-------
categories. However, the model has a tendency to underpredict the peak or the
maximum concentrations over the modeling domain. These results are consistent
with evaluations of the DAM performance at other urban areas by the U.S.
Environmental Protection Agency.
The UAI^ was then apsliec tc assess tne Tmoact of emissions cor-'-c's
implemented unaer me State Implementation ?"ans (SIPs] of trie tnree states ~or
1988 together with appropriate reductions in the pollutant concentrations at the
upwind boundary fo~ two of the ^ive days during wnich UAf oerformed the best.
The modeling results indicate that although there is a decrease in the 1988 peak
ozone levels, the predicted maximum concentrations are well above the NAAQS for
ozone. Even with the imposition of all the extraordinary emissions control
measures committed to under tne SIPs, the results of a one day simulation reveal
that the peak ozone level continues to be well above the NAAQS.
Analysis of the sensitivity of the model output to specific model input
conditions discloses that pollutant transport into the modeling region is
extremely important. Hence, serious consideration should be given to this
feature in addition to other emissions reduction plans for developing meaningful
and effective strategies to meet and maintain the ozone NAAQS in the New York
Metropolitan area. Additional modeling analyses are necessary to quantify the
level cf reduction in the precursor emissions required to meet the ozone NAAQS
in this area.
(iii)
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CONTENTS
Abstract
Tables
' aures,
Acknowledgements xvi - -
Chapter 1 - Introduction 1
Chapter 2 - Characteristics of a High Ozone Day
2.1 Synoptic-Scale Features 7
2.2 Local Features 10
2.3 Selection of Modeling Days 12
Chapter 3 - Model Preparation
3.1 Grid Cell Size 15
3.2 Ambient Air Quality and Meteorological Data 17
3.2.1 Ozone (Oj) 17
3.2.2 iMon-Metnane hydrocarbons (NMHC) 17
3.2.3 Nitrogen Oxiaes ^NO ) 20
/\
3.2.4 Carbon Monoxide (CO) 20
3.2.5 Ancillary Ambient Air Quality Data 20
3.2.6 Surface and Upper Air Meteorological Data 20
3.3 Model Input Parameters - Meteorological 20
3.3.1 Diffusion Break (Mixing Height) 27
3.3.3 Surface Temperature 27
3.3.4 Atmospheric Pressure 27
3.3.5 Concentrati on of Water Vapor 29
3.3.6 Exposure Index 29
3.3.7 Diurnal Photolysis Rate Constant 29
(iv)
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CONTENTS (cont.)
3.3.8 Temperature Gradient 31
2.2.9 Wind Field 31
3.3.10 Initia1 Air Quality and Region Top Concentrations 31
3.3.11 Boundary Concentrations 32
Chapter 4 - Emissions
4.1 1980 Emissions Inventory Development 37
4.2 Connecticut 1980 Emissions Inventory 40
4.2.1 Area Sources 40
4.2.2 Point Sources £0
4.2.3 Mobile Sources 40
4.3 New Jersey 1980 Emissions Inventory 4u
4.3.1 Area Sources 40
4.3.2 Point Sources 42
4.3.3 Mobile Sources 42
4.4 New York 1980 Emissions Inventory 42
4.4,1 Area Sources 42
4.4.2 Point Sources 44
4.4.3 Mobile Sources 46
4.5 1980 Emissions for the Modeling Domain - Summary 48
*•. 6 13S5 Emissions Inventory 45
4.6.1 Area Sources 53
4.6.2 Point Sources 53
4.5.3 Mobile Sources 59
4.7 1988 Emissions Inventory including Extraordinary Measures.... 59
Chapter 5 - Model Application
5.1 Input Data for JD80198(071680) 65
5.2 Input Data for JD80203(072180) 73
5.3 Input Data for JD80204(072280) 73
5.4 Input Data for JD80219(080680) 85
5.5 Input Data for JD80221(080880) 85
(v)
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CONTENTS (cont.)
Chapter 6 - Model Performance Evaluation
6.1 (JAM Simulation of the Ozone Concentration Field
for the Pi ve Days ............................................ 101
6.2.1 Paired Comparison - Data for Connecticut ..................... 113
6.2.2 Paired Comoa^isor - Concentration Greater- Thar IOC ppb ....... 112
6.3 Unpaired Comparison ....................... " .................. 120
6 . 4 Model Performance - Summary .................................. 122
6.5 Modeling Limitations ......................................... 122
Chapter 7 - Control Strategy Simulations
7.1 Initial and Boundary Conditions .............................. 125
7.2 Control Strategies ........................................... 126
7.3 Results and Discussion ....................................... 130
Chapter 8 - Sensitivity Analysis
2.1 Initial and Boundary Concentrations .......................... 139
8.1.1 Sensitivity Run 1 ............................................ 139
c . 1 . L Sens" zi vi z\/ Run 2 ............................................ 142
S.i. 3 Sensitivity Run 3 ............ •. ............................... ^4Z
8.1.4 Sensitivity Run 4 ............................................ 142
8.1.5 Sensitivity Run 5 ............................................ 144
8.1.6 Sensitivity Run 6 ............................................ 144
8.2 Discussion [[[ 146
References 150
Appendix A: Temporal and Speciation Factors for Area and Point Source
Emissions 153
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LIST OF TABLES
Number Page
2.1 Days Classified as "High Ozone Days" During the 1978-83
Oxidant Seasons with Hourly Ozone Concentrations Greater Than
or Equal to 200 ppb 8
2.2 Averages of Meteorological Variables for tne High Ozone
Days at Selected National Weather Service Stations in
the Tri-State Region 11
2.3 Synoptic Weather Pattern Summary for the Five Modeling
Days Selected in 1980 13
2.4 Summary of Local Meteorological Observations ^or the Five
Days Sel ected i n 1980 14
3.1 Ambient Air Quality Monitoring Stations Located Outside the
Model ing Region 23
3.2 Meteorological Parameters Included in the Urban Airshed Model
and Their Variation in Space and Time 26
3.2 Daytime Insolation and Nighttime Cloudiness Conditions as a
Function of Exposure Index 30
3.4 CBII Chemical Speciation Factors as a Function of NMHC
Concentrations 35
4.1 Connecticut 1980 Area Source Emissions by SCC 41
4.2 New Jersey 1980 Area Source Emissions by SCC 43
4.3 New York 1980 Area Source Emissions by SCC 45
(vii)
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LIST OF TABLES
Number Page
4.£ Percentage of Hot/Cold Starts by Vehicle Type and Roadway in
the New York Dortion of the Modeling Domain 47
-.:; -»,ssumec very z 6 ^oeecs ',!-!u-, 3^ ^oaawaj yp& ~or -jev-. -o"r
Dortior of the Modeling Domain 49
4.6 hourly Percentage of Total Vehicle Miles Travelled by
Roadway Type for New York 50
4.7 1980 Emissions Summary Over the Modeling Domain (Tons/Year).... 51
4.3 Speciated Emissions Summary for 1980 Typical Day
(0400 to 2000 Hrs.} 52
4.9 Area Source Projection Factors from 1980 to 1988 54
4.10a Connecticut 1988 Area Source Emissions by SCC 55
4.10b New Jersey 1988 Area Source Emissions by SCC 56
n.lCc I\ievv YorL 198S Area Source Emissions by SCC 57
4.10d 1988 Area Source Emissions by SCC in the Modeling Domain 58
4.11 Projected Annual Growth Rate in Vehicle Miles for the
New York Portion of the Modeling Domain from 1980 to 1988 60
(Tons/Year) 61
4.12b Speciated Emissions Summary for 1988 Typical Day
(0400 to 2000 Hrs.) 62
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LIST OF TABLES
Number
4.l3a Projected 1988 Emissions Summary with Stage II Controls
("ons/vear''
4.13b Projected 1988 Emissions Summary with Extraordinary Measures
'Tons/Year) 6^
5.1 Vector-Averaged hourly Winds for JD80198(071680)
Simul at ion 67
5.2 Hourly Diffusion Break (Mixing Height), Region and Vertical
Cell Top Heignts for JD3G198(G7163C) Simulation 52
5.3 Metscalar Input Parameters for JD80198(071680) Simulation 69
5.4 Pollutant Gradients in the Vertical and Concentrations at
the Top of the Modeling Region for JD80198(071680) 70
5.5 Hourly Highest and Second Highest Ozone Concentrations
Measured on JD80198(07i680) 70
5.c rector-Averaged Hourly winds for JD8G2C3(072180) Simulation.... 74
5.7 Hourly Diffusion Break (Mixing Height), Region and Vertical
Cell Top Heights for JD80203(072180) Simulation 75
5.3 Metscalar Input Parameters for JD80203(072180) Simulation 76
5.9 Pollutant Gradients in the Vertical and Concentrations at
the Top of the Modeling Region for JD80203(072180) 78
5.10 Hourly Highest and Second Highest Ozone Concentration
Measured on JD80203(072180) 78
(ix)
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LIST OF TABLES
Number Page
5.11 Vector-Averaged Hourly Winds for 0080204(072280) Simulation.... 80
5.12 -iour"v j'~~us'or, 5v~eak ^rx'ng isigr.t,. Reel or anc V
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LIST OF TABLES
Number Page
5.24 Pollutant Gradients in the Vertical and Concentrations at
tne TOD of the Mode1ing Region for JD80221'080880 • 9~
5.25 Hourly Highest and Second Highest Ozone Concentrations
Measured on JD8022I8(808280) 9"
6.1 Summary of Paired Comparison of Ozone Concentrations
for Al 1 Data (ppm) 108
6.2 Percentage of Model Prediction Within ±30%, Greater Than 30%,
and Less Than 30% of tneir Corresponding Measured Ozone
Concentrations for the Five Selected Days 110
6.3 Percentage of Model Prediction Within ±30%, Greater Than 30%,
and Less Than 30% of their Corresponding Measured Ozone
Concentrations for Connecticut 115
6.4a Percentage of Ozone Data Within ±30%, Greater Than 30%,
and Less Than 30% of their Corresponding Measured Ozone
Concentrations Greater Than IOC ppo 115
6.4b Percentage of Model Prediction Within ±30%, Greater Than 30%,
and Less Than 30% of their Corresponding Measured Ozone
Concentrations Greater Than 100 ppb for Connecticut 118
6.4c Percentage of Model Prediction Within ±30%. Greater Than 30%,
•i -ir
Concentrations Greater Than 100 ppb for New Jersey and
New York 118
(xi
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LIST OF TABLES
••
Number Page
6.5 Base Case Simulations: Unpaired Spatially and Temporally 121
~.l Summary of Con"-o" Crrategy Scenario 3 imu" af ons . 2IIC'. llr
7.2 Summary o* Emissions for Base Yea1' and Contro"' Strategy
Scenarios (Tons) 131
8.1 "Clean" Pollutant in the Sensitivity Analysis Concentrations
Used as Initial/Boundary Conditions 140
8.2 Summary of Sensitivity Runs 141
A-l Hydrocarbon Speciation Factors for Area Source Emissions in
the Model ing Domain 154
A-2 NO Speciation Factors for Area Source Emissions in the
A
Model ing Domain 156
rt-3 nyarocaroon ana NO Speciazior, Factors for Point
Source Emissions in tne Modeling Domain 157
A-4 New York Minor Point Speciation Factors 169
(xii)
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LIST OF FIGURES
Number Page
2.1 Typical Synoptic Scale Surface Weather Pattern for a
Hian Ozone Dav • 9
2.1 Areal Extent o~ the Modeling Region Which Includes Portions
of the States o* New Jersey. New York and Connecticut 15
2.2 Geographic Distribution of Ozone Monitoring Sites in the
Modeling Region 18
3.3 Geographic Distribution of NMHC Monitoring Sites in the
Moae"i i ng Regi on 19
3.4 Geographic Distribution of NO/NO- Monitoring Site in the
Model ing Region 21
3.5 Geographic Distribution of CO Monitoring Sites in the Modeling
Region 22
3.6 ' Aircraft Spiral Sites in the Modeling Region 24
3.7 Surface and Upper Air Meteorological Stations in tne Modeling
Region 25
3.8 Schematic Representation of the Typical Diurnal Profile of the
Region Top, Mixing Height and the Vertical Cell Height 28
Plane for Urban and Rural Grid Cells in the Modeling Region... 33
4.1 Overview of the Emissions Data Management System 39
(xiii)
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.1ST OF -IGURES (cont.)
Number Page
5.1 Synoptic Weather Mao at C70C hrs. for Each of the "ive
Simul ati o^ Davs 6c
IrrtiE/ Pol'utant £-' st"i nut i or on JD80198(07168C)
5.3 Diurnal Plots of Observed Pollutant Concentrations at the
Southwest Co-ne- GHd or JD80198(071680) 72
Initia" Pollutant Distribution on JD8Q203(072180;
5.5 Diurnal D"iot of Ooservea Pollutant Concentrations at tne
Southwest Corner Grid on JD80203(072180) 79
5.6 Initial Pollutant Distribution on 0080204(072280) 83
5.7 Diurnal Plot of Observed Pollutant Concentrations at the
Southwest Corner Grid on JD80204(072280) 86
5.8 initial Pollutant Distri Dutior, on JD80219(080680) 91
5.9 uiurnai Piot of Observed ^oMutant Concentrations at tne
•Southwest Corner Grid on JD80219(080680) 92
5.10 Initial Pollutant Distribution on JD80221(080880) 98
5.11 Diurnal Plot of Observed Pollutant Concentrations at tne
6.1 Areal Distribution of Ozone on JD80198(071680) from 1400 to
1700 Hrs 102
6.2 Areal Distribution of Ozone on JD80203(072180) from 1400 to
170C H^s 103
;xiv)
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LIST OF FIGURES (cont.)
Number Page
Area! Distribution of Ozone on JD8C204;072280) from 1400 to
-;.- Area" Ci strioution c~ Ozone fo<- JDSC219f 080680) fo^ 1400 tc
170C hrs 105
5.5 Area", Distribution of Ozone for JD8G221(080880) for 1400 to
1700 Hrs 106.
6.6 Scatter Plot of Observed and Calculated Ozone Concentration
for Each of the Five Simulation Days 109
6.7 Histogram of (OBS-PRED) Concentrations (ppm) for Each of the
Five Simulation Days Ill
6.8 Mean and Standard Deviation of the Difference Between the
Observed and Predicted Concentrations as a Function of Time... 112
6.9 Scatter Plot of Observed and Calculated Ozone Concentrations
fc- Data '" Co"rect:c;jt Region 114
6.10 Scatter Plot of Observed and Calculated Ozone Concentrations
for Data Greater than 100 ppb in Connecticut 116
5.11 Scatter PI or of Observed and Calculated Ozone Concentrations
*o^ 2sta Greate^ tha>" ICO cob 1-" *'61,- vcrk and New Jersey 11"
6.12 Mean at Standard Deviation of the Difference between the
Observed Concentrations Greater than 0.10 ppm and Their
Corresponding Predicted Concentrations 119
(xv)
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LIST OF FIGURES (cont.)
Number Page
7.la NMHC Concentrations at the Southwest Corner Grid for
JD80203(07218C) and JD8022K080880) for the Base Year and
7.1b Ozone Concentrations at the Southwest Corne>- Grid for
JD80203(072180) and JD80221(080880) for tne base Vear and
Projected Year 128
7.2 Spatial Distribution of Ozone for Selected Hours ror CSSS Run 1
and CSSS Run 2 122
7.3 Histogram Plot of Cells Exceeding 125 ppb of Ozone for the
Base Runs and the Corresponding Projected Year Runs 133
7.4 Difference Map of Ozone Concentrations (ppb) Between CSSS Run 5
and CSSS Run 1 at 1400 and 1500 Hours 134
7.5 Area! Distribution of Ozone at 1400 and 1500 Hours for CSSS
Run 6 136
T.C& Difference Map of Ozone Concentrations (ppc) for CSSS Run 3
and Its Corresponding Base Case JD80203(072180) 137
7.6b Difference Map of Ozone Concentrations (ppb) for CSSS Run 4
and CSSS Run 1 137
3.2 Ozone Isopleths (ppb) for Selected Hours for Sensitivity
Runs 2 and 6 145
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LIST OF FIGURES (cont.)
Number Page
E-l Location of tne Routine and Special Monitoring Sites for
Orone '-'''-
B-2 Diurnal Plots of the Observed and Predicted Ozone Concentrations
at Monitoring Stations on JD8C198(0716801 172
B-3 Diurnal Plots of the Observed and Predicted Ozone Concentrations
at Monitoring Stations on JD80203(C72180) 180
B-4 Diurnal Plots of the Observed and Predicted Ozone Concentrations
at Monitoring Stations on JD8G204(0722SQj 188
B-5 Diurnal Plots of the Observed and Predicted Ozone Concentrations
at Monitoring Stations on JD80219(080680) 196
B-6 Diurnal Plots of the Observed and Predicted Ozone Concentrations
at Monitoring Stations on JD80221(080880) 204
(xvii
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Acknowledgements
This is the final report for the study entitled "Oxidant Modeling for the
New York Metropolitan Area Project (OMNYMAP)." which was partially funded by the
Office of Air Quality Planning & Standards (OAQPS) of the U.S. Environmental
Protection Agency (USEPA). This document could not nave beer oreoared witnout
~ ", ~ no,--, ^" ~ -i — i^^v. ^ ^ ^ s ^ '• j£Qc'~tmant ^>~ unv^^onrnsritc "^ctsct'O;" "•>^1,~~
Connecticut Department of Envi^onmenta1 Protection (CTDEP), U.S. EPA Regions I
anc II. Of-ice or~ Research 8 Development (ORD) and OAOPS o^ USEDA.
In particular, the resourcefulness and assistance provided by Mr. Norman
Possiel of OAQPS/USEPA, Mr. Kenneth !_. Schere, and Dr. Robin L. Dennis cf
ORD/USEPA to this project deserve soecial recognition.
Tecnnical work on this project was reviewea and approved by a "ecnnical
Committee, chaired by Mr. Edward Davis, with representation of technical staff
from the three state agencies, OAQPS, ORD, and Regions I and II of USEPA.
Management oversight was provided by a Policy Committee, chaired by
Mr. Harry Hovey, consisting of senior staff from the three states, Regions I and
II, and OAQPS of USEPA.
Special thanks are extended to Messrs. Johnnie Pearson and Richard Rhoads
of OAQPS/USEPA who participated with considerable interest in this project and
pro'via&a trie support neeaeo to complete this studj .
ixvii i)
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INTRODUCTION
Pursuant to the 1970 Clean Air Act Amendments (CAA), the U.S. Environmental
Di"ctectior Agency (USEPA) has promulgated the primary and secondary Nationa"
Ambient Air Quality Standard ^ NAAQS) for ozone. As stated in the 36 -edera1
Reg-ste^ 8186 (Ao^1 1971;. this standard was "0.08 DDIT maximurr one-nou-
- ~ p ~ -j^ — v- £— - Q K) net tc o *~ excseciec mc^tr triar; ones oe^ ^ss^" ^c ~£cLS~.r9c c tnc
"Deference test methoc for ozone. However, the measurec concentrations c~~sr
exceeded this value ir ootn uroar anc rural locations. SuDsecuent"i v . oasec uoor
information on the health effects of ozone in the atmosphere, the USEPA revised
the NAAQS to 0.12 pom in 1979 with the standard being attained wher "tne
expected number of days per calendar year with maximum hourly average
concentration above 0.12 parts ne^ million is equal to or less than 1" (-10 CFR
50.9). Under Section 110 of CAA, state and local air pollution control agencies
are required to specify tne metnoas that are to be imolemented to reduce
precursor emissions in urban areas to the extent necessary to comply with the
NAAQS. These measures are to be identified in their State Implementation Plans
(SIPs). To accomplish this in an equitable manner, the regulatory agencies must
be able to relate the existing emission patterns from specific urban source
areas to air quality at downwind receptor locations, expressed in terms of
ground-level ozone concentrations.
Ozone is not usually emitted directly into the atmosphere, but is insteaa a
secondary pollutant that is formed over a period of time "ronri a var'ieti of
atmospheric reactants. The USEPA nas specified a numoer of modeling tecnmques
for estimating the required percentage reduction of precursor (hydrocarbon and
oxides of nitrogen) emissions from an urban source area necessary tc meet the
air quality standards. Since implementation of an emission control strategy may
require tremendous economic commitments and may cause severe social dislocation.
reliable estimates of ozone concentrations due to tne imoact of precursor
making a decision to adopt a particular control strategy for the area.
Downwind ozone levels are related to a specific area's precursor emissions,
and transported ozone and precursor concentrations, by the mathematical models
which predict these relationships in such a manner that various control
-------
strategies can be evaluated. Confidence can be placed in the impact evaluation
process only if reliable ozone prediction relationships are employed.
