of the Guidelines for Air Quality Maintenance Plan-
ning and Analysis.2-tt
In an advance notice of proposed rule-making16 amending 40 CFR 51, published
concurrently with the interpretive ruling,7 major sources are tentatively de-
fined as sources with allowable emission rates of 50 tons for pollutants other
than CO and 500 tons for CO.
15
-------
achievable emission rate, all other sources owned or controlled by the owner
or operator in the AQCR are in compliance, and emission reductions ("offsets")
from existing sources that are generated are greater than the emissions of the
new source and provide a positive net air quality benefit. The guidelines in
this report do not accurately identify situations where the construction or mo-
dification of a major source will lead immediately to a violation of an NAAQS.
That situation is adequately handled in SSR. There is, however, a certain
parallel between SSR and the 51.12(h) guidelines; while SSR tracks the air
quality impacts of major point sources, the guidelines track the growth of all
sources and attempt to identify situations where future growth will lead to a
potential violation of an NAAQS. SSR, including the offset policy, will pro-
vide information on emissions that can be used to maintain an accurate and up-
to-date emission inventory.
PREVENTION OF SIGNIFICANT DETERIORATION (PSD)
PSD is another component of NSR. In most SIPs, it currently applies to
19 categories of sources for particulate matter and sulfur oxides.1" No
source is permitted to be constructed or modified if, in conjunction with the
effects of growth and reduction in emissions after January 1, 1975, of other
sources, it will violate specified air quality increments. All areas have
been initially designated Class II, which specified increments of 10 and
15 yg/m3, respectively, in the annual means of particulate matter and sulfur
oxides. Allowable increments in the short-term averaging times are also pro-
vided. Like SSR, PSD requires an assessment of the impact of the proposed
source in conjunction with all sources constructed after January 1, 1975. This
includes all sources whether or not they are subject to preconstruction re-
view. It is entirely possible for the increment to be fully consumed by area
source growth before the preconstruction review of a source subject to PSD
review.
The 51.12(h) guidelines recommend the tracking and projection of emissions
growth and air quality trends. This provides a continuing assessment of the
PSD increment available for PSD sources. It will also provide some of the
information necessary for the preconstruction review oE a PSD source. PSD and
SSR preconstruction reviews will also lead to more accurate and up-to-date
emission inventories; the availability of which will facilitate the tracking
and assessment of emissions growth recommended in the 51.12(h) guidelines.
MOTOR VEHICLE SOURCE SURVEILLANCE
Transportation control plans (TCP) are required to contain procedures for
obtaining and maintaining data on actual emissions reductions achieved as a
result of implementing transportation control measures. In the case of mea-
sures involving inspection, maintenance, or retrofit, these data must include
the results of an emissions surveillance program designed to determine actual
average per vehicle emissions reductions attributable to inspection, main-
tenance, and/or retrofit. In the case of measures based on traffic flow
These limitations of PSD to 19 categories will shortly be changed to reflect
recent amendments to the Clean Air Act.
16
-------
changes or reductions in vehicle use, the data must include observed changes
in vehicle miles traveled (VMT) and average speeds. The data must be main-
tained in such a way as to facilitate comparison of planned and actual effi-
ciency of the transportation control measures.
The maintenance of such data on the implementation of a TCP will allow
one to verify the projections of VMT, average speeds, and per vehicle emission
rates made in the development of the TCP. Such data is necessary to fulfill
the requirements of Section 51.12(h) as well. It should be noted that it is
doubtful that all areas with TCPs are carrying out such a motor vehicle source
surveillance program. The pending implementation of the Urban Transportation
Reporting System (described in Appendix B of this report) by the Federal High-
way Administration and Urban Mass Transportation Administration, if successful,
should improve this situation with respect to the availability of vehicle use
and traffic flow parameters.
CONSISTENCY REVIEW OF TRANSPORTATION PLANS
The 1970 Federal-Aid Highway Act added Section 109(J) to Title 23 U.S.C.
and directed the Department of Transportation to develop and promulgate guide-
lines to assure that highways constructed with federal funds are consistent
with any approved plan for implementation of any air quality standard. Sub-
sequently, the Federal Highway Administration (FHWA) published final regu-
lations!^ and guidelines^ for analysis to assist the FHWA and metropolitan
planning organizations (MPO) in implementing the regulations. The 109(J)
guidelines list five criteria for determining consistency. MPO transpor-
tation plans and programs must:
not exacerbate any existing violations of the NAAQS
not contribute to a new violation of the NAAQS
not delay attainment of the NAAQS
not interfere with maintenance of the NAAQS
include all appropriate portions of the SIPs.
An annual determination of consistency between the transportation plan
and the SIP, often referred to as the "109(J) review," must be documented and
endorsed by the MPO policy board. The guidelines require that both the high-
way plans and the planning process be reviewed for consistency, and that the
FHWA Regional Administrator must consult with the EPA Regional Administrator
in these reviews. This review for consistency is one of many items that the
FHWA requires to be done to obtain the annual certification of each MPO's
planning process. The regulations also specify that a particular highway
project cannot be built unless FHWA determines that it is consistent with
the SIP- This project determination is to be included in the environmental
impact statement for the highway project.
The MPO transportation plans and programs generally include a short range
Transportation Improvement Program (10 years) and the long range plan (20 to
25 years). MPOs exist in each urbanized area (generally defined by the
Bureau of the Census as metropolitan areas in excess of 50,000 population).
17
-------
The 109(J) review has not been applied in a uniform manner nationwide.
"For a great many MPOs, the air quality analyses on which policy boards have
based their determinations are, at best, superficial, and no attempt has been
made to integrate the analyses into the planning process."14 In other areas,
substantial progress in implementing the 109(J) review has been made.
In areas without TCP's, the 51.12(h) guidelines in this report rely
heavily on the successful implementation of the 109(J) consistency review to
identify areas where the CO NAAQSs may be potentially violated. The regula-
tions,12 in theory, should assure that the planning, location, and construc-
tion of highways are consistent with the SIP and, therefore, prevent viola-
tions due to transportation plans or highway projects.
INDIRECT SOURCE REVIEW
On June 30, 1975, EPA suspended indefinitely the indirect source regula-
tions requiring preconstruction reviews of facilities which attract mobile
source activity that may violate a NAAQS. It applied to construction, in an
SMSA, of a new parking facility of 1,000 cars, a modification of a parking
facility which increases capacity by 500 cars, any new highway project with
more than 20,000 annual daily traffic (ADT), or modifications of highway fa-
cilities which increase ADT by 10,000. It applied to the construction or
modification of parking facilities outside SMSA's of, respectively, 2,000 and
1,000 cars. It also applied to the construction or modification of airports.
By 1977, 17 states, two territories, and two local areas have enacted
some form of indirect source control regulations; 10 states and one local
area are currently implementing their regulations.15 The scope of these
regulations vary - in many cases they closely parallel the suspended EPA
regulations. Those states that have adopted indirect source regulations, in
conjunction with the requirements of 109(J) review, are thus able to track
the growth of most types of development that could lead to a potential vio-
lation of the CO NAAQSs.
A proposed amendment in Appendix C to the indirect source regulations is ex-
pected to be published later this year. It will provide guidelines for the
review of highway and airport construction as indirect sources of air pollution.
18
-------
REFERENCES
1. 40 CFR 51.19(a).
2. Guidelines for Air Quality Maintaining Planning and Analysis, Volume 7:
Projecting County Emissions. U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina.
3. Guidelines for Air Quality Maintenance Planning and Analysis, Volume 12:
Applying Atmospheric Simulation Models to AQMPs. U.S. Environmental
Protection Agency, Research Triangle Park, North Carolina.
4. Guidelines for Air Quality Maintenance Planning and Analysis, Volume 13:
Allocating Projected Emissions to Sub-County Areas. U.S. Environmental
Protection Agency, Research Triangle Park, North Carolina.
5. 40 CFR 51.18(a).
6. OAQPS Guidelines 1.2-046, p. 1. U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina.
7. 41 Fed Regist 55525. December 21, 1976.
8. OAQPS Guidelines 1.2-046, p. 40. U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina.
9. 41 Fed Regist 55525. Footnote No. 3, December 21, 1976.
10. 40 CFR 52.21.
11. 40 CFR 51.19(d).
12. 39 Fed Regist 44441; see also CFR 770.2. December 24, 1974.
13. Guidelines for Analysis of Consistency Beitween Air Quality Plans and
Programs. FHWA and EPA. Washington, D.C. April 1975.
14. Kurtzweg, Jerry. "Progress in Achieving Consistency Between Transpor-
tation and Air Quality Plans," (Presented at the 70th Annual Meeting
of A.P.C.A.)
19
-------
15. S. J. LaBelle, D. A. Seymour, A. E. Smith and M. L. Harbour. The Balance
Sheet Technique Volume II - Preconstruction Review of Airports: Review
of State Regulations, Projects Affected and Resource Requirements. Argonne
National Laboratory, Draft Report of U.S. EPA Office of Transportation
and Land Use Policy (January 1977).
16. 41FR55558 (December 21, 1976).
20
-------
SECTION 4
GUIDELINES FOR IMPLEMENTING 40 CFR 51.12(h)
DEFINITIONS
For particulate matter, sulfur oxides, and nitrogen oxides, the basic
area considered in these guidelines is the county. This is due principally
to the general lack of availability of growth indicators for smaller areas.
If indicators are available, a smaller geographic unit may be used. The
following county classification scheme, based on the availability of data, is
used. Guidance is given separately for each county class.
Category 1: County without monitoring - a county without represen-
tative permanent monitoring for the pollutant species of concern
and without any analysis of growth.
Category 2: County with monitoring - a county with representative
permanent monitoring for the pollutant species of concern and with-
out any analysis of growth.
Category 3: County with condensed growth analysis - a county for
which a condensed analysis of growth and air quality has been
conducted; e.g., the AQMA designation analysis.
Category 4: County with detailed growth analysis - a county for
which a detailed analysis of growth and air quality has been con-
ducted; i.e., the analysis specified in subpart D of part 51 of the
SIP regulations.
States with many small counties (e.g., independent cities in Virginia)
may find it convenient to use multicounty groupings. The procedures outlined
in this section are not applicable to very large counties, only a portion of
which is settled, such as counties in the western areas of the country. In
such cases, the procedures recommend treating a portion of the county (e.g.,
the incorporated area) as a county equivalent. The decision of which portion
of the county to be used should be based on the availability of data and the
nature of the air shed.
For oxidants, the basic area considered is the AQCR. This is due to the
areawide nature of oxidant pollution. The categorization listed above, based
on data availability, is utilized. Carbon monoxide is treated entirely differ-
ently, with the emphasis on detecting localized CO violations.
The sources of data utilized in this section are described in Appendix B.
21
-------
PARTICULATE MATTER AND SULFUR OXIDES - COUNTIES WITHOUT MONITORING (CATEGORY 1)
In the first year of analysis, Step 2 must be performed. Thereafter, the
analysis in Step 2 should be revised to reflect new projections at least every
5 years regardless of the outcome of Step 1 in the intervening years. If the
county is experiencing negative growth, nothing need to be done.
1. a) If new projections are unavailable
Acquire the current estimates of county population and
employment. Compare the current estimates of each in-
dicator with the forecast value for the current year in
the projections used in Step 2. If the current estimates
of either indicator is in excess of the forecast amount,
a new or revised projection should be prepared and Step 2
revised. Prepare a worst-case estimate by extra-
polating the current growth rate 10 years, unless
new projections become available.
b) If new projections are available
Acquire the new projections of county population and
employment. Compare the new 10-year growth rates with
the growth rates in the projections used previously in
Step 2. If the new growth rate is greater, proceed to
Step 2.
2. Prepare a quick worst-case, 10-year projection of the county
emission inventory, ignoring compliance schedule progress at
existing sources. In the absence of better data, update and
project the county emission inventory by multiplying the base
year emissions estimate by the larger of the population or
employment growth factors (projected value divided by base
year value). Estimate the maximum emission density in the
county in any square mile area, or, if unable to do so, divide
the aggregate county emissions by the settled area of the
county. Estimate ambient air quality using Hanna Gifford to
compute the origin cell concentration (Equation (8) of
Appendix A of this report)."1" If the projected concentration
approaches the NAAQS (e.g., 75 percent of the NAAQS), proceed
to the next step.
3. Project the emission inventory and model future air quality
using the procedure outlined in Appendix A. If the projected
air quality approaches the NAAQS (e.g., 75 percent of the
NAAQS), proceed to next step.
Settled area refers to the urbanized or developed area in the county. If
this is unknown or data unavailable, use the incorporated area of the county.
+As described on page 77, it may be appropriate to model large point sources
individually.
22
-------
4. Ambient air quality monitoring should be initiated in the county.
In subsequent years, the procedures for a county with monitoring
(the following subsection) should be followed. If the results
of Step 3 indicated that the projected air quality is in excess
of a NAAQS, proceed to the next step.
5. Notify the EPA regional administrator.
23
-------
PARTICULATE MATTER AND SULFUR OXIDES - COUNTIES WITH MONITORING (CATEGORY 2)
In the first year of analysis, Step 2 should be performed. Thereafter,
Step 2 should be revised to reflect new projections at least every 5 years,
regardless of the outcome of the previous step in the intervening years. If
the county is experiencing negative growth, nothing need to be done.
1. a) If new projections are unavailable
Acquire the current population and employment estimates
for the county. If either indicator is in excess of the
forecast value for the current year in the projections
used in Step 2, a new or revised projection should be
prepared and the analysis of Step 2 revised. Prepare a
worst-case estimate by extrapolating the current growth rate
10 years, unless new projections become available.
b) If new projections are available
Acquire the new projections of county population and employment,
Compare the new 10-year growth rates with the growth rates in
the projections used previously in Step 2. If the new growth
rate is greater, proceed to Step 2.
2. Project air quality 10 years using the population or employment
forecast:
Xp = G (xc - XB> + XB
where Xp = projected air quality level
G = the larger of population and employment 10-year growth
factors (i.e., forecast value divided by current value)
X_ = current air quality level
*
X., = background concentration
B
If the projected air quality is near the NAAQS (e.g., 90
percent of the NAAQS), proceed to next step.
3. Project the most recent county emission inventory 10 years
using the procedures in Appendix A. Model projected air
No specific guidance for estimating the background level is given in this
report. It is believed that the state or local agency is the best judge of
this value. (Note that the estimate of the background level is usually based
on the lowest measured annual air quality concentration in the region; i.e.,
a nonurbanized area away from major sources). It is generally thought of as
including the large scale influence of long range transport and, in the case
of particulates, naturally occurring particulates.
24
-------
quality using the procedures outlined in Appendix A. If
the projected air quality is in excess of a NAAQS, proceed
to the next step.
4. Notify the EPA regional administrator.
25
-------
PARTICIPATE MATTER AND SULFUR OXIDES - COUNTIES WITH CONDENSED ANALYSIS
(CATEGORY 3)
Counties falling into this category will have performed an analysis of
projected air quality at a level of detail of Appendix A of these guidelines
or greater within the past 5 years. If it has not been done in the past 5
years, proceed to Step 2.
1. a) If new projections are unavailable
i. Collect current population and employment estimates
(or other indicators used in the condensed analysis).
Separately compare the total growth in each indicator
with that projected in the analysis of projected air
quality. If any indicator has experienced more growth
than was projected, proceed to Step 1. a) ii.
ii. Using the experienced growth, estimate the current
aggregate emission loading in the county. For example,
multiply the fuel combustion area source emissions of
the most recent emission inventory by the percent in-
crease in employment, industrial process area source
emissions by the percent increase in manufacturing em-
ployment, and the solid waste, transportation, and
miscellaneous emissions by the percent increase in po-
pulation. Total the current point source inventory.
(Project it forward if it is 1 or 2 years out-of-date).
Compare the estimated total emissions in the current
year with that expected for the year from the condensed
analysis. (Linearly interpolate between the base year
emissions and the projection year). Figure 5 is an
example of this, showing current emissions greater than
were expected in the third year. If total emissions
are greater than expected, proceed to Step 1. a) iii.
iii. Assess the validity of final year forecasts of the in-
dicators used to project growth. If they are no longer
valid, proceed to Step 2. Ideally, new projections may
be prepared which may be compared with the old ones.
If this is not the case, ask the organization that
prepared the projections if, in light of recent growth,
the final year estimates are still valid. (At least
one of the indicators has experienced a higher annual
growth rate than was forecast). If there is any ques-
tion as to the validity of the forecast amount for the
final year, proceed to Step 2.
26
-------
AGGREGATE
EMISSIONS
LOADING
IN COUNTY
ESTIMATE OF CURREN^ YEAR
EMISSIONS
LINEAR INTERPOLATION
OF CRITICAL EMISSION
LEVEL
BASE
YEAR
BASE
YEAR +10
TIME
Figure 5. Comparison of estimated current year emissions with that forecast in the
condensed analysis.
-------
1. b) If new projections are available
Acquire the new 10-year projections of county employment and
population (or other indicators used in the condensed analysis).
Compare the new 10-year growth rate x^ith the growth rate in the
projections used previously in Step 2. If the new growth rate
is greater, proceed to Step 2.
2. Project emissions 10 years, and model air quality using the pro-
cedures in Appendix A of this report. If projected air quality
exceeds the NAAQS, proceed to Step 3.
3. Notify the EPA regional administrator.
28
-------
PARTICULATE MATTER AND SULFUR OXIDES - COUNTIES WITH DETAILED ANALYSIS
(CATEGORY 4)
Counties falling into this category will have performed a detailed anal-
ysis within the past 5 years. If this has not been done within the past 5
years, proceed to Step 4.
1. Acquire the indicators used to project the emission inventory.
Separately compare the total growth experienced in each indi-
cator with that projected in the analysis. Linearly interpolate
between the base year and end year of the analysis if necessary.
If any indicator has experienced more growth than was projected,
proceed to Step 2. In addition, annually compute the total point
source emissions and compare the total with that projected in the
analysis. If it is greater than anticipated, proceed to Step 2.
2. Using the experienced growth to project the area source emissions,
estimate the current aggregate emission loading. Compare that
with the expected emission loading for the current year from the
analysis. If it is greater, proceed to Step 3.
3. Assess the validity of final year forecasts of the indicators
used to project growth. If they are no longer valid, proceed
to Step 4. Ideally, new projections will be available which may
be comapred with the old ones. If this is not the case, ask the
organization that prepared the projections if, in light of recent
growth, the final year estimates are still valid. (At least one
of the indicators has experienced a higher annual growth rate
than was forecast). If there is any question as to the validity
of the forecast amount for the final year, proceed to Step 4.
4. Revise the detailed analysis to incorporate the new projections.
If the projected air quality exceeds the NAAQS, proceed to Step 5.
5. Notify the EPA regional administrator.
*
See the discussion in Appendix B.
29
-------
CARBON MONOXIDE - COUNTIES WITH DETAILED ANALYSIS
Counties in this category will have available a recent (less than 5 years
old) detailed analysis of growth and air quality. The detailed analysis should
be revised at least every 5 years.*
1. As they become available, collect the most recent estimates of the
parameters used in the analysis. This may be regional VMT if roll-
back was used in the analysis or ADT at selected links if a simula-
tion model such as APRAC-1A was used. It may be necessary to col-
lect both parameters if both were used in the analysis. It is also
necessary to estimate current stationary source emissions. Compare
the current estimates with forecast values. If any of the estimated
current values are greater than the forecast values, proceed to
Step 2.
2. Reassess the validity of the detailed analysis. If rollback and
regional VMT was used, prepare a new forecast of regional VMT and
recalculate the rollback based on current monitoring data. If a
link-based ADT and a line source model was utilized and only a
few links have experienced greater than anticipated growth (or
less than anticipated reductions) reevaluate the concentration
near the specific links using new ADT projections and hot spot
screening techniques. If many links have experienced greater than
anticipated growth, the simulation model should be reexecuted
using new ADT projections. (The links with the greatest unanti-
cipated growth or in the vicinity of the highest concentrations
may be evaluated first using the hot spot screening guidelines.)
If a future violation of an NAAQS is indicated, notify the EPA
regional administrator.
CARBON MONOXIDE - COUNTIES WITHOUT DETAILED ANALYSIS
It is assumed that the 109(j) consistency review1 will identify all
future potential violations of the CO NAAQS relating to highway projects.
There is, of course, the potential for a violation of the CO NAAQSs due to
other sources such as those that were covered by indirect source review as
well as source configurations that were not included in the definition of
indirect sources."1" States may well wish to initiate a continuing program of
screening promising locations for potential CO violations. An overview of
the CO hot spot planning process is given in Appendix D. For example, every
If the county has a TCP, the motor vehicle source surveillance program may
provide most of the data and some of the analysis to assess the potential of
an NAAQS violation in 10 years.
See, for example, Croke et al. The Relationship of Automotive Pollutants
and Commercial Development. APCA Paper 75-22.6. A typical example would
be highway commercial strip development.
30
-------
year five locations in a county could be evaluated as potential CO hot spots.
If a state has not adopted an indirect source regulation, proposed new indirect
sources would be an obvious choice for such evaluation. If any potential vio-
lations are identified, notify the EPA regional administrator.
31
-------
OXIDANTS - AQCRs WITHOUT MONITORING (CATEGORY 1)
If a recently prepared 10-year projection of AQCR VMT is easily available,
proceed to Step 3.
1. Acquire the estimate of gasoline sales (or state gasoline
tax receipts) for the AQCR. If a positive growth is in-
dicated, proceed to next step.*
2. Compute the sales of gasoline per square mile. Project it
10 years by multiplying it by the forecast population growth
rate. If it is in excess of the value indicated in Table 1,
proceed to the next step.
3. Acquire or prepare a 10-year projection of total VMT in the
AQCR. Compute the VMT per square mile. If it is in excess
of the value indicated in Table 2, proceed to the next step.
4. Prepare or update a hydrocarbon emission inventory for the
AQCR and project it 10 years as outlined in Appendix A.
If the nonmethane hydrocarbon emission density is projected
to exceed 16.9 tons per square mile, proceed to the next
step.
5. Notify the EPA regional administrator. Oxidant monitoring
should be initiated.
If tax receipts or service station revenues are used, they may have to be
adjusted for changes in the price of gasoline or tax rates before comparison
with prior years. If gasoline sales data are not available from the state,
sales data can be obtained from the Census of Retail Trade every 5 years and
updated using population or motor vehicle registration.
32
-------
TABLE 1. CRITICAL GASOLINE SALES DENSITY TO EXCEED 75
PERCENT OF THE HYDROCARBON STANDARD
Analysis year
1986
1987
1988
1989
1990
Critical level
gallons /year /square
Low altitude
357,000
401,000
408,000
412,000
432,000
High altitude
327,000
388,000
396,000
404,000
422,000
mile
California
368,000
418,000
420,000
420,000
430,000
Assumptions:
Note:
Negligible emissions from stationary
sources.
FMVCP in force in April, 1977 (1.5 g/m
1975-1977; 0.41 g/mi 1978 and later).
Gasoline Mileage Standards of the
Federal Energy Policy and Conservation
Act of 1975.
Hanna-Gifford model origin cell concen-
tration at wind velocity of 1 meter per
second, stable atmosphere.
Twenty-five percent of VMT in peak
3-hour period.
Supplement 5 emission factors.
The derivation of this table is described in
Appendix E. Sufficient information is provided
to obtain localized critical values to reflect
localized motor vehicle emission factors, inappli-
cability of the assumptions, and changes in pro-
jected motor vehicle emission factors.
