MODELING SUBGROUP REPORT
Of
Work Group 2*
Atmospheric Sciences and Analysis
REPORT NO. 2-13
July 10, 1981.
*Under the Memorandum of Intent on Transboundary Air Pollution
Signed by the United States and Canada on August 5, 1980.
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Mr. Howard Ferguson, Director
Air Quality and Inter-environmental
Research Branch
Atmospheric Environment Service
4905 Dufferin Street
Downsview, Ontario M3H5T4
Dr. Lester Machta, Director
Air Resources Laboratory
National Oceanic and Atmospheric
Administration
8060 13th Street
Silver Spring, MD. 20910
Dear Mr. Ferguson and Dr. Machta:
We are pleased to transmit under cover of this letter the
interim report of the Modeling Subgroup as provided for in
the Phase II Work Plan. We believe that this report satisfies,
in a scientifically responsible manner, our Phase II objectives.
Sincerely,.
Brand L. Niemann
U.S. Modeling Coordinator
\ .
James W.S. Young
Canadian Modeling Coordinator
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-1-
PREFACE
This is a "Working Report" prepared by the Modeling
Subgroup of Work Group 2. This group is one of five
established under the Memorandum of Intent signed by the
governments of Canada and the United States on August 5, 1980
This "working report" is one of a set of eleven Work
Group 2 reports in Phase 2 which represents the drawing
together of currently available information relevant to
transboundary pollution.
This information will be used by both governments to
develop a consensus on the nature of transboundary pollution.
These reports contain some information and analyses
that are still preliminary in nature; however, they accurately
reflect the current state of knowledge as of July 3, 1981,
on the issues considered, given the resources available to
prepare these reports. Any portion of these reports is
subject to modification and refinement as peer review,
further advances in scientific understanding, or the results
of ongoing assessment studies become available.
More complete "final reports" dealing with a variety of
transboundary air pollution issues are expected in early
1982. These reports will integrate the efforts of the present
"working reports" and will also incorporate editorial revisions,
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-3-
TABLE OF, .CONTENTS
Preface 1
List of Contributors 2
List of Figures 5
List of Tables 7
List of Abbreviations 10
1. Introduction 1-1
2. Summary of Model Profiles 2-1
2.1-1
2.2-1
2.3-1
2.4-1
2.5-1
2.6-1
2.7-1
2.8-1
3. Phase II Data Bases 3-1
3-1
3-6
3-6
3-13
4. Evaluations Against Measured Data 4-1
4.1 Evaluation Criteria 4-1
4.2 Comparison of Model Estimates with 4-3
Observations
5. Development and Intercomparison of Phase I and II 5-1
Transfer Matrices
5.1 Philosophy and Methodology 5.1-1
5.2 Transfer Matrices 5.2-1
5.3 Intercomparison of Transfer Matrices 5.3-1
5.4 Unification of Transfer Matrices 5.4-1
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
Phase
3..1
3.2
3.3
3.4
AES-LRT
ASTRAP
ENAMAP
OME-LRT
RCDM-2
MCARLO
MEP-TRANS
UMACID
II Data Bases
Emissions
Sensitive Receptors
Meteorology
Air Quality and Precipitation
Chemistry
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6. Conclusions and Future Plans 6-1
References R-l
APPENDIX A - List of Modeling Subgroup Reports and A-l
and Other Documents
APPENDIX B - Transfer Matrices for the Phase II B-l
Data Bases
APPENDIX C - Initial Inventory of Mesoscale Models C-l
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-5-
LIST OF FIGURES
Page
Figure 2-1. A Portion of the AES Annual S02 Emissions 2.1-6
Inventory in Kilotonnes S02/Year on the
127 km Grid
Figure 2-2. Calculated and Measured Sulfate Air 2.1-10
Concentrations for July 1978
Figure 2-3. Daily Sulfate Concentrations at the SURE 2.1-11
Toronto Site in July 1978
Figure 2-4. Fractional Change in the Annual Wet Sulfur 2.1-15
Deposition at Muskoka as a Function of the
Fractional Change in Parameter Values
Figure 2-5. Puff Advection and Diffusion Scheme Used in 2.3-4
ENAMAP
Figure 2-6. Schematic Diagram of the OME-LRT Scavenging 2.4-4
Model
Figure 2-7. Total Annual Wet Deposition of Sulfur Per Unit 2.4-14-
Emission Plotted on Log-Log Scale as a Function
of the Model Parameters Being Varied for a
Receptor 200 km East of an Idealized Source
Figure 2-8. RCDM-2 Sensitivity Results 2.5-12
Figure 2-9. SO2 Emission Inventory Grid Used in the CAPITA
Model (104tons S02/year/grid) 2.6-3
Figure 2-10. Schematic of Probabilistic Decisions for the 2.6-6
Simulation of Kinetics.
Figure 2-11. Spatial Distribution of Yearly Average SURE 804: 2.6-9
Data and the Yearly Average of Simulated Sulfate
Concentrations for "Slow", "Average", and "Fast"
S02 Kinetics.
Figure 2-12 Plume Sulfur Budget Standard Conditions and . 2.7-10
(a&b) Noon-time Emissions
Figure 2-13 Plume Nitrogen Budget Standard Conditions and 2.7-11
(a&b) Noon-Time Emissions.
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Page
Figure 2-14. Sensitivity to Precipitation Rate 2.7-13
Figure 2-15. Location of Receptor Points 2.7-16
Figure 2-16. Source Regions Defined for Transfer Matrix 2.7-20
Derivation
Figure 2-17. The Probability Field (x 10"8 km~2) of 2.8-13
Potential Contribution to Observed Mass
Loading of Sulfate to the Adirondacks by
Wet Deposition for August, 1978 and August/
1979 as Computed by the ACID model.
Figure 2-18. The Probable Source Contribution (kg km"2) 2.8-14
to Observed Sulfate Wet Deposition in the
Adirondacks for Agust, 1978 and August,
1979 Based on the Potential for Contribution
Shown in Figure 2-17 and the Location and
Strength of Existing Sulfur Dioxide Sources
in the Grid Area.
Figure 3-1. Locations of Upper Air Wind and. Temperature 3-8
Observations in Eastern North America
Figure 3-2. Schematic Flow Chart of the Precipitation Data 3-10
Processing Programs
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Table 1-1.
Table 2-1.
LIST OF TABLES
Highlights of Activities Proceeding the Phase I
Work Group 2 Model Intercomparison and Evaluation
Effort
Sensitivity Index - Fractional Change in Wet
Deposition As a Function of Fractional Change
in Parameter Value-Annual (dlnDep/dln parameter)
Table 2-2A. Resultant Winds and Persistence Factors at 600
Meters for Input to the Annual Average Dispersion
Model Calculations (1970-1978)
Table 2-2B. Eastern Canadian Resultant Winds and Persistence
Factors at 600 Meters for Input to the Annual
Average Dispersion Model Calculations (1970-1979)
Table 2-3.
Table 2-4.
Table 2-5.
Table 2-6.
Table 3-1.
Table 3-2.
Table 3-3.
Table 3-4.
Table 3-5.
Sensitivity of 804 Wet Depostion to Variation
of Model Parameters
Parameters Choice for 1978 Model Simulations
Transfer Matrix of Total Wet Sulfur Deposition
(kg.S.ha.-J-yr'1)
Comparison of Predicted and Observed Wet Sulfur
Deposition at Targeted Sensitive Receptors
Phase II United States and Canadian SO2 Emissions
on a State and Province Basis (Kilotonnes/Year)-
1980
Phase II United States and Canadian S02 Emissions
for the 63 ARMS Areas (Kilotonnes/Year)-1980
Combined United States-Canada Top 50 Sources of
S02 Emissions -1980
Phase II Targeted Sensitive Areas for Work Group-2"
Modeling
Precipitation Statistics for Use in Regional
Climatological Dispersion Models (1978)
Page
1-3
2.1-14
2.5-7
2.5-9
2.7-15
2.7-18
2.7-21
2.7-23
3-3
3-4
3-5
3-7
3-12
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Table 4-1.
Table 4-2.
Table 4-3.
Page
Table 3-6. Description of LRT Model Evaluation Sites - 3-14
Phase II
Table 3-7. Data at the LRT Model Evaluation Sites - 3-16
Phase II
Table 3-8. Calculated Wet Sulfur Depositions (in kg.S.ha.'1) 3-19
Table 3-9. Precipitation Amounts (in centimeters) at the 3-20
Regional Model Evaluation Sites
Comparison of January 1978 Monthly Average Model 4-5
Concentrations and Total Wet Sulfur Depositions
with Observations
Comparison of July 1978 Monthly Average Model 4-6
Concentrations and Total Wet Sulfur Depositions
with Observations
Comparison of 1978 Annual Average Model Concen- 4-8
trations and Total Wet Sulfur Depositions with
Observations
Table 4-4. Comparison of 1978 Annual Average Model Wet
Sulfur Depositions (kg.S.ha.~l) with Observations 4-9
Table 4-5. Mean and Standard Deviations of the Logarithmic 4-11
Bias Between Model Simulations and Observations
for 1978
Table 4-6. Logarithmic Statistics of Wet Sulfur Deposition 4-14
from the CANSAP Network
Table 4-7. Logarithmic Interval Statements of Wet Sulfate 4-14
Deposition for the CANSAP Network at the 95%
Confidence Level
Table 4-8. Logarithmic Statistics of Sulfur Dioxide Concen- 4-15
trations for the EPRI-SURE Network
Table 4-9. Logarithmic Interval Statements of Sulfur 4-15
Dioxide Concentrations from the EPRI-SURE Net-
work at the 95% Confidence Level
Table 4-10. Logarithmic Statistics of Sulfate Concentrations 4-18
from the EPRI-SURE Network
Table 4-11. Logarithmic Interval Statements of Sulfate Con- 4-18
centrations from the EPRI-SURE Network at the
95% Confidence Level
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Page
Table 5-1. Phase I Transfer Matrix of Annual Wet Deposition 5.2-2
of Sulfur (kg.S.ha.~lyr~l) Per Unit Emission
(Tg.S.yr'1)
Table 5-2. Phase I Transfer Matrix of Percent Contribution 5.2-4
to Annual Wet Sulfur Deposition
Table 5-3. Phase I Transfer Matrix of Annual Wet Sulfur 5.2-9
Deposition (kg.S.ha.~"lyr~l) Per Unit Emission-
(Tg.S.yr-1)
Table 5-4. Model Estimates and Observations of Annual Wet 5.3-5
Sulfur Deposition (kg.S.ha.~!yr.~l) at the Nine
Targeted Sensitive Areas
Table 6-1. Steps in the Model Evaluation Process 6-5
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.LlffT. PF. ABPREVIAT.IPNS
BRCG or RCG - Bilateral Research Consultation Group (U.S.-Canada)
MAP3S/RAINE - Multi-State Atmospheric Power Production Pollution
Study/Regional Acidity of Industrial Emissions
EPA - Environmental Protection Agency (U.S.)
AMS - American Meteorological Society
LRTAP - Long-Range Transport of Air Pollutants
AES - Atmospheric Environment Service (Canada)
CMC - Canadian Meteorological Centre
SURE - Sulfate Regional Experiment (EPRI)
UTM - Universal Transverse Mercator
EPRI - Electric Power Research Institute
ENAMAP - Eastern North American Model of Air Pollution
ASTRAP - Advanced Statistical Trajectory Regional Air Pollution
Model
1-D - one-dimensional
EURMAP - European Regional Model of Air Pollution
SRI - formerly Stanford Research Institute, now SR-I International, Inc.
UNIVAC - name of a computer company
NEDS - National Emissions Data System (EPA)
OME - Ontario Ministry of the Environment
GCA - formerly Geophysics Corporation of America now GCA Corporation
NOAA/ATDL - National Oceanic and Atmospheric Administration/
Atmospheric Transport and Dispersion Laboratory
RCDM - Regional Climatological Dispersion Model
TRI - Teknekron Research, Inc.
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-11-
CAPITA - Center for Air Pollution Impact and Trend Analysis
MEP - Meteorological and Environmental Planning, Ltd.
TRANS - Transport of Regional Atmospheric Nitrogen and Sulfur
APN - Air and Precipitation Monitoring Network (Canada)
CANSAP - Canadian Network for Sampling Precipitation
NADP - National Atmospheric Deposition Program (U.S-.)
ACID - Atmospheric Contribution to Inter-Regional Deposition
DOE - Department of Energy
ARMS - Acid Rain Mitigation Studies
RMS - Root-mean-square-error
RMSB - Standard deviation of residuals
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1-1
1. INTRODUCTION
The Atmospheric Sciences and Analysis Work Group under
the Memorandum of Intent on Transboundary Air Pollution is
charged with describing the transport of air pollutants from
their sources to final deposition, especially acidic deposition
in ecologically sensitive areas. The Work Group has structured
its activities in Phase II into three areas with the following
purposes:
1. Atmospheric Science Review - assess the appropriate-
ness of the methods and assumptions used in regional
models to quantify source-receptor relationships;
2. Regional Modeling - document, evaluate, intercompare
and apply available practical regional models; and
3. Data Analysis Review - use data to establish indepen-
dently (1) the usefulness of models and (2) the validity
of computed source-receptor relationships.
The regional modeling work is being done in a modeling
subgroup consisting of Work Group 2 members and participating
modelers who are directly involved with the operation of the
selected models or are interested in advancing the science
of model evaluation and intercomparisons.
The techniques of regional model evaluations and inter-
comparisons have not been fully developed, but some progress
has been made as a result of recent workshops on Regional
Models (Pt. Deposit, Maryland, November 1979) and Short Range
Dispersion Model Performance (Woods Hole, Massachusetts,
September 1980).
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1-2
In the latter part of Phase I, the Modeling Subgroup of
the U.S.-Canada Research Consultation Group (RCG) and Work
Group 2 prepared a plan (Smith and Whelpdale, 1981) for (1)
the further development of model evaluation and intercompari-
sons using the mechanism of regular workshops as well as for
(2) the actual conduct of the activity to meet the specific
needs of Work Group 2 in Phases II and III. -
The highlights of activities that proceeded the proposed
Work Group 2 model evaluation effort (see Table 1-1) showed
that the Research Consultation Group (RCG), the MAP3S/RAINE
program, and Work Group 2 all have directives and specific
needs for intercomparison and evaluation of regional models.
The" work plan developed by Work Group 2 provided for the
participation of all these groups so that there was some
integration and coordination of their efforts over the next
year.
The purpose of this report is to describe the progress
to date on the model evaluation and intercomparison work
plan. In Chapter 2, the documentation of the selected models
is summarized. The complete documentation of each model is
presented in a series of separate "profile" reports (see
Appendix A). The Phase II data bases on emissions, sensitive
receptors, meteorology, and air quality and precipitation
chemistry are described in Chapter 3. The model simulations
are compared to a standard data set in Chapter 4 using agreed
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1-3
Table 1-1: Highlights of Activities Preceeding the Phase II
Work Group 2 Model Intercomparison and Evaluation
Effort
February 1980
March 1980
June 1980
June 1980
July 1980
September 1980
November 1980
November 1980
December 1980
Establishment of the RCG Subgroup on Atmos-
pheric Transport and Deposition Modeling and
directive to sponsor an evaluation of opera-
tional sulfur deposition models.
Announcement of the MAP3S/RAINE "Model-Off"
to intercompare the MAP3S regional models
using July 1978 data by August 1980.
Release of EPA Report on Research Guidelines
for Regional Modeling of Fine Particulates,
Acid Deposition and Visibility.
RCG Modeling Subgroup starts inventory of
regional models and status of their evaluation,
Release of Initial Data Bases for Inter-
comparison of Regional Air Quality Simulation
Models by the EPA Acid Rain Assessment
Team.
EPA/AMS Workshop on Short-Range Dispersion
Model Performance.
Release of Second RCG Report on LRTAP con-
taining an initial intercomparison and evalua-
tion of several regional models and the
recommendation for a series of workshops on
model intercomparisons leading to a report.
Release of the work plan for Work Group 2
calling for an intercomparison and evaluation
of each reference model.
Release of the draft of the RCG Modeling Sub-
group Report on Modeling Inventory, Analysis,
and Recommendations.
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1-4
upon statistical criteria. In Chapter 5, the transfer matrices
from the participating models are analyzed in an attempt to
quantify the effect of their uncertainty on the assessment
iteration results. Finally, the interim conclusions and future
plans are presented in Chapter 6. Two appendices containing
(1) the list of Modeling Subgroup reports and other documents
and (2) the Phase II transfer matrices are provided at the
end of the report.
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2.1-1
2. SUMMARY P.P. W3D.E.L. PRPF.ILEJ3
2.1 AES-LRT
Qyejc vie w; • _
The modeling approach in the AES program has been to
develop a modular system over the next few years. The first
step has been the development and implementation of a capa-
bility for three-dimensional trajectory analysis (Olson et al.,
1978). The model uses objectively-analyzed wind fields and
computes vertical motions at the following four pressure
levels: 1000, 850, 700f and 500 mb. Input wind fields are
available every six hours on the standard Canadian Meteoro-
logical Centre grid of 381 km at 60° N and interpolation
routines are used to obtain winds at intermediate positions
in time and space. Trajectory segment endpoints are deter-
mined during each time-step by forward time-dimensional wind
field until horizontal and vertical convergence criteria are
reached. The motion of air parcels can be followed backward
(receptor mode) or forward (source mode) in time from anywhere
in North America.
The next step has been the development of a concentration/
deposition box model based on the trajectory model. Air
parcels follow the trajectories across grids of pollutant
emission, monthly mixing height and daily precipitation
amount. Uniform mixing is assumed to occur in the vertical
up to the mixing height, and transformation and removal
processes are linearly parameterized (Olson, et al, 1979).
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2.1-2
The Trajectory Model
The trajectory model assumes a constant acceleration
between endpoints so that an iterative scheme is used to
determine the trajectory endpoint positions. The trajectory
starting points can be located anywhere in the North American
domain between 1000 and 500 mb. Trajectories are normally
computed backward for four days at 6 hour intervals from
selected receptor locations. The wind data are objectively
analyzed at the Canadian Meteorological Center (CMC) every
six hours onto a 381 km grid superimposed on a polar stereo-
graphic projection true at 60°N. The analysis procedure is
in routine operational use and is essentially a three dimen-
sional scheme that incorporates hydrostatic and wind-height
gradient balance routines (Rutherford, 1977), and produces
gridded u and v wind component analyses.
In order to simulate the ascent of parcels through low
pressure areas and descent through high pressure areas, grid
point fields of vertical motion are computed every 6 hours.
In our estimation, the Haltiner technique adequately repre-
sents atmospheric vertical motions and allows air parcels to
rise and fall, so that the trajectories pass through changing
wind regimes permitting the important and substantial influence
of vertical wind shear to affect the parcel trajectories.
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2.1-3
No modifications are made to the analyzed wind components
(u,v) at the upper levels (850, 700, 500 mb). However, due
to the occasional lack of observed wind data at the 1000 mb
level, the geostrophic assumption has a strong influence in
the objective wind analysis and a frictional turning term
(linearized friction coefficient, Anthes, 1978) is applied
to the 1000 mb wind components to take partial account of
the ageostrophic component or cross-isobar flow.
The Concentration/Deposition Model
The model is based on a North American subset of the
Canadian Meteorological Center hemispheric grid. The one-
layer model parameterizes the physical and chemical processes
•
within a box of unit area cross-section which extends
vertically from the ground to the mixing height. The mixing
layer is regarded as being capped by an inversion and pollutant
removal is linearly parameterized by wet and dry deposition
and chemical transformation. Pollution input to each box is
provided from an annual, North American, SC>2 or N02 emissions
inventory on a 127 km grid (Voldner and Shah, 1980) and
instantaneous mixing occurs throughout the box.
The boxes follow trajectories that have been previously
computed and stored by the trajectory model. At each time
step (3 hours) there is a pollutant input from the inventory,
a chemical transformation and a surface deposition. The
combination of these processes results in a new concentration
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2.1-4
value within the box. The new concentration value is carried
over to the next point where the process is repeated. An
improved numerical procedure using the trapezoidal rule,
which assumes a linear parameter change during the timestep,
has recently been satisfactory tested.
If there is only one trajectory associated with a receptor
then the final concentration in the box is assumed to be the
final surface concentration. If there are several trajectories
arriving at different levels above a receptor, the concentra-
tions are averaged to form a final surface concentration for
the receptor. For the Work Group 2 study, only trajectores
starting from the 925 mb level have been used.
The simplified conservation equations describing the
movement, emissions input, transformation and removal of
sulfur dioxide and sulphate are given in parameterized form
in terms of pollutant concentration by:
dcl (vdl t alp> cl (2-1)
"" = - -*tci + fi Q
dt H H
dc2 (Vd2 + a2?> C2 +1 kt cl + f2 Q (2 -
_ a - ^^^^^ 2 H
dt H
the coupled equations (2-1) and (2-2) are solved in Lagrangian
form and represent the change of pollutant concentration in
an air parcel following a trajectory due to deposition, trans-
formation and source input.
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2.1-5
GI and C2 are the atmospheric concentrations of sulfur
dioxide and sulfate respectively. H represents the climato-
logical mixing height field which has been gridded over North
America on the 127 km polar stereographic grid on a monthly
basis. A typical grid point has a monthly average value of
about 500 m in winter and about 1500 m in summer in eastern
North America.
Annual sulfur dioxide emissions are gridded on the 127 km
grid and are represented by the parameter Q. The value at
each grid point represents a uniform emission over a grid
square. Sub-grid scale removal of sulfur or transformation of
sulfur dioxide to sulfate can be approximated by the factor
"f" applied to the inventory. Normally the factors are one
and zero respectively. A portion of the inventory is shown
in Figure 2-1.
The sulfur dioxide to sulfate transformation rate, kj-,
has been given a value of 1%/hour.
Dry deposition is parameterized in terms of a deposition
velocity, V^i for SC>2 and V^ f°r 804. For the Phase I and II
work, V<3i had the value 0.5 cm/sec and V^ had the value
0.1 cm/sec.
Wet deposition is parameterized by scavenging ratios
for SC>2 (aj_) and 804 (33) and also requires a gridded
daily array of precipitation amount (P). For the Phase I
and II work, a-^ had the value 3 x 104 and &2 na^ tne
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2.1-6
99 217 2]
120 k?* 559 .18? 106 156 183
368 77 128 1
5 236 106'' 13 50 liu i«... ^7
-
I 123 ft 3 316
» / 55 159 12t« 32 66 76 \?.k fi:
n o
Figure 2-1. A Portion of the AES Annual SC>2 Emissions
Inventory in Kilotonnes S02/Year on the
127 km Grid
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2.1-7
value 8.5 X 105. Daily precipitation amounts from North
America meteorological networks were analyzed at the Canadian
Meteorological Center onto the 127km grid for use by the AES-LRT
concentration model. The precipitation fields are somewhat
smoothed but still retain the essential precipitation intensity
patterns and give realistic annual station totals of about
700-1100 mm.
For the purposes of the Phase 1 and II work, the North
American emissions inventory was subdivided into 11 regions,
8 in the U.S. and 3 in Canada. Seven American regions were
delineated by groups of the 127 km grid squares which
approximated as closely as possible, the SURE-UTM 80 km
emission grid groupings and state boundaries (WG II, Phase I
report). The eighth region consisted of the remainder of
the U.S. emissions in the SURE domain. The three Canadian
regions consisted of Ontario, Quebec and the Atlantic Provinces
respectively. The receptors or sensitive areas were simply
designated as trajectory end-points in terms of latitude and
longitude and the concentration model computed concentrations
and depositions at these points.
Evaluation of the Trajectory Model
Trajectories from the AES trajectory model have been
compared to trajectories computed from various European and
American trajectory models and are shown elsewhere (Olson,
et al., 1978). Trajectories computed at levels above the
surface (i.e. 925 and 850 mb) intercompared more closely
than surface (1000 mb) trajectories.
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2.1-8
Trajectories have been computed for specific time periods
to assist in the analysis of measured air quality data during
field studies. The trajectories have provided useful infor-
mation concerning air parcel movements and some examples are
shown elsewhere (Anlauf, et al., 1980).
A numerical analysis of the trajectory model has been
conducted and a report is presently being prepared (Walmsley,
et al.f 1981). An analytic non-divergent wind field was
formulated to simulate a real atmospheric wind field and was
used to intercompare the model trajectory positions with the
analytic solutions to the trajectory equation. No serious
deficiencies were found in the formulation of the model and
the largest source of error seemed to be in the horizontal
interpolation routines. The use of cubic interpolation was
shown to give smaller errors than the present linear inter-
polation, but would require a significant increase in compu-
tation time. The errors associated with the present numerical
formulation were shown to be minor compared to uncertainties
in the meteorological data.
Evaluation of the Concentration Model
A preliminary evaluation was reported elsewhere (Olson,
et al., 1979) and a more complete model evaluation using
EPRI-SURE data for October 1977 was also reported elsewhere
recently (Voldner, et al., 1980).
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2.1-9
A comparison between the ENAMAP-1 model and the AES-LRT
model was shown in the second BRCG report (November 1980).
Figure 2-2 shows the sulfate concentration for July 1978 as
computed by the AES-LRT model, the ENAMAP-1 model and the
measurements from the SURE and Ontario Hydro networks. Both
models show maximum concentration at approximately the same
location (southwestern Pennsylvania) and of about the same
magnitude (12-14 ug/m3). The concentrations from both
models decrease to about 2 ug/m3 in northern Ontario and
Quebec and both models show a similar NE-SW pattern orien-
tation. The highest measurements of 15-17 ug/m3 are distri-
buted from Illinois through Pennsylvania but show about the
same overall pattern orientation as the model patterns.
Figure 2-3 shows a comparison between daily measured sul-
fate concentratins from the SURE network and the daily average
concentrations from the AES-LRT model at Toronto, Ontario, for
July 1978. Both the model and the measurements show four main
episodes and they are approximately coincident. The model is
also showing approximately the proper relative magnitudes
compared to the measurements.
The AES-LRT model is continually being evaluated using
network data and a summary of the current evaluation statistics
for the Phase II model for January, July and the entire year
1978 are given in Chapter 4 and the AES-LRT Model Profile.
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2.1-10
—£-T?J— . -
9XSolid lines: SRI ENAMAP-1 model results
CBhumralkar et al., 1980)
^! Dashed lines: AES LRTAP model results
^K (Olson, 1980)
/ Q Ontario Hydro
(__ ^Available measurements md.caled as c\ioc
'. \f\ * oUnt
(All values are in units ol 10"6 g/m3)
Figure 2-2. Calculated and Measured Sulfate Air Concentrations
for July 1978
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2.1-11
40.
o
z:
010.
o
5.
("i"V I I ( 1 i V J
i i j i \ i i | M i i j
Dashed Line = Computed Concentration
Solid Line = Measured Concentration
_L.iJ_V.L_(
IJLJUU J.,1 I.J4JLJU .I..1.J
5.
15. 20. 25.
DRTE
35.
Figure 2-3.
Daily 804 Concentrations at the EPRI-SURE
Toronto Site in July 1978
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2.1-12
Model Sensitivity
The sensitivity of modeled concentrations and deposition
amounts of sulfur compounds at the sensitive receptors (Phase I)
to changes in values of input parameters and parameterization
has been investigated. Dry deposition velocities and washout
ratios for sulfur dioxide and sulfate and the conversion
rate of sulfur dioxide to sulfate were varied within the
range normally accepted for long range transport modeling
(Voldner et al. 1980). Mixing height was held constant over
the continent or allowed to vary monthly and spatially. A
numerical scheme using the trapezodial rule for the solution
of the concentration equations was tested. Model sensitivity
to initial background concentration was also examined. Com-
putations were also made where the parameters were assigned
representative summer and winter values. The model parameters
and changes in parameterization were varied one at a time
from the "base case value" used in Phase I. The results
from these studies have been reported in the full AES-LRT
model profile.
