EPA-450/3-74-056-d
NOVEMBER 1973
HACKENSACK MEADOWLANDS
AIR POLLUTION STUDY -
EVALUATION AND RANKING
OF LAND USE PLANS
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
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EPA-450/3-74-056-d
HACKENSACK MEADOWLANDS
AIR POLLUTION STUDY -
EVALUATION AND RANKING
OF LAND USE PLANS
by
Byron H. Willis
Environmental Research and Technology, Inc.
429 Marrett Road
Lexington, Massachusetts 02173
Contract No. EHSD 71-39
EPA Project Officer: John Robson
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, N. C. 27711
November 1973
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This report is issued by the Environmental Protection Agency to report technical
data of interest to a limited number of readers. Copies are available free of
charge to Federal employees, current contractors and grantees, and nonprofit
organizations-as supplies permit-from the Air Pollution Technical Information
Center, Environmental Protection Agency, Research Triangle Park, North
Carolina 27711; or, for a fee, from the National Technical Information Service,
5285 Port Royal Road, Springfield, Virginia 22161.
This report was furnished to the Environmental Protection Agency by the
Environmental Research and Technology, Inc. , in fulfillment of Contract No.
EHSD 71-39. The contents of this report are reproduced herein as received
from the Environmental Research and Technology, Inc. The opinions, findings,
and conclusions expressed are those of the author and not necessarily those
of the Environmental Protection Agency. Mention of company or product names
is not to be considered as an endorsement by the Environmental Protection
Agency.
Publication No. EPA-450/3-74-056-d
11
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PREFACE
The Hackensack Meadovvlands Air Pollution Study final report consists
of a summary report, five task reports, and three appendices, each bound
separately. This report is the third of the five task reports. Its purpose
is to describe the procedures developed for incorporating air pollution
considerations into the formulation, evaluation and ranking of alternative
urban land use and transportation system plans and policies; and to describe
the results of the evaluation and ranking of four alternative land use plans
for 1990 for the New Jersey Hackensack Meadowlands.
111
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ACKNOWLEDGEMENTS
The work upon which this report is based was performed pursuant to
contract No. EHSD-71-39 with the Environmental Protection Agency, and Contract
No. 1P-290 with the New Jersey Department of Environmental Protection. The
contributions of our subcontractor, Burns and Roe, Inc., are gratefully
acknowledged.
The cooperation and assistance of the many personnel from EPA and NJDEP
contributed greatly to the success of this study. The special assistance of
Mr. Roland S. Yunghans and Dr. Edward B. Feinberg, Environmental Scientists,
Office of the Commissioner NJDEP, and Mr. John Robson, Land Use Planning
Branch, Office of Air Programs, EPA, is appreciated.
IV
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TABLE OF CONTENTS
Page
PREFACE iii
ACKNOWLEDGEMENTS iv
LIST OF ILLUSTRATIONS viii
LIST OF TABLES xi
1. SUMMARY AND CONCLUSIONS 1
1.1 Task Objectives 1
1.2 Results of the Survey of Planning Agencies 2
1.3 Summary of Procedures for Considering Air Pollution in the
Planning Process 5
1.4 Summary of Methodologies for Plan Evaluation and Ranking 8
1.5 Conclusions from the Air Quality Analysis of the Alternative
Land Use Plans for the Hackensack Meadowlands ^
2. INTRODUCTION 19
2.1 Relationship of the Task 3 Report to Other Study
Task Reports 19
2.2 Task 3 Objectives 20
2.3 Structure of the Task 3 Report 21
3. SURVEY OF PLANNING AGENCIES 23
3.1 Objectives and Procedures 23
24
3.2 Summary of Survey Findings
3.2.1 Extent of Current Air Pollution Considerations
in Planning Agencies 25
3.2.2 Constraints to the Consideration of Air Pollution 27
3.2.3 Data Problems 30
3.2.4 Implications for the Design of Air Pollution
Consideration Methodologies 32
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TABLE OF CONTENTS, contd.
Page
PROCEDURES FOR INCORPORATING AIR POLLUTION CONSIDERATIONS 3?
INTO THE PLANNING PROCESS
4.1 General Overview of the Methodology
4.2 Classification of Air Pollution Considerations Within 4J
the Planning Process
41
4.2.1 Geographic Scale of Analysis
4.2.2 Stages of Plan Development
4.3 Procedures for Consideration of Regional Air Quality
4.3.1 Compliance with Ambient Air Quality Standards
4.3.2 Impact on Regional Air Quality
4.3.3 Impact on Receptors
4.3.4 Techniques for Plan Modification
4.3.5 Shortcomings of the Procedures
5. METHODOLOGY FOR PLAN EVALUATION § RANKING 57
5.1 Introduction
r Q
5.2 Procedures for Plan Evaluation
r Q
5.2.1 Basic Requirements
5.2.2 Summary of Plan Evaluation Procedures
5.2.3 Selection of Impact Measures
5.2.4 Other Analysis Procedures for Plan Evaluation
5.3 Procedures for Plan Ranking
5.3.1 Basic Requirements
5.3.2 Background on the Development of Multi-pollutant
Air Quality Indices
5.3.3 Methodologies Considered for Pla" Ranking J^
5.3.4 Summary of Plan Ranking Procedures
6. AIR QUALITY ANALYSIS FOR THE HACKENSACK MEADOWLANDS 81
6.1 Objectives of the Analysis **1
6.2 Summary of Plan Characteristics and Data ^1
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TABLE OF CONTENTS, contd.
Page
6.3 Evaluation of Plans 91
6.3.1 Compliance with Ambient Air Quality Standards 91
6.3.2 Impact on Regional Air Quality 118
6.3.3 Impacts on Receptors 151
6.3.4 Land Use/Air Quality Compatibility 175
6.3.5 Summary of Plan Evaluations 184
6.4 Ranking of Plans
189
REFERENCES 190
GLOSSARY 193
ATTACHMENT A Planning Agencies Surveyed (Attached Herein)
ATTACHMENT B Ambient Air Quality Concentrations for the
1990 Hackensack Meadowlands Plans
(Attached Herein)
VII
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LIST OF ILLUSTRATIONS (contd.)
Figure Page
21 Air Quality Contours/for Hydrocarbons for Plan 1A Expressed
as Ratio of Air Quality/Air Quality Standard 111
22 Air Quality Contours/for Hydrocarbons for Plan IB Expressed
as Ratio of Air Quality/Air Quality Standard 112
23 Air Quality Contours/for Hydrocarbons for Plan 1C Expressed
as Ratio of Air Quality/Air Quality Standard 113
24 Air Quality Contours/for Nitrogen Oxides for Plan 1 Expressed
as Ratio of Air Quality/Air Quality Standard 114
25 Air Quality Contours/for Nitrogen Oxides for Plan 1A Expressed
as Ratio of Air Quality/Air Quality Standard 115
26 Air Quality Contours/for Nitrogen Oxides for Plan IB Expressed
as Ratio of Air Quality/Air Quality Standard 116
27 Air Quality Contours/for Nitrogen Oxides for Plan 1C Expressed
as Ratio of Air Quality/Air Quality Standard 117
28 Regional Air Quality Cumulative Frequency Distribution
for Total Suspended Particulates (TSP) 119
29 Regional Air Quality Cumulative Frequency Distribution
for Sulphur Dioxide (SO,,) 120
30 Regional Air Quality Cumulative Frequency for Carbon
Monoxide (CO) 121
31 Regional Air Quality Cumulative Frequency Distribution
for Hydrocarbons (HC) 122
32 Regional Air Quality Cumulative Frequency Distribution
for Nitrogen Oxides (NO ) 123
.A.
33 Wind Direction Frequency Distribution 14g
34 Grid Plot for Population Density for Plan 1 153
35 Grid Plot for Population Density for Plan 1A 154
36 Grid Plot for Population Density for Plan IB 155
37 Grid Plot for Population Density for Plan 1C 156
38 Grid Plot for Student Density for Plan 1 157
39 Grid Plot for Student Density for Plan 1A 158
40 Grid Plot for Student Density for Plan IB 159
41 Grid Plot for Residential Area Density for Plan 1 160
42 Grid Plot for Residential Area Density for Plan 1A 161
43 Grid Plot for Residential Area Density for Plan IB 162
44 Grid Plot for Residential Area Density for Plan 1C 163
IX
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LIST OF ILLUSTRATIONS (contd.)
Figure
45 Grid Plot for Commercial and Industrial Land Use
Density for Plan 1
46 Grid Plot for Commercial and Industrial Land Use
Density for Plan 1A 165
47 Grid Plot for Commercial and Institutional Land
Use Density for Plan IB 166
48 Grid Plot for Commercial and Industrial Land Use
Density for Plan 1C 167
49 Grid Plot for Open Space in Plan 1 168
50 Grid Plot for Open Space in Plan 1A 169
51 Grid Plot for Open Space in Plan IB 170
52 Grid Plot for Open Space in Plan 1C 171
53 Land Use - Air Quality Compatibility Score Distribution
for Plan 1 178
54 Land Use - Air Quality Compatibility Score Distribution
for Plan 1A 179
55 Land Use - Air Quality Compatibility Score Distribution
for Plan IB 18°
56 Land Use - Air Quality Compatibility Score Distribution
for Plan 1C 181
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Accession Number 98856
Main Title Hackensack Meadowlands Air Pollution Study
s -^ Evaluation and Ranking of Land Use Plans
Personal Author Willis., Byron H - flans.
Corporate Author Environmental Research and Technology inc
Lexington, Mass./Environmental Protection Agency
Research Triangle Park, N.C.;New Jersey Dept. of
Year Published g^xronmental Protection, Trenton.
Call Number PB-238 606
Report Number ERT-P-244-3; EPA-71-39; EPA/450/3-74-046-d;
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LIST OF TABLES
Table
1 Alternative Forms Considered for a Plan Ranking Index 74
2 Sample Calculations for •/. I.-.KI^ indices 75
3 Summary of Land Use In form -it > .•/> f.>r liackensack
Meadowlands Plans
4 Federal Ambient Air Qua! it;, Standards Adopted by-
Environmental Protection V:er,,-.v, April 30, 1971
5 Equivalent Annual Averab > -,i r Qualitv Standards 95
6 Summary of Projected h;?r Mf Quality Data for the
Meadowlands
7 Frequency and Cur.iulativ.-.- ^i.st.-i Ution of Percent of
Total Land Area for Total Suspended Particulates 124
8 Frequency and Cumulative Distribution of Percent of
Total Land Area for Sulfur UJ oxide
9 Frequency and Cumulative Distribution of Percent of
Total Land Area for Carbon P'o.^de 126
10 Frequency and Cumulative Pi-x ributicm of Percent of
Total Land Area for Hydrocarbons
11 Frequency and Cumulative- Distribution of Percent of
Total Land Area for NiTrt.^en G'.dfis 12S
12 Summary of 1990 Anr.in] 1.1 •"-,-; i ons P«r Acre for Hackensack
Meadowlands Land Use Catti^.c. -ri.es 134
13 Integrated Receptor tixpo/urc,- Li. pact Mea?u"es 137
14 Average Receptor Expcsure Iir.rac': Measures 138
15 Relative Ranking Ratio of Integrated Receptor Exposure
Ratio 14°
16 Relative Ranking Ratiu 01 \\ ^rage Receptor Exposure
Ratio 141
17 Relative Ranking of Mans by Pollutant on Basis of
Quantitative Measures cf Impact 142
18 Relative Ranking of Plans 01: Basis of Quantitative Ranking
Index for Combined Pollutant Impacts 145
19 Seasonal Variation in Average Concentration Levels Within
the Hackensack Meadow lane!:, for Plan 1 150
20 Land Use - Air Quality Cor.ratihility Criteria 177
21 Histogram of the Number of Gnu Cells within Each Grid
Cell Having a Specified Number of Pollutant Violations
per Grid Cell 183
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1. SUMMARY AND CONCLUSIONS
1.1 Task Objectives
This report documents the results of the Task 5 studies undertaken
by Environmental Research § Technology, Inc. (ERT) as part of the Hackensack
Meadowlands Air Pollution Study. The two principal objectives of this task
were to develop procedures for incorporating air pollution considerations
into the formulation and evaluation of alternative urban land use and
transportation system plans and policies; and to demonstrate these procedures
through application to the evaluation and ranking of the 1990 comprehensive
land use plans for the New Jersey Hackensack MeadowJands Region. The
specific work undertaken as part of this task included a survey of planning
agencies to determine the extent to which air pollution considerations have
been or will be included in the planning process, the development of
methodologies to permit planners to assess the air pollution impact as-
sociated with land use plans, the development of methodologies to permit
planners to rank and evaluate alternative land use plans in terms of air
quality criteria, and the analysis of the regional air quality impact
associated with the four alternative land use plans for the Hackensack
Meadowlands for the 1990 time period.
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1.2 Results of the Survey of Planning Agencies
A survey of both land use and transportation system planning agencies
was conducted to determine the extent to which air pollution considerations
are currently being considered in the development of plans, and to determine
the basic requirements for procedures and methodologies which would facilitate
the consideration of air pollution in the planning process.
The survey showed a wide variation in the extent of current considera-
tions of air pollution by urban planners and in the attitudes toward the
priority and role of air pollution as a consideration in the planning
process. It was found in general that air pollution currently is not (and
historically has not been) an issue of primary concern among planners.
Consideration of air pollution was found to exist only in special cases
where air pollution represents a major problem of regionwide social,
economic and political concern. Even in such cases most of the effort
was concerned with the abatement of an existing problem and not on the
consideration of the influence of regional patterns of land use on air
quality for future time periods.
Typically, air pollution is considered at a very superficial level of
technical detail by planners and has never been a dominant factor in the
development of a plan. Furthermore planners seldom interface to any
significant degree with state and local air pollution control agencies,
and until very recently little discussion of the available technology for
projecting and analyzing the air pollution consequences of planning decisions
has appeared in the planning literature, it was found, however, that
interests in and concern for air pollution by planners is growing rapidly
both as a consequence of the concern of the general public for environmental
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matters and in response to the requirements of state and federal legisla-
tion requiring the submission of environmental impact statements for
proposed land use developments.
One of the dominant reasons for the lack of consideration of air
pollution in the planning process is that air pollution has not been a
significant problem historically and nas riot been of highest concern
politically. Consequently, air pclliuJMn ranks very low in terms of priorities
within the planning process relative to such issues as employment, economic
development, housing and social needs, Tne second niajor constraint
to the consideration of air pollution is the fact that planning agencies
typically do not have staff personnel with appropriate backgrounds and
technical training and skills in air pollution, do iijt have the required data
base nor access to the required analytical tools to jrojert air quality re-
sulting from proposed future land use plans, ana generally do not have the
resources required to develop such uapci's ill 11 es . A numhcr of other factors
of lesser importance have also contributed to the I;>CK ot consideration of
air pollution in the planning process. For example, planners prefer to view
a region as a system of interacting elements of wnioi air pollution is only
one. Consequently planners are relueia;,t to permit a single element, such
as air pollution, to have a dominant role in the development of a plan. Other
constraints of a more practical n.itiu .• result from the lack of a clear
distinction between the responsibilities uf the planner for abatement of air
pollution problems in the long tern, and those of air pollution control
officials. Finally, it was observed that the power base of planning agencies
is usally quite limited, and consequently planning projects that involve
large scale land developments, where the influence of air pollution considera-
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tions would be greatest, are most vulnerable to short terra political and
economic pressures often contrary to air quality goals.
From the results of the survey it was concluded that a critical need
exists for methodologies and analytical tools which can be used by planners
to make air pollution projections and to analyze the consequences of land
use plans in terms of meaningful air pollution criteria. It was concluded
that most of the routinely collected land use and transportation planning
data are applicable to the derivation of source emission inputs to an
air quality projection model, although considerable additional computations
and processing probably will be required to transform such data into an
appropriate format for input to the model. In addition, however, planners
will be required to collect and work with a significant amount of totally
new kinds of data in order to consider air pollution in the planning process.
Furthermore it was concluded that a computer-based tool for the analysis
of air pollution would be appropriate for planning agencies for determining
air quality associated with large scale regional developments if this tool
can be linked directly to the routine planning process and to the routinely
collected data sets.
It was also concluded that to be of general use to planners, the method-
ologies should permit the planner to evaluate and rank alternative plans
based on quantitative air quality evaluation criteria or indices. Further-
more, the methodologies should permit both a rapid assessment of plans at a
low level of detail and a more detailed and comprehensive analysis of air
quality impacts. Finally, it was concluded that there is a definite need
for procedures and guidelines for considering air pollution at the initial
phases of plan synthesis which would indicate how to locate land use activities
or to modify urban forms in ways that will improve air quality.
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1.3 Summary of Procedures for Considering Air Pollution in the
Planning Process
In response to the general requjregents identified in the survey of
planning agencies, a methodology was developed that would permit planners
to incorporate air pollution considerations within the planning process.
The elements of this methodology consist, generally ci" . r quality information from the input
data; and a set of procedure? fcr t"' v- e-rali:atjon and ranking of alternative
land use plans. This combination of rr.ethudologit s, procedures and analytical
tools represents a system for the analysis of air pollution that has been
designated as the AQUIP System (Air Quality for UjMn and ^Industrial Planning)
The AQUIP System is a computer-oriented set of procedures involving
the planner in an iterative cycle of plan evaluation and modification
consisting of the following basic steps.:
1. The preparation of input iiata vLhcrLpi;±ve of the land use or
transportation plan;
2. The conversion of thi* data ir.ro pollutant emissions data;
3. The prediction and display ,:f mean ambient pollutant concentrations
within the area of interest;
4. The evaluation and ranking of the plan with respect to other plans
through analysis of aii quality contours and the computation of
quantitative measures of Lrep.ict ; and
5. The subsequent modification oi the plan or the input data and the
repetition of the process.
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Of these five steps the first and last require the direct involvement of
the planner to specify and manipulate planning data, to assess the degree
to which a plan satisfies the planning objectives and constraints, and to
specify changes to the plan as deemed necessary. The remaining steps involve
directly the use of computer-based models and data management programs to
perform the required air quality projections and data calculations.
The procedures developed for the analysis of air quality associated
with land use plans are based principally on the evaluation and ranking of
specified alternative land use plans in terms of impact on air quality on
a region-wide geographic scale and in terms of annual and seasonal
average pollutant concentrations. Furthermore the evaluation of air
quality associated with a plan focuses on the analysis of four items:
1. The degree of compliance with ambient air quality standards;
2. The degree of impact on regional levels of air quality;
3. The degree of impact on specific receptors or land use categories
which are especially sensitive to the effects of pollutants; and
4. The indication of ways to modify plans to improve air quality.
Procedures for examining compliance with air quality standards are
straightforward and involve the calculation of projected air quality
contours over the planning region. The maximum values of predicted air
quality levels are then compared with the appropriate ambient air quality
standards.
Procedures for examining the impact of land use plans on regional
air quality are based first on the examination of spatial patterns of air
quality, and secondly on the calculation of quantitative measures of impact
for each pollutant. The examination of the isopleth contours of pollutant
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concentrations over the planning region indicates the location of regions
of low and high pollutant concentrations, and also permits the visual exami-
nation of the influence of the type, location, and intensity of land use
activities on the air quality contours. Tne calculation of impact measures
permits the quantitative assessmcar of the impact of alternative plans on re-
gional air quality and the comparative evaluation and ranking of the alter-
native plans.
An especially important a^pe;:t of the analysis and evaluation of land
use plans is the analysis of impart of ;.~ir pollution levels on specific
high risk receptors and land use categories. The analysis procedures are
based both on the examination of the location of critical receptors rela-
tive to air quality contours and on the calculation of quantitative meas-
ures of impact.
Procedures for plan modification using the AQUIP System consist of general
guidelines based on the tabulae io.-. or the annual emissions per acre for the
different land use categories analyzed for the Mackensack Meadowlands. Such
data are used to identify land use categories which produce significant impacts
on regional air quality levels and contours when moved within a plan, and
land use categories which can be reL" -.ated within the plan without any sub-
stantial impact on regional air pollution concentration patterns.
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1.4 Summary of Methodologies for Plan Evaluation and Ranking
The procedures developed for the evaluation and comparative ranking
of alternative land use plans were based on the interpretation of three
basic types of information: land use data, air quality data, and air
quality criteria. The basic methodologies developed for plan evaluation
and ranking consist of procedures for the analysis of air quality on
a regional scale and for the analysis of air quality impact on specific
land use categories through both the calculation of quantitative
measures of impact and the graphical display and analysis of the spatial
distribution of air quality contours. The analysis of spatial patterns of
air quality can be carried out by calculating isopleth contours of pollutant
concentrations, but their interpretation relies largely on visual examination
and subjective judgment rather than on quantitative analysis. On the other
hand quantitative impact measures permit analytic evaluation, but tend to
subdue the physical and intuitive interpretation of the results. Consequently
the key issue involved in the development of procedures for plan evaluation
and ranking concerns the role of subjective judgment on the part of the
planner. More specifically, the final interpretation of such quantitative
data and its meaning in terms of impact and importance relative to other
planning issues is one based entirely on subjective judgement.
In this study the quantitative measures of impact which were found to
be most useful and meaningful in both plan evaluation and ranking were
1) measures of integrated receptor exposure and 2) measures of average
receptor exposure. The integrated receptor exposure for a given plan is
calculated by superimposing an arbitrary grid system on the planning region,
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forming the product of the number of receptors per grid cell times the
pollutant concentration within the grid cell, then summing this product
over all grid cells within the planning region. This impact measure
physically represents an indicator of the cumulative values of receptor
exposures within the plan. By contrast, the average receptor exposure
impact measure is calculated from the integrated exposure measure by
dividing the resultant integrated exposure measure by the total number
of receptors within the plan. Consequently, the average exposure measure
has units of pollutant concentration, and physically represents an indicator
of the average concentration to which any given receptor within the plan
will be exposed.
The specific receptors investigated in terms of these quantitative mea-
sures of impact were people and land. Two categories of people receptors were
examined: total population, and students. Four categories of land were
examined: total land area of the planning region, residential land area,
open space land area, and the combination of commercial and industrial land
area. In the analysis of the Hackensack Meadowlands plans, the average
total area exposure was examined as the primary measure of regional air quality
and the average population exposure impact parameter was examined as the prin-
cipal measure of impact on critical receptors. However, quantitative impact
measures were calculated for all combinations of pollutants and receptor cate-
gories. In addition the AQUIP System permits a significant amount of flexi-
bility in defining and calculating other quantitative measures of impact, and
in specifying air quality criteria other than ambient air quality standards
for use in the evaluation.
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The specific requirements for the quantitative ranking of alternative
land use plans differ slightly from the requirements for the analysis
and evaluation of plans. The basic need for plan ranking is to generate
a single number, or rank .. index, which can be calculated for each plan to
permit the relative ranking of the plans. This ranking index may be as-
sociated with the impact . j single pollutant, thereby allowing a pollutant
by pollutant comparison and ranking, or it may be associated with the combined
impact of all pollutants, ..c., a multipollutant air Duality index.
Although it is required that the ranking methodology be based on a
formula in order to state the rani ing criteria in quantitative terms, it is
also clear that no ranking scheme is unique or absolute. In fact it is de-
sired that the ranking scheme be sufficiently flexible to accommodate the sub-
jective values of the plainer and his particular circumstances in formulating
the ranking index, and it is required that the results of the ranking metho-
dology give reasonable agreement with known facts and the intuitive judgment
of the planner.
A brief survey of the literature dealing with multipollutant air
quality indices indicates that in spite of the fact that a large number
of such indices have been proposed, some of which are in use, all exhibit
some degree of difficulty in accurately characterizing the status of total
air quality in terms of multipollutant impact, and few were found to be
directly applicable to the ranking of land use plans.
Three specific ranking schemes were examined in detail to determine
their suitability as a ranking index which would be meaningful and useful
in the ranking of alternative land use plans. The methodology finally
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selected for use in the analysis of the alternative land use plans for the
Hackensack Meadowlands is designated as the Normalized Impact Parameter
Ranking Index and was devised as a compromise between the other two indices,
The selected ranking index has the significant advantage that it overcomes
certain pathological cases encountered in the use of the other two ranking
indices, while preserving most of their advantageous features (see Section
5.3.3).
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1.5 Conclusions from the Air Quality Analysis of the Alternative Land Use
Plans for the Hackensack Meadowlands
A study was conducted to evaluate and rank the four alternative 1990
comprehensive land use plans for the New Jersey Hackensack Meadowlands
District in terras of air quality criteria. The basic objective of
this analysis was to demonstrate the procedures and methodologies developed
for considering air pollution in the planning process through the direct
application of such methodologies to the planning alternatives developed
for the Meadowlands. Regional air quality concentrations for total suspended
particulates (TSP) , sulfur dioxide (SO^ , carbon monoxide (CO) , hydrocarbons
(HC), and nitrogen oxides (N(y , *ere analyzed in terms of annual averages and
summer and winter seasonal averages. The analysis also included the
influence of sources outside the Hackensack Meadowlands (i.e., background
sources) on air quality within the planning region.
The four specific plans analyzed in this study were developed by the
Hackensack Meadowlands Development Comission (HMDC) and are designated as:
Plan 1 - The Master Plan
Plan 1A - Self-Supporting New Town
Plan IB - Expansion of New York City Urban Core
Plan 1C - Trend Development Based on Current Zoning
The principal results of the analysis of these plans are summarized in the
following paragraphs.
1. Annual average ambient air quality standards are met for the 1990
time period in all four plans for the Hackensack Meadowlands region for
three pollutants: SO,,, CO, and N0x. Annual average ambient air quality
standards are exceeded for 1990 in all four plans for two pollutants:
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particulates and hydrocarbons. The analysis also indicates that the
background concentration levels for both particulates and hydrocarbons
exceed ambient air quality standards in 1990.
2. Analysis of the air quality of plans on the basis of individual
pollutants indicates that:
a. For TSP, maximum concentrations exceed the standard in all
four plans by a factor of approximately 2.5. Thus air quality
is a critical problem and must be of concern to the planner.
b. For S02, maximum concentrations are on the order of 55 to
60% of the standard. Furthermore the variation among plans
in impact on average regional air quality is less than 15%.
Thus air quality is not a major problem and the planner can
be neutral (relative to regional air quality criteria) in
choosing among the four plans.
c. For CO, air quality is of major concern within Plan IB, for
which the maximum concentration is approximately 90% of the
standard. Since maximum concentrations are less than 70%
of the standard and variation in impact on average regional
air quality is approximately 4%, the planner can be neutral
in choosing among the remaining three plans.
d. For HC, maximum concentrations exceed the standard in all
four plans by a factor of approximately 12. Thus air quality
is a critical problem and must be of concern to the planner.
e. For NO , maximum concentrations are on the order of 65% of
J\.
the standard, and variation in impact on average regional
air quality is approximately 7%. Thus air quality is not
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a major problem and the planner can be neutral in choosing
among the four plans.
3. Analysis of the total regional air pollutant concentration levels
and spatial patterns for the four alternative plans shows a significant
variation among plans for all pollutants except hydrocarbons. The quanti-
tative ranking of plans in terms of the multipollutant impact on total
regional air quality indicates that Plan 1 is best (that is, produces
least average regional concentration levels), followed by Plans IB, 1A
and 1C, respectively.
4. The corresponding analysis of the impact resulting from regional
air pollutant concentration levels and spatial patterns on sensitive cate-
gories of land uses and receptors (primarily population) shows a significant
variation in impact, among the four alternative land use plans. A quantita-
tive ranking of tht alternative plans based on consideration, of a number
of impact measures indicates that Plan 1 is best (that is, has the least
average exposure to the specified classes of receptors), followed by Plans
IB, 1A, and 1C, respectively.