33
-------
TABLE 2. CRITICAL VMT DENSITY TO EXCEED 75 PERCENT OF
THE HYDROCARBON STANDARD
Analysis year
1986
1987
1988
1989
1990
Critical
Low altitude
7.5
9.0
9.5
10.0
10.5
level of VMT/square
millions
mile
High altitude California
7.0
8.5
9.0
9.5
10.5
8.0
9.0
9.5
10.0
10.5
Assumptions:
Negligible emissions from stationary
sources.
FMVCP as of April 1977 (1.5 g/m
(1975-1977; 0.41 g/mi 1978 and
later).
Hanna-Gifford model origin cell
concentrations at wind velocity of
1 meter per second, stable atmosphere.
Twenty-five percent of VMT in peak
3-hour period.
Supplement 5 emission factors.
Note: The derivation of this table is described in Appendix E.
Sufficient information is provided to obtain localized
critical values to reflect localized motor vehicle emis-
sion factors, inapplicability of the assumptions and
changes in projected motor vehicle emission factors.
34
-------
OXIDANTS - AQCRs WITH MONITORING (CATEGORY 2)
1. Acquire the estimate of gasoline sales (or tax receipts) in the
AQCR. If a positive growth is indicated, proceed to the next
step.
2. Acquire a 10-year or greater population projection. Acquire,
from the most recent emission inventory, the proportion of hydro-
carbon emissions (P) from light-duty mobile sources. Determine
the expected reduction in light-duty motor vehicles emissions (ER)
as described in Appendix A.
If currently below the NAAQS, project air quality using the pro-
portional method:
3.
Pop
= X
future
future current Pop
current
(P) (ER) + (1-P)
If currently above the NAAQS, determine the reduction need to
achieve the NAAQS using the revisions forthcoming to Part 51
Appendix J. Determine the projected emission reduction:
projected emission = 1 -
reduction
Pop
future
Pop
current
(P) (ER) + (1-P)
If VMT estimates and forecasts are available, they should be
used in place of the population estimates or projections.
If the projected air quality is above the NAAQS, or if the
projected emission reduction is less than that required, proceed
to the next step.
Perform an air quality analysis as outlined in Appendix A; if
the projected air quality exceeds the NAAQS, proceed to Step 4.
4. Notify the EPA regional administrator.
35
-------
OXIDANTS - AQCRs WITH CONDENSED ANALYSIS (CATEGORY 3)
AQCRs falling into this category will have performed an analysis of pro-
jected air quality at a level of detail of Appendix A of these guidelines or
greater within the past 5 years. If it has not been done in the past 5 years,
proceed to Step 2.
1. a) If new projections are unavailable
i. Collect current population and employment estimates
(or other indicators used in the condensed analysis).
Separately compare the total growth in each indicator
with that projected in the analysis of projected air
quality. If any indicator has experienced more growth
than was projected, proceed to Step 2.
ii. Using the experienced growth, estimate the current
aggregate emission loading in the county. For example,
multiply the fuel combustion area source emissions of
the most recent emission inventory by the percent in-
crease in employment, industrial process area source
emissions by the percent increase in manufacturing em-
ployment, and the solid waste, transportation, and mis-
cellaneous emissions by the percent increase in popu-
lation. Adjust the transportation emissions estimate
for the effects of the FMVCP. Total the current point
source inventory. (Project it forward if it is a year
or 2 out of data). Compare the estimated total emis-
sions in the current year with that expected for the
year from the condensed analysis. If total emissions
are greater than expected, proceed to Step 3.
iii. Assess the validity of final year forecasts of the in-
dicators used to project growth. If they are no longer
valid, proceed to Step 2. Ideally, new projections may
be prepared which may be compared with the old ones.
If this is not the case, ask the organization that
prepared the projections if, in light of recent growth,
the final year estimates are still considered valid.
(At least one of the indicators has experienced a
higher annual growth rate than was forecast.) If there
is any question as to the validity of the forecast
amount for the final year, proceed to Step 2.
b) If new projections are available
Acquire the new 10-year projections of population and employ-
ment (or other indicators used in the condensed analysis).
Compare the new 10-year growth rate with the growth rate used
previously in Step 2. If the new growth rate is greater,
proceed to Step 2.
36
-------
2. Project emissions 10 years, and model air quality using the pro-
cedures in Appendix A. If projected air quality exceeds the
NAAQS, proceed to Step 3.
3. Notify the EPA regional administrator.
37
-------
OXIDANTS - AQCRs WITH DETAILED ANALYSIS (CATEGORY 4)
AQCRs falling into this category will have performed a detailed analysis
within the past 5 years. If this has not been done within the past 5 years,
proceed to Step 4.
jf
1. Acquire the indicators used to project the emission inventory.
Separately compare the total growth experienced in each indi-
cator with that projected in the analysis. Linearly interpolate
between the base year and end year of the analysis if necessary.
If any indicator has experienced more growth than was projected,
proceed to Step 2. In addition, annually compute the total point
source emissions and compare the total with that projected in the
analysis. If it is greater than anticipated, proceed to Step 2.
2. Using the experienced growth to project the area source emissions,
estimate the current aggregate emission loading. Compare that with
the expected emission loading for the current, year from the anal-
ysis. If it is greater, proceed to Step 3.
3. Assess the validity of final year forecasts of the indicators used
to project growth. If they are no longer valid, proceed to Step 4.
Ideally, new projections will be available which may be compared
with the old ones. If this is not the case, ask the organization
that prepared the projections if, in light of recent growth, the
final year estimates are still considered valid. (At least one of
the indicators has experienced a higher annual growth rate than was
forecast.) If there is any question as to the validity of the fore-
cast amount for the final year, proceed to Step 4.
4. Revise the detailed analysis to incorporate the new projections.
If the projected air quality exceeds the NAAQS, proceed to Step 5.
5. Notify the EPA regional administrator.
*
See the discussion in Appendix B.
38
-------
NITROGEN OXIDES - COUNTIES WITHOUT MONITORING (CATEGORY 1)
All priority I AQCRs are required to have at least three nitrogen dioxide
monitors.2 If an AQCR initially did not have nitrogen dioxide monitoring,
it was classified as priority I if it contained an area whose 1970 urban place
population exceeded 200,000.3 The AQCR, if classified as priority I on the
basis of population, could have been reclassified as priority III if measured
concentrations were below 110 micrograms per cubic meter.
A statistical analysis of 1975 nitrogen dioxide concentrations indicated
that there is a 99 percent probability of not exceeding the nitrogen oxide
standard in a county if the county population is below 800,000 or the popu-
lation density is below 140 population per square mile. Thus, considering
the monitoring requirements, it is likely that few counties with the potential
of exceeding the NAAQS will not already have monitoring.
1. As they become available, obtain new 10-year population projections.
Determine if the forecast values of county population and county
population density per square miel are in excess of 800,000 and
140, respectively. If either is in excess of the indicated value,
proceed to the next step.
2. Ambient air quality monitoring should be initiated in the county.
In subsequent years, the procedures for a county with monitoring
(the following subsection) should be followed. Notify the EPA
regional administrator.
*
Two simple ordinary least squares regressions of county population and county
population density on county nitrogen dioxide concentrations. Other variables
and log and reciprocal transformations were also considered, but were found to
provide no additional power in describing nitrogen oxide concentrations.
39
-------
NITROGEN OXIDES - COUNTIES WITH MONITORING (CATEGORY 2)
In the first year of analysis, Step 2 should be performed. Thereafter,
Step 2 should be revised to reflect new projections at least every 5 years,
regardless of the outcome of the previous step in the intervening years. If
the county is experiencing negative growth, nothing need to be done.
1. a) If new projections are unavailable
&
Acquire the current estimates of population and electric
utility nitrogen oxide emissions. If either is in excess
of the forecast value for the current year in the projec-
tion used in Step 2, a new or revised projection should be
prepared and the analysis of Step 2 revised. Prepare a worst-
case estimate by extrapolating the current growth rate
10 years, unless new projections become available.
b) If new projections are available
Acquire the new 10-year projections of county population
and electric utility emissions. Compare the 10-year growth
rate in county population and electric utility emissions
with the growth rates used previously in Step 2. If the
new growth rate of either is greater, proceed to Step 2.
2. Project air quality using the population and emissions
forecast:
Xp = G (X(, - XB> + XB
Q P
G = -2- f + J*. (i-f)
c c
where x = projected air quality level
P
G = projected emissions growth
Xp = current air quality level
\^
X = background air quality level
B
Q = projected electric utility emissions in 10 years
Q = current electric utility emissions
f = proportion of nitrogen oxide emissions from electric utilities
in the most recent county emission inventory
*
VMT instead of population may be used if data is available.
40
-------
P = projected county population in 10 years
P
P = current county population
c
If the projected air quality is near the NAAQS (e.g., 90 percent
of the NAAQS), proceed to next step.
3. Project the most recent county emission inventory using the proce-
dures in Appendix A. Model projected air quality using the proce-
dures outlined in Appendix A. If the projected air quality exceeds
the NAAQS, proceed to next step.
A. Notify the EPA regional administrator.
VMT instead of population may be used if data is available.
41
-------
NITROGEN OXIDES - COUNTIES WITH CONDENSED ANALYSIS (CATEGORY 3)
Counties falling into this category will have performed an analysis of
projected air quality at a level of detail of Appendix A of these guidelines
or greater within the past 5 years. If it has not been done in the past 5
years, proceed to Step 2.
1. a) If new projections are unavailable
i. Collect current population and employment estimates
(or other indicators in condensed analysis). Separately
compare the total growth in each indicator with that
projected in the analysis of projected air quality. If
any indicator has experienced more growth than was pro-
jected, proceed to Step ii.
ii. Using the experienced growth, estimate the current aggre-
gate emission loading in the county. That is, multiply
the fuel combustion area source emissions of the most
recent emission inventory by the percent increase in
employment, industrial process area source emission by
the percent increase in manufacturing employment, and
the solid waste, transportation, and miscellaneous emis-
sions by the percent increase in population. Adjust the
transportation emissions estimate for the effects of the
FMVCP. Total the current point source inventory.
(Project it forward if it is a year or 2 out of date.)
Compare the estimated total emissions in the current
year with that expected for the year from the condensed
analysis. If total emissions are greater than expected,
proceed to Step iii.
iii. Assess the validity of final year forecast of the indi-
cators used to project growth. If they are no longer
valid, proceed to Step 2. Ideally, new projections may
be prepared which may be compared with the old ones.
If this is not the case, ask the organization that
prepared the projections if, in light of recent growth, the
final year estimates are still valid. (At least one of
the indicators has experienced a higher annual growth rate
than was forecast.) If there is any question as to the
validity of the forecast amount for the final year, pro-
ceed to Step 2.
*
VMT should be used to project transportation emissions if it is available.
42
-------
b) If new projections are available
±. Acquire projections of population, employment, electric
utility emissions, and other indicators used in the
condensed analysis. Individually compare the new pro-
jections of growth rates of each indicator with those of
the projections used previously in Step 2. If any one
indicator is projected to have a larger growth rate,
proceed to Step ii.
ii. Prepare a new 10-year forecast of emissions using the
new projections and the procedures in Appendix A. If
the new forecast of emissions is greater than that
prepared previously in Step 2, proceed to Step 2.
2. Project emissions, and model air quality using the procedures in
Appendix A. If projected air quality exceeds the NSAQS, proceed to
Step 3.
3. Notify the EPA regional administrator.
43
-------
NITROGEN OXIDES - COUNTIES WITH DETAILED ANALYSIS (CATEGORY 4)
Counties falling into this category will have performed a detailed anal-
ysis within the past 5 years. If this has not been done within the past 5
years, proceed to Step 4.
1. Acquire the indicators used to project the emission inventory.
Separately compare the total growth experienced in each indi-
cator with that projected in the analysis. Linearly inter-
polate between the base year and end year of the analysis if
necessary. If any indicator has experienced more growth than
was projected, proceed to Step 2. In addition, annually com-
pute the total point source emissions and compare the total
with that projected in the analysis. If it is greater than
anticipated, proceed to Step 2.
2. Using the experienced growth to project the area source emis-
sions, estimate the current aggregate emission loading. Com-
pare that with the expected emission loading for the current
year from the analysis. If it is greater, proceed to Step 3.
3. Assess the validity of final year forecasts of the indicators
used to project growth. If they are no longer valid, proceed
to Step 4. Ideally, new projections will be available which
may be compared with the old ones. If this is not the case,
ask the organization that prepared the projections if, in light
of recent growth, the final year estimates are still valid.
(At least one of the indicators has experienced a higher annual
growth rate than was forecast.) If there is any question as to
the validity of the forecast amount for the final year, proceed
to Step 4.
4. Revise the detailed analysis to incorporate the new projections.
If the projected NAAQS exceeds the NAAQS, proceed to Step 5.
5. Notify the EPA regional administrator.
44
-------
REFERENCES
1. 23 CFR 770.2
2. 40 CFR 51.17
3. 40 CFR 51.3(b)(2)
45
-------
SECTION 5
ILLUSTRATION OF GUIDELINES IN WISCONSIN
The guidelines presented in Section 4 were tested in two states, Wisconsin,
and Massachusetts. In the interim period between the preparation of a draft
of the guidelines for use in the illustration and the preparation of this re-
port, the guidelines were revised to reflect comments by individuals in sever-
al state agencies and the U.S. Environmental Protection Agency. The guide-
lines were also revised based on the experience in Wisconsin and Massachusetts.
Consequently, the process described in this section does not exactly corres-
pond to the guidelines presented in Section 4. The results of the Wisconsin
illustration are summarized below, Massachusetts is treated in the following
section.
An AQMA designation analysis was conducted for all SMSAs in Wisconsin,
but no detailed AQMA analyses have yet been completed. Thus, for this analysis
counties were categorized by the results of the designation analysis and by
the availability of monitoring data. The initial exclusions and inclusions
are summarized in Table 3. Thus an abbreviated analysis was conducted for
most SMSAs for total suspended particulates (TSP); for Milwaukee for sulfur
oxides (SO ), and for Milwaukee, Kenosha, and Racine for oxidants.
X
The results of the condensed analysis for TSP and SOX are shown in Table
2. The condensed analysis for oxidants indicated all three SMSAs should be
designated.
SUMMARY
The illustration of the guidelines required approximately 1 person week.
On the basis of simple roll-forward projections, four counties not currently
violating the short term particulate NAAQS were indicated as having the po-
tential for doing so.
The roll-forward analysis did not take into account emission reductions
at existing sources due to compliance schedule progress; that is, it only
considered the effects of growth. The next step, not performed in this illus-
tration, would be to estimate the projected compliance progress and include
the expected emission reduction in the roll-forward analysis. It is expected
that the further analysis would indicate that there is no potential for a
violation of a NAAQS.
Nine counties currently exceeding the short term particulate NAAQS, one
exceeding the 24 hour sulfur oxide standard, and three exceeding the oxidant
46
-------
TABLE 3. INITIAL INCLUSION/EXCLUSION SUMMARY
SMSA
Appleton-Oshkosh , Wi
Du luth- Super ior , Mn-Wi
Douglas County
Green Bay, Wi
Kenosha , Wi
La Crosse, Wi
Madison, Wi
Milwaukee, Wi
Minneapolis-
St. Paul, Mn-Wi
St. Croix County
Racine, Wi
Part
Nei
Nei
Nei
Nei
Nei
Nei
Nei
Exc
Nei
S02
Exc
Exc
Exc
Exc
Exc
Exc
Nei
Exc
Exc
CO
Exc
Exc
Exc
Exc
Exc
Exc
Exc
Exc
Exc
Ox
Exc
Exc
Exc
Nei
Exc
Exc
Nei
Exc
Nei
N0£
Exc
Exc
Exc
Exc
Exc
Exc
Exc
Exc
Exc
Inc - Included automatically
Exc - Excluded automatically
Nei - Neither included or excluded automatically
47
-------
TABLE 4. AIR QUALITY PROJECTIONS
.e-
00
Wisconsin
SMSA ' s
Appleton-
Oshkosh(A)
Duluth-
Superior
Douglas Co.
Green Bay
Kenosha
La Crosse
Madison
Milwaukee
Minneapolis-
St. Paul
St. Croix Co.
Racine
NAAQS's (ng/ra3)
Base
Year
'72
'72/
'70
'72
'73
'71
'70
'73
'73
Projected 1985 Air Quality
Sulfur dioxide Particulate
Arith. Max. Max. Geom. Max.
Mean 24-hr. 3-hr. mean 24-hr.
NR
NR
NR
NR
NR
NR
83
NR
NR
80
NR
NR
NR
NR
NR
NR
552*
NR
NR
365
NR
NR
NR
NA
NA
NA
969*
NR
NR
1300
83
60
58
84
52
69
95
NR
95
75
276
99
197
186*
93
149
277*
NR
258*
150
Initial
AQMA
designations
Particulates - except
Calutnent County
None
Particulates
Particulate and Oxidants
None
None
Particulates, Oxidants and
sulfur dioxide
None
Particulates and Oxidants
NR - Not Required, due to exclusion criteria
NA - Not available - Base year data not reported in this sample time
(A) used Winnebago County Monitoring Data - Outagamie County is very similar
*
Second highest
-------
standard were shown to have some potential for continuing to exceed the stan-
dard in 10 years. It is expected that additional analysis of emission reduc-
tions due to compliance schedules would also show that there is no potential
of a NAAQS violation in the case of particulate matter and sulfur oxides. This
analysis would take approximately 1 person day.
TSP AND SO
x
The category 1 counties for TSP and SOX (i-e., counties without monitoring
data) are shown in Table 5. For the first step, the only data source required
was a set of current population estimates and 10-year-or-greater projections.
These were obtained from the Wisconsin State Bureau of Program Management.
Table 5 presents the results of the analysis, namely which counties are cur-
rently experiencing growth and which are projected to continue growing. Two
counties, Langlade and Richland, are experiencing population declines and are
thus exempt from further analysis.* The current maximum emission densities
in the remaining counties were estimated from EPA NEDS and U.S. Bureau of the
Census data. These were projected to 1990 using the State of Wisconsin's
population projection of the county. Ambient air quality levels were esti-
mated from these projected emission inventories using the modified Hanna-
Gifford model as described in Appendix A. A 10-mile-per-hour mean wind speed
and stability class D were assumed. As shown in Table 6, all projected con-
centrations were below 75 percent of the standard, so no further analysis was
required.
The category 2 counties, namely, counties with monitoring data, are shown
in Table 7. The first four steps in the growth monitoring guidelines were
conducted for these counties. The table indicates whether the county is
currently experiencing population growth, the projected population growth
factor through 1995 (i.e., 1995 population/1976 population), and the results of
air quality projections made with these growth factors. Population projec-
tions were obtained from the source cited previously, and air quality data
were supplied by the state.
Ashland County is experiencing a population decline and is thus exempt
from steps 2, 3, and 4. Of the remaining counties, nine are currently violat-
ing a NAAQS. The high concentrations in these characteristically rural coun-
ties is thought to be due to nearby point sources, principally paper and
lumber mills. As these sources achieve compliance, the standards are expected
to be met. However, since these counties are expected to experience a rela-
tively high rate of growth (30 to 40 percent), it would be prudent to estimate
the combined effects of compliance schedule progress and growth on future air
quality. This is the recommended next step in the guidelines, an abbreviated
analysis as described in Appendix A.
Aside from the nine counties currently violating a standard, the linear
roll-forward analysis has indicated that four counties currently with air
*The air pollution control agency would still have to monitor the county for
PSD increments, and may have to adopt additional regulations to protect the
standards as a result of windblown agricultural dust.
49
-------
TABLE 5. CATEGORY 1 ANALYSES FOR TSP AND SO (STEP 1)
County Current growth (+/-) Future growth (+/-)
Adams + +
Barren + +
Bayfield + +
Buffalo + +
Burnett + +
Chippewa + +
Clark + +
Crawford + +
Dodge + +
Dunn + +
Florence + +
Fond du Lac (S02 only) + +
Forest + +
Grant (S02 only) + +
Green + +
Green Lake + +
Iowa + +
Iron + +
Jackson + +
Jefferson + +
Juneau + +
Kewaunee + +
Lafayette + +
Langlade - NR
Lincoln + +
Manitowoc (S02 only) + +
Marquette + +
Menominee + +
Monroe + +
Oconto + +
Pepin + +
Polk + +
Price + +
Richland - NR
Rusk + +
Sauk + +
Sawyer + +
Shawano + +
Sheboygan (S02 only) + +
Taylor + +
Trempealeau + +
Vilas (S02 only) + +
Washburn + +
Waupaca + +
Waushara + +
Note: NR - Not required
50
-------
TABLE 6.
CATEGORY 1 ANALYSES FOR TSP AND SO (STEP 2)
County
Adams
Barron
Bayfield
Buffalo
Burnett
Chippewa
Clark
Crawford
Dodge
Dunn
Florence
Fond du Lac (SCv only)
Forest
Grant (SO, only)
Green
Green Lake
Iowa
Iron
Jackson
Jefferson
Juneau
Kewaunee
Lafayette
Lincoln
Manitowoc (S0_ only)
Marquette
Menotninee
Monroe
Oconto
Pepin
Polk
Price
Rusk
Sauk
Sawyer
Shawano
Sheboygan (SO only)
Taylor
Trempealeau
Vilas (S02 only)
Washburn
Waupaca
Wa^-shara
1970-1990
growth
factor
1.88
1.35
1.19
1.16
1.72
1.17
1.13
1.10
1.22
1.14
1.38
1.21
1.32
1.22
1.37
1.14
1.10
1.01
1.15
1.36
1.22
1.18
1.20
1.38
1.09
1.45
1.33
1.23
1.40
1.08
1.57
1.18
1.13
1.17
1.66
1.23
1.18
1.31
1.15
1.74
1.45
1.30
1.37
Emission density
(ton/yr/sq mi)
1972 1990
Estimate Projection
PM SOx PM SOx
0.3
6.8
0.7
0.3
0.9
13.0
2.6
2.2
5.6
1.7
0.4
NR
1.1
NR
1.5
6.1
0.3
0.8
1.5
9.3
4.1
7.5
0.1
5.9
NR
0.9
0.6
4.0
1.6
3.1
4.5
1.4
1.1
4.0
0.2
1.7
NR
1.2
4.0
NR
0.4
4.8
1.0
0.4
9.7
1.1
0.5
1.3
18.5
3.3
3.0
6.3
2.2
0.5
24.5
1.4
38.9
1.6
10.1
0.3
1.2
1,8
10.6
5.3
12.4
0.1
7.5
37.9
1.5
0.9
5.7
2.7
4.5
6.4
2.1
1.7
3.0
0.4
2.8
55.1
1.8
5.7
1.4
0.6
8.0
1.6
0.6
9.2
0.8
0.3
1.5
15.2
2.9
2.4
6.8
1.9
0.6
NR
1.5
NR
2.1
7.0
0.3
0.8
1,7
12.6
5.0
8.9
0.1
8.1
NR
1.3
0.8
4.9
2.2
3.3
7.1
1.7
1.2
4.7
0.3
2.1
NR
1.6
4.6
NR
0.6
6.2
1.4
0.8
13.1
1.3
0.6
2.2
21.6
3.7
3.3
7.7
2.5
0.7
29.6
1.8
47.5
2.2
11.5
0.3
1.2
2.1
14.4
6.5
14.6
0.1
10.4
41.3
2.2
1.2
7.0
3.8
4.9
10.0
2.5
1.9
3.5
0.7
3.4
65.0
2.4
6.6
2.4
0.9
10.4
2.2
Projected
air quality
(ug/m3)
PM S0x
36.3
41.1
36.4
36.2
36.8
44.5
37.6
37.3
39.8
37.1
36.3
NR
36.8
NR
37.2
39.9
36.2
36.4
37.0
43.0
38.8
41.0
36.1
40.5
NR
37.2
36.4
38.7
37.2
37.8
40.0
37.0
36.7
38.6
36.2
37.2
NR
36.9
38.6
NR
36.3
39.5
36.8
8.2
11.7
8.4
8.2
8.6
14.1
9.0
8.9
10.2
8.7
8.2
16.3
8.5
21.3
8.6
11.2
8.1
8.3
8.6
12.0
9.8
12.1
8.0
10.9
19.6
8.6
8.3
10.0
9.1
9.4
10.8
8.7
8.5
9.0
8.2
9.0
26.2
8.7
9.9
8.7
8.3
10.9
8.6
Note: NR - not required - ,
Assumed background: 36 |ig/m PM, 8 ug/m SO
Geometric mean is used for PM
Arithmetic mean is used for SO
51
-------
Ui
N3
TABLE 7.