In summary, dry deposition of sulfur dioxide and wet
deposition of sulfate are the principle removal mechanisms
for sulfur in the base case. Thus changes in the dry
deposition velocity of sulfur dioxide, the transformation rate
of sulfur dioxide to sulfate and the washout ratio of sulfate
results in the largest changes in the wet deposition of sulfur.
-------
2.1-13
This is clearly illustrated in Table 2-1 by the magnitude of
the sensitivity indices in the rows: V^SC^, k, 0^304 and also
by the slopes of curves for the same parameters for
the Muskoka site.
The sensitivity index is defined as the fractional
change in wet sulfur deposition (A) as a function of the frac-
tional change in parameter value (P) i.e./ (dlnA/dlnP). The
curves in Figure 2-4 show log A versus log P.
The model was insensitive to the modified numerical
scheme. The model showed greater sensitivity to an assumed
initial sulfate background concentration (5 ug/m^) than to
the assumed initial sulfur dioxide background concentration
(10 ug/m^), especially at remote sites. In most of the
sensitivity tests, the degree of sensitivity was site depen-
dent. More remote sites were sensitive to parameters affecting
sulfate changes and sites closer to emission regions were
more sensitive to parameters affecting sulfur dioxide changes.
-------
Table 2-1: Sensitivity Index -^ Fractional change in wet deposition as function of fractional
change in parameter value - annual (d In Dep/d In param)
,--•->--•-• ,....._ 5.. _
Parameter
and Range
vdso2
0.2-1.5 cn/s
VdS04
0.1-0.6 cn/s
'
k
0.3-1.5%/hr
*S02
3 x 103 - 3 x 104
*S02
3 x 104 - 3 x 105
*S04
8.54 x 104-1.7 x 106
H (Mixing Height)
0.5 x Base H)-
Base H
H (Mixing Height)
BNDW
-0.55
-0.14
0.49
0.07
0.21
0.34
0.22
i
0.0
ALG
-0.52
.
-0.16
0.55
0.06
0.16
0.39
0.12
'
-0.14
I
MUSK
-0.50
-0.15
0.58
0.06
0.18
0.41
0.13
-0.15
*ECEPTOR£
QUE
-0.59
-0.17
0.56
0.05
0.15
0.37
0.28
0.01
3
SNSC
-0.64
-0.28
0.62
0.04
0.11
0.46
0.37
0.04
VTOH
-0.53
-0.15
0.54
0.07
0.18
0.36
0.17
-0.05
ADIR
-0.53
-0.16
0.57
0.06
0.16
0.39
0.22
-0.08
PENN
-0.40
-0.12
0.55
0.08
0.28
0.42
-0.11
-0.31
SMOKIES
-0.49
-0.19
0.58
0.06
0.21
.49
-0.05
-0.24
ro
•
i—>
i
Base H-(2x Base H)
-------
Figured 2-4.
Fractional Change in the Annual Wet Sulfur Deposition
at Muskoka as a Function of the Fractional Change in
Parameter Values
log (mode? parameter)
-------
2.2-1
2.2 ASTRAP
Overview;
The Advanced Statistical Trajectory Regional Air Pollu-
tion (ASTRAP) model (Shannon, 1981) consists of three main
subprograms; vertical diffusion, horizontal dispersion, and
calculation of surface concentrations and deposition.
Programs for data preparation or presentation of output are
not considered a part of the basic model, since such programs
are usually tailored to a particular application.
Vertical Diffusion Subprogram
The vertical diffusion subprogram contains the dry deposi-
tion and chemical transformation algorithms, as well as a one-
dimensional numerical solution of the standard diffusion equa-
tion by the Gaussian Moment-Conservation technique (Shannon,
1979). Dry deposition is parameterized by the usual applica-
tion of deposition velocities; the major differences between
dry deposition in ASTRAP and that in most other LRTAP models
are that deposition velocities in ASTRAP are a function of
time of day and of season, and that SO2 and 804 deposition
velocities are almost equal in magnitude. The chemical
transformation rate also has diurnal and seasonal variations;
ASTRAP simulations are relatively insensitive to the diurnal
variation, however.
-------
2.2-2
There is- an increased transformation rate during the initial
dispersion (first three hours) for emissions from lower layers,
in order to simulate the effects of increased catalytic trans-
formations in more polluted urban areas. The transformation
rate increase in % hr~^ is specified to be
&Tr = (t-4)*(L-3)/2, t_<4, L<3 (2-3)
= 0, otherwise,
where t is the plume age in hours, and L is the layer indicator
(L = 1 is the 0-100 m layer).
The basic transformation rate varies by season and hour,
with summer and winter midday peak rates of 3.0 and 1.5% hr~^,
respectively, and average rates of 1.1 and 0.48% hr~l,
respectively.
The dry deposition velocities for SC>2 and 804 during
summer have midday peak values of 0.85 cm s~l and average values
of 0.41 cm s'1 for SO2 and 0.46 cm s-1 for SO4. For winter the
midday peak value is 0.65 cm s~l and the averages are 0.25 cm
s"1 and 0.28 cm s"1 for S02 and S04, respectively. During the
first six hours of dispersion the summer means are 0.45 cm s~l
1 = -I
(SO2> and 0.56 cm s (S04); the winter means are 0.28 cm s"-1-
(S02) and 0.39 cm s"1 (s54).
Eddy diffusivity profiles simulate the nocturnal surface
inversion cycle of formation, deepening, and erosion from
below. The values range from 1 to 40 m2 s~l. During the
first 6 hours of dispersion, the lower layers of the model
are not permitted to become stable, however.
-------
2.2-3
The rationale for adjusting the dry deposition velocities
and the stability profiles during the first 6 hours of dis-
persion is that emissions in the lower layer of the atmosphere
occur primarily in urban areas, where the heat island effect
and increased roughness result in decreased lower level
stability and aerodynamic resistance to dry deposition. Thus,
the average deposition and stability patterns for the whole
of eastern North America are adjusted during initial dispersion.
A diurnal variation in the emission rate is also included
in the vertical diffusion subprogram. The variation is a maximum
in the surface layer, and decreases with increasing layer,
until the variation about the average emission rate becomes
zero in the sixth layer (600-800 m). The emission rate varia-
tion is an arbitrary estimation of the effect of diurnal
variations of heating and cooling loads, working hours, and
the like.
The number and thickness of the layers in ASTRAP has
been changed several times, and is a simulation option in the
vertical diffusion subprogram. Since the eddy diffusivity
profiles and emission inventories are specified by layer,
they must be reestimated or relocated each time layer defini-
tion is changed. In computations it is most efficient to
have few and thick layers; however, thick layer definition
reduces the ASTRAP resolution of the nocturnal inversion
cycle and effective stack heights. The most recent ASTRAP
-------
2.2-4
simulations have used nine layers; four of 100 m, three of
200 m, and two of 400 m depth. The total model depth is
thus 1800 m; currently all effective emission heights fall
within the first six layers (lowest 800 m).
Separate vertical profile calculations are made for 302,
primary 804, and secondary 804 (i.e., that produced by
atmospheric transformation of 803) from emissions with each
of the lowest six layers. The advantage of calculation in
this structure is that scenarios of sulfate emission factors
as a function of fuel type, source type, or source region, or
scenarios about different stack heights, can be examined later
without recalculation of profiles.
The output of the vertical diffusion subprogram, for- each
emission layer, are the normalized surface concentrations of
3 =
802, Primary 804, and secondary 804, the normalized mass budget
of each, and the normalized dry deposition of each during the
time increment, all as a function of plume age.
Horizontal Dispersion Subprogram
The horizontal dispersion subprogram utilizes the concept
that long-term diffusion in the horizontal is determined by
the distribution of the plume centerlines rather than by small-
scale diffusion about the centerlines. For a grid of virtual
source locations, simulated tracers are released at six-hour
intervals from each source and transported in a time series
of objectively analyzed wind fields. The distribution of
endpoint locations (number, mean position, and spread) as a
-------
2.2-5
function of plume age (time since release) are computed for
each source. The statistics are calculated and stored for
six-hour increments from 3 to 117 hours. The number of
tracers contributing to each statistic is stored for weighting
purposes, as each endpoint ensemble is composed of a slow
subset of the ensemble for the previous time, due to tracers
being transported out of the computational grid, and as
tracers are subject to depletion by wet removal.
Wet removal simulation is accomplished by first advecting
the tracer for a six-hour time step and then checking the new
location to see whether precipitation has occured during the
six-hour period. If so, a fraction F of the mass represented
by the tracer is deposited as a function of the half power of
the precipitation amount (Hicks and Shannon, 1979),
F = minimum |(h/8)1/2f 4/5J (2-4)
where h is the precipitation amount in mm/6 hours; the
maximum removal for any precipitation event is 80% in order
to simulate the vertical transport of pollutant mass to the
free troposphere by convective processes. Removal of the
80% limitation, which is admittedly an arbitrary choice of
parameter value, would result in a wet deposition pattern
somewhat more oriented towards sources.
In some previous ASTRAP simulations, the coefficents
in the wet removal parameterization have been different from
those shown above, but a half-power formulation has always
been used.
-------
2.2-6
The tracer portions deposited are stored by plume age
for each source, and statistics similar to those for dry
tracers are generated. The fractional "dry" tracer remaining
after a precipitation event is (1-F) times the fraction at
the beginning of the event. The so-called dry tracer is one
not subject to wet removal.
The statistics generated by the horizontal dispersion
program, for a grid of virtual sources and for each increment
of plume age, are the mean position (1(,T), the standard
deviation of the endpoint ensembles (<5£, <3y), and the number
of equivalent dry tracers contributing to the statistic, for
both dry tracers and wet-deposited tracers. Note that these
statistics are independent of sulfur species, because the
wet removal applies to bulk sulfur.
Concentration and Deposition Subprogram
Statistics from the main subprograms are combined with
an emission inventory, including primary sulfate emission
factors, to produce output in a non-normalized form. The
subprogram combines the horizontal distribution statistics
of dry tracers with the normalized 1-D surface concentrations
and dry deposition increments, combines the horizontal distri-
bution statistics of wet tracers with the normalized 1-D
mass budgets, and sums the resulting concentrations and
deposition from each source for a regularly spaced receptor
grid, or for a list of receptor locations. In this sub-
-------
2.2-7
program, scenarios involving different emission distributions
in time and space are easily and economically tested. Scenario
testing of parameterizations such as the dry deposition velo-
cities or wet removal of bulk sulfur involves re-running one
of the other subprograms as well.
Basic products of ASTRAP simulations are regional long-
term average (monthly or annual) fields of SO2 and 804 concen-
trations, and cumulative wet or dry deposition of total sulfur.
Dry deposition can be sub-categorized as dry deposition of SO2
and of 864; however, the wet removal parameterization is for
bulk sulfur and thus speciation is not possible. By inte-
gration of the deposition fields for specified subregions
»
of the grid (such as the eastern U.S. or eastern Canada) a
sulfur budget is also obtained routinely.
Transfer matrices are produced with ASTRAP by separate
calculation and storage of the effect upon each receptor
region for each source region. For such calculation each
source region emission rate is normalized.
Generally speaking, ASTRAP simulations do not require
smoothing for graphical presentation, because the combination •
of limited resolution in wind, precipitation, and emission
data effectively acts as a smoothing operator. For special
applications, such as a point source in a region with hourly
tower winds, resolution can be improved, but in general ASTRAP
should only be applied in upper meso- to regional-scales and
monthly or seasonal time scales.
-------
2.2-8
Adjunct Subprograms
Adjunct subprograms of ASTRAP objectively analyze wind
and precipitation fields, grid emissions horizontally and
vertically, and contour simulated concentration and deposition
fields on a background map of eastern North America.
The wind fields for ASTRAP are computed by first calcu-
lating the mean wind between the surface and height 1 km for
each rawinsonde observation, and then performing a form of
inverse distance-squared objective analysis at regularly
spaced grid points. The objective analysis scheme obviously
cannot improve upon the 12 hr and 200 km - 400 km resolution
of the raw data.
Hourly precipitation observations are summed for six
hours, and analyzed for a grid spacing of about 70 km. The
analysis method is an assignment of the nearest observation
to the center of each cell; this method avoids biasing
statistics of frequency and amount. If no observation site
is inside a grid cell, the nearest observation is used.
Emission data can be either a list of point sources,
with appropriate location and stack data, or a grid of virtual
sources, sorted by effective emission layer in either case.
-------
2.3-1
2.3 ENAMAP
Overview
In the mid-1970's, SRI, International developed a
trajectory-type regional air pollution model, EURMAP (European
Regional Model of Air Pollution), for the Federal Environ-
mental Office of the Federal Republic of Germany (Johnson et
al., 1978). This puff model is capable of calculating long-
term S02 and 804 concentrations and dry and wet depositions
patterns and international exchanges resulting from S02
emissions in each of 13 countries in central and western
Europe.
In the late 1970's, the U.S. Enviromental Protection
Agency (EPA) contracted SRI, International to adapt and apply
the EURMAP model to eastern North America. The first adapted
version of the model, ENAMAP (Eastern North American Model
of Air Pollution), was capable of calculating long-term S02
and 804 concentration and dry and wet deposition patterns
and regional and international exchanges of sulfur resulting
from the emissions of S02 and 804 in each of 13 regions in
the eastern United States and southeastern Canada (Bhumralkar
et al., 1980). Later, the model was revised by EPA to calcu-
late the concentrations, depositions, and inter-regional
exchanges from the S02 and 804 emissions from 52 American
and 12 Canadian regions in the same domain. It should be
noted that another version of the model is currently being
-------
2.3-2
produced. This version will replace the simplistic approaches
of parameterizing vertical mixing, dry deposition, and trans-
formation and will have -added nitrate chemistry by the end of
1981. During Phase II, the ENAMAP model parameterized dry
deposition of sulfur in a more complex manner.
Parameterizations
In Phase I, the ENAMAP model was capable of calculating
3
SC>2 and SO^ concentrations, wet and dry depositions, and
inter-regional sulfur exchanges across a 43 by 33 grid network
with a 70 km resolution and bounded by 30° and 50°N latitude
and 65° and 105°W longitude in approximately 6 minutes of
UNIVAC 1100 central processing unit (cpu) time. This cpu
time does not include the time required to grid the emissions,
wind, and precipitation data, which is performed by pre-
processors. In Phase II, the model domain was expanded to a
46 by 41 grid network bounded by 30° and 55° N latitude and
63° and 105° W longitude.
Basically, the ENAMAP model can be classified as a mass-
conserving Lagrangian puff model. Chemical processes within
each puff are parameterized as they move across the modeling
domain. As 3-hour intervals, the concentrations within and-
depositions from each puff are calculated. Immediately after-
wards, the concentrations and depositions are apportioned to
the grid cells on the basis of the portion of the puff area
in each of these cells.
-------
2.3-3
The rate of loss of mass of SC>2 (dM]/dt) and 804 (dM2/dt)
from each puff can be expressed by the following:
dMj. = -M(kt + kd + kw ) and (2-5)
dt * *
dM2 = -M(-3kt/2 + kd + kw ), where (2-6)
dT 22
M = mass
t = time
kj. = transformation rate of S02 to SO^ (h )
k^ = dry deposition rate (h~^)
kw = wet deposition rate (h ).
Discrete puffs of SO2 and 804 are released every 12 hours
from 80 by 80 km emission grid cells (see Figure 2-5). The
mass of pollutants in each puff is determined by dividing
the annual emissions by 730, the number of 12-hour periods in
a year. These puffs are tracked at 3-hour time steps until
they move outside the model domain or their concentration
drops to an.insignificant level, 0.01 ug/nr for S02 and
0.001 ug/m3 for S04.
Transport — The individual puffs are transported according
to the vertically-averaged and horizontally-interpolated
wind field applicable at that time. These fields are updated
after each time step of 3 hours. Transport wind fields are
generated at 3-hourly intervals using the receptor grid
-------
2.3-4
PUFFS ADVECTED WITH
-OBSERVED WIND FIELDj
AND TRACKED AT
3-HOUR TIME STEPS
S02 - SO?
AT ASSUMED
RATE OF 1%/HR
I EMISSIONS "PUFFS"[
I RELEASED EVERY
J.12 HOURS FROM
i EACH EMISSIONS
,GRID CELL
CONCENTRATION AND WET
AND DRY DEPOSITION
AMOUNTS ASSIGNED TO
EACH RECEPTOR CELL AT
EACH TIME STEP ACCORDING
TO CELL AREAS COVERED
BY PUFF
' DIFFUSION ASSUMPTIONS:"~T
; FICKIAN (M54) IN '.
j HORIZONTAL: UNIFORM
•fMIXING IN VERTICAL
UP TO MIXING HEIGHT
Figure 2-5. Puff Advection and Diffusion Scheme Used in ENAMAP
-------
2.3-5
network of 70-km spacing and the 12-hourly surface and upper-
air wind data available at several Canadian and about 50
United States sites. Upper-air data for Canada and the
United States are provided at the surface and at every 50 mb
level (1000, 950, 850, etc.)
At each data site, average u and v components of the
transport wind in the surface layer (between the surface, hg,
and the model mixing height, hi), are calculated by the
following formulas:
+ u i_i) / I
u = (hi-hi-i) /Mhi-hi-L) -' U-7)
i=2 2 i=2
_ — (2-8)
/ *—
i=2
where the subscripts denote pressure levels. The 43 by 33
transport wind grids are then generated from these layer
averaged wind components by a distance-weighted interpolation
scheme using the weighting factor
2
w = c (2~9L_
C2 + R2
where C is 2500 km and R is the distance (km) between the grid
point and the observation point.
-------
2.3-6
Diffusion —• Since diffusion on the regional scale is less
significant than the transport and removal processes, a very
simple treatment of the horizontal and vertical diffusion is
used in the current version of ENAMAP. Upon release, each
puff is assumed to immediately diffuse vertically to yield a
uniform concentration in the layer between the surface and
the mixing height. In the model, the mixing height (H),
expressed in km, does not vary with latitude, but does vary
seasonally using the relationship.
H = 1.3 + 0.15 S, (2-10)
where S = -1 in winter, +1 in summer, and 0 in spring and
fall (1.15
-------
2.3-7
Transformation — Although it is recognized to be a signifi-
cant, yet complex process over long-range transport distances,
the model parameterization of S02 transformation to 804 is
very simplistic. In the ENAMAP model, the transformation
rate is constant throughout the modeling period: it does
not vary with latitude, season, time of day, or precipitation.
A value of the transformation rate (1%/hr) was chosen after
a review of field, laboratory, and theoretical studies was
conducted by SRI, International.
Deposition — Of all the parameters in the ENAMAP mqdel/ dry
deposition is probably the most challenging to parameterize.
However, to simplify the parameterizations in Phase I, the
S02 and 864 dry deposition rates were treated as constant
throughout the simulation period and did not change diurnally
or seasonally. Therefore, the model actually simulated
nocturnal dry deposition, which in reality is near zero.
For Phase I, the dry deposition rate for SO2 (0.037h~^) was
= _i
approximately five times greater than that for S04 (0.007h J-).
For Phase II, a more complicated parameterization of
the dry deposition process was incorporated into the model.
With the new parameterization, SC>2 and 804 dry deposition
rates were dependent on land-use, season, and stability.
The most significant aspect of this new parameterization was
the 0.07 cm/sec dry deposition velocity for S02 and 804 at
night time.
-------
2.3-8
The wet deposition calculations are based upon hourly
precipitation rates (mm/h) and the duration of puff exposure
to the precipitation. The model does not distinguish between
rain and snow scavenging. Every three hours, the model
determines via preprocessed, objectively-analyzed, three-
hourly precipitation fields, the precipitation intensity in
the vicinity of the puff. Within each three-hourly simulation
period, an average hourly precipitation rate is determined.
This rate and the washout coefficients (0.28h for SC>2 and
0.07h for S04) are multiplied together to determine the
3-hour amount of wet deposition removed from the puff.
Precipitation data with a resolution of 6 hours were
obtained from less than 200 observation sites within the model
domain in Canada and the United States. In addition, precipi-
tation data with a resolution of 1 hour were obtained from a
very dense network of 2000 observation sites within the model
domain in the United States.
Precipitation fields were generated at 3-hourly intervals
using the same 70 km grid network used as the receptor grid
and the transport wind grid by applying three methods. First
of all, using the 1-hourly precipitation rates for the United
States, 3-hourly precipitation grids were generated simply
by averaging the rates observed at all the sites located
within each grid square. If sites were not located within a
grid square in the United States, a rate was obtained for
-------
2.3-9
that grid square by interpolating rates determined at adjacent
grid squares. Secondly, the 6-hourly precipitation rates for
the Canadian sites were used to generate precipitation fields
at 6-hour intervals via the interpolation scheme used for the
generation of the transport wind fields. From these 6-hourly
fields, 3-hourly precipitation fields were generated by temporal
interpolation. Unfortunately, if rainfall occurred for any
length of time in one grid square, the model would treat the
precipitation as if it had fallen at a constant rate over the
3-and 6-hour period. Thirdly, since there were no observing
sites over the Gulf of Mexico and the Atlantic Ocean, precipi-
tation fields are generated at 3-hourly intervals using
hourly precipitation rates based on climatological summaries.
Emissions — Since the ENAMAP model is designed to_consider
primary sulfate emissions, both SO2 and 804 emissions are
gridded separately on an 80 by 80 km UTM grid network. The
=
SC>2 and 804 emission rates from both point and area sources-,
as reported in the 1977 Sulfate Regional Experiment (SURE)
inventory, are used for much of the modeling domain. Since
the SURE region did not cover the central United States,
National Emissions Data System (NEDS) SOX data, maintained
by the United States Environmental Protection Agency, are
used for the states of North Dakota, South Dakota, Nebraska,
Kansas, Oklahoma, Texas, and the portions of Montana, Wyoming,
Colorado, and New Mexico lying within the ENAMAP domain.
-------
2.3-10
These emissions applied to the 1975-1978 period. The NEDS
=
data did not distinguish between S02 and 864 emissions;
however, it was assumed that r for NEDS data was the same as
the r for SURE data where
S02 = r(SOx) (2-12)
SOT = 1 (1 -r)SOx (2-13)-
* 2 x
The values of r derived from the SURE data averaged 0.976 over
the four seasons.
The annual emission grids are generated by simply adding
the annual emission rates from all the point sources within
each grid square and the county-wide area sources of those
counties whose geographical center was located in the grid
square.
No attempt is made to consider natural emissions of SC>2
or 804. Emissions crossing the western boundary and entering
the modeling domain are also not considered by the model.
The model evaluation results are presented in Chapter 4.
Pollutant Fields — At 3-hour intervals, after__ea_ch_qf the_
pollutant puffs have been transported across portions of the
receptor grid network, the amount of SO2 transformed to 804,
the amount of SC>2 and 804 deposited from each puff, and
the resulting concentrations are determined. Immediately
afterwards, the 3-hour depositions are apportioned to the
receptor grid cells according to the percentage of the puff
-------
2.3-11
volume over each cell. The monthly SC>2 and 804 deposition
patterns are then obtained by summing the 3-hourly contribu-
tions of each puff within each receptor grid cell.
=
The monthly-mean SC>2 and 804 concentration patterns are
obtained in a similar manner. The mass of the pollutants in
each puff at 3-hour time steps is apportioned to the receptor
grid cells according to the percentage of the puff volume
over each cell. The concentration contribution from each puff
at the appropriate grid cells is determined after assuming
the mass of pollutant in the grid cell is uniformly dispersed.
The monthly-mean concentration patterns are obtained by summing
the 3-hour concentration contributions of each puff within
each receptor grid and dividing by the number of 3-hour periods
in the simulation period.
Since the model is run for the duration of the simulation
period, the impact of the emissions from a user-specified
emitting region on the concentrations and depositions in a
user-specified receptor region anywhere in the modeling domain
can be easily assessed. The model has been modified to
account for the impact of emissions from 64 emitting regions
on the same 64 regions.
-------
2.4-1
2.4 OME-LRT
Overview;
Several studies have shown that relatively simple models
can provide acceptable estimates of long-term SC>2 and 804
concentrations associated with long-range transport. Using a
numerically efficient statistical model, Fisher (1978) has been
able to compute sulfur deposition rates which are comparable
to those obtained from models such as that developed by
Eliassen (1978); (see also Johnson et al., 1978) which require
considerably more data input as well as computational effort.
In a recent paper, Fay and Rosenzweig (1980) have shown that
a simple analytical model based on the two-dimensional diffu-
sion equation is capable of yielding S02 and 804 concentration
estimates which compare rather well with measurements made
over the United States. Thus, there is empirical evidence
that simple models "work".
The OME-LRT model is statistical in the sense that the
physics of transport is parameterized in terms of statistical
parameters. The basic premise of this class of models is
that long-term concentrations are insensitive to short-term
fluctuations in meteorology. It is assumed that concentrations
averaged over periods of the order of a year reflect "mean"
patterns of the large scale meteorology. This allows one to
take a simple approach to the modeling of long-range transport.
-------
2.4-2
Parameterizations
The treatment of the removal of sulfur is similar to
that proposed by Rodhe and Grandell (1972) and used by Bolin
and Persson (1975) and more recently by Fisher (1978).
However, the submodel is more "physically" based and it will
be seen that it is capable of handling more general physical
situations that those by the model of Rodhe and Grandell
(1972).
The model is based on the idea of classifying pollutant
particles as "wet" and "dry". Wet particles exist during
precipitation and dry particles during dry periods. On a
long term, every travel time from a source is associated
with a certain amount of dry particles and a certain amount
of wet particles. Using this concept one can formulate
differential equations for the evolution of these particles
as a function of travel time from the source. In the formu-
lation, it is assumed that wet particles, released during
precipitation, retain their identity until they encounter a
dry period. Following Rodhe and Grandell (1972) it is
assumed that the average rate of "conversion" from wet to
dry particles is inversely proportional to the average length
of wet periods in a Lagrangian sense. A similar assumption
can be made regarding "conversion" of dry particles to wet
particles. Further, it is assumed that the scavenging
coefficients do not vary with travel time, but are different
-------
2.4-3
for wet and dry periods. If we denote S02 by G and 864 by S,
their evolution can be conveniently shown in Figure 2-6. In
the figure A refers to the S02 scavenging coefficients, k
is the S02 to 804 conversion rate,Xis the 804 scavenging
coefficient, ^ is the average length of wet or dry periods,
and subscripts 'd1 and 'w1 refer to dry and wet particles.
We see that the 'species' Gd(dry S02) is depleted through wet
(%w) and dry deposition (X^), conversion to sulfate (kd)
and conversion to wet S02(l/ d). We also note that wet S02
is converted to dry S02 at a rate given by (l/trw). The
evolution of sulfate as a function of travel time is modeled
in a similar manner. It is important to note that the parti-
cular form of the conversion from dry to wet particles or
vice versa is based on the assumption that the cumulative
frequency distribution of wet or dry periods is exponential
(Rodhe and Grandell, 1972). From the diagram we can immedi-
ately write down the equations for G and S.