Approaches for determining the level of emission reductions necessary to attain
the NAAOS include, in the orde1" of increasing cornel exity. Tinea1" ro^back. the
"Appendix J" method, empirical kinetics moae1 , and numerical models for
ohotochemi ca1 oxidants. The cno^ce c~ aoD^oacr net only a*"ects tne sc^erv~"c
c^eci D~ ~ "• ty of "esu'ts. out a'.sc tne ease cr "implementation • •, a^-as r.av: ~z
"imited or none of the required input data, and/or the expertise ^ecui^ed to
ut~1~ze the approach .
Rollback models, wr.icn are now unacceptable, assume $ c^ect
proportionality between air quality and emissions. Thus, a reduction cf a
secondary pollutant concentration such as ozone, is assumed to be directly
proportional to a reduction in source emissions for an entire region. This
method may be used for regions only wnere very little detailed aata are
available, and then, too, only for screening purposes. Hence, this highly
simplified approach to ozone modeling is largely outmoded.
The "Appendix J," or upper limit oxidant - hydrocarbon concentration
approach, is a technique developed in the early 1970' s which attempted to
develop a simple relationship between afternoon oxidant levels and morning
hydrocarbon concentrations. Since the model complete"1 y disregards the
site-specific or local effects of nitrogen oxides, meteorology, and ozone
transport, tnis aoproacn also is no longer considered valia D> L'3EP^.
Empirical kinetics models represent an attempt to develop the relationships
between ambient ozone concentrations and precursor emissions, based on smog
chamber simulations. Initial concentrations of various precursor mixtures are
Introduced into the smog cnamoer and are subjected to sunlight tc induce
photocnemi cal activity. Resulting ozone concentrations are observed as a
in an isopleth form as functions of initial concentrations of non-methane
hydrocarbons (NMHC) and oxides of nitrogen (NO ). This information was utilized
X
to develop the USEPA Model, Empirical Kinetics Modeling Approach known as EKMA.
The EKMA model is probably the most reasonable model currently available for
-------
relatively widespread use. There are, however, some limitations to the model.
For example, ambient precursor concentrations within the urban area are assumed
to be directly proportional to emissions. Differences may exist between
NMKC/NC "atios fy>oir measurec concentrations and those deduced from emissions
x
inventory data. Another proolem is related to the treatment of background
concentrations. Because of ve^y raoid reactions Detweer NC and C7. the
D^e-ex"1 st" no ozone ;r an a:-" mass moving into an uroan locate :s -ct necessa"" _,
additive tc the ozone Du^laup resulting from locally emitted precursor
oollutants. Ir addition. EKMA canno" creriict spatia" effects, does net a'lov
horizontal pollutant exchange with air outside the parcel, and assumes
instantaneous complete mixing in the vertical direction as the height of the a-:"
column (mixing height) increases. Furtnermore, EKMA is unable to predict ozone
concentrations at locations not represented by physical monitors. Mnally, fo»-
a large urban area such as New York the trajectory approacn is inadequate to
describe the physical mechanisms of the large plume and the effects of a variety
of meteorological conditions.
Numerical photochemical transport and dispersion models such as the Urban
Airshed Model, (JAM (Reynolds, 1979), and Livermore Regional Air Quality Model,
LIRAQ (McCraken, et al., 1975) and the Cal Tech photochmeical grid model (McRae,
et al., 1982) are among the most sophisticated of the approaches, and are
well-suited for predicting tne spatial and temporal distributions of ozone
concentrations downwind of urban areas. In theory, numerical modeling approach
is the best choice. However, in practice, numerous proolems arise. Tnese
include the following: the difficulty of numerically solving tne complex
conservation of mass equations accurately; the high computational costs and
expertise required for model implementation and interpretation; the unknown
effects of treatments of the transoort. diffusion, and reaction orocesses in the
model due to limitations of available data and knowledge: the Targe data
^eauirements for testing critica1 features of the model and its validation: and
pernaos most "mportar,t i \,, ~RS neec 'C1- a spat i a;../ e.nc. tempor ~ •.'. j dcc-;"i.",,c
emissions inventory.
Thus, it is evident from the above discussion that advanced models are
required to properly identify the relationship between emissions and ozone
concentrations. Equitable and effective control strategies can only be
developed based on the numerical models since the photochemistry, transoort, and
-------
-a-
diffusion of ozone are treated In detail by these state-of-the-science models.
However, it is imperative that the emissions data base as well as the aerometric
data used in the model are accurate to ensure that the modeling results are
usefu"1 anc credible. ^irthe". the uncertainties associated with the mode"
results must also be taken into account in the development of meaningful contrc'
st^atscr as *o" ozone.
The goals of this project are to assess and quantify the ozone problem in
the New York Metropolitan area, to evaluate the available control options and
to develoo effective and equitable strategies for reducing the ozone levels in
the region through the application of the (JAM photochemical oxidant model. The
New York Metropolitan area includes portions of the states of New Jersey,
New York, and Connecticut. As a part of tnis study, meteorological and amoient
air quality data were analyzed to characterize those conditions that are
conducive to the formation and production of peak ozone levels in the region.
Based on this analysis, five typical high ozone days in the 1980 oxidant season
were selected for detailed modeling analysis. The pertinent emissions and
meteorological data were assembled to execute -the UAM for these selected days
for the base year, 1980. The model predictions were compared with the
measurements to assess the model performance. These results indicate that the
UAM performance in this study is similar to its performance in other urban areas
such as Tulsa, St. Louis and Philadelphia.
Evaluation of tne control options inciuaea emissions projections of ~ne
1980 baseline to future scenarios (such as tne 1982 SIP for 1988 j in order to
determine whether these measures will reduce the ozone concentrations to the
level of the NAAQS in the region. These projections included changes in
emissions arising from changes in population and activity levels, as well as
specific changes in emissions associated with regulatory actions that are
already mandated under the current laws and regulations and projected oollution
' i i u C ~ 0', . . i l: c . 3 S3SOC"iatiG '•". " t.". J D i'.1'"" " C r iTi"! SI ~ 0 " S Z C* fi t r 0 , ^ • a P C . - 3 " il Q t ~ i
meteorological features observed in 1980, model simulations were performed to
assess the impact of selected emissions reduction scenarios for two of the five
days. Although the predicted peak concentrations in 1988 in the New York
Metropolitan area are reduced from the base year levels, the predicted peaks are
still well above the ozone NAAQS. Simulation of the UAM for one day with the
-------
-5-
iffipositior, cf a",", extraordinary emissions contra" measures included ir. the SI^s
reveals that the peak ozone concentrations are still well above the ozone NAAQS.
Finally, the sensitivity of the model to various input parameters was evaluated
and the results suggest that transport of ozone and its precursors into the
mooeling domain significantly affects tne ozone concentration field over me
tri-state region. Additional modeling analyses are necessary to document
c'sar'y the dynamics associated with the oxidants and the "eve1 c* "educt'cr ~\r
tne precursor emissions requires to meet and maintain czone NAAQS ir tne
New York Metropolitan area.
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-6-
(BLANK PAGE)
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-7-
CHAPTER 2
CHARACTERISTICS OF A HIGH OZONE DAY
Studies of amoient ozone concentrations in the Northeastern part of the
United States have reoortec that the NAAQS value of O.IZ opm is often exceeded.
.."tr concentrations "eacr"'", z as ~~gr as. 1ZC CDC a own wine ~^~ ir~e •, '~ra" "ar";"c
These exceedances are found region-wide, indicating that ozone is a pervasive
ai>" contaminant mainly occurring during the summer months of June. Ju'y and
August, tne so called "ozone season". In oraer to understand prevailing
meteorological characteristics during the days of nigh ozone concentration.
ambient air quality measurements ••'rom the states of New Jersey, New York, and
Connecticut were examined for a six year period frorr> 1978 to 1983. The
criterion adopted to select a day as a high ozone day was that the maximum
hourly concentration at a monitoring station be equal to or greater than 200
ppb. The days thus selected are listed in Table 2.1. The number of days range
from a minimum of 5 days in 1982 to a maximum of 16 days in 1983 with a majority
of them occurring over Connecticut. It should be noted that the number of
monitoring stations and their locations often varied from year to year, and
therefore a subset of high ozone days from Table 2.1 was selected such that
there be at least two stations in Connecticut and at least one station in the
New York-New Jersey area exceeding the 200 ppb concentration value. A general
description of tne meteorological features that are representative of tnis class
2. 1 Synoptic-Scale Features
The daily weather maps published by the National Weather Service (NWS) were
examined for the high ozone days both at the surface anc upper levels. A fairly
consistent weather pattern was ooserved along with a fev\/ outlying cases. Figure
zone stretched from the Northeastern U.S.-Canadian border westward and then
southwestward through the eastern Great Lakes. High pressure prevailed over the
Atlantic and westward through the southern States. The frontal position varied,
in other cases, around this "average" position—latitudes from near James Bay to
central New York and longitudes from western New York to the central Great
Lakes. The "Bermuda High" varied in position from the Atlantic to the extreme
-------
-8-
TABLE 2.1"
Days Classified as "High Ozone Days" During the 1978-83 Oxidant Seasons,
With Hourly Ozone Concentrations Greate" Than or Equal to 200 ppb
vear Hign Ozone Days (du1'Man Day)*
_"'C iOo.CC, /£._/*.. < .j _ , _ . C.-.C. /' O _ O C . /' S _ .1C . , 0 _ i. ,
1979 79167, 79194, 79201, 79205. 79206, 79213
1980 80167. 80176, 80177. 80192. 80198. 80202. 80203. 80204. 80219. 80221.
80240, 80241
1981 81166, 81167,81172, 81189, 81194, 81200
1982 82189, 82197, 82198, 82199, 82220
1983 33165, 33166, 83167. 83174, 33177, 83178; 33184, 33186, 83192, 83195,
83209, 83211, 83220, 83229, 83232, 83239.
*For example, Jullian Day 78166 corresponds to June 16, 1978.
-------
- 9 -
liozo io'« 1012 low 'ooe ' ^ x
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7»- S&^ - '-
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Figure 2.1 Typical Synoptic Scale Surface Weather Pattern for a High Ozone Day
-------
-10-
southern Midwest. In addition, another characteristic feature that was observed
on the smaller scale to the east of the Appalachian Mountains was a "lee-side
trough", which extended with some variation, from southern New England south-
westward to Virginia, tne southern location being more pronounced anc occu^inc
more freauently (Pagnotti, 1987).
i'jeav" tne ^ec" or,. cyclonic "1 ov. was founc a~:c~t ir almost a~~ zases -.-itr a
short-wave trough approaching or passing through the region. Predominant upper
leve1 winOE (500-70C MB leveP varied from northwest through soutnwest. wivle
surface winas were generally southwesterly. Precipitation over some part of the
^egion was often observed while maximum temperatures over the region varied from
the 80's to arcund 100°F.
In some instances, high ozone days were also observed under other
meteorological conditions, usually witn a surface cyclonic feature of some kind
near or within the region. The latter included, for example, a frontal trough.
or a low pressure area centered offshore or to the northeast. Also, a few cases
had the surface and upper level winds from north or northeasterly directions.
2.2 Local Features
The local cl imatological data were scanned to describe a typical high ozone
day. The meteorological variables averaged over 28 cases resulting from the
s^cset cl £i^3if i caziori for selectee National weatner Service (IMG/ stations over
trie tri-state region are listed in Taole 2.2. Maximum temperatures in the
region range from 85°F to 93°F, while the minima range from 66°F to 70°F.
Precipitation occurs between 17% (Central Park) and 45% (Hartford) of the time,
with a station mean of a hundredth of an inch at Central Park to a tenth of an
inch at Bridgeport. The surface winds are generally south to southwesterly.
with average hourly speeds for these days ranging from 3 m/sec (Hartford ana.
(sunrise to sunset) ranges from five to six tenths. Smoke and haze were the
most common weather types reported, along with fog and occasional thunderstorms.
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-12-
2.3 Selection of Modeling Days
By virtue of its design, the UAM requires the detailed input of various
aerometric data sets for simulating the concentration field (Ames, et a"!..
1985a, 1985b). In a majority of the applications, the required input data are
not available f^om ^outine measurements and nave to be aeve"ooec ^"om soeci a'
mon'i-crinc networks. One sucr netwo^K ^s tne 193C Nortneast Cor"~->ao" Reg: one.
Modeling Project (NECRMP, 1982a) conducted by USEPA, which provided a detailed
and extensive aerometric data base for this region. An examination of the
NECRMP data base for aircraft measurements (NECRMP, 1982b) and Table 2.1 reveals
that of the 12 days only 5 days could be considered for the application of the
UAM. The five days are 0080198(071680), 0080203(072180), JD80204(072280),
0080219(080680). and JD8022K080880).
A brief description of the synoptic weather oattern for tnese five Gays is
given in Table 2.3. These days appear to fit the characteristic pattern
discussed earlier for the high ozone day with a frontal array across the
northeastern U.S. border, slightly disturbed west-southwesterly to
west-northwesterly flow aloft, a weak surface trough east of the Appalachians,
and a surface high pressure ridged from the Atlantic Ocean westward across the
southern U.S. In Table 2.4 are listed the local cl imatological data for the
•five days. Most stations exhibit the typical conditions, namely, temperature
maxima in tne upper 80's and 90's °F, minima in the upper 60's and 70's °F, a
p- =v£."ier;ce cf smoke, naze, some ~og anc occasional occurrer.ee cf thunderstorms.
Average SKV cover (sunrise to sunset) is generally five tenths or greater, anc
surface winds are generally south to southwesterly with wind speeds in the range
2-7 m/s.
-------
TABLE 2.3
Svnoptic Weather Pattern Summary for the Five Modeling Days Selected in 1980
JD80198
(071680)
Cold f^ont lies f"om a oosition over Northern Indiana tc
Northern Maine; hign pressure from the Atlantic westward tc
Texas: weak trougr east of the Apoalachian Mountains: "
upD9"-~ eve", vcugr over trie jortneast. \\~~r, ic^tr.weste1-"
aloft, ana short wave aooroaching from the west.
JD80203
Frontal array (cold front-stationary front) midwest through
northern Maine; high pressure >"idge ^rom Atlantic westward to
Alabama; trough east of the Appalachians; upper-level short-wave
approaching from the west, with westsouthwesterly flow aloft.
JD80204
(072280)
Similar to JD8G203(072180), except, southwesterly flow aloft.
JD80219
(080680)
Cold front approaching from southern Canada-Great Lakes region;
high pressure from Atlantic westward to the southern Midwest;
trough east of the Appalachians; upper-level disturbance to the
northwest, with westerly flow aloft.
JD80221
\OoGSSo i
Stationary front - cold front Great Lakes to Northern
hiew Lnglana; mgrt pressure from Atlantic westwaro to tne southern
Miawest ana Texas; slightly cyclonic flow east of tne
Appalachians; upper-level short wave approaching from the
northwest, with west to northwesterly flow aloft and a weak
disturbance over New England.
-------
-14-
TABLE 2
Summary of Local Meteorological Observations for the Five Days Selected In 1980
Date
J33C198( 0~1S8CT
JD80204 (C7228Q1
OD30219(080680)
JD8G221( 080880;
JD80198(071680)
OD8G2G3(0721SCj
0080204(072280)
0080219(080680}
JD80221( 080880)
JD80198(071680)
JQ8C2Q3'072180 ^
0080204(072280)
JD80219(080680)
JD80221(080880)
JD80198(071680)
JD80203(072180)
JD80204(072280)
0080219(080680)
0080221(080880)
JD2C198(Q71580)
JD20203(0721SC)
0080204(072280)
Ju£o2J.5xOc05£u ;
j~p,Q7?i t' 080880 '
0080198(071580)
0030203(072180)
0080204(072280)
0080219(080680)
0080221(080880)
OD3019S( 071630}
1 ' ' - - • ' , -^ ."
u _; o w ,_ -"- \ - i C.ta.3u ;
0080219(080680)
0080221(080880)
Temperature
Maximum Mi
92
9-
9C
88
91
96
101
95
9C
95
97
9°
92
90
94
84
97
87
89
93
99
102
94
iw
9^
91
97
89
88
89
96
bl.
89
92
i or)
nimum
K
67
69
65
73
81
70
73
76
77
S3
73
76
79
70
78
72
75
76
77
82
72
76
80
72
75
72
75
75
70
69
71
70
Weather f
Type*
- c
2\l
1,3.8
1,8
1,3,8
8
3
8
8
3,8
8
3,8
8
8
1,3,8
8
3
8
8
3,8
1,3,8
1,8
8
1,3,8
_ ,3 .0
1,3,8
8
^ecioitation** Averaae Wind
(inches;
-
1.26
0.15
0
0.09
0
0.43
0
0
0.02
o
0.38
0
0
0.05
0
0.19
0
0
0.03
0
0.28
G
0
T
0.22
0.92
T
0
0.01
i. 35
0.08
0
Direction
20C
24C
240
220
250
230
240
250
230
230
240
200
270
220
210
210
210
230
240
220
230
240
25C
230
230
230
230
230
240
200
25C-
250
230
Speed^m/S;
*.*
i- U
2.9
4.2
6.0
4.2
5.1
4 .4
5 . 2
5.8
6,6
5.8
5.0
5.8
5.0
5.2
6.0
4.6
5.6
n. a
4. 1
3.7
w . ~J
5 . 8
6.7
5.6
5.5
5.0
5.1
3.5
— - -
2^2
2.6
Sky Cove*
'vtentns;
-
-
•7
-
8
~~!
7
6
7
7
a
7
5
6
7
6
6
6
7
6
6
5
6
-T
5
5
7
6
-J >.
i-
^j
Net
NO
LaGu
Air
NY
OFK
Air
NY
Cerr
Part
NYC
i^ ,
Brid
oort
CT
Hart'
-
*Weather types: 1: Fog 3: Thunderstorm 8: Smoke, haze
**Total during the day and T corresponds to a trace of precipitation
-------
CHAPTER 3
MODEL PREPARATION
The area! extent of the modeling region selectee in tnis stuay was guiaea
o\ tne primary oojecfwe c* capturinc tne peak ozone concentrations resulting
~^crr ~ns emissions 'r New os^ss1 . ,'jsv, 'c"".. anc Ccfinec"" CL;"C. ~~iuz ~~^ ~ocs ~ ~c
Gomain includes almost a";' of the State of Connecticut and tne man emission
aensity regions of New YoH- anc Nev, Jersey, "rentor., NJ was selected &s tne
approximate location of the southwest corner of tne modeling aomain. Tne areal
extent of the modeling region as snown in Figure 3.1. is 49.6 x 10" Km" witn
east-west and north-south dimensions of 248 and 200 km, respectively.
C.I Grid Cal1 Size
The UAM program utilizes the modeling region as a volume subdivided into an
array of three-dimensional grid cells. The horizontal, i.e., the east-west,
north-south plane is divided into cells of equal size. The vertical cell size
is dependent upon the fixed number of layers into which the layer between the
ground and the top of the simulation region is subdivided. In this study, an
8 km cell equal in east-west and north-south directions, was selected. This
yielded 31 cells in the east-west direction and 25 cells in the no^th-south
direction. The 8
-------
x;
o
c
0
(T
C
0)
•a
o
s
-------
Thus, in summary, the modeling region consists of:
31 cells in the east-west (X) direction,
25 cells in the north-south (Y'; direction, and
4 cells in the vertical (Z) direction
,v~tr tne southwest ^c^ner. tne c^g"*",. set at L'Tf-' DZC.COC.^ ~ ^. ^~c.33C.~ ~ \
and a cell size of 8,000 m. The UTM zone 18, was extended for the easternmost
oarts of Long Island and portions of eastern Connecticut.
3.2 Ambient Air Quality and Meteorological Data
Ozone (0^x,
The geographic distribution of the ozone monitoring stations is snown in
Figure 3.2. In general, monitoring data over the northwest quadrant are sparse,
with the majority of the stations oriented along a southwest-northeast line. In
addition to the routine monitoring stations, data are available at four other
sites from NECRMP. These locations are also shown in Figure 3.2. On a state-
by-state basis, the number of stations in Connecticut, New York and New Jersey
were 10, 13 and 10, respectively with the majority of the New York and
New Jersey stations located in the southwest quadrant of the model domain.
5.Z.L Non-Metnanfe hygrocaroons (NMKC',,
The locations of the non-methane hydrocarbon monitoring stations are shown
in Figure 3.3. It should be noted that no routine monitoring was performed for
these pollutants and that the sites shown in Figure 3.3 represent the special
sampling locations set up under tne NECRMP. The stations were principally
located in the southwest quadrant and were the only ones available for
-------
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-------
-20-
3.2.3 Nitrogen Oxides (NO _).
A
The monitoring stations reporting nitrogen oxides, shown in Figure 3.4,
were a1! located in the soutnwestern portion of the modeling domain. In addi-
tion ro tne data from 15 to 20 routine monitoring stations, data from tnree
othe^" sites f|"orr tne NECRMP stucy were usec to estimate the di st1""1" buvon o~ tne
oxiaes c~ n'troger, ir tne moae":inc aomaV..