Current
Countv ^rowth
;->-/-)
Ashland
Columbia ~
Door -"-
Eau Claire J-
Fond du Lac (TSP only) +
Grant (TSP only) +
Manitowoc (TSP only) +
Marathon x
Marinette v
Oneida +
Pierce +
Portage +
Rock +
Sheboygan (.TSP only) +
Verpon +
Vilas (TSP onlyl +
Wood ^
NAAQS
CATEGORY 2 ANALYSES FOR TSP AND S02 (t^g/m3)
Projected .^^ ,sp
^rowth - ., _
" L. u o Pro jectea
Lactor
:R :R :CR
1 . 24 ' c . 3 !5.9*
1.42 -3.9 26
"'.'S -<".6 41,4
1.20 56,, 60.4
1.20 .:.,: ;>.-i
1.09 ~2.^ 64.8
1.31 -6.3 49.5
1.14 37 3 58.1
1.60 38.9 40.6
1.43 35.3 50
1.42 --5.9 50
1.24 r'3,4 1:7,2*
1.18 33.3 39
1,12 ' 1 : 'l <
1,62 22.7 37
1,17 -r'-.c 65.9
o ^/m?
24 hr
1^76
\R
,64
"6
241
156
136
.47
215
143
134
261
176
314
62
223
99
375
150 u
TSP
roiected
NR
194"
Q3
27«-
180*
1 5
-------
quality near the short-term TSP standard have the potential for violating the
standard in the next 10 years. The combined effects of emission reductions
at existing sources and growth in emission sources on air quality should also
be assessed.
The remaining Wisconsin counties were included in the AQMA designation
analysis and hence fall into category 3. Table 8 shows the results of steps
1 and 2 for these counties. Actual growth factors (i.e., current value/base
value) for population, total earnings (employment), and manufacturing earnings
(employment) are shown in columns 2 to 4, along with the projected growth
factors used in the designation analysis, the values in parentheses. Employ-
ment and earnings growth factors were taken to be interchangeable for this
analysis. The actual growth factors were obtained from the population pro-
jections cited previously, and from 1974 County Business Patterns, the latest
edition available. Because the designation analysis treated the four-county
Milwaukee SMSA as a unit, values for the SMSA were also included in the table.
Dane, Outagamie, Racine, and Winnebago Counties, and the Milwaukee SMSA
required no analysis beyond step 1. No projected growth factors were avail-
able for St. Croix County;>V hence no analysis could be conducted. The re-
maining counties' growth rates required the aggregate emissions loadings be
calculated (step 2). 1974 emissions were thus calculated from the actual
growth factors and 1970 emissions data from the designation analysis. These
values were compared to projected values obtained by interpolation between 1970
and 1975 values used in the designation analysis.
In three out of the four counties, the current estimate of emissions ex-
ceeded the forecast value. Two of these counties are in designated AQMAs;
a subpart D analysis is currently being conducted for Brown and Kenosha
Counties. No further action is required in these counties; however, it would
be prudent to reassess the projections of population and employment being
utilized in the subpart D analysis.
LaCrosse County is not in an AQMA. The next step in the guidelines is a
reassessment of the validity of the growth projections used in the condensed
analysis. It was not possible to do so and no new projections were available.
Consequently, it was assumed that the actual 1970 to 1974 growth rate would
continue over the next 10 years. Using this as a new projection, the con-
densed analysis was revised. The results of this analysis indicates that
the NAAQSs will not be violated.
OXIDANTS
A designation analysis for oxidants was also conducted for Wisconsin's
SMSAs. All areas were automatically excluded from AQMA designation, except
for the Milwaukee, Racine, and Kenosha SMSAs. These areas had oxidant con-
centrations in 1972 above the 320 ug/m3 level. Again, detailed AQMA analyses
for these areas have not been completed, so that categorization was done on
the basis of the designation analysis.
The State of Minnesota is presently conducting the AQMA analysis for this county.
53
-------
TABLE 8 . CATEGORY 3 ANALYSES FOR TSP AND S02
County
Brown
Dane
Douglas
Kenosha
LaCrosse
Milwaukee
Out garni e
Ozaukee
Racine
St. Croix
Walworth
Washington
Waukesha
Winnebago
Milwaukee
SMSA
Population
growth factor
(1975/1970)
1.07
1.04
.99
1.07
1.03
1!
1.04
1
1.04
1.12
1.08
I
f
1.01
1.02
(1
(1
(1
(1
(1
ft*
(1
ft*
(1
.02)*t
.10)
.06)
.08)
.08)
.07)
.07)
(NA)
(NA)
**
ft*
(1
(1
.07)
.08)
Earnings
growth factor
(1974/1970)
1
1
1
1
1
1
1
1
1
1
.21 (1
.17 (1
.16 (1
.30 (1
.27 (1
NA
NA
.18 (1
.21)
.24)
.19)
.16)*
.22)*
.24)
.39 (NA)
.15 (NA)
NA
NA
.09 (1
.07 (1
.23)
21)
Manufacturing
earnings
growth factor
(1974/1970)
1
1
1
1
1
1
1
1
1
0
.11 (1.
.02 (1.
.28 (1.
.28 (1.
.01 (1.
NA
NA
.10 (1.
19)
20)
20)*
05)*
20)
23)
.45 (NA)
.25 (NA)
NA
NA
.09 (1.
.99 (1.
23)
19)
1974 TSP
emissions
(ton/year)
13,090 (12,380)*
NR
2,340 ( 2,340)
1,880 ( 1,670)*
2,530 ( 2,450)*
NA
NR
NA
NR
NA
NA
NA
NA
NR
NR
1974
S02 emissions
(ton/year)
NR
NR
NR
6,280 (5,670)*
5,570 (5,370)*
NA
NR
NA
NR
NA
NA
NA
NA
NR
NR
*
Actual growth exceeds projection
Actual (projected)
^Included in Milwaukee SMSA
NA - Not applicable
NR - Not required
-------
Category 1 counties for oxidants are presented in Table 9, along with the
projected gasoline sales per square mile for 1990, for all counties project to
have positive growth. These values were obtained by projecting 1967 gasoline
sales to 1990 by population growth factors. Because no county was projected
to exceed the 1990 critical density value, further analysis was not required.
Category 2 counties are presented in Table 10, along with the results of
the second step of the growth monitoring analysis. Because current gasoline
sales data were not readily available, positive growth was assumed for these
counties (step 1). Also, because a county-by-county emission inventory was
not readily available, the proportion of HC emissions from light-duty vehicles
was obtained from the appropriate AQCR emission inventory in the 1972 NEDS
summary.
Because Dane and Wood Counties are not currently violating NAAQS, pro-
jected oxidant concentrations were calculated. Both counties are projected
to not violate the NAAQS in 1990, and hence are exempt from further analysis.
The remaining three counties are currently in violation of the NAAQS, requir-
ing calculations of expected reductions in HC emissions. As the table shows,
the projected reductions are less than the required reductions determined from
Appendix J. The regional administrator should thus be notified. Dane is an
urban county which includes the capitol city, Madison. Wood county is rela-
tively rural.
The remaining counties, shown in Table 11, fall into Category 3 for pur-
poses of this analysis. The table shows projected growth factors used in the
designation analysis along with actual growth factors obtained from the same
sources as the factors in Table 8. The Milwaukee SMSA is treated as a unit
in the designation analysis; hence no values are included for the individual
counties contained in it. Furthermore, the growth indicator used to project
emissions in the Milwaukee SMSA was average daily travel (ADT). Because auto-
matic traffic recorder data are available on a regular basis for this area,
ADT was used as the growth factor in this analysis. Finally, employment growth
factors were substituted for earnings as in previous sections of this analysis.
As the table shows, the emission projections have not been exceeded.
NITROGEN OXIDES
The entire State of Wisconsin was automatically excluded from AQMP analy-
sis for N0£. Thus, for this study counties were characterized only by the
availability of monitoring data.
Since the threshold levels for Category 1 countines had not been gener-
ated at the time of this illustration, the areas which exceed these levels and
should initiate monitoring for NOo could not be determined.
Category 2 counties for N02 are shown in Table 12, along with the results
of steps 1 through 4 of the growth monitoring analysis. Two counties, Douglas
and Milwaukee, are experiencing negative growth rates. The remaining counties
all show positive growth rates, but none show sufficient growth to cause a
potential violation of the NAAQS.
55
-------
TABLE 9. CATEGORY 1 ANALYSES FOR OXIDANTS
County
Adams
Barron
Bayfteld
Buffalo
Burnett
Calumet
Chippewa
Clark
Crawford
Dodge
Door
Dunn
Eau Claire
Florence
Fond du Lac
Forest
Grant
Green
Green Lake
Iowa
Jackson
Juneau
Kewaunee
LaCrosse
Lafayette
Lincoln
Manitowoc
Marathon
Marinette
Marquette
Menominee
Monroe
Oconto
One id a
Outagamie
Pepin
Pierce
Polk
Portage
Price
Rock
Rusk
St. Croix
Sauk
Sawyer
Shawano
Sheboygan
Taylor
Trempealeau
Vernon
Washburn
Washington
Waupaca
Waushara
Winnebago
1990 Gasoline sa^es density
I4al/nu-
2,938
21,871
2,346
4,123
6,462
28,514
17,685
8,064
7,316
23,298
25,146
14,102
57,633
NA
47,464
4,430
16,796
20,111
14,643
6,605
11,128
12,585
12,325
68,724
10,511
16,955
40,232
17,923
9,738
10,110
NA
27,230
11,665
2,227
71,363
14,094
20,300
20,173
33,470
3,158
83,242
4,477
26,221
20,958
5,474
11,715
62,574
8,404
14,947
8,891
8,023
100,948
21,312
12,746
106,143
NA - Not available
56
-------
TABLE 10. CATEGORY 2 ANALYSES FOR OXIDANTS
County
n 4. v Population
Current X ., ,; .
growth factor
Proportion of HC
from LDV
Emission
from
reduction . ,
FMVCP Projected
Emission
reduction
required
(expected)
Brown
Columbia
Dane
Vilas
Wood
392
316
130
252
152
yg/m3
yg/m3
yg/m3
yg/m3
yg/m3
1.
1.
1.
1.
1.
26
18
11
45
14
0.
0.
0.
0.
0.
57
57
57
52
52
0.
0.
0.
0.
0.
09
09
09
09
09
NA
NA
69.5
NA
91.8
0.64 (0.
0.52 (0.
NA
0.35 (0.
NA
39)
43)
24)
NA - Not applicable
-------
TABLE 11. CATEGORY 3 ANALYSES FOR OXIDANTS
oo
County
Kenosha
Milwaukee
Ozaukee
Racine
Washington
Waukesha
Milwaukee SMSA
1970 - 1975
Population
growth factor
1.07 (1.08)*
NAt
NAt
1.04 (1.07)
NAt
NAt
NA
1970 - 1974
Total employment
growth factor
1.30 (1.16)
NA
NA
1.18 (1.24)
NA
NA
NA
1970 - 1974
Manufacturing
employment
growth factor
1.28 (1.05)
NA
NA
1.10 (1.23)
NA
NA
NA
1970 - 1975
ADT
growth factor
NA
NA
NA
NA
NA
NA
1.08 (1.22)
1974
Aggregate
emission
loading
7673 (8204)
NR
NR
NR
NR
NR
NR
^Actual (projected)
tIncluded in Milwaukee SMSA
NA - Not available
NR - Not required
-------
TABLE 12. CATEGORY 2 ANALYSES FOR N02
County
Brown
Columbia
Dane
Door
Douglas
Eau Claire
Kenosha
LaCrosse
Marathon
Marinette
Milwaukee
Rock
Vernon
Wood
Current 1976 - 1990
growth Growth factor
+ 1.26
+ 1.18
+ 1.11
+ 1.32
NR
+ 1.14
+ 1.25
+ 1.10
+ 1.24
+ 1.11
NR
+ 1.18
+ 1.10
+ 1.14
1990 Projected
annual average concentration
44.7
17.4
34.9
8.2
NR
26.2
31.8
46.2
25.8
12.7
NR
43.3
19.7
33.4
NR - Not required
59
-------
TIME REQUIREMENTS
Time required to complete the growth monitoring for Wisconsin was dis-
tributed approximately as follows. Data collection from state and census
bureau sources required about 1.5 person days. Categorizing counties for all
pollutants required reviews of the AQMA designation analysis and of monitoring
data reports. Total time required was 6 person-hours.
The Category 1 analysis for TSP and SC>2 only required checking growth
rates. This was accomplished in about 1 person hour. The Category 2 analysis
required somewhat more time to calculate growth factors and to analyze air
quality data, a total of about 4 person hours. The Category 3 analyses
required the greatest time. Actual growth factors were calculated from
population and employment data. (These growth factors were also used in
later analyses). Projected growth factors and emissions loadings had to be
obtained by interpolation between values used in the designation analysis.
Total time required for this category was about 1.5 person days.
The analysis for oxidants required less time than the TSP and SOo
analysis. Projecting gasoline sales for the category 1 counties occupied the
largest block, about 6 person-hours. Calculating projected air quality and/
or emission reductions for Category 2 counties required approximately 3 person-
hours, as did checking the growth factors used in the designation analysis
against actual growth for the Category 3 counties.
The N09 analysis required the shortest time period because only two
categories were involved and the analysis was relatively simple. Approximately
2 person-hours was spent on each category.
The illustration was terminated at the point where a condensed analysis
of the combined effects of growth and compliance schedule progress should be
completed for several counties. Up to this point, the illustration required
slightly less than 1 person week. The remaining analysis, an abbreviated
analysis of growth including the effects of compliance schedules, should take
approximately 1 additional person day.
60
-------
SECTION 6
ILLUSTRATION OF GUIDELINES IN MASSACHUSETTS
A Volume 1 designation analysis was conducted for all SMSAs in Massachu-
setts in 1974. A detailed AQMA analysis for S02 and TSP was also conducted
for the entire state. However, this analysis was found to be inadequate in
light of subsequent guideline revisions, and a new analysis is currently being
performed. Because the new analysis was not complete at the time this illus-
tration of the guidelines was performed, the "old" AQMA analysis has been
assumed valid for the purposes of this study. The principal difference in
methodology between the two AQMA analyses involves the length of the projection
period. Given this situation, a finding that any county requires an AQMA anal-
ysis because of unforeseen growth must be recognized as only illustrative, and
not directly applicable in practice since a new analysis with revised projec-
tions is being prepared.
In the original AQMA designation analysis, all areas of the state were
automatically excluded from being designated as AQMAs for NOX; no recent analy-
sis of growth and air quality is available for this pollutant for any part of
the state. Two areas of the state (Boston and Springfield) have transporta-
tion control plans (TCP); hence, a detailed analysis has been completed for
these areas. The remainder of the state has no recent analysis available for
CO and oxidants; except for Boston and Springfield, all areas of the state
were originally excluded from consideration as an AQMA for CO and oxidants.
However, all areas of the state have subsequently been designated as an AQMA
for CO and oxidants. The county categorizations are presented in Table 13.
SUMMARY
The illustration of the guidelines took approximately 2 person weeks.
Over half of this time was devoted to the development of data on a county
basis. Massachusetts is relatively unique in that counties are unimportant
governmental units; consequently, planning data is seldom summarized on a
county basis. Most air quality control regions, regional planning districts,
and standard metropolitan statistical areas do not follow county boundaries.
The application of the guidelines indicated that the actual growth since
the preparation of the projections used in the PM and SOX subpart D AQMA
analysis probably has been quite different than the forecast growth in the
projections. Further, the projections ate now of questionable validity; new
projections have recently been prepared. The application of the guidelines
thus indicates that the existing detailed analysis for PM and SOX should be
revised. This is currently being done, albeit for a different reason.
61
-------
TABLE 13. CATEGORIZATION OF MASSACHUSETTS COUNTIES FOR
GROWTH MONITORING ANALYSES
County
Barnstable
Berkshire
Bristol
Dukes
Essex
Franklin
Hampden
Hampshire
Middlesex
Nantucket
Norfolk
Plymouth
Suffolk
Worcester
Pollutant
so2
4
4
4
4
4
4
4
4
4
4
4
4
4
4
TSP
4
4
4
4
4
4
4
4
4
4
4
4
4
4
0
X
1
2
2
1
4
2
4
4
4
1
4
4
4
2
NO 2
2
2
2
1
2
2
2
1
2
1
2
2
2
2
CO
5
5
5
5
6
5
6
5
6
5
6
5
6
5
Notes:
1 = County without monitoring.
2 = County with monitoring.
3 = County with condensed analysis.
4 = County with detailed analysis.
5 = County without detailed analysis (CO).
6 = County with detailed analysis (CO).
62
-------
No assessment of the validity of the growth projections for CO could be
completed, as no estimates of regional VMT have been prepared since preparation
of the TCPs. Estimates of VMT are currently being prepared.
Aside from the areas covered by TCP's, three counties have monitoring for
oxidants, all are showing violations of the NAAQS. The analysis conducted to
illustrate these guidelines indicates that two of them have the potential for
continuing to violate the NAAQS in 10 years. Thus the regional administrator
should be notified.
The application of the first steps of the guidelines indicated only one
county has the potential for violating the NO^ NAAQS in 10 years. Further
analysis indicates that, after considering the effects of the FMVCP, there is
not a potential for a violation.
S02 AND TSP
As previously noted, AQMA analyses for these pollutants were conducted for
the entire state on an AQCR basis. This allowed each county to be placed in
category 4. The first step in the growth monitoring analysis for this category
involves checking the projections used in the AQMA analysis.
The indicators used for these projections were population, total employ-
ment, manufacturing employment, and commercial (nonmanufacturing) employment.
Projections of these items were prepared by the Office of State Planning (OSP)
for 1978, 1980, and 1985, with 1972 as the base year. Projections were done
on a town-by-town basis. It was thus necessary to sum and check these values
for the counties.
Updated values for monitoring growth of the indicators were obtained
from various sources and are presented in Table 14.* One additional item is
called for in Step 1 of the Category 4 analysis, namely total point source
emissions for each county. Massachusetts emissions inventories are currently
summarized only by AQCRs and thus could not be immediately used. Given the
results presented in Table 14, Step 2 of the analysis should be conducted
for all counties except Suffolk. This step consists of estimating current
area source emissions by applying the actual growth factors for the analysis
year, adding point source emissions to compute the county total emission load-
ing, and comparing this value to the loading projected in the AQMA analysis.
*Population was available only through the 1973 Current Population Reports
(CPR) issued in June 1975. OSP is producing 1977 estimates (the first offi-
cial state estimates since 1971) but they will not be completed for some
time. Table 14 includes 1973 population projections from the AQMA analyses
and 1973 CPR estimates. A comparison of growth factors (i.e., current year/
base year) rather than absolute values would have been desirable, to account
for possible differences in base year values. However, no CPR estimates
were available for 1972. Employment data were available for 1972, 1973, and
1974 from County Business Patterns. (The 1975 edition will be available
within 2 to 3 months.) Table 14 presents 1974 growth factors calculated
from CBP.
63
-------
TABLE 14. CATEGORY 4 ANALYSES FOR TSP AND SO,
ACTUAL (FORECAST)
County
Barnstable
Berkshire
Bristol
Dukes
Essex
Franklin
Hampden
Hampshire
Middlesex
Nantucket
Norfolk
Plymouth
Suffolk
Worcester
Statewide
1972-1974 1972-1974
, . total employment manufacturing employment
growth factor growth factor
113,151(104,083)
148,988 (150,770)
459,540(443,137)
7,050(6,201)
646,596(653,468)
61,177(59,745)
460,652(467,539)
135,369(127,801)
1,416,429(1,424,284)
4,303(3,844)
616,172(628,493)
367,177(355,841)
713,415(721,244)
649,397(652,918)
5,799,416(5,799,368)
1.23(1.00)
1.07(1.02)
1.10(1.07)
1.11(1.00)
1.09(1.05)
1.06(1.00)
1.10(1.02)
1.34(1.01)
1.12(1.06)
1.18(1.00)
1.16(1.06)
1.15(1.07)
0.95(1.04)
1.09(1.05)
1.08(1.05)
1.71(0.98)
1.06(1.02)
1.11(1.01)
0.76(0.98)
1.11(1.01)
1.17(0.98)
1.06(1.01)
1.20(0.98)
1.07(1.06)
1.22(0.99)
1.13(1.06)
1.22(1.05)
0.81(1.03)
1.13(1.01)
1.07(1.03)
-------
However, after considering the wide divergence between the current estimates
and forecast values, it is clear that a current estimate of emissions would
exceed the forecast amount. Consequently, step 2 was omitted and step 3, the
assessment of the validity of the projections of population and employment,
was conducted.
New projections of population and employment are currently being prepared.
The employment projections are complete, the population projections were not
finished at the time of this analysis. The projections were made by regional
planning districts which can be aggregated to AQCRs. A comparison of the growth
factors obtained from the new and old projections is shown in Table 15. The
new projections are quite different from the old projections; therefore, the
detailed analysis should be revised to reflect the new projections. As noted
earlier, this is currently being done.
OXIDANTS
AQMA analyses for oxidants have not been conducted in Massachusetts. The
Metropolitan Boston AQCR and the Springfield portion of the Pioneer Valley AQCR
were automatically designated for oxidants because they require transportation
control plans. All other areas were automatically excluded due to a lack of
monitoring data at that time. Since then more monitoring data has become avail-
able and all areas of the state have been designated as AQMAs for CO and oxi-
dants. However the analysis has not yet been completed for these areas.
For this analysis any county of which any portion is included in a desig-
nated AQMA is considered to be a Category 4 county. (Worcester County is an
exception, as only the Town of Warren is included in the Springfield AQMA.)
Three counties, Barnstable, Dukes, and Nantucket, fall under Category 1. The
first step in the analysis, collection of county gasoline sales data, is diffi-
cult in Massachusetts, because gasoline taxes, a potential source of this in-
formation, are paid by suppliers on bulk cargoes. Furthermore, for Dukes and
Nantucket Counties, gasoline sales data are not reported in Census documents
because of disclosure problems; i.e., a small number of establishments serve
each county. Because of this situation, these two counties were excluded from
further analysis. It is highly unlikely that these counties have a potential
oxidant problem; they consist entirely of Martha's Vineyard, Nantucket, and
the Elizabeth Islands.
Gasoline sales data for Barnstable County were obtained from the 1972
County and City Data Book for a base year of 1967. This source reports sales
in dollar amounts only. The average price per gallon in 1967 was thus obtained
from the Bay State Gas Retailers Association so that sales in gallons could be
estimated. A positive growth in sales was assumed, and projected sales for
1986 were determined, using population as a growth indicator. These calcula-
tions, and the resulting gallons-per-square-mile figure are shown below. The
result is less than the critical value for 1986 obtained from the guidelines,
indicating that no further analysis is needed.
$16,211,088 (total gasoline sales) x AQ »OA (average 1967 price per
gallon) x 1.71 (1967 - 1986 population growth factor) x -o^r (square
miles) = 211,188 gallons/square mile.