- 1_ Gd + 1__ GW (2-14)
dt
dGw = - >vwGw - kwGw - 1_ Gw + 1__ Gd _ (2-15)
dSd - - ,\dSd + kdGd - 1_ Sd + 1_ Sw (2-16)
cTt ^d • Tw
dSw = •- ^wSw + kwGw - 1_ Sw + 1_ Sd (2-17)
-------
2.4-4
K
"c,
IA
K w
Figure 2-6. Schematic Diagram of the OME-LRT Scavenging Model
-------
2.4-5
If Qgo and QSQ denotes the amount of S02 and 804
released at the source we can write
Gd(0) = fdQSQ ; Gw(0) = fwQso (2-18)
sd(°) = fdQSQ i Sw(0) = fwQso (2-19)
4 4
In (2-18) and (2-19), fa and fw are the fractional dry and
wet periods at the release point. Details of the solution are
given in the complete OME-LRT profile report.
F.B. Smith (1980) concurrently has developed a scavenging
model based on equations almost identical to OME. In his paper
he provides considerable physical insight into the meaning of
wet and dry periods which determine the particle "type" as
used in the OME model. He also considers the effect of the
variation of rainfall rates on the evolution of G and S. The
significant conclusion of this study is that is is necessary
to differentiate between mobile wet and dry synoptic regions
in order to make realist estimates of sulfur depositon.
It is seen from the formulation of the model that one
can specify different removal rates for dry and wet periods.
This can be useful in sensitivity studies. For example, it
is easy to test the recent hypothesis (McNaughton and Scott,
1980) that the S02 to 804 conversion rate is higher during
rain than during dry periods.
-------
2.4-6
The transformation of SC>2 to 804 is a complex process
which depends on a number of physical variables such as solar
intensity and ambient ozone concentration, (see Wilson and
Gillani, 1978). For long-term modeling we assume that the
conversion rate is 1%/hr, a value which is an "average" of
field measurements made during dry periods.
Our knowledge of the conversion of SC>2 to 804 during rain
is almost non-existent. There is some indirect evidence
(McNaughton and Scott, 1980; Scott, 1980; MacCracken, 1978)
to indicate that in-cloud conversion of S02 to 804 can be greater
than 10%/hr. Scott (1980) suggests that more than 60% of the
sulfur in rain falling in summer is associated with S02. Then
it is reasonable to assume that the rate at which SC>2 appears
as sulfur in rain is limited by the rate at which SC>2 is
incorporated into precipitating clouds. The rate at which
clouds draw up the SC>2 is approximately given by w/z^ where w
is the mean updraft velocity at cloud base and z^ is the mixed
layer height, w is given by (Smith and Hunt, 1979)
w =pwR/M (2-20)
In (2-20), pw is the density of water, R is the precipitation
rate and M is the water content of the air entrained into
clouds. Typical values for these variables are M = 5 - 10 gm""-*,
R = 1 mm/hr and z^ = 1000 m. We then find that the "effective"
washout rate w/z^ for S02 is 2: 3 - 6 x 10~ s~ . This suggests
that one way of accounting for in-cloud oxidation of SC>2 to
-------
2.4-7
SC>4 is to add an effective washout rate to the actual wet
removal rate of S02« An alternative is to increase the oxida-
tion rate during precipitation. McNaughton and Scott (1980)
found that a 10%/hr rate was necessary to explain measurements
of sulfur in rain.
Washout of SC>2 is a reversible process which is a function
of pH of rain. The washout rate decreases with pH. For the
range of pH (4-5) usually encountered the scavenging rate
denoted by j is of the order of lO"^"1 (Garland, 1978).
Johnson et al. (1978) use a value of 6 x 10""5s~1(R = 1 mm/hr)
in their modeling study while Fisher (1978) is forced to use
10~"4g-l to explain the measured values of wet deposition.
These relatively high values for j are a consequence of the
additional "washout" associated with incloud conversion of
S02 to 804. We feel that using an increased washout for S02
is the most convenient way to account for in-cloud oxidation.
Increasing the conversion rate during precipitation (McNaughton
and Scott, 1980) has the unrealistic feature of enhancing the
sulfate concentration in the boundary layer.
Maul (1978) has inferred the value of the SC>2 washout
coefficient from a time series of ambient S02 concentrations.
He found that j could be described by the equation
j = aR (2-21)
-------
2.4-8
where a ^ 3 x 10~5. The linear dependence of j or R as well
as the magnitude of a suggests that the "apparent" S02 washout
could be dominated by incloud oxidation of S02« This idea
appears to be supported by the work of Eliassen and Saltbones
(1975) in which sulfur concentration in rain is related to S02
rather than 804 concentration. The effective j used in their
study is «4.0 x 10~5. On the basis of these cited values
for j we used 3 x 10~5S-1 in our work.
The precipitation scavenging of sulfate is represented
by a linear removal rate j. This assumption used by several
authors (Fisher, 1978; Johnson et al., 1978) is clearly
unrealistic for modeling precipitation events. However, it
is probably less critical for long-term estimates of wet
deposition. In our study we used j = 10~"4S-1 on the basis of
Garland's review paper (1978).
Measurements indicate that the dry deposition velocity
v^ of SC>2 is of the order of 1 cm s during daytime. As
suggested by Fisher (1978) we used vd = 0.5 cm s to compen-
sate for reduced deposition during stable nocturnal conditions,
Sulfate is primarily in the form of aerosol whose median
diameter is below 1 JJIR (Garland, 1978). For this particle
size range the deposition velocity is around 0.1 cm s~l. We
used v^ = 0.05 cm s for the reason given in the preceding
paragraph.
-------
2.4-9
We have little guidance on the magnitude of the parameters
and-t^. As they are Lagrangian variables defined with
respect to trajectories of air parcels they cannot be derived
from routinely available Eulerian (fixed point) meteorological
observations. Rodhe and Grandell (1972) have estimated these
parameters assuming a ratio between fixed point and Lagrangian
measurements. Slinn et al. (1979)- have made more reliable
estimates based on actual trajectories originating from Kansas
City. The averages of the January and July, 1975, values are
"Cd = 46 hours and t^ = 7 hours which are comparable to those
suggested by Rodhe and Grandell (1972).
A table in the complete OME-LRT model profile presents
all the model parameters used in the simulations.
The long-term concentration C(r, t) at point r at time t
can be written as (Lamb, 1980)
C(r, t) = Q J p(r, t rg, t1)dt' (2-22)
where Q is the emission rate of the source located at rs and
p(r, tlrs, t1) is the probability density that a particle
I ~"
released at rs at time t1 will be found at j: at time t. To
proceed further we will assume that scavenging and dispersion
are independent. Fisher (1978) and Bolin and Persson (1975)
have used this assumption in their models. This then allows
one to express p as
P(r|rs; -TT) = M(-C) D(r|rs;t) (2-23)
^* I s>~ *w I .->^»
-------
2.4-10
where MCC") depends only" on removal mechanisms and D(r rx; "£")
is a function of large scale dispersion. It is easy to see
that M(tT) corresponds to the functions G^, G^f S^ and Sw for
unit release and is essentially the probability that a particle
will survive after a travel time 'Cr.
The dispersion function D(r rs;tr) will depend on large
scale wind patterns. Bolin and Persson (1975) and Shieh (1977)
have shown that the Gaussian puff equation is appropriate here
D(r r_; C-) = f(z,f) . .1 exp (x-x)^ Xy-y) (2-24)
••• 1 <*• Q •^^^•^^•^•^B^MM* 1 ^m .^MMBMM^K^B ™" I^JSb^Bldl^^B I
2TTtfx$y L 2<*X2 2<3y2 J
where £(z,t) describes the vertical dispersion. The para-
meters of the distribution x(t), y(tr)-are the coordinates of
the mean particle position after travel time from the release
point. The dispersion parameters
-------
2.4-11
sitive to the details of the vertical concentration distribu-
tion. Furthermore, Eliassen and Saltbones (1975) and Johnson
et al. (1978) have successfully predicted long-term averages,
assuming that sulfur is well-mixed through a boundary layer
which is invariant in space and time. On the basis of these
studies we took the distribution of SC>2 and 804 to be uniform
in the vertical through the depth of a constant mixed layer.
We should point out that this limits the resolution of the
model to distances of the order of 100 km from major sources.
The large scale horizontal distribution of pollutants is
determined by the parameters x, y, o"^ and <5y. For the coordi
nates of the mean motion of large scale eddies we assume that
x = u*^
(2-25)
y = 0
where u is the mean velocity of synoptic eddies and t: is the
travel time from the source. Equation (2-25) expresses the
fact that at mid-latitudes weather systems move from the west
to the east. Fay and Rosenzweig (1980) have used this assump
tion in their modeling exercise.
The analysis of trajectories by Slinn et al (1979) and
Bolin and Persson (1979) suggests that <5£ and dy can be
expressed as
< =
-------
2.4-12
On the basis of statistical dispersion theory it is reasonable
to assume that 6"^ and 100 kTonnes/yr S02) point sources listed in the above
mentioned emissions data and 95% of the major (>10 kTonnes/yr
S02) point sources were incorporated into the model's inventory
-------
2.4-13
(usually grouped) to form effective point sources located at
the emissions-weighted geometric means of the coordinates of
the contributing points. Care was taken to amalgamate only
sources situated in similar geographic settings and, in general,
less than 50 km apart. Approximately 60% of all area emissions
and 72% of all minor point emissions were incorporated into
the inventory by adding minor point sources and area sources
located near (< 50 km) major points to that point or combining
small sources concentrated in large urban centers to form
effective point sources.
Sensitivity Study _ __ _
The model sensitivity to uncertainty in the value of the
input parameters was tested by independently varying each
parameter within the range of values citied in the recent
literature. All model parameters are tested separately except
f<3 and fw (fw = 1.0 - f^). For this test an idealized source-
receptor geometry was chosen to enable the testing a model
sensitivity to the input parameters as a function of the
source-receptor orientation. An example of the results of
this model sensitivity test are shown in Figure 2-7. Plotted
is the annual wet deposition of sulfur per unit emission on a
log-log scale as a function of the parameter being studied.
Figure 2-7 actually consists of eighteen pages, one page for
each receptor (see the complete OME-LRT model profile). A
log-log plot was chosen in order to display the fractional
change in the calculated deposition in terms of a fractional
-------
Figure 2-7
Total Annual Wet Deposition of Sulfur Per Unit Emission
Plotted!on Log-Log Scale A6 a Function of the'Model Para-
meters peing Varied for a Receptor 200 km East of An Ideal-
ed Source (see Model Profile for details)
vie
KD
KW
0.00012
ace.02.
LAMDAB
MIXHT
4-90
TAU W
8.C6
UM
o.ar
VD
0.09
VDBAR
0.92
o.or
FD
FW
3.20
VM
5.48
WIND
0.00002
LAMDA
K>
£
45. 'JO
TAU D
2C9.S8
W D1R
-------
2.4-15
change in the model parameter ri"j_,"i.e.
/ n \
dD ( _i 1
dn^ \ D I
dD _i 1 = d InD (2-27)
d
An example of how the results in Figure 2-7 have been
summarized in terms of the input parameter under consideration
and the relative location of the receptor with respect to the
source is as follows:
Dry conversion rate (k^) :
For receptors down wind of the source the calculated wet
deposition rate is insensitive to values of ^(.6% to 1.2%)
except at large distance (~- 1000 km). The result is the
same at cross wind receptors. Elsewhere the calculation
is insensitive to the value of k^j.
The interested reader is referred to the OME-LRT model
profile for the complete discussion. The evaluation results
are presented in Chapter 4.
-------
2.5-1
2.5 RCDM-2 - -
Overview;
The simulation of longer period sulfur dioxide and sul-
fate concentrations on a regional scale presents a formidible
challenge if one wants to apply a grid or trajectory type
model to every day in a season or for an entire year. The
current "short cut" has been to run the models for a selection
of episodes or for one month in each of the seasons. The
\
episode results are then weighted by their relative frequency
of occurrence based on weather patterns or sulfate data (c.f.
Niemann, et al, 1979) to "build up" to an annual average. In
the case of the monthly simulations/ the results are usually
simply averaged together and are assumed to be representative
of the entire year.
A much simpler approach which gives the same basic results
as the more computationally involved methods has been proposed
recently by Fay and Rosenzweig (1979). These authors have
assumed that the longer period sulfur dioxide and sulfate con-
centrations from a point source can be described by the steady
state diffusion equation in which the horizontal eddy diffu-
sivity and conversion and removal rates are uniform in space.
Analytical solutions to the diffusion equations for sulfur
dioxide and sulfate concentrations are found under these simp-
lifying assumptions. Fay and Rosenzweig (1979) found generally
good agreement between sulfur dioxide predictions from their
-------
2.5-2
analytical model and the numerical predictions from the
NOAA/ATDL trajectory model, and between sulfate predictions
using only power plant sulfur dioxide emissions and area
smoothed sulfate data in the eastern U.S. In the latter,
the authors used only one wind speed and direction for the
eastern U.S. and assumed all the power plant emissions were
emitted from just one point.
The sulfate predictions from the steady state model are
also in general agreement with those from the ASTRAP model
(c.f. Shannon, 1979) which requires large amounts of meteo-
rological input data and trajectory calculations. These
results suggest that for more refined applications one should
find an appropriate compromise between the Fay and Rosenzweig
(1979) application which uses only one wind speed and direc-
tion for the entire eastern U.S. and the NOAA/ATDL and ASTRAP'
models which use the highest temporal and spatial resolution
available in upper air weather data. The idea would be to
apply the kind of temporal and spatial averaging to the wind
data that eliminates most of the detailed fluctuations, but
preserves the basic features that produce essentially the same
mean transport field that one gets from a large- number of
trajectories. Certainly, the calculation of the seasonal and
annual resultant wind vectors at all the upper air stations
is the most logical first choice to try. An initial evaluation
of this approval was encouraging (Niemann, et. al., 1980).
-------
2.5-3
Formulation
The two-dimensional steady-state advection-diffusion
equation with removal is:
•M
(2-28)
where u and v are the mean wind velocities in the x and y
directions, Dn is the horizontal eddy diffusivity and "£*
is the removal (wet plus dry) time constant. This equation
can be solved for a steady point source at the origin having
an emission rate Qf with a boundary condition of zero concen-
tration at infinity:
1/2
.
(2"29)
where the x' axis is aligned in the direction of the mean wind
velocity w, Ko is the modified Bessel function of the zeroth
order, r is the radial distance from source to receptor, and
h is the mixing height. The complete derivation of this equa-
tion appears in RCDM profile report.
Singularities occur at r - 0, and when becomes infinite
(the pollutant is inert and non-depositing) while w goes to
zero. The singularity at r = 0 is not severe because C . .
increases only in proportion^ to l/ln(r) — concentrations are,
therefore, still meaningful at small distances. The second
singularity is a consequence of modeling an infinite line source
(aligned in the vertical) as a line segment bounded by z = 0
and z = h. Material will, as a result, increase faster than
-------
2.5-4
it can be removed or laterally dispersed. A slightly positive
w or l/^- forces the system into steady state; and once equilib-
rium is achieved, the dependence of C on w and 1/t is well-
behaved.
For a gridded or source region (i.e. Canadian 11 regions)
emission inventory, the model assumes that emissions are
concentrated at the center of each square or region. The
singularity at r = 0 therefore presents problems when computing
'home grid square or region1 concentrations. Because of
certain model assumptions, there is no reason to expect
predicted concentrations in home grid squares to be realistic,
but they still must be finite, and still should be consistent
with model behavior in adjacent grid squares or regions.
For these reasons, the recent TRI work (Benkeley and Mills,
1980) computed home grid square concentrations as the area
integral (using Simpson's rule) along the mean wind axis in
the home grid square from 0 (center) to 40km (grid square
edge). TRI found, however, that irregardless of the value
of eddy diffusivity, wind speed or removal rate, the integrated
concentration was equivalent to the solution of equation
(2-29) at a distance of 23.5km. For the sake of simplicity
in RCDM model evaluations and applications, the solution of
equation (2-29) at this characteristic distance was adopted
for all home grid square calculations.
-------
2.5-5
The analytical solutions for the horizontal distribution
of primary and secondary pollutants from a steady point source
at the origin having an emission rate Q are:
Ci = Q expf w x'\K \ rj 1 + / w \2 1 1/2 > (2-30)
EDh- \2i% ) °{ [-TV*- (iDh-) j ;--•
-S
respectively, where
and
C2 = /*Q ~ exp/_w x'Y K^Tr) - KQ(e.r) (2-31)
T 2D ] *
(2-33)
. " I
h
Here the x1 axis is aligned in the direction of the mean
wind velocity w, Ko is the modified Bessel function of zeroth
order, r is the radial distance from source to receptor,. h is
the height of the mixing layer, D is the horizontal eddy
diffusivity, and ft is the mass ratio of secondary pollutant
formed per unit mass of primary pollutant. The rate constant
taking into account all forms of depletion of the primary
pollutant is:
— -1 _ _i _i _i ^ «.
(2-34)
where "C"ci~^' ~Cw~" ' anc^ T"c •are respectively, the rate con-
stants for dry deposition, wet deposition, and chemical conver-
sion. The rate constant for loss of secondary pollutant is
1) (2-35)
-------
2.5-6
where the rate constants for wet and dry deposition of the
secondary pollutant are "Cg and T"r , respectively. Contri-
butions from multiple sources of primary pollutants can be
superimposed since the boundary condition at infinity has
been specified to have an ambient concentration of zero.
Winds and Eddy Diffusivities _ _ . ._
The resultant winds and their persistence factors were
computed for the 50 upper air stations in the eastern
U. S. and Canada for 9 and 10 years of twice daily observa-
tions, respectively. The 600 meter level above ground was
selected because it has measured (not interpolated) winds
closest to the general transport altitude of S02 emissions
released from elevated sources. The monthly and seasonal
resultant winds and persistence factors were computed and
are discussed in the Model Profile. The annual values are
presented in Tables 2-2A and 2-2B for the eastern U. S. and
Canada, respectively. These tables slow the subregional
average wind directions over the stations in the eastern
U.S. and Canada are southwesterly (243°) and westerly (276°
and 296°), respectively. The largest variations from these
subregional averages are generally at the stations farthest
from the major S02 emission areas and near the boundary of
the entire region covered by the upper air stations.
-------
2.5-7
Table 2-2A. Eastern United States Resultant Winds and Persistence Factors at
600 Meters fibr Input to the Annual Average Disparsion Model
Calculations (1970 - 1978)
Subregion
Number
I
Average (3)
II
Average (4)
IIIA
Average (6)
IIIB
Average (2)
IIIC
Average (8)
IVA
Average (5)
Station
Dayton, OH
Peoria, IL
Salem, IL
Pittsburgh, PA
Huntington, WV
Sterling, VA
Wallops Island, VA
Fort Worth, TX
Boothville, LA
Lake Charles, LA
Little Rock, AR
Jackson, MS
Shreveport, LA
-
Nashville, TN
Mantgcmery, AL
Athens, GA
Miami, EL
Key West, EL
Waycross, GA
Cape Hatteras, NC
Greensboro, NC
Charleston, SC
Tampa, EL
Green Bay, WI
St. Cloudy MN
Int. Falls, NN
Sault St. Marie, MI
Flint, MI
Resultant
Direction Speed
(degrees) (m/s)
257
261
257
258
263
255
278
277
268
210
181
192
235
229
211
210
247
240
244
259
115
100
239
263
269
246
157
206
273
275
273
274
266
272
5.2
4.4
4.6
4.7
5.7
5.1
4.2
4.2
4.8
4.2
1.6
2.5
3.3
2.4
3.5
2.9
4.1
1.7
2.9
3.2
2.5
3.2
1.9
3.4
3.7
2.5
0.8
2.7
3.8
3.0
3.4
3.7
5.0
3.8
Mean
Speed
(m/s)
9.0
9.4
9.2
9.2
8.9
8.1
8.7
9.1
8.7
9.1
7.3
7.5
8.3
7.6
8.3
8.0
8.3
7.1
- 7.7
7.7
6.5
6.3
7.4
8.9
8.2
7.9
6.6
7.4
9.2
9.3
8.9
9.3
9.5
9.2
Persistence
Factor.
0.58
0.47
0.50
0.52
0*64
0.63
0.48
0.46
0.55
0.46
0.22
0.33
0.40
0.32
0.42
0.36
0.49
0*24
0.37
0.41
0.38
0.50
0*25 -
0.38
0.46
0.32
0^13 -
0.35
0.41
0.32
0.38
0.40
0.53
0.41
-------
2.5-8
Table 2-2A. (continued).
Subregion
Number
IVB
Average
V
Average
Overall
Average
Station
Tbpeka, KS
Monett, MO
(2)
Albany, NY
Caribou, ME
Chatham, MA
Buffalo, NY
Portland, ME
New York, NY
Maniwaki, QC
(7)
(37)
Resultant
Direction Speed
(degrees) (m/s)
245
241
243
272
279
270
258
278
280
271
273
243
3.7
4.8
4.3
4.9
4.9
5.1
6.5
3.7
4.4
2.3
4.5
3.8
Mean
Speed Persistence
(m/s) Factor
9.8
9.6
9.7 -
9.8
10.4
10.6
9.8
8.9
9.6
6.4
9.3
8.7
0.38
0.50
0.44
0.50
0.47
0.48
0.66
0.41
0.45
0.36
0.48
0.43
Persistence Factor
resultant speed
mean speed"
-------
2.5-9
Table 2-2B. Eastern Canadian Resultant. Winds and Persistence
Factors at 600 Meters for Input to the Annual
Average Dispersion Model Calculations (1970-1979)
Canadian
Resultant
Subregion Direction
Number Station (degrees)
1
1
1
1
1
1
1
Average
2
2
2
2
2
2
2
Average
The Pas
Churchill
Trout Lake
Moosonee
Nitchequon
Fort Chimo
Port Harrison
(7)
Maniwaki
Sept Isles*
Sable Island*
Shelburne*
Stephenville
St . John ' s
Torbay*
Goose
(7)
291
321
295
282
307
292
282
296
271
332
263
269
253
258
288
276
Speed
(m/s)
1.5
3.4
2.4
3.5
1.0
3.2
1.5
2.4
2.3
2.0
4.9
4.3
3.2
5.8
3.1
3.7
Mean
Speed
(m/s)
6.6
8.3
7.1
8.4
5.2
7.9
8.5
7.4
6.4
7.4
11.4
9.9
8.6
11.3
8.0
9.0
Persistent
Factor
0.23
0.41
0.34
0.41
0.20
0.40
0.18
0.31
0.36'
0.26
0.43
0.43
0.37
0.51
0.38
0.39
* less than 10 years of data
-------
2.5-10
The persistence factors which are related to the horizon-
tal eddy diffusivity (c.f. Fay and Rosenzweig, 1980) show general-
ly small spatial variability except at sites near ocean coasts or
lakes with more local effects. It is concluded from this
analysis that the assumption of a uniform resultant wind and
horizontal eddy diffusivity fields is probably a good first
approximation on an annual basis in eastern North America.
However for refined applications like those involving transfer
matrices, it is desireable to use the resultant wind vector
from the upper air station closest to each source area (grid,
ARMS, state, or province) rather than the same resultant wind
vector for all the source areas.
Parameterizations _
The conversion and removal parameters used in Phases I
and II were the same as those taken from literature.by Fay
and Rosenzweig (1980), except an annual region-wide mixing
height of 1000m instead of their 650m was used based on
climatological data tabulations (c.f., Hoiworth, 1972; and
Portelli, 1977). Since the model only simulates the total"
deposition, an assumption was made as to the fractions of
=
wet and dry removal of SC>2 and 804. The fractions of wet
and dry removal assumed in Phase I were 10% and 90% for both
S02 and 804 and in Phase II were 5% and 95% for S02 and 30%
=
and 70% for 804. This parameterization will be refined in
the Phase III applications of the model using the fractions
of wet and dry time computed from hourly precipitation data
and the experience gained from the first round of model eval-
-------
2.5-12
re 2-8. RCDM-2 Sensitivity Results (sensitivity of annual
SC>2 AND 304 concentrations at 680 kilometers
downwind to changes in input parameters)
un
iase
Base
H =
H =
H =
H =
Dh =
°h -
Dh =
wh=
W =
W =
W =
*C a
'Cs
*C-
t-=
c
•vFa
•£° =
-£.C =
"Co15
V
Number
(1)
(2)
250
500
2000
4000
2 x
2 x
2 x
0.5
1.0
4.0
8.0
2 x
4 x
3.2
6.0
1.2
4.8
9.6
4.0
3.2
6.4
104
10*
107
104
104
x 105
x 10
x 10
x 10
x 10
x 10
x 10
x 10
4
5
5
5
4
5
5
SO 2
(ug/m3!
1.
2.
7.
3.
9.
4.
3.
2.
7.
1.
1.
2.
3.
2.
8.
5.
1.
1.
1.
1.
1.
1.
1.
98
88
91
96
89
95
80
46
50
62
74
43
07
97
83
65
98
98
98
98
98
98
98
x
x
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
1
10-2
10-2
10-2
10-2
ID"3
10-3
ID'2
io:2
1Q—
10-2
10-2-
10-2
10-2
10-3
10-3
10-2
10-2
10-2
•* 2
io-2
10-2
lO-2
S04
( ug/m 3]
1
4
6
3
8
4
2
6
2
1
1
1
1
4
9
4
6
3
8
4
5
2
3
.63
.31
.52
.26
.15
.08
.07
.51
.44
.39
.48
.78
.62
.73
.08
.08
.53
.26
.15
.08
.48
.45
.35
x
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
1
10-2
10-2
10-2
10-2
10-3
10-3
10-1
10I?
ID"
10-2
10-2
10-2
10-2
10-3
10-3
10-2
10-2
10-?
•• 3
10":?
io"3
10-2
10"2
(1) Mixing Height, H = 1000m
Eddy Diffusivity, E^ = 2 x loVs"1
Average Wind Speed, W = 2.0 m s-1
Inverse Total Depletion Rate, t = 8 x 104 s
Inverse Chemical Conversion Rate, fc= 2.4 x 105 s
Inverse Dry and Wet Deposition Rate, ^g= 1.6
Emission Rate, Q = 1Q3 g s"^-
x 105 s
(2) H = 1500m
0^ = 6.4 x
W = 3.2 m s"l
T= 1 x 10J> s
-f= 1 x 10| s
-Ts= 1 x IO5 s
Q = 103 g s-1
loVs-1
-------
2.5-13
and the removal time constant while the 804 concentrations are
most sensitive to mixing height and the conversion time constant.
The results of the third sensitivity analysis are presented
in the Model Profile.
-------
2.6-1
2.6 MCARLO
Qve.r.view
The CAPITA Monte Carlo model represents an attempt to
provide a conceptually and computationally simple approach
for .da.i,ly simulation of air pollutant concentration and
deposition on the regional scale. The computer programs
which perform the simulations reflect the diagnostic purposes
of the model/ permitting the user to vary each parameter at
will, and are modularly structured so that changes in model
formulation normally correspond to replacing one subroutine
with another. The model is thus continually being modified
to test alternative hypotheses; the discussion below describes
a currently operational version which is not expected to
change dramatically in the near future.
The general approach treats emissions by release of a
number of descrete point masses at each timestep, which are
subsequently horizontally advected in vertically well-mixed
boxes. Diffusion is simulated directly by repeated perturba-
tions of each point mass trajectory. The kinetics of chemical
transformation and dry and wet deposition to surfaces are
simulated by specifying the transition probabilities of all
possible chemical and physical pathways over each timestep.