2.2.2 Ca^bor Monoxide ''CO'
The majority of the CO monitoring stations, shown in Figure 3.5, were
located in the urban areas. The data from these stations were used to provide
estimates cf the distribution of the pollutant concentrations in the moae'ing
domain.
3.2.5 Ancillary Ambient Air Quality Data
Ambient air quality data from stations located outside the domain, listed
in Table 3.1, were assembled to provide the required input data at the
boundaries of the modeling domain. Also, aircraft data collected under the
NECRMP study were utilized to provide information on the pollutant distribution
in the vertical plane. The flight paths over the domain consisted of horizontal
traverses witn spirals at the fixed locations shown in Figure 3.6.
5.2.6 Surface anG upper Air Kieteorologi ca'i Data
The routine NWS station network in the domain, shown in Figure 3.7, provided
the surface wind speed and direction, relative humidity, atmospheric pressure and
temperature measurements. The upper air data were obtained from the NWS station
at JFK Airport, New York City and NECRMP stations shown in Figure 3.7, and the
r *- ~ ~%c ;^ . c E. t - -'9^^. ta^sr ~^crr ~ * 9r~^ ~ctc'" snr i3*~ D0'~c ^" '.'S1/ 'j —^z^1
3.3 Model Input Parameters - Meteorological
For each of the days selected, the UAM simulations were commenced at 0400
Hrs and terminated at 2000 Mrs. The meteorological parameters needed to execute
the UAM program are listed in Table 2.2 and a brief description of the
methodologies adopted for obtaining these parameters is given below.
-------
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5 / \s • i vif^^^r
2 / « * V'?^x
x . i^_i * ^ - *•
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==-—7 _a ^=rl
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\
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J"
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= .•
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-------
-23-
TABLE 3.1
Ambient Air Quality Monitoring Stations Located Outside the Modeling Region
Pennsy'i varna
Scranron
Al1entown
Nev Jersey
Anco^a
Flemi ngton
?ni 1 "i ipsburg
McSui^e AFE
Trenton
Nacctee CreeK
Chester
New
Rhode Island Massacnuse^rs
5i ngnamton
Renssel aer
nGa.vtB.rr
Medfield
Eastor
Somervi 1 le
Pittsfie~jc
-------
- 24 -
13
r^
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4J
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V-l
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£1-
J.
1 1
j )
1 '
:
Ijfe
•
1 1
i-i---
s
3
z ;
* /
r ) *
_ ^ /
z "\
-
-i."" — r^'
o' '"7a ' e\ ' ;
a S \'\ \V - --»
2 O •=? \^ ^ " u \
J"i;T~ "j \ ^ ^^ \ * ^. |
* ^ \ ^ ^^ \ * * 1 *
„_,— Ji '\ ^Jb'*?* A^ |. «* *- Itz"*'^
1 - j*^^ ' ^^-*^ • J^'H-I J"-— s"l'?i?"''
^ - \ \ ^X"\ /"A ifijlUlHliillH'
j/" * L_^-'"-
CO
-------
-26-
TABLE 2.2
Meteorological Parameters Included in the Urban Airshed Model
and Their Variation in Space and Time
Parameter Variability
Space Ti_rrie
Diffusion break (mixing height} t
Top of the modeling region t
Surface temperature x, y t
Atmospheric pressure t
Concentration of water vapor t
Exposure Index t
NG2 Photolysis Rate constant t
Temperature gradient above and
below the diffusion break t
Wind field in terms of u and v t
-------
Diffusion Break (Mixing Height)
The available data for the determination of the hourly mixing heights
included rawinsonde temoerature soundings and vertical profiles of temoeratu^e
and pollutant concentration measured by aircraft obtained at the locations shown
in r:igures 3.6 and 3.7. The methods by which the hourly, mixing neignts were
^e^vec 'ncluaec tncse o~ benKe" ey-Scnulman ,1379 . Veuwstact 1331 . anc
Garrett (1981). Also, the information on the vertical gradients in the ozone
concentration and the extent or" ozone scavenging were utilized in estimating the
spatially invariant hourly mixing heights for each of the selected days.
3.2.2 Top of the Modeling Region
An nourly variable neignt for the region top was selectaa for this stucy.
Tne region too was assumed to rise at a rate slower tnan that of the mixing
height in the morning hours, and by midday both of them became equal. The
region top was assumed to remain constant at that height, while the mixing
height decreased in the late afternoon hours. The top of the modeling region
was set at a minimum height of 1000 m with a minimum depth of 500 m for the
layers between the top of the modeling region and the level below. Figure 3.8
shows schematically the diurnal profile of the top of the modeling region along
with mixing heights ^or the modeling domain.
0.3.3 Surface Temperature
The distribution of the surface temperature within the domain was derived
through an inverse-distance-squared weighting interpolation scheme utilizing the
measurements available at the NWS stations shown in Figure 3.7 for each hour of
the model simulation.
Sea-level atmospheric pressure values, obtained from the NWS stations shown
in Figure 3.7, for each hour are averaged to yield a value over the domain for
that hour.
-------
- 2£ -
I
O
UJ
MIXING HGT •
REGION TOP
' CELL 3 V
CELL 1
TIME (ESI)
Schematic Representation of the Typical Diurnal
Profile for the Region Top, Mixing Height and the
Vertical Cell Height
-------
-29-
3.3.5 Concentration of Water Vapor
Following Byers (1971) and Hull (1974) the specific humidity of saturation,
q_. was obtained as follows:
q (grams of water/grams of air) = 0.622 e /(P-G.37 e j
wnere e . tne saturation vaoo1" oressure (mb) is giver by
wnere X = (T i- 273.16-Bj
= 17.2593882
6 = 35.86
E,. = 6.107S
P = atmospheric pressure (mb)
T = dew point temperature (°C)
In this study, the specific humidity of saturation for each hour was
calculated from the data collected at the NWS station located at JFK airport in
New York City, which was then multiplied by 10 to yield the water vapor
concentration in ppm as a representative value for the domain.
3.3.6 Exposure Index
This parameter is a measure of near ground level stability due to surface
neating or cooling and is estima.teo frorri insolation as snown in Table 3.3. In
tris stud;-, the date jt'"1 ized to estimate the exposure inder included the sc^a"
•~ac~ s.tior. aata f^orr the -Ismingtcr and i'ar'bc-c sites i ~ the southwestern part
of New Jersey and the hourly sky cover conditions reported from the NWS stations
shown in Figure 3.7. An estimate of the exposure index for each hour was made
using these data as well as synoptic weather information.
3.S.7 Oiurna1 Photolysis Rate Constant
A computer program that incorporates the data of Demerjian, et. al., (1980)
was used to calculate layer-averaged N02 photolysis rate constants based upon
the latitude, longitude, month, day and time of day, mixing height, and solar
radiation data. Assuming clear sky conditions and using the mixing height
information, the layer-averaged N02 photolysis rate constants were obtained for
the modeling domain.
-------
-30-
TABLE 2.3
Daytime Insolation and Nighttime Cloudiness Conditions
as a Function or Exposure Index
Exposure Ingex
Insolation Moderate
Slight
Heavy overcast day or nignt
Night time > 4/8 -1
C:oud cover < 3/8 -2
-------
-31-
3.3.8 Temperature Gradient
The temperature gradients above and below the diffusion break were
calculatec f^om the temperature soundings available at one or more locations
shown in -igure 3.7. The gradients for each hour were estimated by averaging
the measured profiles at increments of IOC m above and below the diffusion
D"eaL. ro" tnose nours ~ i*- ,-ir,~ zr cats ve^e 'TO" ava^'ao'e. ~ne r^ac: ertc -i^^-.
ODtainea tnrougn linear interpolation from adjacent nours.
3.3.5 Wing Fie'ic
UAM reauires the soecification of a gridded three-dimensional flow field.
Attempts were made to generate a gridded wind field based uoon the available
surface and 'jpper air data from the stations shown in "igure 3.7, using the
Cla*"k and Eskridge (1977) non-divergent algorithm. However, the spatial
representativeness of the available upper air observations for the entire
modeling domain was found to be questionable because of the influence of
land-sea breeze circulations. Application of a bi-cubic splines interpolation
technique to the surface level winds produced too much smoothing in the derived
wind field. Thus, it was decided to use only the surface based observations and
generate the three-dimensional non-divergent gridded wind field, assumed
invariant in the vertical direction. However, examination of such a wind field
and trajectory patr.s revealed an undue influence from the coastal NWS stations
wMch apoea1" tc b= s-c~sctec' sigr'xi carf y by the land-sea breeze i nteract'cn.£.
.-.e-.cs. e spatially constant but tempera."1"!j ^a-ying vector-averaged wind speed
and direction for each hour of the simulation were considered to be a reasonable
compromise for capturing the transport characteristics prevailing in the
modeling domain.
3.3.10 Initial Ai^ Quality and Region Top Concentrations
The following procedures were adopted to obtain the gridded pollutant
distribution at the surface and in the vertical. For each of the pollutants the
concentrations measured at the ambient air quality monitoring stations shown in
Figures 3.2 to 3.5 for the period 0300 and 0400 Hrs were averaged and formed the
-------
-.1.1-
basis for generating gridded surface concentrations. The methods consisted of
an inverse-distance-squared weighting scheme or the population distribution as a
surrogate parameter, particularly when there were very few or a limited number
of surface stations ^rom wnich date, were available tc make a meaningful ir.te1"-
polatior over the modeling domain. cor the grids over the Atlantic Ocean, the
"cT'iitant concentrations we1"5 assumed tc be tne same as those ;i 1av9v" - arc!
assumec to oe umformlv distributee in tne vertical.
The pollutant measurements made with tne aircraft over the domain were used
to provide the concentration estimates at the top of the modeling domain for
each of the collutants as we"1! as for the layer 4. For the intermediate "levels
between the surface and the base of the layer 4, the concentrations were deter-
mined as follows. If the grid cell was classified as urban, the concentrations
were assumed to be uniform from the surface up to the base of layer 4; and if it
was rural, tne concentrations were obtained using the gradient determined from
the aircraft spiral data. This is shown schematically in Figure 3.9.
Listed in Table 3.4 are the CBII chemical speciation factors which were
developed from the ambient NECRMP data base and applied to the NMHC concentra-
tions in this study. The NO^-NO ambient concentrations were assumed to be in
the ratio of 2 to 1.
3.3.11 Boundary Concentrations
Tne surface concentrations along tne boundaries for eacn nour were
estimated based upon measurements from the monitoring stations listed in Table
3.1. Attempts were made to take into account the wind direction for each hour
in arriving at the surface boundary concentrations considering the "iocation of
the monitoring station and availability of data. The vertical gradients of the
pollutants determined from the aircraft measurements were applied to all four
layer. In those cases where the ozone concentrations in any one of the surface
boundary grids was determined to exceed that of the region top value before the
mixing height entrenches into the layer 4, such grids were assumed to be
uniformly mixed up to the layer 3. In the case of the 4th layer, it was assumed
-------
X
o
UJ
X
REGION
TOP
LAYER 4
I
I.I I.I.
NMHC,NOX 03
CONCENTRATION —-
Urban Grid Cell
x
o
UJ
'I
LAYER 3
x
o
UJ
X
LAYER 2
MODELING DOMAIN
CONFIGURATION
NMHC,NOx Oj
CONCENTRATION —
Rural Grid Cell
Figure 3.9 . Schematic of the Initial Pollutant Distribution in the
Vertical Plane for Urban and Rural Grid Cells in the
Modeling Region
-------
-34-
that the pollutant concentrations are the same as those adopted for the top of
the modeling region. This procedure was adopted for those hours for which the
diffusion break (mixing height) was at or below the base of the layer 4. For
a"1 subseauent hours it was assumed that the ocllutants are well-mixed through-
out the layer 'rom the surface up to the fourth layer. In the case of tne grias
over the Atlantic Ocean, it was again assumed tnat the concentrations we^e at
tne same ":eve;s as tnose of tne layer - v.ntr nc .'s"tica~ grac~:ent. ~^e *C „-•-;',
mix at the boundaries was also assumed to be in tne ratio of 2 to 1 anc the NMHC
concentrations were soeciated as follows - 6?:- carbonyls CCAREj. 2°/-, ole^r."
(OLE), 24% aromatics (ARO), 58% paraffins (PAR), and 3% ethylenes (ETH).
-------
-35-
TABLE 3.4
CBII Chemical Speciation Factors as a Function of NMHC Concentration
NMHC (pob C^ GARB OiE ARC PAR ETH
<50 2 0 25 51 3
50-100 6 3 24 58 3
<100 3 5 Z2 63 3
-------
-36-
(BLANK PAGE)
-------
-37-
CHAPTER 4
EMISSIONS
4.1 1980 Emissions Inventory Development
~~ ri*- J A f^' ^eQL<~'~OQ ~~ CV"*OQQC ~fT'3~~onc ~ P \' s p ~ o ^' ~^x~ s a c r ~o^-'~ 2 ~ "^ u ' 3 °^ ~ c..
soeciated into the hydrocarbon classes used in the Carbon Bond II Chemica1
mecnanism. Since each state covered by the modeling domain has a di^fe^er.t
emissions inventory system, a new emissions data management system was required
to me^ge these data into a form compatible with UAM. To assist in this task,
NYSDEC contracted with Engineering Science (ES), Fairfax, VA for the installa-
tion of computer coaes required for this purpose. ES had ceveloped simi'ar
codes for the U.S. Environmental Protection Agency for the Philadelphia
metropolitan area study (USEPA, 1982).
The system of programs accepts emissions data in the format used by the
National Emission Data System (NEDS). It also makes use of modules from the
Emissions Inventory System (EIS), which provides emissions calculation
procedures. These procedures allow a user to estimate emissions using process
rates or activity levels and emission factors. The emission factors are stored
in a user-maintained table which is arranged by Source Classification Code (SCC)
and pollutant identification number.
The installed system provides tne means 1:0 cisaggregate annual emission
estimates to an hourly basis using specific or typical operating schedules, and
to speciate total hydrocarbons into several classes depending on the composition
of emissions from the source category (see Appendix A). After performing these
calculations, the system formats the data to the specifications of UAM.
sources: major and minor point sources, area sources, and mobile sources.
Major and minor point sources are those sources which emit significant amounts
from smokestacks or other readily identifiable emission points and for wnich
detailed operating data are available. Area sources include residential
emissions and others which are too small and too numerous to handle
individually. Mobile sources are generally considered to be motor vehicles on
established roadways.
-------
-38-
In this study, major point sources were defined as those with annual
emissions greater than 100 tons and a stack height greater than 65 meters and
the remaining were classified as minor point sources and are individually
formatted by the system. However, minor point sources falling within a gr:>d
were comoined aue to the computational limitations imposed by DAM moael . Area
source emissions we-^e calculated and maintained seoa^ately for UD re 5^ source
catego^'ei anc corno^nec w'tnin eacr c^ic c~~". M.oc~'"e source eirrss'ons a-~~
generally tabulated by grid cell. The installed system handles all four source
categories and oe^forms the necessary combinations. In addition, other modules
have been provided for the conversion of data from NEDS to EIS format,
allocation of county-level area source data to the grid cell level and for
calculation of area source emissions. Figure 4.1 illustrates schematically the
flow of aata through the system. Once the data are in the EIS ^ormat. taoles
are developed consisting of factors organized by SCC that indicate the seasonal,
aaily, and hourly variations in emission rates and proportion of the tota1
hydrocarbons into the corresponding hydrocarbon category. The program performs
a simple multiplication of the annual estimate of each pollutant and the
appropriate factors to yield 24 hourly emission rates per source. A
post-processing program takes the factored data and formats it to the
specifications of UAM. Emissions from mobile sources, which are not stored in
EIS format and which have been prepared on an hourly basis, require a separate
factoring and formatting program.
Ui". ~C rtUuS'Li i j , trie aVc.~, • au i £ Gate, d!"c 36 : GOfT, " T, tH£ C "C^Ti^t tTSt ~3
required as input to the processing programs. For example, point source aata
may be obtained more readily in the NEDS format, while the area source
activities are tabulated at the county level instead of at the grid-cell level.
For this reason, some additional computer codes were used to distribute
county-level activities to the grid cells, to calculate emission estimates based
on activity levels and emission factors, and to re-arrange the data into EIS
Thus, the EIS programs convert point and area source data in NEDS format to
EIS transactions, sort the transactions, insert emission factors into the
transactions, calculate emission estimates if requested and create or modify an
EIS master file, and create an emission factor table based on SCC.
-------
- 39 -
f COUNTV LEVEL
i AREA SOURCE
DATA and GRID
i DEFINITION
AREA SOURCE
ALLOCATION
i
GRIDDED
AREA SOURCE
DATA
NEDS FORMAT
EIS ROUTNES TO
BUILD AREA SOURCE
MASTER FILE
MASTER "ILt
MOBILE.
SOURCES
FACTORING AND
DATA PR€P
WRHED MODEL
INPUT DATA
POINT SOURCES
NEDS FORMAT
EIS ROUTINES TO
BUILD POINT SOURCE
MASTER FILE
(CJL
j MASTER FILE J * MASTER FILE |
• MAJOR PO(NT3j j MINOR POINTS
REPORTS
SUMMARIES
Figure 4.1 Overview of the Emissions Data Management System
-------
-40-
Each State was responsible for collecting and preparing the necessary data
for processing by the ES programs. A description of the procedures used for
each generating State's inventory is provided below.
4.2 Connecticut 1980 Emissions Inventory
Connecticut's available emission inventory was in NEDS format on a
state-Gesignea grid system. NEDS activity levels were summed into tne grids Dy
Connecticut Department of Environmental Protection (CTDEP) and orovidea to New
York State Department of Environmental Conservation (NYSDEC). Also provided
were the aoprcpriate emission factors based on AP-&2 (USEDA, 1984) T"or eacn
source category. ES programs are then used to process the data into DAM format,
ana in Tao'ie 4.1 emissions are listed'by 3CC category for 1980.
4.2.2 Point Sources
CTDEP provided their point source emission inventory in NEDS format. ES
programs are applied to separate major and minor sources and process the data
into proper format for DAM.
4.2.3 Mobile Sources
Connecticut mooile source emissions of VCC, CO, NC (K.g/aay> were
X
calculated using MOBILES model. NYSDEC developed factors which are applied to
daily values to convert these emissions to an hourly format. ES programs
processed these data into the proper UAM format.
4.3 New Jersey 1980 Emissions Inventory
4.3.1 Area Sources
The New Jersey Department of Environmental Protection (NJDEP) provided the
data necessary to create a UAM compatible area source emissions inventory.
Activity levels for each source category were given for each NJ county in the
-------
- 41 -
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-42-
modeling domain. Appropriate emission factors were also provided. Since most
area source emissions are based on population, the same basis wa**s used for
dividing these emissions into the modeling grid. NJDEP supplied 1980 U.S.
Census population data for each murncioality and the oercentage of the
municipality located in each grid. Factors were tnen developed to apportion
tcta" county emissions into eacr gric. lf a grid contained emissions ^rom one
or more counties anchor states, tne emissions were comoinec aur'ing a ",ate^
processing operation. The ES programs were applied and in Table 4.2 are
summarized the area source emissions for 1980 by SCC category.
4.3.2 Point Sources
New Jersey's point source data were in a format that could not ^eadily be
converted to the EIS format. Therefore, it was determined that an emission
inventory prepared for tne NECRMP was compatiole with tne ES programs, using
this NECRMP inventory, the ES programs were applied to separate major and minor
sources and the data was processed into proper UAM format.
4.3.3 Mobile Sources
NJDEP provided mobile source VOC emissions (kg/day) using MOBILES, for each
county ir the modeling region. Utilizing the population distribution, these
county-wide emissions were allocated to the corresponding grids using the ES
prog-ami. Emissions of NC ana CC were then octainee b\, scaling tnese VCC aata
using composite emission factors (g/mile) for each of these pollutants. NVSDEC
developed factors which were applied to daily values to create hourly emission
levels. Once on a gridded basis, ES programs processed the mobile emissions
into the UAM format.
4 . £ New York 1980 Emissions Inventory
4.4.1 Area Sources
NYSDEC developed the data necessary to use the ES programs for creating
their area source emission inventory in UAM format. Activity "levels for each
source category were determined for each NY county in the modeling region.
Aopropriate emission factors were also assembled.
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As with the New Jersey data, population was used as the basis to distribute
most county level emissions to the modeling grids. Two source categories were
deemed to have more appropriate methods of disaggregation - Vessels and Aircraft
emissions. Vessel emissions are v>estricted to waterways in each county and
aircraft emissions a^e limited to tnose grids which contained airports.