65
-------
TABLE 15. COMPARISON OF 1972-1985 PROJECTIONS
AQCR
1973 Most recent
projections projections
used in AQMP (1977)
Manufacturing Employment
Berkshire
Pioneer Valley
Central
Merrimack
Southeastern
Metropolitan Boston
Berkshire
Pioneer Valley
Central
Merrimack
Southeastern
Metropolitan Boston
1.31
0.97
1.14
1.15
1.00
1.30
Nonmanufacturing
1.17
1.14
1.43
1.34
1.09
1.44
0.84
0.95
0.86
0.94
0.88
0.93
Employment
1.33
1.27
1.06
1.25
1.40
1.22
66
-------
Three counties, Berkshire, Franklin, and Worcester, fall into Category 2.
Again, because gasoline sales data required for Step 1 were difficult to ob-
tain, positive growth was assumed. Because all three counties are currently
in violation of the NAAQS of 0.08 ppm, the second step of the analysis is to
determine whether the expected reduction in HC emissions due to FMVCP will be
sufficient to maintain NAAQS for the projection year given projected growth.
Table 16 presents the data and results for the three counties in question.
The proportion of HC emissions from LDV was obtained from the 1972 NEDS emis-
sion summaries for the appropriate AQCRs. Required concentration reductions
were determined using Appendix J. Two counties show potential violations of
the NAAQS and thus the regional administrator should be notified. Franklain
is a rural county; Worcester is predominantly urban.
The remaining Massachusetts counties fall into Category 4. However, the
AQMA designations were automatic, and no subpart D AQMA analysis has yet been
performed. Thus, no growth monitoring analysis for these counties is possible
or actually needed in practice at this time.
N02
As noted above, all counties in Massachusetts were automatically excluded
from AQMA analyses for N0~. Counties are thus categorized by the availability
of current monitoring data. The thresholds in Step 2 of the Category 1 analy-
sis had not yet been generated at the time of this analysis, so only the growth
in Category 2 counties was reviewed.
Category 2 counties for NCL are presented in Table 17, which shows the
results of Steps 1 through 4 of the growth monitoring analysis. Only Hampden
County is projected to violate the NAAQS of 100 yg/m3. It would thus require
a condensed analysis as presented in Appendix A. This analysis indicates
that the NAAQS will not be violated, principally due to the effects of the
FMVCP.
CO
Counties are placed in two categories for CO, namely those with detailed
analyses of traffic and air quality, and those without such analyses. In
Massachusetts, two metropolitan areas, namely Boston and Springfield, have
transportation control plans. However, the detailed analyses conducted for
these plans covered only part of each AQCR. Counties were thus categorized
by whether they were in large part included in these analyses. The results
are shown in Table 13.
For Category 6 counties the first step in growth monitoring is comparison
of current VMT or ADT with values projected in the detailed analysis. These
current values are not readily available for Massachusetts, so that no growth
monitoring analysis was conducted for Category 6 counties.
67
-------
TABLE 16. OXIDANT DATA AND CALCULATION RESULTS FOR
CATEGORY 2 COUNTIES IN MASSACHUSETTS
County
Berkshire
Franklin
Worcester
1976
maximum
°x
concentration
278 yg/m3
400 yg/m3
404 yg/m3
Population
growth factor
1976-1986
1.05
1.06
1.14
Proportion of"
HC emissions
from LDV
0.55
0.66
0.62
1986
Expected
cone.
reductions
0.44
0.53
0.46
Required
cone.
reductions
0.42
0.65
0.65
TABLE 17. CATEGORY 2 ANALYSES FOR NO,.
Current
County . ,
J growth
Barnstable +
Berkshire +
Bristol +
Essex +
Franklin +
*
Hampden +
Middlesex +
Norfolk +
Plymouth +
Suffolk
Worcester +
1976-1985
growth factor
1.25
1.05
1.10
1.18
1.04
1.09
1.09
1.11
1.20
NR
1.10
1985 projected
concentration
87.5
52.5
46.2
59.0
49.9
124.3
80.7
64.4
33.6
NR
83.6
Currently violating NAAQS.
68
-------
TIME REQUIREMENTS
Data collection was the most significant time requirement in the analysis,
requiring about 1 person week. The reason for this is that most data for Massa-
chusetts are summarized by towns, and county summaries required extensive
manual calculations. Approximately 1 person day was also spent in calculating
growth factors from disaggregate data. A review of the designation analysis
and monitoring data for categorization of counties required about 1 person day.
Calculations contained in most tables required only about 4 person hours to
complete. Checking the analysis and calculations and preparing a summary
report required approximately 3.5 person days, so that the total time spent on
the analysis was slightly more than 2 person-weeks.
69
-------
APPENDIX A
SCREENING METHODS FOR PROJECTING EMISSIONS AMD AIR QUALITY
In order to identify those areas of a state that are undergoing an amount
of development such that it presents a potential for a violation of the NAAQS
within a period of 10 years, it may be necessary, ultimately, to perform a sub-
part D AQMA analysis; i.e., an analysis following Volumes 7, 8, 12, and 13 of
the Guidelines For Air Quality Maintenance Planning and Analysis (hereafter
referred to as the "Guidelines"). The following procedures are presented as a
screening tool to identify those areas that, though they exceed preliminary
screening threshold criteria, would likely be shown in a subpart D analysis
to not present a potential for violating the NAAQS.
The following procedure is a modification of those presented in Chapters
4 and 5 of Volume I of the Guidelines, the AQMA designation analysis. It
should be considered the minimum level of detail acceptable for such an analysis.
METHODS FOR PROJECTING EMISSIONS
In order to identify those areas that could violate a NAAQS during a
10-year period, it will be necessary to first determine current emissions,
project these emissions 10 years (or more than 10 years if a 10-year projection
of population, employment, etc., is unavailable). From the projected emissions,
air quality can then be estimated by techniques presented and compared with
the applicable standards to determine if the area being considered should, in
fact, have a subpart D analysis conducted.
Estimating Current Year Emissions
For point sources prepare a source-by-source tabulation of emissions.
For area sources, it is unlikely that an area source inventory is avail-
able for the current year. Therefore, the county area source inventory must
be updated to reflect both growth since the preparation of the inventory and
the application of any applicable control regulations. Determine first the
base year emissions from the sources in the area source inventory and then
multiply by the following factors to account for growth:
70
-------
Fuel combustion employment or earnings
Industrial process manufacturing employment or earnings
Solid waste population
Miscellaneous population
Transportation (PM and SO ) population or, if available, VMT
X
It is not necessary to estimate current year transportation emissions for HC
and NO .
x
Projecting Emissions 10 Years
For HC and NOX emissions from transportation sources, the following for-
mula may be used to project emissions 10 years using the existing area source
inventory. (It is not necessary to make a calculation to determine the current
level of emissions for transportation sources):
where Q = Projected emissions in 10 years.
(Q ) . = Baseline emission from source category i.
B i
G. = Growth factor for source category i.
E = Emission factor ratio for source category i (see Table A-l).
Project future emissions from current year emissions for all source cate-
gories other than transportation using the formula:
QP = (QC}i (1 + D±E±) (2)
where Q = future emissions from source category i.
(Q ) = current emissions from source category i.
c i
D. = growth rate of emissions for 10 years for source category i.
E. = emission factor adjustment for source category i (applied only
to industrial process sources - for all other categories E = 1.
Growth rates (D in Equation (2)) for 10-year emissions growth are the same
as those used to estimate current emissions. That is, the percent increase in
total earnings or employment projected for 10 years may be used to project
emissions from fuel combustion. The percent increase in manufacturing earnings
or employment may be used for industrial processes; the percent increase in
population may be used for solid waste emissions, particulate matter and SO
71
-------
TABLE A-l. EMISSION FACTOR RATIOS
K>
Low
altitude
High
altitude
California
Base
year
1977
1978
1979
1980
1981
1977
1978
1979
1980
1981
1977
1978
1979
1980
1981
1936
0.
0.
0.
0.
0.
0.
0.
0.
20
23
27
32
40
.18
20
23
0.28
0.
0,
0,
0.
0.
0.
,35
,19
,23
.27
,34
.40
Light-duty
1987 1988 1989
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0,
0.
0.
16
18
21
25
30
12
14
16
,19
24
14
.17
,20
,25
,30
0.15
0.17
0.20
0.23
0.29
0.11
0.13
0.15
0.18
0.22
0.14
0.16
0.19
0.24
0.29
0.14
0.16
0.19
0.22
0.29
0.10
0.12
0.14
0.16
0.20
0.13
0.16
0.19
0.23
0.28
HC
1990 1986
0.12
0.13
0.16
0.19
0.28
0.09
0.10
0.11
0.14
0.17
0.12
0.14
0.17
0.21
0.25
0.40
0.44
0.48
0.53
0.58
0.33
0.37
0.41
0.45
0.50
0.40
0.44
0.48
0.53
0.58
Heavy-duty
1987 1988 1989
0.37
0.40
0.44
0.49
0.53
0.32
0.35
0.39
0.44
0.48
0.37
0.40
0.44
0.49
0.53
0.
0.
0.
0.
0.
36
39
43
47
52
0.31
0.
0.
0.
0.
0.
0.
0.
0.
0.
34
38
42
47
36
39
43
47
52
0.35
0.38
0.42
0.46
0.51
0.30
0.33
0.37
0.41
0.46
0.35
0.38
0.42
0.46
0.51
1990
0.29
0.31
0.35
0.38
0.42
0.25
0.28
0.31
0.35
0.38
0.29
0.31
0.35
0.38
0.42
1986
0.25
0.28
0.32
0.38
0.45
0.29
0.32
0.37
0.42
0.49
0.25
0.28
0.34
0.40
0.47
Light-duty
1987 198S 1989
0.23
0.25
0.30
0.34
0.41
0.27
0.29
0.33
0.38
0.44
0.24
0.27
0.32
0.38
0.45
0.22
0.24
0.28
0.33
0.39
0.25
0.28
0.32
0.36
0.42
0.23
0.26
0.32
0.37
0.45
0.19
0.21
0.25
0.29
0.34
0.21
0.24
0.27
0.31
0.36
0.22
0.25
0.30
0.35
0.42
NO
X
1990 1986
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
18
20
24
28
33
21
24
27
31
36
22
25
30
35
42
1.13
1.11
1.10
1.09
1.08
1.60
1.51
1.40
1.31
1.23
1.13
1.11
1.10
1.09
1.08
Heavy-duty
1987 1988 1959
1.
1,
1.
1.
1.
1,
1,
1.
1.
1.
1,
1.
1.
1,
1,
13
.11
.10
.09
.08
.63
.54
.42
.33
.26
.13
.11
.10
.09
.08
1.13
1.11
1.10
1.09
1.08
1.65
1.56
1.44
1.35
1.27
1.13
1.11
1.10
1.09
1.08
1.13
1.11
1.10
1.09
1.08
1.66
1.58
1.46
1.36
1.28
1.13
1.11
1.10
1.09
1.08
1990
1.13
1.11
1.10
1.09
1.08
1.77
1.68
1.55
1.44
1.37
1.13
1.11
1.10
1.09
1.08
Assumptions: FMVCP as of April 1977, Supplement 5 of AP-42
NOTE: The emission factor ratio is the projection year fleet composite emission factor divided by the base year fleet composite
emission factor. Areas where national assumptions for fleet composition, etc. are inappropriate should calculate a
localized ratio.
-------
emissions from transportation, and the miscellaneous category. For power
plants, it is again recommended that the state contact electric utility com-
panies directly.
An adjustment will be needed to account for control of new industrial pro-
cess sources because of new source performance standards. Generally, these
standards will be more stringent than limitations presently contained in the
SIPs. The adjustment needed to account for future new source performance
standards would be the ratio of the estimated percent allowable emissions under
the future new source performance standards to the percent allowable emissions
in the current year. These ratios should be estimated for each county on the
basis of its existing industrial mix. Using the point source inventory, de-
termine the proportion of emissions for each process. Use these proportions
to determine a weighted average of the E values for each process. This must
be done for each pollutant. Bear in mind that the "E" value applies only to
industrial process sources. For other source categories, use E = 1.
MODELING AIR QUALITY CONCENTRATIONS
Introduction
This section of the guideline presents information concerning models re-
commended for use in predicting future air quality, once future emissions have
been calculated.
Relating Oxidant Concentration to Hydrocarbon and NO Emissions
' ''' ' » -- - - - L - " - - _.___.._ J. 1. . I -- - I - - ^ ~ -
Appendix J to 40 CFR Part 51 "Requirements for Preparation, Adoption,
and Submittal to Implementation Plans" (published in the August 14, 1971 and
republished in the November 25, 1971 Federal Register) is being revised. It
is anticipated that the revision will allow one to determine the same infor-
mation, percent reduction required, on the basis of oxidant concentrations
and the HC/NOX ratio.
The revised Appendix J should be used as follows:
1. Project future HC and NOX emissions as shown in the previous section.
2. Determine the expected emission change by:
F F
base - future , nn<7
emissxon change = = x 1UIU
base
3. Determine the required percentage hydrocarbons emission reduc-
tions using Appendix J and the highest observed 1-hour oxidant
concentration during the baseline year.
4. If R required from Step 3 is greater than R expected from Step 2,
the area should be subjected to a subpart D analysis. This will
be especially true if the expected emission change is negative.
73
-------
Analytical Techniques for Other Pollutants-Relating Projected Emissions
to Air Quality
Proportional Roll-Forward Model
Present air quality may be projected 10 years for pollutants other than
oxidants and CO (i.e., air quality may be projected for TSP, S02, and NOX)
using the proportional roll-forward model as shown in the following formula:
^future .
xp - Q uc - XB; -i- XB
^current
where XP = projected air quality level
XR = background concentration
X = current air quality level
V_*
Q = projected emissions in 10 years
^future v J
0 = current year emissions
xcurrent
While the proportional roll-forward technique is a potential means for
selecting counties for more detailed analysis, it has several shortcomings
which may render it unsuitable, or impossible, to apply. There are:
1. Base year air quality observations are required.
2. The monitoring data must be representative of the area of
interest (i.e., a monitor dominated by a single point source
or a small number of select sources may result in anomalous
predictions.)
3. The meteorology occurring during the base period must be simi-
lar to that which is of interest during the period being modeled.
Where the above conditions apply with particular force, it may be appro-
priate to use the Hanna-Gifford model described in the next section. The
model* is based upon the integral of gaussian plume contributions from upwind
area sources. The ground level air pollutant concentration (x) is then
given by:
Hanna, S. R. A Simple Method of Calculating Dispersion From Urban Area Sources.
J. Air Poll. Contr. Assoc., 21:774-777, 1971.
74
-------
X =
Y2
Qa(x,y)
dx / -- exp
irUo a
y z
2a
dy
where x = surface concentration (yg/m )
2
Q - area source strength (yg/m /sec)
a
U = windspeed (m/sec)
a ,a = plume dispersion function (m)
y z
x = distance downwind from the source (m)
y = crosswind distance from the plume centerline (m)
With this assumption that the plumes are narrow (i.e., yj_ and y2 approach
OT) and that Q (x) is a function of x only, Equation (4) becomes:
a
D
X =
dx
(5)
0
where D = limit of integration (m) for which further contributions is
negligible.
To integrate Equation (5) in closed form, the vertical dispersion a is ex-
pressed in terms of the power law: z
a = ax
z
(6)
If the integration distance is broken into elements of length Ax, the fol-
lowing expression is obtained:
/T/Ax\ l
_ jiiirL
A. /i t_\
a(l - b) U
N /
Q0 + £ Q, (21 +
i = 1 1 V
- (21 - I)
l")
(7)
where x = concentration at the center of the receptor square
(i = 0) (ug/m3)
2
Q. = area source strength for upwind square (i) (yg/m /sec)
ty
In many cases the concetration contribution from neighboring square can be
neglected so that Equation (7) becomes simply:
75
-------
- b
Qo
The application of the Hanna-Gifford model is described in detail in
Volume 12 of the "Guidelines." Hanna-Gifford may be used to estimate both
short-term and annual average concentrations. It is of importance to note
that where relatively large point sources are known to affect the concentra-
tions in a county, it is considerably more accurate to estimate the impact
of these sources separately using an appropriate point source model. Volume
10 of the "Guidelines," Reviewing New Stationary Sources, has recently been
revised and provides a conveniently methodology for performing this task.
In addition, the basic point source dispersion models are available in the
UNIMAP system, a computer package that has been installed in several state
agencies and which can also be accessed through the EPA regional offices.
76
-------
APPENDIX B
SOURCES OF DATA
The sources of the data employed the guidelines presented in the previous
section are reviewed below. First, the suggested parameters to be used for
growth tracking in counties with a detailed analysis are identified. Second,
the typical sources of each data item cited in the previous sections is dis-
cussed. Finally, the method of collection, frequency, and geographic detail
of the more prominent sources are summarized.
PARAMETERS TO BE USED IN COUNTIES WITH DETAILED ANALYSIS
The parameters that are typically used to project emissions growth in a
detailed analysis are reviewed first; suggested indicators for tracking growth
are then discussed.
Given the relatively complex emission projection in a detailed analysis,
it is necessary to simultaneously monitor the growth trends of several indi-
cators. The recommended parameters* for projecting emissions are identified
in Table B-l. The parameters are delineated into three levels; the level that
was chosen for preparing an emissions forecast depended on the availability of
resources, required accuracy, and quality of the base year emission inventory.
While Table B-l indicates the parameters that were recommended in Volume 7 of
the Guideline for Air Quality Maintenance Analysis and Planning, many states
did not necessarily follow its recommendations in detail.
As might be expected, there is as yet little collected information on the
use or success of the Volume 7 techniques. Information for several states was
collected as part of a forthcoming feasibility study on computerization of the
techniques, and the reviews might be described as mixed." Data required by
the techniques, especially those from state and local planning agencies, were
often nonexistent, incomplete, or in hard to use formats. In at least one
state, projections for each AQMA had to be based on "vastly different" data
sources.9 In general, area source data were more difficult to obtain, and
cross-checking of sources often revealed contradictions. Point source data
collection was straightforward but very time consuming. Many states chose to
use data sources other than those suggested or required by Volume 7. However,
the Volume 7 recommendations and requirements were generally found to be "as
good as" others used by the states.
Due to the apparent variety in projection techniques that were employed
by the states in preparing a detailed analysis, it is not possible to specify
exactly which parameter should be used to now track the actual growth. The
77
-------
TABLE B-l. TYPICAL PROJECTION PARAMETERS
Source category
Level 1 parameter
Level 2 parameter
Level 3 parameter
CO
Industrial process
Earnings by 2 digit SIC
Residential Population
Commercial /institutional Commercial /institutional
earnings
Industrial (area source) Manufacturing earnings
Motor vehicles Population
Off highway Agriculture earnings
Railroads
Vessels
Marine gasoline
Aircraft
Electrical generation
Gasoline evaporation
Solvent evaporation
Interview
Interviews, DOT
nat. proj.
Population
Local airport plans
FAA nat. proj.
Interview, FPC data
Population
Population
Land use/industrial
growth studies
Land use plans
Land use plans
Land use plans
VMT
Agriculture land use,
construction
earnings
Interviews
Interviews DOT
nat. proj.
Population
Local airport plans
FAA nat. proj.
Interview, FPC data
VMT
Population
Interview
Land use plans
Interview point source
Interview point source
VMT by vehicle type
Agriculture land use,
construction
earnings
Interviews
Interviews DOT
nat. proj.
Population
Local airport plans
FAA nat. proj.
Interview, FPC data
VMT
Population
-------
parameters recommended below are based on the use of the projection technique
in Volume 7. Where a state adopted a modified approach to projecting emis-
sions, the appropriate growth tracking parameter should be obvious.
The recommended indicators for tracking growth in counties with detailed
analyses are given in Table B-2. The differences between Tables B-l and B-2
are obvious, primarily occurring because of the unavailability of the parameter
that was used to project emissions on an annual basis. A typical example is
the use of a land use plan to project emissions. Very few communities annually
update their land use inventory. (Those that have a parcel based geographic
information system, described in Appendix C, are a prime example of one that
would do so). Annual summaries of building permits issued are very easily
obtained in most communities or from national sources described later in this
section. The building permit provides the same level of detail and accuracy
as the land use plan and is thus an appropriate growth indicator.
The indicators in Table B-2 are also grouped by level; these are keyed
to the levels in Table B-l. If a county projected growth with a parameter
of a certain level, it should attempt to track growth with an indicator of
equal or higher level.
An indicator different from the one used to project growth may be used.
For example, though earnings were used to project industrial emissions, it
may be more convenient to track growth with manufacturing employment. In such
cases it is necessary to obtain an estimate of employment for the base year
of the analysis so that a growth factor may be constructed. If building
permits; i.e., the total floor area approved for construction in building
permits, are used to track growth, it is necessary to estimate the total floor
area of manufacturing and commercial/institutional establishments in the base
year.
In addition to tracking the growth in parameters that were used to pro-
ject area source emissions, the current aggregate emissions from point sources
should be estimated on a regular and periodic basis and compared with the pro-
jected point source emissions.
Current regulations require emissions dara for certain sources to be
updated on a semiannual basis. These sources include:
New sources or source modifications resulting in emissions of
100 tons a year of any criteria pollutant (1000 tons a year
for CO).
Sources meeting compliance schedule increments.
Major source shutdowns.
Sources subject to continuous monitoring requirements.
In addition, many states require regular renewals of source registrations or
permits, at periods ranging from 1 to 5 years, for most major sources. Thus,
79
-------
TABLE B-2. RECOMMENDED GROWTH TRACKING INDICATORS
Source category
Level 1
Level 2
Level 3
00
o
Industrial process
Residential
Population
Annual update of point source inventory
Residential Residential
building permits
building permits
Commercial/institutional Commercial/institutional Commercial/institutional Commercial/institutional
Industrial (area source)
Motor vehicles
Off highway
Railroads
Vessels
Marine gas
Aircraft
Electrical generation
Gasoline evaporation
Solvent evaporation
employment building permits
Manufacturing employment Manufacturing
building permits
Population Vehicle registrations
* *
building permits
Manufacturing
building permits
VMT
Population
Population
Population
*
*
Interview Interview
Interview Interview
Population Population
Interview Interview
-Annual update of point source inventory
vehicle registrations VMT
Population Population
"These sources may be ignored unless they are known to be significant sources in the county of
interest.
A current estimate of emissions should be prepared from recorded sales of gasoline and diesel oil
for off-highway uses at the state level and allocated to the county.
-------
point source growth monitoring under these guidelines will usually impose only
a minor burden on the responsible agencies.
TYPICAL SOURCES OF DATA ITEMS
The sources of the indicators utilized in the guideline for counties
without a detailed analysis are reviewed below.
Current Population Estimates
Estimates of the current populations of a counties are often compiled
annually by a state agencies such as the department of public health or
education. Annual estimates are also available from the U.S. Bureau of the
Census Current Population Reports Series P-25 and P-26. Frequently, the
problem will not be obtaining an estimate of the current population but
deciding which one of several available ones to use. In such cases the
regional planning agency should be consulted. Current population estimates
are usually available with a 6-month time lag.
Population Projections
Ten- and 20-year projections of population by county are commonly made
by a state planning agency or commerce department at irregular intervals.
Regional planning agencies may have also prepared their own projectors.
Utility companies and banks are also occasional sources of this data. Only
when regional or state data is unavailable should the BEA OBERS projections
be used. Projections are typically revised every 5 years.
Emission Inventories
A recent area source county emission inventory will usually be available.
If it is not, the one prepared annually by the National Air Data Branch (NADB)
of the Office of Air Quality Planning and Standards may be used.