5. Background air quality levels represent a major influence on
total air quality levels within the Hackensack Meadowlands planning region.
Background air quality accounts for between 65% and 99% of total concentra-
tion levels within the planning region (depending on the specific pollutant),
and completely dominates the spatial patterns of total air pollutant concen-
trations. The background air quality contours for all pollutants show a north-
south orientation with concentrations increasing from west to east. The pattern
of concentrations shows the strong influence of pollution from the New York
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City urban region on Hackensack Meadowlands air quality levels. Since a signi-
ficant spatial variation in background air quality levels occurs over the
Hackensack Meadowlands region, the relative location of land use activities
becomes a significant factor in mir.iiM-.ing the contribution of the specific
plan to regional air quality level- nr,l > >. minimising the impact of the re-
sultant regional air quality levels on r-po^fic receptors and land use
categories.
6. Since background concentre cr - repre^.t such a high percentage
of total air quality within the Mead,M,,ids for any given plan, the resultant
variation among plans in total air quality necessarily will be small.
For example, the maximum observed variaMons a,n,ng the four plans in average
regional air quality occurs for SO, and IS less than 15%. As a consequence
land use planning may be regarded as >n ineffective procedure for abatement
of regional air pollution in the vicinity of major urbanized areas unless
the planning region is sufficiently large that "background" concentration
levels represent only a small pere-iaa- ;.for ^rtn,rle, less than 50%) of
total air pollutant concentration io/els.
7. Analysis of the impact reciting froir the alternative land use
plans on regional air pollutant concent ration levels and spatial patterns
shows significant variation, among nlans due to: (1) the percent mix of
land use categories; (2) the relative location of land use categories; and
(3) the relative density or intensity of land use activities. The observed
variations in regional air pollute concentration levels and spatial patterns
are found to be extremely sensitive to the percent mix of manufacturing
and transportation related land use activities. Manufacturing influences
IS
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primarily particulates, SO,, and NO concentrations, while transportation
activities influence the CO concentrations. As a consequence, these land
use categories should be located within a plan relative to the spatial
pattern^ of background concentrations in order to minimize net impact on
total regional air quality levels.
8. In the Hackensack Meadowlands planning region, all land use activities
other than manufacturing and transportation have a negligible impact on re-
gional air quality levels and spatial patterns and therefore can be located
within a particular plan rather arbitrarily to provide minimum impact to
specific critical receptors and land use categories. Since the degree of
impact on critical receptors is especially sensitive to the relative location
of the receptors within the plan, the relative location of critical receptors
and land use categories represents an extremely important consideration in
the formulation and evaluation of land use plans. For example, it is observed
that those plans which rank best in terms of population exposure have resi-
dential areas predominantly located in the western portions of the Hackensack
Meadowlands planning region where concentrations generally are at their
lowest levels.
9. Regional air quality is relatively insensitive to the amount of
open space within any of the four plans. A direct tradeoff from manufacturing
to open space land use, for example, would be highly beneficial to regional air
quality levels, not because of the addition of open space within the plan,
but rather because of the deletion of manufacturing land uses.
10. The analysis of regional scale air quality considerations is not
sufficient to assess microscale impacts (that is, variations in concentrations
over short distances and short time periods). Consequently, caution is
16
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urged in interpreting results of regional air quality impact analyses. Such
analyses will indicate which choice of a land use plan minimizes the impact
on regional air quality levels and on critical receptors, but may not
indicate the existence of, nor provide a solution to, microscale impact
problems.
17
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2. INTRODUCTION
2.1 Relationship of the Task 3 Report to Other Study Task Reports
This report documents the results of the Task 3 studies undertaken as
part of the Hackensack Meadowlands Air Pollution Study. This study of the
air quality of the New Jersey Hackensack Meadowlands was carried out by
Environmental Research f? Technology, Inc. (ERT), under contract to the New
Jersey Department of Environmental Protection and to the Environmental Pro-
tection Agency, Office of Land Use Planning. The general objective of this
study was to develop a system of procedures (designated herein as the AQUIP
System) to permit land use and transportation planners to incorporate in a
meaningful way air pollution considerations into the planning process, both
at the formative stages of plan development as well as in the detailed eval-
uation of already developed land use plans.
This Task 3 Report is oriented specifically toward describing the general
procedures for considering air pollution in the planning process through tech-
niques for the analysis of air pollution impact on regional air quality. The
other major task reports for this study focus more specifically on: 1) the
technical details of the methods for preparing emissions data (the Task 1
Report); 2) the technical description of the air quality prediction model and
.its validation (the Task 2 Report); and 3) the detailed description of compu-
ter programs and data management software, together with directions for their
use (the Task 5 Report). Finally, the general planning guidelines based on
the results of this study are documented in the Task 4 Report.
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2.2 Task 3 Objectives
The general objectives of Task 3 were to develop procedures for incor-
porating air pollution considerations into the formulation and evaluation
of alternative urban land use and transportation systems plans and policies;
and to demonstrate these procedures through application to the evaluation and
ranking of the 1990 comprehensive land use plans for the New Jersey Hackensack
Meadowlands region.
In order to achieve these general objectives, the more specific work
elements were to:
1. Survey planning agencies to determine the extent to which air
pollution consideration have been or will be included in the
planning process.
2. Develop methodologies (including the specification of required
data, data processing, and use of analytic tools) to permit
planners to assess the air pollution impact associated with land
use plans.
3. Develop methodologies to permit planners to rank alternative land
use plans.
4. Perform a regional air quality impact analysis of the four land
use plans for the Hackensack Meadowlands for the 1990 time period.
5. Derive conclusions and guidelines of general applicability for
considering air pollution within the planning process.
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2.3 Structure of the Task 3 Report
This report contains the complete documentation of the work undertaken
in Task 3, including a description of the methodologies developed, the data,
the results of the analysis of the plans, and the conclusions derived from
the analysis. Section 3 of this report documents the results of the survey
of planning agencies. Section 4 documents the general methodology and pro-
cedures developed by ERT for incorporating air pollution considerations into
the land use and transportation planning process. Section 5 documents more
specifically the detailed procedures for plan evaluation and plan ranking in
terms of air quality criteria. Section 6 documents the results of the air
quality impact analysis, evaluation, and ranking of the four alternative land
use plans for the Hackensack Meadow lands region.
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3. SURVEY OF PLANNING AGENCIES
3.1 Objectives and Procedures
The survey of land use and transportation agencies served to fulfill
several objectives essential to the development of appropriate and useful
procedures for permitting planners to incorporate air pollution considerations
into the planning process. The primary objective was to identify the extent
to which planners currently consider air pollution in the planning process.
The second objective was to identify those factors influencing the extent
to which planners might consider air pollution considerations in future plan-
ning efforts. A third objective was to define the needs of planners for data,
analytic tools, methodologies, and guidelines which would facilitate the con-
sideration of air pollution in the planning process. The final objective was
to utilize this information in the development of the. AQUIP System.
The survey was carried out by interviewing both administrative and
technical personnel within the urban planning and transportation system
planning agencies. Agencies surveyed were selected to achieve a represent-
ative sample in terms of size, resources, staff skills, and scope of planning
responsibilities. The specific agencies surveyed are listed in Appendix A.
These include agencies at the state, regional, county, and city levels of
government as well as private planning groups. Some are devoted exclusively
to transportation systems planning while others are devoted to comprehensive
urban and land use planning. These agencies also include some known to be
active in the field of air pollution consideration as well as some known to
have either little concern for or few problems with air pollution.
In the course of the survey, staff members of the agencies were
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interviewed on a variety of subjects. The survey included a review of
current and past planning projects; a discussion of basic attitudes of the
planners towards air pollution as a problem and as an issue in the planning
process relative to the priorities of other planning issues and considerations;
a discussion of constraining factors in the consideration of air pollution; a
discussion of the internal resources, skills, and data available for consid-
ering air pollution; and a discussion of what planners would like to see in
the way of methodologies, tools and guidelines for assistance in considering
air pollution.
3.2 Summary of Survey Findings
As anticipated, the survey showed a wide variation in the extent of
current consideration of air pollution in the planning process, and in the
attitudes toward the priority and role of air pollution as a planning consid-
eration. The principal findings of this survey are reported in the following
sections, which deal with: 1) the extent of current considerations of air
pollution; 2) the identification of constraints faced by planner;; in consid-
ering air pollution; 3) problems associated with the compatibility of avail-
able planning data and the data requirements for air pollution analyses; and
4) implications for the design of the AQUIP System based on results of the
survey. Results of other recent surveys on the same subject have been re-
ported by Hagevik and by Van Nest and Hagevik . Many additional articles
reflecting the viewpoint of planners toward air pollution and other environ-
345
mental considerations can be found in the planning literature ' ' .
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3.2.1 Extent of Current Air Pollution Considerations in Planning Agencies
It was generally found that air pollution historically has not been an
issue of primary consideration among planning agencies. Consideration of air
pollution was found to exist only in special cases where air pollution repre-
sents a major problem of region-wide social, economic, and political concern.
Even in these special cases, however, little detail was exhibited in the
analysis of pollution consequences for future time periods. Most of the
emphasis was placed on cleaning up an existing problem through source emission
controls and regulations, and through conventional zoning control techniques
to regulate land uses. Air pollution considerations in such cases are typically
oriented toward the, analysis of areas which are already largely developed
rather than on areas of future development. Consequently, most current
planning efforts have no significant consideration of the influence of
regional patterns of land use on air quality for future time periods.
It was also found that the extent to which air pollution is given con-
sideration in the planning process currently is largely related to the re-
sources available to the planning agency in terms of staff size, skills,
and scope of planning projects, as well as funds available for inhouse or
consultant studies. In most cases where air pollution has been considered,
federal funds have been involved to some extent, and most of the studies
have been undertaken by university resources or by consultants.
It was found that attitudes of planners towards the relative importance
of air pollution as a factor in land use planning varied widely. Most were
sympathetic with air pollution as a problem and as an issue of concern, but
many felt that it was a largely overplayed issue relative to other planning
25
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concerns, while others felt that it should be the responsibility of the air
pollution control bureaus. As a general rule, it was found that little im-
portance was attached to air quality as a planning criteria by planning
agencies within regions where air pollution currently is not a problem, even
though it potentially could become a significant problem because of expanding
population and urban growth.
It was also found that state and local air pollution control agencies,
rather than land use planning agencies, have demonstrated the most concern
for air pollution on the regional scale. As a result of some of these major
air pollution studies, air quality prediction models have been developed for.
the application to specific metropolitan regions such as Chicago, New York,
Nashville, and St. Louis. However, in spite of the development of such
modeling techniques, the use of these models in actual transportation and
land use planning activities has been noted as an obvious application but
never applied to the actual planning process. Furthermore, until very re-
cently, little discussion of this available technology has appeared in the
planning literature, and no significant attempts have been made to use the
dispersion modeling techniques in the planning process for the analysis of
air pollution impact.
Throughout the duration of this study, however, it was observed that
attitudes among planners are changing rapidly and that there is a growing
concern among planners for air pollution and other environmental consider-
ations, a concern which is growing at least as rapidly as the concern of the
general public for environmental matters. Much of this concern is in direct
response to the legal requirements as set forth by the A-95 review process,
by the National Environmental Policy Act of 1969 (for submission of environ-
26
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mental impact statements for proposed developments involving federal funding),
and by Section 4(f) of the Department of Transportation Act of 1966, as
amended in Section 18 of the Federal Aid-Highway Act of 1969. It was found,
however, that in some agencies there is an attitude of reluctance in comply-
ing with such legal requirements because of the uncertainty of the interpre-
tation of these requirements and because of the added effort and costs neces-
sary to comply with these requirements. Consequently, it was generally found
that planning agencies devote no more than the minimum essential effort to
considering air pollution concerns.
3.2.2 Constraints to the Consideration of Air Pollution
Exploring the reasons for the lack of air pollution considerations in
planning is important in determining the probable extent of future consider-
ation by planners.
A dominant feature of the planning process is the allocation of limited
regional resources to the solution of regional problems such as employment,
social problems, economical development, and housing. Furthermore, the al-
location of resources to the solution of these problems not only is based on
the needs as perceived by the planning agency, but also very realistically is
responsive to key political and economic pressures at play within the region.
Consequently, it is not surprising that air pollution has not been ranked
particularly high in terms of important issues for consideration within the
planning process. In most cases, it has not been a significant problem
historically and has not been of highest concern politically.
Perhaps the greatest constraint to the consideration of air pollution
is the fact that planning agencies do not have staff with appropriate back-
27
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grounds and skills in air pollution, do not have access to the required
analytic tools nor the data base required to project air quality resulting
from proposed future land use plans, and generally do not have the resources
required to develop these capabilities.
It was found that planners typically have not received formal training
in considering environmental effects in general nor in considering air
pollution effects in particular. Planners generally have only a limited
understanding of air pollution terminology, air quality criteria, air
quality standards, or the effects of different pollutants on health and
plant life. Similarly they generally have very little understanding of
what considerations are important in air pollution, and what analytic tech-
niques are available for assessing air pollution impacts.
An equally significant constraint to the consideration of air pollution
was observed to result from a general lack of resources within planning
agencies. As a branch of state, county, or city governments it was observed
that planning agencies generally have extremely limited funding and numbers
of personnel, especially personnel with specialties in computers, modeling,
and air pollution. Furthermore, there was a wide variation in the resource-
fulness and initiative exhibited by planning agencies in seeking and acquiring
federal funding to either develop inhouse skills or to engage outside con-
sulting firms to perform detailed environmental studies.
Another constraint is that planners usually work with broad issues at
low levels of detail. As a consequence, while the analysis of air pollution
impacts of land use plans requires a high degree of specific detail concerning
land uses and transportation facilities, there is a tendency among planners to
treat air pollution at a broad scale and low level of detail. A related
problem is imposed by the time frame of the planning exercise. It is clear
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that ideas concerning the content and relative location of land uses change
rapidly in the development of the land use plan. In addition, it is evident
that there is a large margin of uncertainty in projections made with respect
to such concerns as future employment, population, social patterns, and life
styles.
It was found that planners feel a great risk in committing resources to
air pollution abatement through planning when there exists such uncertainty
in terms of changes in future technology dealing with air pollution, changes
in the attitude of the general public toward air pollution as a critical
issue, and changes in the ordering of priorities of problems and issues within
the planning region.
Furthermore, it was found that planners like to view a region as a
system and are interested in knowing the relationship and tradeoffs that
may occur between the consideration of various air pollution planning mea-
sures and other environmental concerns, such as water resources and quality,
solid waste disposal techniques, and so forth. Planners generally are not
content to look at air pollution alone, nor permit it to have a dominant role
in the development of the plan.
Another constraint results from the current lack of a clear distinction
between the responsibility of the planner for abatement of air pollution
problems in the long term and that of air pollution control officials.
It was found that many planners feel it is not within their jurisdiction to
incorporate air pollution into the planning process but rather feel that more
effective solutions could and should be achieved by direct control of emission
sources through the air pollution control agencies and their powers of regu-
lation and enforcement. Existing land use zoning laws present many difficult-
ies in providing an effective mechanism for controlling air pollution.
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An additional constraint on the consideration of air pollution is re-
lated to the power base of the planning agency. It was found that planning
agencies with jurisdiction over large regions ffor example, state, regional,
and county agencies) typically have an extremely limited power base. On the
other hand, in smaller jurisdictions where the planning agency has more
autonomy and control over land uses (such as within cities or small tract
developments) the planning region is too small or too highly developed for
land use planning to bo effective in influencing regional air quality.
Consequently, in thosr regions having the most potential for land development
and where the influence of air pollution considerations would be greatest,
it was observed that the planning agency has least control over the
implementation of a land use plan.
3.2.3 Data Problems
In order to be useful to the planner the methodologies and procedures
developed for considering air pollution must be highly compatible with the
procedures and the data normally used by planners. The consideration of air
pollution analytically requires relatively specialized types of data, in
particular meteorological data and source emissions data are required as
inputs to the air quality prediction model.
The required meteorological data for air pollution analysis is available
for most metropolitan regions from the National Climatological Center located
in Asheville, North Carolina, in the appropriate format for input to the
model. The more difficult problem is posed by the requirement to develop an
emissions inventory for input into the model based upon planning data or data
routinely collected by or available to planning agencies. The problem is
compounded by the requirements to develop an emissions inventory projected
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to a future time period as specified by the plan. Existing emissions inven-
tories, as developed by state and federal air pollution control agencies,
are necessary for model calibration but are only partially useful in deter-
mining future emissions inventories, especially in the 20 to 30 year time
frame of most land use and transportation planning efforts.
In computing an emissions inventory for input to the model, significant
emission sources, such as power plants, are usually represented as point
sources. One-dimensional distributed sources, such as roadways, are usually
represented in terms of straight line segments or line sources. Finally,
a large number of relatively small emission sources (such as residential
dwelling units or surface street traffic) are typically represented collec-
tively in terms of arbitrarily shaped polygons or area sources representing
land use zones.
It was found that planners never collect nor work directly with emissions
data. Furthermore, it was found as a result of the survey that planners seldom
collect or use data related to major point sources in the form necessary for
computing emissions (for example, projection data on the capacity, locationy
fuel use, and stack height for power plants and large incinerators). In most
cases, however, such data are collected by and available from utilities, air
pollution control agencies, and other government sources. It was also found
that planners (especially transportation planners) have excellent transport-
ation projection data, and that the majority of the data is in a format and
at a level of detail sufficient for use in calculating line source emissions.
Finally, it was found that the data required to calculate area source emissions
are similar in format to the type of data most frequently collected and used
by planners, but often lack sufficient detail to carry out the calculations.
31
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For example, planning information tends to deal with industries by broad
categories (e.g. by specification of SIC numbers) and rarely with the charac-
teristics of a specific firm which influence the level of emissions at a
particular location. The land use planner does work with parameters such as
acres and lot coverage, which can yield an estimate of the number of square
feet of floor space for a facility (essential for calculating fuel use), but
seldom works with specific fuel use data, for example, the particular type
and amount of fuel, or the percent used for process heating, or the method
by which space heating is accomplished (such as central heating systems
versus individual heating plants). On the other hand, it was found that
some of the data currently collected by planners are very detailed, for
example, projections of housing, employment, and population, but are not
directly applicable to the calculation of emissions.
Consequently, it was concluded from the results of the survey that to
a large extent, data collected by planners can be utilized to calculate
the required emissions inventories. However, planners will be required to
collect and work with new kinds of data in order to consider air pollution
in the planning process. The subject of input data requirements and pro-
cedures for calculating emissions data from land use planning data is dis-
cussed fully in the Task 1 Report.
3.2.4 Implications for the Design of Air Pollution Consideration
Methodologies
It was found that planners have considerable capabilities and back-
grounds in mathematical modeling, data processing, and projection techniques
Planners work to a great extent with data tabulations as well as with maps
and graphic representations of data, and they have available large amounts
32
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of current and projected land use and transportation data, often in the form
of computer data files. Consequently, it was concluded that a computer based
tool for analysis of air pollution would be appropriate for the larger plan-
ning agencies and those associated with large scale regional developments,
especially if this tool can be linked directly to the routine planning process
and to the routinely collected data sets.
Thus a further basic requirement for the design of the air pollution
planning methodology is that it permit planners to work with available land
use data to the greatest extent possible. Most of the routinely collected
land use and transportation data appear to be applicable to the derivation
of source emission inputs to the atmospheric diffusion model, although
probably requiring considerable calculations and data processing to transform
the data into an appropriate format for input to the model. Current trans-
portation planning data appears to be highly compatible with the input data
requirements for air pollution analysis. On the other hand, new kinds of
data will be required by the planner, for example, source emissions data
associated with major point sources such as power plants, incinerators, and
industrial processes (especially when projecting to a future time period).
Consequently, it is essential that the methodology permit the planner to
work directly with land use data whenever possible, and that the additional
types of data to be collected be clearly specified.
In terms of the more general requirements for the analytic methodology
for incorporating air pollution considerations into the planning process,
it was found that most planners expressed a desire to have more data and
information available to them for considering the effects of air pollution
resulting from land use plans in some quantitative way, although most pre-
33
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ferred simplified tables and guidelines rather than a detailed and involved
procedure for computing such information. Consequently, it was concluded
that to be of practical use to planners, the methodologies developed must
permit both a rapid assessment of plans at a low level of detail and a set
of analytic procedures to permit a more detailed and comprehensive analysis
of air quality impact. Such analytic tools should permit the planner to
evaluate and rank alternative plans based on quantitative air quality eval-
uation criteria or indices. Furthermore, the procedures should provide
Planners with quantitative guidelines to indicate how to locate land use
activities or to modify urban forms in ways that will improve air quality.
Significantly it was found that there is as much interest among planners
in considering air pollution during the initial synthesis of the plan as
there is for considering the detailed impact analysis and evaluation of
alternative plans. One of the most commonly expressed desire? among
planners was to have some indication of how to put together elements of
the plan at the formative stages according to some principles of air pollution
consideration.
Additionally, it was found that planners normally interpret regional
values expressed by the general community and attempt to set goals ir, the
planning process in accordance with such values. Furthermore, they are
accustomed to injecting their own subjective value judgment in the process
of developing a plan and allocating the resources of a region to achieve
these goals. Consequently, any planning evaluation process must preserve
the ability of the planner to make such value judgments.
Finally, it was found that the desired analytic methodology should be
versatile enough to permit planners to apply it not only to the evaluation
34
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of a plan in terms of regional air quality analysis, but also in terms of
impact analysis in the microscale. The need for techniques to examine the
air pollution impact of specific plan elements and facilities at the micro-
scale level of detail [especially during the plan implementation stage) in
accordance with the requirements of environmental impact statements is widely
recognized among planners. Similar!'.-, the methodology should permit planners
to investigate the relationship betvsee i ^ir quality considerations and other
design considerations, for exanpV>, the relationship between air quality and
water quality, or the implication.^ of pians to achieve good air quality on
satisfying the transportation requirements of a region.
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4. PROCEDURES FOR INCORPORATING AIR POLLUTION CONSIDERATIONS INTO THE
PLANNING PROCESS
4.1 General Overview of the Methodology
The elements of the methodology to permit planners to incorporate air
pollution considerations within the planning process consist of:
1. A set of procedures for collecting, processing, and interpreting
input data.
2. A set of procedures for generating air quality information
from land use data.
3. A set of procedures for the evaluation and ranking of
alternative land use plans.
The combination of these procedures, methodologies, and analytical tools repre-
sents a system for incorporating air pollution considerations into the plan-
ning process. This system has been designated as AQUIP, a system for con-
sidering Air Quality for Urban and Industrial Planning.
The AQUIP System is a computer oriented set of procedures involving
the planner in an iterative cycle of plan evaluation and modification as
represented schematically in Figure 1. More specifically the AQUIP System
may be thought of as being made up of the following basic steps or procedures:
1. The preparation of input data descriptive of a land use or
transportation plan.
2. The conversion of this data into pollutant emissions data.
3. The prediction and display of mean ambient pollution concentrations
within the area of interest.
37
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OVERALL PLANNING
GOALS, CRITERIA AND
CONSTRAINTS
THE PLANNER
AND THE
URBAN-INDUSTRIAL PLAN
PLANNING DATA
CONVERSION METHODOLOGY
FROM PLANNING DATA TO
EMISSIONS DATA
EMISSIONS DATA
AIR QUALITY COMPUTATION
MODEL
CLIMATOLOGICAL
DATA
AIR QUALITY DATA,
MAPS, ETC.
PLAN EVALUATION
METHODOLOGY
AIR QUALITY
STANDARDS AND
CRITERIA
ANALYSIS Of PLAN ADEQUACY RELATIVE
TO AIR POLLUTION CRITERIA
Figure 1 The AQUIP System Conceptual Design
.38
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4. The evaluation and ranking of the plan with respect
to other plans through analysis of air quality contours
and the computation of quantitative measures of impact.
5. The subsequent modification of the plan or the input data
and repetition of the process.
Of these five steps, the first and last require the direct involvement of
the planner to specify and manipulate planning data, to assess the degree
to which a plan satisfies objectives and constraints, and to specify changes
to the plan as deemed necessary. The remaining steps together form a model
in which the techniques and methodologies are quantitatively embodied as
self-contained computer programs.
A basic feature of the AQUIP System is that it permits the direct
input of land use planning data. As a result it can be used to compute
ambient air pollution concentrations related to specific land use activities,
The primary outputs of the system are in the form of computer-generated
maps and tabular listings of data. For example, computed concentrations
for each of the pollutants may be displayed as isopleth contours and over-
layed on base maps of the planning region, permitting a rapid visual cor-
relation of air pollution concentration levels and spatial distribution
patterns with the types and relative locations of land uses.
The heart of the AQUIP System is the mathematical diffusion model used
to compute pollutant concentrations averaged over arbitrarily specified time
periods. Typical time averaging periods for regional scale air quality
analysis are seasonal and annual averages. The model is a version of the
Martin-Tikvart Advection-Diffusion Model which has been modified by ERT to
improve the accuracy of calculating concentrations over short transport
distances and to improve flexibility in the use of the model.
39
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A third essential element of the AQUIP System is the air quality data
management and impact analysis software. In this portion of the system the
user can specify arbitrary measures of impact based on manipulation of air
quality data, emissions data, land use data, air quality standards, or any
other basic data from the input data set. In this step correlations among
such data sets can be tabulated or presented graphically, showing for example,
the distribution of air pollution concentrations, emissions densities,
impact parameters, land use densities, or any other subset of the basic data
of interest to the planner. Furthermore, such data can be used to compare
and rank plans in terms of air quality standards and criteria as specified
by the planner.
The details of procedures for converting land use data to emissions data
in formats required for input to the model are described in the Task 1 Report.
The details of the air quality projection model and the procedures used for
its validation are described in the Task 2 Report. The detailed description
of the computer programs, the procedures for using these programs, and the
interface between computer programs within the AQUIP System are described
and documented in the Task 5 Report.
The objective of the remainder of this chapter is twofold: 1) to discuss
the scope and level of detail of analysis appropriate to the consideration
of air pollution within the planning process; and 2) to discuss the specific
criteria, considerations and procedures essential to the analysis of air
pollution within the planning process.
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4.2 Classification of Air Pollution Considerations within the Planning
Process
In considering the application of air pollution analysis to problems
associated with land use planning it is necessary to match the analytical
approach to the level of detail and scope of the particular planning problem.
Of the many ways of classifying air pollution considerations, two appear most
useful in characterizing the appropriate approach to the analysis of land use
planning problems: these include the geographic scale of the analysis, and
the stage of the plan design within the planning process.
4.2.1 Geographic Scale of Analysis
One of the more useful ways to differentiate problems for air quality
analysis is in terms of the geographic scale of analysis. The characteristics
of the problem fall conveniently into three categories: regional, corridor
(or sub-regional), and microscale.
The analysis of air quality at the regional scale implies problems
characterized by areas on the order of 50 to 100 square kilometers or greater.