The model output, in terms of mass (concentration of deposition)
of each pollutant species over each of several thousand points
in the horizontal plane at the end of each timestep, is related
to the concentration and deposition over the course of 24 hours by
-------
2.6^2
summing the masses over each of the day's timesteps.:_.w_ithin
grids to arrive at units of mass/area (deposition of_-vertical
burden) or mass/volume (concentration) when a scale height is
provided.
The CAPITA model was initially oriented toward-sulfate
concentration, with calibration against measured sulfate and
haziness (bext-) inferred from visual range observations. The
model is not intended to resolve local impact of large sources
and is unsuitable for temporal resolution below about one day.
However, simulation of synoptic "episodes" of high concentration
and deposition is an important objective, so that diffusion
and detailed meteorology are retained even though results in
•
this report correspond only to seasonal and annual averages.
Emissions
Emissions are represented by virtual point sources,
representing arbitrary mixtures of actual point and area sources,
The current version uses a 444-point emission grid scheme,
with unequal mass of pollutant associated with each point
mass (see Figure 2-9). The emission grid spacing is nominally
190 km, except in the northeastern U.S. and southeast Canada,
where the grid spacing is 95 km. The emission grid, on a
polar stereographic projection true at 60°N, does not include
natural sources nor western North America sources. The version
in use is a combination of published inventories by Clark
(1980) for the U.S. and Voldner et al. (1980) for Canada. The
use of a grid for emissions, rater than more precise location
-------
2.6-3
S 2 2 2 3 517375329
sii 19 a s sjjsuTsr a rant v
18 8222O
a 8 98 -\l 22 93017171320 9 S 0 217 S/2 0
2018 I « 2 <4 1 I 0 0 0 0
«- 0 12 88 339aiO£Zlt01
1718 2 S 0 8 I I % S 1
9 3t S187«0187*S2
11 I* 13 «7
Figure 2-9 SC>2 Emission Inventory Grid Used in the CAPITA
Model (10*tons S02/year/grid)
-------
2.6-4
of equal-mass virtual sources, was motivated by the ease with
which alternate emission inventories (or alternate pollutants)
can be examined, simply by changing the values in a file
without recalculation of trajectories.
Advection
Only horizontal advection is explicitly considered
(although vertical shear and veer is reflected in the diffusion
module). The winds at 6 hour intervals are supplied by
preprocessor routines and are assumed to represent bulk flow
through a simple inverse distance squared interpolation of
observed winds, without imposing criteria of vorticity.
The current version utilizes midday surface winds for
advection, modified by a seasonally calibrated wind speed
multiplier (1.7-2.2) and a 10° veering. The wind fields
between midday observations are obtained by linear interpolation
at each gridpoint. It should be noted that, since wind fields
are externally supplied, any suitable data set may be used
(i.e. rawinsonde observations or analyzed winds). Since wind
fields outside the continent are unknown, trajectories that
go over the sea are terminated.
Diffusion
It is common to disregard diffusion in long term regional
simulation of long range transport by considering only "mean"
transport by the observed wind fields, relying on the synoptic
swings of the mean plumes to yield a smooth concentration
field. Although not rigorously correct (Csanady, 1969), the
-------
2.6-5
assumption that, the mean wind field trajectory represents the
pollutant center of mass trajectory is often used in short
term "episode" models as well. The CAPITA Monte Carlo model
maintains its discrete form by direct simulation of diffusion
as a random walk for each point mass of emitted pollutant.
The random walk is currently implemented by displacement
of each trajectory end point onto a circle of radius /2kAt;
an empirical value of k= 4xl05 m2/s was adopted. Patterson
et al. (1981) provide a detailed description of the technique
and some of its implications when the model is used for daily
simulation. On seasonal timescales, the diffusion simulation
is unimportant in practice.
Kinetics
Just as for the random walk nature of diffusion, the
CAPITA Monte Carlo approach treats the kinetics of chemical
transformation, dry deposition and wet removal as stochastic
events. The model requires specification of transition
probabilities, as indicated in Figure 2-10. Over each
timestep, all possible paths (S02 conversion to 804, etc.)
are assigned a probability of accurence such that the sum of
the probabilities = 1. For some purposes, such as graphical
depictions of regional episode dynamics, it is useful to
treat kinetics as a discrete event: the random choice of the
path S02 or 804, for example, either occurs or does not, with
all of the point mass simulated to be completed in the form
of either S02 or 804. Equivalent simulation of the ensemble
-------
2.6-6
decanted SO
so;
deposited SOj
Figure 2-10. Schematic of Probabilistic Decisions for the
Simulation of Kinetics
-------
2.6-7
mean is achieved by algebraic allocation of mass among the
various forms, treating the transition probabilities as
expected fractions of conversion and removal.
Currently, the model assumes that S02 emissions contain
=
1% primary 804, and lumps wet and dry deposition together.
The values used are constant diurnally and, by diagnostic
comparison to SURE, CANSAP, and MAP3S data, the following
seasonal 6 hour transition probabilities were derived:
S02 -S02 S02 -S04 S02 -DS02 802 - DS04 804 -804 804 -DS04
January 0.887 .050 .057 .006 0.787 .213
April 0.811 .072 .108 .009 0.787 .213
0.741 .092 .156 .011 0.787 .213
October 0.811 .072 .108 .009 0.787 .213
Simulation of wet removal will be included in Phase III
of the MOI. The formulation requires knowledge of the
probability of the pollutant experiencing precipitation within
a timestep. From the spatially dense hourly precipitation
data, the number of reports of precipitation divided by number
of reporting sites yields the likelihood of being in rain.
Removal percentage for both 802 an^ s®4' given that the
pollutant is in a precipitating airmass, then multiplies the
probability of precipitation to yield the desired transition
probabilities of wet removal.
-------
2.6-8
Validation and sensitivity studies
The CAPITA Monte Carlo model has been compared to sulfur
concentration and deposition for both episode studies (Patterson
et al., 1981) and seasonal averages (CAPITA Progress Report,
January 1981). Earlier studies indicated that the transport
dominates such that the simulation is somewhat insensitive to
both source specification and kinetics for episode studies.
Sensitivity to kinetic parameters of annual average simulation
is graphically indicated in Figure 2-11, illustrating the
range of 804 concentration arising from "slow", "average" and
"fast" kinetics.
Calculation'of'unit'transfer"matrix
The Monte Carlo simulation via discrete puffs of pollu-
tant permits calculation of source-receptor relationships,
such as transfer matrices, via simple counting. Each psuedo-
source in the emission inventory is identified with one source
ID, and each receptor grid is assigned a receptor ID; for the
Phase II effort, the 11 Canadian source regions and 9 Phase I
targeted sensitive receptors were chosen. The CAPITA transfer
matrices were calculated on a state/sub-province basis with
each source also a receptor. Thus the receptors represent
rather large regions. The Adirondack receptor, for example,
is the New York state average rather than a single receptor
grid.
-------
2.6-9
12.00
SLOW
14.00
0000 i.oom t.eom in
4.00
oooo t.oaoo i.oooo in
Figure 2-11,
Spatial Distribution of Yearly Average SURE
304 Data and the Yearly Average of Simulated
Sulfate Concentrations for "Slow", "Average",
and "Fast" SC>2 Kinetics
-------
2.6-10
Calculation of the unit transfer matrices (A) is
independent of the emission inventory,
R = A * S
where R is the receptor vector and S the sources, but the
calculation is influenced by the number of virtual sources
used, i.e. the number of trajectories originating at each
time step from the source area. The calculation of A (i,j),
the transfer matrix coefficient relating source strength of
source j to concentration/deposition at receptor i, is
A(i,j) =1 IE, Cm / Nj (2-36)
cTj m
where m is all trajectories from" j to i," Cm is the concentra-
tion/deposition added by a source strength of 1 Tg/yr impacting
upon a receptor of 1 grid square in size (nominally 127x127
km), dj is the number of trajectories originating within source
j, and N is the number of grids which comprise receptor i.
The ratio Cm/dj will be an improved estimate and converge
as dj —> <*> . Increasing the number of trajectories also offers
better spatial coverage of the source region. Increasing N
also leads to more stable estimates of the appropriate A(i,j),
but at the expense of enlarging the receptor size and thus
averaging concentration/deposition until at some point even
large gradients may become obscured. At some point, the
-------
2.6-11
improved estimates of larger receptors and the loss of useful
information for control strategy development must balance.
It appears that the state/subprovince scale is an appropriate
one for transfer matrix calculation.
-------
2.7-1
2.7 MEP-TRANS
OVERVIEW
The objective in .developing the MEP transport and disper-
sion model was, to allow the use of long-term historical meteo-
rological data in determining the spatial dispersal of sulfur
and nitrogen originating from a point source (Weisman, 1980) .
A trajectory-based model was selected to satisfy both
requirements of resolving the patterns of single plumes near
the sources and the effects of large scale atmospheric motions
in transporting the plumes over distances of one thousand
kilometers or more. The use of historical data allows analysis
of the number of occasions on which a given location was sub-
jected to the influence of the plume for a given period and
the- total contribution from all such occasions on a long-term
basis.
By incorporating dispersal of the plume and the chemical
transformations of 862 and NOX within the plume, an assessment
can be made of the long-term influence of a point source over
a large area.
A regional model/ TRANS (Transport of Regional Anthropo-
genic-Nitrogen and Sulfur), has been modified to evaluate the
transport and deposition from a number of sources in Eastern
North America.
-------
2.7-2
Trajectory Model
Since vertical motions are of a lower order of magnitude
than the horizontal motions, air-parcel trajectories are
determined from the horizontal wind field and its variation
in time. This wind field is obtained from the sea-level
pressure field distribution through the so-called geostrophic
approximation with some adjustment being made in both speed
and direction in order to be representative of the 300 to 500
meter level above the surface.
The observational data consists of sea-level pressures
obtained at 6-hourly intervals on the CMC 381 km grid. A
total of 156 (12x13) pressure values are used in the grid,
these being fixed for the period of computation.
A method due to Sykes and Hatton (1976) is used in which
orthogonal polynomials in the two space co-ordinate x and y,
and in time co-ordinate t, are fitted to the data. The space
polynomials are orthogonal polynomials defined on the network
of observing points by recurrence relations. The series of
six-hourly observations for the day are fitted with a set of
orthogonal time polynomials, allowing determination of pressure
at any time between observations. The spatial pressure field
is fitted within one millibar error corresponding to a wind
field error of the order of one m/s.
-------
2.7-3
Since under the geostrophic approximation the wind field
is related to the pressure gradient, the required pressure
derivatives are readily obtained from the orthogonal polynomial
coefficients.
Chung (1977) has derived a method by which a wind field
representative of the atmospheric motions 300 to 500 meters
above the ground may be obtained from the geostrophic wind.
This method is used. In this approach, both speed and direc-
tion adjustments are obtained by means of a regression equation
in terms of the geostrophic wind speed and the 3 hour pressure
tendency.
The trajectory integration is done by a method due to
Peterssen (1956), in which an iterative procedure is used to
determine the new position after travel time t. In this
iterative procedure the winds are determined at the appropriate
location and time from the polynomial fits.
The integration can be carried forward in time to determine
the motion of the air parcel from an arbitrary location, and
can be carried backward in time to determine the history of
air parcels arriving at an arbitrary location.
Accuracy of Trajectory Determinations
The accuracy of the trajectory determinations depends on
three aspects of the computations; namely, the representative-
ness of the derived winds for the transport, the accuracy of
the pressure fits and interpolations and the accuracy of the
integration procedure.
-------
2.7-4
The accuracy of the integration procedure was determined
from tests carried out over 96 hours of travel time in both
forward and backward trajectory modes with a 3-hour time-
step. It showed a maxium difference in spatial position of 1
km, indicating a negligible source of error in comparison
with the uncertainities in the pressure fields.
The pressure field uncertainities are due to fitting
errors and errors in the original data. Only a small fraction
of the observational data error (error of the of about 0.5 mb)
is being transmitted to the interpolated values for the missing
data. The fitting procedure introduces a smoothing of the
pressure fields: it introduces an error in the pressure field
»
»
but tends to eliminate random noise inherent in the original
data. Frontal features are usually not resolved by the
pressure data leading to error in trajectory determination
near fronts. Typically for randomly oriented velocity error,
trajectory positional error may be of the order of 50 km after
1 day's travel. Where a sharp gradient in velocity exists,
as in a strong depression, the position of an air parcel after
24 hours travel can be several hundred kilometres from the
true position.
It has been verified that trajectories calculated from
modified geostrophic winds seemed to simulate best the
trajectories of tetroons released and balasted to travel at
about 300 meters (Hoecker, 1977).
-------
2.7-5
Dispersion and Deposition Model
The pollutant material contained in the air parcel
centered on the plume trajectory is assumed to disperse with
time, so that the horizontal distribution about the centerline
can be approximated by a normal (Gaussian) distribution. The
vertical distribution is assumed to be uniform.
The mixing height is allowed to undergo a standard diurnal
cycle ranging from 0.2 to 2.0 times the seasonal mean value
in four discrete vertical steps. The pollutant material in
each of the four layers is transported by the same wind field
and participates in the wet deposition. Only the pollutant
material below the mixing height is assumed to be subject to
dry deposition.
The deposition of material from the plume onto ground
is modeled by means of the deposition velocity concept. The
material flux at the ground surface is determined by
w = vd C(x,y,o) (2-37)
where w is flux in g/m^/s
if Vd is deposition velocity in m/s
and C is concentration in g/m3
Within the model, the deposition velocity is dependent
on time but is not explicity made variable in the spatial
coordinates.
-------
2.7-6
The washout or rainout of material from the plume is a
complex process dependent on the raindrop size distribution,
the aerosol size distribution, the aerodynamic and chemical
retention efficiencies, the rainfall rate, gaseous desorption
rate, and the material distribution in the plume. All of these
parameters are highly variable and difficult to determine at
a given occasion by experiment. It is therefore common to
parameterize this process by means of a bulk washout parameter.
The rate of removal of plume material is given by
WA = \C (2-38)
where C is concentration distribution, and
X is the washout coefficient.
The flux of material to the ground is then given by
FW = j WA dz (2-39)
-/a
The washout coefficient is proportional to precipitation
rate and is specified for each plume segment separately.
Precipitation rate for a given segment is determined from 3
hourly precipitation intensities over the network of observing
stations. Thus the washout of material is governed by the
precipitation encountered by each plume segment in its travel
path as determined by historical record.
For the case of SC>2 washout, the approach suggested by
Barrie (1981) has been adopted. In this approach, the washout
coefficient is expressed in terms of a washout ratio as:
X = WSQ2 (2-40)
H
where H is the mixing height.
-------
2.7-7
The washout ratio is defined in terms of the rate constants
for the solution of S02 in the water droplets as
log W = log(K1KH) + pH . (2-41)
S02
and
K-LKg = 6.22 x 10"8 exp [4755. 5/T] (2-42)
This approach allows the temperature and pH dependence
of the S02 washout ratio to be explicity incorporated.
The chemical transformation of SC>2 to 804 in the plume
is modeled as a first order reaction, so that the concentra-
tions are coupled in the form
(2-43)
"it
^C2 = 3/2 kt G! - k2C2 (2-44)
}t
where C^ is the S02 concentration
C2 is the 804 concentration
k is the decay rate of S02 : k = kj. + k^
where k^ is the chemical tranformation rate
ki is the dry deposition factor k^ = v^/H for S02 and
k2 is the corresponding factor for 864
and the factor of 3/2 accounts for the difference in molecular
weights.
For plume washout, an additional term is incorporated in
k^ and k2 to account for source depletion.
-------
2.7-8
The implementation of the transformation in the model is
through modification of the source terms after each time step
according to the following solutions of Equation (2-44):
Ql (t +At) = QI (t) exp [ - kAt] (2-45)
Q2 (t +At) = Q2 (t) exp (-
k
3/2 kt Ql (t+At) [exp [k2-ki)£t]-l] (2-46)
where Qi is the emission rate of material labelled by i.
In the program, the rate kt as well as the other removal
terms can varied from one timestep to the next. Linear inter-
polation within a time-step allows for increased resolution
of the concentration and deposition fields.
A similar equation is assumed to hold for the N02 and
N03 constituents of the plume, except that the factor of 3/2
is replaced by 1.35. The NO to N02 conversion is assumed to
be instantaneous for purposes of long range transport. It is
assumed in doing so/ that the nitrogen and sulphur compounds
do not participate in a common set of reactions. This assump-
tion likely has limited validity due to the observation that
some radicals as well as free oxygen can participate in both
reactions.
-------
2.7-9
Model Sensitivity
The model described in the previous section contains a
number of parameters which determine the rate of plume spread,
chemical transformation, deposition by dry and wet processes
and vertical extent of mixing. Since a number of these para-
meters can be variable and are not well determined experimen-
tally, it is important to determine the effect of varying
these parameters on the rate of depletion of material from
the plume.
Figure 2-12a shows the disposition of plume material with
time for the standard values of the parameters. Figure 2-12b
shows the corresponding budget for a noon-time emission. The
»
mixing height, deposition velocities and transformation rate
follows a diurnal variation about the average value ranging
from 2 times the average in mid-afternoon to 0.2 times the
average in the late night. All values are converted to
equivalent sulfur and normalized to the S02 emission rate.
It is found that for normal conditions, the decay time
of SC>2 is about 24 hours and total sulfur, 45 hours. Simi-
larly, a noontime emission has a SC>2 decay of time of about
36 hours and total sulfur decay time of 72 hours. Similar
computations for N02 and total nitrogen, respectively, are
shown for standard conditions in Figures 2-13a and b.
-------
2.7-10
Figure 2-12a
Plume Sulphur Budget
Standard Conditions
1.0
S
u
H
U
.8
.6
N
.4
L
u
M
,S02
S04
Figure 2-12b
Plume Sulphur Budget
Noon-Time Emissions
12
34 36 48 60 T2
TIME IN HOURS FROM EMISSION
84
96
-------
2.7-11
Figure 2 -13a
Plume Nitrogen Budget
Standard Conditions
12
Figure 2-13b
Plume Nitrogen Budget
Noon-Time Emissions
\
24 36 48 60 72
TIME IN HOURS FROM EMISSION
84
-------
2.7-12
It has been found that, after 42 hours of travel, a 0.1
cm/s S02 deposition rate leaves twice as much material in
the plume as the 0.75 cm/s deposition rate and ten times as
•
much as the 2.0 cm/s deposition rate. The higher deposition
rate reduces the 804 formation by 50% within the same period.
A high transformation rate of SC>2 to 804 of 0.025 per
hour generates and maintains 10 times as much 804 in the plume
as does the low rate of 0.001 per hour. The total sulfur in
the plume at long travel times is twice as large for the high
transformation rate, due to the lower deposition velocity for
sulfate.
The effect of varying the deposition velocity of 804 on
sulfate levels indicates that only a 50% variation is evident
after 24 hours, for deposition velocities in the range of
0.1 to 2.0 cm/s.
An effective mixing height of 1200 metres leaves twice
as much SO2 and nearly 50% more sulfate in the plume after
24 hours as does the 500 m mixing height due to the lowering of
the deposition rate of both components.
Moderate rain (5 mm hr~l) results in a very rapid removal
by plume washout; the SC>2 decay time decreases to 9 hours with
what little sulfate forming initially being washed out very
rapidly (see Figure 2-14).
The nitrogen budget behavior was found to be similar to
the sulphur budget behavior described above.
-------
2.7-13
Figure 2-14
Sensitivity to
Precipitation Rate
U
SO? STANDARD CASE
S04 STANDARD CASE
NO
PRECIP
NO
PRECIP
24 . 36 48 6O 72
TIME IN HOURS FROM EMISSION
-------
2.7-14
An annual sensitivity analysis was performed for a single
source by carrying out the annual runs with a set range of
parameter values, varying only one parameter at a time.
Table 2-8 presents the results for the sensitivity of 804 wet
deposition as an example. Although most of the effects of
the varying parameters on 804 wet deposition seem intuitively
in the right direction, some are not and point to the inter-
relations among the several removal and transformation processes
within the model, and show that one cannot consider the various
parameters as being truly independent.
Model Results for 1978
Basis for Computations:
The emissions data for S02 and NOX used in the modeling
study were the 127 km gridded data currently being used by AES
in their regional transport evaluations.
A total of 70 trajectory origins were selected to coincide
wi-th grids having a large emission rate. For each trajectory
origin, 5-day trajectories at 3-hourly time steps were gene-
rated for the full year. The trajectories are used in con-
junction with the 3-hourly precipitation data to define the
precipitation intensity for each segment of the plume.
Concentrations and loadings were calculated at 75 receptor
points as shown in Figure 2-15. The receptor locations were
chosen to coincide with the 11 sensitive receptor areas defined
-------
TABLE 2-3 Sensitivity of 804 Wet Deposition to Variation of Model Parameters
Percent Change
due to choice of
Distance
Fran Source
(km)
0
100
200
500
700
1000
>
- 100
- 200
- 500
- 700
- 1000
- 1500
1500
Average 804
Wet Dep. (mgS/m2)
Standard Par am.
42.26
20.21
6.86
1.89
0.67
0.17
0.07
Transformation
Rate
Low
-47
-45
-39
-34
-30
-23
-23
High
+80
+72
+47
+30
+19
- 2
0
Deposition Velocity
S0? SOA
Low
+18
+27
+55
+77
+98
+140
+143
High
-26
-32
-46
-54
-60
-72
-75
Low
+5
+7
+13
+21
+20
+22
+21
High
-16
-20
-31
-43
-40
-40
-39
Washout Rate
of S04
Low
-52
-38
+28
+87
+173
+433
+407
High
+3
_o
-11
-21
-22
-21
-25
N)
~J
>L
Ul
-------
2.7-16
* 97
,11
.58
.68
kSS
.9
L>T
.19
A 291
\
'AS,
\
X !
A 31
.IS
.71
.*4- •
A)0
Figure 2-15 Location of Receptor Points
-------
2.7-17
by AES and a number of monitoring stations in the APN, CANSAP,
MAP3S, NADP, EPRI, NADP and Ontario Hydro networks to facili-
tate subsequent comparison with data. Based on the sensitive
tests, the values of the parameters shown in Table 2-9 were
selected for the 1978 comparison.
Concentrations and Deposition Fields:
By summing the concentration at each receptor due to all
the sources modeled, the total annual average concentrations
fields are generated. It,is found that the annual SC>2 concen-
tration range from 1 ug/m3 in Northern Ontario and Northern
Quebec to 30 ug/m3 over a wide region of the Eastern USA, with
an isolated peak of 50 ug/m3 in the Ohio Valley region. The
annual average SO^ concentrations range from 1 ug/m in
Northern Ontario and Quebec to 20 ug/m3 in the Eastern U.S. with
a peak of 25 ug/m3 in the Ohio Valley region. The N02 concen-
tration range from 0.5 to 20 ug/m3 with two regions of higher
concentration corresponding to the Detroit and New York areas.
Predicted NO^ concentration range from 1 ug/m3 in Northern
Ontario to 20 ug/m3 in the New York area.
Maximum dry deposition of SO2 in the order of 2.5 g S/m2/yr
occurs rn the areas of high concentrations. The 804 dry depo-
sition is approximately 10% of the SO2 deposition. Dry
deposition of nitrogen is up to 0.5 N/m2 for NO2 and 0.1 g N/m2
for N03.
-------
2.7-18
TABLE 2-4. Parameter Choice for 1978 Model Simulation
Parameter Sulphur Nitrogen
Summer Winter Summer Winter
Primary Deposition 0.8 0.3 0.5 0.3
Velocity (cm/s)
Secondary Deposition 0.1 0.1 0.1 0.1
Velocity (cm/s)
Transformation
Rate (% hr'1) 2.0 1.0 5.0 2.0
Primary Washout - - 0.04 0.04
Rate (hr"1)
Secondary Washout 0.3 0.3 0.3 0.3
Rate (hr-1)
Mixing Height (m) 750 500 750 500
-------
2.7-19
o
The wet deposition of SC^ ranges from 0.5 g S/m /yr in
Northern Ontario and Quebec to 1.5 g S/m2/yr in Ohio with an
isolated peak of 2 g S/m2/yr. The wet deposition of SO4 reaches
1 g S/m2/yr in the Ohio region. Wet deposition of nitrogen
range from 0.01 to 0.5 g N/m2/yr, being approximately equal
for the two species.
The dry deposition for sulphur has a maximum value of
over 3 g S/m2/yr, while dry nitrogen depositions are in excess
of 0.5 g N/m2/yr. The wet deposition of sulphur ranges from 0.1 g
S/m2/yr in Northern Ontario and Quebec, to in excess of 2.5
g S/m2/yr, with a peak of 3 g S/m2/yr in Ohio. The deposition
of nitrogen ranges from 0.05 g N/m2/yr to 1.0 g N/m2/yr in the
lower Great Lakes regions.
There is a large area of total (wet plus dry) sulphur
deposition in excess of 3g S/m2/yr, centered in the Ohio Valley
and extending into Southern Ontario. Total nitrogen depositions,
expressed as N, are approximately one-third of the sulfur
deposition on a regional basis.
Transfer Matrices
For the purpose of the present evaluation, 13 source
regions and 11 receptor locations were considered, as indicated
in Figure 2-16. Table 2-10 shows the transfer matrix for wet
sulfur deposition. The first column shows the total emission
from each region in Tg S/yr (millions of Tonnes per year).
Source region 9 (Ontario) also includes number 12 (Sudbury).
-------
2.7-20
Figure 2-16
Source Regions Defined for
Transfer Matrix Derivation.
Sensitive Receptors are
indicated by small numbering.
-------
Source
Region
1 Mich
2 111, Ind.
3 Ohio
4 Penn
5 NY to Maine
6 Kent Term
7 N Virg to NC
8 Rest of USA
9 Ontario
10 Quebec
11 Atlantic
Provinces
12 Sudbury
13 West Can
TOTAL DEPOSIT
12 Excepted
Q(TGS/Vr)
0.986
2.447
2.464
0.989
1.261
1.289
1.270
3.153
0.971
0.526
0.221
0.501
0.274
TABLE 2-5. Transfer Matrix of Total Wet Sulfur Deposition (kg.S.ha~1yr.~-L)
RECEPTORS
1234 5 6 789 10
B.Waters Alg. Musk Que. S. N.Sc Vt.NH. Adir. Penn. Smokies Florida
0.14
0.12
0.02
0.01
0.00
0.01
0.01
0.73
0.07
0.02
0.00
0.04
0.16
1.22
0.78
0.34
0.08
0.06
0.06
0.03
1.07
2.11
0.18
0.00
0.97
0.01
1.25
0.76
2.34
0.59
0.83
0.12
0.20
0.38
2.73
0.26
0.01
0.93
0.00
0.18
0.20
0.57
0.45
1.56
0.04
0.11
0.06
0.70
1.86
0.07
0.41
0.00
0.08
0.05
0.20
0.20
1.34
0.01
0.06
0.03
0.14
0.30
0.31
0.06
0.00
0.25
0.29
0.81
0.82
2.89
0.05
0.28
0.09
0.86
1.66
0.04
0.47
0.00
0.41
0.32
1.16
1.27
2.38
0.08
0.36
0.16
1.51
0.98
0.02
0.94
0.00
0.65
0.42
4.85
6.39
0.79
0.23
1.59
0.16
0.96
0.08
0.02
0.32
0.00
0.11
0.93
0.71
0.16
0.01
2.59
0.95
0.91
0.92
0.00
0.00
0.01
0.00
0.00
0.12
0.02
0.01
0.00
0.23
0.08
1.04
0.00
0.00
t
0.00
0.00
0.00
11
Arkansas
0.03
0.69
0.05
0.01
0.00
0.13
0.01
0.91
0.01
0.00
0.00
0.00
0.00
10
15.851
1.29
5.95 9.47 5.80
2.72
8.04 8.65 16.14
7.29
1.50
1.84
-------
2.7-22
Cjomp.ar.is.on. pjE. Jl.odel. fiejs,ul.ts.. .tp, Pat.a
The comparisons that are made must be considered to be very
tentative. No extensive data set is available for 1978, except
concentrations in precipitation, and the methods of analysis
seem to produce a different measure of sulfur compounds
(Barrie, 1981).