Employment Estimate
Annual estimates of employment by county are often available from the
state employment security department. These estimates may include only
employment covered by unemployment insurance and must be adjusted so as to
reflect the total employment. The regional or state planning agency will be
able to air in this adjustment. Annual employment estimates may also be
available from banks, chambers of commerce, or economic development commis-
sions. Care should be taken to adequately adjust whatever estimate is used
K
There are often several single purpose regional agencies in an area besides
a multifunctional planning agency; e.g., regional transportation planning
agencies, and, of course, the regional air pollution agency. In general,
there will be one lead regional agency that provides comprehensive areawide
polity planning. Consult the National Association of Regional Councils
Directory2 if the identity of the regional agency is unknown.
81
-------
so it is compatible with the projections it is compared with. If regional
or state sources cannot provide employment data, it can be obtained from
Dunn and Bradstreet. Dunn and Bradstreet data is available with essentially
no time lag.
Earnings
Estimates of earnings are also often available from the same sources as
employment. These estimates will also have to be adjusted for coverage as
for constant dollars.
Estimates of Average Daily Traffic (APT)
ADT estimates on major facilities are made at various intervals by
county, regional, and state transporation planning agencies. The regional
transportation planning agency should be able to identify the best source of
this data, if it has not already compiled it.
Estimates of Regional Vehicle Miles Traveled (VMT)
A regional VMT estimate should be available from the same sources as ADT.
In addition, it is proposed that the states and metropolitan planning agencies
be required to report this data to the Federal Highway Administration (FHWA)
and the Urban Mass Transit Adminstration (UMTA) every 2 years in the Urban
Transportation Reporting System. States currently estimate county VMT on a
regular basis. Table B-3 presents a list of potential sources of this informa-
tion in each state.
Gasoline Sales
Sales of gasoline (or gasoline tax receipts) by county can often by ob-
tained from the state revenue office. Six states are known to compile this
information, shown in Table B-4.
DETAILED DESCRIPTION OF PROMINENT SOURCES
The data sources can be conveniently grouped into four categories, popula-
tion, employment, construction and motor vehicle and are summarized in Table B-5.
Table B-5 lists the data items, method of collection, frequency, and geographic
detail for each source.
Population
Census of Population
Public Law 94-521, signed in October of 1976, provides for a mid-decade
census which will furnace more frequent population counts and updates of the
characteristics of the population. The first mid-decade census will be taken
in 1985 and will not be as extensive as the decennial census. Table B-6 lists
the questions asked of households in the 1960 and 1970 censuses; the 100 per-
cent questions and some sample questions, although which of these and how many
of them has not been decided as yet.
82
-------
TABLE B-3. VEHICLE MILE DATA AVAILABLE IN 1973
State
Extent of data available
Department, name of contact, tel. no.
Alabama No data on vehicle miles kept by
county for all roads
Alaska Some data on gasoline sales by
county available
Arizona Annual vehicle mile data by county
for state roads only
Arkansas Annual vehicle mile data by county
for all roads
California Biannual vehicle mile dat.a available
by county for nil roads Ln "Histori-
cal State Highway, County Road and
City Street Statistics"
Colorado No annual vehicle mile data by
county or any related data
Connecticut No vehicle mile data or related
information available on a county
level
Delaware Annual vehicle mile figures by
county for all roads
Florida Annual gasoline sales figures by
county, based on tax receipts, for
fiscal year ending in June
Georgia Special report on 1971 vehicle mile
figures for all roads by county, no
material on an annual basis
Hawaii Annual vehicle mile data by county
for all roads and annual vehicle
registrations by county
Tdaho No annual vehicle .nile data
available, or any related data
Illinois Vehicle miles figures by county
for all roads every 3 years
Indiana ho data on vehicle miles kept by
county or any related data
Iowa Annual vehicle mile data by county
for all roads
KanttaH Annual vehicle mile data by county
for all roads
Kentucky Annual vehicle mile data by county
for all roads, tot/il of all counties
[nil appreciably short of statewide
total as given in FHWA "Highway
Statistics"
State Highway Dept., Bureau of Research
and Development, Mr. Lee
Telephone: (205) 269-7312
State Dept. of Highways, Planning Division
Mr. Eberhardt
Telephone: (907) 364-2121
State Highway Dept., Planning and Survey
Division, Mr. Green
Telephone: (602) 261-7252
Dept. of Highway Planning and Research
Division, Mr. Bingam
Telephone: (501) 569-2426
State Dept. of Public Works, Traffic
Department, Mr. Bailey
Telephone: (916) 445-3127
Dept. of Highway, Planning and Research
Division, Mr. Doland
Telephone: (303) 757-9262
Dept. of Transportation, Bureau of Planning
and Research, Mr. Bark
Telephone: (203) 566-2414
Bureau of Highway Planning
Mr. Shoe
Telephone:(302) 678-4343
Dept. of Transportation, Division of
Transportation Planning, Mr. Freggar
Telephone: (904) 488-4111
State Highway Dept., Division of Highway
Planning, Mr. Tenkin
Telephone: (404) 656-5460
Dept. of Transportation, Highway Planning
Division, Mr. Uehara
Telephone: (808) 548-7655
State Highway Dept., Planning and
Traffic Division, Mr. Sullivan
Telephone: (208) 384-2591
Division of Highways, Bureau of Research
and Development, Mr. Tornton
Telephone: (217) 525-7748
State Highway Commission
Technical Services
Telephone: (317) 633-5816
State Highway Commission, Division of
Planning, Mr. Studder
Telephone: (515) 296-1306
State Highway Commission, Planning and
Development Division, Mr. Button
Telephone: (913) 296-3841
Dept. of Highways, Division of Planning
Statistical Section, Mr. Blackmore
Telephone: (502) 564-2500
(continued)
83
-------
TABLE B-3 (continued)
State
Kxtent of data available
Department, name of contact, tel. no.
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Misslss Ippi
MlHuoiirl
Montana
Nebraska
Nevada
New Hatnpsh ire
New Jersey
Ne.w Mex Leo
New York
North Carolina
North Dakota
Annual vehicle mile figures for
state roads only in "Annual Report,
Louisiana State Highways"
Vehicle mile totals for all
roads by county
State road mileage figures
traffic counts for certain roads
"Traffic Trends" annual
No vehicle mile data or related
information available on a county
basis
No data on vehicle mile figures kept
by county or related information
No annual vehicle mile data avail-
able, or any related data
Annual vehicle mile data by county
for state roads only
Annual vehicle mile data for state
roads only
Vehicle mile figures by county for
all roads; 1969 and 1971 only from
special report
No data on vehicle miles by county
available on any related data
Annual vehicle mile figures by
county for all roads; in "Status
of Road Systems"
No vehicle mile data or related
information available on a county
basis
Annual vehicle mile figures by
county for state roads only
Annual vehicle mile data by county
for all roads in "New Mexico
Traffic Survey"
No vehicle mile data or related
information available on a county
level
No data on vehicle miles kept by
county or any related data
Annual vehicle mile data by county
for all roads in "Annual Traffic
Report"
Dept. of Highways, Traffic and Planning
Division, Mr. Reeves
Telephone: (502) 389-53A1
Dept. of Transportation, Bureau of
Transportation Services, Mr. Picher
Telephone: (207) 289-3131
State Highway Administration Office
of Planning, Mr. Cloonan
Telephone: (301) 383-4436
Dept. of Public Works
Planning Office, Mr. Genino
Telephone: (617) 7275124
Dept. of State Highways, Transportation
Planning Division
Telephone: (517) 373-2663
Dept. of Highways, Traffic Analysis
Division, Mr. Gildemister
Telephone: (612) 296-3147
State Highway De;pt., Traffic and Planning
Division, Mr. Livingston
Telephone: (601) 354-7172
State Highway Dept., Planning Section,
Mr. Klamm
Telephone: (314) 751-2825
State Highway Commission, Planning
Survey Div., Mr. Divine
Telephone: (406) 449-2564
State Highway Dept., Programming and
Planning Division
Telephone: (402) 477-6012
Dept. of Highways, Planning Survey
Division, Mr. Ross
Telephone: (702) 882-7080
State Dept. of Public Works
Planning and Economics Division, Mr. Lee
Telephone: (603) 271-3344
State Highway Department, Planning
Division, Mr. Green
Telephone: (609) 292-3530
State Highway Dept., Planning and
Programming Dept., Mr. Beechum
Telephone: (505) 983-7381
Dept. of Transportation, Office of Planning
and Development, Mr. Tweedis
Telephone: (518) 457-5540
State Highway Commission, Dept. of
Planning and Research, Mr. Former
Telephone: (919) 829-3141
State Highway Dept., Planning and
Research Division, Mr. Zinc
Telephone: (701) 224-2512
(continued)
84
-------
TABLE B-3 (continued)
State
Extent of data available
Department, name of contact, tel. no.
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
Souty Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
Wc'Ht Virginia
WlHconsIn
Wyoming
Annual vehicle mile figures by
county for state roads only "Ohio
Highway Mileage Report"
No data on vehicle miles kept by
county or any related data
Annual vehicle mile data by county
for state roads only
Annual vehicle mile figures by
county for state roads only
No vehicle mile data or related
information available on a county
level
No data on vehicle miles kept by
county or any related data
Annual vehicle mile data by county
for all roads
No data on vehicle miles kept by
county or any related data
Annual vehicle mile data by county
for all roads
Vehicle mile data for 1971 only
by county for all roads from special
traffic study
Vehicle mile totals for all roads
by county for 1970 only
No data on vehicle miles kept by
county or any related data
Annual vehicle mile data by county
for all roads
Vehicle' milt' figurew by county for
state roads, special study 1971 only
Annual vehicle mile data for all
roads by county.
Annual vehicle mile data by county
for state roads only
State Dept. of Highways, Division of
Planning and Programming, Mr. Whilkins
Telephone: (614) 469-2617
Dept. of Highways Current, Current
Planning Division
Telephone: (405) 521-2575
Dept. of Transportation, Traffic and
Engineering Div., Mr. Owens
Telephone: (503) 378-6277
Dept. of Transportation, Bureau of Trans.
Planning Statistics, Mr. May
Telephone: (717) 787-5983
Dept. of Public Works
State Traffic Engineer
Telephone: (401) 277-2694
State Highway Dept., Traffic and Planning
Division, Mr. Hammand
Telephone: (803) 758-3370
Dept. of Highways, Research and Planning
Division
Telephone: (605) 224-3278
Dept. of Highways, Research and Planning
Bureau, Mr. Werpool
Telephone: (615) 741-3687
Dept. of Highways, Research and Planning
Bureau, Planning Survey Div., Mr. Wright
Telephone: (512) 475-4846
State Dept., of Highways, Systems Planning
Division, Mr. Jester
Telephone: (801) 328-5707
Department of Transportation
Highway Planning Division, Mr. Leach
Telephone: (802) 828-2671
State Dept. of Highways, Div. of Traffic
and Planning
Telephone: (703) 770-2876
State Dept. of Highways, Dept. of
Planning and Research, Mr. Cummings
Telephone: (206) 753-6005
West Virginia Dept. of Highway Advanced
Planning Division, Mr. Brennan
Telephone: (304) 348-3113
Dept. of Transportation, Division of
Planning, Mr. Pamperin
Telephone: (414) 266-2752
State Highway Dept., Planning and
Programming Div., Mr. Caukel
Telephone: (307) 777-7552
Note: Annual contact with states that presently produce no relevant data is advisable. It
is likely that an increased number of states will adopt methods to tabulate vehicle
miles by county in the future.
85
-------
TABLE B-4. CONTACTS COUNTY SALES OF GASOLINE DATA
State
Contact
Arizona Mr. Dave Tweedie
Gas Tax Auditor
1739 W. Jackson
Pheonix, Arizona 85007
Florida State of Florida
Gas Bureau
Department of Revenue
Tallahassee, Florida
(904) 488-7417
Georgia Curtis B. Molding, Director
Motor Fuel Tax Unit
Department of Revenue
318 Trinity Washington Building
Atlanta, Georgia 30334
Louisiana Richard L. Clousing, Supervisor
Special Fuels Tax Unit
Department of Revenue
P.O. Box 201
Baton Rouge, Louisiana 70821
(504) 389-6223
Minnesota James F. Dagen, Director
Petroleum Division
Minnesota Department of Taxation
Centennial Office Building
Saint Paul, Minnesota 55101
New Mexico c. Tampin
Bureau of Revenue
State of New Mexico
Baatan Memorial Building
Santa Fe, New Mexico 87501
86
-------
TABLE B-5. SUMMARY OF NATIONAL AND COMMERCIAL DATA SOURCES
Source
Data
Method of collection
Frequency
of issue
Geographic
detail below
national
Comments
Population
Department of Commerce, Bureau
of the Census
Census of population
Current Population Reports
- Population Estimates and
Co Projections, P-25
- Federal State Cooperative
Program for Population
Estimates, P-26
Population: Census
race
age
sex
marital status
education Sample
employment
income
ethnic origin
Population estimates
Quinquennial
Annual
States, counties,
SMSA'S, cities,
census tracts
States, counties
The first- mid-decade/census will
be conducted in 1985
State and county population estimates
are published in both P-25 and P-26
Employment
Department of Commerce, Bureau
of the Census
Census of Manufacturers
- Area report
- Special report
Number of establishments Census
Employees
Production workers
Manhours
Value added
Cost of materials
Value of shipments
Capital expenditures
Inventories
Quinquennial
(for years
ending in "2"
and "7")
States, counties,
SMSA's, cities
Location of Manufacturing Number of establishments
Plants, Area Sequence by employment size
categories
States, counties
Data sorted by county by 4-digit SIC
Available on tape approximately
2 years after Census
-------
TABLE B-5 (continued)
Source
Data Method of collection , ?u
or issue
Geographic
detail below
national
Comments
Annual Survey of Manufactures
- Statistics for States,
SMSA's, Large Industrial
Counties, and Selected
Cities (AS-6)
Number of establishments Survey of 65,000
Employees firms
Payroll
Production workers
Production wages
Production manhours
Value added
Cost of materials
Value of shipments
Capital expenditures
End-of-year inventories
Annual, except States, counties,
for years SMSA's, cities
ending in "2"
and "7"
The information is presented
- by 4-digit SIC for the
state
- by county (not by SIC)
- by 4-digit SIC for SMSA's
- by 4-digit SIC for
selected counties
CO
CO
- Employment and Labor
Costs for Operating
Manufacturing Establish-
ments (AS-8)
County Business Patterns
Number of employees
Payroll
Number of establishments Treasury Form 941, Annual
Number of employees
First quarter payroll
Distribution of firms
by employment size
categories
Schedule A for
single establish-
ment firms
Mail questionnaires
to multi-
establishment
firms
States
States, counties,
SMSA's
nnd
Number of employees
Sales volume
States, counties.
Post Office, in-
dividual firm
Economic Information
Systems, Inc.
Number of employees
Sales volume
Estimated consumption
Estimated production
Data file con-
structed from:
- census reports
- corporate annual
reports
- industrial direc-
tories
- engineering
manuals
See text
States, counties,
Post Office, in-
dividual firm
Consumption and production
estimated using input/
output method; based on
-------
TABLE B-5 (continued)
Source
Data
Method of collection
Frequency
of issue
Geographic
detail below
nat ional
Comments
Construction
Department of Commerce, Bureau
of the Census
Current Construction Reports
Housing Authorized by By type of structure:
Building Permits - C40 ownership
number of units
value
Information reported Monthly, annual States, SMSA's,
by permit issuing permit issuing
places (Form C404) places
The monthly issue is a survey
of 4,000 more active places
The annual issue includes all
14,000 permit issuing places
00
MD
Bureau of Domestic Commerce
Construction Review
By type of structure:
ownership
value
Data collected by
Bureau of the
Census (C404
reports)
Monthly, annual States, 22 SMSA's Residential and nonresidential
construction
Nonresidential in 13 general
categories
Bureau of the Census
Unpublished data file:
CH:D1
Residential and Nonresi-
dential Permit Authorized
Construction
By type of structure:
number of buildings
authorized
value
number of units
(residential)
C404 reports Monthly, annual States, counties, Data file for C40 and
permit issuing Construction Review
places
Nonresidential in 14 general
categories
McGraw-Hill Information
Systems, F.W. Dodge
Division
Dodge Construction
Potentials
By 267 project types:
ownership
value
square feet
number of stories
number of units
(residential)
See text
Monthly, annual States, counties Reported on a job by job basis
-------
TABLE B-5 (continued)
Source
Data
Method of collection
Frequency
of issue
Geographic
detail below
national
Comments
Motor vehicle
Federal Highway Administration
and the Urban Mass
Transportation
Administration
Urban Transportation
Reporting System
(proposed)
Highway data:
road miles
lane miles
vehicle miles of
travel
passenger occu-
pancy
CBD cordon measurement
Demographic data:
population
dwelling units
employment
passenger vehicle
registrations
land"areas
R.L. Polk and Company
Motor Statistical Division Vehicle registrations
From states and
metropolitan
planning
organizat ions
Every 2 years
Every 2 years
Every 2 years
Every 4 years
Every 4 years
Every 2 years
Every 2 years
Every 2 years
Every 2 years
Every 2 years
From states' records Monthly, quar-
terly, annual
Urban areas
First publication expected
in 1979
States, counties,
towns, census
tracts
-------
1 TABLE B-6. CONTENT OF I960 AND 1970 CENSUS
Population items 1960, ? 1970, %
Relationship to head of household 100 100
Color or race 100 100
Age (month and year of birth) 100 100
Sex 100 100
Marital status 100 100
State or country of birth 25 20
Years of school completed 25 20
Number of children ever born 25 20
Employment status 25 20
Hours worked last week 25 20
Weeks worked last year 25 20
Last year in which worked 25 20
Occupation, industry, and class of worker 25 20
Activity 5 years ago - 20
Income last year:
Wage and salary income 25 20
Self-employment income 25 20^
Other income 25 20
Country of birth of parents 25 15
Mother tongue 25 15
Year moved into this house 25 15
Place of residence 5 years ago 25 15°
School or college enrollment (public or private) 25 15
Veteran status 25 15
Place of work 25 15
Means of transportation to work 25 15
Mexican or Spanish origin or descent - 5
Citizenship - 5
Year of immigration - 5
When married 25 5e
Vocational training completed - 5
Presence and duration of disability - 5
Occupation-industry 5 years ago - 5
Single item in 1960; two-way separation in 1970 by farm and nonfartn
income.
Single item in 1960; three-way separation in 1970 by social security,
public welfare, and all other receipts.
Q
This item is also in the 5-percent sample but limited to State of
residence 5 years ago.
Street address included in 1970.
Q
In 1960, whether married more than once and date of first marriage;
in 1970, also includes whether first marriage ended by death of spouse.
91
-------
State and local data is available on computer tape or in these four
reports:
PC(1)-A Number of Inhabitants
PC(1)-B General Population Characteristics
PC(1)-C General Social and Economic Characteristics
PC(1)-D Detailed Characteristics
Publications A and B are based on the 100 percent questions while C and D
are based on the sample questions.
Current Population Reports
State and county population estimates are published in Series P-25,
Population Estimates and Projections and in Series P-26 Federal-State
Cooperative Program for Population Estimates. The states furnish data on
vital statistics and other variables (depending on estimation method) to the
Bureau of the Census who calculates and publishes the estimates. Provisional
estimates and revisions are published each year. States which do not agree
with the estimates prepared under the Federal-State Cooperative Program
publish their own estimates in Series P-25. The state contacts for the pro-
gram are listed in Table B-7.
Employment
U.S. Department of Commerce, Bureau of the Census.
Census of Manufacturers
The Census of Manufacturers is part of the Economic Census series which
is published for the years ending in "2" and "7." Data is provided on the
number of establishments, employees, production workers, manhours, payroll,
inventories and other measures of industrial activity. The Area Series
gives statistics for the states, counties, and SMSA's. The data is listed
by 4 digit SIC code for the state, the SMSA's, and selected counties; gen-
eral statistics (not by SIC code) are given for all the counties.
Available only on computer tape is the Location of Manufacturing Plants,
Area Sequence which is part of the Special Reports Series. This data file
gives the number of establishments by employment size categories for each
4-digit SIC by county.
The other economic censuses are taken for the retail and wholesale
trades, the construction industries, mineral industries, and selected ser-
vices. Each of these censuses has an area report series which contains data
for states, counties, and SMSA's. All include the number of establishments,
employees and payroll, as well as other data.
Annual Survey of Manufacturers (ASM)
The purpose of the ASM is to provide data for the years when the census
of Manufactures is not conducted and so the variables contained in the ASM
reports are approximately the same as the Census. The ASM sample is com-
prised of 65,000 firms, including all firms (single- or multi-establishment)
with more than 250 employees.
92
-------
TABLE B-7. FEDERAL-STATE CO-OP PROGRAM CONTACTS
Mrs. Carolyn Sawyer
Center for Business and Economic
Research
Graduate School of Business
University of Alabama
Box AK
University, Alabama 35486
Mr. Robert B. Weeden, Director
Office of the Governor
Pouch AD
Juneau, Alaska 99811
Mr. David L. Gale
Alaska Department of Labor
Research and Analysis Section
Box 3-7000
Juneau, Alaska 99801
Mr. Jack Kronenfeld
Department of Economic Security
Bureau of Planning
Post Office Box 6123
Phoenix, Arizona 85005
Dr. Forrest Pollard
Industrial Research and Extension
Center
University of Arkansas
Post Office Box 3017
Little Rock, Arkansas 72203
Mr. Nelson Rasmussen
Population Research Unit
State Department of Finance
1025 P Street
Sacramento, California 95814
Mr. Richard Lin
Colorado Division of Planning
520 Centennial Building
1313 Sherman Street
Denver, Colorado 80203
Mr. Robert Odell
Vital Statistics Section
State Health Department
79 Elm Street
Hartford, Connecticut 06115
Mr. Bart Lewis
Bureau of Economic and Business Research
College of Business Administration
University of Florida
Gainesville, Florida 32601
Mr. Ronald Crowe
Office of Planning and Budget
270 Washington Street, S.W.
Atlanta, Georgia 30334
Mr. Robert C. Schmitt
Department of Planning and Economic
Development
Post Office Box 2359
Honolulu, Hawaii 96804
Mr. Shigeo Tengan
State Department of Health
Post Office Box 3378
Honolulu, Hawaii 96801
Mrs. Janet Wick
Bureau of Vital Statistics
Idaho Department of Health and Welfare
Statehouse
Boise, Idaho 83720
Mr. Clyde A. Bridger
Illinois Department of Public Health
535 West Jefferson Street
Sprinfield, Illinois 62761
Dr. Robert A. Calhoun
Indiana State Board of Health
1330 West Michigan Street
Indianapolis, Indiana 46206
Mr. James Taylor
Planning Support Unit
Office for Planning and Programming
523 E. 12th Street
Des Moines, Iowa 50319
Dr. Cornelia Flora
Population Research Laboratory
Kansas State University
Manhattan, Kansas 66506
93
-------
TABLE B-7 (continued)
Ms. Helen Gelof
State Planning Office
Thomas Collins Building
530 South DuPont Highway
Dover, Delaware 19901
Mrs. Barbara Denton
Research Division
College of Administration and
Business
Louisiana Tech University
Ruston, Louisiana 71270
Mr. Dale Welch
Research and Vital Records
State Department of Health and Welfare
Augusta, Maine 04330
Mr. Terry Lied
Maryland Center for Health
Statistics
State Department of Health and Mental
Hygiene
201 W. Preston St. O'Connor Building
Baltimore, Maryland 21201
Massachusetts (Vacant)
Mr. David Milstein
Office of the Budget
Lewis Cass Building
Post Office Box 30026
Lansing, Michigan 48913
Ms. Hazel Reinhardt
Minnesota State Planning Agency
101 Capitol Square Building
505 Cedar Street
St. Paul, Minnesota 55101
Mrs. Ellen Bryant
Department of Sociology
Mississippi State University
Post Office Drawer C
State College, Mississippi 39762
Dr. Mike Spar
Urban Studies Center
University of Louisville
Gardencourt Campus
Alta Vista Road
Louisville, Kentucky 40205
Ms. Vicki Stepp
Bureau of Business Research
The University of Nebraska
Lincoln, Nebraska 68508
Mr. Samuel Males
Bureau of Business and Economic Research
The University of Nevada
Reno, Nevada 89507
Mr. Thomas Duffy
Office of Comprehensive Planning
Executive Department
State House Annex
Concord, New Hampshire 03301
Ms. Shirly Goetz
Office of Business Economics
Department of Labor and Industry
Post Office Box 845
Trenton, New Jersey 08625
Mr. James McCormick
Bureau of Business Research and Econ.