Air quality at such a scale of analysis is appropriately analyzed in terms of
long-term time-averaged air pollutant concentrations, such as seasonal or
annual averages. This scale is appropriate for the analysis of seasonal
variations in air quality and the analysis of the influence of regional scale
topographical features, synoptic meteorological conditions, and climatological
conditions. This scale is also appropriate for the analysis of large-scale
land developments, especially regional land use plans oriented towards a
future design time period. Under such circumstances the accuracy of the
described source emissions can be relatively broad scale so long as it re-
mains commensurate with a level of accuracy appropriate to the planning process,
41
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In particular, the level of analytical detail should be sufficient to detect
changes in regional air quality due to major planning options in terms of
the relative mix of land use types, the relative location of land uses within
the plan, and the relative intensity of land uses. Furthermore, this scale
of analysis permits the study of constraints imposed by the existence of
already developed lands and facilities by incorporating into the analysis an
inventory of background source emissions. While this scale of analysis permits
the planner to overview regional air quality patterns and concentration levels,
it cannot give sufficient detail in terms of time averages or spatial resolution
of concentration patterns to analyze localized impacts within the plan (for
example, variations in concentrations occurring over distances less than
1 or 2 kilometers, and over small time intervals such as a few hours).
The second geographic scale of analysis is designated as a corridor or-
sub-regional scale, and is particularly suited for the analysis of corridors
along major roadway facilities up to distances of a few hundred meters from
the road, or in the vicinity of sub-regional developments. This scale of
analysis permits a greater level of detail in describing the source emissions
and correspondingly permits a finer time and spatial resolution of pollutant
concentrations. At this scale, however, the analysis begins to encounter
problems of accuracy resulting both from localized influences, for example,
industrial sources in the vicinity of the roadways, and from regional back-
ground concentration levels.
The third and most highly detailed level of air quality analysis is
associated with the microscale analysis, and is appropriate to the description
of very localized air quality impacts such as in and around roadways or in
the immediate vicinity of buildings. Air quality analysis at this geographic
scale and level of detail would be of interest to the planner in determining
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on
the impact of specific facilities at a given location, for example, plan
view air quality contours in the vicinity of a major roadway intersection,
or air quality concentrations in the vertical cross-section of a roadway.
Such detail would permit the assessment of the relative impact of elevated,
at grade, or depressed roadway configurations on air rights structures, or
commercial activities and residential areas set back from the right of way.
This scale of analysis requires a highly detailed specification of source
emissions and geometries. Because the local concentrations at this level are
responsive to rapid changing meteorological conditions and source emissions
configurations, the analysis at this scale usually examines only "instan-
taneous" concentrations resulting from a single specified set of meteoro-
logical and emissions conditions, typically representative of worst case
and nominal situations. Although the state of the air in modeling concen-
trations over short time intervals and small distances is less advanced,
nevertheless this scale of analysis is highly useful in the planning process,
especially in selecting facility designs which minimize such localized impacts,
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4.2.2 Stages of Plan Development
Although planning ideally is an ongoing process, nevertheless the
development of a plan has three relatively distinct stages: the synthesis
or initial design of a plan, the evaluation and detailed analysis of a plan
and its alternatives to select a master plan, and the implementation of the
adopted plan. At each stage the requirements for air pollution analysis are
slightly different and represent a convenient method of classifying air
pollution considerations in the planning process.
In the plan synthesis stage the air pollution analysis ideally should
consider both regional air quality impacts and microscale impacts. First of
all, in developing plans, many ideas are considered and rejected rather
quickly. Plan alternatives are sketched on the basis of broad planning
issues and their implications on the mix of land uses and their relative
locations and densities. Thus the air quality analysis must permit a
correspondingly rapid estimation of the impact of the land use plans on
overall regional levels of air quality. A second need of the planner, how-
ever, is an understanding of the localized impacts of specific facilities
or elements of the plan in order to mitigate local air pollution problems
and to consider system effects. At this stage for example, the planner
should know the regional impacts as well as the localized impacts on specific
receptors and the results from alternative facility design concepts such as
central heating systems, and the relative density of residential areas.
In the second stage the planning process will be attempting to analyze
in some detail the aspects of the several planning alternatives in order to
determine in more detail the implications of each in terms of such consid-
erations as satisfying regional needs, development costs, economic feasibility,
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and environmental impact. In terms of the analysis of air quality, this
longer and more detailed evaluation of the plan requires primarily an analysis
of regional air quality to determine in detail the impact of the land use
or transportation system plan on regional air quality levels. Thus at this
stage, the appropriate air quality analysis is characterized by a more de-
tailed evaluation and ranking of alternative plans, and by a process of trial
and error in modifying plans to alleviate air pollution problems or to con-
sider the tradeoffs between air pollution considerations and other planning
issues. Analysis at this level of detail may require many months for
completing the air pollution analysis and a substantial amount of detail in
specifying land uses, their location, and other characteristics of the plan,
such as power plant locations and operating characteristics.
During the plan implementation stage the primary requirement for the
air quality analysis is to identify sub-regional and microscale impacts of
proposals for specific land uses, such as housing developments, and for specific
facilities such as roadways and incinerators. Such an analysis is necessary in
the planning process at this scale to generate required environmental impact
statements, to assess local impacts on critical receptors, to assess where to
locate a specific facility, to determine whether to permit a given type of
development, and to assess the efficacy of alternative designs for a specific
facility in alleviating a localized air pollution problem.
4.3 Procedures for Consideration of Regional Air Quality
In the current study the scope of the effort was directed only toward the
evaluation and ranking of alternative land use plans in terms of impact on
regional air quality. Thus the procedures are concerned with the analysis
of pollutant spatial distributions at the region-wide geographic scale and
with annual and seasonal time-averages of pollutant concentrations.
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Under these conditions, the procedures developed for the consideration
of regional air quality must at a minimum permit the planner to determine for
a given plan what air quality problems exist, where they are located, how
serious they are, and how they can be reduced or eliminated. More specifically,
the procedures developed in this study allow the planners to:
1. Determine whether the air quality resulting from a given land
use plan is in compliance with appropriate ambient air quality
standards.
2. Evaluate the impact of various plans in terms of spatial patterns
and concentration levels, and in terms of calculated quantitative
measures of impact on both regional air quality levels and
specific receptors.
3. Rank alternative plans in terms of established air quality
criteria.
4. Determine how to modify a plan in order to improve it relative
to air quality criteria.
The general procedures for using the AQUIP System to accomplish these air
quality analysis objectives are described in the following paragraphs.
4.3.1 Compliance with Ambient Air Quality Standards
Determining whether the air quality concentration levels resulting from
a proposed land use plan will comply with appropriate ambient air quality
standards is the most fundamental and direct method for considering air
pollution in the planning process. These standards have been established
by both federal and state laws and represent quantitative criteria which must
be met. Values represented by these standards are based on the best available
data concerning the effects of each pollutant on health, materials, vegetation,
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and visibility. Specifically "primary" standards reflect concern for impact
on human health, while "secondary" standards reflect concern for impact on
the general welfare (that is all other effects of air pollution impact on
society). Consequently there is an implicit relationship between ambient
air quality standards and air pollution impact.
Through use of the AQUIP System, air pollution concentration levels and
spatial distributions resulting from a given land use plan can be tabulated
and displayed graphically for each pollutant in terms of isopleth contours over-
laid on a base map of the land use plan. This air quality data can be tab-
ulated directly in terms of air quality averaged over each grid cell within
the planning region, or the results can be output directly in terms of the
ratio of the air pollution concentration to the ambient air quality standard.
Through these tabular and graphic outputs the planner can determine which
pollutants exceed standards, where the pollutants exceed standards, and by
how much the pollutants exceed standards.
In addition, analysis of the output data can be examined to determine
the contribution to total air quality resulting directly from the plan as
well as to identify the background concentration levels resulting from the
influence of emission sources located outside the planning region. Such an
assessment of background air quality levels and the display of the spatial
patterns of background air quality concentrations permit the planner to
assess how much flexibility exists within the planning region in choosing
elements of the plan in order to achieve other planning goals, such as more
employment or more housing, without violating air quality standards. One of
the key results of such an analysis is a determination of the degree to which
the consideration of air pollution is important within the planning process.
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4.3.2 Impact on Regional Air Quality
Procedures for examining the impact of land use plans on regional air
quality are based first on the examination of the spatial patterns of air
quality and. secondly, on the calculation of quantitative measures of
impact of each pollutant on regional air quality levels.
The first required step is an examination of air quality contours
(1 e spatial patterns of pollutant concentrations) for background air quality
over the region of interest. The resultant background spatial patterns and
concentration levels .ill show first the basic average regional concentration
!evels in relation to air quality standards and secondly, the location of
low and high pollutant concentrations within the planning region. This »-
dicates initially where to locate elements of the land use plan in order to
mlnimiZe peak total air quality concentrations (i.e. background concentrations
plus plan contributions). For example, if the planning region is located
within a highly urbanized region, background sources of emissions (especiaUy
those from industrial areas and transportation systems, will strongly In-
Huence pollutant concentration patterns within the region and hence ln-
nuence the Nation and ,ix of land use categories within a p!an to achieve
compliance with air quality standards.
The second step in the general procedure for examining regional air
quality is to determine total air quality contours for each pollutant for
the alternative plans and to compare the variations in these contours a»ng
the different plans. A convenient working procedure is to prepare a plastxc
overlay for each p!an showing the oase map of land use categories. Placing
the overlay onto the various pollutant concentration patterns (especially
the colter-generated graphic displays, permits a visua! examination of
the influence of land use types, and the relative location and intensity of
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land use activities on air quality patterns.
As a final step, a quantitative assessment of the impact of alternative
land use plans on regional air quality can be investigated by defining and
calculating quantitative measures of impact. The primary utility for such
measures of impact is in the comparative evaluation and ranking of alternative
plans. Quantitative measures of impact appropriate to the analysis of
regional air quality are discussed in detail in Section 5.
4.3.3 Impact on Receptors
The third major consideration in the procedures for analyzing the air
pollution impact of land use plans is the determination of the impact of the
resultant total regional air quality on specific land use categories and
critical receptors.
Of major concern within the planning process are the effects resulting
from the exposure of land use categories and critical receptors to various
pollutants. For example, carbon monoxide (CO) has direct effects on human
health resulting from short time exposures at high concentrations, but not
on plant life. Hydrocarbons, on the other hand, have no direct health effects
but do have very significant effects on plant life. Consequently, the planner
can significantly modify the localized impact of various pollutants on sen-
sitive receptors through the appropriate relative location of land uses within
the plan. For example, since elderly, ill, or very young persons are consid-
ered to be more susceptible to the effects of pollutants than the general
population, planners should be conscious of the locations of schools, hos-
pitals, and nursing homes in the plan relative to pollutant concentration
patterns.
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As in the case for the analysis of impact on regional air quality, the
procedures for the analysis of the impact of total regional air quality levels
on receptors are based first on the examination of the location of critical
land use categories and receptors relative to the spatial patterns of pollu-
tant concentrations, and secondly on the calculation of quantitative measures
of impact. The analysis of the spatial concentration patterns is achieved by
overlaying the plan base map on the calculated pollutant air quality contours
to correlate air quality concentrations with critical receptors. Furthermore,
the impact analysis computer programs within the AQUIP System permit the user
to define and calculate various types of quantitative correlations between land
use data and air quality data, and thereby generate any desired measures of
impact.
It is to be noted that there is no unique nor absolute method to evaluate
the air quality impact of a plan on regional air quality levels or specific
receptors. The analysis, for example, can examine the exposure of specific
receptors, such as total land area, open space, school children, or total
population, but each will result in a different measure of air quality impact.
Each impact measure represents a value judgment of the planner concerning the
relative importance of specific receptors and specific pollutants Ln evaluating
a plan. The inclusion of value judgments in the definition of impact measures,
however, is not necessarily detrimental to the procedures for plan evaluation.
It merely indicates that the relative worth of a plan ultimately is a reflect-
ion of a human value judgment, a problem in plan evaluation which is not new
to planners.
Since each of the pollutants has a different impact on different receptors,
a final step in the plan evaluation procedures is to define and calculate a
measure of the combined impact of several pollutants on a specific receptor.
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Such a single overall measure of air quality impact forms the basis for the
ranking of the different land use plans and is discussed in detail in
Section 5.
4.3.4 Techniques for Plan Modification
The fourth and final essential step in the procedures for considering
air pollution in the planning process is the method to guide planners in
modifying plans in ways that will improve general regional air quality or
will mitigate specific air quality problems. Through use of the AQUIP System
to display air quality contours and to calculate impact parameters, the
planner can identify the location and severity of air quality problems
and analyze the character of these problems in terms of the types of re-
ceptors and pollutants involved. The methodology for plan modification
makes use of this basic information to improve air quality.
In general a visual examination of the air quality contours should be
made first to identify air pollution problems, identify which sources are
the most likely contributors to the problem, and to identify which receptors
are most seriously affected. Then based on this examination, critically
affected receptors and land use categories should be moved to regions
within the plan showing lower concentration levels.
If a more organized and systematic approach to plan modification to
improve air quality is warranted in terms of the resources at the disposal of
the planner, a number of more sophisticated analytical techniques can be devised.
In particular, the AQUIP System can be used to compute: 1) sensitivity
coefficients, 2) receptor oriented influence coefficients, and 3) source
oriented influence coefficients.
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Sensitivity coefficients represent the changes in air pollution concen-
tration at a receptor point resulting from systematic changes in source
emission characteristics. This provides a direct air quality relationship
for a specific source-receptor pair.
Receptor oriented coefficients represent a set of data which, for a
given receptor, identify those sources which contribute concentrations of
greater than a specified amount or percentage at the receptor point. This
data can be used by the planner in determining which sources to modify,
while the sensitivity data indicates approximately how much of a change is
required in a given source to achieve necessary reductions in concentrations
at the receptor.
Source oriented coefficients, on the other hand, represent a set of
data which, for .a given source, identify the region within the plan over
which the source contributes concentrations of greater than a specified
level. This data in effect represents the influence region for the specified
source under the specified meteorological conditions. This data, which can
be displayed graphically, can assist the planner in determining where to
locate elements of the plan to minimize overlapping regions of influence
of major (but perhaps essential) sources.
These analytical influence coefficient data sets for plan modification
are not included in the current version of the AQUIP System, although they
can readily be incorporated into the system.
Instead the .procedures for plan modification using the current AQUIP
System have been derived empirically from the air pollution study of the
Hackensack Meadowlands and are listed as planning guidelines and are fully
documented in the Task 4 Report. A primary result of these guidelines is the
listing of the annual emissions per acre for the different land use categories
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analyzed for the Hackensack Meadowlands (see Table 12, Section 6).
On the basis of such data, those land uses which have a significant impact
on regional levels of emissions and hence a dominant effect on regional
pollutant concentration levels and air quality contours can be readily
identified. The result is the identification of land uses which produce
a significant change in regional air quality contours when moved within the
plan, and a corresponding identification of those land use categories which
have no significant impact on air quality contours when their location is
moved within the plan.
As a consequence, these guidelines can be used: 1) to establish rapidly
the emissions loading within a planning region due to a specified mix of
land uses; and 2) to identify which land use categories can be relocated
within the plan without a substantial impact on the regional air quality
concentration patterns. The result is a set of guidelines by which the
planner can locate heavy-polluting land use categories by the appropriate
consideration of meteorological conditions (primarily prevailing wind
directions) and by consideration of background air quality patterns and
levels. The basic idea is to place heavy polluters at locations having least
background concentration levels. Correspondingly, planners can locate other
land use categories, especially those of high sensitivity to pollutant effects,
in order to reduce localized impacts on such critical receptors.
These concepts for plan modification guidelines are described more
fully in the Task 4 Report, and are illustrated by the results of the
Hackensack Meadowlands impact analysis discussed in Section 6 of this report.
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4.3.5 Shortcomings of the Procedures
One of the basic problems with the above described procedures for
the evaluation of plans in terms of quantitative measures of impact is
that such impact measures are surrogates for air pollution effects of more
direct interest both to the planners and the general public. Specifically,
one would like to know the direct relationship of pollutant concentrations
to health effects, costs, material damage, aesthetic qualities of a region,
economic and social consequences and so forth. Such relationships, however,
are not presently well understood and basic information and data, concerning
health effects, costs, and economic consequences are scarce and often quite
unreliable. As reliable cost and effects data become available, however,
they can readily be included in the AQUIP System analysis procedures,
primarily by incorporating them directly into the quantitative measures of
impact.
A second basic problem related to the analysis procedures described
above is that these procedures do not readily permit the generation of
information and data showing the relationship between air pollution con-
siderations and other issues within the planning process. In most cases
such issues are to some degree interactive with air pollution considerations.
For example, the relationship between solid waste problems and air pollution
levels may be a direct function of the impact on water quality levels,
depending upon alternative choices of techniques of solid waste treatment
and disposal. 'However, further research and much more hard data are required
before such systems relationships can be fully taken into account within
the consideration of air pollution in the planning process.
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A final problem related to the procedures for investigating regional
air quality is that the resultant time averaging periods and geographic
scale of analysis do not give adequate information concerning microscale
impact problems. The regional air quality analysis, for example, gives no
information on peak hour traffic conditions; the resultant peaking of concen-
trations over short distances and short time periods will not show up as a
problem when averaged over longer time periods and larger distances. Thus,
conclusions concerning the land use plan based on a regional scale geographic
analysis with annual average concentrations must be evaluated and interpreted
with extreme care. Although the resultant mix and location of land use cate-
gories for a land use plan may be selected in such a way as to minimize the
impact on both regional air quality levels and critical receptors, nevertheless
the regional scale analysis may not indicate the existence of, nor provide
a solution to, microscale impact problems.
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5. METHODOLOGY FOR PLAN EVALUATION AND RANKING
5.1 Introduction
The analysis of a land-use or transportation plan in terms of air quality
criteria depends on three basic types of information: land-use data, air
quality data, and air quality criteria. As discussed in the preceding
chapter the general procedures for incorporating air pollution considera-
tions into the planning process require the calculation and analysis of these
data both in terms of spatial patterns of pollutant concentrations and their
correlation with land uses, and in terms of quantitative measures of impact
(either on general regional air quality levels or on specific land-use cate-
gories and high-risk receptors). The analysis of spatial patterns of air
quality can be carried out by calculating isopleth contours of pollutant
concentrations, but their interpretation relies largely on visual examina-
tion and subjective judgment rather than on quantitative analysis. On the
other hand, quantitative impact measures permit analytic evaluation, but
tend to subdue the physical and intuitive interpretation of results.
The evaluation and comparative ranking of plans is based on the inter-
pretation of these types of data and analytical results. Such an evaluation
would be complex and cumbersome without a systematic approach, and the
ranking or ordering of results would be especially difficult without some
means of expressing the results quantitatively. Consequently, because of
the critical importance of this subject, the purpose of this chapter is to
describe in more detail the characteristics and use of quantitative impact
measures in plan evaluation and ranking. Since procedures for plan evalua-
tion differ from those for plan ranking, they are discussed separately in
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the following sections. Specifically the section on plan evaluation sum-
marizes the general evaluation procedures, identifies receptors and land
uses of prime concern in the evaluation, and identifies the impact measures
selected for the analysis. Similarly the section on plan ranking identifies
some prior efforts to develop total (i.e., multipollutant) air quality rank-
ing indices, describes the ranking index selected for this analysis, and
summarizes the basic procedures for plan ranking.
5.2 Procedures for Plan Evaluation
5.2.1 Basic Requirements
In this study, plan evaluation is meant to imply the analysis and
interpretation of air pollution impact for a single plan and the comparison
of plans on the basis of single pollutants. In order to carry out the
evaluation of a plan the procedures must permit the evaluation of both
regional air quality impact and the impact on specific receptors. Further-
more, the plan evaluation methodology must incorporate some quantitative
measure of these impacts both in terms of impacts from individual pollutants
and in terms of the combined impact of several pollutants. Ideally,, such
quantitative impact measures should be relatable to some standard reference
value, such as ambient air quality standards, in order to permit a convenient
intuitive or physical interpretation of the calculated values.
5.2.2 Summary of Plan Evaluation Procedures
The basic methodology for plan evaluation consists of procedures for
the analysis of air quality on a regional scale and for the analysis of
impact on specific land uses and critical receptors through quantitative
raeasures of impact and through graphical displays of the spatial distribution
of air quality contours.
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The essential steps in these procedures consist of:
1. The calculation and comparison of pollutant concentration levels
with ambient air quality standards.
2. The correlation of air quality contours and concentration levels
with specific land use categories, their relative location, and
intensity of use.
3. The calculation of impact measures as defined in terms of regional
air quality and in terms of impact on specific receptors.
4. The calculation and display of supplementary air quality or land
use data, for example, the calculation of additional impact
measures, or the display of the location of critical receptors.
The critical step in the plan evaluation is the calculation of air
quality data, for example, the ratio of pollutant concentrations to ambient
air quality standards for each pollutant at points within the planning
region. Examination of isopleth contours of this ratio within the planning
region thus indicates the location and size of regions which exceed standards,
and the amount by which standards are exceeded for each pollutant. The speci-
fic steps for obtaining air quality and land-use data, and for generating
contour maps and tabular data using the AQUIP System are discussed in detail
in the Task 5 report, which describes the computer programs, their required
inputs, the resultant outputs, and procedures for using these programs.
The further evaluation of the plan, however, is primarily concerned
with the analysis of quantitative impact measures. A characteristic feature
of the plan evaluation procedure is that it focuses on the impact resulting
from each pollutant rather than from a combination of pollutants. This
permits a comparison of impacts on various receptors on a pollutant by pol-
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lutant basis. Multipollutant impact measures are more useful for comparing
and ranking alternative plans (as discussed in Section 5.3). The specific
impact measures used for plan evaluation in the Hackensack Meadowlands air
pollution study are described in the following paragraphs, and the analytic
results and interpretation based on these impact measures are documented in
Chapter 6.
5.2.3 Selection of Impact Measures
An essential element of the evaluation of land-use and transportation
plans is the calculation and analysis of quantitative measures of impact
on regional air quality and specific receptors. In general, the impact
measure must be related to a specific plan, to a specific receptor or land-
use category within the plan, and to a specific pollutant. Thus the impact
parameter (IP) is a function of three variables: the plan, the receptor
and the pollutant.
In this study the impact parameters which were found to be most useful
and meaningful in plan evaluation were: (1) measures of integrated receptor
exposure, and (2) measures of average receptor exposure. The integrated
receptor exposure for a given plan is calculated by superimposing an arbi-
trary grid system on the planning region, forming the product of the number
of receptors per grid cell times the pollutant concentration within the grid
cell, then summing this product over all grid cells within the planning
region. The general formula for the integrated receptor exposure impact
parameter is
lP(j,k,l).re = I R.(k,l)c (j,k) C5'1)
.Li C • 1 1
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where
IP (j,k,l) = impact parameter for pollutant j, plan k,
and receptor 1
R. (k,l) = number of receptors (or land-use area) in
1 grid cell i for plan k and receptor 1
C. (j,k) = mean predicted ambient concentration within
1 grid cell i for pollutant j and plan k
j = specified pollutant
k = specified plan
1 = specified receptor or land-use category
i = ith grid cell within the planning region
ire = designation for integrated receptor exposure.
This impact parameter has units of number of receptors times pollutant con-
centration, and clearly is an indicator of the cumulative value of receptor
exposure within the plan. Since this impact measure is sensitive both to
the number of receptors and to concentration levels, it is likewise clear
that the impact measure will be higher when larger numbers of receptors
are exposed, just as it will be higher when higher concentrations exist. It
is to be noted also that this exposure is based upon the calculation of the
mean annual concentrations. Thus the exposure represents the mean concentra-
tion to which a receptor is exposed at any instant in time. The important
distinction is that this impact measure is based on exposure rather than
dosage, which can only be inferred based on an assumed time duration of
exposure.
The second impact parameter, the average receptor exposure is calculated
from the integrated exposure impact parameter simply by dividing the resultant
integrated exposure by the total number of receptors within the plan. Thus
the units of the average exposure impact parameter are units of concentration.
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Physically, the average exposure is an indicator of the concentration to which
any given receptor within the plan will be exposed on the average. However,
since exposures are zero in regions of the plan where no receptors exist, it
is to be noted that this impact parameter represents the average pollutant
concentration only within those regions of the plan where receptors are
located.
The choice of specific receptors or land uses for use in plan evaluation
can be arbitrary and is largely a matter of judgment on the part of the
planner and should reflect those issues which he considers most important.
In the Meadowlands study the land-use categories and receptors examined were
total land area of the planning region, population, students, residential
land area, open space land area, and a combination of commercial and industrial
land area.
An impact parameter based on total land area represents a good measure
of impact on regional air quality. Since the total area of the planning
region is fixed, the integrated and average exposure impact parameters differ
only by a constant factor and thus both are representative of the mean pol-
lutant concentration throughout the entire planning region.
Impact parameters based on population and student receptors are of
interest in terms of health effects. Students, especially those in elemen-
tary grades, represent receptors highly sensitive to the effects of pollutants.
An impact parameter based on hospitals and nursing homes is also of interest
since the elderly and the ill are considered to be high risk receptors, but
was not included in the analysis due to the difficulty in deriving information
on this class of receptors from the given land use data.
An impact parameter based on residential land area is of interest since
it is most representative of the basic conditions for which the ambient air
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quality standards were established; namely, areas where the general public
has a high degree of access and high probability of long-term exposures.
Residential area is of concern in terms of effects on health, plant life,
materials, and aesthetics.
An impact parameter based on open space is of interest because of the
special nature of this land use category. Open space typically denotes parks,
wooded areas, recreation areas and playgrounds, and open water. The general
public usually has free access to such areas, although time exposures within
these areas may be somewhat limited. Thus there is some concern for aesthetics
and for health effects on both human and wildlife populations. Of greatest con-
cern, however, is the exposure of plant life to pollutants.
Commercial and industrial areas are of interest since they include such
areas as shopping centers, roadways, and pedestrian malls, where the general
public has free access, although exposure usually occurs for short time periods,
Such areas also have large numbers of working personnel, although applicable
industrial health and safety standards typically are much less stringent
than ambient air quality standards.
From this large (and non-exhaustive) number of receptors, it is clear
that selecting impact parameters most appropriate to the evaluation of a
plan is a matter of judgment in terms of the specific plan and circumstances.
In the analysis of the Hackensack Meadowlands plans, the integrated total
area exposure was examined as a measure of regional air quality levels, and
the average population exposure was examined as the principal measure of
impact on critical receptors.
5.2.4 Other Analysis Procedures for Plan Evaluation
There is no limit to the number of correlations and impact measures
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that can be defined and applied to the evaluation of land-use and
transportation plans. The impact measures described above for use in the
Meadowlands air pollution study are obvious choices and are easily generated
from the AQUIP System using readily available air quality and land use data.
However, the AQUIP System allows a significant amount of flexibility in
defining and calculating other measures of impact and in specifying air
quality criteria other than ambient air quality standards.
As a specific example of an alternative (but supplementary) approach to
plan evaluation, a quantity arbitrarily defined as a "land-use compatibility
score" for a given plan was calculated for the Meadowlands plans. First, a
"land-use air quality compatibility matrix" was constructed (as illustrated in
Table 20 of Sec. 6.3). This matrix lists land use categories (or receptors)
versus pollutants, bach element of the matrix represents in our judgement the
relative sensitivity (or tolerance) of a particular land use or receptor to a
given pollutant. For convenience of calculation and interpretation, the
numbers in the matrix represent the ratio of the permissible pollutant con-
centration to the appropriate air quality standard. This matrix does not
redefine air quality standards, but rather assigns a tolerance factor based on
value judgement to each land-use category or receptor. For example, commercial
and industrial land may be considered as being relatively insensitive to SO effe
and thus capable of tolerating SO concentrations up to twice the S0? standard,
whereas open space may be considered as being highly sensitive to effects of
HC, and thus capable of tolerating hydrocarbon concentrations of no more
than one-half the HC standard.