The results indicate a tendency to over-predict the 804
concentrations and seem to result from the choice of SO2 to
=
804 conversion rate.
The general pattern of wet sulfur deposition is in general
agreement with the data as shown in Table 2-11. The data for
Eastern Canada, however, indicate that the model might be
under-predicting the transport into this region.
It is interesting to note that, even if data on nitrogen
oxides are fragmentary and uncertain at this time, the ratio of
_ =
wet N03 to 804 deposition in Southern Ontario and Quebec,
estimated using a simple nitrogen chemistry, is 1:2, a value
which is in agreement with a number of experimental studies
carried out in these areas.
-------
2.7-23
TABLE 2-6. Comparison of Predicted and Observed Wet Sulfur
Deposition at the Sensitive Receptors
SENSITIVE RECEPTOR
MODEL PREDICTED
WET S DEPOSITION
FOR 1978 (kgS/ha/yr)
1. Boundary Waters
2. Algoma
3. Muskoka
4. Quebec-Montmorency
5. Southern Nova Scotia
6. New Hamsphire
7. Adirondacks-Whiteface
8. Pennsylvania-Penn State
9. Southern Appalachians
10. Florida
11. Arkansas
1
6
10
6
3
8
9
16
7
2
2
OBSERVED
WET S DEPOSITION*
3
3
6
5
3
7
7
12
7
5
7
As read from a map prepared by the National Atmospheric
Deposition Program based on NADP and CANSAP data for
March 1979 to March 1980.
-------
2.8-1
2.8 UMACID
METHODOLOGY ."'___
The Atmospheric Contributions to interregional Deposition
(ACID) model has been designed at the University of Michigan
for use in either a source-oriented or receptor-oriented mode
to estimate either the contributions of a given source to
downwind concentrations or the contributions of upwind sources
to a given receptor. The model incorporates the horizontal
dispersion due to vertical wind shear, first-order chemical
transformation, spatially and temporally varying dry deposi-
tion/ and precipitation scavenging at each time step. The
model employs a unique moving grid technique to simulate
»
regio'nal scale dispersion. The model is supported by a
variety of software programs required to prepare the raw
data for input into the model.
The model is not intended for use in the near-field range
(travel times less than six hours) since the trajectories
are generated from upper-level winds at increments of twelve
hours availability.
The model requires trajectories to be calculated a priori.
For this study the trajectories were calculated using a tech-
nique developed by Heffter (1980) for the National Oceanic
and Atmospheric Administration (NOAA) Air Resources Laboratory.
The model uses observed rawinsonde and pibal data to construct
the trajectories. The upper air temperature profiles are read
-------
2.8-2
and potential temperature profiles are constructed. The winds
are averaged over a layer of the atmosphere based on these
profiles. The top of the layer is defined as a stable layer
(non-surface based) in which the potential temperature gradient
exceeds 5°C / km. If no such layer is found, the model uses
a prescribed default"value (set to 1500 m for this study).
The base of the layer is determined by the wind profile. The
model scans the wind profiles to determine the base of the
mixed layer, defining it as the height at which the shear of
the wind velocity with height becomes less than 5 m sec ~1
between adjacent observation heights. If the shear is less
than this value at the surface/ the model integrates from the
surface. If the layer of shear exceeds 500 m the model assumes
a base of 500 m.
The model interpolates wind data in time and space to the
location of the trajectory, estimating its location at three
hour increments. Observed winds are used within 300 nautical
miles of the location of the trajectory. The interpolation
is performed using a weighting function which is proportional
to the inverse of distance squared. Additionally, there is
additional weight given to measurements along the axis of
the trajectory (1.0-0.5 I sin*f* | , where '-f is the downwind
alignment). Trajectories are computed using station data
where at least two reporting levels are available for
averaging in the specified layer and only for those segments
where at least two reporting stations are within the 300
mile limit or one station within 150 miles.
-------
2.8-3
The trajectory model has been tested against other models
(Hoecker, 1977) and with tetroon releases and recoveries over
scales of 300 to 1300 km and was found to predict the flow
with the least scatter of the four models tested. Heffter
and Ferber (1977) used a tracer gas released from Savannah,
Georgia/ to compare the model with measurements made in New
Jersey. The concentrations predicted by the model, using an
empirical dispersion factor, were in reasonable agreement
with those observed. Similar agreement was reported by Ferber
et.al. (1976) using tracer gas released from Idaho .and
followed across the United States.
The diagnoses of the downstream path of emitted material
requires an accurate description of the motion of air in time.
Data input errors or inaccurate interpolation schemes will
cause deviations in the location of the calculated trajectory
from the actual path of the air. Additionally, the calculated
trajectory represents the mean motion of the total layer and
should be thought of as a centerline of possible transport.
The vertical wind velocity shear through the mixed layer,
coupled with the vertical mixing will disperse the emitted
material away from the center line.
The use of ensembles of trajectories is an attempt to
minimize the effects of random errors in individual trajectory
analysis. The main factors which could hinder an exact evalua-
tion of the trajectory path using a constant layer model such
as Heffter's are:
-------
2.8-4
1. large-scale vertical motions/
2. the relative sparsity of observations in both time
and space,
3. the inaccuracies of observations, and
4. inaccuracies in the time and space interpolation
schemes employed.
Clearly, large scale vertical motions do pose a serious
threat to the accuracy of a constant layer model. A sustained
vertical motion of 0.5 cm sec"1 (possible in the vicinity of
a warm front, for example) over the course of one day of
trajectory motion would lead to a vertical displacement of
over 400 m. In a layer model with an average mixed layer
depth of about 1500 m this shift represents a sizable depar-
ture from the layer being averaged. If a particular wind
direction was climatologically associated with a particular
large-scale vertical motion, then this could lead to syste-
matic errors in the trajectory results.
It is assumed in the use of ensembles of trajectories
that this is not the case. The errors resulting from vertical
motion, interpolation schemes, observational errors, and
sparsity of data are assumed to be random. Thus the ensemble
analysis of trajectories over reasonably long time periods
will yield climatologically meaningful results about the
transport of material from the source.
-------
2.8-5
Horizontal Dispersion
The use of a mixed-layer trajectory model assumes that
the material being traced is moving with the mean motion of
the mixed-layer. This assumption will only be true if the
material is, in fact, well-mixed through the layer and there
is no shear in the layer to disperse the material away from
the mean flow.
Over sufficiently long travel times (> 3 hours) the
dispersion of atmospheric admixtures will be dominated by the
shear of the wind velocity in the vertical. The climatology
of this dispersion for long travel times has been calculated
by Samson (1980) from the divergence of trajectories for
sublayers of the mixed-layer. The distribution of the proba-
bility of contributing to receptors downstream was found to
be normally distributed about the mixed-layer trajectory.
The broadening of the probability field was found to be a
linear function of travel time as
= 5.4t (2-47)
where c^ and dy are the along and cross-trajectory standard
deviations of sublayer displacements, respectively, at time
t hours away from the origin.
The ACID model uses this parameterization to describe the
potential contribution of a source to downstreaam receptors.
-------
2.8-6
Additionally, the dispersion over long sampling times due to
the meander of plume centerlines is explicitly included in
the model through the use of trajectory integrations at six
hour time steps through the period of interest.
Dry Depos i tion
The ACID model uses a scheme for calculating dry deposi-
tion which follows the method of Shieh, et al., (1979). Dry
deposition is allowed to vary as a function of time of day,
season of the year, and location. To simulate the variations
due to location, the estimates of Shieh, et al., (1979) for
varying land use are stored for each grid point in the model.
These values of deposition velocity are stored in BLOCK DATA
subroutines with different values for each season.
To simulate the variation in dry deposition due to changes
in atmospheric stability, the gridded deposition velocities
are forced to vary diurnally according to the form
vd(X,Y;t) = 2vd(X,Y) sin(t -tar) + vdn (2-48)
(tss-tsr)
for tsr< t t, t>tss
-------
2.8-7
where v<3 is the deposition velocity as a function on longi-
tude, X; latitude, Y; and time, t. The deposition velocity
varies as a sine wave from sunrise, tsr, to sunset, tss, with
an average value of v<-j(X,Y) as obtained from Shieh et.al.
The deposition velocity during the nocturnal hours is kept
at a small value, v
-------
2.8-8
rate, then the area of highest relative impact may well be
close to the source.
The ACID model assumes a diurnally varying transformation
rate/ as suggested by Gillani et.al. (1978) with a form similar
to dry deposition. The conversion rate, k^, from sulfur
dioxide to sulfate species is assumed to behave as:
kt(t) = 2kt sin(t -tSF) +ktn (2-50)
(tsg-tgr)
for tsr£ t t, t>tss
where k~t is an average afternoon value and k^n is a low night
time value.
The system of equations to be solved along each trajec-
tory result from mass continuity for both sulfur dioxide and
sulfate. For sulfur dioxide, the equation expressing the rate
of change of probability of impact is
dp = -ktp - kdp - kwp (2-52)
Ht"
where dp/dt expresses the rate of change along the trajectory
of the probability of impact, p. The equation for the rate
of change of probability of impact for sulfate is likewise
written as
ds = kj-p-k^s - kws . (2-53)
dt
-------
2.8-9
The terms k and k refer to the removal rates for sulfur
dioxide and sulfate, respectively, and the subscripts d and
w refer to dry and wet removal. The removal rates for dry
deposition are inversely proportional to the dry deposition
velocities mentioned above, with a proportionality constant
equal to 1 meter.
Because of the variability of dry and wet deposition and
the forced variation in chemical conversion rate, equations
2-52 and 2-53 must be solved at each time step using a fourth-
order Runga-Kutta techhnique.
Wet Deposition
A number of methods have been proposed for parameterizing
the loss of gas and aerosol material from the atmosphere due
to precipitation. Rates have been put forth by Dingle and Lee
(1973), Englemann (1970), and Scott (1978). The wet removal
of sulfur dioxide in ACID is accomplished by assuming a first
order loss rate with respect to pollutant concentrations.
The loss rates for sulfur dioxide is given by kw = 0.005P(t)
(Dana et.al., 1975) where P(t) is the precipitation rate in
millimeters per hour. Wet removal of sulfate aerosol is
parameterized to be k = 0.232 P(t)°'625.
-------
2.8-10
Precipitation data collected hourly at stations in the
United States and eastern Canada have been obtained for the
years from 1976 to 1978. The data, available in station
form (three years of data for each station, station after
station) was sorted and reassembled in a synoptic format
(all stations for each hour, hour by hour) for use by the
ACID model. This precipittion data was summed over three
hour increments, checking for data validity, and gridded in
the same form as dry deposition parameters.
The ACID model is a sequential puff trajectory model.
An initial puff is generated at the first timestep as a
two-dimensional normal distribution of probability of sulfur
dioxide impact. The domain of this puff is interogated to
determine the underlying location for dry deposition, the
time of day for diurnal processes, and the existence of
precipitation. The Runga-Kutta subroutine is called for
sulfur dioxide and then sulfate. The amount of probability
removed by wet deposition at each grid point is stored for
each pollutant.
For analysis of individual episodes the ACID model
allows partial losses from the puff without affecting the
probability in adjacent areas of the puff. This is accom-
plished through a unique moving grid, following the course
of the trajectory. After the first step, the remaining field
will often have an irregular shape relative to its initial
-------
2.8-11
normal distribution. The moving grid is formed along the
axis of the trajectory segment and the along-trajectory
and cross-trajectory distances to the underlying fixed grid
points are stored. The resultant probability puff, after
cons-ideration of the removal and transformation, is trans-
planted to the next time step and interpolated to the fixed
grid points under the new location. The interpolation is
performed with a scheme which simulates the dispersion
expected over the time step.
The new fixed grid puff is again subjected to the
processes of wet and dry removal and chemical transformation
and the remaining sulfur dioxide and sulfate probabilities
of impact are added to the grid. This loop is continued
until the trajectory terminates.
The Atmospheric Contributions to Inter-regional Deposi-
tion (ACID) model takes into account the processes described
above to produce a probability field of the potential for
source contribution. The potential contribution field was calcu-
lated for each event in each of two months, August 1978 and
August 1979. The potential contribution field for each event
was weighted according to the amount of mass loading (preci-
pitation volume multiplied by concentration of sulfate ion)
and an ensemble potential contribution field for the combined
-------
2.8-12
months was obtained. Figure 2-17 shows the ensemble potential
contribution field for the thirteen precipitation events in
the two month period. Interestingly, the highest potential
for contribution to sulfate wet deposition at this recepter
is from sources in central New York State. The location of
the maximum potential is dictated by the climatology of
trajectories for the precipitation events and the dispersion
of the probability versus the upstream increase in probability
due to the slow conversion rate of SC>2 to 804.
While this region has the greatest potential for contri-
bution/ the probable source regions for the observed sulfate
deposition can be obtained by multiplying this field times the
S02 emissions field (Benkowitz, 1979). Figure 2-18 shows the
product of these two fields and in contrast to Figure 2-17,
indicates that the likely sources of the sulfate deposition
are SO2 emission in eastern Ohio, western Pennsylvania and
other parts of the Midwest.
Additional analyses indicate that the field of probable
source contribution obtained by simply weighting individual
potential fields by precipitation amount is similar to Figure
2-18, through the difference in the two fields shows a slight
increase in contribution potential for Ohio. Basin sources and
a loss for the large northern Ontario sources. Thus, while
there is some bias in mass loading toward sources in the Ohio
Basin, the field of probable sources is largely governed by the
amount of precipitation rather than the concentration of ion.
-------
2.8-13
92 90 88 86 84 82 80 78 76 74 72 70 68
tit I ill I I II I I I M I I I I
34
32 •
92 90 88 86 84 82 80 78 76 74 72 70 68
Figure 2-17. The Probability Field (x 10~8 km"2) of Potential
Contribution to Observed Mass Loading of Sulfate
to the Adirondacks by Wet Deposition for August,
1978 and August, 1979 as Computed by the ACID Model.
-------
2.8-14
90 88 86 84 82 80 78 76 74 72. 70 68:
STT
- 32
92 90 88 86 84 82 80 78 76 74 72- 70 68.
Figure 2-18. The Probable Source Contribution (kg km~2) to Observed
Sulfate Wet Deposition in the Adirondacks for August,
1978 and August, 1979 Based on the Potential for Contri-
bution Shown in Figure 2-17 and the Location and Strength
of Existing Sulfur Dioxide Sources in the Grid Area.
-------
2.8-15
Probable contribution fields computed individually for
August, 1978, and August, 1979, show marked differences. The
contributions in the former month with higher sulfate mass
loading are more sharply defined than those for the ensemble
shown in Figure 2-18. In contrast, the latter month, when
mass loading was lower but precipitation was similar, showed
a much more diffuse contribution field. In both months,
however, the probable sources remained in the Ohio River
Basin.
Because of uncertainties in trajectory modeling, the
trajectories used in this study were only computed to 72
hours upwind of the sampling site. Thus this study is limited
in that it can only estimate the source contribution which
may have occurred in that time span. It is possible that
under certain conditions the sulfate particles could remain
in- the atmosphere for longer than 72 hours, thus increasing
potential contribution from sourcs even further upwind. How-
ever, the mean residence time of sulfate particulates has been
estimated to be 60 hours which is comparable to the time span
studied here.
-------
3-1
3. PHASE II DATA BASES
3.1 Emissions
In Phase I the U. S. modelers used the SURE S02 emission
inventory (Klemm and Brennan, 1981) on the SURE grid system
(80 km x 80 km), aggregated to the 60 EPA/DOE ARMS (Acid Rain
Mitigation Study) regions by an EPA contractor. On the other
hand, the Canadian modelers used a composite of the SURE or
MAP3S inventory and the Canadian Environmental Protection
Service inventory for eastern Canada, aggregated to 11 large
regions (8 in the U.S. and 3 in Canada). To eliminate these
differences in the U.S. and Canadian modeling, a unified
Phase II U.S.-Canadian S02 emission inventory was produced
for agreed-upon source-receptor areas by Work Group 2 in
cooperation with Work Groups 1 and 3B. However, the Modeling
Subgroup of Work Group 2 found it difficult to standardize.
the source areas in Phase II because of the re-programming
required by some of the models. However, the-receptor areas
were standardized to an extent as will be described in the
next section. The Phase II unified S02 emission inventory
was produced on a state/province, 63 ARMS area, and top 50
point source basis to accommodate the needs of all 5 Phase I
models. The Modeling Subgroup agreed to encourage all the
participating models to plan to use the unified S02 emission
inventory on a state/province basis in the early part of
Phase III.
-------
3-2
In Phase II, the most recent Canadian inventory (Choquette
and Vena, 1980) was converted from its original longitude-
latitude basis to the 63 ARMS area bas-is. Furthermore, Work
Group 3B had an EPA contractor review, recommend, and provide"
the best S02 emissions data for the 10 major sectors of
emissions on a state, ARMS area, and top 50 major point
source basis. All the above activities have been incorporated
in the Phase II SC>2 Emission Inventory Report (No. 2-4) pro-
duced by Work Group 2 in cooperation with Work Group 3B.
This report supercedes the information in Appendix 6 and the
Addendum to Appendix 6 of the Work Group 2 Phase I report.
The Phase II best estimate of current U.S. - Canadian SC>2
\
emissions at the state, province and the ARMS area levels
are presented in Tables 3-1 and Table 3-2, respectively. A
list of the combined top 50 point sources in the eastern U.S.
and Canada is shown in Table 3-3.
Work Group 2 is continuing work with Work Group 3B to
produce best estimates for primary sulfate, NOX, and historical
(1940-1978) SOX and NOX emissions on a state/province basis.
In addition, best estimates for SOX and NOX emissions in the
western states and provinces will be developed in Phase III.-
-------
3-3
Table 3-1. PHASE II UNITED-STATES AND CANADIAN SC>2 EMISSIONS
ON A STATE AND PROVINICE BASIS (KILOTONNES/YR) - 1980
State or
Province
Alabama
Arkansas
Connecticut
Delaware
Dist. of Col.
Florida
Georgia
Illinois
Indiana
Iowa
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
New Hampshire
New Jersey
New York
North Carolina
Ohio
Pennsylvania
Rhode Island
South Carolina
Tennessee
Vermont
Virginia
West Virginia
Wisconsin
Sub-Total
Newfoundland
Prince Edward Is.
Nova Scotia
New Brunswick
Quebec
Ontario
Total
629.7
100.5
128.4
79.1
36.1
840.3
581.1
1 350.8
1 872.9
323.8
1 158.0
234.3
95.6
288.7
315.7
895.9
363.1
180.3
1 175.5
76.4
332.4
1005.9
519.8
2 811.6
1 874.9
27.5
260.6
1 011.8
13.3
351.2
1 034.0
609.2
20 578.4
56.5
15.8
217.3
223.8
1 106.1
1 843.1
Utilities
470.0
53.0
22.3
44.4
_*
651.7
480.0
983.3
1 380.0
222.5
1 044.7
20.7
21.2
191.8
132.2
631.2
192.4
122.3
985.9
50.4
103.9
470.2
354.1
2 236.5
1 218.3
3.0
173.5
873.6
0.0
202.9
901.1
454.4
14 691.5
5.3
5.9
88.2
91.7
1.6
436.9
Non-Ferrous
Smelters
67.5
58.4
35.3
12.9
174.1
_
-
-
12.0
609.6
929.8
Trans.
10.3
6.5
7.8
1.3
22.6
16.5
27.6
17.9
9.2
9.4
7.6
2.0
7.5
1.6
13.1
23.0
10.4
5.8
14'. 1
1.6
19.5.
31.4
13.9
35.0
32.0
2.4
7.7
13.9
1.1
14.4
4.9
11.6
403.7
2.0
0.4
3.1
2.9
18.3
21.3
Ind/Res/
Comm.
95.7
26.8
97.3
20.2
10.6
91.2
51.2
250.5
382.4
82.6
80.6
54.3
57.2
76.5
167.6
205.0
75.1
23.7
101.0
22. .1
148.1
4 6 6.. 4
109.2.
433.1
392.6
21.6
69.2
93.4
-11.9
113.2
102.1
131.8
4 058.1
. 41.9
9.5
108.9
100.5
386.2
Other
53.7
14.2
1.0
13.2
2.9
80.9
22.3
99.1
101.3
9.3
25.1
157.3
9.7
24.8
2.8
36.7
17.7
28.5
16.1
2.3
60.9
37.9
42.6
107.0
196.7
0.5
10.2
18.0
0.3
20.7
25.9
11.4
1 251.0
7.3
-
17.1
16.7
90.4
260.0 195.1
Manitoba 515.2 7.4 485.5 4.6 13.3 4.4
Sub-Total 3 977.8 637.0 2 036.9 52.6 920.3 331.0
* Emissions included with Maryland
Source of U.S. Data: Mitre Corporation, April 24, 1981 and E.H. Pechan,
May 30, 1981
Source of Canadian Data: Environment Canada (Frank Vena)
-------
3-4
Table 3-2.
Phase II United States and Canadian S02 Emissions
for the 63 ARMS Areas (Kilotonnes/yr) - 1980
ARMS "Area
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
u.s;
82.6
5.8
6.7
52.4
355.0
11.2
74.1
9.4
220.7
343.3
611.9
452.1
390.0
675.2
30.1
266.3
125.1
353.6
975.7
148.5
465.0
723.5
675.6
532.3
28.9
274.9
165.9
243.3
429.7
130.2
530.3
150.0
Canadian
7.5
12.4
0
0
0
0
0
0
0
36.5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
ARMS Area
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
U.S.
27.6
130.2
583.5
200.9
312.3
91.7
3.1
1289.8
291.5
721.8
402.2
645.5
1446.0
2006.1
544.4
339.7
981.8
48.8
611.8
314.8
Canadian
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
48.^4
3.8
0
0.5
1.2
370..6
872.5
1.3
628^5
18.1
332.7
831.5
5^5
171.9
10.9
Source of U.S. data: MITRE Corporation, April 24, 1981 and
E.H. Pechan, May 30, 1981
Source of Canadian data: Environment Canada (Frank Vena)
-------
Table 3-3
Combined U.S.-Canadian Top 50 Sources of SC>2 Emissions - 1980
Rank
t
1
2
3
4
5
6
7
8
9
10
11
12
13
14
: is
16
17
18
19
20
21
22
23
24
25
26
Plant
Name
Inco
Noranda
Paradise
Inco
Muskingum River
Gavin
Cumberland
Clifty Creek
Baldwin
Monroe
Labadie
Kyger Creek
Harrison
Johnsonville
Mitchell
Hatfield Ferry
Eastlake
Bowen
Lambton G.S.
Gibson
Nanticoke G.S.
HBMS
Cones ville
Shawnee
Algoma Steel
Bruner Land
State/
Province
Ontario
Quebec
Kentucky
Manitoba
Ohio
Ohio
Indiana
Indiana
Illinois
Michigan
Missouri
Ohio
West Virginia
Tennessee
West Virginia
Pennsylvania
Ohio
Georgia
Ontario
Indiana
Ontario
Manitoba
Ohio
Kentucky
Ontario
Pennsylvania
Emission
( kilotonnes/yr )
807.5
537.5
418.8
333.5
306.7
297.5
296.2
295.3
237.2
224.3
222.6
219.7
215.1
188.0
187.3
173.5
172.8
170.3
160.3
187.8
155.1
152.0
151.8
146.1
143.3
139.3
Rank
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
Plant
Name
Montr ose
New Madrid
Sammis
Coffeen
Krammer
Big Bend
Falconbridge Nickel
Keystone
Petersburgh
Conemaugh
Widows Creek
Mount Storm
Cardinal
Stuart
Joppa
Thomas HL
Montour
Kincaid
Gal latin
Gallagher
Gaston
Kingston
Avon Lake
Lakeview G.S.
State/
Province
Missouri
Missouri
Ohio
Illinois
West Virginia
Florida
Ontario
Pennsylvania
Indiana
Pennsylvania
Alabama
West Virginia
Ohio
Ohio
Illinois
Missouri
Pennsylvania
Illinois
Tennessee
Indiana
Alabama
Tennessee
Ohio
Ontario
Omission
( kilotonnes/yr )
138.0
135.1
' 133.7
124.8
123.8
122.7
122.3
121.5
120.9
118.2
118.8
116.4
115.0
113.1
107.6
101.8
96.9
96.0
95.6
94.6
93.6
92.0
91.7
91.4
Source of U.S. data: EPA Airtest Program (1979-1980)
Source of Canadian data: Environment Canada (Frank Vena)
-------
3-6
3.2 Sensitive Receptors
In Phase I, the Canadian modelers used 9 receptor areas
while the U.S. modelers used the 60 or 63 ARMS areas as recep-
tors, with 10 of the 63 areas designated specifically as sensi-
tive areas. Work Group 1 was to provide an updated list of
sensitive areas during Phase II. However, since the Modeling
Subgroup had not received any additions or deletions to the
Phase I Canadian receptor points or ARMS sensitive areas by
the time it needed to generate the Phase II transfer matrices
and evaluate the models, the subgroup decided to adopt a
composite of the Phase I U.S. and Canadian areas (see Table
3-4). This provided the 2 "receptor oriented" models with a
minimum number of Phase II receptor areas to be used.. The
other 6 Phase II models ran on either the 11 Canadian source
regions and 9 receptor areas or the full 63 ARMS areas (all
these areas were considered potential receptor areas as well
as source areas).
3.3 Meteorology
The participating models require as inputs either-high
resolution upper-level wind, mixing height, and precipitation
data or seasonal and annual averages of the same. The
locations of the routine upper-level wind and temperature
data sites in the eastern U.S. and Canada are shown in Figure
3-1. The Modeling Subgroup acquired a 10-year period of
data (1970-1979) for the 14.Canadian and 37 U.S. sites shown
-------
3-7
Table 3-4. Phase II Targeted Sensitive Areas
for Work Group 2 Modeling
Area Longitude and SURE Grid
Number Name Latitude (approx*) Centroids (X,Y)
1 Boundary Waters 93°, 49° 4, 26
2 Algoma 84°, 46.5° 12, 22
3 Muskoka 79.5°, 45° 17.5, 19.5
4 Quebec City 72°, 47° 12.5, 22.5
5 Southern Nova Scotia 66°, 44° 30.5, 19.5
6 New Hampshire 72°, 45° 25, 20
7 Adirondacks 74°, 44° 23.5, 18.5
8 Western Pennsylvania 78°, 41° 18, 13
9 Southern Appalachia 84°, 35° 12.5, 5.5 .
10 Arkansas 92°, 36° 2.5, 7.5
11 Florida 82°, 30° 13.5,-1.5
* may vary by +0.5°
-------
3-8
Figure 3-1. Locations of Upper Air Wind and Temperature
Observations in Eastern North America
-------
3-9
in this figure. Since the RCDM-2 model uses averaged wind
data, monthly, annual, and multi-year wind statistics were
computed from the data base. The other models used the same
basic data base, but pre-processed in different ways to
calculate trajectories as described in Chapter 2 and their
individual model profiles.