I^idividua1 c'^oort activity "eve's oota^nec '^om tne New Yc1"" Metrcoo1 ~ tar
'-ansDortatior, Counc' '. ' NYMTC ; are usec oC prooortion tne counc;> errrssior -eta's
into the approoriate grids. Population for each grid was calculated from 1980
US Census data. NYMTC orovided this data at 1 km grids for most New Yort:
counties which are then summed into the appropriate UAM grids. NYMTC had no
data for Sullivan and Ulster counties so the procedure which New Jersey followed
was used to apportion those counties' emissions to the modeling grids. The ES
orograms were applied and the 1980 area source emissions from New York are
listed in Table 4.3 by SCC category.
4.4.2 Point Sources
New York's point source data were also in a format that could not be
converted to the EIS format. Therefore, NY data had to be processed
independently and subsequently combined with that from the other states. A
search of the NYSDEC Source Management System (SMS) identified those sources
meeting the major point source criteria. Only utility boilers and one
correctional facility Doiler were classified as major point sources. All others
vv-re aesr;ieo nvino; poirri, sources for "iis s
A survey was sent to each utility requesting actual hourly electricity
generation values for the five modeling days. The five hourly values were
averaged and emissions calculated using the average 1980 heat rate (Btu/kwhr)
and aporooriate emission factors based on AP-42, unless unit specific factors
were available. Hourly emissions from the correctional facility's boiler are
Operate permit. Those hourly emissions from the major point sources were then
divided into the 'JAM species and processed into the correct format. Only NO
A
emissions are used for this exercise. VOC emissions from these boilers were
deemed negligible and not included in the model.
-------
- 45 -
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-------
-46-
The minor point source data required additional evaluation. Since the data
could not be processed (divided into model species by hour) by the ES programs,
NYSDEC undertook the task. The SMS tracks pollutant emissions on a chemical
basis, referenced to the Chemical Abstract Series (CAS1) identification number.
The 1980 emissions data were examined and it was determined that over 98% of the
VOC emissions in tne area were classified as one of 35 distinct ool H'tants.
-actors were aeve'iooec using tne CBII cnermca" ssec'ation for eacr, of tnese 55
pollutants. The remaining 2% of VOC emissions were assigned a default
soeciatior arrangement corresponding to that for the category Miscellaneous
Organics (CAS No. NY990-00-0). The speciation breakdown for these 35 pollutants
for the New York point source inventory is shown in Appendix A.
4.4.3 Mobile Sources
New VorK Metropolitan Transportation Council (NYMTC) provided 1980 daily
mileage estimates for each of its 60 analysis areas in the New York City
Metropolitan area. Mileage for each analysis area was given for five vehicle
types - light duty gas vehicles (LDGV), taxis, light duty gas trucks (LDGT),
heavy duty gas vehicles (HDGV), and heavy duty diesel vehicles (HDDV). For each
vehicle type, mileage was given for three roadway types - freeway, arterial and
local streets. Percentage hot/cold starts were also included for each roadway
type by analysis area.
Trie assignment moae'i tnat generated tne aoove data computes tne venicle
type aistrioution ana percentage not/cold starts on a county-wioe basis. A
review of these data, including comparisons of MOBILES emissions on the county
level, revealed that each borough (county) of New York City should be modeled
separately, while the suburban or surrounding counties had similar enough
characteristics to use a single MOBILES emission simulation. Also, since taxi
mileage was given for only Manhattan, Bronx, Queens and Brooklyn and taxi
the taxis separately.
Table 4.4 shows the vehicle type distribution and percentage hot/cold
starts used in the MOBILES program. The MOBILES version used by the NYSDEC
included all USEPA suggested modifications to the model up to June 1985.
-------
FREEWAY
ARTERIAL
LOCAL
1
-4"1-
ABLE 4.
Percentage of Hot/Cold Starts by
in
COUNTV
Manhattan
Bronx
Brooklyn
Queens
Staten Is
Other Co.
Manhattan
Bronx
Brooklyn
Queens
Staten Is
Other Co
Mannattan
Bronx
Brooklyn
Queens
Staten Is
Other Co.
the New
!/ Z.
L.DGV
98 . 4%
89 . 3%
O £ £a
o ~> , 3/0
90 . 5%
86 . 9%
88 . 3%
76 . 0%
89 . 3%
85 . 5%
90 . 6%
86.9%
88 . 3%
76.0%
89 . 3%
85.5%
90 . 6%
36 . 9%
O Q TV
U O . u /o
York POT
EXCLUDING
LDGT
A OO/
w . O/O
C QO/
D . O/o
7 . /%
5 . 0%
/ . 8 fa
7 . 8%
8.2%
5 . 8%
7.7%
5 . 0%
T no/
/ . u /o
~7 no/
i . O/o
3 . 2%
5.8%
7 . 7%
5 . 0%
7 . 8%
7 . 8%
ior of
r I t~ f-
HDGV
0.6%
3 . 7%
4 . 8%
-"* 1 O/
O . -t. /o
4 . 3%
2 . 6%
10 . 4%
3 . 7%
4 . 8%
3 . 1%
n no/
H . o/o
2.6%
10.4%
3 . 7%
4 . 8%
3 . 1%
A . 3%
2 . 6%
4
Vehicle
the Mode"
«. 2 b . i. J K
TAXIS
HDDV
0 . 2%
1 OO'
2.0/0
•}0/
1.0%
1 . 3%
5.4%
1 . 2%
2.0%
1 . 3%
1 . 0%
1.3%
5 . 4%
1 . 2%
2 . 0%
1 . 3%
1 . 0%
1 . 3%
Type and Roadway
ino Domair
NON-CAT
v -,<>,
6. 5%
/ . J/o
™< . ^ ;o
C DO/
S . 3 /o
5.9%
23 . 5%
12.9%
14 . 0%
11.0%
" 1 7"'
J. 1 . I/O
12.0%
44 . 1%
25.9%
30 . 0%
22 . 0%
23 . 3%
23.5%
. -
CA
"' HO"
6 . 0%
2 . 8%
-* . L. /O
W . J./0
3 . 8%
6.4%
12 . 0%
5 . 5%
8.5%
6.3%
7 CO/
. b/o
11.0%
22 . 7%
11.1%
17.0%
12.5%
15.1%
25.8%
-,-
i nL /2T
1 C O0/n
o fl °'
9.1%
, . — /o
7.5%
7 . 7%
30 . 5%
16.8%
18.2%
14.3%
15.2%
14.9%
57.4%
33 . 6%
36.3%
28 . 5%
30.2%
30.6%
-------
-48-
Typical speed scenarios were developed for rush hours, daytime, and
nighttime for the three roadway categories. These are listed in Table 4.5. The
data used in the analysis were obtained from the reports published by the NYS
Deoartment of Transoortation which orovided the hourly percentage of traffic for
15 locations within New York City as well as reports from othe1" "local agencies.
The d">st*"iout"1 or, of total VMT ^or the tn^ee "oaaway tyoe catego^es a^e ""stec
in Taole 4.6.
Hourly emissions for each grid we^e ther comouted by summing fo^ each
roadway type the appropriate emission factor times the daily mileage of each
analysis area within the grid, multiolied by the hour"iy percent of traffic and
the percentage of the analysis area in the grid. The appropriate emission
factor denended on the time of day (night, rush nours. in-oetween) and county
(Manhattan, Rest of NYC) which in turn determined the speed, percentages of
not/co id start and the vemcle mix.
4.5 1980 Emissions for the Modeling Domain - Summary
The annual VOC and NO emissions from the three states are summarized in
A
Table 4.7 for the four source categories. These emissions were further
disaggregated as listed in Table 4.8, in g-moles on a daily basis (0400 to 2000
hours), and in terms of CBII species assuming the carbon ratios of 1,2,1,6 and 2
for Paraffins. Olefins, Carbonyls, Aromatics and Ethylenes, respectively. On a
3b;"-centaqe oasis trie moo lie sources contrioute aooiit oC% OT tne i\io Duraen ana
approximately 45% of tne VOC's for a typical day covering the nours of
simulation for the base year 1980. The next important contribution to NO and
VOC's are the area sources, with approximately 28% and 44%, respectively.
4.6 1988 Emissions Inventory
control strategies proposed in the approved 1982 SIPs and projected changes in
population levels. Utilizing the U.S. Census data, the area source projection
-------
-49-
TABLE 4.5
Assumed Vehicle Speeds (MPH) by Roadway Type
AREA
Manhattan
Resu of
New York City
Other
Counties
fo1" New Yo>"k Portion
TIME
Rush Hours
In Between
Nights
Rush Hours
y In Between
Nights
Rush Hours
In Between
Nights
of the Model ino
FREEWAY
20
4C
55
35
45
55
45
55
55
Domain
ARTERIAL
10
30
45
25
35
45
35
45
45
.GCAL
5
25
35
15
25
35
25
35
35
Rush Hours are: 7, 8, 9 AM & 3 PM to 7 PM
In between hrs are: 10 Ai\ zo 3 Pf'i
Nignt Time Hours are: 7 Pl^i to 7 AM
-------
rlCUF.
C.5°c
0.5%
0.5%
4 0.6% 0.7% 0.6%
5 0.7% 1.3% 0.9%
2.3%
-50-
TABLE 4.6
(ourly Percentage of Total
Travelled bv Roadwav Tvoe
rREEWA" ART
0.4%
0 . 4%
0 . 4%
0 . 6%
0 . 7%
2 . 2%
7 . 5%
10.1%
6 . 2%
5.1%
5.2%
5.4%
5 . 4%
5 . 8%
673''
. / /a
c re
£.9%
6.1%
4 . 2%
3 . 1%
2 . 4%
2 . 0%
Vehicle Mile:
for New York
L T^ - r* i_
0 . 5%
0 . 5%
0 . 5%
0 . 7%
1 ID/
_ . 0/0
3 . 8%
£ ~°'
u . u/o
6 . 3%
5.3%
5 . 2%
5.4%
5.7%
5.7%
6 . 2%
7 . 1%
o ^n.'
C . w ,'C
C Of"
o . 0 /c.
6 . 0%
4 . 7%
3.7%
3.0%
2 . 4%
8 10.1% 6.3% 6.2%
9 6.2% 5.3% 5.3%
10 5.1% 5.2% 5.5%
11 5.2% 5.4% 6.3%
12 5.4% 5.7% 6.9%
1 PM 5.4% 5.7% 6.8%
2 5.8% 6.2% 7.0%
3 6.7% 7.1% 7.4%
6 6.1% 6.0% 5.7%
7 4.2% 4.7% 4.7%
8 3.1% 3.7% 3.7%
9 2.4% 3.0% 2.8%
10 2.0% 2.4% 2.3%
12 1.0% 1.2% 1.1%
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-53-
factors from 1980 to 1988 for each county were calculated and are listed in
Table 4.9 for the three states. One exception to this method is the category of
gasoline marketing. In the case of New York and Connecticut, the 1982 SIP
regulations reauire the implementation of Stage II vaoor recovery for 1988.
Since such controls were already in place for New Jersey, they were accounted
•""or ir 1980 base year emissions for New Jersey.
-.6.1 Area Sources
Applying the factors listed in Table 4.9 to the 1980 area source inventory,
orojected VOC and NO emissions were calculated for 1988 and are listed ^r
X
Tables 4.10a through 4.10d for Connecticut, New Jersey, New York, and the
•nodeling region respectively.
4.6.2 Point Sources
The 1988 point source emissions were projected based upon control
regulations expected to be in effect prior to 1988. Since the majority of the
major point sources are mainly utility boilers, emission levels are not expected
to change significantly from these sources. However, Connecticut expects the
addition of several resource recovery facilities which will result in a slight
ircrease in emissions under this category.
ociuStantia" emission reauctior.s are expectea, however, from tne minor point
sources. Connecticut proviaea a 1985 inventory in tne format required oy tne
processing programs. It was considered by CTDEP to represent the emission
levels expected to occur in 1988. Therefore, no projection factors were
required for this 'data.
NJDEP utilized the 1930 emission inventory summary by SCC code and
degree of control expected. These factors were then used to project the 1980
inventory to 1988. A similar approach was adopted to project the New York minor
source emissions.
-------
-54-
TABLE 4.9
Area Source Projection Factors
From 1980 to 1988
Connect!cut
New Jersey
0265
0425
0478
0565
0705
0725
1155
1505
0300
1380
2240
2260
2980
3060
3180
3260
4120
5020
5300
5440
Fairfield
hartforc
Litchfield
Middlesex
New Haven
New London
Tol1 ana
Windham
Bergen
Essex
Hudson
Hunterdon
Mercer
Middlesex
Monmouth
Morris
Passaic
Somerset
Sussex
Union
1.0374
1.0412
1.0383
1.0711
1.0231
1.0429
1.0616
1.05016
0.95753
0.97093
1.11740
,06696
,10821
,06759
1.10174
0.99778
1.15925
1.23865
1.01167
0600
1620
3440
4520
4660
5140
5640
5660
5720
6580
6600
6840
7320
Bronx
Dutchess
Kings
Nassau
New York
Orange
Putnam
Queens
Richmond
~, ~ ~ • ~ V-, ^
Suffolk
Sul1ivan
Ulster
Westchester
,0180
.0761
.0015
1.0119
0177
1006
0888
0127
1.0949
1.35S1
1.0636
1.0606
1.0517
1.0054
-------
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-59-
4.6.3 Mobile Sources
New Jersey and Connecticut provided 1988 mobile emissions determined by
using MOBILES with uodated VMT (vehicle miles travelled) data and emission
factors. New York's 1982 SIP assumed a 2% annual growth rate to project future
years' mileage. The actual annual growth rate through 1985 by county, listec in
~ac>~ e ~.-~. /vas 2.Ccc wmcr, /vas aaootea "c oroject ~ne 1982 "eve ;.
In summary, the projected 198S annual emissions for VOC and NC., by source
type and region are listed in Table 4.12a and in Table 4.12b, along with tne
soeciated emissions summary for the model application. The percentage change
from the 1980 base year (see Table 4.12a) shows that there is an overall
reduction of about 32% and 14% in "the VCC's and NO emissions, respectively.
A
4.7 1988 Emissions Inventory Including Extraordinary Measures
The 1988 projection inventory included only those control strategies that
are implemented to date. Other SIP mandated measures such as Stage II gasoline
vapor recovery, controls on architectural surface coating, automobile
refinishing and consumer/commercial solvent and small source RACT have not been
fully implemented. Thus, each of these measures are assessed separately and
collectively. In Table 4.13a are listed the emission summaries by state and
source type with the imposition of Stage II controls which has effectively
achieved anotner 2« reduction in tne v/OC emissions. «aoption of the otner
control measures noted earlier would result in a furtner reduction of aoout 6>0
in the VOC emissions (see Table 4.13b) or a total reduction of 40% from the 1980
base year.
-------
-60-
TABLE 4.11
Projected Annual Growth Rate
Por New
COUN'Y
Manhattan
Bronx
Brookl yn
Queens
Staten Is
Nassau
Suffolk
Westch.
Rockland
Putnam
Dutchess
Orange
York Portion
1980-1985
INCR
10.7%
SOD'
. o /o
'9 . 4%
10.8%
19 . 5%
8 . 5%
15.9%
10.5%
12.5%
21.6%
16.9%
12.2%
NEW YORK
of the Modelino
GROWTH
RATE
2.1%
1 . 6%
1 . 8%
2 . 1%
3 . 6%
1.6%
3 . 0%
2.0%
2.4%
4 . 0%
3.2%
2.3%
CITY
OTHER COUNTIES
in Vehicle Miles
Domain from 1980
ANNUAL
1980-1988
INCP
17.7%
13.6%
15.5%
nQO/
. O/O
33 . 0%
23 . 9%
26 . 6%
17.3%
20.7%
36 . 7%
28 . 4%
20.2%
80-88
INCR
18 . 6%
19.7%
to 1988
GROWTH
RATE
2 . 1%
1 . 6%
- no/
1 . O,o
2 . 1%
3.6%
1 . 6%
3 . 0%
2.0%
2.4%
4 . 0%
3 . 2%
2.3%
GRGw'Th
RATE
2 . 2%
2 . 3%
COMBINED
19.3%
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-------
-65-
CHAPTER 5
MODEL APPLICATION
cor each of the five days selected, a simulation package conforming to tne
^A"'' 'note: "sq;^ "sments I'JSE^A: ^9855.. 1935b, !,Nas oreoarec ~:r ~r>9 .3 icur
simulation oeriod (0400 to 2000 Mrs; using the methodologies described in
Chanter 3. The detailed descriptions o* the input data for eacn day a^e given
below.
5.1 Input Data for JD80198(071680) Simulation
On the synoptic scale weatner map for this day, shown in Figure 5.la. ~ne
"Bermuda1' type high pressure area extenaea from the Atlantic Ocean westward
through the southern states. A cold front lay from the Canadian Maritimes
west-southwestward to western Lake Erie, where it became a warm front; the
latter turned west-northwestward into western Wisconsin, where an occluded-cold
frontal structure ran nearly north-south. Weak low pressure was located to the
west of the Lakes, while weak high pressure was found to their east.
The hourly vector-averaged wind speeds and directions for this day are
listed in Table 5.1. The winds were generally from the south-southwest around 4
to 5 m/s. Tne other meteorological parameters are listed in Taoles 5.Z ana 5.5.
Tne mixing neignt reacnea a maximum of 1460 m. The pollutant gradients in tne
vertical and the concentrations at the top of the modeling region are listed in
Table 5.4. The initial surface distributions of the pollutants are shown in
Figure 5.2. The hourly highest and second highest measured ozone concentrations
are listed in Table 5.5. A peak value of 291 ppb occurred over Connecticut.
The diurnal variation of the pollutant concentrations in the southwest corner
-------
- 66 -
SURFACE WEATHER MAP
T'OOAMES.T
(016 1012
1020
4020
. SURFACE WEATHER MAP
Aujutt 6.1960 7.00AM E.ST
SURFACE WEATHER MAP
August8.198O 7>OOAM£ST
Figure 5.1 Synoptic Weather Map at 0700 Hrs. for Each of the Five Simulation Days
-------
-67-
TABLE 5.1
Vector-Averaged Hourly Winds for JD80198(071680) Simulation
HOUR
0400 -
0500 -
0600 -
0700 -
0300 -
0900 -
1000 -
1100 -
1200 -
1300 -
1400 -
1500 -
1600 -
1700 -
1800 -
1900 -
0500
Q60C
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
WIND SPEED
'm/s)
3.93
4.63
3.79
4.07
4.40
4. 59
^.72
4.71
4.24
4.75
4.76
5.30
4.88
5.17
4.51
4.23
WIND DIRECTION
(°)
230
99C
t-i_ ~j
225
227
231
ni •?
i-^ L.
O O ^
c-OO
225
231
234
239
232
246
232
219
200
-------
-68-
TABLE 5.2
Hourly Diffusion Break (Mixing Height), Region and Vertical Cell Top
Heights for JD80198(071680) Simulation
DIFFUSION BREAK
HOUR
0400
0500
0600
0700
0800
0900
1000
J-J-wU
1200
1300
1400
1500
1600
1700
1800
1900
- 0500
- 0600
- 0700
- 0800
- 090C
- 1000
- 1100
• J.CUU
- 1300
- 1400
- 1500
- 1600
- 1700
- 1800
- 1900
- 2000
!TT1)
450
450
450
450
450
525
630
765
1145
1400
1460
1460
1460
1250
1060
900
REGION TOP
•V
1000
1000
1000
1000
1000
1025
1100
IZG5
1295
1400
1460
1460
1460
1460
1460
1460
TOP OF CELL
3
450
£50
450
450
450
525
600
/U j
795
900
960
960
960
900
855
795
2
300
300
300
300
300
350
400
t / U
530
600
640
640
640
600
570
530
(m)
i
150
150
150
150
150
j. / C
200
(L~ 3
265
300
320
320
320
300
285
265
-------
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-------
-70-
TABLE 5.4
Pollutant Gradients in the Vertical and Concentrations at the Top
of the Modeling Region for JD80198(071680)
Do~ -utant
Gradient
Concentration at the Top
of the Mode1-;nc Rec4or
0.
NU
NMHC*
CO
5.62
-4.19
-34.66
-50.00
85
r
30
?r
''ppDc/lOO
Table 5.5
Hourly Highest and Second Highest Ozone Concentrations
HOUR
1200 - 1300
1300 - 1400
1400 - 1500
1500 - 1600
1500 - 1700
1700 - 1800
Measured on 0080198(071680)
HIGHEST
CONCENTRATION
(OOD )
210
280*
291**
274
265
230
157
STATION
New Haven
Stratford
New Haven
Stratford
Hartford
Middl etown
;•. " QG i S'CCWf .