Then the AQUIP System software, primarily the IMPACT program, was used
to: (1) calculate within each grid cell of the planning region the number
of pollutants (from 0 to 5) which violated any one of these land-use air
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quality compatibility criteria, and (2) display graphically on the plan the
spatial distribution of the number of violations per cell. This display
shows the regions of the plan where more pollutants tend to violate the land-
use compatibility criteria and thus indicate regions of more severe air quality
problems. As a final step, the land-use compatibility score was calculated
by summing the number of violations per cell over all grid cells within the
plan.
Other useful analytic procedures to aid in plan evaluation include:
(1) The calculation of sensitivities of air quality (or impact parameters)
to changes in land-use type, location, or intensity; (2) the graphical dis-
play of the location and intensities of land uses within the planning region;
and (3) the creation of yet other data sets, such as additional correlations
between air quality and land-use data, which can be displayed graphically.
For example, in the analysis of the Hackensack Meadowlands plans it was
found useful to display the spatial distribution of the intensity of the
major land-use categories and to correlate visually land-use categories,
locations, and intensities with air quality contours. It was also
found useful to examine the influence of a few major facilities and to calcu-
late the concentrations resulting from the specific facility. In particular,
some limited sensitivity data were obtained for the location of a major
incinerator within the Meadowlands region and for the influence of local
roadways.
As practical working procedures for the plan evaluation it was found
useful to construct a plastic overlay showing the boundaries, rivers, major
roads, and outlines of land-use categories for each plan. This overlay was
made at the same scale as all of the computer graphic outputs. As a result
the single land-use map could be overlaid onto the dozens of air quality
65
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contour maps and impact parameter spatial distribution maps. For reference
and correlation work it was also found useful to develop a color photograph
of the plan itself at the same scale as the computer graphic air quality
maps.
5.3 Procedures for Plan Ranking
5.3.1 Basic Requirements
The requirements for the ranking of alternative land-use plans differ
slightly from the requirements for the analysis and evaluation of a particular
land-use plan. The basic need for plan ranking is to generate a single num-
ber or index which can be calculated for each plan to permit the relative
ranking of the plans. This ranking index may be associated with the impact
of a single pollutant, thereby allowing a pollutant by pollutant comparison
and ranking. The more common need, however, is to compare plans on the basis
of a single ranking index representative of the total air quality resulting
from the combined impact of all pollutants (i.e., a multipollutant air quality
index).
As discussed previously in this report it is clear that no ranking
index is unique or absolute. In fact it is desired that the ranking index
be sufficiently flexible to accommodate subjective value judgments in the
ranking methodology. It is required, however, that the ranking methodology
be based on a formula in order to permit the ranking to be based on quanti-
tative criteria precisely stated in objective terms. It is also required
that the results of the ranking methodology give reasonable agreement with
known facts and intuitive judgment.
Finally, it is not necessary to give special weighting to plans which
66
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do not meet air quality standards since the principal objective is to estab-
lish the relative ranking of plans. Consideration of the degree of compli-
ance with standards is more appropriately the subject of the plan evaluation,
where plans with serious problems in meeting standards would either be rejec-
ted or modified in some way to alleviate the problem.
5.3.2 Background on the Development of Multipollutant
Air Quality Indices
Considerable attention has been devoted to the problem of characterizing
the overall air quality associated with the combined influence of several
pollutants. The common basic desire is to devise a single number (or index)
calculated by a formula or other quantitative means which would represent
a measure of overall air quality. Air pollution control agencies in many
cities and states have attempted to devise such an index both as a means of
conveying information to the general public and as a means of technically
assessing the severity of air quality; for example, to indicate the inception
of various levels of episode conditions. Such an index is useful (if not
mandatory) in estimating the benefits on total air quality of control stra-
tegies which influence several pollutants to different degrees. The federal
government has attempted to rank the total air quality in different locations
(e.g., major cities) on the basis of such an index in order to aid in estab-
lishing priorities for its air pollution programs. The multipollutant air
quality index has also been proposed for use in comparing total air quality
resulting from different sources, and in establishing meaningful long-term
trends in air quality for a region even when the pollutant mix is changing.
Finally, such an index is essential in the planning process to rank alterna-
tive land-use and transportation plans.
67
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Among the many indices in use or proposed for use, the simplest measure
of total air quality involves the summation of individual pollutant emission
weights . The next level of sophistication generally involves the use of
weighting factors based on air quality standards for combinirg pollutant
emissions or concentrations. One such index is "Pindex" as developed by
Babcock . The original version of Pindex used emissions data for TSP,
SO,,, NO,., CO, and HC and included a sulfur oxides-particulate matter (S0y-
PM) synergism term and a provision accounting for the photosynthesis of
oxidants. In this index, weighting (or tolerance) factors equivalent to the
reciprocal of air quality standards were applied to each pollutant. In a
o
revised version of Pindex , ambient concentrations (not emissions) were
used, the SO..-PM synergism term was removed, hydrocarbons were deleted as
a pollutant, and tolerance factors were extrapolated from EPA standards to
equivalent values based on 24-hour averages for all pollutants.
Similar indices have been devised by a number of air pollution control
agencies, although most combine only two or three pollutants, primarily SOY,
A
PM, and occasionally CO and oxidants. For example, Fulton County (Atlanta),
q
Georgia uses an index which combines concentrations of three pollutants
as fractions of their respective standards, and the (San Francisco) Bay Area
Air Pollution Control District uses an index which sums four pollutants
(N02, CO, COH*, and oxidants) weighted by factors related to California air
quality standards.
A number of other indices have been devised which combine pollutants
based on power'law formulas. For example, in an early effort Green
proposed an index based on based on S02 and COH in which the concentration
for S02 was raised to a power and multiplied by a constant and added to a
Coefficient of Haze (for particulate matter).
68
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similar term for COH. A similar index has been used by the Province of
12 1 ^
Ontario ' , and more recently applied to the Sarnia, Ontario, petro-
chemical complex in conjunction with synoptic meteorological forecasting.
Another index, based on weighting factors related to air quality standards
and involving a power law formula, has been proposed by the Oak Ridge National
8 15
Laboratories ' , and has been used by the Knox County (Tennessee) Air
Pollution Control Department . Specifically, this index combines CO,
SOY, NOY, TSP, and oxidants by weighting the ambient concentrations of each
A A
pollutant by the reciprocal cf their respective EPA air quality standard
(extrapolated to a 24-hour averaging period). The sum of these weighted
concentrations is multiplied by a constant and then raised to a power such
that all pollutants at their standards yield a combined index of 100.
17 18 19
A variety of other formulations have also been proposed ' '
For example, the Columbia-Willamette Air Pollution Authority uses an index
based on the integrating nephelometer , which measures light-scattering
and hence relates air quality to visibility rather than pollutant concentra-
21
tions. In Osaka, Japan, several indices for combining S02 and TSP have
been investigated, including an index based on multiplying the highest values
22 23
of SO and TSP observed during a day. In New York City the alert system '
A
24
is based on several combinations of SO.,, CO, and COH. Prodehl and Lowry
have developed an index which describes geophysical potential for air pol-
lution by predicting inversion severity based on vertical temperature gradi-
ents rather than on pollutant levels.
More sophisticated indices involving statistical measures of pollution
levels have also been proposed ' . For example, Fensterstock, et al
has proposed an index in which ambient pollutant concentrations are standard-
ized to yield individual pollutant indices, and the resultant individual
pollutant indices are weighted and summed to form a single total air quality
u9
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index. This methodology may use concentrations which are taken from ambient
monitoring data or are predicted by means of a diffusion model. The concen-
trations are converted into a standard statistical distribution with a pre-
set mean and standard deviation. The resultant individual pollutant indices
are assumed to be equally weighted, although values other than unity can be
used. ^Likewise, the index can incorporate any number of pollutants although
it has only been used to combine SOX, CO, and TSP because of lack of avail-
able data.
In spite of these diverse efforts to develop multipollutant air quality
indices, the great majority exhibit characteristics which limit
their utility, meaningfulness, or general applicability. One of the problems
is that most such indices are specialized to a locality, usually in order to
take advantage of available sources of data and to reflect the most important
local air quality problems. For example, most indices incorporate only a
few pollutants, predominantly S02 and TSP (especially in industrialized
regions). Likewise, one or more other pollutants such as CO, HC, or oxidants
may be included depending on local problems. Data availability has been a
particularly constraining factor since most regions have not had extensive
ambient air monitoring networks, nor have monitored more than one or two
major pollutants on a continuous basis. Furthermore, in some cases the
indices have been based on specific monitoring instruments which may not
measure pollutant concentrations directly.
In addition to these problems, a number of other problems of a more
general nature occur which limit the utility of the proposed indices. For
example, several basic problems are associated with the use of air quality
standards as weighting factors: standards do not exist for all pollutants;
standards are written in terms of different time-averaging periods for vari-
ous pollutants; state and federal standards occasionally differ; and standards
70
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may be subject to change. Other problems are associated with the interpre-
tation of values resulting from such indices. Indices referenced to air
quality standards permit some degree of intuitive interpretation, but those
based on arbitrary definitions and scaling factors are more obscure in meaning.
Consequently, studies usually must be undertaken to establish empirically a
relationship (i.e., correlation) between index values and observed severity
of total air quality.
Another basic problem relates to the choice of data for use in the cal-
culation of the index. Inputs based on maximum observed concentrations within
a specified time period at a given monitoring sites are not as representative
of regional air quality as data averaged over several monitoring sites and
over longer time periods. Most indices are oriented toward assessing day to
day air quality levels and only a few can be extended to longer time periods,
for example, to assess seasonal and annual air quality. Furthermore, the
number of pollutants that can be considered is generally limited to the major
pollutants since few others are routinely monitored, and little is known
about their effects, concentration levels, or criteria for evaluation.
A final problem is that none of the proposed indices relate directly
to effects of prime interest; for example, the relationship of total air
quality to health, economics, and aesthetics. Furthermore, such indices do
not account for effects on specific receptors; for example, the specific
influence of pollutant levels and distribution patterns on population.
5.3.3 Methodologies Considered for Plan Ranking
Of the many concepts for multipo]lutant air quality indices, only a
few were considered to be applicable to the ranking of land-use plans. The
methodology for ranking plans must, for example, have the capability of:
(1) combining an arbitrary number of pollutants (provided evaluation criteria
-------
are available), (2) incorporating concentrations data representative of
regional air quality (in particular, data from many points within the region
averaged over seasonal and annual time periods), and (3) incorporating the
influence of regional air quality on specific receptors. Furthermore, it
is recognized that no ranking methodology is unique, and that none can yet
incorporate pollutant effects of most direct interest, particularly health
and economic effects.
On the basis of such requirements and constrairts, several potentially
useful ranking schemes were considered. In this section, three basic schemes
representing the most viable candidates for a ranking index are described
since all were considered to have both good and bad features, and since
the final choice was based on value judgment.
In most general terms the ranking index is calculated for a given plan
in terms of a formula which combines the weighted contribution of the dif-
ferent pollutants. This is represented by the following formula:
RI(k,l) = I WF (j) IP(j,k,l) (5-2)
j
where
RI(k,l) = ranking index for plan k and receptor 1
WF(j) = weighting factor for pollutant j
IP(j,k,l) = impact parameter for pollutant j, plan k, and receptor 1
j = specified pollutant
k = specified plan
1 = specified receptor or land-use category
This ranking index depends on the initial selection of an impact parameter
of the type discussed in Section 5.2.3 (for example, average population
exposure or integrated total area exposure). Such indices thus have the
capability of incorporating effects on specific receptors. Other forms for
72
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both the ranking index and the impact parameter were considered, particularly
power law formulas. These were rejected, however, since they complicated
the ranking index without contributing to the meaningfulness of the results.
Consequently, the three ranking schemes finally considered reduced to
a question of the form of the weighting function (i.e., how to combine the
impact parameters for different pollutants). The three schemes are desig-
nated as:
1. The Relative Ratio ranking index.
2. The Pindex ranking index.
3. The Normalized Impact Parameter ranking index.
The characteristic formulas for the weighting functions for each of these
ranking indices are listed in Table 1 and sample calculations of each index
are illustrated in Table 2.
It was found that the first scheme, the Relative Ratio ranking index,
is an especially good procedure for comparing plans on a pollutant by pollu-
tant basis and was, in fact, used for such an analysis of the Meadowlands
plans. It gives not only the relative rank of plans, but also an indication
of the percent variation between plans in air quality as based on the specific
impact parameter under consideration. Furthermore, results for the combina-
tion of all pollutants show good agreement with intuitively expected ranking
results, especially those based on a visual examination of air quality con-
tours. However, this index does exhibit a pathological case when an impact
parameter for a specific pollutant and plan becomes an extremely small value
relative to the other impact parameters (as illustrated in Table 2 for pol-
lutant A, plan 1). This may occur either when one pollutant has very low
concentrations for a specific plan, or when the number of receptors effected
is very small for a specific plan. Since the weighting factor is formed
73
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TABLE 1
ALTERNATIVE FORMS CONSIDERED FOR A PLAN RANKING INDEX
Ranking Index1- •*
1. Relative Ratio*-2-1
2. Pindex^3-1
3. Normalized Impact
(4)
Parameter
1
n
1
n
1
n
Weighting Factor
~~ 1 ~
min IP (j,k,l)
__ k
r : i
AAQS (j)
1
avg IP (j,k,l)
k
(1) RI (k,l) = Z WF (j) IP (j,k,l)
where
(2) min IP
k
(3) AAQS(j)
avg IP
RI(k,l) = ranking index for plan k and receptor 1
WF(j) - weighting factor for pollutant j
IP(j,k,l) = impact parameter for pollutant j, plan k, and
receptor 1
j = pollutant
k = plan
1 = receptor or land use category
n = number of pollutants
= minimum value of the impact parameters calculated
for the plans (for a given pollutant and a given
receptor).
= mean annual ambient air quality standard (or extra-
polated equivalent) for pollutant j.
= average value of the impact parameters calculated
for the plans (for a given pollutant and a given
receptor).
74
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TABLE 2
SAMPLE CALCULATIONS FOR RANKING INDICES
Matrix Element
Impact parameters
Weighting Factors for:
Relative Ratio
(based on rain IP)
Pindex
(based on AAQS)
Normalized IP
(based on avg IP)
Relative Ratio
weighted impact
parameters
Pindex weighted
impact parameters
Normalized Impact
Parameter weighted
impact parameters
Matrix
Plan
1
2
3
--
—
--
1
2
3
1
2
3
1
2
3
Pollutant
A
1
10
16
1/1
1/20
1/9
1.0
10.0
16.0
0.05
0.50
0.80
0.11
1.11
1.78
B
20
15
25
1/15
1/5
1/20
1.33
1. 00
1.67
4.0
3.0
5.0
1.00
0.75
1.25
C
4
2
3
I/2
1/5
1/3
2.0
1.0
1.5
0.8
0.4
0.6
1.33
0.67
1.00
Ranking
Index
--
--
--
--
--
4.33/3=1.44
12.00/3=4.00
19.17/3=6.39
4.85/3=1.62
3.90/3=1.30
6.40/3=2.13
1.44/3=0.48
2.53/3=0.84
4.03/3=1.34
Numbers in this table are hypothetical.
75
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from the reciprocal of the minimum impact parameter found among the plans
(for the specified pollutant), the corresponding weighting factor for the
pollutant involved in the pathological case will be extremely large relative
to the weighting factors for the remaining pollutants. As a consequence,
the ranking order of the plans will be entirely dominated by the single pol-
lutant (as illustrated by pollutant A in Table 2). This in effect says that
if a single pollutant has a very low concentration or impact in a single plan,
then that plan gets ranked highest regardless of the consideration of other
pollutants. This is an undesirable result since ideally such a circumstance
should be discounted as a singular fortunate event and the ranking should be
based on the relative impacts of the remaining pollutants. It is not expected
that this pathological case will occur often, however, especially if back-
ground pollutant concentration levels within the planning region are high
relative to concentration levels resulting directly from the plan.
The second ranking index is based on the work of Babcock7'8 and
hence is designated as Pindex, although the formula for the current £lan
ranking index is somewhat more generalized than that originally proposed by
Babcock for an index of total air quality Since the weighting factor for
each pollutant impact parameter is formed by taking the reciprocal of the
mean annual ambient air quality standard (or extrapolated equivalent) for
that pollutant, the Pindex ranking index has the especially good feature that
it relates the impact to an absolute basis or criteria, namely, air quality
standards. Thus, .the ranking index bears some relation to an established
basis and hence at least some intuitive feeling for the meaning of different
magnitudes of the index can be established.
76
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However, because the impact parameter for each pollutant is normalized
by its air quality standard, this index does not give a good indication of
percent variation in air quality among plans. Furthermore, it exhibits a
pathological case when a specific pollutant has exceptionally high concen-
tration values relative to its air quality standard for all plans (as illus-
trated by pollutant B in Table 2. In such a case the contribution from
that particular pollutant completely dominates the ranking index. Since
the same thing happens for all plans, the result is that the ranking order
for the plans follows exactly the order of the impact based on the single
pollutant. Philosophically, this may be an entirely acceptable result to
the evaluator since it says that if one pollutant exceeds standards in all
plans by a large value, then that pollutant represents the most critical
problem; and the best plan, therefore, is the one which has the least severe
problem in terms of this singular (worst) pollutant. For this analysis it was
concluded, however, that this pathological case should be avoided since it
is not evident that the contributions of other pollutants should be ignored.
For example, variations among plans in terms of the singular pollutant may
be very small, while substantial variations may occur among plans for other
pollutants. Furthermore, it is observed that this pathological case can
occur with high frequency, especially for planning regions in the vicinity
of urban areas, since it results from situations in which there are high
levels of background concentrations for one or more pollutants.
The third scheme, the Normalized Impact Parameter ranking index, was
devised as a compromise between the other two indices and has the significant
advantage that it overcomes the difficulties encountered in the pathological
cases for the other two ranking indices. In particular, this is accomplished
by forming the weighting factor for each pollutant impact parameter by taking
77
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the reciprocal of the average impact parameter for all plans being considered.
In other words, once the impact parameters are calculated for each plan for
a specific pollutant, the average value is calculated, and its reciprocal
used as the weighting factor for the specified pollutant. The process is then
repeated for the remaining pollutants (see Table 2). As a consequence of
using these weighting factors, the results of the ranking methodology are
much less sensitive to the conditions which lead to the pathological cases of
the other ranking schemes, as illustrated by the sample calculations in
Table 2.
For example, if one plan and one pollutant yield a small impact para-
meter, then this term contributes very little to the total ranking index
since it will be divided by the average impact parameter for the various
plans rather than by the minimum impact parameter. Thus the weighting fac-
tors effectively discount this situation which led to the pathological case
for the Relative Ratio ranking index. Furthermore, it is observed that the
Normalized Impact Parameter ranking index preserves the same relative ratios
among plans when ranked on a pollutant by pollutant basis as the Relative
Ratio ranking index. However, it does not preserve the same relative ratios
for combined pollutant rankings as the Relative Ratio index, although it does
preserve the same relative ranking of plans.
Likewise, as illustrated by pollutant B in Table 2, if one pollutant
has extremely large impact parameter values for all plans relative to its
air quality standards, then the use of weighting factor based on the, average
value of these impact parameters preserves the relative differences among
plans for the pollutant, while preventing it from dominating the ranking
index as happened in the pathological case for the Pindex ranking index.
78
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Under such conditions the other pollutants are weighted more heavily than
in the Pindex method. It is to be noted, however, that the Normalized Impact
Parameter ranking index does not yield numerical values which can be intuitively
related to an absolute scale of reference as does the Pindex ranking index.
5.3.4 Summary of Plan Ranking Procedures
On the basis of the relative merits of the three basic ranking indices
considered in the previous section for use in the methodology for plan rank-
ing, the Normalized Impact Parameter ranking index has been selected for use
in calculating the relative ranking of plans.
The specific procedures adopted for ranking of alternative land-use
plans include the following steps:
1. Select or define the measure of impact (impact parameter) of
interest to serve as the basis for the evaluation.
2. Calculate the quantitative measure of impact for each plan and
each pollutant. This can be done either by hand calculations
based on the air quality and land-use data generated previously
from the AQUIP System for the plan evaluation or can be programmed
and calculated directly by the AQUIP System.
3. Tabulate the results of the calculations of the impact parameter
for each plan and each pollutant. It is to be noted that no
maps result since the data has no inherent spatial distribution
characteristics.
4. Examine the ranking of plans on a pollutant by pollutant basis.
To do this, the above-tabulated impact parameter data can be used
to calculate for each plan the Relative Ratio ranking index as
79
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described in the previous section, showing both the relative rank
of plans and the percent variation in air quality among plans for
the given pollutant.
5. Examine the ranking of plans on the basis of the Normalized Impact
Parameter ranking index for the combination of pollutants. This
can be done by calculating values for the ranking index for each
choice of impact parameter either manually or with the AQUIP System.
The resultant values of the index for each plan form the numerical
ranking of the alternative land-use plans.
6. Repeat the procedure for ranking plans on the basis of combined
pollutants for different impact parameters in order to determine
whether different impact parameters cause the ranking of plans
to change.
7. As an optional step, rank plans based on the calculation and
evaluation of other indices, for example, Land use/Air quality
Compatibility Scores. Such Land-use Compatibility Scores were
not used as a formal basis for plan ranking in the Meadowlands
study primarily because the procedure is too complex and the
meaning of the ranking score is somewhat obscure and not readily
relatable to experience and intuition. Such results were used,
however, to provide useful auxiliary information in the plan
evaluation and ranking process.
80
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6. AIR QUALITY ANALYSIS FOR THE HACKENSACK MEADOWLANDS
6.1 Objectives of the Analysis
This section documents the results of a study conducted to evaluate and
rank in terms of air quality criteria the four alternative 1990 Comprehen-
viRl
sive Land Use Plans for the New Jersey Hackensack Meadowlands planning
region. The basic objective of this analysis was to demonstrate the proce-
dures and methodologies developed for considering air pollution in the
planning process through the direct application of such methodologies to
the planning alternatives developed for the Meadowlands. Regional air
quality concentrations for particulates (TSP) , sulfur dioxide (S02), carbon
monoxide (CO), hydrocarbons (HC), and nitrogen oxides (NOX), were analyzed
in terms of annual averages and summer and winter seasonal averages. The
analysis also included the influence of sources outside the Hackensack
Meadowlands (i.e., background sources) on air quality within the planning
region.
6.2 Summary of Plan Characteristics and Data
The New Jersey Hackensack Meadowlands District is a tract of land
»
measuring approximately four mi 16s by eight miles extending in a north-south
direction along the Hackensack River. As shown in Figure 2, the Meadowlands
is located at the hub of the New York - New Jersey metropolitan area. Within
a five-mile wide zone around the Meadowlands is Manhattan immediately across
the Hudson River to the east, Jersey City and Newark to the south, Paterson
and Passaic to the northwest, and Hackensack to the north.
81
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HAC KEN SACK
MEADOWLANDS
DISTRICT
Figure 2 Location of the Hackensack Meadowlands District
82
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Today, the Hackensack Meadowlands consists largely of meadows, marshes,
and salt-water swamps. Of its nearly 20,000 acres only 7,000 are committed
to permanent uses. These consist largely of transportation networks (high-
ways, railroads, and an airport), distribution centers (freight terminals,
warehouses, storage tanks, and utility transmission lines), and solid waste
disposal (over 30,000 tons per week from more than 100 municipalities.)
In 1968 the New Jersey legislature passed the "Hackensack Meadowlands
Reclamation and Development Act"26 creating a commission having the authority
to prepare, adopt, and implement a master plan for the orderly development
of the district. As a consequence, a number of alternative comprehensive
land use plans have been prepared to compliment previous development in the
district and to correct existing imbalances in regional land uses. Planners
of the Hackensack Meadowlands Development Commission (HMDC) envision develop-
ing the Meadowlands in order to provide more than 300,000 jobs and homes for
some 185,000 persons by 1990 while preserving nearly 5,000 acres for conser-
vation land and open space.
The four specific plans analyzed in this study were developed by the
HMDC and are designated as:
27
Plan 1 - The Master Plan
Plan 1A - Self-Supporting New Town
Plan IB - Expansion of New York City Urban Core
Plan 1C - Trend Development Based on Current Zoning
The original plans are in color to distinguish between the many activities.
They are presented here in black and white (Figures 3 through 6) - the
master plan is presented in color in reference 27.
83
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45 "
45 "
45 "
+- "t-
572 573 574 575 576 577 578 579 580 581 583 583 !)84
L —~"! Manufacturing
r •.'*•; \ '•, '1 Conservation
ywytv/V/fh Low Density Residential CO Ou)
Island Residential (50 Du)
I Parkside Residential (SO Out
P~ ^^}
I- ' • -j Special Uses
— Mass Transit and Commuter Railroad
Turnpike and Limited Access
O (''I lift Cultural Center
Business Oistnc'
Transportation Center
Research
Commercial Reasotion
Hotel-Office-Highway Commercial
Figure 3 Alternative Meadowlands Land Use Plan No. 1-The Master Plan
84
-------
57? 573 574 575 576 577 578 579 580 581 582 583 584
r~~*-=- ~- Manufacturing
-
O W//fiA Cultural Center
t\V.y,V.,'i Low Density Residential (IO Du)
I Medium Density Residential (SO Du)
High Density Residential (8O Du)
\ Special Uses
-.-.„_ Turnpike and Limited Access
Business District
Commercial Recreation
Hotel-Office-Highway Commercial
Figure 4 Alternative Meadowlands Land Use Plan No. lA-Self-Supporting
New Town
85
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45 :"
45'°
572 5/3 574 575 576 577 578 579 580 581 582 583 584
\- -_ \ Manufacturing
o
Low Density Residential (IO Du)
Medium Density Residential (3ODu)
High Density Residential ISO Du)
Other Uses
Mass Transit
Turnpike and L imitefl Access
O Cultural Center
Business District
Commercial Recreation
Hotel-Office -Highway Commercial
Figure 5 Alternative Meadowlands Land Use Plan No. IB-Expansion of
New York City Urban Core
86
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f 4- 4- + +
572 573 574 575 576 577 578
,79 580 581 582 583 584
— Manufacturing
!;!(,')';' Parks
V/1/I//A Low Density Residential
'/f/////*A
tij|l[|[|m Transportation Center
—— Turnpike and Limited Access
bi1'!''"''! Hotel -Off ice -Highway Commercial
Commercial Recreation
Airport
Figure 6 Alternative Meadowlands Land Use Plan No. IC-Trend Development
Based on Current Zoning
87
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The basic data and assumptions concerning the land uses for each of the
plans were supplied by the HMDC and were processed and coded for input to the
AQUIP System as described in the Task 1 Report. The resultant percent mix
of land use categories, and population and traffic projections for the dif-
ferent plans are summarized in Table 3.
The four plans show significant differences both in the relative loca-
tion of land uses and in the percent mix of land use categories. Plan 1,
the Master Plan, is characterized by a large amount of open space (31%
including open water), a relatively low population (148,000), and a broad
mix of industrial and commercial activities. The dominant feature of the
plan is the expansive area along the Hackensack River devoted to parks and
conservation land. Only 6% of the total area is allocated to residential
area, which consists mostly of high density island high-rise apartments and
parkside residential areas located at points within this open space region.
The business and commercial activities are located primarily in the central
region of the Meadowlands west of the Hackensack River. Industrial activities
(i.e., manufacturing, 8%, and distribution, 22%) are largely located in the
eastern half of the region, although a sizable area (8%) devoted to research
industry is located along the western border of the district. Plan 1 also in-
cludes various modes of public transportation, including novel means of water-
borne transit, as well as new roadways. Arterials servicing the high density
residential areas are located to minimize local surface street traffic.