Research
The University of New Mexico
Albuquerque, New Mexico 87131
Mr. John Smith
New York State Economic Development
Board
AESOB - 17th Floor
Post Office Box 7027
Albany, New York 12225
Ms. Francine J. Ewing
Office of State Budget and Management
N.C. Department of Administration
116 West Jones Street
Raleigh, North Carolina 27603
94
-------
TABLE B-7 (continued)
Mr. Mike Boxberger
Missouri Division of Budget and
Planning
State Capitol
Post Office Box 809
Jefferson City, Missouri 65101
Ms. Susan Selig Wallwork
Bureau of Business and Economic
Research
University of Montana
Missoula, Montana 59801
Mr. Roger Jacks
Research and Planning Division
Oklahoma Employment Security
Commission
310 Will Rogers Building
Oklahoma City, Oklahoma 73101
Dr. James Weiss
Center for Population Research and
Census
Portland State University - Box 751
Portland, Oregon 97207
Mrs. Nathalie Sato
Office of State Planning and
Development
Post Office Box 1323
Harrisburg, Pennsylvania 17120
Ms. Carmen G. Garcia de Laguerre
Puerto Rico Planning Board
Minillas Government Center
North Building, De Diego Avenue
Post Office Box 9447
Santurce, Puerto Rico 00908
Mr. Chester Symanski
Statewide Planning Program
Room 201
265 Melrose Street
Providence, Rhode Island 02907
Mr. Richard W. Blair
Division of Health Statistics
Department of Health
17th Floor - Capitol Building
Bismarck, North Dakota 58505
Ms. Arlene Eis
Office of Research
Department of Economic and Community
Development
30 E. Broad Street - State Office Tower
Columbus, Ohio 43215
Mr. Walter L. Cooley, Chief
Division of Public Health Statistics
State Department of Health
115 Colchester Avenue
Burlington, Vermont 05401
Dr. Julie Martin
Tayloe Murphy Institute
Graduate School of Business
Administration
University of Virginia
Post Office Box 6550
Charlottesville, Virginia 22906
Ms. Theresa Lowe
Population Studies Division
Office of Program Planning and Fiscal
Management
House Office Building
Olympia, Washington 98504
Dr. Leonard M. Sizer
Office of Research and Development
Center for Extension and Continuing
Education
West Virginia University
Morgantown, West Virginia 26505
Mr. Henry Krebs
Bureau of Health Statistics
State Division of Health
P.O. Box 309
Madison, Wisconsin 53701
95
-------
TABLE B-7 (continued)
Mr. Bobby Bowers
Division of Research and Statistical
Services
South Carolina Budget and Control
Board
1026 Sumter Street
Columbia, South Carolina 29201
Mr. Charles Sisk
Public Health Statistics
State Department of Health
Pierre, South Dakota 57501
Ms. Shirley King Hart
Tennessee State Planning Office
660 Capitol Hill Building
301 Seventh Avenue, North
Nashville, Tennessee 37219
Texas (Vacant)
Mr. Fred Doll
Division of Business and Economic
Research
College of Commerce and Industry
University of Wyoming
University Station - Box 3925
Laramie, Wyoming 82071
Mr. Gangu Ahuja
Statistical Systems Division
Office of Planning and Management
Munsey Building - Room 644
1329 E Street, N. W.
Washington, D. C. 20004
Mr. Kenneth Jensen
Utah Department of Employment
Security
174 Social Hall Avenue
Salt Lake City, Utah 84111
96
-------
The (AS)-6 series "Statistics for States, SMSA's, Large Industrial
Counties and Selected Cities' is the only ASM report with statistics for
substate areas. A "large industrial" county is defined as one having more
than 5,000 employees. The data included are the number of employees and
production workers, value added, cost of materials, value of shipments,
capital expenditures, and end-of-year inventories.
Other ASM reports which contain data for states are:
AS-4 Fuels and Electric Energy Used, by Industry Groups
AS-5 Expenditures for New Plant and New Equipment
AS-7 Book Value of Fixed Assets and Rental Payments
for Buildings and Equipment
AS-8 Employment and Labor Costs for Operating Manufacturing
Establishments
County Business Patterns (CBP)
CBP reports contain the number of establishments and employees, the
distribution of establishments according to employment size categories and
the first quarter payroll for all 2-, 3-, and 4-digit SIC codes except agri-
culture, mining, and public administration. Compiled annually, the data are
reported for states and counties with SMSA summaries by 2-digit SIC. The
information is obtained from Treasury Form 941, Schedule A (the reporting
form for FICA) for single establishment firms and from mail surveys of multi-
establishment firms. CBP reports are issued approximately 12 months after
the end of the calendar year of reference.
Dun and Bradstreet: Duns Market Identifiers
Dun and Bradstreet's primary function is a credit clearinghouse. In-
cluded among the data they collect on individual firms and establishments is
the parent firm, the management personnel, the number of employees, the sales
volume, and the SIC codes of the firm. The Dun's information can be provided
in a variety of ways, one way being a tabulation by geographic area (the
smallest is a zipcode area) and by SIC code(s). It is possible to purchase
a computer tape which contains the name, address and other information for
every firm in a state or other area (approximately $15,000 for Massachusetts).
Another possibility is a hard-copy tabulation of employment or sales volume
(in employment size categories) by 4-digit SIC code for each county (approxi-
mately $1500 for Massachusetts). An entry is updated when a credit inquiry about
the firm is received. If there are no inquiries, the name and address of the
firm is checked once a year. Dun and Bradstreet is sometimes slow to pick up
new entries and is weak in the retail sector, particularly in recording
branches of retail chains. A major advantage of the Dun and Bradstreet in-
formation is the availability of data on individual firms since the confiden-
tiality requirements of the Census are not applicable to D & B.
97
-------
Economic Information Systems, Inc. (EIS)
EIS collects information from census documents, corporate annual reports,
state and industrial directories, and engineering manuals. The data file
consists of the names, addresses, and parent companies of all manufacturing
establishments and mines having 20 or more employees. Also included in the
file are estimates of the consumption and production of the companies. These
estimates are obtained from input/output analysis based on the Census data
on consumption and shipments. The data file is updated quarterly using the
documents listed above and at irregular intervals on some industrial groups
with information furnished by EIS clients.
Construction
Current Construction Reports
Current construction reports provide data on housing units authorized,
started, completed, sold, demolished; total value of new construction put in
place; data on expenditures for additions, alterations, repairs on private
residential units in the United States. Most of this information is pub-
lished for census regions and occasionally SMSA's.
One exception is publication C-40, Housing Authorized by Building Permits,
which gives data for stated, SMSA's, and permit issuing places. The data,
which includes the ownership (public and private), the number of units by type
of structure (single-family, apartment building, etc.), and the estimated
value, is provided by permit issuing places. Approximately 4,000 more active
permit places form the basis for the monthly publication while the annual
publication includes all 14,000 permit issuing places.
Construction Review
Construction review, published monthly by the Bureau of Domestic Commerce,
contains information furnished by the Bureau of the Census and F. W. Dodge.
Most of the data is on a national level including construction put in place,
housing starts and completions, and contract awards. Data on residential and
nonresidential permit authorized construction is published for states and
22 SMSA's. Nonresidential data is given in the 13 general categories listed
in Table B-8.
The information received from the permit issuing places and reported in
publications C-40 and Construction Review can be obtained from the unpublished
data file CH:D1, "Residential and Nonresidential Permit-authorized Construc-
tion." The file, which contains the number of buildings authorized, the
estimated value and the number of units for residential construction, is or-
ganized by type of structure (in the same categories as C-40 and Construction
Review) for each permit place.
The data is available on computer tape and can be procured monthly (at
$50 per month), monthly with an annual summary ($650 per year), or in the
annual summary alone $$200 per year). A paper copy is available to govern-
ment users at no charge and contains data for each permit issuing place by
type of structure, grouped by county with county and state totals.
98
-------
TABLE B-8. CATEGORIES OF NONRESIDENTIAL CONSTRUCTION
Amusement and recreational buildings
Churches and other religious buildings
Industrial buildings
Parking garages
. Residential garages
Service stations and repair garages
Hospitals and other institutional buildings
Office, bank, and professional buildings
Public works and utilities buildings
Schools and other educational buildings
Stores and other mercantile buildings
Other nonresidential buildings
Structures other than buildings
McGraw-Hill Information Systems Company, F. W. Dodge Division
The Dodge Construction Potentials (DCP) report, for each construction
job, the square feet, the ownership, the value, the number of stories and,
for residential construction, the number of units for 267 project types,
including industrial construction by 2-digit SIC code.
The DCP data are collected primarily by a staff of reporters who obtain
information on new projects from architects, engineers, and major builders.
This information is supplemented by the use of newspapers and reports from
permit issuing places for projects valued under $50,000 and for less populated
areas. Adjustments are made to the file when a project is abandoned or can-
caled or when specification changes increase the value. Dodge estimates that
the DCP cover approximately 96 percent of all construction. The remainder
is mostly comprised of "force account" construction, which is work performed
by full time crews of industrial firms, utilities and local governments for
their own use. There is no size limitation on projects included in the Dodge
files.
The DCP are organized by county with category totals specified by the
user. Issued monthly with running or annual totals, the DCP are available
on computer tape, cards, or print-out. The cost of the DCP varies between
$1000 and $1500 for an individual state for the monthly data or an annual
total. Previous years' data can be acquired at a 40 percent discount. The
DCP for industrial categories alone can be purchased for 10 percent less than
the cost of the total data file.
99
-------
Motor Vehicles
Proposed Urban Transportation Reporting System
To satisfy the requirements of Section 15(a) of the Urban Mass Trans-
portation Act of 1964 (as amended) and to furnish the information required
by the FHWA to administer the Federal Aid Highway Program (23 CFR 1.5) and
the Transportation Improvement Program (Federal Register, Vol. 40, No. 181,
September 17, 1975, Paragraph 450.120A8vi), a national transportation report-
ing system has been devised. The highway and vehicle use portion is currently
undergoing review by the Office of the Secretary, after which it will be sub-
mitted to the Office of Management and Budget for review and publication in
the Federal Register. The current expectation of the UMTA is that the Phase I
data, listed in Table B-9, will be collected for 1978 for publication during
July of 1979. Table B-9 is a summary of the proposed data elements, the antici-
pated reporting intervals, the areas affected, and the implementation schedule.
The data will be collected by state highway departments and metropolitan
planning organizations.
R.L. Polk and Company, Motor Statistical Division
R.L. Polk collects vehicle registration data from states' records. The
data is tabulated by make, by model year and by type of vehicle (passenger
car, truck, etc.) for domestic and foreign vehicles and is available for new
registrations or total registrations monthly, quarterly or annually. The
smallest geographic area available is a census tract. R. L. Polk data are
available from EPA.
The "By Make By Year" series presents the total registration as of
July 1 for the state, counties and cities of more than 2,500 population by
make and model year of passenger cars and trucks. The "Three Column Count"
series gives the number of passenger cars registered, the number of trucks
registered and the total number of vehicles registered by county. R.L. Polk
reports are usually furnished in paper copy although other arrangements are
possible. The company declined to give a cost estimate because the cost to
a state depends on what arrangement Polk has with the state; to some states
the data is gratis while to others the cost depends on the number of counties
and detail required.
Review of State and Local Data
The various data items collected and compiled by the U.S. Bureau of the
Census are also generally available from state sources. The data discussed
here, then, are those that are typically collected only by the states or
local agencies.
New Source Review
The most important source of growth information for air quality planning
is the review of new air pollution sources. Current regulations call for a
state study of any new facility which will emit 100 tons or more of any
criteria pollutant per year (1000 tons for CO). The study must determine the
impact of the source on ambient air quality and the implications of the source
for SIP requirements. A number of states have lower threshold emission values
for identifying sources for review. New source review procedures should thus
provide the responsible agency with information on major sources.
100
-------
TABLE B-9. SUMMARY OF PROPOSED DATA ELEMENTS FOR THE URBAN TRANSPORTATION
REPORTING SYSTEM
Data element and classification
Reporting
interval
(years)
MPOs
affected
implemen-
tation phase
Highway data
Road miles
By functional classification 2 A*^c ^
By geographic area" 2 All 1
Lane miles of arterials during peak period 2 All 1
By functional classification of arterials
By number of lanes ,
By geographical area
By 1-way or 2-way direction
Miles of reversible lanes 2 All 1
Vehicle miles of travel ,
By functional classification 2 All 1
By geographic area° 2 A^e *
By vehicle type 4 - 2
Passenger occupancy 4 2
By vehicle type ,
By geographic area ,
CBD cordon measurement 4 - 2
Passenger occupancy
Vehicle type
Traffic volume and congestion 4 - 2
Demographic data
Population ,
By geographic area 2 All 1
Dwelling units ,
By geographic area 2 All 1
Employment , 2 All 1
By geographic area
By CBD
Passenger vehicle registrations 2 All 1
By county located in or containing urbanized area
By vehicle type
Land areas 2 All 1
By urbanized area
By central city
By central business district
By federal-aid system boundaries
Measurement of system performance
Highway system: land area and dwelling units within travel
time contours
From CBD 2 - S 1
From airport 4 - 8 2
From major non-CBD employment center 4 - 2
From major non-CBD shopping center 4 - 2
Transit system: land area and dwelling units within travel
time contours
From CBD 2 - 8 1
Metropolitan Planning Organizations.
Geographic areas: central city, outside central city, urbanized area.
Areas with population between 50,000 and 200,000 report only urbanized areas.
Functional type: interstate, freeways and expressways, other principal arterials, minor
arterials, collectors, and locals.
Only areas with population of 200,000 or more; a systemwide sampling method will be used.
Only areas with population of 750,000 or more.
80nly areas with population of 200,000 or more.
After census figures become available, dwelling units and population within contours will be
calculated on a 4-year cycle.
SOURCE: "Proposed Urban Transportation Data Reporting Requirements for States and Metropolitan
Planning Organizations," Transportation Research Board, National Academy of Sciences,
prepared for the Federal Highway Administration and the Urban Mass Transportation
Administration, U.S. Department of Transportation, 1976.
101
-------
Indirect Source Review
Federal new source review regulations initially required review of
indirect sources; i.e., new facilities associated with high levels of mobile
source activity. However, activities under these regulations have been
indefinitely suspended, and indirect source review is now a matter of state
discretion. Table B-10, which summarizes state data sources, indicates those
states with indirect source regulations currently in effect.^ The regula-
tions are typically based on the size of the facility, and require an analy-
sis of the air quality impacts of mobile activity. Regulations vary from state
to state with respect to the sizes and types of facilities subject to review.
Environmental Impact Statements
A number of states (indicated in Table B-10) require environmental impact
statements or assessments for various development activities.5 xhe types of
development requiring the statements vary from state to state; e.g., all
developments with significant environmental impacts, versus public projects
above a certain size. Statements typically describe the project and attempt
to quantify its environmental impacts. Some states also require development
permits for projects having "greater than local impacts."
Economic Development Agencies
Other potential state sources of growth information are various economic
development agencies. These agencies' activities typically include assembling
or banking sites for industrial development, and maintaining information on
state economic activities. These agencies may also be associated with state
universities or chambers of commerce. For example, the Bureau of Business
Research at the University of Texas publishes monthly statistics on industrial
expansion, including square footage and work force additions.°
Public Utility Data
Another possible data source, though one that shows considerable quality
variation from state to state, is public utility customer data. For example,
the Baltimore Air Quality Task Force used computerized files of meter types
and locations to allocate area source emissions for an air quality maintenance
planning analysis. However, the breakdown of customer data by facility types
or by subareas is not a standard part of utility reporting and might require
special analyses. Further, total area coverage is not guaranteed, as munic-
ipal distribution systems which purchase power from utility companies may be
exempt from data reporting requirements.
Local Data Sources
Local governments are usually concerned to some degree with monitoring
development, as a large part of their revenue comes from property tax receipts.
Hence, local assessment files are a potential source of information that is
regularly updated. The usefulness of these data, however, depends on the
extent to which they can be easily summarized; i.e., whether they are main-
tained in a computerized format. The exact extent of computerized assessment
files is not known. It is known, however, that only 140 of the approximately
14,000 assessing jurisdictions in the country use computer-assisted assessment
102
-------
TABLE B-10. STATE PROJECT REVIEW DATA SOURCES
State
Alabama
Alaska
Arizona
Arkansas
Californi i
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Sources:
indirect
source review
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
EIS
requirements
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Development
permits or
regulations
X
X
X
X
X
X
X
X
103
-------
methods; i.e., calculation of taxes from sales and property data.8 The actual
number of jurisdictions with computerized files might be significantly higher.
It is also important to note that local jurisdictions are the source of
building permits reported to the U.S. Bureau of the Census, and that these
data are thus fairly readily available.
104
-------
REFERENCES
1. Guidelines for Air Quality Analysis and Planning, Volume 7: Projecting
County Emissions. U.S. Environmental Protection Agency, Research Tri-
angle Park, North Carolina.
2. Directory. National Association of Regional Councils, 1700k St. N.W.
Washington, D.C. 20006. (202) 296-5253.
3. Interpretative Ruling for Implementation of the Requirements of 40 CFR
51:18.
4. LaBelle, S. J., D. A. Seymour, A. E. Smith and M. L. Harbour. The Balance
Sheet Technique Volume II - Preconstruction Review of Airports: Review
of State Regulations, Projects Affected and Resource Requirements. Argonne
National Laboratory, Draft Report of U.S. EPA Office of Transportation
and Land Use Policy (January 1977).
5. American Institute of Planners Research Office. Survey of State Land Use
Planning Activity. U.S. Department of Housing and Urban Development,
Washington, D.C. January 1976.
6. Texas Industrial Expansion. Bureau of Business Research, University of
Texas at Austin. 1:1 et seq.
7. Division of Program Planning and Analysis. Air Quality Maintenance Anal-
ysis for the Baltimore, Maryland Intrastate Air Quality Control Region for
Total Suspended Particulate Matter and Sulfur Dioxide. Bureau of Air
Quality and Noise Control Technical Memorandum 76-06. Maryland Department
of Health and Mental Hygiene. Baltimore. March 1976.
8. Partial List of Jurisdictions with Computer Assisted Assessment Systems
(Draft). International Association of Assessing Officers, Chicago,
Illinois, February 1975.
9- Cirillo, R. R. and M. J. Senew. Feasibility Study for the Development
of a Computerized Emission Projection and Allocation System: Phase I,
Preliminary Feasibility Study. Environmental Systems Division, Argonne
National Laboratory, Argonne, Illinois, November 1976.
105
-------
APPENDIX C
GEOGRAPHIC INFORMATION SYSTEMS
INTRODUCTION
In monitoring growth for air quality maintenance planning it is important
to know both the amount and the spatial characteristics of new development,
and to be able to operate with these data in an easy and efficient manner.
Therefore, as part of the development of a growth monitoring method, several
current geographic information systems were reviewed for their applicability
to the problem.
A geographic information system may be defined thusly: a combination of
a spatially defined data base and related analysis and presentation techniques
that allows the user to study spatial variations in selected data items. These
systems may or may not be computerized, but for this study only computerized
systems have been reviewed.
A geographic information system typically contains planning-type data
items referenced to a geographic coordinate or numbering system; e.g., the ex-
tent of a given land use in a given square kilometer. The data are obtained
from a number of sources; census data, maps, surveys, assessment records,
aerial photography, and satellite imagery may all be used. Because the systems
are generally designed for comprehensive planning purposes, a wide range of
data is included; viz, physical data such as soil types, slopes, and vegetative
cover, that can be used for site planning analyses and water quality planning;
cultural data such as land use, historic sites, and planning and zoning classes,
that comprise a basic land use planning inventory; and political or civil
districts, such as census tracts, townships, and planning districts, that make
possible easy retrieval and comparison of data from or for various jurisdictions
or purposes.
Raw data are generally classified and compiled as maps at a given scale.
The maps are then encoded by grid overlay techniques or by point or line
digitization. Actual storage and retrieval techniques vary from system to
system and are usually designed for specialized planning purposes. A typical
system would include computer mapping and data tabulation packages, allowing
the user to apply weights to selected data items or to "search" the data base
through conditional commands. For example, the user might want a map of all
developable lands zoned for heavy industry. He/she would define "developable"
from data items such as surface geology, proximity to roads, and proximity to
services and utilities. Resulting sites would then be screened with zoning
information, producing a map of all sites meeting the criteria.
106
-------
In general, the uses of these systems for air quality planning are lim-
ited. They provide land-use information that can be used for allocating area
source emissions as per the techniques in Volumes 7 and 132 of the AQMP
Guidelines, or by the application of land-use based emission factors. They
may also provide topographic information useful for facility siting studies.
However, they may be suitable for growth monitoring simply because they con-
tain land-use data that are in some way related to emissions, and can be used
to obtain summaries and analyses of these data with relatively little effort.
Two factors determine their final suitability, namely, the ease and frequency
of system updates, and the degree of detail of system data. Growth monitoring
is obviously impossible without regular updates, and lack of detail in the
data; e.g., insufficient information on land-use intensities, can severely
limit such applications.
A number of systems were identified for preliminary review, and are
described in some detail below. The reader should keep in mind that these
systems have been designed for planning at different governmental levels and
hence reflect different concerns. They may be thought of as falling along a
continuum whose end points might be termed "large-area" and "parcel-based"
systems. Large area systems are typically used for statewide or regionwide
planning. Because of their extent, that a detail must be limited somewhat to
keep the data base to a manageable size. Parcel-based systems are used for
county or local planning, and contain very detailed data. Thus, a large-area
system might contain the amount of land used for multifamily housing in a
given square kilometer, while a parcel-based system could include structural
characteristics of each multifamily building.
The question of data detail, and hence data collection costs, is central
to the problem of system updates. For most purposes, land-use information
is the subject of update efforts, as other system data are relatively fixed.
For large-area systems, it is generally agreed that remote sensing techniques
offer a cost-effective means of obtaining land-use information. However,
there are limits to the detail available through remote sensing, and other
techniques may be less costly for small areas. Parcel-based systems are ty-
pically linked to real estate tax assessment files, which are updated regu-
larly to avoid loss of revenues. Assessment information thus provides a
relatively simple means for updating land-use information in these systems.
Regarding data detail and the use of remote sensing techniques, the
reader should be aware of the land-use classification system most widely used
with remote sensing data. This is the U.S. Geological Survey (USGS) Land
Use and Land Cover Classification System.^ The system is based on the levels
of detail available with various remote sensing techniques and the needs of
planning agencies. Table C-l provides a brief summary of the system's charac-
teristics and logic.