2nd HIGHEST
CONCENTRATION
(ppo)
183
252
291*
260
262
170
^ t
STATION
'Greenwich
Derby
Derby
Hartford
Mi ddl etown
Hartford
„ w C. w 1 ^ "-4
*
**
Highest for the day
Second hignest for the day
-------
IMTlAt SURFACE DISTRIBUTION OP OZONE
FOR J08CM96 (071680)
SURFACE DISTRIBUTION OF
FOR JDBO198 (071680)
MTUl. SURFACE DISTRIBUTION OF MUHC
~0ft J08CH98 1071680)
*0 (8 tO
X-AXIS
iMTUL SURFACE DISTRBUTON OF CO
FOR J080198 (071680)
Figure 5.2 Initial Pollutant Distribution on JD&0198 (071680)
-------
— <4O -i
OZONE
J
NO,
i 120-
O 100-
^^
<
CC 80'
1-
g 60-
0
-9
o ^®~
o
20-
*•*
30-
o
25-
0 20-
0
IS-
C'
-------
-73-
5.2 Input Data for JD802Q3(Q72180)
Examination of the daily surface weather map in terms of large-scale
synoptic features, shown in Pigure 5.1b. reveals that a "Bermuda high" extended
westward to the soutnern Miawest. A warm front, with waves of low pressure on
i~, ran nearly east-west f^om Maine to well north of _aKe Ontario, wne^e a co'c
"•-cr.t "an 3ou~nwarc tner 3ou~nwes~i'
-------
-74-
TABLE 5.6
Vector-Averaged Hourly Winds for JD80203(072180) Simulation
HOUR
0400 -
0500 -
0600 -
0700 -
0800 -
0900 -
1000 -
1100 -
1200 -
1300 -
1400 -
1500 -
1600 -
1700 -
1800 -
1900 -
0500
0600
0700
0800
0900
1000
1100
1ZOG
1300
1400
1500
1600
1700
1800
1900
2000
WIND SPEED
:>,''$ 1
3.67
2.84
4.19
4. 07
4.24
3.46
3.92
4.36
4.33
4.58
4.95
5.07
5.13
5.13
5.08
4.72
WIND DIRECTION
' o >,
232
239
244
235
244
240
238
233 '
232
227
222
205
204
199
206
217
-------
-75-
TABLE 5.7
Hourly Diffusion Break (Mixing Height), Region and Vertical Cell Top Heights
for JD80203(072180) Simulation
0400
Q50C
0600
0700
0800
0400
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
HOUR
- 0500
- 06CC
- 0700
- 080C
- 0900
- 1000
- 1100
- 1200
- 1300
- 1400
- 1500
- 1600
- 1700
- 1800
- 1900
- 2000
DIFFUSION BREAK
(m)
285
30C
360
445
570
660
710
8*0
1195
1535
1670
1805
1895
1850
1500
960
REGION TOP
(m)
1000
1000
1000
1030
1110
1160
1160
1250
1370
1535
1670
1805
1895
1895
1895
1895
TOP
3
235
300
360
"135
570
660
560
750
870
1035
1170
1305
1395
1395
1395
960
OF CELL
2
190
200
240
290
380
4dQ
i40
750
580
690
780
870
930
930
930
640
(m)
1
95
100
120
145
190
220
1 1 n
250
290
345
390
435
465
465
465
320
-------
- 76 -
ct:
111
x
Q.
oo
O
in
CM
o
0
o
on
o
0
LO
oo
0
o
r—
ro
o
o
00
CO
o
o
oo
00
0
o
<— 1
01
CM
o
o
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ro
m
o
o
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o
CO
0
o
1 — 1
IT)
CM
O
O
T— <
r— 1
CM
0
0
•=f
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3
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cn
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m
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o o
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o o
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o o
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o
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o
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I
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CM
I
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o
en
-------
IMTUL SURFACE CXSTR18UTIC* OF OZONE
POP JD80203 <072«80J
INITIAL SURFACE DISTRIBUTION OF NO?
7
JD8C205 (072160;
to tj »o zi
X-AXIS
IMTIAL SURFACE DISTRIBUTION OF NUHC
FOR J080203 (072180)
to « to zs
X-AXIS
IMTIAL SURFACE DISTRIBUTION OF CO
FOR JD60203 (072180)
Figure 5.4 Initial Pollutant Distribution on JD80203(072180)
-------
-78-
TABLE 5.9
Pollutant Gradients in the Vertical and Concentrations at the
Top of the Modeling Region for JD80203(072180)
utar.t
NMHC*
Gradient
'POD '100m''
7.42
-5.4/1
-11.72
-50.0
Concentration at the TOD
or the ^"'oce" ~'nc Rsc4
50
20
*DDDC/100 HI
TABLE 5.10
Hourly Highest and Second Highest Ozone Concentrations Measured
1200 -
1300 -
1400 -
1500 -
1600 -
>ur\ Cu
1300
1400
1500
1600
1700
HIGHEST
NCEmRATIGK
(ppb)
230
227
240
303*
235
on JD80203(072180)
2nd HIGHEST
STATION
Derby
Stony Brook
Stony Brook
Stratford
New Haven
CONCEN i RA i
(PPD)
202
224
229
195
224
ION STA i I0i\i
Hempstead
Stratford
Stratford
Middl etown
Stratford
1800 - 1900 200 Middletown
* Highest for the day
Second highest for the day
**
185
Hartford
-------
- 79 -
2001 OZONE
180 4 ° 45-
^ o
02 160-1 40-
fc 1
— 440 i 35-
-, ' c
£T 1OO-
~
Ui 80 -
z
o 6°-
u
40-
20 -
0
450 -
-~ 400-
03
Q.
S 350-
O 300-
K 250-
m 200 -
CJ
O * 5C~
'00-
"1
0 0
0 c ~ 25-
G
o
O 45-
1°-
o
o
IVU£
O C
0 0
0 0
° 000000°
o
o
2 4 6 8 10 12 14 16 16 20 2 4 6 8 10 12 14 16 18 20
NMHC °
0
1600-
O
0 o o ° o 0 1400'
0 O o 1200-
0 ° 1000-
O
800-
600-
400-
200-
CO
0 O
0 0
0 0
o o o o
o o o o
0 0
24 6 8 10 12 14 16 18 20
TIME (E.S.T.)
2 4 6 8 10 12 14 16 . 18 20
TIME (E.S.T.)
?iurri£l Plot of CbFerved Pel
Corner Grid on JD8C2G2^CT2IS1
lutar.t Concentrations at the Southwest
-------
-80-
TABLE 5.11
Vector-Averaged Hourly Winds for JD80204(072280) Simulation
HOUR
3COO -
0500 -
0600 -
0700 -
0800 -
0900 -
1000 -
1100 -
1200 -
1300 -
1400 -
1500 -
1600 -
1700 -
1800 -
1900 -
G50G
0600
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
WIND SPEED
(m/s)
3 . 51
3.37
3.21
3.62
3.98
3.96
4.62
4.43
4.52
4.69
5.66
5.51
5.48
5.66
5.23
4.60
WIND DIRECTION
(°)
225
236
238
246
227
235
227
224
233
220
217
216
214
219
221
-------
-81-
TABLE 5.12
Hourly Diffusion Break (Mixing Height), Region and Vertical Cell
HOI
0400 -
0500 -
0600 -
0700 -
csoc -
0900 -
1000 -
1100 -
1200 -
1300 -
1400 -
1500 -
1600 -
1700 -
1800 -
1900 -
T
JR
0500
0600
0700
0800
C90C
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
op Heights for
_> " " ' v * • | * "" X r ~\ » %
(m)
315
405
555
705
O' n
870
950
1040
1180
1400
1595
1625
1625
1550
1360
1180
0080204(072280)
r cr ?, ' ' ' ~~ ^ Q
(m)
1000
1000
1100
1205
i T 1 n
1370
1370
1385
1430
1475
1595
1625
1625
1625
1625
1625
Simulatioi
3
315
405
555
705
m <~\
870
870
885
930
975
1095
1125
1125
1125
1125
1125
n
~j T " 'T
2
210
270
370
d7Q
"" 1 ^
~ i 1 j
580
580
590
620
650
730
750
750
750
750
750
105
135
185
70 c;
_ _ ,
290
290
295
310
325
365
375
375
375
375
325
-------
- 82 -
o: <
a.
00
O
a:
a.
i—(r—It—I C\J i-H r—It—Ir—I O CT> CO P- I (~- P--
oococococooooococor--r~-r~r^r-r~i^-
cn cr> cji cr> cn en oS cr> CP o*> cj> o^ cr>
oooooooooooooooo
(TS
3
I— O
< a.
o: -=C
LU ce
O —*UDijDr~~
CO
in
LU
—I
CQ
C\J
CM
o
CM
O
CO
Q
i.
O
s_
O)
-(J
LU
00 Q
O Z
Q. 1—1
X
LU
OO>— I «-H
CMCNJCMCM
•— IOOO'— I
o
CQ
i — cocncncD
OOC3OOOOOOOOOOOOO
OOOOOOOOOCDOOOOOO
I I I I I I I I I I
< o
ae _i
LU LU
a. CQ
LU
o >— i I-H
oooooo-— i <— i i— i— -i >— i >— ior— oooiO'-HCMn'^-ur)tDp--ooai
O O O O O O i—t <—* i—t '—I «--* '—' '—I i—I i—! i—t
-------
- 83 -
MTUL. SURFACE DISTRIBUTION OF OZONE
FOR J080204 (072280)
IMTIAL SURFACE DISTRIBUTION OF NO?
FOR J060204 (072280)
18 ' ' ' ' tb ' ' ' ' IS ' ' ' ' *0 » S "to ' ' ' '
-------
-84-
TABLE 5.14
Pollutant Gradients in the Vertical and Concentrations at the
Top of the Modeling Region for JD8Q204(07228Q)
Gradient
NO,
NMHC*
CO
9.43
-6.04
-43.36
-50.0
Concentration at the top
of "".ns ^ode'^na Reoion f'
60
5
30
20
*ppbc/100 rn
TABLE 5.15
Hourly Highest and Second Highest Ozone Concentrations
HOUR
1200 - 1300
1300 - 1400
1400 - 1500
1500 - 1600
1600 - 1700
1700 - 1800
1300 - 1900
*
**
Measured on 0080204(072280)
HIGHEST
CONCENTRATION
(ppb)
168
218
227**
220
240*
160
148
STATION
Stratford
Stratford
New Haven
Middletown
Hartford
Hartford
L-' ncnf ie id
2nd HIGHEST
CONCENTRATION
(ppb)
139
200
226
212
150
143
113
STATION
Derby
New Haven
Stratford
Hartford
Middl etown
iJtcnf iel d
Susan Waaner
Highest for the day
Second highest for the day
-------
-85-
The highest and second highest measured hourly ozone concentrations for
this day, listed in Table 5.15, indicate a maximum of 240 ppb at Hartford,
Connecticut with concentrations in excess of 200 ppb at other locations over
Connecticut. The concentrations adopted for the pollutants at the southwest
boundary cell are shown in Figure 5.7.
5.4 Input Data for JD80219(080680)
On this day the synoptic situation, shown in Figure 5.Id, is slightly
different from the previous cases. A break-off extension of the "Bermuda" high
was centered over West Virginia. A frontal zone was draped north of the border
to a low pressure near James Bay.-
The vector-averaged hourly winds are listed in Table 5.16, with speeds
ranging from about 3 to 5 m/s from a south-southwest to southwesterly direction.
The other input meteorological parameters are listed in Tables 5.17 and 5.18.
The pollutant gradients and the concentration at the top of the modeling region
are listed in Table 5.19. The initial surface distributions of the pollutants
for the simulation day are shown in Figure 5.8. The highest and second highest
measured hourly ozone concentrations are listed in Table 5.20 with the highest
value of 249 ppb. The hourly boundary concentrations for the southwest corner
grid are shown in Figure 5.9 to provide an example of the typical values used in
this simulation.
5.5 Input Data for JD80221(080880)
The synoptic weather pattern for this day, shown in Figure 5.1e, consists
3f a aouoi e-structured 'Bermuda'1 mgn with canters over :he Atlantic ana ,'i'est
Virginia. A frontal system arched across the northern part of the country. A
high pressure center was found over James Bay, with a weak low pressure on the
stationary portion of the front over Lake Superior.
-------
- 86 -
100-
90-
a.
"T 70-
^^
o
K 60-
CC
t- 50-
Ul „„
O 40-
Z
8 30-
20-
10-
0
400-
s^
CD
«: 300-
*^
*™^
2
O
^ 200-
0:
l-
2
LU
g 100-
o
o
OZONE
o ° . .- i N0?
O O 45 1 £•
o !
o
35-
o
o
30-
o 25-
o 20-
15-
C, ^Q.
o
o
5-
2 4 6 8 (0 12 14 16 18 2O
NMHC
1600-
O 00 1400-
° 0 ° 1200-
O O 0
n (00°"
O
O
00 800-
O
600-
O
400-
200-
0 0
O
o
0 -. 0
0 O
C 0 0 0 O 0
246 8 10 12 14 16 18 20
CO
o
o
o o o
o o o
o
o
o o o
o
o
o
2 4 6 3 10 12 14 16 18 20
TiME (E.S.T)
4 6 d 10 12 14 16 18 20
TiME (E.S.T.)
Figure 5.7 Diurnal Plot of Observed Pollutant Concentrations at the
Southwest Corner Grid on JD80204(072280)
-------
-87-
TABLE 5.16
Vector-Averaged Hourly Winds for JD80219(08Q680) Simulation
HOUR
0400 -
0500 -
0600 -
0700 -
0800 -
0100 -
1GOG -
1100 -
1200 -
1300 -
1400 -
1500 -
1600 -
1700 -
1800 -
1900 -
0500
0600
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
WIND SPEED
(m/s)
3.47
2.80
3.51
3.42
2.91
2.79
2.13.
3.73
3.27
3.71
4.10
4.51
4.97
4.41
3.96
3.59
WIND DIRECTION
(°)
218
225
259
260
231
234
so •*, *-t
237
220
234
234
239
238
231
247
251
-------
-88-
TABLE 5.17
Hourly Diffusion Break (Mixing Height), Region and Vertical Cell Top
Heights for 0080219(080680) Simulation
0400
0500
0600
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
rtOuR
- 0500
- 0600
- 0700
- 0800
- 0900
- 1000
- iico
- 1200
- 1300
- 1400
- 1500
- 1600
- 1700
- 1800
- 1900
- 2000
DIFFUSION BREAK
\vi
120
165
225
315
450
600
750
945
1145
1240
1240
1240
1240
1110
920
800
REGION TOP
.01 ,
1000
1000
1000
1000
1000
1050
1105
1150
1195
1240
1240
1240
1240
1240
1240
1240
TOP
•^
120
165
225
315
450
600
705
750
795
840 •
840
840
840
795
750
720
OF CELL
£
30
110
150
210
300
400
470
500
530
560
560
560
560
530
500
480
...
40
55
75
105
150
200
235
250
265
280
280
280
280
265
250
240
-------
- 89 -
ae. —I
un
ca
<:
01
co
to
a
co
o
cn
T—I
CM
O
co
a
to
i.
0)
4-)
a>
tT3
5-
m
Q.
3
Q.
rO
rO
00
00
o
CO
O
o
1
QC
•=)
O
O O O CD
O O O O
m 10 r- co
o o o o
i i i i
o o o o
o o o o o
un
o
to
o
O CD O
o o o
cn o <-<
O t—I t—I
I I
o o
o
o o o o o
o o o o o
oj oo «s" m 10
o o
o o
r-- co
co
o
01
0
1
O
o
o
1
o
0
1
o
o
CM
1
o
o
oo
i
o
o
1
CO
o
in
1
0
O
-.0
o
o
o o
o o
en o
<—( CM
I I
O O
o o
CO cn
-------
-90-
TABLE 5.19
Pollutant Gradients in the Vertical and Concentrations at the Too
of
Pollutant
°3
N02
NMHC*
CO
the Modeling Region
Gradient
(oDb/lQQm)
3.70
-1.73
-14.82
-50.00
for JD80219(080680)
Concentration at
of the Model i na
iPPQj
65
2
30
20
the Top
Reai on
*pobc/100 m
TABLE 5.20
Hourly Highest and Second Highest Ozone Concentrations
HOUR
1200 - 1300
1300 - 1400
1400 - 1500
1500 - 1500
1500 - 1700
1700 - 1300
1800 - 1900
*
**
Measured on JD80219(080680)
HIGHEST
CONCENTRATION
234
249*
220**
217
201
206
168
STATION
Stratford
Stratford
Stratford
Derby
Ctrarfora
Stratford
Stratford
2nd HIGHEST
CONCENTRATION
180
182
197
190
140
137
101
STATION
Derby
Bridgeport
Derby
Gtratford
Deroy
Middletown
Middletown
Highest for the day
Second highest for the day
-------
- 91 -
INITIAL SURFACE DISTRIBUTION Of OZONE
FOR J08020 (080680)
INITIAL SURFACE DISTRIBUTION OF N02
FOR J080219 (080660)
r / s
(sJ8/ <*
15 K
X-AXIS
IMTIAL SURFACE DISTRIBUTION OF NUHC
FOR J080219 (080680)
IMTIAL SURFACE DIST»!8UT»Of OF CO
,oao«8o;
Figure 5.8 Initial Pollutant Distribution on ^80219(080680,
-------
- 92 -
so-, OZONE
- J 0 ° ° °
03
oT eo-
^ 50-
o
h-
< 40-
cc
^>_
"2 30-
LU
O
2 20-
0
1600-
^ 1400-
00
Q_
a 1200-
^"
g 1000-
< 800-
cc
2 600-
UJ
o
2 400-
O
O
200-
j ->
0 30-
o
0 25-
0
20-
o
15-
o O 10-
^ c .
-
2 4 6 8 10 12 14 16 18 20
NMHC
3200-
2800-
2400-
0
0 2000 -
0 ° 1600-
o
o 1200-
0 0
'0 800-
0 °
00 o 400-
o
N02
o o
o o _ .^
o o o o n o
o o
o
o
24 6 8 10 12 14 (6 18 20
CO
o
o
o
o
0 0
0
O O O
0 0
o
0
o
o
2 4 6 3 10 12 14 '6 18 2O
TIME(E.S.T.)
24 6 3 10 !2 14 16 f8 20
TIME (E.S.T)
Figure 5.9 Diurnal Plot of Observed Pollutant Concentrations at the
Southwest Corner Grid on JD80219(080680)
-------
-93-
The hourly vector-averaged wind speeds and directions are listed in Table
5.21. The winds were from a south-southwesterly direction, with speeds ranging
from 3.5 to 5 m/s. The other input meteorological parameters are listed in
Tables 5.22 and 5.23. The mixing height reached a maximum of 1400 m. The
pollutant gradients in the vertical are listed in Table 5.24 along with the
aistributions of the pollutants for the simulation aay are shown in Figure 5.13.
The highest and second highest measured hourly ozone concentrations are listed
in Table 5.25. The peak value was 246 ppb and exceedances of over 200 ppb are
noted for other hours. Diurnal variation of the pollutant concentrations at the
southwest corner grid are displayed in Figure 5.11.
-------
-94-
TABLE 5.21
Vector-Averaged Hourly Winds for JD80221(08088Q) Simulation
HOUR
0600 -
0500 -
0600 -
0700 -
0800 -
0900 -
1000 -
1100 -
1200 -
1300 -
1400 -
1500 -
1600 -
1700 -
1800 -
1900 -
G50G
0600
0700
0800
0900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
2000
WIND SPEED
(m/s)
3 . 53
3.48
3.77
3.24
3.67
3.82
3.99
4.57
5.26
4.80
5.09
5.63
4.49
5.11
4.48
4.84
WIND DIRECTION
(°)
227
234
241
244
231
232
237
238
233
235
236
236
234
245
239
224
-------
-95-
TABLE 5.22
Hourly Diffusion Break (Mixing Height), Region and Vertical Cell Top
Heights for JD8022K 080880) Simulation
HOUR
0400
0500
0600
0700
C300
0900
1000
1100
1200
1300
1400
1500
1600
1700
1800
1900
- 0500
- 0600
- 0700
- 0800
- T900
- 1000
- 1100
- 1200
- 1300
- 1400
- 1500
- 1600
- 1700
- 1800
- 1900
- 2000
Lr-'Ji. i-J.-i sn.c..-K
(m)
345
345
345
375
-05
450
540
700
1020
1400
1400
1400
1400
1170
940
710
(m)
1000
1000
1000
• 1000
1CCQ
1040
1100
1160
1280
1400
1400
1400
1400
1400
1400
1400
-'
3
345
345
345
375
•105
450
540
660
780
900
900
900
900
795
705
630
J ., „.:_.