In contrast, Plan 1A, the Self-Contained New Town, is characterized
by a higher population (408,000), greater residential area (17%), and less
open space (18%). The open space areas are predominantly located on the
fringes of residential areas, acting as buffers to surrounding industrial areas,
88
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TABLE 3
SUMMARY OF LAND USE INFORMATION FOR
HACKENSACK MEADOWLANDS PLANS
Residential^ J
10 DU/AC (dwelling units/acre)
20 DU/AC
30 DU/AC
50 DU/AC
80 DU/AC
TOTAL
Commercial £ Industrial
Commercial
Manufacturing (light 5 heavy)
Research
Distribution
Special Use
Airport & Transportation Center
TOTAL
Open Space
Water
Parks £ Conservation
TOTAL
Other1-1-1
Highway § Railroad
Special
TOTAL
TOTAL LAND AREA
(19,600 acres)
f2)
Total Population
f2)
Total Students^ '
Total VMT/Year (xlO6) (3^
Percent of Total Plan Area
Plan: 1
1
5
r,
4
8
8
22
1
5
48
11
20
31
12
3
15
100%
147,604
25,758
1,040
1A
2
7
8
17
4
14
0
19
0
4
41
7
11
18
21
3
24
100%
IB
1
5
15
21
3
15
0
22
0
4
44
7
11
18
15
2
17
100%
1C
1
1
1
18
0
50
0
4
73
7
2
9
14
3
17
100%
408,080 469,788 8,161
59,689 114,647 0
1,405 1,515 970
(1) As coded from land use maps -- figures used may not correspond exactly
with original estimates given by the HMDC.
(2) As computed from land use data. 6
(3) Totals include the regional network traffic of 930x10 VMT: in addition,
4x10^ hrs. idling/yr. are assumed for parking lots for all plans.
89
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The primary commercial and industrial land use activities are devoted
to manufacturing (14%) and distribution (19%). A significant feature of
this plan is that essentially all of the population is located within the
central portion of the planning region spread from west to east with low
density areas in the west and extremely high density areas in the east.
Furthermore, nearly all manufacturing activity is located in the southern por-
tion of the planning region, while distribution activities are located in
both the eastern portion of the region and in the vicinity of Teterboro
airport. Characteristically, major access roadways are on the fringe of the
residential areas to reduce surface street traffic. Since it is assumed
that employment will be served mostly by local population, and that
most of the journey to work trips will be served by the local roadway system,
a significantly high percentage of land use is devoted to highways (21%) .
Moreover, no rapid transit is indicated in the plan. Consequently, the total
miles of vehicular traffic projected for this plan (1.4 billion VMT/yr) re-
flects both the higher population and the increased levels of local traffic.
Plan IB, the New York City Urban Core Expansion, is nearly identical to
Plan 1A in percent mix of land use categories but has a significantly dif-
ferent location of these land use activities. The primary difference is that
nearly all residential area (21%) is located in the western part of the
district; and while Plan 1A has areas of low and extremely high density dwelling
units, Plan IB has mostly intermediate density dwelling units. The eastern
portion of the Meadowlands is predominantly devoted to commercial and industrial
land use activities. Manufacturing (15%) is widely dispersed, being located
mostly in the southern and northeastern portions of the district. Distribution
(22%) is similarly dispersed widely throughout the region. Again, as in
Plan 1A, open space is used as a buffer between residential and industrial
90
-------
areas, and to expand the open space along the river. Plan IB has the largest
projected population (nearly 470,000) and the largest projected amount of
traffic (over 1.5 billion VMT/year) of the four plans. Because of its planned
close relationship to the New York City urban core, this plan also con-
tains a substantial amount of rapid transit and commuter railroads, in addi-
tion to new arterials to serve the residential areas.
Plan 1C, the Trending of Current Zoning, is significantly different
from the other three plans in the percent mix of land uses. It contains less
than 1% residential area (to serve a projected population of approximately
8,000), while having little open space (9%) except for that associated with
open water. Most of the region is devoted to commercial and industrial
activities (73%), primarily distribution (50%). Industrial areas (18%) were
allocated by the HMDC to 10-acre plots as shown in Figure 7. Furthermore,
because of the low population, this plan also has the lowest projected traffic
(0.97 billion VW/year), reflecting primarily the regional network traffic.
6.3 Evaluation of Plans
6.3.1 Compliance with Ambient Air Quality Standards
One of the fundamental criteria for the assessment of air quality
associated with each land use plan is based on compliance with ambient air
quality standards (AAQS). In order to assess compliance with standards,
however, the calculated annual average pollutant concentrations must be
compared to corresponding annual average standards. As shown in Table 4,
standards based on annual average concentrations do not exist for all pollu-
tants, and such direct comparisons cannot be made. As a result, equivalent
91
-------
4524
4523
4522
4521
4520
45 I 9
45 1 8
45 17
45 I 6
4515 -
45 14
45 I 3 -
45 I 2
45 I i
4510
572 573 574 575 576 577 578
579 580 581 582 583 584
o
CVJ
U>
Figure 7 ' Location of Manufacturing and Industrial Land Use
Categories for Plan 1C
92
-------
Federal Ambient Air Quality Standards Adopted by Environmental Protection Agency
April 30, 1971; New Jersey Ambient Air Quality Standards for Sulfur Dioxide and Particulates
Ug/nT (ppm)
1 , ,
Pollutant l~hT ?ax
Sulphur Oxides as SO
Primary Federal Std.
Secondary Federal Std.
N.J. Std., (Chapt.13)
11 it
Particulates
Primary Federal Std.
Secondary Federal Std.
N.J. Std., (Chapt.13)
Carbon Monoxide
Primary § Secondary Fed. Std.
Hydrocarbons as CH
Primary 5 Secondary Fed. Std.
Photochemical Oxidants as 0,
Primary $ Secondary Fed. Std.
Nitrogen Dioxide as N0_
Primary § Secondary Fed. Std.
cone. x
668 (0.25)6
534 (0.20)7
40,000 (35)
160 (0.08)
3-hr max
1
cone.
6 am - 9 am
160 (0.24)4
3-hr max
1
cone.
1300 (0.5)9
8-hr max
1
cone.
10,000 (9)
24-hr max
1
cone
365 (0.141
260 (0.1)
267 (0.10)6
214 (0.08)8
260
150
1956
Annual
Average
80 (0.03)2
60 (0.02)2
53 (0.02)2
45 (0.017)3
753
603
653
100 (0.05)2
1 Maximum Values in Federal Standards are not to be exceeded more than once per year.
2 Arithmetic mean
3 Geometric mean
4 Nonmethane hydrocarbons, expressed as methane (CH.) , for the 3-hr period 6 am - 9 am.
5 Conversions from micrograms per cubic meter to parts per million are made at one atmosphere pressure and 25° C
for Federal standards -20° C C for New Jersey standards.
6 Arithmetic average concentration not to be exceeded and to be attained no more than once in twelve consecutive month.
7 Arithmetic average concentration to be attained or exceeded no more than nine times in twelve consecutive months.
8 Arithmetic average concentration to be attained or exceeded no more than four times in twelve consecutive months.
9 Any maximum three hour concentration not to be exceeded more than once per year.
Source: Environmental News Press Release, Friday, April 30, 1971; National Primary and Secondary Ambient Air Quality Standards
New Jersey Air Pollution Control Code, Chapter 13, Air Quality Standards
-------
values of ambient air quality standards for annual time averaging periods
were derived where both possible and meaningful. The resultant standards
(or their extrapolated equivalents) as used in this analysis are summarized
in Table 5, along with an indication of the method of derivation. As noted
in Table 5, the standards used for comparison were the Federal secondary and
New Jersey ambient air quality standards.
The primary basis for extrapolating values of standards from short
j i28
period standards to equivalent annual average values was the Larsen model .
The one exception to this case, however, was for the hydrocarbon standard in
which the Federal 3-hour air quality standard was used. The extrapolation
of the 3-hour hydrocarbon standard to an annual average was not considered
to be valid since background levels of hydrocarbons (less methane) from
natural sources may be very high, possibly exceeding standards at various
times and places. Thus, since background levels do not go to zero in
the absence of man-made sources, it is not expected that the statistical
model of Larsen, which is based on the reduction of empirical data associated
with concentrations of pollutants which are due primarily to man-made sources,
would apply directly. By contrast, it is expected that CO background levels
are likely to approach zero in the absence of man-made sources; consequently,
extrapolation of the short-term CO standard to an annual average would appear
to be meaningful and valid.
The MARTIK program within the AQUIP System was used to project the 1990
mean annual pollutant concentrations at each grid point within the planning
region. These data points were input to the LANTRAN program, which tabulated
the ratio of the mean annual pollutant concentrations to their respective
air quality standards at each grid point (a ratio designated as AQ/AAQS) and
printed out a graphical display of such data for each grid cell within the
94
-------
TABLE 5
EQUIVALENT ANNUAL AVERAGE AIR QUALITY STANDARDS
Pollutant
Standard
(ug/m )
(ppm)
Derivation
TSP
so
CO
HC
70.1
53.0
1425.0
160.0
100.0
0.02
1.25
0.24
<3>
From N.J. (geometric
mean) annual standard(2)
N. J. annual standard
Extrapolation from Federal 8-hour
standard using statistics from
N.J. measurements data (2)
Federal (secondary) 3-hour
standard (4)
Federal (secondary) annual
standard
(1) Annual arithmetic mean, never to be exceeded
(2} Extrapolations based on use of Larsen Model. (Larsen, R.I. :
"A Mathematical Model for Relating Air Quality Measurements
to Air Quality Standards", Office of Air Programs Publication.
No. AP-89, EPA, Office of Air Programs, Research Triangle Park,
N.C., 1971.)
(3) Conversion to ppm not strictly possible without specifying
composition of pollutant: HC is based on CH.; NO is based
on NO . X
2
(4) Extrapolation of 3-hour (6 to 9 AM) standard to an annual
standard not considered valid.
95
-------
planning region. The maximum values of this AQ/AAQS ratio found for each
pollutant within each plan are summarized in Table 6. The corresponding
spatial patterns over each plan for each pollutant are shown in Figures 8
through 27. Hand-drawn isopleths for this AQ/AAQS ratio give a rapid indi-
cation of where air quality standards are exceeded within the Meadowlands
region and by how much.
The analysis of total air quality concentrations within the Meadowlands
planning region shows that the maximum predicted annual average concentrations
for 1990 comply with ambient air quality standards for S02> CO, and NOX> As
indicated in Table 6, maximum S0? concentrations are on the order of 55 to 60%
of the standard. Similarly, maximum CO concentrations are on the order of
70% of the standard (except for Plan IB in which CO is approximately 90% of
the standard), and maximum NOX concentrations are on the order of 65% of the
standard.
Calculations of the projected air quality for 1990 indicates that par-
ticulates (TSP) exceed standards in all four plans by a factor of approxi-
mately 2.5. Furthermore the analysis of background data shows that back-
ground TSP concentrations within the Meadowlands region (i.e., concentrations
from sources other than the plans themselves), exceed air quality standards
for 1990 in all four plans. The TSP emissions data shows that these high
background concentration levels result primarily from the fact that particu-
lates are predominantly related to fuel burning for space heating and that
major control regulations are already in effect. As a result, little change
is anticipated in current emissions factors for 1990.
The results also show that hydrocarbons exceed the air quality standards
for all plans in 1990 by a factor of approximately 12. Furthermore as indi-
cated in Table 6, the background concentration levels, which represent nearly
96
-------
TABLE 6
SUMMARY OF PROJECTED 1990 AIR QUALITY DATA
FOR THE MEADOWLANDS
Pollutant
TSP
so2
CO
HC
NOY
A
Plan
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
Ratio of Total AQ to
Annual AQ Standard
Minimum Maximum
1.51 - 2.46
1.55 - 2.44
1.53 - 2.56
1.62 - 2.52
0.34 - 0.55
0.37 - 0.58
0.35 - 0.56
0.40 - 0.61
0.54 - 0.67
0.56 - 0.69
0.56 - 0.91
0.54 - 0.66
8.65 - 12.3
8.69 - 12.3
8.78 - 12.3
8.73 - 12.3
0.42 - 0.64
0.43 - 0.64
0.42 - 0.64
0.44 - 0.65
Background AQ as %
of Total AQ
Minimum Maximum
95 - 97
86 - 92
95 - 99
77 - 89
85 - 95
75 - 88
78 - 88
64 - 96
95 - 99
90 - 94
87 - 95
95 - 99
99
99
99
99
94 - 98
86 - 98
90 - 98
78 - 90
97
-------
/ b
10
11
1 -;
+.444444444
xxxx
xxxx
XXX xxx
X X X A * >XXXX>XAX
XXXXAXXXXXXXXX
< X X X X x A >' X X X X X X X
XXX X > A X X X X
x/xxxx
4+/XXXX/XXXX
XX \XXXXXXXXX
X v X A > X x X / > X X X
x x * x x. x x A x x x x x x
X X A / \ * X X A
X X x X X X >- X > X
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xxxxxxx
x x < x y x >'
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x x x xx x x
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X X X X X X X X X
x x .< x x. x x x x
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X X X --, X X X X X A
11
11
Figure 8
Air Quality Contours for Particulates for Plan 1,
Expressed as the Ratio of Air Quality/Air Quality Standard
98
-------
1 n
11
12
14
1 1
X A X X
X XXX
X » X X
XX
X > X X
X XX*
xx*x
X X XX
xxxx
XX XX
xxxx
xxxx
Figure 9 Air Quality Contours for Particulates for Plan 1A,
Expressed as the Ratio of Air Quality/Air Quality Standard
99
-------
A I -J ' / J
1'",
1 ,-•
1 1
1 "
4--l444++t-+
4-44++4*-+44
4+++
XX XX
X X X X
XX XX
i XXX
xxxx
X > x X
X X XX
XXXX
xxxx
XXX X
X X X
A / X X
X X X X x -» »
X x, X X X X >
A X A A
. xxx
x •; x x x
X A X X A
X X V
1 U
11
Figure 10 Air Quality Contours for Particulates for Plan IB,,
Expressed as the Ratio of Air Quality/Air Quality Standard
100
-------
1" i J
1 U
11
N
1.75
10
11
1.75
Figure 11 Air Quality Contours for Particulates for Plan 1C,
Expressed as the Ratio of Air Quality/Air Quality Standard
101
-------
11
X X
N
0.4
11
Fieure 12 Air Quality Contours for Sulfur Oxides for Plan 1,
Expressed as the Ratio of Air Quality/Air Quality Standard
102
-------
t- L'
1 I;
-L J
N
Figure 13 Air Quality Contours for Sulfur Oxides for Plan 1A,
Expressed as the Ratio of Air Quality/Air Quality Standard
103
-------
11
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', X A ," ", * v. * .' A
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/ Y x x x > »' x y x
/ v y x . x X A * X
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4 + + + 4+ + +4-I 4+4
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Figure 14 Air Quality Contours for Sulfur Oxides for Plan IB,
Expressed as the Ratio of Air Quality/Air Quality Standard
104
-------
i I
>L .
11
N
O.5
O.4
0.5.
\
A
A.
\
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a 5
0.5
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> x X
11
Figure 15 Air Quality Contours for Sulfur Oxides for Plan 1C,
Expressed as the Ratio of Air Quality/Air Quality Standard
105
-------
.60,.
ii
/I/
M H -» « I? H ^ M H H u ^ f-l H
HlHf-H-<
H ^ H " ^ W H
1U 11
11
Figure 16 Air Quality Contours for Carbon Monoxide for Plan 1,
Expressed as the Ratio of Air Quality/Air Quality Standard
106
-------
xxxxxxxx
: X T.
i:
XXXXXXXX.
xxxxxxxx
xxxxx-»xxx»
X XXXXXXXX'XXXXX
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Figure 18 -r~ cr^"/s"^s^is s^
108
-------
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i >d £• * H-"•• -1? H « h (? *•< H 6
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11
11! 11
Figure 19 Air Quality Contours for Carbon Monoxide for Plan 1C,
Expressed as the Ratio of Air Quality/Air Quality Standard
109
-------
. K 1 u H L 0 T K> t L / b
1 1
1 ,.
XX
;XXAXXXXXXX xxxx
xxxxxxxxxxxxxxxxx
X-XXXXXXXXXXXAXKXXX
•;*XXXXXAXXXX X > A
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xxxxxxx
xxxxxxx
xxxxxxx
xxxxxxx
xxxxxxx
xxxxxxx
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xxxxxxx
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xxxxxxxxxo
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• + X X/X XXXXXxXX
• + + xin
-------
11
12
N
/ A X X / i \ X A * ; '
A A «. / > X X X X > ', r
*xx x x >: > > x A / \
A X X '•' A X A X
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11
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1 4
1 i
Figure 21 Air Quality Contours for Hydrocarbons for Plan 1A,
Expressed as the Ratio of Air Quality/Air Quality Standard
111
-------
N
1 i
7 '1
>XXXX,»XXXX
x x x > v x x x x x
xxxxxxxxxx
xxxxxxxxxx
XXXX XXXXVX
>XX>XXXXXX
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11
12
o
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xxxxxxxxxxx
xxxxxxx/xxxxx
8.9
13
11
i n
10
11
12
5175 10.7 11.7
22 Air Quality Contours for Hydrocarbons for Plan IB
22 Air^ualx y^ ^ ^^ ^ ^ Quality/Air Quality Standard
112
-------
>' I (. 1
1 1
11
X X X ,\ < ,X X X < X V A X X X
)>XxXXXAx».\/,
X X X X H K /. \ A •< A
A > A X A X X X A X '
A X X X x X X A X >'
X X X X A X X X A A t •
XAAXAXAAAM
XXXXXXXA \--\
X X X / A A A A * A A -. A A
X .4 X A x x .' ;< A x x x
A A A ' X , X A A
X. X X ' * > A » *
>Xx/////.x
>'XX//XxAX
/. >' A > >' X A
X A / ' 'A *
X i X x )'>,«.
XXXXXXXXx'XXX
X X X X X X > X X , / x X <
11
111
y ,
x •
A A
X
X f
X
A
/>
A
XX
A v
A <
A \
XS
,\ >,
', A
f. X
A <
/ .
/ ,y
X X
/
> A
A A
". f,
XX
A X
X -
•v <,
X A
\ A
1 A
A A
X *,
•'• \
A A
A i
\ X
' V
X '
' A
A A
\ A
A *
x\
.< A
x x
\
A,
A
A
/
A
X
<,
«,
X
/
/
A
A
A
X >
A >
>• A
A f,
\ A
/ X
> X
A X
,x
i.
A
A
/
A -'
' A
\ A
^
A A
A I
il
10.7
Figure 23 Air Quality Contours for Hydrocarbons for Plan 1C,
Expressed as the Ratio of Air Quality/Air Quality Standard
113
-------
1 0
11
.50
II
x ,i
5
to
X
XXX
x x x x x
x x x x x
xxxxx
x x x x x
xxxxx
xxxxx
14
11
10
11
12
.55 .60
24
114
-------
11
IV
.50
N
L S
.55
11
1 ;
.1 n
Figure 25 Air Quality Contours for Nitrogen Oxides for Plan 1A,
Expressed as the Ratio of Air Quality/Air Quality Standard
115
-------
4 + +
4
4
4
•f
+
+
+
+
4
•»•
4
4
+
•f
+
•f
+•
4
•»•
+
+
•f
+
+
+
-t-
-«•
•f
+
+
4
-»•
-t-
+
-t-
+
+
•f
•f
4-
4
+
+
•f
•f
-f
+
4
4
4
+
+
4
+•
-f
+
+
4
-t-
4
4
4
4-
+
•f
X
-*-
4
4
+
•f
4
4
4
+
4
+
+ + +
+ + + + •»•
-(••»• + +•>• +
+ +•»••»••»••*• +
4+ + + * + + +
44f4 + + + -t- +
4 + *
4 +• + •»•»•
+ •»•+«•
03 +->
t-l UJ
o cy
<4-C
TJ ^
•H >s
X +J
O -rl
Vi a)
3 ctf
O
•P 0)
c -c
o +->
u
Oj V)
3 (/)
•H
•<
0,
K
(N
bO
•i-l
PL,
-------
UK 1 I HLl
/ o
in 11
1 4
11
12
.5(9
Figure 27 Air Quality Contours for Nitrogen Oxides for Plan 1C,
Expressed as the Ratio of Air Quality/Air Quality Standard
117
-------
99% of total HC concentrations, also exceed standards. These high levels
of HC concentration are due predominantly to the projected increase in
emission factors for areawide solvent evaporations, which alone account for
nearly 50% of 1990 HC emissions. This increase offsets the anticipated
decreases in HC emissions from automobiles and point source industrial pro-
cesses so that 1990 emission levels are nearly 2/3 of the 1970 levels.
An additional way of examining the compliance of land use plans with
air quality standards is to examine the amount of area within each plan
which exceeds the standards. In particular, the curves shown in Figures
28 through 32 show directly for each plan and for each pollutant the amount
of land area within the planning region which exceeds the ambient air quality
standard, or any fraction thereof. In Figure 29, for example, curves are
given for the four plans for concentrations in relation to the SO.^ standard.
These curves show, for example, that nearly 99% of Plan 1C area exceeds 40%
of the S02 standard. Similarly, 85% of the land area of Plan 1A exceeds 40%
of the standard, while 75% of the land area of Plan IB exceeds 40% of the
standard, and only 60% of the total land area within Plan 1 exceeds 40% of
the SO- standard. Consequently these curves conveniently and quantitatively
show the amount of land area exposed to any given level of pollutant concen-
tration. The basic data on which these curves are based were generated by the
LANTRAN program, and are tabulated in Tables 7 through 11.
6.3.2 Impact on Regional Air Quality
6.3.2.1 Background Concentrations
In order to analyze total air quality within the Meadowlands it is
necessary to project not only pollutant concentrations resulting directly
118
-------
100
Plan I
Plan IA
Plan IB
Plan 1C
Figure 28 Regional Air Quality Cumulative Frequency Distribution
for Total Suspended Particulates (TSP)
119
-------
100
X
Al
o
T3
C
CO
>.
o
O
c
o
'en
o
cr
c
c
D
O
O
0)
H
o>
0.
Plan IA
Plan IB
Plan 1C
Figure 29 Regional Air Quality Cumulative Frequency Distribution
for Sulphur Dioxide
120
-------
131
Air Quality
Percent of Total Land Area Within Planning Region With Ratio (Air Quality standard'
OQ
l-i
o n
o H-
x o
H- 3
Cu fa
m H
n
o
fD
-rt
H
0)
,0
(T>
3
n
x
n
o
3
CO
-------
100
Plan I
Plan IA
Plan IB
Plan 1C
12.68
Figure 31 Regional Air Quality Cumulative Frequency Distribution
for Hydrocarbons (HC)
122
-------
Plant
Plan (A
Plan IB
Plan 1C
0
Figure 32 Regional Air Quality Cumulative Frequency Distribution
for Nitrogen Oxides (NO )
A.
123
-------
TABLE 7
FREQUENCY DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH Xj < AIR QUALITY/AIR QUALITY STANDARD £ X2
FOR TOTAL SUSPENDED PARTICULATES (TSP)
PLAN
1
1A
IB
1C
Frequency Distribution Intervals (X to X'.)
1.50 to
1.75
73
49
62
20
1.75 to
2.00
23
47
32
24
2.00 to
2.25
3
3
1
3
2.25 to
2.50
1
1
2
2
2.50 to
2.75
0
0
1
1
CUMULATIVE DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH AIR QUALITY/AIR QUALITY STANDARD > Xj
FOR TOTAL SUSPENDED PARTICULATES (TSP)
PLAN
1
1A
IB
1C
Cumulative Distribution Intervals (X,)
1.50 to
1.75
100
100
100
100
1.75 to
2.00
27
51
36
80
2.00 to
2.25
4
4
4
6
2.25 to j 2.50 to
2.50 i 2.75
i
1
1
3
3
0
0
1
1
124
-------
TABLE 8
FREQUENCY DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH X < AIR QUALITY/AIR QUALITY STANDARD $ \2
FOR SULFUR DIOXIDE (S02)
PLAN
1
1A
IB
1C
Frequency Distribution Intervals (Xj to X2)
0.3 to
0.4
40
15
26
1
0.4 to
0.5
58
75
67
66
0.5 to
0.6
2
9
7
32
0.6 to
0.7
0
0
0
1
CUMULATIVE DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH AIR QUALITY/AIR QUALITY STANDARD £ Xj
FOR SULFUR DIOXIDE (S02)
PLAN
1
1A
IB
1C
Cumulative Distribution Intervals (X.^
0.3 to
0.4
100
100
100
100
0.4 to
0.5
60
85
74
99
0.5 to
0.6
2
9
7
33
0.6 to
0.7
0
0
0
1
125
-------
TABLE 9
FREQUENCY DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH X < AIR QUALITY/AIR QUALITY STANDARD « X2
FOR CARBON DIOXIDE (CO)
PLAN
1
1A
IB
1C
Frequency Distribution Intervals (X.. to X )
0.50
to
0.55
1
0
0
7
0.55
to
0.60
52
28
22
50
0.60
to
0.65
43
60
40
39
0.65
to
0.70
4
12
30
4
0.70
to
0.75
0
0
1
0
0.75
to
0.80
0
0
2
0
0.80
to
0.85
0
0
4
0
0.85
to
0.90
0
0
0
0
0.90
to
0.95
0
0
1
0
CUMULATIVE DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH AIR QUALITY/AIR QUALITY STANDARD £ \1
FOR CARBON DIOXIDE (CO)
PLAN
1
1A
IB
1C
Cumulative Distribution Intervals (X )
0.50
to
0.55
100
100
100
100
0.55
to
0.60
99
100
100
93
0.60
to
0.65
47
72
78
43
0.65
to
0.70
4
12
38
4
0.70
to
0.75
0
0
8
0
0.75
to
0.80
0
0
7
0
0.80
to
0.85
0
0
5
0
0.85
to
0.90
0
0
1
0
0.90
to
0.95
0
0
_1
0
126
-------
TABLE 10
FREQUENCY DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH X1< AIR QUALITY/AIR QUALITY STANDARD « X2
FOR HYDROCARBONS (HC)
PLAN
1
1A
IB
1C
Frequency Distribution Intervals (X, to X^)
i.80 to
8.77
4
4
4
3
8.77 to
9.75
40
39
39
40
9.75 to
10.72
27
27
25
27
10.72 to
11.70
25
26
28
26
11.70 to
12.68
4
4
4
4
CUMULATIVE DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH AIR QUALITY/AIR QUALITY STANDARD £ X1
FOR HYDROCARBONS (HC)
PLAN
1
1A
IB
1C
Cumulative Distribution Intervals (X )
7.80 to
8.77
100
100
100
100
8.77 to
9.75
96
96
96
97
9.75 to
10.72
56
57
57
57
10.72 to
11.70
29
30
32
30
11.70 to
12.68
4
4
4
4
127
-------
TABLE 11
FREQUENCY DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH Xj < AIR QUALITY/AIR QUALITY STANDARD ^ X.