Previous model evaluation and application efforts- have
been limited to just a few meteorological periods for which
the high-resolution precipitation data for the eastern
U.S. and Canada had been merged, formatted in synoptic order,
and gridded. Recently this obstacle was removed by (1) the
acquisition of five years (1975-1979) of hourly precipitation
data for the eastern U.S. and Canada and (2) the development
and application of four computer programs for preparing
these data for regional models by an EPA contractor (Mayer-
hofer, 1980). The flow chart for the system of four compute'r
programs is shown in Figure 3-2. This system was applied
during the early part of Phase II to compile and grid th.e
hourly precipitation data for the months of January and July
1978. Copies of these data sets were distributed to the
participating modelers. This system is currently being used
by the MAP3S/RAINE program and an EPA contractor to prepare
the precipitation data for additional periods in 1978 and
1979 for use in Phase III.
-------
3-10
Figure 3-2. Schematic Flow Chart of the Precipitation Data
Processing Programs
-------
3-11
Some significant differences between the outputs of the
EPA precipitation data processing programs and those used by
SRI for ENAMAP were noted and the EPA program outputs were
selected so the intercomparisons of wet removal calculated
by the different models were not confused by different
precipitation fields at the very outset.
Two other EPA computer programs were used to compute
statistics of temporal and spatial variations in wet and
dry periods for use in specifying parameters in the OME and
RCDM models. An example of the output from these programs
in Table 3-5 shows that: (1) the annual spatial variability in
precipitation on a state basis was less than about 30% in
1978 and, (2) the percent of time with precipitation was about
5% or less.
An analysis of the variability of the meteorological
s,
periods selected for initial model evaluation and production
of transfer matrices was made during Phase II and has been _ .
reported elsewhere (Niemann and Summers, 1981). Basically,
the Modeling Subgroup concluded that the two selected months
(January and July, 1978) were fairly representative according
to most of the criteria used, but the modelers should run
their models on longer periods of record including up to 5
years after the Phase II evaluation work. The variability
in the transfer matrices for the same month in different
years is a measure of the representativeness, or lack thereof,
of any one month of meteorological data.
-------
Table 3-5. Precipitation Statistics for Use in Regional Climatological Dispersion Models (1978)
Season
No. of
States
Alabama
Arkansas
Connecticut
Delaware
Florida
Georgia
Illinois
Indiana
Iowa
Kentucky
louisana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
New Hampshire
New Jersey
New York
North Carolina
Chio
Pennsylvania
Rhode Island
South Carolina
Ttennessee
Vermont
Virginia
West Virginia
Wisconsin
Guages M*
38
57
15
3
52
57
75
73
76
58
35
23
16
22
58
63
53
96
24
20
87
49
93
141
3
27
44
20
49
46
59
14.4
11.8
13.5
14.1
11.3
12.8
5.2
8.4
2.0
16.2
15.9
9.5
12.7
13.6
5.2
1.4
15.2
4.5
11.5
13.3
11.5
12.3
9.1
12.1
15.2
10.4
17.6
9.3
11.9
13.0
2.1
Winter
SV*
22
35
19
13
35
26
53
39
38
36
26
20
27
25
34
35
23
56
35
22
28
28
28
24
11
31
23
33
26
32
45
%
5.0
4.4
6.8
7.4
4.4
6.0
3.0
3.8
1.8
5.5
5.2
5.3
6.0
6.7
4.8
1.4
4.5
2.3
7.2
8.6
7.0
5.7
5.5
6.9
7.7
4.7
6.4
6.8
5.4
6.9
2.0
M
15.7
13.9
10.3
15.4
11.8
12.4
10.5
11.0
9.5
12.1
11.7
8.9
12.2
9.2
6.4
6.2
16.1
13.0
9.1
12.4
8.8
14.1
9.7
10.7
11.3
12.0
13.3
7.4
13.7
10.2
8.2
Spring
SV
20
16
28
13
44
20
23
15
29
13
41
22
20
18
22
31
19
20
60
20
35
16
14
20
19
19
19
16
23
20
20
%
4.1
4.6
4.9
7.4
2.6
4.2
5.6
5.5
4.6
5.6
2.3
4.2
6.1
5.8
4.2
3.9
3.8
5.0
5.6
7.1
.5.4
5.4
5.9
6.5
6.2
3.9
5.5
5.5
5.8
5.9
4.1
M
12.8
9.0
10.2
13.7
21.1
13.1
in. 8
12.5
12.2
13.5
15.1
7.8
13.8
10.4
9.4
13.6
12.1
12.1
10.4
13.8
9.9
14.7
11.3
12.1
7.9
14.0
12.3
11.0
12.6
15.2
15.0
Summer
SV
38
31
17
6
26
38
27
31
26
30
48
25
17
29
38
31
45
30
25
20
22
34
30
21
38
29
29
17
25
24
19
Annual
Fall
%
2.6
2.5
4.4
4.2
4.8
3.3
2.9
3.2
3.3
3.4
2.7
3.5
4.1
5.0
3.1
4.0
2.5
2.6
5.1
5.1
3.8
3.6
3.8
4.1
4.3
2.8
3.3
5.0
3.6
4.6
4.5
M
5.9
11.3
7.8
5.9
9.0
4.8
7.5
7.4
9.1
8.2
8.4
7.4
5.7
7.1
8.8
4.9
6.4
8.9
6.6
6.9
8.6
6.7
7.2
7.7
8.3
5.9
7.3
7.3
5.2
6.1
8.5
SV
30
30
15
15
51
29
22
22
29
30
28
21
27
18
26
46
25
25
26
19
44
26
23
24
10
35
20
21
26
29
28
%
1.8
3.5
3.7
2.9-
2.5
2.0
3.0
2.9
3.3
3.3
2.1
4.1
2.4
3.9
3.9
2.4
1.9
2.9
3.9
4.1
4.0
2.4
3.5
3.8
4.4
2.2
3.3
4.7
2.5
3.2
3.5
M
49.1
45.8
41.0
47.5
53.0
42.8
34.3
39.4
33.7
49.5
50.7
33.3
44.5
40.1
30.0
26.6
49.6
39.0
37.6
45.9
38.5
47.7
37.4
42.5
43.3
41.8
50.4
35.0
42.8
44.7
34.3
SV
20
16
11
9
19
20
16
17
18
13
21
11
11
15
22
29
18
17
33
12
19
19
16
14
8
21
12
14
15
18
15
%
3.4
3.9
4.8
5.3
3.5
3.7
3.9
4.0
3.3
4.7
3.0
4.2
4.7
5.2
4.0
3.0
3.2
3.3
5.4
6.2
5.0
4.2
7.2
5.3
5.7
3.3
4.9
5.4
4.3
5.3
3.7
*M - mean precipitation (inches) over all recording rain gauges reporting in the State.
SV - coefficient of spatial variability (%) (standard deviation of individual gauge means
about the mean M over all the gauges in the State)
% - percent of total time when precipitation lasted one hour or longer
-------
3-13
3.4 Air Qua!ity and Precipitation Chemistry
The Modeling Subgroup agreed to evaluate the participating
models against ambient.sulfur dioxide and sulfate concentra-
tions and wet sulfur depositions at selected sites in eastern
North America. The selection of the sites (see Table 3-6)
considered geographic coverage, amount of data capture,
degree of local effects, etc. Unfortunately, it was impossible
to assemble an internally consistent data set because of
different sampling frequencies, analytical techniques, exposure
criteria, etc. Two of the most important reservations about
the SC>2 and S04= data bases are that: (1) more than 50% of
the SURE Phase II SC>2 data were below the lower quantifiable
limit (3 ppb or about 8 ug/m3 (Mueller, 1981); and (2) the
sulfate data in Quebec and other eastern provinces are of .
significantly lower quality and quantity than the SURE Phase
II data (La Fleur, 1981). ~
The compilation of data at the selected sites is con-
tained in Table 3-7. Generally, the air quality data show:
(1) maximum values of annual SC>2 concentration over the
Ohio River Valley which decrease northward into Ontario and;
(2) maximum annual SO^~ concentrations over and east of
the Ohio River Valley which decrease northeastward into
Canada.
-------
3-14
Table 3-6. Description of the Regional Model Evaluation Sites-Phase II
Program/
Number Name Agency Longitude Latitude
1 Montaque, MA SURE(l) 73.0 42.4
2 Scranton, PA SURE(2) 76.5 41.0
3 Indian River, DE SURE(3) 75.4 38.5
4 Duncan Falls, OH SURE(4) 82.0 39.7
5 Rockport, IN SURE(5) 87.1 37.8
6 Giles City, TN SURE(6) 86.0 35.3
7 Fort Wayne, IN SURE(7) 85.2 41.2
8 Chapel Hill, NC SURE(8) 78.8 35.9
9 Lewisburg, WV SURE(9) 80.4 37.6
10 Warren, PA SURE(16) 78.8 41.8
11 Brush Valley, PA SURE(18) 78.7 40.4
12 Louisa, KY SURE(22) 83.0 37.8
13 Sullivan,IN SURE(23) . 87.7 39.2
14 Port Huron, MI SURE(25) 83.0 43.0
15 Braidwood,IL SURE(27) 88.2 41.4
16 Toronto, OT SURE(30) 79.6 43.6
17 Land-between-Lakes,TNSURE(34) 88.0 36.1
18 St. Louis, MO SURE(38) 91.0 38.6
19 Nekoosa, WI SURE(39) 90.0 44.0
20 Ithaca, NY SURE(40) 76.5 42.3
21 Dayton, OH SURE(42) 84.2 39.9
22 Whiteface, NY SURE(51) .74.0 44.3
23 York, PA SURE(52) 77.0 40.2
24 Rents Hill, ME SURE(53) 69.5 44.5
25 Simcoe, ON OME(22071) 80.3 - 42.9
26 Orillia, ON OME(47019) 79.4 44.6
27 Kingston, ON OME(52017) 76.8 44.4
28 Sault Ste. Marie, ON OME(71042) 84.4 46.5
29 North Bay, ON OME(75010) 79.5 46.3
30 Atikokan, ON CANSAP 91.5 48.7
31 Kingston, ON CANSAP 76.5 44.2
32 Charlo, NB CANSAP 66.3 48.0
33 Shelburne, NS CANSAP 65.2 43.7
34 Mt. Forest, ON CANSAP 80.7 44.0
35 Peterborough, ON CANSAP 78.3 44.2
36 Simcoe, ON CANSAP 80.2 42.8
37 Chibougamau, PQ CANSAP 74.4 49.8
38 Sept Isles, PQ CANSAP 66.2 50.2
39 Maniwaki, PQ CANSAP 76.0 46.3
40 Truro, NS CANSAP 63.2 45.3
41 Stephenville, NF CANSAP 58.5 48.5
42 Whiteface, NY MAP3S 73.8 44.4
43 Ithaca, NY MAP3S 76.7 42.4
44 Penn State, PA MAP3S 78.0 40.8
-------
3-15
Table 3-6 (continued)
Number
45
46
47
48
49
50
51
52
53
Program/
Name
Chariot tesville, VA
Urbana , IL
Brookhaven, NY
Lewis , DE
Quebec City, PQ
Sorel, PQ
Sept Isles, PQ
Frederiction, NB
St. Margarets Bay,NS
Agency L<
MAP3S
MAP3S
MAP3S
MAP3S
Quebec (514)
Quebec (172)
Quebec(656)
New Brunswick
Nova Scotia
Longitude Latitude
78.5
88.3
72.9
75.0
71.2
73.1
66.4
66.7
63.9
38.0
40.0
40.9
38.8
46.8
46.0
50.2
46.0
44.8
-------
3-16
Table 3-7: Data at the Regional Model Evaluation Sites-Phase II
January 1978
Site
Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
'39
40
41
42
43
so2
(ppm)
0.007
R
R
0.026
0.018-
0.012
0.017
0.004
0.013
0.020
0.040
0.017
0.030
0.014
0.012
0.013
0.019
0.008
0.007
0.016
R
0.003
R
0.007
0.012
t£*
(ug/m-
3.6
5.4
5.5
8.8
8.1
6.9
11.2
5.5
6.7
7.5
6.7
8.8
6.0
8.2
7.2
5.0
8.1
4.6
4.5
5.4
R
R
9.4
3.0
5.2
7.4
4.2
13.7
WSDEP
(mg/1)
JULY 1978
1.3
1.7
1.3
1.9
7.0
1.7
1.0
0.9
0.9
0.6
so2
(ppm) I
0.002
0.018
0.002
0.008
0.014
0.001
0.005
0.002
R
0.025
R
0.004
0.014
0.006
0.006
0.013
0.005
R
0.004
0.008
0.007
R
R
0.003
0.008
4-j
[ug/mj
9.3
12.8
9.5
16.9
13.8
11.6
11.2
8.9
15.4
16.4
12.0
8.8
10.0
11.8
9.2
12.8
5.9
10.9
13.7
7.0
10.9
7.4
16.0
11.1
11.3
10.3
WSDEP
(mg/1)
1.3
10.1
4.4
2.3
13.6
10.2
3.1
4.6
6.9
3.8
2.5
4.2
" Annual 1978
so, so*
(ppm) (ug/nH)
0.005
0.020
0.007
0.015
0.014
0.004
0.009
0.003
0.003
5.7
7.5
6.3
10.1
8.7
7.7
7.6
6.5
7.3
WSDEP
(mg/1)
(WDEP)
(#M3N.)
1.8
7.1
4.9
2.6
7.1
5.9
7.0
3.3-
4.4
4.0
3.0
2.9
2.8
3.8
10
10
8
11
6
10
10
9
11
9
11
10
9
6
-------
3-17
Table 3-7. (continued)
Site
January 1978
SO.
SCT
44
45
46
47
I8
49
50
51
52
53
WSDEP
(1)
Number (ppm) (ug/m3) (mg/1)
0.9
JULY 1978
Annual 1978
SO^ 5U"4 WSDEP 5O^ S~07 WSDEP (2)WDEP)~
(ppm) (ug/m3) (mg/1) (ppmT (ug/m3) (mg/1) (#MON.)
11.9
5.2
7.3
2.5
4.3
3.8
2.8
8.8
4.8
6.0
3.4
3.1
3.0
3.1
2.3
2.5
11
8
5
7
8
Key: R - data rejected because of small data capture, etc.
blank - parameter not measured at the site or insufficient data
(1) - wet sulfate deposition - precipitation weighted concentrations
NOTE: CANSAP wet deposition data have not been corrected for
collector efficiency or evaporation.
(2) - "Annual" wet sulfate deposition is for the number of months
noted and has not been prorated.
-------
3-18
It was also not possible to assemble an internally
consistent data set for wet sulfur deposition because of
different sampling frequencies, analytical techniques/ expo-
sure criteria, etc. Probably the most important reservation
about the wet sulfur deposition data base is that the data
from event (i.e. like MAP3S) and monthly (CANSAP) sampling
period networks need adjustment to be consistent. Adjustment
methods are currently being proposed and evaluted by both
the Modeling and the Monitoring and Interpretation Subgroups
of Work Group 2 for resolution in the early part of Phase
III (July 1981 to January 1982).
Generally, the wet sulfur deposition data (Tables 3-7 and
3-8) show maximum values over, east, and north of the highest
SO2 emission density states, but with considerable spatial
variability. Most of the variability is due to the variability
of the precipitation amounts themselves (see Table 3-9).
With regard to the use of monitoring data in regional model
evaluation, uncertainties and errors are possible from faulty
instrument exposure and analytical techniques, limited sample
size, meteorological variability from year to year, and the
highly episodic nature of some pollutants like wet sulfur
deposition. Preliminary results of data analyses have shown
that wet sulfur deposition in eastern North America is generally
much more episodic than precipitation itself. Fortunately,
the spatial and temporal variability in precipitation decreases
-------
3-19
Table 3-8. Calculated Wet Sulfur Depositions (in kg.S.ha.""1)
Site
Number
30
31
32
33
34
35
36
37
38
39
40
41
42
43
4.4
45
46
47
48
January
0.03
0.35
0.63
0.20
0.96
0.06
• 0.10
0.12
0.50
0.20
0.44
July
0.37
0.61
0.57
0.08
1.22
0.88
0.78
0.97
0.92
0.77
1.39
1.69
0.89
1.50
"Annual "
2.92
7.61
4.37
6.12
10.12
7.07
11.59
2.99
7.04
5.68
7.36
6.42
6.05
4.76
9.27
6.15
2.71
3.91
5.43
( # mon . )
(10)
(10)
(8)
(11)
(6)
(10)
(10)
(9)
(11)
(9)
(11)
(10)
(9)
(6)
(11)
(8)
(5)
(7)
(8)
-------
3-20
Table 3-9
Precipitation Amounts (in centimeters)
at the Regional Model Evaluation Sites
Number
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
January
0.7 (2.9)(
6.1 (18.7)
14.6 (21.0)
"Annual"(3)
3.6
4.1
1.0
3.2
4.1
16.9
10.0
10. 01
15.0
15.0
(8.1)
(8.9)
(7.7)
(9.8)
(7.4)
(25.3)
CJ}9.6)
17.0
8
1
3
1
2
2
7
6
4
6
10
4
12
6
12
14
2
14
e
•
•
•
•
•
•
•
•
e
e
•
•
•
•
•
•
o
6
8
9
0
7
6
5
3
0
1
4
5
0
2
0
0
9
0
(
(
(
(
(
(
(
(
(
(
(
10.
3.
10.
2.
4.
4.
10.
6.
6.
6.
13.
7
2
0
2
5
0
5
9
2
1
4
)
)
)
)
)
)
)
)
)
)
)
48.8
32.3
26.6
69.9
42.8
35.9
49.6
27.4
47.6
42.4
72.9
65.4
64.8
37.6
90.7
61.9
26.2
50.7
64.6
84.0
66.7
98.3
57.9
65.4
73.9
68.5
81.5
64.9
98.4
111.5
65.4
NOTE:
(1) number in the parentheses are for the standard rain gauge while the
first number is for the collector
(2) the difference between collector and standard gauge values is about
+ 10% at the MAP3S sites
(3) "Annual" total precipitation is actually the total for. the
number of months listed in the last column of .Table 3-9
-------
3-21
dramatically as one goes from daily to annual and multi-year
time periods, unless the period contains significant aberrations
(e.g. droughts). This suggests that probably 5-10 years of
observations are needed to fully evaluate regional models,
especially their simulations of acid deposition.
-------
4-1
4. EVALUATIONS AGAINST MEASURED DATA ________
4.1 Evaluation Criteria _ _ . ..
Based on the recommendations of the EPA/AMS Workshop on
Short Range Dispersion Model Performance, the Modeling Sub-
group adopted the confidence interval statement and certain
statistics on the residuals between observations and model
predictions as the basis for regional model evaluation in
Phase II. Since statistical inference techniques are better
established for normal distributions, it is convenient to
deal with the logarithms of the depositions or concentrations
which are observed to be approximately log-normally distributed!
The model evaluation procedure is as follows:
(1) Define coi = In Coi and 6pi = In Cpi where
coi = observed variable , Cpi = predicted variable
(2) Compute di = £0i - £pi
(3) Compute the 95% confidence intervals for the mean
and standard deviation of d^ using standard methods:
di < cf < d2 ; Gdi < CTd" < Cd2 where
d = mean of d , 6 = standard deviation of d
The six numbers dj^, d", d£/ (Tdi, ^3", and 0~d2 are the
basic model evaluation measures which can be used to construct
the probable distribution of df.
-------
4-2
Since the high end of the concentration (or deposition)
distribution is also important this aspect of model evaluation
was included using the following measure:
N
M
_(4-l)
where Coi refers to the highest observed concentrations
(depositions) and Cp^ refers to the simulated concentrations
(depositions) at the locations of the highest observed. The
Modeling Subgroup selected N = 5.
Another useful model evaluation parameter adopted is
the spatial correlation coefficient which gives information
about the ability of the model to reproduce the observed
concentration (deposition) field. .,-.
The above statistical tests are based on several postul-ates
about the distribution of the residuals. One important
assumption is that the residuals are independent of each
other. Independence is a strong assumption and there are many
ways it could fail to be true. For example, air quality and
deposition data for any given sampling period- are spatially
correlated and systematic patterns in the residuals are
probable. If the residuals are correlated, the least-square
estimators are not best and least-square formulas for the
standard errors are not applicable.
-------
4-3
A second important assumption is the independence of the
residual and the model estimate. Again, when the observational
data and the model predictions are both spatially correlated,
it is expected that residuals and the models estimates are
also correlated. In this case the least-square coefficient
estimates are biased.
During Phase II, further consideration will be given to
the statistical tests used for the comparison of experimental
data and model estimates and to the implication of correlated
data sets. In this initial evaluation we have assumed the
data sets are random.
4.2 Comparison"of'Model'Est imates with Observations _ '_
4.2.1 Overview '
An initial comparison of model simulated average concen-'
trations and wet depositions has been completed for the AES-
LRT, ASTRAP, MOE-LRT, and RCDM models.
Comparison of AES, ASTRAP and RCDM monthly (January and July)
average- S02 and 804 concentrations and total wet sulfur deposi-
tions with monitoring data gave the following--results: -
For January 1978, the AES-LRT model on the average over-
predicted both the S02 and 804 concentrations- The ASTRAP
model S02 concentrations were on the average closer to the
observed SO2 concentrations. These comments are based on
only 21 S02 and 26 804 data points; hence, statistically
there no discernible difference between the performance of
-------
4-4
these two models. The RCDM model almost consistently under-
predicts S02 concentrations for January 1978 by a factor of
two or greater; however, January 804 concentration estimates
•
are on the average very close to the observed concentrations.
The wet sulfur depositions from AES-LRT and ASTRAP were on
-the average significantly larger than the observed depositions.
Predictions of January wet sulfur deposition by RCDM are on
average close to the wet deposition calculated from observed data.
However, no overall conclusions may be drawn due to the
small number of observations (11 stations) and some uncertain-
ties in the deposition data. Table 4-1 summarizes the January
1978 intercomparison of AES-LRT, ASTRAP and RCDM models with
wet sulfur deposition and SC-2 and 804 air quality data.
The July 1978 model 802 and 804 concentrations are on
the average not as close to the observed as the January
estimates were (see Table 4-2). Both AES-LRT and ASTRAP
over-predicted the 802 concentrations; however^ on the
average, the ASTRAP simulations for the 20 sites are close ~
to the observed. The converse is true for 804 concentrations
(30 stations) in that both models on the average under-predicted,
with AES-LRT simulations closer to the observed. RCDM model
predictions of July ambient S02 concentrations are on the average"
very close to the observed concentrations; however, the RCDM
model underestimates the 804 concentrations for the same period.
-------
Table 4-1. Comparison of January 1978 Monthly Average Model Concentrations
and Total Wet Sulfur Depositions with Observations? j
i ' !
(2)
(1)
Site #
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
so2
Obs.
0.007
—
—
0.026
0.018
0.012
0.017
0.004
0.013
0.020
0.040
0.017
0.030
0.014
0.012
0.013
0.019
0.008
0.007
0.016
—
0.003
—
0.007
0.012
Concentration (ppm )
ASTRAP
0.014
—
—
.017
.013
.006
.019
.008
.010
.027
.017
.009
.020
.018
.019
.018
.007
.010
.008
.016
—
.007
—
.006
.029
1
SO4 Concentration (ug/ftr)
RCDM AES-LRT Obs. ASTRAP
0.004
— — •
—
.009
.007
.006
.005
.005
.007
.007
.007
.007
.006
.005
.004
.006
.006
.004
.003
.006
—
.004
—
.003
.006
!
;013 3.6 9.2
— 5.4 10.2
— 5.5 5.9
.028 8.8 8.3
.025 8.1 5.6
.016 6.9 3.5
.016 11.2 7.8
.011 5.5 4.8
.015 6.7 5.3
.021 7.5 10.3
.048 6.7 8.7
.019 8.8 5.2
.022 6.0 7.4
.018 8.2 7.8
.013 7.2 8.1
.017 5.0 7.6
.019 8.1 3.4
.021 4.6 4.6
.005 4.5 3.8
.014 5.4 7,4
— — —
.008 — —
— 9.4 10.3
.008 3.6 4.8
.017, ,5.2 10.0
7.4 4.0
4.2 4.5
13.7 ,i.3
RCDM AES-LRT
7.1
8.1
8.0
7.7
5.8
6.0
5.6 .
7.5
8.0
7.6
8.2
7.5
5.2
5.6
4.1
6.3
5.3
3.7
2.4
7.5
8.3
5.5
6.6
5.6
6.2
3.0
10.1
11.4
13.1
11.1
7.7
8.0
8.0
11.3
10.9
12.8
13.5
10.5
7.4
7.8
5.9
9.4
5.5
4.6
2.2
10.4
—
—
12.7
5.2
9.3
7.5
,7.3
2.5
Site #
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Wet Sulfur Deposition
Obs.
.03
.35
—
.63
—
.20
.96
.06
.10
.12
.50
.20
—
—
.44
—
—
—
—
(
ASTRAP
0.16
1.57
—
0.17
— '
1.8
2.7
0.5
0.2
1.3
.1
.04
—
—
1.9
—
—
—
—
RCDM
.05
.46
—
.20
—
.48
.61
.16
.11
.33
.15
.07
—
—
.74
—
—
—
—
(kg.s.ha."1)
AES-LRT
.04
1.20
—
1.12
—
1.64
1.76
.21
.16
.67
.69 ^
.49 '
'**• en
—
2.91
—
—
—
—
(1) For site name, network and location see Table 3-6
(2) There are inherent variabilitiesjin SO2 concentrations due to local effects
'• which the present models cannot Simulate. . .
i *' • i ;
r ' "' ' i j ' i '
NOTE: Results for ENAMAP and the other 3 models are, expected to be available by September 1981 in an Addendum
-------
,
Site #
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
49
50
51
52
53
so2
Obs.
.002
.018
.002
.008
.014
.001
.005
.002
—
.025
—
.004
.014
.006
.006
.013
.005
—
.004
.008
.007
—
—
.003
.008
—
—
— -
—
— -
— —
—
—
r i \ t
Table 4-2
Concentration (ppm)
I ' ^^.
Comparison i of July 1978 M^phly Average Model Concentrations
and Totali Wet Sulfur Deposrcions with Observations
(2)
ASTRAP RCDM AES-LRT
.007
.008
.002
.007
.007
.003
.010
.003
— .
.017
—
.004
.014
.010
.009
.012
.003
—
.004
.008
.012
—
—
.003
,021
—
—
—
—
—
—
—
—
IV*k^» f* -1 t* y"»
.004
.006
.005
.009
, ,.007
.005
.006
.004 -.
—
.007
—
.007
.007
.006
.005
.006
.005
—
.004
.006
.008
—
—
.002
,006
— !
—
t .