-
230
230
230
250
~-7^
300
360
440
520
600
600
600
600
530
470
420
115
115
115
125
_ — C
150
ISO
220
260
300
300
300
300
265
235
210
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-97-
TABLE 5.24
Pollutant Gradients In the Vertical and Concentrations at the Top
of the Modeling Region for JD80221(08088Q)
°3
N02
NMHC*
CO
Gradient
5.69
-2.08
-25.95
-50.00
Concentration at the Top
.ppo;
70
6
30
20
*ODbc/100
TABLE 5.25
Hourly Highest and Second Highest Ozone Concentrations
HOUR
1200 - 1300
1300 - 1400
1400 - 1500
1500 - 1600
1600 - 1700
1700 - 1800
1800 - 1900
Measured on JD80221(080880)
HIGHEST
CONCENTRATION
(ppb)
213
246*
237**
236
197
160
143
STATION
Stratford
Stratford
Stratfora
Stratford
Stratford
Stratford
Stratford
2nd HIGHEST
CONCENTRATION
(ppb)
180
170
167
145
141
132
143
STATION
Greenwi ch
Bridgeport
Hr^ageoor-c
Stony Brook
Derby
Derby
Middl etown
**
Hignest for the day
Second highest for the day
-------
- 98 -
MTUL SURFACE DISTRIBUTION OF OZONE
FOR JD80221 1080880)
IMTIAi. SURFACE DISTRIBUTION OF N02
FOR JD80221 (O80880)
« K 25 JO < i tt 19 «0 It SO
SURFACE o«STj«8trr>cN CF
FOR JD8022< (080880)
FOR J08022< SOSCSaO)
I-
19 IO «•
X-AXIS
a »
Figure 5.10 Initial Pollutant Distribution on JD8022K080880)
-------
- 99 -
100-
90 -
OJ
OL 80-
Q.
O
t- 60-
N02
0 0
o
0 ° 0 0
o o
0 o o o 0 o
0 "• ' ! 1 1 1 1 ' ' u • •; - ••": • •." '• • :
2 4 6 8 10 12 14 16 18 20 2 4 6 3 10 12 '4 15 18 20
900-
^ 800-
tn
0.
Q. 700-
O 600-
| 500-
l_
Z 400-
» j
| 300-
O
200-
100-
NMHQ, Q o
0 3200 -
_ o
o
0 0 ° ° 2800-
o o 0
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2000-
1600-
1200-
800-
40O-
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0 ; i i " • • : ; 0 i : ! : i ' 1 1 '
2 4 6 8 10 12 14 16 18 20
TIME (E.5.T.:
2 4 6 8 10 12 14 16 18 20
TiME (E.5.T.:
Figure 5.11 Diurnal Plot of Observed Pollutant Concentrations at the
Southwest Corner Grid on JD8022K080880)
-------
- 100 -
(BLANK PAGE)
-------
-101-
CHAPTER 6
MODEL PERFORMANCE EVALUATION
The results of the UAM simulation for the five selected high ozone days are
tne basis of its overa,: predictive capaoiiity and its aoiiity to capture t.-.e
high concentration values through the application of various statistica1
measures recommended by the AMS workshop (Fox, 1981).
6.1 DAM Simulation of the Ozone Concentration Field for the Five Days
Us~'ig the 'node 'lout data described """! the orevious c"aota°, r>e !jAM -/as
executed to provide hourly averaged ozone concentration fields for each of tne
five days. In Figures 6.1 to 6.5 are shown the isopleths of predicted ozone con-
centrations for selected hours when concentration maxima are expected to occur
for each of the five days. One of the characteristic features of the five days
simulated is the occurrence of a double peak over the modeling domain around the
time of the occurrence of the ozone maximum with one peak over the northeastern
portion of Connecticut and the other over the border areas of northeastern
New Jersey-New York. Only in the case of J080219 (080680) was there no clearly
defined double peak. This may be due to the lower advection rate, and limited
mixing in the vertical which could result in the merger of the two peaks. Also,
in some instances, the peak concentration formed over the New Jersey-New York
region is higher than the peak occurring over the Connecticut region suggesting
a strong influence of pollutant transoort through the southern and western
Dounaaries.
5.2 Paired ^omoar-sons - All Data
It should be noted that whereas the UAM predictions represent volume-
averaged hourly concentration values (averaged over the cell volume specified in
the program], the measured concentrations are at monitoring stations ^ecresentea
by points in space. Hence, perfect agreement between measured and predicted
concentrations should be considered as fortuitous. To assess the model per-
formance, the grid point nearest to the monitoring station is located and the
oredicted concentrations at this grid point are compared with the measurements
-------
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PP8 O MOO FOR BASE-RUNi
- 102 -
10
19
10-
JD80O8 -
(O
19
X-AXIS
20 23
30
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PPB Q 1600 FOR BASE-RUN)
a-i
19-
10-
3-
JO 80198
(0
20
AREAL OtSTRI6UTCN OF OZONE
GREATER THAN 125 PP8 O 1500 FDR BASE-RUN 1
C
X-AXIS
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PPB iQ, (700 FOR BASE-RUN I
20-
vt
x
13-
10-
3-
X-AXIS
19 20
X-AXIS
Figure 6.1 Axeal Distribution of Ozone on JD8Q198<071680) from 1400 to 1700 3rs.
-------
- 103 -
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PP8 C I4OO FOR 1980 BASE-RUN 2
AREAL DISTRIBUTION OF OZONE
THAN 125 PPB c«oo FOR oso BASE-RUN 2
J0802O3
IS 20
X-AXIS
JO
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PPB C 15OO FOR 1960 BASE-RUN 2
X-AXIS
AREAL DISTRIBUTION OF OZONE
GREATER THAN ',£5 PP9 ft '700 FOR 9ASE-RUN 2
E J
-i
»-
X
4
18-
-------
- 104 -
19-
-------
AREAL DISTRIBUTION OP OZONE
GREATER THAN (25 PP8 O WOO FOR BASE-RUN4
- 105 -
JO 80219
T—r—t—r—i—i—i—r~i—r"i—i—f—i—i—T—i—'—i—T—T—!—< i i I I
9 KJ 18 » 23
X-AXIS
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PPB ft (SCO FOR BASE-RUN 4
SO
10
JO 80219
t»
X-AXIS
so
20-
15-
x
4
23
10
s-
AREAL DtSTRIBUTON OF OZONE
GREATER THAN 125 PP8 O 1500 FOR BASE-RUN 4
^080219
(0
15 20
X-AXIS
30
AREAL DISTRIBUTION OF OZONE
GREATER THAN (25 PPB fl, 1700 FOR BASE-RUN 4
1 8 M 18 20
X-AXIS
JD 80219
so
a
Figure 6.4 Areal Distribution of Ozone on JD80219(080680) from 1400 to 1700 Hrs.
-------
- 106 -
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PPB O WOO FDR BASE-RUN 5
AREAL DISTRIBUTION of OZONE
GREATER THAN (25 PP8 O I&OO FOR BASE-RUNS
29 JO
AREAL DISTRIBUTION OF OZONE
GREATER THAN (25 PP8 O t500 FOR BASE-RUNS
x
4
10
23
IS 20
X-AXIS
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PPB O
-------
-107-
from the monitoring station. Diurnal plots of the observed and predicted concen-
trations at the monitoring stations are presented in Appendix B. Several
standard statistical measures (Willmott, 1981; Fox, 1981; Rao, et al., 1985) are
computed, and the results are listed in Table 6.1. The high correlation
coefficients (r ., Ql- > 0.098) indicate that the model predictions are reason-
C I I *r • -7-J
able either when the data are considered on an individual day-by-day basis or on
an ensamc'is cas'3. -clever, on an overal" oasis, :re -oca- :vr"w:~ ~.~~.z ~.r.i
concentrations by about a factor of two as indicated by the mean of ratios of
predicted to the observed concentrations. Of the five days, the two that show
the highest correlation coefficient and index of agreement are 0080203(072180)
and JD8022K080880).
A scatter plot of the observed and oredictsd concentrations *or all data
for each of trie days considered is snown in ?igure 6.5. In addition to :re
one-to-one line (perfect prediction), an envelope of ±30% of the observed
concentrations is shown in the figure by dashed lines. The percentage number of
points lying within ±30%, greater than 30%, and less than 30% are provided in
Table 6.2. The percentage of data within the ±30% envelope for each of the days
is about 30% or better, while the percentage of underprediction is about 10%.
Figure 6.7 is a histogram of the difference between the measured and
predicted concentrations for each of the simulation days. The percentage of
data falling within ±0.03 ppm ranges from 45 to 51% depending upon the simula-
tion day, with the majority of the remaining data generally in the over-
prediction category (OBS-PRED < -0.03 ppm). The exception for this is the
performance on JD80204(072280), (see Figure 6.7) for which about 27% of the data
are in the overprsdiction category. However, examination of the model
oerformance measures listed in Table 6.1 for this day indicates that its slone
and correlation coefficient are sligntiy "ower in comparison vith other days.
For each of the simulation days, the diurnal variation of the mean
difference between the observed and the predicted concentrations along with the
standard deviation of the difference is shown in Figure 5.3. It is interesting
to note that up to about 1300 Hrs the difference is confined to rO.03 ppm, and
for the remaining hours of simulation the mean differences exceed 0.05 ppm,
indicating an overprediction by the model. Also, the error spread in the
afternoon hours is considerably larger than during the morning hours for each of
the days.
-------
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- 109 -
050
036 -
02T -
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009
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000
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000
Figure 6.6 Scatter Plot of Observed.
and Calculated Ozone Concen-
trations for Each of the Five
Simulation Days
010
020
030
-------
-110-
TABLE 6.2
Percent of Model Predictions Within ±30%, Greater Than 30%
and Less Than 30% of their Corresponding Measured Ozo
Concentrations ror ~ne Five Selected Cavs
_ Day _
JD80198 J080203 JD80204 JD80219 JD80221
Category (071680) (072180) (072280) (080680) (080880) All Data
Percentage Witnin . 3 7Q „
Ot HO OU ^U ^-^ _^
Percentage of -„ ,, , -n ^0
Over Prediction b° 44 °° b2
nH H ,- 13 10 12 8 7 10
Under Prediction
Sample Size 418 432 422 422 408 2102
-------
- Ill -
-o -, JD80198 (071680)
::Uj3lIs
1
-OM -oi« -ol* -a., a -o.o. -o.oa o.oa o.o« o.io o.i»
- JD802C3 ;C72180)
—o. 1-4. —o. i o —Q,O* —Q.aa o oa a.o* 0,10
JD302G4 '0722301
ao —
10 —
—o.i a —a.a* — a.02
0.0* 0.10
30 —
xo —
JD80219 (08068O)
HP
1^
—a-1" —0.1 * — o. 10 —o.o« —o.oa o.oa o.o«
J080221 (080880)
—o.io ~o.o« —o.oa
o.oa o,o«
Figure 6.7 Histogram of (OBS-PRED) Concentrations (PPM)
for each of the Five Simulation Days
-------
0.1 i
J
-0.
O.H
a. -0.1
Q.
^ 0.1
£-0.1
o
— 0.1 i
0 1
-0.1-"
- 112 -
I -
* v 7
T
: T z
T J t '
V i -i-
)
J080198(071680)
I T
O i 1
i
T T
i i
T T
JD80203(072180!
nnm mm
JD80204(072280)
5 j
I
I
JD80219(080680)
S s
TTTt
1 1 i 1
JD80221I080880)
H i 1 }
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19
HOUR
Figure 6.8 Mean and Standard Deviation of the Difference between the
Observed and Predicted Concentrations as a Function of Time
-------
-113-
6.2.1 Paired Comparison - Data from Connecticut
Since the measured ozone measurements for the five days indicate that the
peak concentrations occur over the Connecticut region, assessment of the model
performance in this region would be of particular interest. Figure 6.9 is a
envelope. In Table 6.3, the percentages of points within, below ana aoove ~ne
±30% envelope for each simulation day as well as the ensemble are listed. ~he
percentage of underprediction is about 10%, with about 50% of the data lying in
the ±30% envelope. In terms of the model performance, the day JD80203(072180)
has 60% of its predictions within the ±30% envelope followed by JD80221(080880)
i.-nth 50%, and in both cases about 9% or "ess of the data are •'n the
jiidsrpraai cti on category.
6.2.2 Paired Comparison - Concentrations Greater Than 100 ppb
It is important to analyze the model performance in simulating high ozone
concentrations in order to provide an assessment of the model's ability to
capture the peak concentration values. Toward this end,' any hourly measured
concentration greater than or equal to 100 ppb and its corresponding predicted
value were examined as a set for (a) the domain as a whole, (b) the Connecticut
region alone, and (c) New York and New Jersey. Scatter plots of the observed
and predicted concentration for each of the five days are shown in Figures 6.10
and 6.11 for the latter two cases, respectively. The percentage of points lying
within, above and below the ±30% envelope are listed in Tables 6.4a, 6.4b, and
6.AC for the entire domain, Connecticut, and New York and New Jersey.
respectively. The model appears to perform quita well, with at least 60% of the
oreai czions
-------
- 114 -
0 30
0 20 -
-•2*.
All DATA - COMN. '
JD80198(071680)
ODD
010
020
OSS
010
036
o:s
0 30
020 -I
-
010
0 30
«a MTA - com
. I
0 00 -I r
OIO 020
095
/
0 30
020
+
1
-rC
0 00
ALL WTA - COHN.
JB02I9(0«0630)
010
020
0 30
DBS
0 20 _.
0 10
0.00
030
Figure 6.9 Scatter P Lot of Observed ind
Calculated Ozone Concentrations
for Data in Connecticut Region
-------
-115-
TABLE 6.3
Percent of Model Predictions Within ±30%, Greater Than 30%,
and Less Than 30% of their Corresponding Measured Ozone
Day
Category
Percentage Within
±30%
Percentage of
Over Prediction
Percentage of
Under Prediction
Sample Size
JD80198
(071680)
49
35
16
142
JD80203
(072180)
64
27
9
140
JD80204
(072280)
46
42
12
139
JD80219 -
(080680)
43
43
9
127
JD80221
(080880)
50
44
6
125
All Data
51
o3
10
673
-------
o jo
- 116 -
0 20
010
+/
-H-
036
027
0 00 -f 1 r
0 30
010
> 100 P»B - CONK.
JD80138(071B«))
OZO
OBS
0 30
000
0 30
> 100 ?°B - COW.
JC80K5(0721SO)
009
018
0 27
036
0 20
0 10
0 OO
> ioo PPB - com. I
JB802M(072280)
010 02O
OBS
0 20
0 10
-t-
> 100 PP8 - COHN.
.0)80219(080680)
0 00 T-
010
020
0 30
OBS
0 20
Piaure 6.10
Same as Fiaure 6.9 but for
Data Greater than 100 PPb
in Connecticut
o 10
o oo
• '.oo pfB - com.
-380221(080880)
0 10 0 20
08S
0 30
-------
010 -.
T '"" X
010
>100 PW - «.T., «.
JW1«<071$80>
OZO
0 JO
C2£
ooo --
>loo m - «.r.. i.
JW203(07U80)
010
020
0 3C
0 20
/ T
X -r
010 .,
>joo PPB - i.r., «.j.
OO45
OO90 01SS
CBS
0180
0 00
>100 PCS - I.T.. I.J.
.00719(0806801
010
020
010
Figure 6.11 Same as in Figure 6.9 but
for Data Greater than 100 PPb
in New York and New Jersey
»ino m -1.1.. i.j.
mazuanuo)
OZO
030
-------
-118-
TABLE 6.4a
Percent of Model Predictions Within ±30%, Greater Than 30%,
and Less Than 30% of their
Corresponding Measured Ozone
Concentrations Greater than 100 ppb
Percentage v^itnin
±30%
Percentage of
Over Prediction
Percentage of
Under Prediction
Sample Size
Percent
JD80198
50
20
30
118
JD80203
_ _ - -
76
17
7
164
--PLE
of Model Predictions
and Less Than 30'
Concentrations
Category
Percentage Within
±30%
Percentage of
Over Prediction
Percentage of
Under Prediction
Sample Size
Oercsnt
JD80198
(071680)
59
10
31
68
of Model ^
% of thai r
Day
JD80204
„ -
60
3
37
63
5 . -b
Within
J080219
• ^ - -
69
17
14
70
±30%, Greater
JD80221
60
40
-
100
Than 30%,
64
21
15
515
Corresponding Measured Ozone
Greater than 100
JD80203
(072180)
80
14
6
84
TABLE
"9di ctions
Day
JD80204
ppb for Connecticut
JD80219
(072280) (080680)
65 56
4
31
46
6.4c
Within
and Less Than "0% ^f their ^orr-^so
Concentrations Greater than 100
Category
Percentage Within
±30%
Percentage of
Over Prediction
Percentage of
Under Prediction
Sample Size
JD80198
(071680)
39
31
30
50
JD80203
(072180)
70
21
9
80
21
23
43
±30%. Greater
JD80221
(080880) All
60
40
-
52
Than 30%.
Data
66
17
17
293
ondina "
-------
- 119 -
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.
I
00
CD
o -o 1
0.1
-0.1 -
?
in
JD80198(071680)
i
i
I T I T ^
* I I t <
1
r T i
1 t i
JD80203(072180)
'III
> \ M
1
JD80204(072280)
t
5 o
JD80219(08068C)
JD80221 (080880)
-5—*—*—t—*-
i i t J
Figure 6.12
H 12 13 14 15 16 17 18 19
HOUR
Same as Figure 6.8 but for the Observed Concentrations
Greater than 0.10 ppm and their Corresponding Predicted
Concentrations
-------
-120-
five days over the domain when measured concentrations exceed 100 ppb. The
systematic bias evident when all data are considered (see Figure 6.8) is absent
in this case, and the mean differences between the observed and predicted are
within ±0.05 ppm.
6 . 3 Urea1' yqd Cons arisen
Another way to assess the model performance is through an unpaired com-
parison of the daily maxima of the measured and predicted concentrations at each
of the monitoring stations independent of their time of occurrence. The ratio
between the predicted and measured peaks ranges from 1.29 to 1.72 for the ozone
monitoring network over the tri-state region. The difference in the time of
occurrence of the measured and oredicted oeaks ranges from ±2 hrs Tor the
New Jersey stations to ±5 Hrs for locations in Connecticut with the New York
sites falling in between. A similar analysis of the second rpgnest measured and
second highest predicted concentrations at each of the monitoring stations yields
a ratio in the range of 1.36 to 1.82 with a time difference of ±2 to ±5 Hrs.
However, it should be recognized that, in general, the location of the model
predicted ozone maximum may not necessarily be associated with those locations
where ambient air quality measurements are available. Hence, for the purpose of
comparison, the maximum measured and predicted ozone concentrations (independent
of time and space) for all the five days are provided in Table 6.5. It should
be noted that the measured ozone maxima for these five days are reported from
the monitoring stations in Connecticut, as are the predicted values. The ratio
of predicted to measured hourly maximum concentrations are in the range of 0.70
to 1.00 with a time lag of 0 to 3 Hrs. This indicates that the Tiodel under-
predicts tne pea< vaiue over the modeling domain as well as lags in terms of the
--.me of occurrence of -ne Tiaximum. "his aiscreoancv Tay ~e aue "o rumerous
factors SUCH as the uncertainty in tne specification of the initial and boundary
pollutant concentrations, space and time variation in the adopted mixing height,
and the wind fields as well as the lack of day-to-day variations in the emis-
sions data. It should also be noted that meteorological data summarized in
"Taole 2.4 indicate the occurrence of precipitation over portions of :he
simulation region, presumably resulting in some scavenging of the pollutants in
the real atmosphere, while the UAM does not include such processes.
-------
-121-
TABLE 6.5
Base Case Simulations: Unpaired Spatially and Temporally
Concentration (ppb)
Run Date
1 JD80198(071680)
2 JD80203(072180)
3 JD80204(072280)
4 JD80219(080680)
5 JD80221(080880)
Measured^
Max
291
303
240
249
246
Hr
14-15
15-16
16-17
13-14
13-14
Predicted
Max
205
229
191
229*
246
Hr
17-18
15-16
16-17
15-16
16-17
Katio
0.70
0.76
0.79
0.92
1.00
++Measured at any monitor in the Connecticut Region
Predicted at any grid in the Connecticut Region
-------
-122-
6.4 Model Performance - Summary
The results from the above analysis suggest that the model has performed
reasonably well with about 60% of the predictions in the ±30% envelope about
the perfect prediction line when measured concentrations are greater than 100
oob. Both temooral and soatial comcarisons of the measured aid oredicted
concentrations indicate tnac tne UAH overpreaicts on the average, ,-iowever, t,: =
model is found to underpredict for the subset comprised of measured concentra-
tions greater than or equal to 200 ppb. The model performance for the days
JD80203(072180) and JD80221(080880) is, in general, better than the other three
days with a tendency to underpredict the peak concentrations. Simulation
studies conducted for Tulsa (Reynolds, et al., 1982), St. Louis (Cole, et al . ,
1983), and Philadelphia (Haney and Braverman, 1985) using the DAM have reoortec
similar results. The fact that the model does not reproduce tne measured
maximum concentrations in tne modeling domain should not aeter its application
in emissions control strategy evaluations, as long as the estimated ozone
concentrations due to the imposition of specific controls are assessed in a
relative sense.