FOR NITROGEN OXIDES (NO )
PLAN
1
1A
IB
1C
Frequency Distribution Intervals (X to X,J
0. 40 to
0.45
35
23
30
6
0.45 to
0.50
28
29
27
31
0.50 to
0.55
22
32
23
38
0.55 to
0.60
11
11
15
20
0.60 to
0.65
4
5
5
5
CUMULATIVE DISTRIBUTION OF PERCENT OF TOTAL LAND AREA
WITH AIR QUALITY/AIR QUALITY STANDARD £ X
FOR NITROGEN OXIDES (NOX)
PLAN
1
1A
IB
1C
Cumulative Distribution Intervals (X,)
0.40 to
0.45
100
100
100
100
0.45 to
0.50
65
76
70
94
0.50 to
0.55
37
48
43
63
0.55 to
0.60
15
16
20
25
0.60 to
0.65
4
5
5
5
-------
from sources of emissions within the Meadowlands hut also concentrations
influencing the Meadowlands region resulting from sources of emissions outside
the Meadowlands region (i.e., the background sources). For the purpose of
this analysis the background includes specifically sources outside the Hacken-
sack Meadowlands District as well as regional network traffic including those
links within the Hackensack Meadowlands District for which long-range projec-
tions have already been made by the New Jersey Department of Transportation.
By definition, the background also includes existing major point sources
within the Hackensack Meadowlands District since they are common to all plans.
The specific method for calculating and projecting background emissions
to the 1990 time period are described in detail in the Task 1 Report. The
MARTIK program of the AQUIP System was used to calculate air quality concen-
trations for background sources and the SYMAP routine was used to display
graphically the results. The resultant air quality contour patterns for
annual average concentrations for the five pollutants under consideration
are shown in Figures Bl through B5 of Appendix B to this report.
The analysis of background air quality indicates that it is a dominant
influence on regional air quality within the Meadowlands. As illustrated
in Table 6, the background pollutant concentrations range from 65% to 99%
of the total concentration levels within the Meadowlands planning region,
depending upon the particular pollutant and plan. Furthermore, the spatial
patterns of the background air quality concentrations are shown to account
for the predominant north-south orientation of the contours and the increase
in air quality levels from west to east. The general variation of background
air quality contours over the Meadowlands region indicates both the strong
influence of pollution from the New York City urban core region on the
Meadowlands, and the influence of meteorological conditions, especially the
prevailing westerly winds.
129
-------
Since background concentrations for each pollutant have such strong
spatial variations within the Meadowlands, it is evident that consideration
of background is highly important in locating land-use categories and major
sources of emissions within a land use plan, both to minimize impacts on
critical receptors and to avoid adding to existing regional problems.
It is also evident that since background concentrations represent such a
high percentage of total air quality within the Meadowlands for any given
plan, the resultant variation among plans in total air quality will be
extremely small. For example, a 100% variation in emissions resulting
from alternative land use plans may cause only a 10% change in total regional
air quality levels. As a consequence it may be concluded that while con-
sideration of background pollutant concentrations is essential for plans
in the vicinity of major urbanized areas, nevertheless land use planning
is an ineffective device for abatement of regional air pollution unless
the planning region is sufficiently large that "background" concentration
levels represent only a small percentage (for example, less than 50%) of
total air quality levels.
6.3.2.2 Analysis of Total Air Quality Contours
Total pollutant concentrations for summer, winter, and annual averages
were calculated by adding the background to individual plan contributions.
Emission sources for each plan include major new point sources, new line
(roadway) sources, and gridded area sources. The methodologies for projec-
ting the plan emissions data and the listing of the resultant emissions
data are described in the Task 1 Report. The MARTIK program within the
AQUIP System was used to calculate pollutant concentrations from the plan
emissions and the results were added to the previously calculated background
130
-------
air quality concentrations to get total air quality for each plan. The
SYMAP program was used t> produce computer-generated displays of air quality
concentration patterns. Specifically, isopleth air quality contours for
each of the four plans, five pollutants, and three seasons (that is, annual
concentration averages plus summer and winter seasonal averages) are shown
in Figures B6 through B65 in Appendix B.
The visual correlation of the air quality contours illustrated in
Figures B6 to B65 (or alternatively the isopleths of the AQ/AAQS ratios
illustrated in Figures 8 to 11) with the location of land uses for each
plan as illustrated in Figures 3 to 6 show the impact of land uses on the
spatial patterns of regional air quality. This analysis shows distinct
variations in contours among the different plans for each pollutant (except
for hydrocarbons) despite the previously acknowledged high levels of back-
ground concentrations.
In particular, comparison of the isopleth contours for mean annual
TSP concentrations (Figures 8 to 11) indicate that the best air quality
is given by Plan 1 followed by Plans IB, 1A, and 1C. In general, the
contours are predominantly in a north-south direction with concentrations
increasing from west to east. These general characteristics (common to
all plans) are clearly attributable to the dominant influence of the
background. Examination of the plan to plan variations in TSP concentra-
tions, however, indicates that the dominant influence on the shape of
the contours-is due to the location and amount of land use devoted to
manufacturing. This is especially evident from the comparison of the
contours for Plans 1A and IB. In these plans, which have essentially
equivalent percent mixes of land uses, the air quality contours are
131
-------
significantly worse in Plan 1A and are strongly correlated with the con-
centration of manufacturing activities in one general location within the
plan. By contrast the manufacturing activities in Plan IB are widely
dispersed within the plan.
The corresponding examination of S02 contours (Figures 12 to 15)
indicates that Plan 1 has the least concentrations throughout the region,
followed by Plans IB, 1A, and 1C. The contours in each plan show clearly
the influence of the airport. Similarly, the examination of the shifts
in air quality contours (particularly in Plans 1A, IB, and 1C) shows a
very strong correlation with the location and amount of manufacturing land
use activity. Also, other general characteristics of these contours which
show the strong influence of background concentrations, are similar to those
for TSP.
Air quality contours for NOX (Figures 24 to 27 also show characteristic
patterns and correlations with land uses which are similar to those for both
TSP and S02. Likewise, Plan 1 has best regional air quality for NOX, fol-
lowed by Plans IB, 1A, and 1C.
The isopleth contours for CO concentrations (Figures 16 to 19) show
entirely different characteristics in spatial patterns and in correlations
with land uses for the four plans. Lowest regional concentration levels
occur for Plan 1C followed in order of increasing regional concentrations
by Plans 1, 1A and IB. Not only does this ranking follow the order of
increasing levels of vehicle trip miles (as indicated in Table 3), but also the
variations in the shape of the contours is strongly correlated with the location
of major new arterials within the plans. This is especially noticeable
in Plans 1A and IB, which have the highest population, the most residential
area, and the most distinctive patterns of new arterial roadways serving
132
-------
these residential areas. As a consequence, it is observed that air quality-
contours for CO are indirectly related to the location of highly populated
residential areas.
Finally, the plan by plan comparison for air quality contours for
HC (Figures 20 Co 23J* shows an almost undetectable change in concentration
levels and spatial patterns. This indicates that the plans have absolutely
no influence on HC concentrations or spatial patterns in the Meadowlands;
air quality is determined entirely by regional background levels.
It is concluded from this visual analysis of air quality contours
that the major impact on regional pollutant concentration levels and on the
spatial distribution of these concentrations is due to the relative percentage
of land use devoted to manufacturing and to transportation activities. This
is supported by the data presented in Table 12 which lists the total annual
emissions per acre for each land use category studied for the 1990 Meadow-
lands Laad Use Plans. This table shows that those land use categories
having the largest emissions per unit land area are manufacturing (for TSP,
S00 and NO ) and transportation (for CO); all other land use categories have
ii A
ieiatively small emissions per unit area. Consequently all other land use
categories for each plan contribute only a negligible influence on the shape
of the air quality contours regardless of the relative location of the land
use within the planning region.
The visual examination of pollutant air quality contours for each of
the plans also indicates the importance of the relative location of land
uses v/ithin the plans. This is conveniently illustrated by comparing
Flans 1A and IB since the relative mix of land uses is quite similar for
bot.i plans.
See pages 110 to 113
133
-------
TABLE 12
SUMMARY OF 1990 ANNUAL EMISSIONS PER ACRE FOR
HACKENSACK MEADOWLANDS LAND USE CATEGORIES
Land Use Category
Residential
10 DU/AC
20 DU/AC
30 DU/AC
50 DU/AC
80 DU/AC
Commercial § Industrial
Comm.
Mfg.
light
heavy
Research
Distribution
Special Use
Airport
Transport Center
Cultural Center
Open Space
m
Other1 J
Highway (lb/10* VTM)
Stadium (lb/10 hrs idling)
Pollutant Emissions
flb/vear/ acre)
TSP
24.0
180.0
180.0
250.0
210.0
60.0
1080.0
5400.0
2.25
60.0
60.0
100.0
180.0
45.0
0
700
4.3
so2
1.2
117.0
117.0
162.5
136.5
44.0
1128.0
5400.0
16.5
44.0
44.0
1000.0
132.0
33.0
0
400
4.4
CO
36.0
3.6
3.6
5.0
4.2
0.8
9.4
60.0
0.3
0.8
0.8
3000.0
2.4
0.6
0
Emission
11,000
12.2
1C
12.0
54.0
54.0
75.0
63.0
12.0
141.0
900.0
4.5
12.0
12.0
350.0
36.0
9.0
0
Factors --
1,000
2.7
NOX
7.2
86.5
86.5
120.0
100.8
96.0
845.0
5400.0
36.0
96.0
96.0
100.0
288.0
72.0
0
1,500
0.9
(1) Assumes 400,000 flights/year from Teterboro Airport, and 700 acre area.
(2) N.B. Activities not specified on basis of emissions per unit area.
134
-------
As previously observed, the location of nearly all manufacturing activities
within a concentrated region in the southern part of the Meadowlands in Plan
1A generally causes pollutant concentrations for TSP, S02> and NOX to be worse
than for Plan IB where the distribution and manufacturing activities are more
widely dispersed throughout the plan. It is also observed that the high density
residential area in Plan 1A is located in the eastern part of the Meadow-
lands where pollutant concentration levels generally are highest. By con-
trast in Plan IB the predominant location of populated areas is in the
western part of the region where pollutant concentration levels generally
are significantly lower. Moreover, it is observed that this shift in the
relative location of residential areas has little influence on the concen-
tration levels for TSP, SCL and NOX. This would indicate a reasonable
degree of freedom on the part of the planner to shift the relative location
of residential areas to minimize localized impacts on population, students
and other critical receptors without significantly changing regional air
quality concentration levels or patterns.
The corresponding examination of air quality contours for CO shows
distinctly different characteristics for Plans 1A and IB. In this case
air quality concentrations are primarily influenced by the location of
major roadways and by the amount of vehicle trip miles for each plan.
Furthermore to the extent that roadways are used to service residential
areas, the location of residential areas will influence CO air quality
contours. Even so, it is apparent that since CO concentration levels
generally increase from west to east, those plans (such as Plan IB) having
more population concentrated in the western parts of the Meadowlands will
have fewer people exposed to the higher CO concentration levels.
135
-------
Likewise, since the background levels of HC are so high that there is
no significant variation in air quality among the plans, those plans having
most of the population located in the western parts of the region will have
the least impact on population.
6.3.2.3 Quantitative Comparison of Plans by Pollutant
In addition to the above efforts to analyze the regional air quality
on the basis of the visual examination of air quality contours, a significant
portion of the analysis focused on quantifying the impact of the alternative
land use plans on regional air quality in terms of the impact measures defined
in Section 5.2.3. In particular, the impact measures included both the inte-
grated total area exposure and the average total area exposure which differ
only by a constant since the total area of the planning region is constant.
The impact measures for both integrated and average total area exposures
were calculated from the LANTRAN output data associated with Figures 8 to 27,*
2
which show mean annual pollutant concentrations for each 1 km grid cell
within the Meadowlands for each plan and each pollutant. The impact mea-
sures for the integrated total area exposure are given in Table L3, and the
corresponding average total area exposure values are given in Table 14.
These impact measures show quantitatively the levels of regional air
quality for each of the four plans and can be used to evaluate the air
quality impact of different plans. In the analysis such quantitative com-
parisons of alternative plans were made on a pollutant by pollutant basis
by forming the "relative ratios" of the impact measures for each plan. This
was done by assigning a relative ratio of 1.0 to the plan with the smallest
impact measure and forming corresponding ratios for other plans relative to
their impact measures. The resultant relative ratios for each pollutant
*
See pages 98 to 118
156
-------
TABLE 13
INTEGRATED KECL-PTOK LXPOSURI, IMPACT MEASURES
RECEPTOR
TOTAL AREA
(Acres)
POPULATION
(Persons)
STUDENTS
(Persons)
RESIDENTIAL
AREA
(Acres)
UrfclN bPACb
(Acres)
COMMERCIAL
INDUSTRIAL
AREA
(Acres)
PLAN
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
'1
i
1A
IB
1C^J
TSP
fva/nn
2.7SE06
2.88E06
2.83E06
1
3.06P.OC-
!
1.70EO"
!
5.08E07
i 5.99E07
I.06E06
2.92E06
7.41E06
1.34E07
1 _ . _
0.0"
1.45E05
4.06E05
4.89E05
2.96E04
7.20E05
4.23EOS
4.08E05
2.20E05
1.09E06
. _. i
1
9.66EOS
1.03E06
4.87EOS
so?
_[ppm_l
1.98E02
2.10E02
' 2.04E02
2.27E02
1 . ] 8E03
3.64E03
3.91E03
7.68E01
2.03E02
5.29E02
9.55E02
l_
i
0.00
10.1
28.8
34.8
2.13
50.6
29.9
28.8
16.4
78.2 i
70.0
75.7
36.7
POLLUTANT
CO
(ppm)
1.76E04
1.82E04
1 .89E04
i
1.75E04
1.09F05
j 3.19E05
3.67E05
6.21E03
1.89E04
4.65E04
9.01E04
0.00
9.31E02
2.S7E03
3.27E03
1.73E02
4.64E03
2.68E03
2.74E03
1.26E03
6.98E03
6.10E03
6.93E03
2.80E03
HC
(Ug/m )
3.79E07
3.80E07
3.81E07
5.81E07
2.33E08
6.84E08
7.26E08
r
1.3SE07
3.97E07
9.91E07
1.78E08
0.00
1.99E06
5.41E06
6.47E06
3.76E05
9.84E06
5.60E06
5.SOE06
2.75E06
1.49E07
1.26E07
1.41E07
S.93E06
NO
(Mg/m )
1.14E06
1.18E06
1.17E06
1.22E06
1
6.85E06
2.06E07
2.21E07
4.21E05
1.17E06
3.00E06
5.41E06
0.00
5.84E04
1.64E05
1.96E05
1.17E04
2.94E05
1.71E05
1.66E05
8.87E04
4.47E05
3.92E05
4.33E05
1.92E05
-------
TABLE J4
AVERAGE RECEPTOR EXPOSURE IMPACT MEASURES
RECEPTOR
TOTAL AREA
(Acres)
POPULATION
(Persons)
STUDENTS
(Persons)
RESIDENTIAL
AREA
(Acres)
OPEN SPACE
(Acres)
COMMERCIAL
and
INDUSTRIAL
AREA
(Acres)
PLAN
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
• IB
1C
1
1A
IB
1C
POLLUTANT
TSP
(ug/nO
1.42E02
1.49E02
1.45E02
1.56E02
1.1SE02
1.24E02
1.17E02
1.30E02
1.13E02
1.24E02
1.17E02
0.00
1.16E02
1.23E02
1.17E02
1.31E02
1.17E02
1.22E02
1.18E02
1.30E02
1.16E02
1.21E02
1.20E02
1.29E02
so2
Cppni)
0.0101
0.0107
0.0104
0.0116
0.0080
0.0090
0.0083
0.0094
0.0079
0.0088
0.0083
0.00
0.0081
0.0087
0.0083
0.0094
0.0082
0.0086
0.0084
0.0097
0.0083
0.0087
0.0087
0.0097
CO
(ppm)
0.898
0.928
0.965
0.891
0.74
0.78
0.78
0.76
0.73
0.78
0.79
0.00
0.74
0.78
0.78
0.77
0.75
0.78
0.80
0.74
0,74
0.76
0.84
0.74
IIC
(ug/m3)
1.93E03
1.94E03
1.95F03
1.94E03
1.58E03
1.68E03
1.55E03
1.65E03
1.54E03
1.66E03
1.55E03
0.00
1.59E03
1.64E03
1.55E03
1.67E03
1.60E03
1.62E03
1.60E03
1.63E03
1.59E03
1.57E03
1.64E03
1.57E03
NO
(y g/m3)
58.237
60.086
59.633
62.363
46.4
50.5
47.0
51.6
45.4
50.3
47.2
0.00
46.8
49.6
46.9
51.8
44.6
49.6
48. ^
52.4
47.6
49.0
50.4
50.6
138
-------
for the four plans are listed in Table 15 for the integrated total area
exposure impact parameter and in Table 16 for the average total area
exposure impact parameter.
These relative ratios show directly the percent variation among plans
in the impact on mean annual regional air quality levels for a specific
pollutant. For example, sir.ce the average total area exposure impact
parameter for S0? has the minimum value for Plan 1, Table 16 shows the
relative ratio of 1.0 for Flan 3, and relative ratios of 1.059, 1.032 and
1.149 for Plans 1A, IB and 1C, respectively. The direct interpretation of
these relative ratios is that the average SO, concentration over the
Meadowlands region for Plan 1A is 5.9% greater than the corresponding
average for Plan 1 (i.e., air quality is 5.9% worse). Likewise, the
average regional concentration level of S02 for Plan IB is 3.2% greater
than Plan 1; and for Plan 1C the average regional S0? concentration is
14.9% greater than for Plan 1. Thus the relative ratio shows that there
is a nearly 15% variation among plans in terms of regional air quality
for S02.
These relative ratios can be used not only to show the percent vari-
ation among the plans in terms of impact on air quality, but also can be
used as a means of ranking the plans for a specified pollutant. Table 17
lists in the order from best to worst the ranking of plans for each pol-
lutant (and for each impact parameter, namely, for integrated and average
total area exposures).
The results of the analysis of each plan on a pollutant by pollutant
basis using these quantitative measures of impact generally show a very
good agreement between the quantitative ranking of plans and the subjective
ranking of plan based on the visual examination of the pollutant contour
139
-------
TABLE 15 (1)
RELATIVE RANKING RATIO OF INTEGRATED RECEPTOR EXPOSURE RAT.O
51.J57 j 50.66-;
5q nca ! 53.77
RESIDENTIAL [ 1_
LAND ARLA |"
1A
COMMERCIAL | 1
and
INDUSTRIAL
AREA
(1) Ratio i, calculated for a
exposure (persons or area X P011""" "£" llest value. Ratio for a plan
raTpollurt S^^rr-c?.- ^ Poll-t a,ong *. »»»,
plans.
f21 Plan 1C has no student populauon specified.
C3) Values for Plan R are oa.ed on no contnbuUon fro, d.str.but.on sources.
-------
TAHLI. Ib
RhLAmi, RANUNI, RATIO Oi AVERAGE RECEPTOR IXPOSURE RATIOll)
RECEPTOR
or
LAND USh PLAN
TOTAL AREA 1
1A
111
— — - _ — _
POLLUTANT
I
ISP SO, CO 1 IIC
r " ~^~ •
1 .000 1 .00!) 1 .008 1 .000
NO
1 000
1
1 11. VI 1 .059 1 042 1 .005
1 0:i 1 032 1 .084 1 007
I - 11 '
H '! 1.101 1 149 1.000 1.006
1.032
1.024
..
1 1 071
i i 'I
POPULAIION ^ 1 , i OIK) 1.000 1 000 I O'l 1 000
i i . - -
]A ' 1 OKI , 1 023 i 1 .054 1 .(IS',
- — — -
1.0S8
i" i i 015 i 03P i i .or- 1 i .000 ; 1.014
l'; l-l-> 1.17) 1.027 1.070 1.112
1
SlUUt NTS 1
1 .000 1 .000 , 1 .000 1 .000
' 1A ' 10'', l.UJ ' ] ()(,,) [_07-r
1
in
i '
l,Lf21l
RESIDLM'IAL 1
;
1A
! - - . .. i
1 .«ii 1 Hid , 1 .072 1 .007
t • <-.---
1
1.000 I.OOO 1.000 ' I.OM)
! - -
1.062 1 087, 1.043 1.060
1.000 I
1.107
--
1.039
i . ooo
1 .060
111 1 "OH ( i (131 1.049 1.000 1.003
1( | J.I'.- 1 171 1.030 1.078
OPEN SPACE
1 .000 1 .000 1 .1)1" 1 .003
ARFA ' " ~;,
1A
H'
1.044 ' 1.049 1.046 i 1.015
1 010 ! 1 014 1.074 1.000
- - - i l - , ('
. 1C
1110 ] 1,'4 1 .000 1.018
1 |
COMMERCIAL ' jl 1-l)0" - 1 00° J-007 l-0^
1.109
1
1 . 000
-- —
1.111
1 . 083
1 176
1 000
and " if " ~ [ - - -- — — - |
INDUSTRIAL 1A
AREA ' ,
IB
1
K«>
1.037 1 048 1.030 1.003
; 1 i
1.032 1.038 1.093 1.047
1 . lOfi 1 .!<>.) 1 .000 ] .000
)
1 .026
1.057
1.063
(1) ' Ratio is calculated for j given pollutant by dividing the average receptor
exposure fin units of pollutant concentration) by the average exposure of the
particular plan having the smallest value. Ratio for a plan and a pollutant
shows relative impact of a given pollutant among the various plans.
(2") Plan 1C has no student population specified.
(3) Values for Plan 1C are based on no contribution from distribution sources.
-------
TABLE 17
RELATIVE RANKING OF PLANS BY POLLUTANT ON BASIS OF QUANTITATIVE MEASURES OF IMPACT
Impact Measure
Integrated and
average total
area exposure
Integrated
population
exposure
Average
population
exposure
Integrated
open space
area exposure
Average open
space area
exposure
Integrated
students
exposure
Average
students
exposure
Integrated
residential
exposure
Average
residential
exposure
Integrated
commercial and
industrial area
exposure
Average
commercial and
industrial area
exposure
Plan
Rank
(Best to Worst)
4
1
4 j
1
-J
3
4
1
4
^
_
4
3
4
1
2
3
4
i
4
i
3
4
i
->
3
4
| 2
TSP
Plan
IB
_IA_
1C
1A
1
IB
1A
1C
IB
1A
J,
1
IB
1
1A
1
IB
1A
1C
_J
_1A_
J_
_1E_
Ratio)
M flnfi)
(1 071)
_ii*Q3a)
flr1011
so2
Plan
]_ J_
1R ,
1C L
(1.0) i 1C _
(16.0)
(47.9)
(SI. 8)
1 ^
1A
fl.OOOJ L l _+-
__il.ois) 1 IB ;
fl 081) 1A
(1.12S)
fl.OOOl
^ fl.8531
__CU9-2Jll
1C i
(Ratio) 1
_LU3QOJ
_(J.032} .
(i nsq)
fl.1491
11.0) ..
CO
'Ian (Ratio)
O£ i-O-QliCi
1 f 1.008)
IA : (i.Q4;)
IB n ns4i
IC_I_IKOI
115.4) , 1 _JJ~!-iL
(47. 4j
.£50.91
.i^_151.4J
IB (59.1)
li.ocoi i LI.OOOJ
£1.05811 IC^ LMITJ
(1.1231
_IC_<— LUO-BOJ
_JJJ.
1A
P. 2711 1 _;
(1.0001
_1UQ441
(1.110)
_tlyoop-i_
[ (4.589)
u -o
_1UOOQ1_
(1.031)
^ --(2)
(1.000)
__14J8_941_
f!6.526)
j Cl-QQfU
IllyOOSJL
.!.. Ily06 21
;C fi.i32i_
1A
IB
1 1
IB
1A
_L£_
j_a,QC01_
J_uy28.4i_
L12-.-1151-
(2.2381
11.000)
_111032)
fl.lOSl
IB '
-JA.^
1 _,
1A
^01_
1
IB
1A
(1 8251
(3.094)
C.1 .0141 i
(1.049)
(1.174)
(1.000)
(2.606)
[_4.6991
--P)
[1.0001
h_lU056j__
[1.1241__
— (2
1C
JJ.OOO)
fi T\T\
IB ! (16.329)
j_
.. IB.
1A
1C
IA.
1
IA
IB
1C
^031J~
| (1.171)
IB ! (1.053) i
IA (1.054)
1C ! fl.OOO)
JA-a-U^UU
IB ' C2J86J
1 (3.694)
_l£ • fl.OOOl .
1 ' tl.017)
_lA._^jLly>461 —
IB 1 12.074)
1 ; (1.0001_
1A ! 12 466)
Plan
1
IA
IB
1C
i
HC
(Ratio)
(1.000)
fl.0051
(1.0C61
(1.0071
(1.000)
(17.3)
1A :(5U.7)
IB
IB
1C
1A
1C
_IB_
IA
i
IB
1
1C
1
1A
IB ' 1_4 . 'T72) | 1 3
-12)!
1 j fl.OOO)
1A _[_(!. 064]
1B_U.1.072J
-(2)
ir ^jj^oooj
1 (5 382]
_lA_114t83_2]
IB ;(18.902)
_l j_UJO.W
_JC_._CL.p30_L_
J.4_ j fl .043]
i IB i (1.049)
Cl.oooi Lie _^ ci.oooi
j (2 . 064)
1 IA 12.184j_
I IB I J2. 481)
1
IB
1A
Plan
1
IB
-4A—
1C.,
1C
1
1A
(53.8) IB
fl.OOO) 1 1
(1 .021) 1 .IB
(1.070) 1A
(1.085) 1C
^Liy32fll_
+ li.OQOJU
(2.03fc)__
1A
(3.578) 1
fl.OOO) i 1
Cuoos) 1 ia
(1.018J 1C
NOX
(Ratio)
fl.OOOl
(1.024)
(1 03?)
fl.0711
^J 1.000)
(16.3) _
L(.48.9)
(52.5)
fl.OOO]
(1.014}
(1.088)
' (1.U2)
, fl.OOO'!
ntst
(3.089)
_IUOOQ1
^ [1.083)
(1.176)
j 1.000) |_1. ^_il . OOP) ,
j (2.496) 1A
(4.484)
-(2)
UI-OGO)
j_Li.oo7j_
(1.077)
UJL
LL_
tlB
U
i (2.564J__
--C2J
_,_lIiP0Qi_
(1.107)
: --(2)| --(2)
1C
1
IB
__1A_
1C
J_11.000) 1 1C
4_LS_.ii31__j_J^_
(17.207) IB
.Liuoeoi-
' (1.078L
1C ^11.0001
1A
1 IB
; (2.131) j 1 (2.497) ! 1
(1.000)
f 1.04 8)
liyoss)
(1.164)
1C_| U .uuuj
1 ' £1 007]_
-p
4— --
1A..| C1._C3Q1 |_L_
IB i fl .093) IB
! i
tit
1C
1 (1.000.1 |
' (4.996)
(16. "SI)
__J_£1 ...COO)
._1UC0.31_
(1.109)
1C _11.000J__
_j _£2 A 2>J r A A (2. . 0461_
„ (2.378) | 1B_12.25SL_
(2.513)
i (1.047)
1
•fit
K
(2.333)
J_IL057J_
1 (i.oe-3)
("Ratio of best plan is defined as unity; other
1C has no student population specified.
represent the relative values of the exposure parameter.
142
-------
patterns. For example, the quantitative ranking of plans for TSP gives
(from best to worst) Plans 1, IB, 1A, and 1C, respectively. Furthermore,
the same ranking is given for S02 and NO confirming the subjective ranking.
The advantage of the quantitative procedure is that it shows the degree of
variation among plans on air quality impact. For example, for particulates
there is only a 10°6 variaticn among plans, whnJe for SO., there is a 14.9%
variation, and for i\!0x a 7° variation. It is also observed for these
three pollutants that average regional air quality for Plan IB is no more
than 2 to 3% worse than for Plan 1.