—
— •
—
• i
—
.014
.018
.018
.027'
.018
.011
.013
.010
—
.020
—
.015
.016
.017
.013
.015
.013
—
.005
.015
.016
l i
T-
.010
.015
—
! ;
I
1
— —
• ' 1
j
T^lf «%»"t>3
t '
SO^ Concentration (ug/for)
i i
Qbs. ASTRAP RCDM AES-LRT
i i
9.3 10.7 8.0 11.4
12.8 10.2 9.4 13.4
9.5 4.2 8.5 10.1
16.9 8.9 • 9.7 15.1
13.8 5.9 7.3 10.4
.11.6 3.3 6.5 9.6
11.2 9.9 8.2 11.7
• 8.9 3.7 7.8 9.4
__ — __ —
15.4 16.1 9.6 14.9
16.4 8.6 9.8 14.4
— — — —
12.0 9.2 8.9 10.5
8.8 10.1 7.2 11.9
10.0 8.4 8.3' 8.7
11.8 12.4 6.5 13.0
9.2 3.1 8.7 7.7
12.8 3.3 6.1 5.8
5.9 3.7 5.0 3.2
10.9 11,0 9.1 13.6
13.7 ' 11.3 9.0 13.2
7.0 ' 8.5 7.8 11.5
10.9 9.6 9.5 13.4
7.4 6.7 6.3 10.9
16.0 15.4 9.0 13. £
11.1 8'.8 8.1 11.3
11.3 9.9 8.2 12.4
}d.o '2.9 5.7 3.4
— •__ — —
|1.9( 5.1 5.0 '4.7
... — — —
| • • i
|5.2 1.8 3.5 2.1
7.3 3.7 4.9 4.2
'2.5 2.1 4.2 6.4
Site #
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
Wet Sulfur Deposition
Gbs.
.37
.61
.57
.08
—
1.22
.88
.78
.97
.92
.77
1.39
—
1.69
0.89
1.50
—
0.27
—
ASTRAP
.14
2.28
.94
.20
—
2.14
3.19
.92
.63
1.46
.26
.11
—
2.90
2.82
.93
—
.80
—
1 |
i
RCDM
.12
.51
.18
.18
—
.55
.69
.23
.14
.39
.14
.07
—
.63
.77
.69
—
.50
—
(kg.S.ha."1)
AES-LRT
.39
1.85
.36
.30
—
1.37
1.20
.79
.27
1.98
.53
.14
—
1.83
4.15
2.04
—
1.66
—
(2) There are inherent variabilities|in SO2 concentrations due to local!
effects which the present models cannot simulate ' ' ; |
NOTE: Results for'ENAMAP'and the 3'models are expected to be available by'September 1981 in an Addendum
',1 • i • ; i I I ' • > ! • I I ! I I ' I '
-------
4-7
July wet sulfur depositions were on the average slightly
over-predicted by the AES and ASTRAP models and were on the
average under-predicted by the RCDM model. The standard
deviations for the three models are large and there were
only 15 observations.
-The comparison of annual model averages with observations
was possible only for a small data set. Tables 4:-3 and 4-4
summarize this preliminary comparison. Based on 9 stations,
the observed annual SC>2 concentrations on the average- were
over-estimated by ASTRAP, AES-LRT and MOE-LRT. The RCDM model
under-estimates on average. Over-prediction was less for
the MOE-LRT and ASTRAP models than by the AES-LRT model; how-
ever/ statistically there was no discernible difference due-
to the small sample size. The annual 804 concentrations are-
on the average under-estimated by the MOE-LRT and ASTRAP
models at the 13 sites considered. (Note that the ASTRAP
annual average is based on only the arithmetic average of 2 .
monthly averages, namely, January and July). The AES-LRT model
on the average slightly over estimates the 804 concentration.
The predictions of the RCDM model were on average:, very: close to
the observed 804 concentrations.
Annual wet sulfur depositions were slightly over-predicted
by all four models when assessed on the average of. the 8
CANSAP data sites reporting at least 10 months of data in 1978.
The deviations about the average geometeric mean are large for
-------
Table 4-3. Comparison of 1978 Annual Average Model Concentrations and Total Wet Sulfur Depositions
With Observations
(2)
(1)
Site"!
1
2
3
4
5
6
7
8
9
49
50
51
52
53
902 Concentration(ppm)
Obs.
.005
.020
.007
.015
.014
.004
.009
.003
.003
—
— .
—
—
• —
U)
(2)
(3)
NOTE:
(3)
ASTRAP
.011
.013
.005
.012
.010
.005
.014
.005
.007
—
—
—
—
—
RCDM
.004
.006
.005
.009
.007
.005
.006
.004
.007
—
—
—
—
—
AES-LRT
.011
.016
.015
.027
.023
.015
.014
.012
.016
—
—
—
—
—
MOE-LRT
.008
.012
.009
.014
.013
.004
.008
.004
.007
—
—
—
—
—
SO^ Concentration (ug/irr)
Obs.
5.7
7.5
6.3
10.1
8.7
7.7
7.6
6.5
7.3
8.8
—
4.8
6.0
3.4
(3)
ASTRAP
10.0
10.5
5.0
8.6
5.8
3.4
8.8
4.2
5.3
4.9
—
3.7
3.3
1.8
RCDM
8.3
9.5
8.8
9.5
7.1
6.4
7.9
7.8
9.0
5.8
—
3.2
5.0
4.4
AES-LRT
9.6
14.1
15.1
14.7
12.3
13.2
9.0
14.1
14.6
3.7
—
1.4
3.3
4.3
MOE-LRT
6.4
8.2
7.1
7.4
5.1
3.2
5.4
4.5
6.1
3.5
—
1.9
3.4
3.6
For site name, network and location see Table 3-6.
There are inherent
the present
models
variabilities in SO2 concentrations due to local effects which
cannot simulate. . ,
Annual average based on arithmetric mean
Results for ENAMAP and the other
3 models
in an Addendum.
i
i ;
1
i
i
i i
. •
•
i i t
'
•
1 ( i
' ;
. 1
,
"
* • ' '
t • *
. • i
t ' i
> 1 1
' 5 1 '
are
. i
-
i .. i
of January
and July
monthly
expected to be available by
.
* ••
i ,
, . .
• i •
•
* i
averages.
September
1981
...
1
!
i
f
00
-------
Table 4-4 Comparison of 1978 Annual Average Model Wet Sulfur Depositions (kg.S.ha."1)
with Observations
(3)
Site #
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
(1)
Obs.
2.92
7.61
—
6.12
—
7.07
11.59
—
7.04
—
7.36
6.42
—
—
9.27
—
—
—
—
Wet Sulfur
(2)
ASTRAP
1.77
23.01
—
2.23
—
23.89
35.36
—
5.02
—
2.32
0.96
—
—
28.23
—
—
—
—
Deposition (kg.
KCDM
1.17
6.15
—
2.35
—
6.57
8.28
—
1.46
—
1.73
0.81
—
—
9.36
— .
—
—
—
AES-LRT
1.48
14.14
—
4.03
—
17.28
18.96
—
2.41
—
3.70
2.25
—
—
33.40
—
—
—
—
S.ha.-1)
MOE-LRT
2.88
9.29
—
6.56
—
9.58
15.53
3.74
—
5.74
3.70
—
—
25.28
—
—
—
. — •
t
vo
(1) Sites with }.ess than 10 months of monthly deposition data contributing
to the total for 1978 have been omitted from this comparison.
J2) Annual average based on arithmetic mean of January and July monthly averages.
{3) Includes a background deposition of 2 kg.S.ha."-*- due to emissions not included
! in the model inventory. ,,
-------
4-10
both the ASTRAP and AES-LRT models; however, the MOE-LRT showed
much smaller deviations between the observed and the predicted.
The RCDM predictions of annual wet sulfur deposition were much
lower on the average than the observed.
The mean (Mg) and standard deviation (Sg) of the
logarithmic bias
di =£n C0 - QJI Cp
i *i
are presented in Table 4-2. The station names, numbers and
locations are presented in Section 3.4 (Table 3-6).
During Phase II, a hierarcy of model evaluation statistics
were adopted, but only the AES-LRT model computed all of them
(see next section). It is expected that these statistics
for the other participating models will be available by
September 1981 in an Addendum to Chapter 4 of the Modeling
Subgroup Interim Report. Note that the AES-LRT evaluation
data set is slightly different than the observation data
which was used in this section.
-------
4-11
Table 4-5. Mean and Standard Deviations of the Logarithmic Bias Between
Model Simulations and Observations for 1978
Pollutant
Model
S02
AES-LRT
ASTRAP
OME-LRT
RCDM-2
S04
AES-LRT
ASTRAP
OME-LRT
RCDM-2
WSDEP
AES-LRT
ASTRAP
OME-LRT
RCDM-2
January
N Mg Sc
21 -0.24 0.37
21 -0.008 0.54
21 0.86
26
0.47
26 -0.22 0.57
26 0.05 0.61
0.07 0.48
11 -1.03 0.62
11 -0.78 1.48
11 -0.04 0.86
July
N
20
* 20
20
30
30
30
15
15
15
-0
-0
0
0
0
0
-0
-0
0
Mg
.91
.16
— —
.04
.10
.43
— —
.32
.20
.17
—
.85
S
0.
0.
0.
0.
0.
0.
1.
1.
a.
g
71
55
— •
68
43
46
— —
26
04
05
— •
97
N
9
9
9
9
13
13
13
13
8
8
8
8
Mg
-0.
-0.
-0.
0.
-0.
0.
0.
-0.
0.
0.
0.
0.
Annual
(1)
80-
16-
12
22
19
26
36
01
24
18
07
95-
Sg
0.
0.
0.
0.
0.
0.
0.
0.
2.
1.
0.
0.
(1
54
48
37
60
64
38
37
27
29
12
34
72
Note: Site 44 has been eliminated from the calculation
N: number of sites
Mg: mean of the logarithmic bias
Sg: standard deviation of the logarithmic bias
-------
4-12
4.2.2 Evaluation Statistics for the AES-LRT Model
The model results have been compared with data in 1978
from:
o (Canadian Sampling of Precipitation) CANSAP net-
work, which provides sulfate in precipitation on
<.
a monthly bases.
o (Electric Power Research Institute Sulfur Regional
Experiment) EPRI SURE network which measures
ambient air concentrations of S02 and 804 on an
hourly and 24 hourly basis, respectively. The
network had 45 monitors (Class II) operating during
six intensive months and 9 monitors (Class I)
year round.
Data from these networks have been screened for gross errors
and for the EPRI SURE network, only months (stations) with
data capture of more than 65 percent have been selected.
4.2.2.1 CANSAP DATA
The measurements from the CANSAP network are generally
higher than the modeled values from the AES-LRT model
especially at the more remote sites (see AES-LRT Model Profile)
This effect is partially due to inadequate model parameteri-
zation but may also be due to poor siting, contamination and
evaporation effects in the data samples and the absence of
background concentrations in the model values. The network
-------
4-13
data quality is being reviewed and some locations may not be
found entirely suitable for continued model evaluation.
Tables 4-6 and 4-7 show the logarithmic statistical
parameters for the model evaluation using CANSAP data. Table
4-6 shows a small mean error for January but the measured
means were larger than the modeled means for July, and over
the year. The standard deviations of the residuals (RMSB)
were smaller than the standard deviation of the measurements
for each time period indicating that the model showed some
skill in simulating the measured deposition distributions.
The spatial linear correlation coefficients (r) have values
of 0.6 to 0.85 indicating that the model generally estimated
an acceptable sulfate deposition pattern throughout eastern
Canada.
Table 4-7 shows the logarithmic interval statements of
the 95% confidence level for the bias and the variance of
the residuals. The annual mean error is 0.71 and the annual
standard deviation of the residuals is 0.78. The confidence
limits are such that there is a 95% chance that the annual
bias lies between -0.06 and 1.5 and that the annual variance
of the residuals lies between 0.31 and 1.7.
4.2.2.2 EPRI-SURE Data
Tables 4-8 and 4-9 show the logarithmic evaluation results
using the EPRI-SURE network data for sulfur dioxide and sulfate
concentrations. Twenty class 1 and nineteen class 2 sites were
-------
4-14
Table 4-6. Logarithmic Statistics of Wet Sulfate Deposition
from the CANSAP Network
1978
Jan.
July
Annual
Measured
Std.
Mean Dev.
.33 .66
1.5 .72
1.5 .47
Model
Std.
Mean Dev.
.28 .88
.97 1.1
.76 1.1
Mean
Error
d
*.
.05
.55
.71
Corr.
Coeff .
r2
.37
.73
.64
RMSB
RMSE
-------
4-15
Table 4-8. Logarithmic Statistics of Sulfur Dioxide
Concentrations from the EPRI-SURE Network
1978
Jan.
July
Annual
Measured
Std.
Mean Dev.
-4.4 .62
-5.2 .80
-4.9 .69
Model
Std.
Mean Dev.
-4.1 .51
-4.3 .36
-4.1 .29
Mean
Error
d~
-.22
-.85
-.78
Corr.
Coeff .
r2
.64
.39
.35
RMSB
RMSE ^d"
.42 .37
1.1 .64
.95 .57
Table 4-9. Logarithmic Interval Statements of Sulfur- Dioxide
Concentrations from the EPRI-SURE Network at the
95% Confidence Level
Time
1978
Jan.
July
Annual
Bias
d-L
-------
4-16
selected on a data capture basis for the January and July
evaluations but only nine class 1 sites were used for the
annual evaluation.
The ratios of modeled to measured sulfur dioxide and
sulfate concentrations for January/ July and annually for
1978 from the EPRI-SURE Network were computed (see AES Model
Profile). There is a wide variation in the sulfur dioxide
concentration ratios (7.5 to 0.7) partly because of the
inherent variability in sulfur dioxide concentration due to
local emission and terrain effects which the model cannot
simulate, partly because of the presence of zeros and ques-
tionably low measured values which were below the detection
limit of the instruments and partly because the present model
parameterization tends to overestimate the sulfur dioxide
concentration especially during the summer months.
The logarithmic statistics in Table 4-8 are based on the
sulfur dioxide concentration in ppm. The statistics show that
the model mean is generally higher than the measured mean
(e~4'lppm > e~4*9ppm), the standard deviation of the residuals
is less than the standard deviation of the measurements and the
square of the correlation coefficient (r^) indicates that the
model explains between about 1/3 to 2/3 of the measured data
variation. The logarithmic interval statements in Table 4-9
show that the annual bias ranges between -1.4 and -.21 and
the annual residual variance ranges between 0.15 and 1.2 for
eight degrees of freedom.
-------
4-17
Table 4-10 shows that the modeled sulfate concentrations
are generally larger than the measured concentrations. The
square of the correlation coefficient indicates that very
little of the spatial variation of the sulfate concentration
is explained in a linear way by the model. In addition, the
standard deviation of the residuals (RMSB) is larger than the
standard deviation of the measured data. The implication is
that the current parameterization of the model has difficulty
in simulating the spatial distribution of monthly and annual
average sulfate concentrations as measured by the SURE network
but is more skillful in simulating the sulfur dioxide distri-
bution. This appears to be partly due to the larger amplitude
variation of the measure sulfur dioxide data which the model
simulates better than the smoother, more evently distributed
measured sulfate concentrations.
The confidence limits of the standard deviations of the
residuals show that there is a 95% chance that the logarithmic
residual standard deviation lies between 0.13 to 0.43 in
January, 0.06 to 0.21 in July and 0.02 to 0.19 annually for
1978 given the degrees of freedom shown in Table 4-11. The
annual logarithmic bias ranges from -0.75 to -0.35.
4.2.2.3 Evaluation Summary
The ratios of modeled to measured concentrations indicate
that the current parameterization gives mean model air concen-
trations which are generally higher than the measured air
-------
4-18
Table 4-10. Logarithmic Statistics of Sulfate Concentrations
from the EPRI-SURE Network
1978
Jan.
July
Annual
Measured
Std.
Mean Dev.
1.8 .32
2.4 .27
2.0 .17
Model
Std.
Mean Dev.
2.1 .44
2.4 .38
2.6 .19
Mean
Error
1
-.23
.02
-.55
Corr.
Coeff.
r2
.10
.30
.06
RMSB
RMSE ^d"
.51 .46
.32 .32
.59 .23
Table 4-11. Logarithmic Interval Statements of Sulfate
Concentrations from the EPRI-SURE Network at
the 95% Confidence Level
Time
1978
Jan.
July
Annual
Bias
d!
-------
4-19
concentrations. These effects are due to a combination of
modeling assumptions and to some extent to the siting and
accuracy of the network data. For Phase I and II studies,
the model used a relatively low sulfur dioxide dry deposition
velocity (0.5 cm s~l) which produces somewhat larger concen-
trations and wet depositions close to major source emission
areas. The mixing heights are climatological monthly averages
and do not properly simulate the variations in the boundary
layer depth any one day. The assumption of an inversion
lid prevents mass from leaving the boundary layer so that
simulated surface concentrations may be occasionally too high.
The temporal and spatial correlations and residual statis-
tics exhibit a wide variation between sites and time periods/
but the statistics indicate that the AES-LRT model shows some
skill at simulating the spatial and temporal concentration
patterns in spite of the many modeling assumptions. The scar-
city of reliable, consistent and extensive air quality and
precipitation chemistry data gives wide limits to the confi-
dence intervals and makes the statistical evaluations diffi-
cult and somewhat inconclusive at this point. However, some
meaningful model modification can be made and tested using
these data bases as a statistical reference and these tests
will be conducted on a continuing basis. In addition, the
emissions inventory is being updated and converted to a
seasonal basis.
-------
5.1-1
5. DEVELOPMENT AND INTERCOMPARISON OF
PHASE I~AND II TRANSFER MATRICES
5.1 Philosophy and Methodology
The transfer matrix f^j is a function of a large number
of variables, each of which can assume values within appropriate
limits. This implies that the sensitivity of f ij to changes
in these variables is an important factor in the selection of
an "optimum" emission reduction strategy. In this chapter we
introduce the sensitivity matrix as one way of quantifying
this sensitivity.
Recall that the deposition Dj (or concentration) at a
receptor j is related to emissions Qi from source regions
denoted by "i" through the equation
f ^i (5-1)
The change in Dj associated with changes in both f^j and
can be written as
Dj = . Qi f ij
i i
+"2 & Qi fij (5-2)
i
where A denotes a change. Let us think of A f ij as the
"error" related to the uncertainty in model input. Then
Dj can be related to a change in emission A Qi only if the
uncertainty in A. Dj is much less than ^ AQifij. The
equivalent mathematical statement is
^ (Qi + AQi)Afij « Z A Qi f^ (5-3)
-------
5.1-2
This discussion clearly points out the importance of knowing
the uncertainty in fij which we denote by rij. In theory we
could calculate part of the contributions to fij by running
the long-range transport model for various ranges of input
variables. However, that provides only the contribution due
to uncertainties in model parameters, not the inherent uncer-
tainties in the model itself. The problem with this approach
is that it is necessary to recompute fij each time the range
of a chosen input parameter is modified. Specifically, we
would have some difficulty in answering a question such as:
How does fij change if the deposition velocity v^ is altered
by a factor of three rather than a factor of two? We can
make the description of fij more flexible by writing
(5-4) -
where |3k= A^k/^Mc
and c*. k refers to the variables fij depends on. The sensitivity
matrix is defined by
Sijk = ><^ij/*>vv <*^ ' (5-5)
The reason for using logarithms in (5-5) becomes clear if we
notice that
Sijk = (Afij/fij)/^^/^) (5-6)
-------
5.1-3
we see that Sjifc is diraensionless; its magnitude will tend
to be manageable. Furthermore, we are usually interested in
the sensitivity of f^ to fractional changes in Q^. Sj.ik
.is ideally suited for this.
In writing (5-3) we have assumed that s;[-i]c is not a
strong function of k. Otherwise the linear form of the
equation is not valid. Only model testing will tell us
whether our definition of Sijk is useful. Note that s^^,
£
unlike .• ^, is not a function of A«CV So once it is com-
1] K.
puted we can determine the sensitivity of fij to a given /i^.
We should point out that Sij]C will depend on the "struc-
ture" of the long range transport model from which it is
derived. Specifically,* s^jk for the same parameter such as
deposition velocity will differ from model to model.
Transfer matrices may contain substantial information
about the budget implications of a model and about the meteo-
rological conditions for which the model was operated. If
the receptor areas of the matrix representation span a large
region, one can directly calculate budgets for material emitted
and deposited within that region.
4
Suppose a set of matrices Sj_j give deposition flux of
type & in receptor areas i due to unit emissions from source-
areas j. Then the inner product of each matrix with area of
each region (Aj_)f
-------
5.1-4
Ai Sij (5-7)
represents potential mass deposition of type ^ over the whole
region per unit time, per unit of emission rate from source
j (i.e., a dimensionless quantity).
Combining all the forms of deposition, one can obtain
the total potential mass fraction of pollutant deposited in
the region
$j = ^ $j (5-8)
and the relative fractions of each type,
IjVfj (5-9)
More generally, the mass fraction deposited in any
•
aggregate subregion is just the partial sum over the desired
receptor regions.
One could say that each area weighted matrix element,
summed over deposition types
At Zl Sj'j (5-10)
L
is a measure of the "coupling" strength between source j and
receptor region i. It represents the fraction of emissions
from j that would be deposited in i.
Thus, the matrix provides substantial information about
various budget breakdowns within the extent of coverage of
the receptor regions in the representation. The fraction
transported out of this region presumably is (1 - $j), unless
the model leaves mass suspended in the atmosphere or in other
sinks.
-------
5.1-5
Other measures of budget can also be derived. For
example, if the centerline distances among emitter and receptor
regions is known (r^j), then average transport distance from
j is given crudely by
5. JL \
ij sij + Rj Aj sjj / (5-11)
where Rj is a measure of average transport distance within the
local (diagonal) region.
Some similar measures can be defined from a receptor
point-of-view. For example, the average distance traveled
by pollutants deposited in i would be,
(5-12)
where D^ = ^ L*. Si-jE^ is the total deposition flux in
region i.
-------
5.2-1
5.2 Transfer Matrices
5.2.1 Phase I
In Phase I, wet sulfur deposition transfer matrices were
generated from the MOE, AES, ASTRAP, ENAMAP, and RCDM models
using somewhat different emission inventories. In order to
intercompare the individual matrix elements the values were
normalized using a unit emission rate of 1 Teragram of sulfur
per year. The normalized matrix elements for 11 emission
regions and 9 receptor areas are presented in Table 5-1.
The actual annual sulfur emission rates used by each model
are presented in column 3 of Table 5-1. The standard devia-
tions over the 5 model values for wet sulfur deposition, a
convenient measure of the variability among the models, ranged
from 0.01 to 4.32 with an average value of about 0.50. The
ENAMAP model results were primarily responsible for the
largest standard deviations. The standard deviations over
the four model values for wet sulfur deposition, excluding
ENAMAP, ranged from 0.01 to 1.75 with a mean of about 0.42.
The percent contributions of each source regions on each
receptor area are presented in Table 5-2. The standard
deviations over the 5 model values of wet sulfur deposition
ranged from 0.01% to 22.7% with an average value of about 5%.
Again the ENAMAP model results were primarily responsible for
the largest standard deviations. These variations are attri-
butable to the differences in the way the modelers parameterized
-------
I
Table 5-1. Phase I Transfer Matrix of:
Annual |Wet Deposition of Sulfur (kg.ha~Tl'.yr~l)
per unit emissiori (Tg.S.yr"^) ' ! ' •' I
> M I t
(1)
Source
Regions
1
Mich.
2
111.
Ind.
3
Ohio
4
Penn.
5
N. York
to Maine
6
Kent.
Term.
Models
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
! • 1 '
1
Emiss.
(Tg.S)
0.784
0.973
1.194
1.194
1.194
2.538
1.937
2.077
2.077
2.077
1.983
2.381
2.163
2.163
2.163
1.021
1.028
0.990
0.990
0.990
1.143
1.204
1.208
1.208
1.208
1.202 !
1.418
1.473' !
1.473 j
1.473 i
1 ! I
> I
1
B. Waters
(1)
0.07
0.21
0.44
0
1.11
0.06
0.05
0.24
0
0.79
0.04
0
0.08
0
0.30
0.03
0
0.01
0
0.10
0.02
0
, 0
0
0.05
j 0.03 I
0
0.07
0 '
6.28
! 1 i
• i -
i
' •
t
i
Alg.
(2)
0.40
2.40
2.59
0.97
3.95
0.23
1.20
1.32
0.11
1.14
0.15
0.25
0.86
0.06
0.80
0.12
0.29
0.29
0
0.36
0.07
0.17
0.08
0
0.21
0.10
0.14
0.45
o.oi
0.38
t
i
1 i
i
i i i
! '' 1
Musk.
(3)
0.93
3.20
2.50
1.67
2.51
0.32
1.10
1.40
0.08
1.35
0.32
1.80
1.84
0.36
2.32
0.28
1.30
1.13
0.04
1.62
0.19
0.50
0.44
0.01
1.08
0.14 :
0.71 !
0.16
o.oi i
0.63 :
i
, i
i
i i
i i
i
Rece
Que.
(4)
0.34
1.00
1.46
0.13
1.68
0.15
0.31
0.75
0.02
0.81
0.19
0.46
1.04
0.02
1.23
0.21
0.68
1.10
0 .
1.06
0.25
1.30
0.79
0
0.99
0.09
0.07
0.42
0
0.36
!.
1
tor Areas
S. N.Sc.
(5)
0.39
0.31
0.55
0.19
0.38
0.18
0.10
0.37
0.02
0.26
0.28
0.21
0.60
0.09
0.52
0.40
0.29
1.20
0.07
0.95
1.00
2.00
2.51
2.86
2.33
0.13
0.07 <
0.24
6.01
6.17
! ,
i
t
'
i
i
Vt. NH.
(6)
0.56
0.72
0.73
0.20
0.75
0.23
0.30
0.52
0
0.48
0.32
1.00
0.91
0.05
0.96
0.39
1.80
1.79
0.07
1.59
0.56
2.20
3.00
1.28
2.98
0.14
0.21
0.38 !
0.01
0.29
i
. i 1
'
Adir.
(7)
0.86
1.10
1.14
0.11
1.11
0.31
0.36
0.82
0.01
0.74
0.47
1.30
1.50
0.12
1.60
0.57
2.20
2.59
0.32
2.63
0.80
2.40
2.50
0.97
3,19
0.18
0.42 !
0.63 !
9-pi i
0.46
• i
1 * i
!
1
i
Penn.
(8)
1.70
1.70
0.81
0.13
1.09
0.76
1.10
1.18
0.06
1.40
2.00
4.70
3.29
1.01
3.66
4.40
7.90
4.61
10.61
4.24
0.33
0.42
0.69
0.07
0.88
0.46
1.50
1.88
0.13
1.48
(
Smokies
(9)
0.12
0.21
0.07
0.14
0.32
0.47
0.77
0.60
0.36
0.91
0.23
0.25
0.53
0.09
0.83
0.11
0.10
0.07
0
0.43
0.05
0
0.01
0 i
0.13 '
1.60
3.10
4.22
4.24
3.95
1
in
-------
Table 5-1. Phase I Transfer Matrix of: (continued)
Annual Wet Deposition of Sulfur (kg.ha'^.yr"1)
per unit emission (Tg.S.yr"*)
7
W.Virg.
to N.C.
8
Rest of
(USA) Fid
to Mo. to
Minn.