6.5 Modeling Limitations
It is well known that several sources of uncertainty exist in air quality
modeling that could affect the predicted concentrations of the pollutants.
These uncertainties can be broadly categorized as "reducible" and "inherent"
uncertainties. Errors in the input data to the model as well as inadequate
formulation of the physical and chemical processes in the model lead to
reducible uncertainty since uncertainties associated with these can be minimized
tnrougn -riore accurate ^nout aata as .veil as 'moroved noae i "ormuiat^on.
Inherent uncertainty stems ^om the stochastic nature of the atmosphere. Mo
matter how perfect the model and the input data are, the imprecision cannot be
reduced below a fundamental level because of the lack of predictability of the
transport and diffusion processes in the atmosphere. Therefore, the model
estimates will almost always differ ^rom the measured concentrations. yowever.
an understanding of the input uncertainty arising from errors in measurements,
errors in estimation, non-representativeness of the data, etc., will enable
proper interpretation of the modeling results.
-------
-123-
As mentioned before, the the numerical modeling approach adopted here is
data-intensive. It should be recognized that errors stemming from sparsity of
available data and the approximations used to generate information at each grid
point for each variable will propagate through the model and affect the
predicted concentrations. Quantification of the modeling uncertainty due to the
proolem. No attempts are made in mis report to quantify the JAM limitations or
uncertainties associated with the DAM application to the New York Metroooiitan
area because of the complexity of the problem. Evaluation of the modeling
uncertainty is beyond the scope of this study.
-------
-124-
(BLANK PAGE)
-------
-125-
CHAPTER 7
CONTROL STRATEGY SIMULATIONS
One of the primary objectives of this study was to evaluate whether
sa;-:C~ec :crtrol st.'atagias ;n "ne ;"?cunor emisir'ort >c'j'.; esc ~.: " - ;
attainment of the NAAQS for ozone in the New York Metropolitan area. ~o
this end, the (JAM has been applied for five high ozone days occurring in "he
1980 ozone season. Evaluation of the model performance in predicting the
measured ozone levels revealed best performance of the model on two days -
JD80203(072180) and J080221(080880). Hence, these days were selected for
assessing the impact of emissions control strategies on 'the ambient ozore
concentrations. An emissions ;nventory oasea ^pon :.'ie I35Z C;a;e I,np . ementa;'. ::•
°lans (SIPs) for 1988 was prepared and the 'JAM simulation was oer^orTied for
these two days with appropriate modifications to the initial and boundary ai^
quality conditions, keeping the meteorological conditions the same as those for
the 1980 base year cases. In this section, the results of the various control
strategy scenarios are presented and are compared with the base case(s) to
evaluate the effect of emissions reduction plans on the ambient ozone
concentrations in the study region.
7.1 Initial and Boundary Conditions
The methodology adopted for defining the initial and boundary conditions
for the control strategy simulations was as follows. For the initial
conditions, a comoarison was made between the projected 1988 NO and '/OC
A
emissions and those of the 1980 base case, and the percentage Deductions *or
tnese two ooilurants were calculated. "hese emissions -eductions ^vere "Hen
applied to scale the base year initial NO, and VOC concentration fields f^om the
/\
surface up to the top of vertical layer 3 (tnrough the mixed layer), under the
assumption that the changes in the precursor emissions have a similar effect on
the ambient concentration fields. The 1988 VOC and NO concentrations at the
boundaries were obtained by reducing the base year boundary concentrations of
VOC and NO by 40% and 20%, respectively, based upon the upwind region SIPs.
A
In the case of ozone, no direct methods are available to estimate the
future year boundary and initial fields due to the changes in the precursor
-------
-126-
emissions levels. Given that the ozone concentrations at the top of the
modeling region for the five simulated days in the base year are in the range of
60 to 85 ppb, the proposed changes in the emissions both upwind and in the
domain could result in a reduction of about 20 to 30% or in the 40 to 60 ppb
range for ozone levels at the top of the modeling domain. These estimates are
consistent with the suggested background levels (Wolff and lio«. 19~8: '<<*', ' <.
et. a!., 1984). Another metnoa is to apply tne E.KMA procedure (E.?n, ^9c-+; :o
estimate the expected changes in the ozone concentrations from changes in the
VOC and NO levels. This procedure, results in a reduction of about 18% in
X
ozone for an assumed change in the VOC and NO levels of 40% and 20%,
A
respectively. In this study, as a first approximation, a 20% reduction from the
ambient 1980 ozone levels was adopted for estimating the 1988 ozone concentra-
tions for the region too and the initial and boundary fields. As an examo"1- of
the 1988 boundary conditions, the changes in the NMHC and ozone concentrations
for the southwest corner surface grid ceil for the two days JD3G203f072150) ana
JD80221(080880), are shown in Figure 7.la and 7.1b, respectively.
7.2 Control Strategies
A set of six control strategy scenario simulations (CSSS), listed in Table
7.1, was performed to evaluate five control strategies proposed by the project
(OMNYMAP) Policy and Technical Committees with three of the five strategies
utilizing measures implemented and/or proposed in the current SIPs of the three
states. The CSSS Runs 1 and 2 are based upon the projected 1988 emissions with
the meteorological conditions prevailing on the days JD80203(072180) and
JD80221(080880), respectively. The changes in the emissions resulting from the
various control strategies are listed in Taoie 7.2. In che case of C333 Runs 1
ana 2. :ne "eductions in 70C ^na '10 emissions ~"om the ".980 oase '/ear are ^2%
A
and 14%, respectively, while with ^mp i ementation of che full SIP measures I.C333
Run 6), the reductions in the VOC's are estimated to be an additional 8% over
the CSSS Run 1 case in the tri-state area. It should be noted that these
changes in VOC and NO, emissions are not uniform or across-the-board reductions
A
but /ary ~"om grid call to jr^d :al\ The C3S3 Runs 4,5, and o utilized tne
JD80203(Q72180) meteorological conditions but with the modified emissions while
CSSS Run 3 was designed to investigate the effect on the ozone maximum due to
the reduction of Connecticut VOC emissions from the base year 1980.
-------
- 127 -
1000-
130C1
g; 600
LJ
2 1
O
O
400-
2001
456789
«0 H 12 43 44 13 16 IT 48 19 20
TIME (£ST)
-------
- 128 -
2001
180
160
z
UJ
"
o
u
80-
60
40
20-
0
072180
A
CS5S RUN 4.
11 12 13
TIME (ESI)
15 '6 17 18 i9 CO
100-
90
•0
70
•0
4
-------
-129-
TABLE 7.1
Summary of Control Strategy Scenario Simulations (CSSS)
Run #1 Application of DAM using 1988 emissions inventory with
JD8Q203(072180) meteorological conditions.
Run -?2 Application of Li AM using 13S5 emissions invertoo ,-.:,-
JD80221(080880) meteorological conditions.
Run #3 Application of DAM with 1980 base year inventory excluding VOC
emissions from Connecticut with JD80203(072180) meteorological
conditions.
Run ?f<\ Application of (JAM using 1988 emissions inventory /JT tn 06,=
reduction in NO from all sources in
A
JD80203(072180) meteorological conditions.
reduction in NO from all sources in Connecticut only and
A
Run #5 Application of DAM using 1988 emissions inventory with controls
on gasoline vapors (marketing and motor vehicle) and
JD80203(072180) meteorological conditions.
Run #6 Application of (JAM with fu1_l 1988 SIP (extraordinary measures)
and JD80203(072180) meteorological conditions.
-------
-130-
7.3 Results and Discussion
The spatial distributions of ozone for CSSS Runs 1 and 2 for the hours when
peak concentrations are expected to occur are shown in Figure 7.2. For both
days, the isopleths show the occurrence of a double peak similar to the base
case although the oeak value over the modeling domain has decreased "^om
JD80221(080880) case. The relative reduction in the peak concentration is
approximately 19% in both cases for an emissions reduction of 32% in the VOC's
and 14% in the NO over the modeling domain from the base year. The areal
X
extent of the decrease in the level of ozone exceedances was examined by
counting the number of cells equal to or exceeding the concentration of 125 ppb
r"or each nour starting at 0900. This is snown as a nistogram plot in Figure 7.3
ooth for the entire modeling domain (667 cells/ as weii as for trie Connecticut
region alone (203 cells). Cn a percentage basis for the peak czcne rcur ;f
1500, the decrease in the number of ceils (areal extent) is aoout 50% for
JD80203(072180) compared with about 20% for the JD80221(080880) case for the
entire domain as well as for the Connecticut region for the peak ozone hour of
1500. This may be due to the differences in the prevailing meteorological and
initial/boundary conditions on these two days.
The runs, CSSS Run 5 and Run 6, are an extension of the control strategies
to further reduce the 1988 emissions with tne imposition of additional controls
on gasoline vapors in New York and Connecticut (marketing and motor vehicles -
CSSS Run 5) and the implementation of controls on (a)architecture coatings,
(b)auto body refinishing, (c)consumer/commercial solvents, and (d) small source
3ACT (C3S5 Run 5). L'naer the CSSS Run 5 scenario, the estimated Deduction ~n
the 1988 VOC emissions ,vas an additional 2%. -mile "or "CSS -,un 5. the ^auction
,;as about 5% from the base 1988 emissions level fCSSS Run 1). ~o comoare the
effects of emissions reductions on ozone levels, the predicted concentration
^ields for CSSS Run 5 were subtracted from those of CSSS Run 1 ^or the hours of
highest concentrations (1400 and 1500 Hrs) and are shown in Figure 7.4. The
differences are of the oroer of 1 oob over the Connecticut region wrnch -: s
essentially within the noise range and, therefore, the additional controls in
New York and Connecticut arising from CSSS Run 5 have very little impact on the
reduction of the ozone levels in the domain on this day.
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- 132 -
ARE*. OtSTWamON OF OZONE
GREATER THAN 125 PPB ft 1500 FOR CSSS-RUN 1
3
>•
it to if 10 a 10
X-AXB
AREAL DISTRIBUTION OF OZONE
GREATER THAN 125 PP8 ft I6OO FOR CSSS-RUN 1
to
18-
8-
«0 18 tO
X-AXB
csrrnaurzN CF OZONE
GREATER THAN 25 PP8 fl 1500 FOR CSSS-RL9< 2
OSTRiSUTCN vy C2CWE
GREATER THAN C5 PP9 4 «CO PCS? CSSS-f?UN 2
i
>•
w to
X-AXIS
M
X) 1» 10
X-AXIS
Figure 7.2 Spatial Distribution of Ozone for Selected
Hours for CSSS Run 1 and CSSS Run 2
-------
SCO
- 133 -
Totol Nurrfcer of C*ts 667
4 5 £ 7 8 9 10 11 12 13 14 15 16 17 »« 19
Totol Number of Cells 2O8
4 5 « T • 9 10 11 12 <3
15 16 47 46 19
Totol Number of C«Us 667
>BASE RUN 4
4 * 4 7 « * 10 11 42 13 14 15
Totol IVumoer of Calls 208
4 S « 7 • » 10 11 12
13 14 15 16 17 18 19
Figure 7.3 Histogram Plot of Cells Exceeding 125 PPb of Ozone for the
Base Runs and the Corresponding Projected Year Runs
-------
- 134 -
I*.
is
18
I
3.0
8 !
7 a
(.0
5.0
• 0
3.:
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s.o
5. a
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2.8
1500
/-fiX15
igure 7.4
Difference Hap of Ozone Concentrations (ppo; 3etween
CSSS Run 5 and CSSS Run 1 at 1400 and 1500 Hours
-------
-135-
In Figure 7.5 are shown the ozone isopleths for CSSS Run 6. The peak ozone
concentration is 175 ppb compared with 185 ppb in the case of CSSS Run 1. The
area! extent or the number of cells equal to or exceeding 125 ppb for CSSS Run 6
is shown in Figures 7.3a and 7.3b for the entire domain and for the Connecticut
region only. Comparisons between the results of CSSS Run 1 and CSSS Run 6
10% for tne entire domain, as well as for the Connecticut region alone.
Although the controls identified under CSSS Run 6 are not explicitly evaluated
with the meteorological conditions prevailing on JD80221(080880), from a
comparison of the results of CSSS Run 2 with the corresponding base case it
should become evident that these emissions reductions cannot result in ozone
concentrations below the level of the ozone NAAOS. Thus, while the reduction in
9.7ii~34cns under CS2o "Run 5 has 'esulted "n a ^r-ther "eduction •" t~e ?. re~~
extent of the ozone exceedances, these strategies cannot reduce the peak ozone
concentration in the New York Metropolitan area to the level of the ozone MAAQS.
Two other runs, CSSS Run 3 and CSSS Run 4, were performed to evaluate the
effects of emissions controls imposed over the Connecticut region only. In CSSS
Run 3 the 1980 base year inventory was utilized to exclude all VOC emissions
from the Connecticut region, and CSSS Run 4 was based upon a 50% reduction in
the 1988 NO emissions from Connecticut. The results of these two simulations
/\
are presented in terms of the difference maps in Figures 7.6a and 7.6b. In the
case of CSSS Run 3, the decrease in the ozone levels is on the order of 6 to 8
ppb over the northeast portion of the domain, while in the case of CSSS Run 4,
the change is ±3 ppb. Thus, these reductions of VOC and NO emissions in the
X
Connecticut area alone have minimal or no effect on the predicted ozone levels
over the modeling domain.
In summary, the UAM simulations for the two days with the control measures
identified in the SIPs for the New /ork Metropolitan area demonstrate that
(a) there is an overall improvement in the ozone concentration levels from the
1980 base year, and (b) the peak ozone concentrations would not likely be
Deduced to levels at or below that of the ozone ^AAQS in the 1988 ozone season.
-------
- 136 -
20-
19-
-------
- 137 -
rs.
tc.
13.
II.
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16.
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Figure 7.6a Difference Map of Ozone Concentrations (ppb) for CSSS Run 3
and its corresponding Base Case JD80203(072180)
Figure 7.6b Difference Map of Ozone Concentrations (ppb) for CSSS Run 4
-------
-138-
(BLANK PAGE)
-------
-139-
CHAPTER 8
SENSITIVITY ANALYSIS
Analysis of the control strategy options considered in this study indicates
-^nt- ? i ~n ^f - --3.P;" oort^ons c^ the "node1 "ina domain wi"'"' continue to ?ycssd ^i~c-
NAAQS for ozone during tne 1988 ozone season. To anaerstano how some or ~~~
input variables affect the predicted ozone concentrations, six sensitivity runs
were performed with this data base. For each of these runs, meteorological
conditions prevailing on JD80203(072180) were considered, since model evaluation
results indicate "best" model performance on this day, with variations in the
(JAM input data bases of initial and boundary concentrations and emissions. In
this section the methodology aaootea to oerform the sensitivity runs 15
presented along with the results and tneir implications.
8.1 Initial and Boundary Concentrations
A set of initial concentrations for the pollutants NMHC, NO , CL, and CO
A O
was selected to be representative of "clean" background conditions and is
reflective of "minimum" ambient concentration levels. The pollutant concentra-
tions for the "clean" conditions, listed in Table 8.1, are assumed to be uniform
across the domain. Similarly, when a "clean" boundary condition was desired,
the concentrations in Table 8.1 were used for the boundaries as well as for the
region top.
The sensitivity tests were designed to evaluate the influence of initial
ana boundary concentrations ana emissions on the predictea ozone concentrations
:n the -nodeling domain. A :ota"i of six sensitivity -uns. "isted 4-n "aoie 3.2.
were performed and the ^esuits are discussed below.
8.1.1 Sensitivity Run 1
This simulation was designed to evaluate the effects of initial conditions
with "clean" air influx into the modeling domain; the emissions in the domain
were "turned off". The initial conditions at the beginning of the simulation
reflect the interaction of the base year emissions in the domain up to the start
-------
-140-
TABLE 8.1
"Clean" Pollutant Concentrations Used as Initial/Boundary Conditions
in the Sensitivity Analysis
Pollutant Concentrations foci}1)
°3
N02
NO
NMHC*
CO
0.1
2.0
1.0
5.0
20.0
'ppbc
-------
Model
Sensitivity
To
-141-
TABLE 8.2
Summary of Sensitivity Runs
Model Input
Initial
Conditions
072130
Boundary Region Top
Conditions Concentration
Emi ssions
None
Model Output
No exceedances over ,'i
and NY.
Emissions
Clean
Clean Clean 1988 Emissions Peak CL of 43 ppb
from CSSS over CT @ 1700-1800 Mr.
Run 1** No exceedances over
NJ and NY.
Initial and From CSSS
Lataral 3oun- Run 1
aary Conai-
tions, and
Region Top
Concentration
Lateral Clean
Boundary
Conditions
Lateral
Boundary Con-
ditions and
Region Top
Concentration
Initial
Conditions
and
Emissions
From CSSS From CSSS
Run 1 ?'ur, 1
None
From CSSS
Run 1
Clean
None
Clean
From CSSS
Run 1
From CSSS
Run 1
None
From CSSS
Run 1
Clean
Clean
1988 Emissions
. from CSSS
Run 1
Pea< CL of io3 ceo
,-*> -^ O * /\ i^ f*> " — -if
over , . .- .-o^-.c^j
and exceeaance over
MJ ana NY.
50 ppb over CT; 100 ppb
over NY; and exceedances
over NJ (southwestern
portion of the modeling
domain) .
Wide areas of exceedances
over NY, NJ and
southwestern CT.
Peak impact of 158 ppb
over CT @ 1300-1400 Hr.
.No axcaedances over MY
and NJ.
se case corresponds to 1980 emissions with realistic initial, boundary and region top
icentration and predicted peak ozone concentration of 229 ppb over Connecticut (see
gure 6.2).
a CSSS Run 1 corresponds to 1988 emissions with realistic initial, boundary, and "egion
D concentrations (Table 7.1), and predicted peak ozone concentration of 185 ppb over
inecticut (Figure 7.2).
-------
-142-
of the simulation as well as pollutant transport from upwind regions. A peak
ozone value of 107 ppb was predicted in the Connecticut region with lower
concentrations over the rest of the modeling domain. This run demonstrates that
even with the exclusion of emissions and pollutant transport into the modeling
domain, reasonable initial conditions alone could produce ozone levels of the
order of 100 opb.
8.1.2 Sensitivity Run 2
In this simulation, the effect of 1988 emissions alone was evaluated by
imposing "clean" pollutant levels both for the initial concentration fields and
for the boundary (transport) conditions. The peak value of ozone formed under
tnese conditions was 43 ppb over me Connecticut region, far below the ieveis
projected from CSSS Run 1, indicating the importance of tne roie of tne initial
as well as pollutant influx "hrougn cne lateral boundaries arc region ~op.
8.1.3 Sensitivity Run 3
In contrast to the previous run where "clean" conditions were considered
for the initial and transported pollutant fields, this run incorporates
"realistic" initial and transported pollutant concentrations from CSSS Run 1
with the emissions "turned off". The effect of these "realistic" conditions is
that over the Connecticut region an ozone peak value of 158 ppb was predicted
with concentrations exceeding 125 ppb for parts of New York and New Jersey. The
area! distribution of ozone for 1400 Hrs., shown in Figure 8.1, has the
characteristic double peak formation, revealing the importance of the
"realistic" initial and boundary 'ields.
3.1.4 Sensitivity Run ^
In this run, the influence of the peak ozone levels formed from the lateral
transport of pollutants into the domain is examined by setting the
concentrations at the too of the region to the "c1ean" "'evel while retaining the
boundary conditions to reflect those of CSSS Run 1. Also, the initial pollutant
fields were set to the "clean" conditions with no emissions in the domain. This
-------
- 143 -
-a
SIXV-A
-a
X
7
x
StXV-A
x sa.
•o
c
13
\ (%. r
\ 1 "\ t-m
X. I -
^N. y?5
^ V
-
.
-
0 /
/
* /
z /
s
s 2 o « ^ a''1^''''"'1''^'
^J [ 1
* >•
"4
* >
Z . j
IP^
• • -i- • •. g
W
0
U-l
w
0
W
CJ
c
co
1)
u
cr
•"1
b
SIXV -
-------
-144-
simulation, shown in Figure 8.1, indicates ozone concentrations exceeding
125 ppb over New Jersey, and levels reaching 100 and 50 ppb over New York and
Connecticut, respectively. This suggests that the boundary fields play a role
in the generation of the peak over the New Jersey - New York area in addition to
contributing to the peak over the Connecticut region.