The visual ranking of plans for CO is also verified by the quantitative
analysis. Table 17 indicates that Plan 1C is best, followed closely by Plan
1 (a less than 1% difference) and by Plans 1A and IB. The subjective observa-
tions concerning HC concentrations are also verified by the quantitative
analysis which shows that among all four plans the maximum variation is only
0.7%. Furthermore, the ranking (which was ambiguous in the visual analysis)
is shown to be Plans 1, 1A, 1C, and IB from best to worst, respectively.
6.3.2.4 Comparison of Plans for Combined Pollutant Impacts
In the previous portions of the analysis, the impact of land use plans
on regional air quality concentration levels has been based either on the
subjective visual examination of air quality contours or on the analysis
of quantitative measures of impact. In both instances the alternative
plans were compared on a pollutant by pollutant basis. To complete the
comparison of plans it is necessary to rank the plans on the basis of multi-
pollutant impacts on regional air quality. The "Normalized Impact Para-
meter" ranking index (described in Section 5.3.3) was used to measure the
impact of all five pollutants combined in terms of the exposure of the total
study area.
145
-------
The computation of the Normalized Impact Parameter ranking index is
based on a simple manual calculation and the results are shown in Table 18
for impact parameters based on integrated total area exposure and average
total area exposure. The results of this multipollutant ranking of the
alternative land use plans show that Plan 1 is best followed by Plans IB,
1A, and 1C, respectively.
6.3.2.5 Impact of Open Space on Regional Air Quality
The sensitivity of regional air quality to the percent mix of land
uses is shown by the following example which also illustrates the effective-
ness of open space as a factor in air pollution considerations.
From Table 3 a comparison of the percent land use mix for the various
plans shows that Plan 1 has 8% manufacturing and 8% research. It also has
31% open space and 6% residential area, for a total of 37% for these two
categories. Plan 1A, on the other hand, has 14% manufacturing and no
research. This plan has 18% open space and 17% residential area, a com-
bined total of 35%. Finally, Plan IB has 15% manufacturing and no research.
It has 18% open space and 21% residential area for a combined total of 39%. If
the 8% research category in Plan 1 were converted to an additional 8% manu-
facturing land use (for a total of 16% land use devoted to manufacturing in
Plan 1) then, as indicated in Table 3, Plans 1, 1A, and IB would be very
similar in the percent land use mix except for the relative mix between
open space and residential area.
As shown in Table 12 the dominant source of SO,, emissions among the
land use categories is manufacturing; emissions per unit area due to resi-
dential areas and research industrial categories are very much less by
comparison. From the data in Tables 3 and 12 the total emissions of S02
144
-------
RELATIVE RANKING OF PLANS ON BASIS OF QUANTITATIVE RANKING INDEX FOR
COMBINED POLLUTANT IMPACTS
PLAN RANK
(Best to
worst)
1
2
3
4
AVERAGE
AREA
EXPOSURE
Plan
1
IB
1A
1C
Index^1'
0.97
1.00
1.004
1.03
AVERAGE
POPULATION
EXPOSURE
Plan
1
IB
1A
1C
Index
0.95
0.97
1.03
1.04
AVERAGE
STUDENT
EXPOSURE
Plan
1
IB
1A
(2)
Index
0.96
1.00
1.05
-
AVERAGE
RESIDENTIAL
EXPOSURE
Plan
1
IB
1A
1C
Index
0.96
0.97
1.02
1.05
AVERAGE
OPEN SPACE
Plan
1
IB
1A
1C
Index
0.96
0.99
1.01
1.07
AVERAGE
COMMERCIAL AND
INDUSTRIAL AREA
EXPOSURE
Plan
1
1A
IB
1C
Index
0.96
0.99
1.02
1.03
PLAN- RANK
(Best to
worst)
1
2
3
4
INTEGRATED
AREA
EXPOSURE
Plan
1
IB
1A
1 1C
Index H
0.968
0.996
1.002
1.028
INTEGRATED
POPULATION
EXPOSURE
Plan
1C
1
1A
IB
Index
0.0332
0.540
1.624
1.798
INTEGRATED
STUDENT
EXPOSURE
Plan
1
1A
IB
(2)
Index
0.49
1.24
2.27
-
INTEGRATED
RESIDENTIAL
EXPOSURE
Plan
1C
1
1A
IB
Index
0.11
0.54
1.51
1.84
INTEGRATED
OPEN SPACE
Plan
1C
IB
• 1A
1
Index
0.48
0.93
0.95
1.63
INDUSTRIAL
COMMERCIAL AND
INDUSTRIAL AREA j
EXPOSURE
Plan
1C
1A
IB
1
Index
0.52 '
1.07
1.18
1.22
(1) Index = Normalized Impact Parameter Index (as defined in text).
(2) Plan 1C excluded - it has no students.
-------
resulting directly from sources within Plan 1 can be calculated before and
after the conversion of the 8% research land use category. The result is
an estimated 73% increase in emissions due directly to sources in Plan 1.
If it is further assumed that these additional emissions, which arise from
8% of the Meadowlands area, diffuse uniformly over the entire Meadowlands
region, then average regional S02 concentrations generated by the plan
itself will increase by 5.8%.
The data in Table 6 shows that background S02 concentrations for Plan 1
range between 35% and 55% of total regional S02 concentration levels. If it
is arbitrarily assumed that the average background level is 45% of total air
quality, then the net increase in average regional air quality within the
Meadowlands planning region would be (1 - 0.45)5.8% or a total of 3.2%.
Comparison of the relative ratios of average regional S02 concentrations for
Plans 1, 1A, and IB as listed in Table 16 shows average concentrations for
Plan 1/to be 1^9% higher than for (the origina!) Plan 1, and average concen-
trations for Plan IB to be 3^ higher than for (the original) Plan 1. Since
the conversion of 8% of the total land area from the research category to
manufacturing within Plan 1 would cause an approximate increase in total re-
gional S02 air quality in Plan 1 of 3J%, the resultant air quality for Plan
1 thus would be within the same range of values as regional S02 air quality
for Plans 1A and IB, even though Plan 1 still retains 31% open space and only
6% residential area.
It is concluded from this simple example that open space is not a
dominant influence on regional air Duality concentration levels. Rather,
regional air quality is far .ore sensitive to "heavy polluting" land use
categories. A direct trade between manufacturing and open space land uses.
146
-------
however, would be highly beneficial to regional air quality levels, not
because of the addition of open space within the land use plan, but rather
because of the deletion of manufacturing land use categories.
Finally, it is to be noted that this analysis of the effects of open
space says nothing about localized (microscale) impacts. It is highly
probable that the presence of open space can have a significant effect on
local pollutant levels, especially variations in concentrations over small
distances and short time periods, which would not be observable at the
regional scale of analysis.
6.3.2.6 Seasonal Variations
Seasonal variations in total air quality were investigated by calculating
the summer (June-August) and winter (December-February) average concentrations
for all five pollutants in each of the four alternative plans. These seasonal
values were compared with the corresponding mean annual (12-month) concentra-
tions .
The preparation of emissions data for the summer and winter cases is
described in detail in the Task 1 Report. The meteorological data for the
two seasons is described in the Task 2 Report. For reference, wind direction
roses for the summer, winter and annual cases are illustrated in Figure 33. *
These meteorological and emissions data were input to the MARTIK program and
the resultant projected air quality concentrations within the Meadowlands
were displayed by the by the SYMAP program. Computer-generated figures
showing the isopleth contours of pollutant concentrations are given in
Appendix B. Air quality contours for the annual case are illustrated in
Figures B6 to B25, for the summer case in Figures B26 to B45, and for the
winter case in Figures B46 to B65.
''See page 150
147
-------
Summer
W -
Winter
.20
Annual
Figure 33 Wind Direction Frequency Distribution
148
-------
The comparison of the annual, summer and winter cases shows a significant
degree of variation in air quality contours for a given pollutant and a given
plan. The corresponding comparison of the variation in air quality contours
among different plans for a given pollutant and a given season shows that
the characteristics of the seasonal contours are similar to those of the
annual case. Moreover it is observed that the relative ranking of plans in
terms of average regional air quality for a given pollutant is generally
the same for the seasonal cases as for the annual case.
The pattern and degree of seasonal variation in air quality contours
for a given pollutant and a given plan are illustrated by the calculation
of the average total area exposure impact parameters (or equivalently the
average regionwide pollutant concentration level). The results, shown in
Table 19 for Plan 1 for all five pollutants, are representative of the
seasonal variations for the other plans.
Seasonal variations are expected to occur as a result of the combined
effect of differences in emission rates of the various pollutants with
time of year and the differences in meteorological conditions prevailing.
Because both the spatial variation in emission strength and the properties
of emissions from elevated sources vs. low level sources is different for
each pollutant, simple interpretations of the detailed seasonal variations
predicted over the Meadowlands District are not possible. The results
generally reflect the larger emission rates of pollutants and the generally
poorer dispersion conditions associated with winter. The results for
hydrocarbons levels show the reverse trend -- concentrations in the summer
are slightly larger than those in the winter. This trend was also observed
in the air quality measurements data collected near the Meadowlands and used
for the model calibration (see Table 2-5 of the Task 2 Report).
149
-------
en
O
TABLE 19
SEASONAL VARIATION IN AVERAGE CONCENTRATION LEVELS
WITHIN THE HACKENSACK MEADOWLANDS FOR PLAN 1
Season
Summer
Annual
Winter
Pollutant
TSP
Avg Cone
Ug/m
85.3
116.8
127.8
Relative
Ratio
1.00
1.37
1.49
so2
Avg Cone
pphm
0.83
0.84
1.08
Relative
Ratio
1.00
1.01
1.29
CO
Avg Cone
ppm
0.36
0.74
1.56
Relative
Ratio
1.00
2.07
4.34
HC
Avg Cone
3
1943
1607
1881
Relative
Ratio
1.21
1.00
1.17
NC
Avg Cone
Ug/m
54.3
48.4
73.3
>x
Relative
Ratio
1.12
1.00
1.52
-------
6.3.3 Impacts on Receptors
6.3.3.1 Principal Receptors of Interest
As discussed in Section 5.2.3 the receptors and land use categories
of particular interest in this analysis include population, students, resi-
dential area, open space, and the combination of commercial and industrial
area. As shown by the percent background levels in Table 6 the direct con-
tribution of the source emissions from any particular land use plan repre-
sents only a small fraction of the contribution to total regional air
quality. However, the impact of total regional air quality on specific
receptors within a plan can be major, especially if the concentration
levels associated with total air quality within the planning region are
high.
The basic data for these receptors were retrieved from the coded land
use data base by using the COMP 5 routine (as described in the Task 5
Report) of the LANTRAN program in the AQUIP System. In particular, informa-
tion concerning the number of receptors (or alternatively the amount of land
area associated with each land use category) within each grid cell within
the planning region was retrieved and processed for use in the impact
analysis.
These data were used primarily to correlate the specific number of
receptors with pollutant concentration levels within each grid cell as
151
-------
necessary to calculate quantitative impact parameters. However, these data
were also displayed graphically through use of the LANTRAN program to show
the spatial distribution and densities by grid cell for each receptor or
land use category of interest. These results are shown in Figures 34 to
52. (Since no schools were specified in the Plan 1C planning data, no plot
of the spatial distribution of students is given.) These spatial patterns
of receptor locations and land use densities were used in the visual corre-
lation of air quality contours and receptor data. For example, Figures 34
to 37 show the spatial distributions of population density for the four
plans. Similar plots are given for students, residential area, commercial
and industrial area, and open space. (Open space land use was coded manu-
ally from the plan base maps for input to the LANTRAN program.)
6.3.3.2 Comparison of Plans by Pollutant
The visual correlation of air quality contours with land use categories
and critical receptors provides a great deal of insight into both the impact
of land use plans on air quality and the impact of regional air quality
on specific receptors. It is found, however, that the basic results
determined by the use of quantitative impact measures confirm the subjective
conclusions derived from such visual evaluations of plans. As a consequence,
the primary results of the analysis of the pollutant by pollutant, impact of
air quality on specific receptors and land use categories are reported in
terms of quantitative measures of impact.
As discussed in Section 5.2.3 the quantitative measures of impact
found to be most useful in the analysis of receptor impacts are integrated
receptor exposures and average receptor exposures. These impact measures
were calculated for each of the five basic receptors described in the previous
152
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156
-------
6 7 H
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157
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159
-------
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160
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161
-------
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162
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Figure 44 Grid Plot for Residential Area Density for Plan 1C
163
-------
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Density for Plan 1
164
-------
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165
-------
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Density for Plan IB
166
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Density for Plan 1C
167
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Figure 49 Grid Plot for Open Space in Plan 1
168
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169
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170
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171
-------
section using the IMPACT program of the AQUIP System. In particular, the
LANTRAN program was used to retrieve both the land use data for each receptor
and the air quality concentration data for each pollutant, and to format the
data on a gridded basis for input to IMPACT. These basic input data were
used with a routine written in terms of the hyperlanguage of the IMPACT
program to compute the impact parameter formula discussed in Section 5.2.3.
The results of the calculations of the impact measure for each pollutant,
for each plan and for each receptor are listed in Table 13 for integrated
receptor exposure impact parameters and in Table 14 for average receptor
exposure impact measures.
As was done in the case of the analysis of regional air quality, these
impact measures were used to form the relative ratios among the calculated
impact measures for each plan for a given pollutant. Such relative ratios
are listed in Table 15 for integrated exposure measures and in Table 16 for
average exposure impact parameters.
These relative ratios show the percent variation among the four plans
in the impact on a specified receptor due to a given pollutant. They
also form a basis for ranking the impact among the plans for a single
pollutant. A summary of the ranking of plans on this pollutant by pollutant
basis is given in Table 17 for each receptor.
The analysis of receptor impacts is illustrated by the results of the
evaluation of the alternative plans in terms of impact on population. This
special interest in population is based on a concern for the adverse effects
of pollutants on the health of the general population and further motivated
by the fact that the Federal primary ambient air quality standards were
developed to protect public health. The ranking of plans based on the
integrated population exposure impact measure clearly goes according to
172
-------
the level of population within each plan and is the same for all pollutants.
Plan 1C is shown to be best (having least total population) followed by
Plans 1, 1A and IB. This impact measure reflects the fact that the total
impact on receptors within a plan increases with the number of receptors
(i.e., people) as well as with the level of concentration to which the
receptors are exposed. It is also observed that the relative differences
in pollutant concentrations among the plans are too small (because of the
high background levels) to overcome the relative differences among plans
due to population levels.
By contrast, the ranking of the plans for the average population expo-
sure impact measure shows that tne ranking order depends upon which pollu-
tant is considered. For example, the ranking of the plans is similar for
particulates, S02 and NOX. Plan 1 is best, followed by Plans IB, 1A, and
1C. Since this impact measure represents the average concentration to which
any person within the populated area is exposed, it is noted that Plan 1
ranks best primarily due to its low regional concentration levels. On the
other hand, Plan IB ranks better than Plan 1A due to the relative location
of populated regions within the plan. The population in Plan IB is pre-
dominantly located within the western regions of the Meadowlands where
concentrations generally are lowest, while Plan 1A has a significant amount
of population located in the eastern portions of the Meadowlands where
concentration levels generally are much higher. Although percent mix of
land use categories in Plans IB and 1A is very similar, the quantitative
ranking in Table 17 shows that the impact on population can vary by as
much as 8%, depending upon the pollutant.
The ranking of the plans in terms of average population exposure to
CO shows that Plan 1 remains best, but is followed by Plans 1C, IB, and 1A.
173
-------
This shift in relative rank of Plan 1C (from fourth to second) reflects the
fact that regional CO levels in Plan 1C are significantly lower than those
in Plans IB and 1A. It is again observed that locating large portions of
the population in the western part of the Meadowlands causes Plan IB to
rank higher than Plan 1A.
The ranking in terms of average population exposure to HC shows that
Plan IB is best, followed by Plans 1, 1C, and 1A. Since the HC concentration
spatial patterns are completely dominated by background air quality, this
ranking of the plans is in the order of those having the most population
distributed in the western portion of the region where concentrations are
lowest. This case represents a situation in which the plans have no effect
on regional air quality levels, and hence the receptor impact is completely
dominated by the relative location of receptors and land uses within each
plan.
It is thus concluded that the degree of impact on critical receptors
is especially sensitive to the relative location of the receptors within
the plan, and that the relative location of critical receptors and land
use categories represents an extremely important consideration in the formu-
lation and evaluation of land use plans.
6.3.3.3 Comparison of Plans for Combined Pollutant Impact
In order to compare the plans on the basis of the combined effects
of all pollutants, the multipollutant ranking index for each impact measure
was calculated from the formula described in Section 5.3.3 for the Normalized
Impact Parameter ranking index. It is to be noted that the ranking of plans
on the basis of impact related to the effects on specific receptors is
accomplished by this ranking index and is the first known such attempt at
ranking plans or air quality relative to effects on specific receptors.
174
-------
The Normalized Impact Parameter ranking index was calculated by hand
from data previously generated in the analysis. The results are listed in
Table 18 for each combination of impact measure and receptor category of
interest, and are tabulated in order of rank from best to worst. The
results show that for average receptor exposures Plan 1 ranks best, followed
by Plans IB, 1A, and 1C for all receptor categories examined. This multi-
pollutant ranking is in close agreement with the subjective ranking based
on the visual correlations between air quality patterns and land use plans.
By contrast the multipollutant ranking based on integrated receptor
exposure impact measures resulted in every case in the ranking of plans in
the order of increasing numbers cf receptors. For example, the ranking
of plans (from best to worst) for integrated population exposure is in the
order of increasing population; namely, Plans 1C, 1, 1A, and IB. This
result is the logical consequence of the defined impact measure which
counts both the numbers of receptors as well as the levels of pollutant
concentrations to which they are exposed. Consequently, this is a useful
measure of the total degree of impact, but the results must be interpreted
and used with caution. For example, such an impact measure may be indicative
of the total cost of health care associated with regional air quality but
would not be indicative of the health risk to the average person.
6.3.4 Land Use/Air Quality Compatibility Score
An example of a new method for evaluating and ranking alternative land
use plans is the "land use/air quality compatibility" scoring technique
as described in Section 5.2.4. The primary objective of the analysis of
plans based on the use of this methodology was to illustrate through direct
175
-------
application to the Meadowlands the versatility of the AQUIP System for
carrying out arbitrarily specified air quality impact analyses.
The compatibility score for each plan was calculated by a special
routine written with the user-oriented hyperlanguage of the IMPACT program.
In general the concentrations for each pollutant were compared with a
compatibility criteria for each land use activity on a cell by cell basis
within the grid system. The cumulative number of violations of the
criteria represents the compatibility score for a plan: the lowest score
indicates the greatest compatibility.
The matrix of the land use/air quality compatibility criteria (i.e.,
the criteria associated with each combination of land use and pollutant)
used for this analysis is given in Table 20. These criteria are based
entirely on subjective value judgments. Only four land use (or receptor)
categories were included: residential area; commercial and industrial area;
open space; and students. Both the land use and the air quality data were
generated by the LANTRAN program.
The results of the calculation of the compatibility score are given
as follows:
PLAN
Plan 1
Plan 1A
Plan IB
Plan 1C
COMPATIBILITY SCORE
249
248
287
153
The number of violations for each grid cell was displayed by the LANTRAN
program for each of the four plans as illustrated in Figures 53 to 56.
These figures show the spatial pattern of the degree of conflict between
land uses and the air quality concentration levels for all pollutants.
176
-------
TABLE 20
LAND USE - AIR QUALITY COMPATIBILITY CRITERIA
(1)
Land Use Category
(or special receptor)
1. Residential Area
2. Commercial S Indus-
trial
3 . Open Space
4. Students
Pollutants
TSP
1.0
2.0
1.0
0.25
so 2
1.0
2.0
1.0
0.25
CO
1.0
1.5
1.5
0.25
HC
1.0
2.0
0.5
0.25
NOX
1.0
2.0
0.5
0.25
*• -'Values in matrix represent compatibility criteria, expressed as ratio
of allowable pollutant concentration to the annual average ambient air
quality standard.
177
-------
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for Plan 1A
179
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4+444
44444
+ 4 + + +
44 + 4 +
"|
+ 4+++4 +4+4
Hs;
» e b tr t? b fc "•» e H f: H b b t
• t- 1- r H e o b f-1 e - u <- H f
4 4 4 4 +
4 4 4 4 4
4444 +
*• 4^4 4
4 4 |4 4
1-4444
XXXXX
x x y x x
xxxxx
xxxxx
AXXXX
xxxxx
x x2x A
AXXXX
xxxxx
xxxxx
X < X X X
x x y x x
xxxxx
xxxxx
xxxxx
1't
13
11
10
11
12
Figure 56 Land Use - Air Quality Compatibility Score Distribution
for Plan 1C
181
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Finally Table 21 shows a histogram of the number of grid cells within
each plan having a specified number of pollutant violations per grid cell.
It is to be noted that the maximum number of violations that can occur
within any grid cell is 5 (corresponding to the number of pollutants
considered) regardless of the number of different land use compatibility
criteria violated by a given pollutant.
The analysis and interpretation of these data shows that every grid
cell has at least one land use compatibility criteria which is violated by
some pollutant. Plan 1C ranks highest having the least number of land use/
air quality conflicts. This is due primarily to the fact that, this plan
has the least variety of land use categories and in particular has fewer
of those land use categories having low tolerance to air quality levels.
On the other hand Plan IB ranks worst having a particularly large number
of grid cells with land use compatibility criteria violated by all five
*
pollutants.
These results are useful to the planner since they show the location
and degree of potential conflicts between land use categories and air
quality levels. Furthermore they represent a simplified procedure for
accounting for the combined effects of several pollutants. However the
results do not necessarily represent an appropriate index for ranking
plans since they are based on integrated affects, which as discussed
previously concerning integrated exposure impact parameters do not always
accurately reflect planning goals.
'it is noted that in Plan 1C the land use categories associated with dis-
tribution activities were not included in this scoring. As a consequence
the high ranking of Plan 1C is somewhat exaggerated although the inclusion
of all distribution activities would not change the relative ranking of
Plan 1C by this scoring method.
182
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•3
O
O
"55
O
a
o
O
"55
O
TABLE 21
HISTOGRAM OF THE NUMBER OF GRID CELLS WITHIN EACH GRID CELL HAVING
A SPECIFIED NUMBER OF POLLUTANT VIOLATIONS PER GRID CELL
0
40
0
0
Plan 1
Plan IA
1234
Air Quality Compatability Score
•tu
"c
O
O
"55
o
0
-
-
Plnn !R
0 12 345
4O •••
•*-
C
a
o
o
"55
0
O
-
- .' :
Plan 1C
183
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6.3.5 Summary of Plan Evaluations
6.3.5.1 General Criteria and Conditions for the Evaluation
The evaluation of the four alternative Hackensack Meadowlands 1990
Comprehensive Land Use Plans was based primarily on the considerations of:
1. Compliance with ambient air quality standards.
2. The influence of background concentrations on total air quality
within each plan.
3. Average regional air quality concentration levels.
4. The percent variation in total air quality among the plans on a
pollutant by pollutant basis.
5. Average exposures of critical receptors and land use categories to
pollutant concentrations.
A subjective evaluation of plans was carried out by means of a visual
examination of air quality contours and the correlation of such contours
with the land use categories of each plan. A quantitative analysis and
evaluation of plans was carried out by the calculation of quantitative
measures of impact. This quantitative evaluation was based primarily on
"averaged" impacts (such as average regional concentration levels or
average levels of exposure to specific receptors) rather than "integrated"
impacts (which are proportional to both average concentration levels and
the total number of receptors affected).
In addition to these criteria, the evaluation of the plans was subject
to other constraints and general considerations. In particular the analysis
was oriented toward regional effects based on the calculation of mean
annual pollutant concentration levels. The analysis considered the effects
184
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on regional air quality (and on critical receptors) resulting primarily
from differences among the four plans in 1) the percent mix of land use
categories; 2) the relative locations of land uses; and 3) the relative
intensity of land use activities. The relationship between pollutant
concentrations and effects such as health effects and economic consequences
were not considered. Moreover, the analysis did not consider locallized
or microscale impacts. Finally, the analysis did not consider the inter-
relationship between air pollution effects and other environmental concerns
such as water quality and solid waste disposal.
6.3.5.2 Results of Plan Evaluations
It was found that all four land use plans behaved similarly relative
to compliance with ambient air quality standards. Three of the pollutants,
S0?, CO, and NO , were found^to comply with standards in all plans. Two
£• A.
of the pollutants, TSP and HC, were found to exceed ambient air quality
standards in all four plans.
The visual examination of air quality contours showed relatively small
but distinctly observable variations among the plans for each given pollutant
with the exception of HC. In all cases it was found that background con-
centration levels represent 65% to 99% of total air quality within the
region (depending on the specific plan and pollutant) and thus represent
the most significant influence on concentration levels and spatial patterns
for each of the plans and each of the pollutants.
It was concluded that particulates represent a critical air quality
problem in all plans since background concentrations as well as total air
quality exceed standards in the 1990 time period. On the other hand, S02
185
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is not considered to be a critical problem in terms of regional air quality
since predicted concentration levels are well within the limits of the
ambient air quality standard. Furthermore the observed variation in
impacts on average regional air quality among Plans 1, 1A, and IB is less
than 6% while the impact of Plan 1C on regional air quality is 15% greater
than for Plan 1. This indicates that Plans 1, 1A, and IB are highly
preferable to Plan 1C in terms of average SCL air quality.
Air quality concentrations for CO are not considered to be a critical
problem on the regional scale for Plans 1, 1A, and 1C, since concentrations
are well within the ambient air quality standards. In Plan IB, however,
air quality reaches approximately 90% of the standard and thus becomes an
issue of critical concern, especially since under such circumstances
locallized concentrations resulting from short period peak taffic condi-
tions have a high probability of exceeding standards.
Air quality for HC is a critical consideration in all plans because
of the large factor by which standards are exceeded. Just how critical it
is, however, depends strongly on the goals and judgment of the planner,
especially since the primary concern for HC is with effects on plant life
and the formation of photochemical oxidants rather than with direct health
effects. Furthermore, since background levels represent on the order of
99% of total air quality in all plans, it is clear that land use planning
is an ineffective approach to abating HC air quality problems. However,
by appropriately locating critical receptors within a land use plan, the
planner can achieve minimum exposures of critical receptors and land use
categories.
186
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Air quality for NO is not considered to be a critical consideration
A.
since total air quality levels are well below standards. In addition
variations in average regional concentration levels among the plans are
relatively small (approximately 7%).
These results show that in many cases the planner can be neutral in
his choice of a plan based on air quality considerations. In particular
these results indicate that in the presence of high background levels,
total air quality levels are extremely insensitive to the choice of a
plan, even when emissions resulting from alternatives differ, significantly.
Thus when total pollutant concentrations are well below standards, the
consideration of air quality is not necessarily a critical factor in choosing
among alternative land use plans. For example, it is noted that in plans
where total air quality for S02> CO, and N0x is well within ambient air
quality standards, the planner can be relatively neutral in his choice of
a plan, provided that he is only concerned with these specific pollutants.
As a result of the evaluation of plans on the basis of single pollutant
impacts, the ranking for TSP, S02, and N0x was found to be (from best to
worst) Plan 1, IB, 1A, and 1C for nearly all choices of impact measure
based on average exposures (in contrast to integrated exposure impacts).
The ordering of plans for both CO and HC was found to depend strongly on
the specific receptors impacted. However, on the basis of average CO
exposures, Plan 1 was judged best generally for all receptors of interest.