Classifications for Levels I and II have been developed by USGS. Classi-
fications for Level III and beyond are developed by each user for his partic-
ular purposes. Most air quality planning to date has required land-use data
at Level III or higher detail; e.g., number of dwelling units, floor/area
ratios.
107
-------
TABLE C-l. USGS LAND USE AND LAND COVER CLASSIFICATION
SYSTEM CHARACTERISTICS
Classification
level
Typical data
characteristics
Example of
classification
category
II
III
IV
V
LANDSAT or
other satellite
imagery
High-altitude photography
at 40,000 feet or above;
less than 1:80,000 scale
Medium-altitude photography
at 10,000 to 40,000 feet;
1:20,000 to 1:80,000 scale
Low-altitude photography
at 10,000 feet or below;
more than 1:20,000 scale
Ground surveys; more than 1:2,000 scale
Urban or
built-up land
Residential
Single-family
units
Ten dwelling
units/hectare
Ten dwelling
units/hectare,
5-6 rooms/
dwelling units
108
-------
The reader should also be aware of the factors affecting the costs of
obtaining data by remote sensing techniques. Interpretation is the generally
most expensive element of a survey. Resolution, accuracy, and ease of inter-
pretation is a function of photo height. Clearly, the lower the photo height,
the greater the data detail and hence the amount of information that must be
interpreted. However, higher altitude photography yields less detail and hence
increases the difficulty of interpretation. Photo flights thus tend to be
custom-tailored to the data needs of the client agency.
The interpreted data must also be ground-checked for accuracy, as inter-
pretation is a somewhat subjective process. A skilled interpreter can gen-
erally achieve "ground truth" better than 90 percent if the classification
categories are congruent with the data scale and detail.
PRELIMINARY REVIEWS
As noted, a number of systems were originally identified for review.
Preliminary reviews of seven systems were conducted via literature reviews
and telephone discussions with the agency personnel responsible for the sys-
tems. Characteristics of interest were system applications, the scale, detail,
and age of system data, update procedures, data sources, and system costs and
funding sources. This section presents a brief description of each system
and the review results.
The seven systems reviewed were: the New York State Land Use and Natural
Resource Inventory (LUNR); the Maryland Automated Geographic Information Sys-
tem (MAGI); the Fairfax County Urban Development Information System (UDIS);
the Charlotte-Mecklesburg Planning Commission Land Use File; the Wilmington
Metropolitan Area Planning Council (WILMAPCO) Land-Use File; the New Castle
County Automated Environmental Resource Information Systems (AERI); and the
San Diego Polygon Information Overlay System (PIOS-II).
Three of these systems, LUNR, MAGI, and UDIS, were selected for more
detailed review. The results of these reviews, and of the reviews of three
land-use mapping projects relevant to the project concerns, are presented in
subsequent sections.
The results of the preliminary review are summarized in Table C-2. The
reader should be aware of one point in interpreting the table. Because sys-
tems are designed for different purposes, cost comparisons are not especially
meaningful. Further, some systems have incurred pilot program and development
costs which are not relevant to later systems. Finally, some totals include
software development costs while others represent only data collection and
computerization costs.
Several other systems are under development at this time. Because they are
not yet complete or in-use they have not been reviewed. These include the
Alabama Resources Information System (ARIS), the Minnesota Land Management
Information System (MLMIS),5 and four systems under development by Environ-
mental Systems Research Institute in California and Pennsylvania.6
109
-------
TABLE C-2. SELECTED GEOGRAPHIC INFORMATION SYSTEM CHARACTERISTICS
System name
LUNR
MAGI
UDIS
Charlotte-
Mecklen-
burg Land
Use File
Wilmington
Land Use
File
AERI
PIOS-II
Responsible agency
New York State
Economic Develop-
ment Board
Maryland Office of
State Planning
Fairfax County (VA)
Office of Research
and Statistics
Charlotte-Mecklen-
burg Planning
Commission
Wilmington (Del.)
Metropolitan Area
Planning Council
Nev Castle
County Areawide
U'aste Treatment
Management Program
Comprehensive
Planning Organization
of the San Diego
Region
Year system Development Development Size of Basic data Update Year current Air quality
established cost funded by: study area unit frequency data collected planning use
1968 5800,000 New York, 140,000 km2 1 km2 None 1967-68 Yes
HUD,
Appalachian
Regional
Commission
1974 $200,000 Maryland, 31,865 km2 92 acres As available 1973 No
HUD, NASA
1973 $735,000 Fairfax 1,046 km2 Parcel Continuous 1976 Yes
County,
HUD
1972 $1,200,000 Mecklenburg 1,406 km2 Parcel Annual 1976 No
County,
HUD
1976 $100,000 Delaware, 1,134 km2 Parcel Annual 1974 No
New Castle
County, HUD
1975 $150,000 EPA 1,134 km2 5.7 acres As needed 1974 No
1974 $58,000 San Diego 11,036 km2 Polygon 2 years 1975 Yes
RCOG, HUD
UMTA
-------
All the systems contain data that are potentially useful for air quality
planning, namely land uses. However, as noted previously, data detail is of
some importance, as is the way in which data are coded. For example, a
Level III classifibation is of little value for a 1 knr grid cell if the cell
is assigned a single value representing only the primary land use. There-
fore, methods of coding land-use data were examined and are summarized in
Table C-3. The adequacy of the data for air quality planning was evaluated by
comparison with the data requirements for Volumes 7 and 13 of the AQMP
guidelines.
TABLE C-3. LAND-USE CODING TECHNIQUES
System name
LUNR
Coding technique
2
Percent of each km
Highest
classification
level
III
Adequacy
for air
quality
planning
yes
with a given land use
MAGI Primary and secondary uses, III no
presence only
UDIS Primary land use, with V yes
structure characteristics
Charlotte-Mecklenburg Up to five land uses, with V yes
Land-Use File structure characteristics
WILMAPCO Primary and secondary V yes
Land-Use File uses, with acreages and
structure characteristics
Q
AERI Primary, secondary and III yes
testiary uses with
acreages
PIOS-II Area of each land use stored NA yes
as a polygon
o
Additional measures of intensity may be required for some uses.
The New York State Land Use and Natural Resource Inventory (LUNR) con-
tains land use, economic, and physical data for each of the 140,000 square
kilometers in New York State. Data were obtained from low-altitude aerial
photography flown from 1967 to 1970, from USGS maps, and from state geological
and engineering maps and surveys.^ Development cost of LUNR was approximately
$800,000, with $700,000 going to consultants and contractors. Roughly 70 per-
cent of the cost was for airphoto interpretation, with the remaining costs
split between the actual photo flights and computerization of the data. Data
were coded by a grid overlay technique. Data values are the percentages of
111
-------
were coded by a grid overlay technique. Data values are the percentages of
each square kilometer having a certain value or characteristic.
LUNR data are available as airphotos, standard land use maps, computer
produced maps, data summaries for user-selected variables and areas, and data
tapes. The computer mapping programs allow the user to weight variables and
to sort data by using conditional criteria. This allows the user to quickly
identify areas with certain characteristics, as is required in critical re-
source studies or site suitability analyses.
LUNR is currently maintained by the New York State Economic Development
Board, and is available to public and private users on a fixed-cost basis.
System data and products are available for any or all parts of the state.
LUNR has been used most of 10 as a data base for comprehensive planning, but
the age of the data tends to limit current applications. LUNR uses are sum-
marized in Table C-4.
Update procedures for LUNR at the statewide level do not currently exist.
A pilot project to update data for two counties was funded by the Appalachian
Regional Commission, and was recently completed. ^ Other updates have been
conducted by local and regional agencies, but there are no current plans for
statewide data collection. The problem of updates is discussed in more detail
in the following sections.
LUNR land-use data have been used for air quality maintenance planning
in a fashion similar to the Volume 7 and 13 techniques. Another project
involved application of land-use based emission factors to LUNR data as part
of a regional plan evaluation. These applications are discussed in the
detailed review in the following section.
The Maryland Automated Geographic Information System (MAGI) contains data
for 88,000 separate grid cells, each containing 92 acres (2,000 ft by 2000 ft)
comprised of the state of Maryland and its surface waters. The data are
divided into three general categories. "Capability variables" are those which
determine whether an area can support a given activity. "Suitability varia-
bles" are used to determine whether an area should support the activity.
"Special Study Variables" are used to extract other data from the system by
special-purpose districts.
MAGI data were obtained from 30 different sources, including USGS and
Soil Conservation Service Maps and maps and surveys by various state agencies.
Initial development cost was approximately $200,000. Development occurred in
three phases, with funding in the first and last phases by the state of Mary-
land and HUD. The second phase, involving software development and a test of
the applicability of ERTS data, was funded by NASA.1^
MAGI data can be output as maps or statistical summaries, and various
analysis models are available for data manipulation. These latter are used
to identify special features, such as urban centers, from combinations of
system data variables.
112
-------
TABLE C-4. USES OF LUNR INVENTORY PRODUCTS ACCORDING TO TYPES OF RESPONDENTS
Types of uses
Category of respondent
State agencies
Regional planning
agencies
County planning
agencies
Local planning and
associated agencies
Conservation commissions
and environmental ad-
visory boards
Consulting firms and
private industry
Miscellaneous public
and private users
Total
Basic land
use informa-
tion file
for admin-
istrative
purposes
3
6
10
2
3
2
3
29
Basic
land use
comprehensive
planning
purposes
2
9
18
1
13
4
47
Exam-
inations
of land
uses in
special
zones
6
3
6
1
4
8
28
Identi-
fications
of pat-
terns of
specific
land uses
4
3
3
1
2
5
18
Open space
& environ-
mental
management
studies
4
5
1
13
10
5
38
Project
reviews
for environ-
mental
impact
5
2
2
16
25
Special
studies
& miscel-
laneous
2
1
3
1
2
4
13
26
Unsuc-
cessful
Instruc- or in-
tional complete
uses uses
8
2
1
2
8
6
16 9
16 36
No detailed
response
(usually
due to
lack of
familiarity)
11
1
10
3
2
9
10
46
Total
45
25
58
11
31
66
73
309
Areawide land use and development planning.
Source: Reference 9, Table 3.
-------
Current land-use data was obtained from 1973 aerial photography. The pre-
sent land-use classification system falls between land-use information to only
Levels II and III, but coding techniques limit two categories in each grid cell.
MAGI was originally conceived as a data base for preparation of a state
land-use plan. Its main uses to date are capability and suitability analyses
for state planning projects. The Maryland Energy and Coastal Zone Administra-
tion has contracted for the use of MAGI for siting major facilities; e.g.,
power plants, in the coastal area. Oak Ridge National Laboratory has also used
MAGI for tests of the power plant siting program developed by ORNL personnel.
Various small-area analyses have also been conducted. Local agencies use the
MAGI data, and often update it or collect other data in the same format. The
Baltimore Regional Planning Council, for example, will use MAGI to develop
sections of its Section 208 Regionwide Water Quality Plan. There are, however,
no provisions for entry of these data into state files.
In general, agencies designated for Federal planning functions; e.g.,
A-95, 3-C, or Section 208 agencies, have used MAGI sparingly, for various
reasons. The Metropolitan Washington Council of Governments decided not to
use MAGI data because comparable data were not available for the Virginia
portion of the metropolitan area.15 T^e Baltimore Air Quality Task Force
chose not to use MAGI data for AQMP preparation because land-use intensity
was not sufficiently detailed.16 MAGI is discussed in more detail in a sub-
sequent section.
Fairfax County (Va.) Urban Development Information System (UDIS) contains
data for approximately 150,000 parcels of land. System data include existing
and planned land use, various geographic (district) references, assessment
information, zoning information, building permits, building plans, and sewer
facilities. Data were obtained from various county sources, including the
county real estate assessment file, public works records, and water authority
records and aerial photos. The assessment file was previously computerized,
simplifying transfer of data to UDIS. Total funding for the development of
UDIS was $735,000, with $351,000 from HUD and $384,000 from Fairfax County.
It has been estimated that developing a system similar to UDIS in a compara-
ble county would cost approximately, $250,000, with $45,000 for computer costs
and $205,000 for administrative and personnel costs.1?
UDIS data are available to users as standard summary reports, or as maps
or tables produced for special needs. The system is designed to provide data
useful for numerous planning functions in the most usable format. The purpose
of the system is to monitor all relevant aspects of development in Fairfax
County.
One of the most valuable aspects of UDIS is its update procedure. Since
the system is largely based on the county assessment file, it can be updated
almost simultaneously with the assessment data. Furthermore, the assessment
file is updated regularly to prevent loss of county revenues. Other informa-
tion, such as rezoning applications and building permits, is also added on a
regular basis. Further, construction progress is monitored through permit
and inspection data.
114
-------
The present applications of UDIS include: "land-use planning, public
facility programming, revenue projection, land-use control research and
evaluation, population movements, and housing estimating and forecasting."
Data are provided to all county offices and various state and regional
agencies.
UDIS is discussed in more detail in a subsequent section.
The Charlotte-Mecklenburg (N.C.) Land-Use File is a parcel-based file
similar to UDIS. It is also linked to the county assessment file and hence
updated annually. It contains data for approximately 125,000 parcels, includ-
ing five levels of land-use information, structure characteristics, and var-
ious location codes.18
Development cost for the entire assessment and land-use file system was
approximately, $1,200,000, including software. Data coding costs were ap-
proximately $1 per parcel. The system was funded by Mecklenburg County and
by HUD for comprehensive planning applications. '
System data are used by various agencies. The planning commission uses
the data base for community development planning. The system has also been
used by the Police and Fire Departments. System access is available through
a program package which generates summary reports. The planning commission
also maintains an in-house programming capability for special applications.
The Wilmington (Del.) Metropolitan Planning Council Land Use File is
another parcel-based file. It was developed from county tax maps and compu-
terized files and land-use information. It contains multilevel land use and
acreage information, along with parcel numbers and other geographic codes;
e.g., traffic zones. Development cost was approximately, $100,000, or about
$1 per parcel.
Updates are (or will be) conducted annually from tax records. The tax
files are now updated weekly, but no direct link to the land-use file exists.
This means that the annual update must be done manually from revised tax maps.
The file is used primarily to produce land-use summaries for comprehen-
sive planning purposes.
The New Castle County Automated Environmental Resource Information System
(AERI) is a grid-based file covering the same geographic area as the WILMAPCO
Land-Use File. The data base contains information for approximately 49,000
5.7-acre grid cells. The system is designed for water quality planning and
hence contains detailed physical and land cover data, as well as land use,
utility, and planning and zoning information. Land-use data is coded by
predominant and secondary types; i.e., most prevalent and second most pre-
valent uses in a cell, and the classification scheme corresponds approximately
to Level III detail.
Data were obtained from a number of local, state, and federal sources.
Land-use data were obtained from special-purpose aerial photography. The
total cost of system development and data collection was approximately,
115
-------
$150,000, funded by EPA through the Section 208 program. The system incor-
porates software for searching, mapping, and overlaying data files for various
analyses. Outputs include two types of maps and data summaries.
The agency hopes to be able to use the system for other planning applica-
tions and hence recognizes the need for updating land-use information. At
the present time no update procedure has been developed, but an effort is
being made to incorporate any authorized subdivisions and rezonings.22
The San Diego CPO Polygon Information Overlay System (PIOS-II) contains
physical, denographic, and land-use data for San Diego County. The data are
encoded as polygons, through line digitization techniques, and may be re-
trieved in either polygon or grid cell formats.^ The agency has found that
the grid cell format is more useful, especially when three or more data files
must be overlaid. System development cost was approximately $55,000 with
funding from HUD, UMTA, and the San Diego CPO, which represents the regional
council of governments.
PIOS-II land-use data were originally obtained from 1971 aerial photo-
graphy. These data were updated by comparison with 1975 aerial photos ob-
tained from San Diego County. The CPO recognizes the need to update land-use
information, and plans to do so at 2-year intervals, using aerial photos.
Various sources of photography were explored, including NASA high-altitude
(U-2) flights, but none were found to cover the entire county on a regular
basis. Therefore, special-purpose flights will probably be conducted for the
updates.
PIOS-II has not been used as a system for air quality planning, but land
use and activity summaries prepared from system data have been used to allo-
cate emissions to a grid system for model studies. This effort was conducted
as part of the air quality maintenance planning process for San Diego County.
On the basis of the preliminary review, three systems were selected for
more detailed study: LUNR, MAGI, and UDIS. LUNR was chosen, even though it is
somewhat dated, because of its use in the development of some Air Quality
Maintenance Plans (AQMPs) for New York state. Furthermore, methodologies and
costs of updating the system have been explored in some: detail by Economic
Development Board personnel. Finally, LUNR data have been used extensively
for various planning purposes and user evaluations of the system are readily
available.
MAGI was selected for review because it is a relatively up-to-date state-
wide system with extensive use. Some data in the system are updated regularly,
and others when the data become available from special studies. Maryland State
Planning Office personnel have also examined various methods for updating land-
use information on a regular basis, including the use of LANDSAT data.
UDIS was selected from the three parcel-based systems largely because of
its extensive use. All the parcel systems are derived from tax assessment
files and can generate roughly the same outputs. The principal difference is
that the UDIS software and reporting formats are somewhat more specialized and
116
-------
hence more costly to operate. However, UDIS has experienced a wider variety
of applications and thus has more extensive documentation.
AERI and PIOS-II were not reviewed because of the difficulty in obtaining
data within the time and budget constraints of the project.
The detailed reviews concentrated on two aspects of the systems, namely,
update procedures which would be needed for growth monitoring, and applica-
tions of the systems to air quality planning. The results of these reviews
are presented in the following three sections.
NEW YORK STATE LAND USE AND NATURAL RESOURCE INVENTORY
As noted, LUNR was chosen for review because New York State Economic
Development Board personnel have examined the problems of system updates in
some detail. However, at the present time update procedures for LUNR at the
statewide level do not exist. A pilot project for preparing an updated ver-
sion, the Land-Related Information System (LRIS) was funded by the Appalachian
Regional Commission. LRIS was completed for Broome and Tioga Counties
(1238 km^) at a cost of approximately $125,000. LRIS involved substantially
more than a simple land-use update, including the collection of detailed
physical data. LRIS, however, does not include a computerized data base.
Land-use information in LRIS was obtained from orthophoto interpretation at
a cost of approximately $60,000, with $37,500 going to preparation of the
orthophoto quads and $22,500 to interpretation.26 Coverage of the entire state
bv this method was estimated to involve 90 to 100 person years of labor for
77
interpretation alone. '
Updates of LUNR have been undertaken by local and regional planning
agencies, usually for specific needs. Recent updates have been made possible
by the New York State tax mapping program, which is providing airphoto cover-
age of most of the state in an effort to produce detailed real estate tax maps
for the entire state. However, this program is a one-time-only effort.2^
Thus, the main problems in an update are the availability of aerial photogra-
phy and the cost of extensive field checking. No mechanism exists for incor-
porating local updates into the statewide system. However, the extensive
use of LUNR has made possible the development of a relatively complete USGS
Level III classification system for the state.29
The prognosis for regular LUNR updates is not good. The system is cur-
rently based in an "unstable" (for budget reasons) agency, whose functions
are partially duplicated by other agencies; e.g., the tax mapping program.
While LUNR data are potentially useful for a number of state planning func-
tions making the costs of an update potentially sharable, there is little
coodination of state data needs. A committee has recently been formed for
this purpose, but any action is not forthcoming. Most coordination to date
has been based on "good interpersonal communication."3°
As noted previously, LUNR has had a wide range of applications. With
regard to this review, it is worth noting that almost 70 percent of LUNR
users think that data for "rapid change areas" should be updated at least
every 2 years. Further, more than half think statewide updates should be
conducted at least every 5 years. ^
117
-------
Air quality planning applications of LUNR have been carried out through
local and regional agencies, in cooperation with the state Department of En-
vironmental Conservation. A current application is underway in the prepara-
tion of the air quality maintenance plan for the Utica-Rome AQMA. The
Herkimer-Oneida Comprehensive Planning Program updated LUNR land-use data to
1975 from airphotos and ground checking. Approximately 1,500 km^ were updated,
at a cost of $11,000. The updated land-use information was then used as a
basis for projections, and will be used in conjunction with employment and
population data from allocating area source emissions. Emission totals for
cities and towns will be allocated by employment and population totals, and
then allocated to subareas with the land-use data.
In a previous application, land-use based emission factors were applied
to LUNR data as part of an effort to evaluate the air quality impacts of a
proposed regional plan for the Rochester area. It was found that the LUNR
data lacked sufficient detail on land-use intensities. Consequently, employ-
ment and population data were used in a fashion similar to the Utica-Rome
applications, and the LUNR data were then used for the final allocation.
In summary, LUNR as it currently exists is not especially useful for
growth monitoring, and its data format limits its usefulness for air quality
planning in general. Furthermore, updates, even with the current format, are
cumbersome and costly at the statewide level. Data collection costs are the
major component. Aerial photography is relatively expensive, and the labor
and time required for interpretation and field checking; are prohibitive for
any single application. A cost-benefit analysis of the system has been pro-
posed as part of the effort to coordinate state data needs, and any results
will likely affect decisions about updating the system.
MARYLAND AUTOMATED GEOGRAPHIC INFORMATION SYSTEM
As noted previously, the MAGI coding scheme for land-use data limits
system applications for air quality planning. However, MAGI is a statewide
information system with some update procedures in progress, and hence merits
further study.
MAGI data are updated as new data become available; e.g., county land-
use plan updates are entered when the plans are formally adopted. Physical
data in the system are relatively fixed, but "cultural" data such as land use
will be updated as the need arises and the data become available. Plans are
currently being made to update MAGI land-use data to 1975, using high altitude
aerial photography available from NASA. However, the program which funded the
U-2 flights has been terminated and other data sources will be required for
later updates of land-use information. The state has riot made any commitment
to continuing collection of land-use data, and updates will likely be done
with data collected for special needs or for other programs.
*
Herkimer-Oneida GPP is the regional planning agency for the Utica-Rome area.
118
-------
Maryland state planning personnel estimate the cost of a land-use update
from mid-altitude aerial photography at about $100,000, split almost evenly
between photo acquisition and interpretation. This cost was felt to be
reasonable for updates at 3-year intervals, provided that the costs could be
spread to all system users. -^ The only problem foreseen was the lag time
involved in making the information available; i.e., the relatively long period
required for photo interpretation and computerization of the data.
Maryland planning personnel also investigated the possibility of using
LANDSAT data for system updates. It was concluded that the satellite data
could be used to produce Level I information, but that it could not be used
to meet state demands for Level II and III data. It was, however, concluded
that the satellite data could be used to indicate those areas where more de-
tailed updates are required; e.g., rapid change areas.^" It is important to
note that "change detection" with LANDSAT in this case means changes from one
Level I classification to another. Thus, Level II or higher level changes
that are potentially important for air quality planning might not be detected.
In summary, MAGI faces problems very similar to those faced by LUNR in
regard to its use for growth monitoring. In fact, the problems involved in
the use of remote sensing data for updates seem to limit the application of
large-area systems to detailed change detection to a serious degree. The
costs of obtaining, interpreting, and ground checking the data, as well as the
time involved are substantial. Further, the detail of data available from all
but low level aerial photography may not be sufficient for air quality plan-
ning purposes
THE FAIRFAX COUNTY URBAN DEVELOPMENT INFORMATION SYSTEM
The level of detail and frequency of updates for UDIS seem to be ideal
for growth monitoring for air quality planning. This is not surprising, as
the system is designed to provide information on all aspects of land develop-
ment. Each county agency responsible for some aspect of development provides
information to the system on a regular basis. Zoning changes, building per-
mits, and use permits are all monitored, and regular summary reports are pro-
duced. All relevant data are updated annually, at a minimum.