5.1.5 Sensi ti vi ty RLII 5
This run complements the previous run such that the pollutant
concentrations at the top of the region were set to those of CSSS Run 1, or to
the "realistic" levels. There were no emissions within the domain and the
initial pollutant fields were set to the "clean" conditions. The areal
distribution of ozone for this simulation, shown in Figure 8.1, nas wide areas
exceeding 125 ppb over much of New Jersey, New York and portions c~ southwestern
Connecticut. This simulation, in contrast to sensitivity Run 3. demonstrates
the role of the initial conditions on the prediction of peak ozone levels over
Connecticut.
8.1.6 Sensitivity Run 6
In this run, the effect of inclusion of emissions with realistic initial
conditions and "clean" concentrations for the region top and boundaries was
examined. This run can be compared with Sensitivity Run 2 in which the initial
conditions and transported pollutants were set to the "clean" level. This
simulation yields no exceedances of the ozone NAAQS over New Jersey or New York
but predicts a peak ozone value of 158 ppb over the Connecticut region. In
Figure 3.2 are snown tne areal distributions for selected hours for Sensitivity
Kuns I ana 6. In ooth ;ases no second ozone )ea« was "ormea 3ver ~.r.e
New Jersey-New Yorx region inaicating the effact of ":lean" boundary
concentrations. The peak arising from the realistic initial pollutant
concentrations in this run snows areas of exceedances of the NAAQS, while with
the "clean" conditions it is well below the standard, indicating the influence
and "TiDortance of the "nitial oollutant fields.
-------
- 145 -
AREAL DISTRIBUTION OF OZONE ©15OO HRS FOR SENS-RUN 2
29
10-
m
2
8-
I—r—1—r—1—i—i—I—r—I—i i I—I I I I—I I 1 I I I I—I I I I—f
19 W 19 20 29 SO
X-AXIS
AREAL DISTRIBUTION OF OZONE
GREATER THAN 80 PP8 ft '300 FC« SENS-RUNS
20-
19-
75 ,—I—' ' ' ' I I > I I i i I. i—i—• i ' • •
« 18 10 29 SO
X-AXIS
Figure 8.2 Ozone Isopleths (PPb) for Selected Hours for
Sensitivity Runs 2 and 6
-------
-146-
8.2 Discussion
Six sensitivity runs were performed to examine the effects of transport of
pollutants into the New York Metropolitan area coupled with the emissions from
the region. In all these runs, the adopted boundary conditions refer either to
those included in Table 8.1 as the "clean" influx or to thoss adooted ^rom CSSS
Run 1, as cnscussea in Chapter 7. It ;-,ouia oe cruaent tc assess .jr,et.:er cr.e
ozone concentrations exceeding 125 ppb during 14-00 to 1600 Mrs. at the southwest
boundary will affect the predicted concentration fields in the New Jersey area.
Examination of the isopleths for Sensitivity Run 5 (see Figure 8.1) shows that
the peak value of 156 ppb occurs approximately 120 km from the southwest
boundary. During this period the winds were from a south-southwesterly
direction at 4 to 5 m/s suggesting a travel time of 6 to 8 Hrs. ~or trie admass
from the southwest boundary to reach the location of the peak concentrat1on.
Thus, tnese hign ozone levels at this oounaary snould nave little effect on trie
predicted peak ozone concentration in the New Jersey area. However, the cells
near the southwest boundary could be affected by the transport of ozone
exceeding 125 ppb (Sensitivity Run 4), and perhaps the peak ozone concentration
of 131 ppb in Figure 8.1 could be attributed solely to this high ozone influx.
Sensitivity Run 3, in which the emissions have been "turned off" predicts
concentrations in excess of NAAQS over the modeling domain just from the initial
concentrations and pollutant transport, while Sensitivity Run 6 reveals that
"turning off" the influx of concentrations into the domain but including
emissions will also result in similar exceedances of the NAAQS over the region.
Furthermore, emissions alone within the domain, without the influence of the
initial and boundary concentrations (Sensitivity Run 2), result in a peak ozone
of 43 ppb over Connecticut. Thus, i: is evident tnat controls or reductions ;n
the emissions levels ,-ntmn the Tioaenng a amain ;nouia oe :ouoiea .vitn
reductions in ozone and its precursors transport from the jpwina ^agions :r\
developing meaningful strategies to meet and maintain the NAAQS for ozone in the
New York Metropolitan area.
-------
-147-
CHAPTER 9
SUMMARY AND CONCLUSIONS
In this study, the Urban Airshed Model (UAM) was used to simulate five high
.'rone javs ' "• ~he _9£G :z3'r;3 ^easco "~'T=s3 -----a ^ayc -«er" "hvr ~ ct~'~' is-1. ~
excaedances of tne ozone NAAQS over wide areas of cne New Yorv. Mecrcco ',-a,i
region consisting of portions of the States of New Jersey, New York, ana
Connecticut. Typical meteorological conditions associated with high ozone days
are as follows: (a) winds from the south to southwest at 4 to 5 m/s, (b) surface
temperatures in excess of 80's°F, and (c) a high pressure system over the
Atlantic, ridged westv/ard through the southern states.
The New York Metropolitan area lies within the emissions-rich Northeast
urban corridor with significant inter-urban transport of ozone and its
precursors. All five days simulated show the occurrence of two peaks, one over
central Connecticut attributable primarily to emissions from the NY/NJ area, and
the other over the northeastern New Jersey and New York border areas attribut-
able to the influx of ozone and its precursors into the modeling domain from the
upwind boundary.
The first part of the study was designed to adoot the UAM to the New York
Metropolitan area, and to assess the model's performance in simulating observed
ozone concentrations. Analysis of modeling results revealed that although the
model underpredicts the peak concentrations over the modeling domain, the
performance of the model in predicting within the ±30% envelope of the measured
concentration levels is reasonable both on an individual day basis as well as on
an ensemole oasis. ~he Jer^ormanca stat" sti C3 of concentrations greater :han
100 ppb over the entire modeling domain or over the New Jersey-New vork region
or over the Connecticut region revealed that at least 60% of the model
predictions were within the ±30% of their corresponding observed concentrations.
Of the five days that were simulated, two days, JD80203(072180^ ana
JD80221(080880), were used in the detailed evaluation of the control measures
identified in the State Implementation Plans of the three states for attaining
the NAAQS for ozone. The reductions in the VOC and NO emissions in the
A
modeling region in 1988 were estimated to be 32% and 14%, respectively, from the
-------
-148-
1980 base year emissions. Assuming that the SIP and motor vehicle reductions in
the upwind emissions will occur in 1988, concentration levels at the boundaries
were reduced by 40% in VOC, 20% in NO , and 20% in ozone from their 1980 levels,
A
The UAM simulations for the two selected days with the projected 1988 emissions
indicate that the peak ozone level over the Connecticut region decreases by
about 20% from the 1980 level but is still well above the MAAQS for ozone. The
50% depending upon the simulation day.
Adoption of additional extraordinary emissions controls, as envisioned
under the SIPs, upon such source categories as architectural coatings, auto
refinishing, consumer/commercial solvents and adoption of small source RACT
"or the 1988 emissions resulted :n a ^0% reduction -n 7CC f-om the 132?
oase year. rhe 'JAri .jirnu . at~on ^si:". ^ ~r>~3 _jS8 emiss'ons ' ^ventc.;1;, "evea .•=•.; ;,~aZ
these extraordinary control measures result in only a marginal ^morovement "" n
the peak ozone level and in the areal extent of the ozone exceedances. Thus, it
is evident that even with these proposed control measures of VOC and NO
X
emissions in the New York Metropolitan area, the peak ozone levels can be
expected to be well above the ozone NAAQS during the 1988 ozone season.
In an attempt to assess the influence of the initial and boundary condi-
tions, and emissions on the predicted ozone levels, several model sensitivity
simulations were performed using the JD80203(072180) meteorological conditions.
The results indicate that even when the emissions in the New York Metropolitan
area are "turned off", transport into the modeling domain alone could lead to
exceedances of the NAAQS over the region. Peak ozone levels in this scenario
are comoarable to those predicted by a 40% VOC emissions reduction strategy
'CSSS Run 5). Further, hypothetical! y "clean" air ^nfux through the boundaries
and ''realistic" initial conditions and emissions also result in exceedancs of
the MAAQS. However, neither of these extreme cases, "turning off" the emissions
in the modeling domain or having the modeling domain surrounded oy "clean"
boundaries, are realistic assumptions.
-------
-149-
The results presented here strongly suggest that both emissions reductions
within the New York Metropolitan area and further reductions in ozone and its
precursors transport from the upwind areas are necessary to meet and maintain
the ozone NAAQS in the region. Clearly, additional modeling analyses are needed
to document the level of control required to achieve the NAAQS for ozone in the
-------
-ISO-
References
Ames, J., T.C. Meyers, I.E. Reid, D.C. Whitney, S.H. Golding, S.R. Hayes, and
S.D. Reynolds, "SAI Airshed Model Operation Manuals Volume I - Users
Manual," EPA-600/8-85-007a, 1985a.
Ames, J., S.R. Hayes, T.C. Myers and O.C. Whitney, ''SAI Airshed /locei Opera-"; :r.±
Manuals Volume II - Systems Manual," EPA-600/8-85-007b, 19S5b.
Benkley, C.W., and L.L. Schulman, "Estimating Hourly Mixing Depths from
Historical Meteorological Data," Journ. of Appl. Meteor., 18, 772, 1979.
Syers. H.R.. General Meteorology. McGraw '-Mil Book Comoany. New VT* . V?~l.
Clark, T.R. and R. Eskridge, "Non-divergent Wind Analysis Algorithm from rne
St. Louis RAPS Network," EPA-600/4-72-049, 1977.
Cleveland, W.S., B. Kleiner, J.E. McRae, and J.L. Warner, "Photochemical Air
Pollution Transport from the New York City Area into Connecticut and
Massachusetts," Science, 191, 179, 1976.
Cole, H.S., D.E. Layland, G.K. Moss and C.F. Newberry, "The St. Louis Ozone
Modeling Project," EPA-450/4-83-019, 1983.
"Compilation of Air Pollutant Emission Factors," Publication No. AP-42,
Supplement 15, EPA, 1984.
Demerj ;an. (.L., <.!_. Scnere, and J.~. Dererson, '""''heoreti cal Estimates :f
Actinic (Spherically Integrated) Flux and Photolytic Rate Constants of
Atmospheric Species in the Lower Troposphere," in Advances in Environmental
Science and Technology, Vol. 10, pp. 369-459, J. Pitts and R. Metcalf,
eds., John Wiley & Sons, New York, New York, 1980.
"Emissions Inventories for Urban Airshed Model Application in the Philadelphia
AQCR," EPA-450/4-82-005, 1982.
-------
-151-
Fox, D.G., "Judging Air Quality Model Performance," Bull. Am. Meteor. Soc., 62,
599, 1981.
Garrett, A.J., "Comparison of Observed Mixed-Layer Depths to Model Estimates
Using Observed Temperatures and Wind and MUS Forecasts," Journ. of Appl.
Meteor. . 20, 1277, 1981.
Haney, J.L. and T.N. Braverman, "Evaluation and Application of the Urban Airshed
Model in the Philadelphia Air Quality Control Region," EPA-450/4-85-QG3,
1985.
Hull, A.M., Comments on "A Simple But Accurate Formula for the Saturation Vapor
Pressure Over Liquid Water,'1 Journ. of Appl. Meteor., 13. 606. 13/4.
McRae, G.J., W.R. Goodin, and J.H. Seinfeld, "Mathematical Modeling cf
Photochemical Air Pollution," EQL Report No. 18, California Institute of
Technology, Passadena, CA.
Nieuwstadt, F.T.M., "Steady State Height and Resistance Laws of Nocturnal
Boundary Layer: Theory Compared with Cabauw Observations," Bound. Layer
Meteor., 20, 3, 1981.
Northeast Corridor Regional Modeling Project - Description of the 1980 Urban
Field Studies (NECRMP, 1982c) EPA-450/4-32-018, 1982.
Northeast Corridor Regional Modeling Project - Aircraft Measurements - New York
and Vicinity (NECRMP, 198Cb) EPA-450/4-31-012, 1982.
Northeast Corridor Regional Modeling Project - Continuous Non-methane Organic
Compound Data Collection (NECRMP, 1982) EPA-450/4-80-034, 1982.
Northeast Corridor Region Modeling Project - Ozone and Precursor Transport in
New York. City and Boston during the 1980 -'eld °^ogram. 1980a.
Pagnotti, V., "A Meso-Meteorological Feature Associated with High Ozone Days
Over the Northeastern U.S.," Jour, of Air Poll. Contr. Assoc. (In Press),
1987.
-------
-152-
Rao, S.T., G. Sistla, V. Pagnotti, W.B. Petersen, J.S. Irwin, and D.B. Turner,
"Evaluation of the Performance of RAM with the Regional Air Pollution Study
Data Base," Atmos. Env., 19, 229, 1985.
Reynolds, S.D., "The Systems Application Incorporated Urban Airshed Model: An
Cverv" ew o~ Decent Oeu3l cement '','ori'.,'' I^tsr^it" or r.1 3~~~"~''~'^>"ic9 ~.^
Photocnemi cal Oxidant Pollution ana Irs Control, £?A-6CC/ 3-77-OGla, 157r
Reynolds, S.D., H.Hogo, W.R. Oliver and I.E. Reid, "Application of the SAI
Airshed Model to the Tulsa Metropolitan Area," SAI Report #82004 to USEPA
under Contract No. 68-02-3370, 1982.
Spicer, G.'/J., D.'.-J. Joseph, P.R. StickseK and G.P. Ward. "Ozone Sources r-c
Transport in the Northeastern Jnitea States,1' Z.vv. 3t; . ^ecn^. . 13, 373.
1979.
Willmot, C.J., "On the Evaluation of Models," Phys. Geog., 2, 184, 1981.
Wolff, G.T., P.J. Lioy, R.E. Meyers, R.T. Cederwall, G.D. Wright, R.E. Pasceri,
and R. S. Taylor, "Anatomy of Two Ozone Transport Episodes in the
Washington, D.C. to Boston, Massachusetts Corridor," Env. Sci. & Techn. 11,
506, 1977.
-------
-153-
APPENDIX A
Temporal and Speciation Factors for Area and Point Source Emissions
The total VOC and NO emission inputs were divided into the DAM required
X
hydrocarbon species and/or NO-NO,, splits using the data developed by Engineering
Sciences for USEPA ^EPA, 1982. Temporal factors for araa sour;a emissions
detailed in the ES study were adopted in this application.
In the case of point source categories not included in the ES study,
appropriate factors were determined based upon similarities in fuels burned
and/or orocess description. For example, emissions from bituminous coal fired
utility boilers were assumed to have the same component solics regardless of :na
manner in which the fuel was burned, and in the following Tables are listed tne
factors used in the QMNYMAP study:
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-------
- 156 -
TABLE A. 2
NOx SPECIATION FACTORS FOR AREA SOURCE EMISSIONS IN THE MODELING DOMAIN -
SCC
90100222 1
90100330 1
90100500 1
9010060O 1
.90200 11 1_1 .
90200222 1
90200330 1
9020044G_i.
90200500 1
90300222 1
903GOJi30__i
90300440 1
903005OO 1
90600700 1
90600600 1
90 fip Q? on t
90700700 1
90700SOO 1
_ 9070220G_1
9070240O 1
90803100 1
90603300 1
90900440 1
90904430 1
91002400 1
9 1 -aoft 1 on i
913082OO 1
91 308 300 1
-S130S400 t
91303500 1
NO
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- 169 -
TABLE A.4
NEW YORK MINOR POINT SOURCE SPECIATION FACTORS
CHEMICAL NAME
3TAL ORGANIC SOLVENTS
MISC. ORGANICS
METHYL ETHYL KETONE
TOLULENE
ORGANIC SOLVENTS
ZTHANOL
DIMETHYL70RMANIDE
OTHER ALIPHATIC EST
ALIPHATIC ALCOHOLS
ffiR ALIPHATIC KETONES
-IPHATIC HYDROCARBONS
ISOPROPYL ALCOHOL
TETRACHLOROETHYLENE
TRICHLOROETHYLENE
ACETONE
HYDROCARBONS -MISC .
XYLENE,M O&P MIX
NAPTHENES (CYCLO)
METHANOL
TOTAL HYDROCARBONS
2? ALIPHATIC CHLORINE
OTHER ACETATES
PAINT THINNER
OTHER ALIPHATIC ET
AROMATIC NITROGEN
miYL ISOBUTYL KETONE
•K ALIPHATIC HALOGENS
ISOBUTYL ALCOHOL
NAPTHALENE
ISOPROPYL ACETATE
OTHER ALIPHATIC AMIN
NONMETHANE ALKANES
ALIPHATIC HYDROCARBON
PYRIDENE
NONSPECIFIC ODOROUS
CAS NO.
NY998-00-0
NY990-00-0
00078-93-3
00108-88-3
NY530-00-0
0006-4-17-5
00068-12-2
NY690-00-0
NY580-00-0
NY645-00-0
NYS50-00-0
00067-63-0
00127-18-4
00079-01-6
00067-64-1
68476-39-1
01330-20-7
NY335-00-0
00067-56-1
NY495-00-0
NY740-00-0
NY685-00-0
NY920-00-0
NY595-00-0
NY435-00-0
00108-10-1
NY780-00-0
00078-83-1
00091-20-3
00108-21-4
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-170-
APPENDIX B
Diurnal Plots of Predicted and Measured Ozone Concentrations
The diurnal variation of the measured and predicted ozone concentrations at
the monitoring stations in the OMNYMAP domain, see Figure B-I, are presentee for
each of the five days. These diurnal plots presented in this manner are helpful
in providing a qualitative assessment of the UAM performance.
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- 171 -
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3-2 Diurnal Plots of tne observed and predicted ozone concentrations
monitoring stations on 0080198(071680).
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3-3 Diurnal Riots of the observed ana oredictea ozone concentrations at
monitoring stations on JD80203(072180).
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before cumpleltnzj
REPORT NO.
EPA 450/4-87-011
2.
3. RECIPIENT'S ACCESSION NO
TITLE AND SUBTITLE
Application of the Urban Airshed Model to the New
York Metropolitan Area
5 REPORT DATE
May 1987
6. PERFORMING ORGANIZATION CODE
AUTHOR(S)
Dr. S. T. Rao
8. PERFORMING ORGANIZATION REPORT NO
'ERFORMING ORGANIZATION NAME AND ADDRESS
Division of Air Resources
New York State Department of Environmental
Conservation
50 Wolf Road, Albany,
•New York 12233
10. PROGRAM ELEMENT NO
J13A2r
11 CONTRACT, GRM,\ r
CX811945-01-0
, SPONSORING AGENCY NAME AND ADDRESS
U. S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final Report
14. SPONSORING AGENCY CODE
SUPPLEMENTARY NOTES
"^ nfeAcq"oal s of the "Oxidant Modeling for the New vor'< Metropolitan Area
MNYMAP)" are to examine (a) the extent and magnitude of the ozone proolem i-1 trip New
rk area; (b) the impact of specific control strategies committed to by New Jersey,
w York and Connecticut in the 1982 State Implementation Plans (SIPs);"(c) the role of
'llutant transport from upwind regions; and (d) strategies to meet and maintain ozone
AQS in the New York area. In this study, the urban AIRSHED model was used to simulate
ve high ozone days in the 1980 oxidant season. The model results were analyzed to
sess'the performance of the model in simulating the observed ozone concentrations.
amining the data set of ozone concentrations greater than 100 ppb reveals that 60% of
e predicted values were within ±30% of their corresponding observed concentrations.
wever, the model has a tendency to underpredict the peak concentrations over the
deling domain. The results of simulating the emissions controls to be implemented by
88 indicate that although there is a decrease in the peak ozone levels, predicted
mcentrations are well above the NAAQS for ozone. Even with the imposition of extra-
•dinary emissions control measures, the results of a one day simulation reveal that
e peak ozone level continues to be well above the NAAQS, Analysis of the sensitivity j
r the ozone predictions to specific model inputs indicates that pollutant transport is
iportant and that additional modeling is necessary to quantify the level of controls
;quired to meet the ozone NAAQS in this area.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
Air Pollution
Meteorology
3zone
^hotochemical Modeling
3. DISTRIBUTION STATEMENT
Release unlimited
••
b. IDENTIFIERS/OPEN ENDED TERMS
19. SECURITY CLASS (Tins Report/
Unclassified
20. SECURITY CLASS {This page I
Unclassified
c. COSATI i-ield/Group
21 NO. OF PAGES
233
22. PRICE
!PA Form 2220-1 (Rev. 4-7")
PREVIOUS EDITION IS
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