For HC, Plan 1 was judged best on the basis of impact on regional air
quality considerations while Plan IB was judged best on the basis of average
population exposures (a result strongly influenced by the location of
most residential areas in the western part of the Meadowlands).
187
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The correlation between land uses and regional air quality showed
generally that lowest average regional pollutant concentration levels for
TSP, S02, and N0x are achieved by those plans having the least percentage
of land use devoted to manufacturing, and lowest levels for CO result from
plans having the least vehicle trip miles. Similarly, it was found that
the location of manufacturing land use within a plan is the dominant
influence on TSP, SO , and NO air quality contours, and that the location
of roadways within a plan is the dominant influence on CO air quality
contours.
In addition, it was generally found that those plans having the
least pollutant impact on population and residential areas were those
having the most population and residential areas located in the western
portions of the region (or more specifically, in those regions of the
plan where background concentration levels are lowest). Plans 1 and IB
generally ranked highest in terms of impact on population—Plan 1 because
of its lower regional average concentrations and Plan IB because of its
better location of residential areas within the plan.
Finally, it was observed that all land use categories other than
manufacturing and transportation, have a significantly smaller impact on
regional air quality. Thus in the presence of high background levels,
such land uses can in general be located arbitrarily within the land use
plan without any significant impact on regional concentration levels or
air quality contours. However, the relative location of such land uses
within a plan can cause a significant change in the degree of impact on
critical receptors and land use activities. Consequently it is concluded
that the consideration of air pollution in the planning process is important
188
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not only as a means to long term air quality improvement but also as a
means of reducing impacts on sensitive receptors.
6.4 Ranking of the Alternative Land Use Plans
As a final step in the evaluation and ranking of the land use plans,
the Normalized Impact Parameter ranking index was calculated for a variety
of choices of impact parameters and receptors of interest. It wa§ judged,
however, that for the purposes of ranking the land use plans, impact
parameters based on average receptor exposures are the most meaningful
representation of concerns and objectives in the planning process. The
use of impact parameters based on integrated receptor exposures does provide
useful information, but the results of the ranking based on such integrated
impacts are not as meaningful to planners who must also respond to other
planning considerations and constraints. The logical result of evaluating
plans on the basis of integrated impact measures would be the selection of
a plan consisting predominantly of those land use categories most tolerant
to air quality, a result which may be in direct conflict to the needs of
the planner to provide housing and employment, to fulfill transportation
demands, and to achieve balanced land uses.
Examination of Table 18 shows that the resultant ranking of plans based
on the Normalized Impact Parameter ranking index for average receptor
exposures is (from best to worst) Plan 1, IB, 1A, and 1C. This ranking
occurs for nearly all receptors of interest and is consistent with intuitive
judgment based upon the visual examination of air quality contours. More-
over this multipollutant ranking order is the same as the ranking of plans
based on single pollutants for most receptors of interest.
189
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REFERENCES
1. Hagevik, G. (ed.)- The Relationship of Land Use and Transportation
Planning to Air Quality Management, Center for Urban Policy Re-
search and Conferences Dept., University Extension Division,
Rutgers University, New Brunswick, N.J., May 1972.
2. Van Nest, W. and G. Hagevik. Air Pollution References for the Urban
Planner. Monticello, Illinois: Council of Planning Librarians Ex-
change Bibliographies, 1972.
3. Journal of the American Institute of Planners, Vol. XXXVII, No. 4,
July, 1971.
4. Meshenberg, M.J., "Environmental Planning 1: Environmental Informa-
tion for Policy Formulation". Planning Advisory Service Report
No. 263, American Society of Planning Officials,Chicago,111.,Nov.1970
5. Meshenberg, M.J., "Environmental Planning 2: A Selected Annotated
Bibliography". Planning Advisory Service Report No. 264, American
Society of Planning Officials, Chicago, 111., Dec. 1970
6. Environmental Quality, The Second Annual Report of the Council on
Environmental Quality, August, 1971. U.S. Gov't. Printing Office,
Washington, D.C.
7. Babcock, L.R. A Combined Pollution Index for Measurement of Total Air
Pollution. Journal of Air Pollution Control Association, 20: 653-
659 (October 1970).
8. Babcock, L.R. and N.L. Nagda. Indices of Air Quality. University of
Illinois at Chicago Circle (Presented at the 138th Meeting of
American Association for the Advancement of Science, December
1971).
9. Fulton County Health Department. Fulton County Air Pollution Index
(undated). Atlanta,Georgia.
10. Bay Area Air Pollution Control District. Combined Pollutant Indexes
for the San Francisco Bay Area. Information Bulletin 10-68. San
Francisco (1968) .
11. Green, M.H. An Air Pollution Index Based on Sulfur Dioxide and Smoke
Shade. Journal of the Air Pollution Control Association, 16: 703-
706 .(December 1966),
12. Shenfeld, L. Note on Ontario's Air Pollution Index and Alert System.
Journal of the Air Pollution Control Association, 20: 612 (July
1970).
13. Shenfeld, L. and F. Frantisak. Ontario's Air Pollution Index. Water
Pollut. Contr., 108: 55-58 (November 1970).
190
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14. Gillies, O.K.A. and H.G. McAdie. The Operational Forecasting of Un-
desirable Pollution Levels Based on a Combined Pollution Index.
Ontario Research Foundation (Presented at the 65th Annual Meeting
of the Air Pollution Control Association, Miami Beach, June 1972).
15. Thomas, W.A., L.R. Babcock and W.D. Shults. Oak Ridge Air Quality
Index. Oak Ridge National Laboratory, Tennessee Publication Number
ORNL-NSF-EP-8 (September 1971).
16. Duncan, J.R. and L.R. Babcock. Use of an Air Quality Index in Knox
County, Tennessee (being prepared).
17. Middleton, J.T.M. Air Pollution. Nation's Cities (August, 1967).
18. Huston^ S.J. Development and Evaluation of Daily Air Pollution Poten-
tial Forecasts for Philadelphia (unpublished NAPLA report).
19. Rich, T.A. Air Pollution Studies Aided by Overall Air Pollution Index.
Environmental Science and Technology, 1: 746-800 (October 1967).
20. Berg, N.J., and Kowalczyk. Air Quality Index Designed to Serve the
Needs of a Regional Air Pollution Control Authority (Presented at
the PNWIS-APCA meeting, Portland, Oregon, November 1969).
21. Konosuke, N., T. Honda, T. Suzuka, K. Mitsuoka, and Y. Ishikawa.
A Proposal of Air Pollution Index Relating to Particulate Matter -
Sulfur Dioxide Synergism. J. Pollution Control, 7: 27-37 (November
1971).
22. City of New York. Department of Air Resources, Air Pollution Imple-
mentation Manual for a High Air Pollution Alert and Warning Sys-
tem (October 1968).
23. City of New York. Department of Air Resources. The Daily Air Pollu-
tion Index, unpublished report, October 1968).
24. Prodehl, V.H., and W.P. Lowry. The Development and Application of an
Air Pollution Advisory Index as an Aid to Controlling Open Burning
(Presented at the PNWIS-APCA meeting, Portland, Oregon, November
1969) .
25. Fensterstock, J.C., K. Goodman, G.M. Duggan, and W.S. Baker. The
Development and Utilization of an Air Quality Index (Presented at
the 62nd Annual Meeting of the Air Pollution Control Association,
New York, June 1969).
26. Chapter 404, Hackensack Meadowlands Reclamation and Development Act,
State of New Jersey, 1969.
27. Goldman, C. and C. Mattson, Hackensack Meadowlands Comprehensive Land
Use Plan, Hackensack Meadowlands Development Commission, State of
New Jersey, October, 1970.
191
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28 Larsen R.I., A Mathematical Model for Relating Air Quality Measure-
U Sits to'Air Quality Standards, Office of Air Programs Publication
No. AP-89, EPA, Office of Air Programs, Research Triangle Park,
N.C., November 1971.
192
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GLOSSARY
Activity, Activity Level - basic land use and transportation planning
units of intensity of use - vehicles per day on a highway, acres
of residential land use, square feet of industrial plant space.
Activity Index - a numerical conversion factor to transform the level of
activity specified for a land use category into demand for fuel for
heating purposes.
Air Quality Contour - a contour line in a plane (usually the horizontal
or vertical) representing points of equal concentrations for a specified
air pollutant.
Air Quality Criteria - factors used in this study that represent a basis
for decision-making, for example ambient air quality standards.
Air Quality Prediction - the calculation of current or future air pollutant
concentrations at specified receptor points resulting from the action
of meteorological conditions on source emissions.
Albedo - the fraction of solar radiation reflected from the ground surface.
Ambient Air - that portion of the atmosphere, external to buildings, to
which the general public has access.
Ambient Air Quality - concentration levels in ambient air for a specified
pollutant and a specified averaging time period within a given geographic
region.
Ambient Air Quality Standard - a level of air quality established by federal
or state agencies which is to be achieved and maintained; primary
standards are those judged necessary, with an adequate margin of
safety, to protect the public health; secondary standards are those
judged necessary to protect the public welfare from any known or
anticipated adverse effects of a pollutant.
193
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AQUIP - an acronym for Air Duality for Urban and Industrial Planning,
a computer-based tool for incorporating air pollution considerations
into the land use and transportation planning process.
Atmospheric Boundary Layer - the lower region of the atmosphere (to
altitudes of 1 to 2 km) where meteorological conditions are strongly
influenced by the ground surface features.
Atmospheric Dispersion Model - a mathematical procedure for calculating
air pollution concentrations that result from a specified array of
emission sources and a specified set of meteorological conditions.
Average Receptor Exposure - a measure of the average impact of air quality
levels on specific receptors; the measure is based on the integrated
receptor exposure divided by the total number of receptors in the
study region.
Background Air Quality - levels of pollutant concentrations within a study
region which are the result of emissions from all other sources not
incorporated in the model for the study region.
Background Emissions - the emissions inventory applicable to the background
region; that is, all emission sources not explicitly included in the
inventory for the study region.
Climatology - the study of long term weather as represented by statistical
records of parameters such as winds, temperature, cloud cover, rainfall,
and humidity which determine the characteristic climate of a region;
climatology is distinguished from meteorology in that it is primarily
concerned with average, not actual, weather conditions.
Concentrations - a measure of the average density of pollutants usually
specified in terms of pollutant weight per unit (typically in units
of micrograms per cubic meter), or in terms of relative volume of pollutant
per unit volume of air (typically in units of parts per million).
194
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Default Parameters - values associated with a parameter for a category of
activities (such as heavy manufacturing) assigned to the activity para-
meter for a subcategory of activities (such as electrical machinery
production) when the actual value for the subcategory is not known.
Degree Days (Heating Degree Days) - the sum of negative departures of average
temperature from 65°F; used to determine demand for fuel for heating purposes.
Effective Stack Height - the height of the plume center-line when it be-
comes horizontal.
Emission Factor - a numerical conversion factor applied to fuel use and
process rates to determine emissions and emission rates.
Emissions - effluents into the atmosphere, usually specified in terms of
weight per unit time for a given pollutant from a given source.
Emissions Inventory - a data set describing the location and source strength
of air pollution emissions within a geographical region.
Emissions Projection - the quantitative estimate of emissions for a specified
source and a specified future time.
Equivalent Ambient Air Quality Standards - air quality levels adopted in
this study to permit analysis of all air pollutants in terms of annual
averages; in cases where state and federal annual standards do not exist,
the adopted levels are based on the extrapolation of short period stan-
dards.
Fuel Related Sources, Fuel Emissions - fuel related sources use fuel to heat
area, or to raise a product to a certain temperature during an industrial
process, or for cooking in the house; they produce fuel emissions.
(See also Non-Fuel Related Sources.)
195
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, Fuel Use Propensity, Fuel Demand - the total heat requirement (space
heating plus process heating) determines the fuel demand; the propensity
to use a particular fuel or fuels determines the actual amounts of various
fuels used to satisfy the heat requirement.
Heating Requirements - the demand for fuel is specified in terms of the
heating requirements:
space heating - the fuel used to heat area, such as the floor space
of a school in the winter, is that required for space heating; the
heat content or value of that fuel defines the space heating re-
quirement CBTUs, British Thermal Units of heating content).
r^^n-^c.e heating, process heating, - the fuel used to raise a pro-
duct to a certain temperature during an industrial process or for
cooking (with gas) in the home is that required for process heating
or non-space heating. It is generally not related to outside tempera-
ture whereas space heating requirements are.
heating, percent process heatinj
^o7"of a fuel or its heat content that is used for space heating
or process heating defines,respectively, the percent space heating
or percent process heating.
Impact Measure (or Parameter) - a quantitative representation of the degree
of impact on air cuaUty or specific receptors resulting fro, concentrations
of specified pollutants.
influence Region - the influence region for a study area is the geographica!
region containing the emission sources responsible for at least 90% of
the ground ievel concentrations (averaged throughout the study area, of
all pollutants considered.
196
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Integrated Receptor Exposure - a measure of the total impact of air quality
levels on specific receptors; the measure is based on the summation
within the study region of the number of receptors times the concentration
levels to which they are exposed.
Inventories - the aggregation of all fuel and process emissions sources is
called the emissions inventory; the components for use with the model:
current inventory - all sources for 1969
background inventory - all sources for 1990 not directly related
to the meadowlands plans.
P1an inventories - all sources for 1990 related to the Meadowlands
plans; this excludes any source outside the Meadowlands boundary
and also excludes existing major single sources and the highway
network.
Isopleth - the locus of points of equal value in a multidimensional space.
Land Use Intensity - the level of activity associated with a given land use
category, for example the population density of residential areas.
Land Use Mix - the percent of total study region area allocated to specific
land use categories.
Meteorology - the study of atmospheric motions and phenomena.
Microscale Air Quality - the representation of air quality in a geographical
scale characterized by distances between source and receptor ranging
from a few meters to a few tens of meters.
Mixing Depth - the vertical distance from the ground to the base of a stable
atmospheric layer (also called inversion height).
Model Calibration - the process of correlating model predictions with observed
(measurements) data, usually to determine calibration factors relating
predicted to observed values for each pollutant.
197
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Model Validation - the detailed investigation of model results by comparison
with measured values to identify systematic discrepencies that may be
corrected by alterations of model parameters or model mechanics.
Non-Fuel Related Sources, Process Emissions, Separate Process Emissions -
non-fuel related sources do not bum fuel primarily for heating purposes
or do not burn fuel at all; these include transportation sources, in-
cineration, and certain industrial processes; they produce process or
separate process emissions. (See also Fuel Related Sources.)
Ranking Index - a quantitative representation of the net impact on air
quality or specific receptors resulting from all pollutants being con-
sidered.
Receptor - a physical object which is exposed to air pollution concentrations;
objects may be animate or inanimate, and may be arbitrarily defined in
terms of size, numbers, and degree of specificity of the object.
Receptor Point - a geographical point at which air pollution concentrations
are measured or predicted.
Regional Air Quality - the representation of air quality in a geographical
scale characterized by large areas, for example, on the order of 50
square kilometers or greater.
Schedule - number of hour, per year a fuel burning activity will consume fuel;
used to determine heating requirements.
Source - any stationary or mobile activity which produces air pollutant
emissions.
Source Geometry - all sources for modeling purposes are considered to exist
as a point, line, or area, defined as follows:
point source - a single major emitter located at a point.
line source - a major highway link, denoted by its end points.
198
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area source - a. rectangular area referenced to a grid system; in-
cludes not only area-wide sources, such as residential emitters,
but single emitters and highway links deemed too small to be con-
sidered individual point or line sources by the model.
Stability Category - a classification of atmospheric stability conditions
based on surface wind speed, cloud cover and ceiling, supplemented by
solar elevation data (latitude, time of day, and time of year).
Stability Wind Rose - a tabulation of the joint frequency of occurrences of
wind speed and wind direction by atmospheric stability class at a
specific location.
Total Air Quality - the air quality at a receptor point resulting from back-
ground emission sources and from emission sources specifically within
the study region.
Trapping Distance - the distance downwind of a source at which vertical
mixing of a plume begins to be significantly inhibited by the base
of the stability layer, and gaussian vertical distribution can no
longer be assumed.
Wind Sector - a 22-1/2 degree wind direction range whose center-line is one
of the sixteen points of the compass.
199
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Planning Agencies Surveyed
1. California Air Resources Board
1108 Fourteenth Street
Sacramento, California 95814
2. California Department of Public Works
Division of Highways, Materials and Research Dept,
5900 Fulsom Blvd.
Sacramento, California 95819
3. Metropolitan Washington Council of Governments
1225 Connecticut Avenue Northwest
Washington, D.C. 20036
4. Office of Planning and Programming
Washington, D.C. Dept. of Highways and Traffic
415 Twelfth Street N.W.
Washington, D.C. 20004
5. Argonne National Laboratories
Center for Environmental Studies
9700 So. Cass Avenue
Argonne, Illinois 60439
6. Boston Redevelopment Agency
New City Hall
Boston, Mass. 02109
7. Boston Transportation Planning Review
100 Boylston Street
Boston, Massachusetts 02116
8. Metropolitan Area Planning Council
44 School Street
Boston, Massachusetts 02108
9. East-West Gateway Coordinating Council
St. Louis Area Council of Governments
720 Olive Street
St. Louis, Mo. 63101
10. Air Pollution Control Division
St. Louis County Health Department
801 South Brentwood Boulevard
Clayton, Mo. 63105
11. St. Louis County Dept. of Planning
Government Center, 7900 Forsyth Street
Clayton, Mo.
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12. Hackensack Meadowlands Development Commission
1099 Wall Street West
Lyndhurst, New Jersey 07071
13. Middlesex County Planning Board
County Administration Bldg., JFK Square
New Brunswick, New Jersey 08901
14. New Jersey Dept. of Transportation
1035 Parkway Avenue
Trenton, New Jersey 08625
15. Nassau-Suffolk Regional Planning Board
Veterans Memorial Highway
Hauppage, L.I., New York 11787
16. Interstate Sanitation Commission
10 Columbus Circle
New York, New York 10019
17. New York City Department of Air Resources
New York City Environmental Protection Administration
57 Astor Place
New York, New York 10003
18. Department of City Planning
New York City Planning Commission
2 Lafayette Street
New York, New York
19. New York City Office
New York State Office of Planning' Services
1841 Broadway
New York, New York
20. New York State Urban Development Corporation
1345 Avenue of the Americas
New York, New York 10019
21. Regional Plan Association
230 West 41st Street
New York, New York
22. Tri-State Transportation Commission
100 Church Street
New York, New York 10007
23. Division of Air Pollution Control
Pennsylvania Department of Health
Harrisburg, Pennsylvania 17120
202
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24. Pennsylvania Department of Transportation
Transportation and Safety Building
Harrisburg, Pennsylvania 17120
203
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ATTACHMENT B
AMBIENT AIR QUALITY CONCENTRATIONS
FOR THE 1990
HACKENSACK MEADOWLANDS PLANS
TABLE B-l
LISTING OF AMBIENT AIR QUALITY MAPS
Figure
B-l
B-2
B-3
B-4
B-5
B-6
B-7
B-8
B-9
B-10
B-ll
B-12
B-13
B-14
B-15
B-16
B-17
B-18
B-19
B-20
B-21
B-22
B-23
B-24
B-25
B-26
B-27
B-28
B-29
Air Quality
Background
11
11
11
it
Total
It
(t
11
Total
M
it
M
Total
11
it
n
Total
n
ti
tr
Total
it
it
it
Total
n
n
n
Averaging
Period
Annual
n
n
ii
n
Annual
11
it
n
Annual
n
"
ii
Annual
n
n
M
Annual
n
n
n
Annual
n
n
n
Summer
n
n
n
Pollutant
TSP
so2
CO
HC
NO
X
TSP
n
ii
n
so2
II
11
11
CO
It
II
It
HC
it
n
n
NO
X
M
n
ti
TSP
it
n
M
Plan
-
-
-
-
-
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
205
-------
TABLE B-l (conI:)
B-30
B-31
B-32
B-33
B-34
B-35
B-36
B-37
B-38
B-39
B-40
B-41
B-42
B-43
B-44
B-45
B-46
B-47
B-48
B-49
B-50
B-51
B-52
B-53
B-54
B-55
B-56
B-57
B-58
B-59
B-60
B-61
B-62
B-63
B-64
B-65
Total
ii
ii
n
Total
n
n
n
Total
n
M
it
Total
M
n
n
Total
n
n
M
Total
n
n
it
Total
n
n
it
Total
n
ii
n
Total
it
n
n
Summer
n
n
ti
Summer
n
M
n
Summer
M
II
It
Summer
M
ii
n
Winter
n
n
n
Winter
n
n
ti
Winter
n
n
M
Winter
it
n
it
Winter
it
n
it
so2
it
n
ii
CO
It
II
II
HC
n
M
M
NO
X
n
n
it
TSP
it
n
n
so2
II
II
II
CO
It
II
II
HC
n
n
n
N0x
tt
n
n
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
1
1A
IB
1C
206
-------
T
0
• •••••• H^H^MHWH noonognno *
-------
Figure B-2 Hackensack Meadowlands
19Vu Alk EUAL1TY
AI.NUAL UACMixOUNU
UATA VALUE cXTKS-Mtb AHfc
units are in pphm
(parts per hundred million)
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, ) , j , = = == = = = = = + + +4*»*
, , , t,, -•- =S = 3 = S = = = + + * + + + *
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208
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1
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Figure B-5 llackensack Meadowlands
1990 AIM QUALITY LONCtHTxAI 1Oh
NOX
ANNUAL dtCKuROUNU
DMA V'LUt cXlKtMtb A«(-
units are in yg/m
=-=========+
+ X X X
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211
-------
Figure B-6 Hackensack Meadowlands Plan 1
1990 AIR QUALITY CONCENTRATIONS
DATA VALUE EXTREMES ARE
units are in ug/m
ABSOLUTE VALUE RAMCE APPLVl^r, Trl EACH LFVEL
I'HAjinuM' iRciuDtJ IK HIGHEST tewtt
PERCFNTAGE GF TOTAL ABSOl'JTE V»LUE RANt,F APPLVINC TO EACH LEVEL
12,50 12.50 u,jo 12.50 12.50 12.51 12,50 12.50
fREOUENC" nlSTBIBUTIPN Cf UATA POINT VALUES IN EACH LEVEL
212
-------
Figure B-7 Hackensack Meadowlands Plan 1A
199Q AJR QUALITY CONCENT*ATJHN^
AN'JUAL.
I OATA VALUE FXTft£f1ES ARC
j units are in ug/m
,71
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14 *4«-
A J i •••
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~-----J 4 J "-•* -----------. BB«.B.e.B.++++ + + 4.+ X
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F VALUE m isf APPLYIM. 11 FAT ' uv=L
f'H4xr«.i-. r'eiKtffi iv "i..4tHT in-fi r-Jivi
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MN fh .lATrt I'.rnr VAlllfS IN FrtfM LE
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213
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Figure 6-9 Hackensack Meadowlands Plan It,
1 199,1 AIR OU4LITV CDMC|NTK»Tirms
j PARTIC'JI.ATFS * ~
1 iNNUAL • —
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( UAU VALUE EXTBFMES ARE 133.77 317,17 ...
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Figure B-10 Hackensack Meactowlanus Plan 1
19?i) 41H mail rv c r F IT« u I -.
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+ 1990 t!R OUAlITY cnNCfMTHlTIll'IS
I
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DATS V41DE EXTREMES ARE
units arc in pphm
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Figure B-14 Hackensack Meadowlands Plan 1
1990 AIR DUALITY CONCENTRATIONS
CD
ANNUAL
DATA VALUE EXTREMES ARE
units are in ppm
(parts per million)
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figure B-21 Hackensack Meadowlands Plan IT ^|B j
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Figure B-23 hackensack Meadowlands Plan JA
1990 AIR QU4LITY CDNCENTKATKlNb
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1990 MR QUALITY CONCENTRAT IONS
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l-igure K-27 HjLXcnsack Meadowlands I' I an 1A
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Figure B-28 Hackensack Meadowlands Plan IB
19?' MX Qi'AI.I rv c," CE IT« ITl'i is
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Figure B-29 llackensack Meadowlands Plan 1C
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Figure B-32 Hackensack Meadowlands Plan IB
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Figure B-33 Hackensack Meadowlands Plan 1C
1990 MR SlliLITV Cii'-CE''TK4' I1" •>
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! ligure B-37 Hackensack Meadowlands P
* 19^0 AIR QUALITY C nNC E^TK AT I : ,4$
* r '
i DATA VALUE EXTREMES ARE
T units are in ppra
t (parts per million)
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t 4 1 4144414444444444414- -*»«a*4-4-4-*4-*C = --*-4-
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+ + + BB3B 4- 4- + 4- -f 4- 4- 4- 4-4-4-4-4> !
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-* 1 * 2 *. J « 4 • ! *——6 -« 7 » 8 * 9 * 1- *——I——*—.—*
Figure B-38 Hackensack Meadowldnds Plan 1 ...
1990 AIR QUALITY CONCENT*AT[ONS .....II.
SUMMER -I...IIIIII.II"
DATA VALUE EXTREMES ARE H06.05 2781,03 ....IIIIII."*
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Figure B-42 Hackensack Meadowlands Plan 1
1990 AIR QUALITY CONCENTRATIONS
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units are in tig/m
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1990 AJR QUALITY CONCENTK4T jriNS
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1990 AIR OU4LITV
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1990 AIR QUALITY CDNCENTKATinNS
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TECHNICAL REPORT DATA j
(Please read Instructions on the reverse before completing) |
1 REPORT NO. 2.
EPA-450/3-74-056-d
4. TITLE AND SUBTITLE
HACKENSACK MEADOWLANDS AIR POLLUTION STUDY-
The Evaluation and Ranking of Land Use Plans
7. AUTHOR(S)
Byron H. Willis
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Environmental Research and Technology, Inc.
429 Marrett Road
Lexington, Massachusetts 02173
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
3. RECIPIENT'S ACCESSION-NO. |
fi
5. REPORT DATE ?
November 1973 j:
6. PERFORMING ORGANIZATION CODE \,
1
8. PERFORMING ORGANIZATION REPORT NO. £
1
ERT Project No. P-244-3 i;
J:
10. PROGRAM ELEMENT NO. [,
11. CONTRACT/GRANT NO.
EHSD 71-39 " i
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
Prepared in cooperation with the New Jersey Department of Environmental Protection,
Office of the Commissioner, Labor and Industry Building, Trenton, N. J. 08625
16. ABSTRACT
The Hackensack Meadow!ands Air Pollution Study consists of a summary report and
five task reports. The summary report discusses the procedures developed for
considering air pollution in the planning process and the use of these procedures to
evaluate four alternative land use plans for the New Jersey Hackensack Meadowlands for
| i990. The task reports describe (1) the emission projection methodology and its
application to the Hackensack Meadowlands; (2) the model for predicting air quality
levels and its validation and calibration: (3) the evaluation and ranking of the land
use plans; (4) the planning guidelines derived from the analysis of the plans; and
(5) the software system.
17. KEY WORDS AND DOCUMENT ANALYSIS
a. DESCRIPTORS
Land Use
Planning and Zonning
Local Governments
County Governments
State Governments .
Regional Governments
Air Pollution Control
13 DISTRIBUTION STATEMENT
Unlimited
b. IDENTIFIERS/OPEN ENDED TERMS
19. SECURITY CLASS (This Report)
Unclassified
20. SECURITY CLASS (This page)
Unclassified
c. COSATI Field/Group
21 NO. OF PAGES
200
22 PRICE
EPA Form 2220-1 (9-73)
272
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