The problem with generalized application of the Fairfax system is cost.
The level of detail needed for planning in a rapid growth area like Fairfax
County is not necessary for community planning in other areas; hence, the
cost of establishing such a system in these areas cannot be justified. Fur-
ther, UDIS and the other parcel systems have been developed in areas already
having computerized tax assessment files, thus greatly reducing data collection
costs. However, for areas meeting all the qualifications, parcel-based sys-
tems are an efficient method for monitoring growth by land-use changes.
UDIS is also used for air quality studies through a process and set of
models recently developed for Fairfax County. UDIS provides land use and
structure characteristics used to calculate and allocate stationary source
emissions by computerized versions of the Volume 7 and 13 techniques. The
calculated emission values are stored in a version of the EIS/P&R Subsystem,
119
-------
and can be input to a version of the Air Quality Display Model for concentra-
tion calculations. Mobile source emissions are treated in a separate model
segment and can be input to a version of the HIWAY model. The models are
arranged in stages, allowing the user to check results of one operation before
they are input to the next segment. The models were tested in Fairfax County
with somewhat mixed results. The HIWAY model segment was modified to handle
queuing effects, and yielded satisfactory results. The AQDM tests were less
successful, owing to insufficient monitoring data for calibration and the
difficulty of separating out the effects of the nearby Washington, D.C.
metropolitan area.
LAND-USE MAPPING BY REMOTE SENSING TECHNIQUES
As noted previously, the most effective way of updating land-use informa-
tion for large areas is by application of remote sensing techniques. Problems
with this approach include the costs of obtaining, interpreting, and field
checking the imagery, as well as obtaining adequate detail for growth moni-
toring. Nonetheless, the approach holds some promise. In this section three
projects that use remote sensing data for land-use mapping on a more or less
regular basis are briefly reviewed.* These are the California Department of
Water Resources Land-Use Survey Program, the USGS Land Use and Land Cover
Mapping Program, and the USGS Census Cities Experiment in Urban Change
Detection.
The California Department of Water Resources is charged with determining
water management requirements in the state. Detailed land-use information
is essential to determining these requirements. Given the rather rapid rate
of growth and change in California, this data must be updated on a regular
basis. This is accomplished through the use of aerial photography and field
surveys. The aerial photography is used to produce land-use maps on USGS
7.5 minute quadrangle sheets. The acreage of each land-use category for each
county, water agency jurisdiction, and similar areas is then computed and
stored in a computer readable format. This data can then be retrieved for a
wide range of planning purposes. The land-use classification scheme is
approximately equal in detail to a Level III scheme.39
The survey is budgeted at approximately $350,000/year of which about
two-thirds is available for data collection. Funding is obtained solely from
the State of California. The intent of the agency is to cover the entire
state at 10 to 12 year intervals. Rapid change areas are covered at shorter
intervals, averaging about 5 to 6 years. Remote, unchanging areas may be
covered at intervals greater than 12 years.
This program represents the only ongoing statewide commitment to moni-
toring land-use change that was discoeverd in the course of this project.
The cost figures could be considered applicable to the use of remote sensing
data for growth monitoring for air quality planning. (The land-use categories
*
For a readable summary of USGS services, the EROS data center, and further
examples of the use of remote sensing data the reader is referred to the
December 1976 issue of Practicing Planner.^
120
-------
are potentially useful, although some additional data on use intensity would
be needed.) It seems clear that the costs of covering the entire state on
an annual basis would be prohibitive.
The USGS Land Use and Land Cover Mapping Program is an effort to map
land use for the entire country at a maximum scale of 1:100,000 using high
altitude photography. The program is aimed at establishing baseline data with
a uniform classification for general planning purposes. Updates will be done
only on a needs basis, but this could mean coverage of urban areas of 5-year
intervals. Growth monitoring could thus be a possible goal of the program if
rapid growth areas could be identified from other sources. However, the
applicability of the data is very limited, as the detail achieved in only a
Level II classification. Further, the smallest parcel considered in the pro-
gram is approximately 10 acres.^1
An ongoing project which holds more promise is the Experiment in Urban
Change Detection conducted by the Geography Program of the USGS. At present,
a detailed land-use map of Washington, B.C. has been prepared from LANDSAT
multispectral scanner (MSS) data to prove the feasibility of mapping land use.
Change detection involved comparison of this map with one produced from high
altitude aerial photography taken 3 years earlier. However, change detection
by computer comparisons of LANDSAT imagery is feasible and may be attempted
in the future.
LANDSAT MSS data provides a minimum resolution of one picture element
(pixel) which represents about 1 acre. Land-use classifications are obtained
from LANDSAT data through the following process: A part of a LANDSAT scene,
usually composed of 2 sets of spectral data, is subjected to cluster analysis,
and each pixel is assigned to a cluster having similar characteristics. The
resulting cluster data is overlaid on a map of existing land uses, and the
land use represented by each picture element is noted. The data are then
analyzed statistically to provide a "signature" of spectral values for each
land-use category. The computer is then used to produce a land-use classifi-
cation for each picture element in the complete scene.^ The process thus
allows land-use categories to be defined in a number of ways. The Washington,
D.C. study used some 26 land-use spectra categories, cutting across Levels I
to III. These categories were combined into 11 land-use categories for
final mapping.
The final map was then compared visually with a map produced from high-
altitude aerial photography flown at an earlier date. The project was
successful at detecting numerous land-use changes across the Washington area.
Further, one of the final mapping categories was "disturbed land," allowing
for detection of construction activity. (This category can be separated from
agricultural land by use of imagery from different seasons.)
The relative costs of producing the two maps are of some interest. The
map produced from aerial photography required approximately 2 person-years of
effort. Preparation of data used for the LANDSAT map required approximately
3 person-days of effort by skilled analysts, and some computer time. (The map
is printed directly from computer data tapes, using a newly developed laser
121
-------
exposure process.) However, two factors that affect the cost should be noted.
First, land-use maps at a usable scale; e.g., 1:24,000, must be available for
classification of LANDSAT data. Second, the process is in the development
stage, involving specially trained personnel and experimental techniques.
For example, classification of land uses from clustered LANDSAT data required
8 minutes of computer time on an experimental machine developed for USGS.
Classification on an in-use machine such as an IBM 370/66 would require over
20 hours.43
In summary, the LANDSAT change detection process offers some promise for
eventual application to growth monitoring. However, major problems remain to
be resolved. First, and most important, the detail available from LANDSAT
data may not be sufficient for growth monitoring for air quality maintenance
planning purposes. That is, land-use classification systems such as the USGS
Washington categories may be too general for growth monitoring. Further,
redefining the categories to be more specific may not be possible; e.g.,
separating the spectral signatures of commercial and industrial development
may not be possible. Generally, the more heavily urbanized the area, the
greater the difficulty in separating land uses. This problem has not yet
been examined in detail. A second problem is that the process is not yet
thoroughly developed, so that costs are difficult to determine. Other methods
of growth monitoring may prove more cost-effective; e.g., analysis of building
permits or other data already collected on a regular basis.
SUMMARY
None of the geographic information systems reviewed holds promise for
statewide growth monitoring at the levels required for air quality planning.
Large area systems generally lack sufficient data detail. Furthermore, they
face the time and cost problems presented by the use of remote sensing data
for system updates. Parcel-based systems are effective for relatively small
areas, but the costs of their application to larger areas are prohibitive.
Their data detail and update procedures are ideal for growth monitoring, but
are generally dependent on links with computerized assessment data. Growth
monitoring for large areas with remote sensing techniques does hold promise.
However, the problems of cost and detail noted previously, and the experimental
nature of sophisticated interpretation techniques limit their application at
the present time.
This review has raised four points of potential importance for growth
monitoring. First, existing geographic information systems can conceivably
serve as sources of baseline data for monitoring land-use changes. Second,
those areas with parcel-based systems have a ready source of data that should
be applied to growth monitoring. Third, the data sources for parcel-based
systems suggest that many localities may already collect adequate data for
other purposes. Finally, the possibility of using remote sensing data, espe-
cially satellite imagery, in conjunction with other techniques might be worthy
of further examination. The USGS experiments have shown that LANDSAT imagery
can be used to detect some land-use changes. If the cost and accuracy can be
improved, it might be possible to identify "changing" areas which could then
be examined in detail by more conventional means.
122
-------
REFERENCES
1. Office of Air Quality Planning and Standards. Guidelines for Air
Quality Maintenance Planning and Analysis; Volume 7: Projecting
County Emissions. Second Edition. EPA-450/4-74-008, U.S. Environ-
mental Protection Agency, Research Triangle Park, North Carolina.
1975.
2. Office of Air Quality Planning and Standards. Guidelines for Air
Quality Maintenance Planning and Analysis; Volume 13: Allocating
Projected Emissions to Subcounty Areas. EPA-450/4-74-014, U.S.
Environmental Protection Agency, Research Triangle Park, North
Carolina. 1975.
3. Anderson, J. R., E. E. Hardy, J. T. Roach, and R. E. Witmer.
A Land Use and Land Cover Classification System for Use With Remote
Sensor Data. Geological Survey Professional Paper 964, U.S. Govern-
ment Printing Office, Washington. 1976.
4. Herring, B. E., and R. I. Vachon. Development of Alabama Resources
Information System, ARIS; Annual Report, 1 July 1974 to 1 May 1976.
Auburn University. Industrial Engineering and Mechanical Engineering
Department, Auburn, Alabama. 1976.
5. Menter, James. University of Minnesota Center for Urban and Regional
Affairs. Personal Communication.
6. Dangermond, Jack. Environmental Systems Research Institute.
Personal Communication.
7. Crowder, R. Land Use and Natural Resource Inventory of New York
State; What it is and How it is Used. Office of Planning Services,
State of New York, Albany. November 1974.
8. Office of Planning Services. LUNR Classification Manual. State of
New York, Albany. 1974.
9. Crowder, R., R. Porreca, and J. Tarantino. Survey of Users: LUNR.
New York State Economic Development Board, Albany. September 1974.
123
-------
10. Porreca, R., and R. Crowder. Completion Report to the Appalachian
Regional Commission for ARC Grant No. 74-63. NY-2870-73-I-201-0607,
New York State Economic Development Board, Albany. March 1976.
11. Hogan, Rick. New York State Department of Environmental Conservation.
Personal Communication.
12. Steinitz Rogers Associates, Inc. Environmental Assessment, Regional
Development Plan. Genesee/Finger Lakes Regional Planning Board, Rochester,
New York. 1975.
13. Dangermond, J., and J. Antenucci. Maryland Automated Geographic Informa-
tion (MAGI) System. Maryland Department of State Planning Baltimore.
25 pp. May 1974.
14. Antenucci, John. Maryland Department of State Planning. Personal
Communication.
15. Antenucci, John. Personal Communication.
16. Fostel, Henry. Baltimore Regional Planning Commission. Personal
Communication.
17. Hyson, J. L., Jr., W. B. Rucker, N. Ahuja, and R. P. Ahner. A Handbook
for Creating an Urban Development Information System. County of Fair-
fax, Fairfax, Virginia. (No date).
18. Malarkey, Robert. Charlotte-Mecklenburg Planning Commission. Personal
Communication.
19. Powers, Tom. Charlotte-Mecklenburg Planning Commission. Personal
Communicat ion.
20. Gould, A. J. Wilmington (Del.) Metropolitan Area Planning Council.
Personal Communication.
21. Environmental Systems Research Institute. New Castle County Automated
Environmental Resource Information (AERI) Systems. New Castle County
Areawide Waste Treatment Management Program, Wilmington, Delaware. 1975.
22. Szatos, Vern. New Castle County Areawide Waste Treatment Management
Program. Personal Communication.
23. Comprehensive Planning Organization Staff. PIOS-II General System
Description, Comprehensive Planning Organization of the San Diego Region.
San Diego, California. 1974.
24. DeBerry, Terry. Comprehensive Planning Organization of the San Diego
Region. Personal Communication.
124
-------
25. Mross, Robert. Air Pollution Control District of San Diego County.
Personal Communication.
26. Crowder, Robert. New York State Economic Development Board. Per-
sonal Communication.
27. Porreca, R., and R. Crowder. Completion Report to the Appalachian
Regional Commission for ARC Grant No. 74-63. NY-2870-73-I-201-0607,
New York State Economic Development Board, Albany, p. 134. 1976.
28. Porreca, Robert. New York State Economic Development Board.
Personal Communication.
29. Crowder, Robert. Personal Communication.
30. Porreca, Robert. Personal Communication.
31. Crowder, R., R. Porreca, and J. Tarantino. Survey of Users: LUNR.
New York State Economic Development Board, Albany. Table 8.
September 1974.
32. Hogan, Rick. Personal Communication.
33. Steinitz Rogers Associates, Inc. Environmental Assessment, Regional
Development Plan. Genesee/Finger Lakes Regional Planning Board,
Rochester, New York. 1975.
34. Antenucci, John. Personal Communication.
35. Morgan, III, John W., Maryland Department of State Planning.
Personal Communication.
36. Thomas, E. L., D. S. Simonett, et al. Application of ERTS-1 Data
to Integrated State Planning in the State of Maryland. Prepared
by Maryland Office of State Planning and Earth Satellite Corporation
for ERTS Program Office, NASA Goddard Space Flight Center, Greenbelt,
Maryland. Contract No. NAS5-21779. December 1974.
37. Rucker, William D. Fairfax County (Va.) Office of Research and
Statistics. Personal Communication.
38. Fairfax Air Quality Model Final Report. Submitted to County of Fairfax
Office of Research and Statistics by Engineering Sciences, McLean,
Virginia. November 1976.
39. Department of Water Resources. Land Use in California. Bulletin No. 176.
Department of Water Resources, The Resources Agency. State of California,
Sacramento. 1971.
40. Sawyer, Glen. California Department of Water Resources. Personal
Communication.
125
-------
41. Kleckner, Richard L. USGS Geography Program. Personal Communication.
42. Ellefsen, R., L. Gaydos, and J. Wray. Computer Aided Mapping of Land
Use Using ERTS Multispectral Scanner Data. Paper presented at First
Pan American Congress on Photogrammetry, Photointerpretation and
Geodesy, Mexico City, Mexico. July 1974.
43. Wray, James. USGS Geography Program. Personal Communication.
44. Practicing Planner. American Institute of Planners. December 1976.
Volume 6, No. 5. pp 10-26.
126
-------
APPENDIX D
OVERVIEW OF THE PROCESS FOR CONTROL OF CO HOT SPOTS
Controlling CO hot spots requires several steps: identification of the
potential hot spots, detailed analysis of each hot spot, and selection of
control measures.
Figure D-l is a flow diagram for the overall process for selection of CO
control measures. Each of the numbered steps will be briefly described.
STEP 1: PRELIMINARY SCREENING
Preliminary screening of roadways and intersections to identify possible
CO hot spots is the first task. Preliminary screening procedures use gen-
eralized procedures and a minimum amount of traffic data; available data can
be used in most cases. To facilitate the rapid screening of many locations,
simple charts and nomographs have been developed. The output is simple the
identification of potential hot spots; no quantitative estimates of CO con-
centrations are produced.
STEP 2: VERIFICATION SCREENING
Verification screening is a more detailed manual analysis of locations
that are shown by preliminary screening to be potential hot spots. Verifi-
cation screening uses a larger amount of site-specific data than does pre-
liminary screening, and produces quantitative estimates of CO levels. New
traffic data will be needed in many instances.
STEP 3: DETAILED MODELING
Once the hot spots are identified, they are analyzed with detailed
analytical models (usually some form of computer model). Modeling provides
the base case against which alternatives are judged. Modeling generally
requires the collection of new data on traffic, air quality, and meteor-
ology. Modeling reveals the degree of emission reduction that is needed from
traffic controls.
STEP 4: IDENTIFICATION OF ALTERNATIVE IMPROVEMENTS
Knowing the amount of CO emissions reduction that is needed, the planner
can begin to narrow the choice of control measures by identifying those alter-
natives that appear capable of meeting the air quality requirements. New (or
existing) transportation planning data are obtained at this point, to allow
127
-------
o
PRELIMINARY
SCREENING
VERIFICATION
SCREENING
DETAILED
MODELING
IDENTIFICATION OF
ALTERNATIVE
IMPROVEMENTS
EVALUATION OF
ALTERNATIVES
SELECTION OF
CONTROL MEASURES
IMPLEMENTATION
EVALUATION
AVAILABLE TRAFFIC DATA
LIMITED ADDITIONAL
TRAFFIC DATA
COLLECT NEW
TRAFFIC DATA,
AIR QUALITY DATA,
METEOROLOGICAL DATA
OBTAIN
TRANSPORTATION
PLANNING DATA
AIR QUALITY EFFECTS
SOCIAL, ECONOMIC
INSTITUTIONAL,OTHER
EFFECTS
Figure D-l. Decision-making process for selection, of
CO control measures
128
-------
forecasting emissions in future years and to allow consideration of macro-
scale traffic changes when necessary. The alternatives to be evaluated
should be capable of achieving the required reduction in emission concentra-
tion at each hot spot, after accounting for other mitigating factors such as
new vehicle pollution control devices
STEP 5: EVALUATION OF ALTERNATIVES
Evaluation of air quality effects uses the models from Step 3 and deter-
mines if the required reductions would be met. For those alternative measures
that would satisfy the air quality criteria (only), the other effects are then
identified and quantified. If the alternative control measures are inadequate,
or if it is prudent to examine additional alternatives because of implemen-
tation obstacles that may arise, the process would revert to Step 4 at this
point.
STEP 6: SELECTION OF CONTROL MEASURES
Selecting among the alternative measures requires balancing the nonair
quality effects (assuming that only those measures that will achieve the
required reductions are being considered at this point). The thrust of the
choice is to minimize the adverse impacts. For example, the decision might
be between two control measures that are similar except that one requires more
capital outlay but is more beneficial to fuel consumption. Such choices are
commonly made in transportation facility planning.
STEP 7: IMPLEMENTATION
Having selected a measure, it must be implemented. When planning
measures, the time to accomplish this step should be considered in all anal-
yses of effectiveness.
STEP 8: EVALUATION
After implementation, the traffic and air quality should be monitored
and calculations made to determine if the required reductions in emission
concentrations will be achieved. Rarely are planning predictions exact; in
some cases it will be necessary to adjust the control measures, or supplement
them, in order to (1) meet air quality goals or (2) amelicrate unexpected
impacts.
HOT SPOT SCREENING GUIDELINES
The two screening tasks described above (Step 1 and Step 2) have recently
been documented1 in a set of guidelines for the identification and analysis
of locations with the potential for experiencing violations of the National
Ambient Air Quality Standard for carbon monoxide. These guidelines are de-
signed to identify potential carbon monoxide hot spots, using only data on
automobile traffic and thus avoiding the need for time-consuming and costly
monitoring of air quality at potential hot spots.
129
-------
The overall technique is a refinement of a hot spot analysis procedure^
developed from a previous U.S. Environmental Protection Agency (EPA) report3
concerning the affects of emissions from proposed indirect sources. The hot
spot analysis procedure has also been expanded to provide the capability of
accounting for a number of additional conditions beyond those included in the
original procedure. At the present time, the hot spot screening procedure
does not provide techniques for screening future CO hot spots using projected
motor vehicle emission factors. This capability is currently being developed
and may be available in the future.
130
-------
REFERENCES
1. Stanley, S. T., T. P. Midurski, and R. M. Patterson. Guidelines for
Identification and Evaluation of Localized Violations of Carbon Monoxide
Standards, Volume I. GCA/Technology Division Interim Draft Final Report
prepared for U.S. Environmental Protection Agency, Research Triangle
Park, N.C., under Contract 68-02-1376, Task Order No. 22. July 1977.
2. Midurski, T. P. and A. H. Castaline. Guidelines for Identification and
Evaluation of Localized Violations of Carbon Monoxide Standards. Final
Guideline Report. GCA/Technology Division, Bedford, Massachusetts.
Prepared for U.S. Environmental Protection Agency, Region I Office,
Boston, Massachusetts. Publication Number EPA-901/9-76-001. January
1976.
3. Guidelines for Air Quality Maintenance Planning and Analysis. Volume 9:
Evaluating Indirect Sources. U.S. Environmental Protection Agency,
Research Triangle Park, North Carolina. Publication Number EPA-450/4-
75-001. January 1975.
131
-------
APPENDIX E
BASIS OF TABLES 1 AND 2
By conservatively assuming no atmospheric transformation of hydrocarbons
takes place, the Hanna-Gifford model is assumed to be applicable. The basic
Hanna-Gifford model for the origin cell concentration (equation (8) of Appendix
A) is as follows:
L-b
x = ' " v~' Q
a (1-b) u
substituting the following as a worst case situation,
a = 0.06
b = 0.71
u = 1 meter/sec
and a 1 square mile cell,
AX = 1609.3 meters
one obtains,
X = 319.17 Q
where x is expressed in yg/m3 and Q is expressed yg/mi'-/sec. The critical
emission density to exceed 75 percent of the NAAQS is:
(0.75) 160 = 319.17 Q
Q = 0.376 yg/m2/sec
or 33.81 tons per square mile per year.
Tables IV-1 and IV-2 assume negligible emissions from stationary sources and,
further, that the only significant source is light duty motor vehicles.
Twenty-five percent of the VMT is assumed to occur in the peak 3-hour period,
thus the equivalent annual emission rate is:
3 *3 Q1 I -
j j. ol I TT;
132
-------
The critical level of annual VMT per square mile in year n is
\
->-6
|E + E | (1.103 x 10"
I npstwx n / I
{16.9 tons/m2/yr)
8 /
VMT = ' ' - '
n
where E is the composite exhaust emission factor in year n and E is the
npstwx . .... . , , , . n
composite evaporative emission factor in year n, both expressed in grams per
mile. The critical level of annual gasoline sales density in year n is then
simply obtained by:
where M is the fleet composite gasoline mileage in year n expressed in miles
per gallon.
133
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
REPORT NO.
EPA-400/1-77-001
2.
4. TITLE AND SUBTITLE
A PROCEDURE FOR TRACKING EMISSIONS GROWTH AND AIR
QUALITY MAINTENANCE
5. REPORT DATE
September 1977
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
Frank H. Benesh
Phillip D. McLellan
8. PERFORMING ORGANIZATION REPORT NO
GCA-TR-77-20-G(a)
I. RECIPIENT'S ACCESSIOWNO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
GCA CORPORATION
GCA/TECHNOLOGY DIVISION
Bedford, Massachusetts 01730
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-01-4354
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Transportation and Land Use Policy
Washington, D.C.
13. TYPE OF REPORT AND PERIOD COVERED
Final Report
14. SPONSORING AGENCY CODE
200/00
15. SUPPLEMENTARY NOTES
16. ABSTRACT
Guidelines to assist state and local agencies in designing information systems
to track trends in growth and to assess the potential of a violation of a
National Ambient Air Quality Standard within 10 years are described. The
information system may be used to reassess the adequacy of State Implementation
Plans as required by current federal regulation (40 CFR 51.12(h)). The guidelines
are illustrated in two states, Wisconsin and Massachusetts.
17.
d.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
AIR POLLUTION FORECASTS
URBAN PLANNING
REGIONAL PLANNING
INFORMATION SYSTEMS
b.IDENTIFIERS/OPEN ENDED TERMS
AIR QUALITY MAINTENANCE
AIR POLLUTION POTENTIAL
IMPLEMENTATION-AIR
POLLUTION PLANNING
EMISSIONS GROWTH
c. COSATI Field/Group
B. DISTRIBUTION STATEMENT
Distribution Unlimited
19. SECURITY CLASS (This Report)
UNCLASSIFIED
21. NO. OF PAGES
145
20. SECURITY CLASS (Thispage)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
135
-------