9
Ontario
10
Quebec
11
Atlantic
Provinces
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
i
1.703
1.223
1.610
1.610
1.610
1.196
3.743
4.012
4.012
4.012
0.906
0.985
0.949
0.949
0.949
0.595
0.519
0.464
0.464
0.464
0.187
0.235
0.453
0.453
0.453
* ENAMAP
did not consider s<
0.03
0
0.02
0
0.14
0.09
0.24
1.09
1.90
2.16
0.08
0.10
0.09
0
0.29
0.06
0
0.02
0
0.02
0.01
0
o ;
-L_*
0
(
Hjrce regior
•
0.08
0
0.34
0.01
0.35
0.39
0.61
0.56
0.46
0.92
0.51
1.80
2.92
1.32
2.04
0.18
0.19
0.52
0
0.14
0.03
0
0.02
—
0.02 j
, ,
i 11 4n
0.15
0.33
0.80
0.11
1.08
0.34
0.24
0.44
0.15
0.42
1.60
3.30
4.71
12.86
5.07
0.32
0.58
1.14
0
0.47
6.05
0 >
0.10
—
0.06
, . ,
ttie Pha*
i . i
(1) Annual deposition transfer matrix elements for th<
arithmetric m£an of the ! equivalent
)
1
!
,
1
1 1
0.13
0.33
0.61
0
0.65
0.15
0.05
0.29
0.03
0.32
1.00
1.70
3.83
0.59
4.10
1.50
2.90
2.61
0
1.23
0.16
0.43
0.63
—
0.11
i
0.28
0.25
0.56
0.02
0.52
0.15
0.03
0.15
0.03
0.08
0.57
0.61
1.17
0.20
0.86
0.73
0.96
2.06
2.20
1.50
0.74
2.60
3.07
—
2.42
0.22
0.90
0.87
0.05
0.79
0.20
0.08
0.20
0.02
0.15
1.10
1.60
1.41
0.16
1.74
2.30
3.30
2.09
1.50
2.41
0.16
0
2.48
—
0.60
,
0.29
1.10
1.24
0.06
1.23
0.26
0.13
0.27
0.02
0.23
1.20
2.00
3.08
0.63
2.51
0.59
1.50
1.90
0.04
1.33
0.10
0
1.23
—
0.23
;e I modeling , ' , .
0.85
3.50
4.04
2.67
4.99
0.40
0.53
0.50
0.31
0.46
0.53
1.20
0.43
0.18
0.90
0.13
0.19
0.12
0
0.15
0.05
0
0.08
—
0.04
0.16
0.49
1.18
0.26
1.39
1.00
2.50
1.40
0.14
1.21
0.05
0
0.02
0.01
0.14
0.03
0
0
0
0.02
0.01
0
0
—
0.01
i
1 , ' '
j ASTRAP and ENAMAP models are based on an ,
January 1978 and July; 1978 elements.
1 : !
1
; i
.> , . . , ,
. ' i
1 ' 1 j • • :
I ! . .
• . i ; > i •
I : i
>
j
i
i * ',
i
, •
1 • ' i
i ' '
I"'--- , i 1
i i '
'
i i )
Ul
?0
-------
Table 5-2. Phase 11 Transfer Matrix of:
' . T i T '
! Percent Gontributic
I
!
Source
Regions
1
Mich.
2
111.
Ind.
3
Ohio
4
Penn.
5
N. York
to Maine
6
Kent.
Term.
Models
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
BITMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
B. Waters
(1)
8.1
13.3
13.5
0
15.4
24.2
6.7
3.8
0
5.5
12.9
0
1.4
0
2.4
4.8
0
0.2
0
0.8
4.8
0
0
0
0.4
6.5
o ,
1.6
.P
2.7
! I
i
i
in 'to Annual Wet Sulfur Deposition
' ' 1 ' ' "1 . ' ' ' " ' i :
1
Alg.
(2)
11.5
22.1
35.2
35.0
44.1
21.5
23.1
9.0
1.9
6.4
11.1
5.8
6.7
1.3
5.1
4.5
2.9
2.3
0
2.3
3.3
1.9
0.6
0
H
4.5
M
;4.3
04
3.0
• ' i
i
•
i >
i >
' i i
Musk. .
(3)
14.3
17.6
25.4
19.6
23.4
15.9
12.5
7.2
0.5
6.3
12.3
25.0
10.8
2.4
12.5
5.5
7.4
6.7
0.3
8.8
4,3
3.4
2.4
0.1
5.3
3.3
5.7
5.4
0.1
4.1
f
i
i
'
t • ' 1 '
: j
Receptor Areas '
Que.
(4)
6.7
11.1
19.3
25.1
21.8
10.0
6.7
5.0
2.2
5.3
9.5
12.2
7.9
1.8
9.2
5.4
7.8
8.5
0
8.1
7.4
17.8
5.5
0
6.7
2.8
M
3.9
,9-?
,3.3
1 1
•
S. N.Sc.
(5)
6.2
5.1
10.0
3.9
' 8.6
9.6
3.4
3.3
0.2
3.0
11.6
8.5
6.2
1.1
6.8
8.5
5.1
12.7
0.8
12.7
25.0
40.7
23.7
31.2
27.7
3.3
1.7
3.0
04
2.7
Vt. NH.
(6)
7.5
5.3
10.3
11.5
11.1
9.9
3.8
3.7
0.1
3.5
10.7
18.3
7.5
1.6
8.2
6.8
13.7
14.9
2.3
13.8
10.9
20.6
22.3
38.4
23.2
2.7
2.3
3.7
0.4
3.0
i i t
Adir.
(7)
10.6
7.0
12.9
8.6
12.5
12.5
4.5
4.7
0.2
4.2
14.8
20.4
9.8
5.6
10.4
9.2
14.7
17.1
14.7
17.3
14.4
18.5
14.8
39.7
18,8
2.3
M
5.0
0.6
.3.6
'
Penn.
(8)
8.6
5.1
6.9
1.3
8.7
12.5
6.6
5.1
0.3
5.6
26.3
33.7
16.4
6.1
16.8
29.6
24.2
23.2
64.8
19.7
2.5
1.5
3.1
0.4
3.7
3.6
6,3
11.3
1.0
8.2
1
Smokies
(9)
1.7
1.2
0.9
3.8
4.0
22.3
9.0
3.9
4.8
5.7
8.3
3.6
4.0
1.3
5.9
2.1
0.6
0.6
0
3.1
1.1
0
0.1
0
0.8
37.1
26.4
38.4
77.4
34.1
t
l
i
i
01
V
-------
5-2.! (Continued)
1
Phase ^ Transfer Matrix of:
Percent Contribution to Annual-Wet
-i....... -. .1 i ...... ^ . . ..
1
Sulfur Deposition
. 7
W. Virg.
io N.C.
i
' 8
Rest of
(USA) Fid
to Mo. to
Minn.
9
Ontario
10
Quebec
11
Atlantic
Provinces
Western
Canada
Eastern
U.S.A.
Contri-
bution :
Total
Canadian'
Contri- ;
but ion.
* ENAMAI
! MOE
i AES
! ASTRAP
i ENAMAP
RCDM
MOE
, AES
' ASTRAP
ENAMAP
RCEM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM
AES ,
ASTRAP
ENAMAP
RCDM
MOE
AES
ASTRAP
ENAMAP
RCDM j
MOE
AES
RCDM '
did not c
1 6.5
! o
i 0.4
i 0
1 1.2
1
!l6.1
60.0
J77.8
ioo.o
69.6
11.3
6.7
1.3
0
1.9
4.8
0
0.2 •
0
0.1
0
0
0
*
0
13.3
i
83.9
80.0
98,6
100.0
98.0
16.1
20.0
,1.5
0
,2.0
4.8
1 o
J3.0
!0.2
J2.5
i?.i
i2U
17.8
38i7'
23.9
17.0
17.3
18.9
22.8
10.9
4.1
1.0
2.2
0
0.5
0.4
0
0
0
,1.9 ,
i
78.3
79,8
78,8
77.2 !
88.6
21.5
20.2
21.2
22.8
11.4
! 5.1 '
! 2.3'
i 5a
1 0.8
i 6.4
l ' i
' s:o
i 5.1
ilO.4
1 4JO
9.2
27.4
18.8
22.9
72.2
22.6
3.7
1.7
3.7
0
1.4
0.2
0
0.1
0.1
0,5
68.7
79,0
73,4
,27.8
75.9
1
31,3
,21.0
26.7 :
72.2 I
24,1 i
5.6
14.4
15.1
0.3
5.4
t -
4.6
2.2
8.8
15.0
9.7
24.1
18.9
24.2
55.3
25.4
23.1
16.7
10.9
0.2
5.0
0.8
1.1
1.0
0.2
0 ,
i ;
1 t
i
> i
52.0
6,3.3
63.9
44.4
69.4 1
i
48.0
36.7
36.1 ;
55.6
30.6
: 9.8
! .5.1
6.4
! 0.3
! 7.4
1-3.7
I 1.7
i 6.1
i 1.5
4.3
10.8
10.0
10.0
2.0
9.3
8.9
8.5
11.7
14.4
10.7
2.9
10.2
6.8
6.8
0
i
1
*
77.7
71.3
71.5
83.7
73.2
, 522.6
28P7
,28.6
16.4 i
26.8
|6.5
8.4
;7.8
il.8
7.4
;4.l
!2.3
|6.5
'2.4
5.3
16.5
12.2
9.6
4.4
12.3
23.7
13.0
9.3
26.9
11.2
0.5
0
4.4
1.1
0
i
59.1 !
74,7
76.8 ;
68.7
75.4
40.7
25.2
23.3
31.3
24.6 1
7.9
8.9
\ 8.8
' 3.1
: 8.7
; 4.9
3.2
i 7.2
! 2.9
6.0
17.5
12.7
11.3
23.7
13.5
5.6
5.1
6.8
1.0
4.7
0.3
0
1.7
0.3
1.2
I
i
1
76.6
81.0 i
80.3
75.4
81.5
,23.4
,19.0
19.8 :
24.6 i
,18.5 i
9.9
12.8
21. 9 ;
17. 6'
25.0
3.1
6.0
!9.9
!7.6
8.5
3.2
3.6
1.8
0.9
3.4
0.5
0.3
0.3
0
0.4
0.1
0
0.1
0
0
t
96.1 !
96.2 !
97.8
99.1
96.1
3.8
3,9 ;
2.2 !
0.9 !
3.9 1
5.0
! 3.6
i 9'7
; 4.3
110.9
20.4
55.1
42.3
i 8.4
34.6
0.9
0
0.2
0.1
0.8
0.4
0
0
0
0.1
0
0
0
0
0
i
98.0
99.5
99.8
99.9
99.1
1.3
0
0.2
0.1
0.9
'• i i i i
onsider source region, 1 in the Ih,ase I modeling : i • 1
1 ' '' 1 ! ' ' 1 ! !
i i ' • i : ; i • ;
U1
V
in
-------
5.2-6
the physical processes and treated the available input data
- emissions, winds, precipitation, etc. (see Chapter 2 and
the Model Profiles).
The matrix elements show the largest variations in
normalized values and percentage contribution for the impact
of^Ontario emissons on Muskoka (1.60 from MOE to 12.86 kgS.ha.~l
yr"1 per Tg.S. from ENAMAP and 18.8% from AES to 72.2%
from ENAMAP). The large ENAMAP value was due to the location
of the receptor area about 300 km further west, much closer
to the Sudbury source region, than by the other models (ENAMAP
used the proper location for the receptor in Phase II).
The second greatest variation in matrix element values
was for the impact of the Pennsylvania source area on t'he
Pennsylvania receptor area. The values ranged from 4.24
(RCDM) to 10.61 kgS.ha."1 yr"1 per Tg.S. (ENAMAP). Other
matrix elements in Table 5-1 with significant variations
included the impact of the Michigan source region on the
Algoma receptor area (0.40 from OME to 3.95 from RCDM), the
Ontario source region on the Quebec receptor area (0.59 from
ENAMAP to 4.10 from RCDM), the Ohio source region on the
Pennsylvania receptor area (1.01 from ENAMAP to 4.70 from
AES), and the Virginias to North Carolina source area on the -
Pennsylvania receptor area (0.85 from MOE to 4.99 from RCDM).
Those matrix element values with the least variation -
where the models agree the best - tend to be associated with
the receptor areas farthest from the source regions.
-------
5.2-7
For instance, for all intents and purposes, all the models
indicate no impact on the Boundary Water receptor area from
the Canadian Atlantic Provinces.
It was concluded that no one model consistently generates
extreme matrix element values. The values generated from any
one model may be significantly higher (or lower) than those
generated by the other models for a few of the matrix elements.
However/ the same model generates comparable values for many
other matrix elements. So it was further concluded that the
elimination of any one of the 5 models as a potential tool for
further studies was not justified in Phase II.
5.2.2 Phase II
In Phase II, several changes in the input data and
parameters to some of the models resulted in some changes
from the Phase I transfer matrix element values. These
changes included the use of:
(1) the same meteorological data (wind and precipitation
data for January and July of 1978),
(2) the same sulfur emissions inventory (1 Tg of sulfur
from each model source region - the number of model
source regions varied from 11 (AES) to 64 (ENAMAP),
however),
(3) the same locations of receptor areas (after Phase I,
it was discovered that not all the modelers were
using the same location for several receptor areas;
some models did not consider the Algoma receptor
area), and
(4) a more complex and more realistic wet and dry sulfur
deposition parameterization scheme in the ENAMAP
model.
(5) RCDM and ASTRAP revised their transfer matrices based
on analysis of their Phase I results.
-------
5.2-8
Table 5-3 presents the Phase II transfer matrix values
for wet sulfur deposition per Tg.S.yr"!. The standard devia-
tion over the absolute values for the models ranged from 0.01
to 4.75 with an average value of about 0.52. The largest
standard deviations were in receptor region 8 (Pennsylvania).
The transfer matrix values for the 2 new Phase II models,
MEP and MCARLO, will be discussed in the Addendum to the
Modeling Subgroup Report expected by September 1981.
The intercomparison of values in Tables 5-1 and 5-3 are
discussed in the next section for sets of transfer matrix
values in Phase I having the greatest range of values. The
complete set of Phase II transfer matrix displays are contained
»
in Appendix B.
-------
Table^3'. Phase II Trans fp
i Annual} Wet Depos
| per unit emissip
r Matrix of: , , . — ,
ition of Sulfur (kg.ha~l.yr~-'-) : j • • ! :
i (Tg.S.yr-f) ' • j • '• ; 1 • j . \
i • i , ... i ..... i . • | | i i i
1 ' . • , 1 ! i : 1
j i 1 • ! 1
;
Source
Regions
1
Mich.
2
111.
Ind.
3
Ohio
4
Perm.
i 5
N. York
to Maine
i
i
Models i
MOE i
AES :
ASTRAP
ENAMAP
RCDM
MEP
MCARLO
MOE
AES
ASTRAP
ENAMAP
RCDM
MEP
MCARLO
MOE
AES
ASTRAP
ENAMAP
RCDM
MEP
MCARLO
MOE
AES
ASTRAP
ENAMAP
RCDM
• MEP
MCARLO
i MOE
AES
] ASTRAP
ENAMAP
RCDM
; MEP
MCARLO
Ml 1
Emiss. 1
(Tg.S) |
0.784 i
0.973 i
1.194 i
1.194
1.194
2.538
1.937
2.077
2.077
2.077
1.983
2.381
2.163
2.163
2.163
1.021
1.028
0.990
0.990
! 0.990
: . ,
1.143
1.204
1.208
1.208
1.208
' 1
i - !
(i) Annual deposition matr
equivalent January 19"
>
• j Receptor Areas : i i '
Bi Waters ;
i
(i) :
0.07
0.21
0.06 '
0,04
0.30
0.14
0.06
0.06
0.05
0.07
0.00
0.25
0.05
0.01
0.04
0.00
0.02
0.00
,0.11
0.01
.0.00
0.03
| 0.00
0.00
0.00
0.04
0.01
o.oo
0.02
0.00
0..00,
0.00
Alg.
(2)
0.43 j
2.36 !
1.47 i
0.71
0.94
1.24
0.50
0.23
1.24
0.61
0.11
0.37
0.32
0.23
0.16
0.25
0.31
0.00
0.31
0.14
0.08
0.13
0.29
| 0.14
0.00
0.16
i 0.08
i 0.03
1 0.08
0.17
; 0.02
0.01
0.02 0.10
0.00 | 0.05
0.00
x elements
8 and July J
•'
'
0.01
Musk. !
i
(3) i
0.92
3.19 '
3.44
1.40
1.37
1.27
0.61
0.31
1.14
1.02
0.58
0.50
0.31
0.28
0.32
1.85
0.75
0.02
0.91
0.95
0.33
0.29
1.26
0.48
0.00
0.84
0.60
0.20
0.22
0.50
0.12
0.04
0.53
0.66
0.17
if or Aoittfif ana
978 elements.
t
Que.
(4)
0.33
1.03 '
1.10
1.32
0.73
0.18
0.33
0.15
0.31
0.71
0.59
0.28
0.08
0.20
0.18
0.46
0.92
0.75
0.47
0.23
0.33
0.21
0.68
0.74
0.73
0.54
0.45
0.34
0.26
1.33
1.38
0.60
0.47
1.24
0.35
ENAMAP
S. N.Sc. ,
I
(5) i
0.37 ;
0.31
0.20
0.00
0.28
0.08
0.06
0.18
0.10
0.12
0.00
0.12
0.02
0.04
0.28
0.21
0.25
0.00
0.23
0.08
0.05
0.39
0.29
0.52
i 0.00
0.37
0.20
0.05
i 0.98
1.99
0.59
; o.oo
0.53
1.06
i 0.08
Vt. NH. -
I
(6) !
0.54
0.72
1.03
0.73
0.35
0.25
0.31
0.22
0.26
0.70
0.46
0.17
0.12
0.17
0.31
1.01
0.83
0.99
0.38
0.33
0.27
0.38
1.75
1.94
i 1.55
i 0.79
i 0.83
0.36
0.59
2.24
3.02
! 1.63
1.30
: 2.29
0.52
imoqea.a are udstxj on i
i '
Adir. i
(7) i
0.83
1.13
2.33
1.35
0.57
0.42
0.40
0.30
0.36
1.16
0.35
0.28
0.13
0.28
0.46
1.34
1.79
0.90
0.65
0.47
0.47
0.57
2.24
2.15
; 3.91
1 1.37
I 1.28
0.50
0.83
i 2.41
i 2.94
3.46
1.71
1.89
0.29
Penn.
(8)
1.66
1.75
1.08
1.56
0.69
0.66
0.27
0.74
1.14
1.04
1.12
0.66
0.17
0.32
1.99
4.75
3.91
7.24
1.88
1.97
0.61
5.42
7.88
,12.16
.12.82
1.37
6.46
< 0.68
0.40
0.42
0.31
i 3.37
! 0.46
0.63
; Q.2.2
Smokies '
i
(9) !
0.12 ,
0.10
0.07
0.79
0.18
0.11
0.20
0.47
0.77
0.40
0.56
0.54
0.38
0.43
0.24
0.25
0.24
0.23
0.42
0.29
0.23
0.12
0.00
0.04
0.24
0.13
0.16
0.05
0.05
0.00
0.01
0.06
0.06
0.01
0.01
lit; umcui UA. me
'
i
1 !
" " 1 • i ' ' I !
en
•
10
ID
-------
Table ^^31 Phase II Transfer; Matrix of: (continued)
Annual ijfet Deposition of Sulfur (kg.ha~l.yrrl)
per uni£ emission!(Tg.S.yr~l)
6
Kent.
Term.
7
W.Virg.
to N.C.
8
Rest of
(USA) Fid
to Mo. to
Minn.
9
Ontario
10
Quebec
11
Atlantic
Provinces
MOE
AES
ASTRAP
ENAMAP
RCDM
MEP
MCARLO
MOE
AES
ASTRAP
ENAMAP
RCDM
MEP
MCARLO
MOE
AES
ASTRAP
ENAMAP
RCDM
. MEP
MCARLO
MOE
AES
ASTRAP
ENAMAP
RCDM
MEP
MCARLO
MOE
; AES
ASTRAP
ENAMAP
RCDM
MEP
MCARLO
MOE
AES
1 ASTRAP
ENAMAP
RCDM
MEP
MCARLO
1.202
1.418
1.473
1.473
1.473
1
i
1.703
1.223
1.610
1.610
1.610
1.196
3.743
4.012
4.012
4.012
0.906
0.985
0.949
0.949
0.949
i
,
q.595
P- 5,19
0.464
0.464
0.464
, ,
0.187
0.235
6.453
0.453
0.453
i i
i
i
0.03
0.00
0.03 i
0.00
0.14
0.01
0.00
0.03
0.00
0.00
0.00
0.06
0.01
0.05
0.09
0.24
0.24
0.12
0.37
0.23
0.06
0.08
0.10
0.04
0.02
0.17
0.07
0.20
0.06
0.00
O.OQ
O.OQ
P.03
0.03
0.01
i 0.01
0.00
0.00
0.00
0.00
0.00
0.00
.
0.10
0.14
0.22
0.00
0.18
0.05
0.04
0.08
0.00
0.05
0.00
0.15
0.02
0.01
0.38
0.61
0.38
0.15
0.25
0.34
0.11
0.62
1.83
5.43
1.45
1.30
2,. 17
0.47
! 0.20
0.19
0.19
0.00
0.12
0.34
0.09
! 0.03
0.00
i 0.00
0.00
O..Q;
0.01
0.00
!
0.14
0.71
0.40
0.03
0.28
0.09
0.10
0.16
0.33
0.25
0.00
0.51
0.16
0.09
0.33
0.27
0.37
0.02
0.18
0.12
0.09
1.63
3-3,5
6.89
1.41
1.91
2.8.1
0.61
0,.3|8
< 0..58
0.65
0.00
! 0.3,0
Q.49
0.28
0.06
0.00
O.OQ
0.00
0.04
0.06
6.01
( ,
0.09
0.07
0.14
0.05
0.16
0.03
0.11
0.13
0.33
0.37
0.38
0.30
0.09
0/14
0.15
0.05
0.12
0.08
0.12
0.02
0.05
1.00
1.73
.2.15
1.61
1.52
0.72
0.44
1.58
2.89
7.71
0.90
0.59
3.53
0.56
! 0.18
I 0.43
0.02
p. 07
Q..10
'0.30
0.05
0.13
0.07
0.04
0.00
0.07
0.01
0.01
0.27
0.25
0.26
0.00
0.18
0.05
0.02
0.15
0.03
0.03
0.00
0.05
0.01
0.01
0.55
0.61
0.16
0.00
0.56
0.14
0.08
0.71
0.96
0.25
\ O.OQ
2.33
0.57
0.21
0.75
2.55
' 0.87
: o.oo
; 0.93
! 1.42
0.17
0.13
0.21
0.52
0.12
0.11
0.04
0.07
0.22
0.90
0.84
0.83
0.37
0.22
0.15
0.20
0.08
0.15
0.12
0.07
0.03
0.05
1.04
1.62
1.18
1.20
0.64
0.89
0.3?
2.99
: 3.28
1.54
3.06
0.81
3.15
0.20
0.19
0.00
0.03
i 5.78
0.33
0.19
0.04
I
0.17
0.42
0.96
0.17
0.19
0.06
0.16
0.29
1.14
1.03
1.77
0.60
0.28
0.20
0.25
0.13
0.26
0.15
0.11
0.05
0.09
1.14
2.03
2.18
1.75
0.95
1.56
; 0.32
! 0.65
1.54
i. 2.11
1.35
0.53
1.87
0.17
Q.12
; Q.OO
0.00
5.39
0.12
0.10
0.01
0.45
1.48
1.30
1.16
0.61
0.18
0.26
0.91
3.52
5.98
7.73
2.79
1.25
0.42
0.39
0.53
0.32
0.19
0.25
0.05
0.08
0.54
1.22
0.25
0.53
0.39
0.99
0.17
Q.13
i 0.19
i 0.12
'- 0.03
0.13
0.16
0.10
0.05
j 0.00
0.00
0.35
0.02
0.07
0.00
1.64
3.10
8.17
3.91
1.29
2.01
0.75
0.18
0.49
0.13
2.73
0.48
0.75
0.17
0.99
2.46
2.74
3.05
0.81
0.29
0.20
0.05
0 00
0.02
0.25
0.06
0.05
0.09
0.03
0.00
0.00
0.03
0.03
0.00
0.01
0.02
0.00
0.00
0.09
0.01
0.00
0.00
•
Ui
•
1
o
-------
5.3-1
5.3 Intercomparison of Transfer Matrices
For the Phase I transfer matrix of annual wet sulfur
deposition, the models disagreed significantly in the impact
of the Ontario source region (9) on the Muskoka receptor area
(3). The values ranged from 1.60 to 12.86 kg.S.ha"1 yr"1 per
unit emission (1.60 to 5.07 kg.S.ha.-1 yr"1 per unit emission
if the 12.86, computed by ENAMAP which used an incorrect set
of coordinates to define the location of this receptor area
is deleted). The range of values was about the same in Phase
II [1.41 (ENAMAP) to 6.89 (ASTRAP)] for the same 5 Phase I
models. The MOE model computed the least impact in Phase I
while the ENAMAP model predicted the least impact in Phase
II. The RCDM model, which computed the greatest impact in
Phase-* I (5.07) computed an impact of 1.91 in Phase II. The
Phase I ASTRAP value of 4.71, increased to 6.89 in Phase II.
For Phase I transfer matrices for annual wet sulfur deposi-
tion, the models disagreed in the impact of the Pennsylvania
source region (4) on the Pennsylvania receptor area (8)
(4.24 to 10.61 kg.S.ha."1 yr.-1 per unit emission). For the
Phase II transfer matrix, the models disagreed even more
[1.37 (RCDM) to 12.84 (ENAMAP)]. The RCDM value decreased from
4.24 to 1.37 and the ASTRAP value increased significantly
from 4.61 to 12.16.
-------
5.3-2
The Phase I model results also varied significantly for
the impact of the Michigan source area (1) on the Algoma sen-
sitive area (2) [values ranged from 0.43 to 3.95]. For the
Phase II transfer matrix, the variation in values decreased
significantly [from 0.43 (MOE) to 2.36 (AES)]. The MOE model
yielded the lowest value in both Phases I and II. The RCDM
value of 3.95 in Phase I decreased to 0.94 in Phase II. The
ASTRAP Phase II value of 1.47 was considerably lower than its
Phase I value of 2.59, while on the other hand, the AES Phase
II value of 2.36 was slightly less than its Phase I value of
2.40.
The model calculation of the impact of the Ohio source
region (3) on the Pennyslvania receptor area (8). also varied
significantly in Phase I (1.01 to 4.70). The Phase II transfer
matrix shows an even greater range of values [1.88 (RCDM) to
7.24 (ENAMAP)]. In Phase I, the ENAMAP value was the lowest
(1.01); while in Phase II, its value was the highest (7.24).
The RCDM Phase II value was about half of its Phase I value
of 3.66, while the MOE value essentially did not change-
The ASTRAP Phase I value of 3.29 was slightly lower than its
Phase II value of 3.91.
The Phase II range in values [0.91 (MOE) to 7.73 ENAMAP]
for the impact of the Virginias and North Carolina source region
(7) on the Pennsylvania receptor area (8) also increased from
Phase I (0.85 to 4.99). In both phases, the MOE value was
-------
5.3-3
the lowest. The RCDM Phase II value of 2.79 was less than
its Phase I value of 4.99. On the other hand, the ASTRAP
Phase II value of 5.98 was greater than its Phase I value
of 4.04.
Finally, the Phase II range of values [1.00 (OME) to
2.15 (ASTRAP)] decreased from Phase I (0.59 to 4.10) for the
impact of the Ontario source region (9) on the Quebec receptor
area (4). The RCDM Phase I value of 4.10 decreased to 1.52
in Phase II. Likewise, the ASTRAP value decreased from 3.83
in Phase I to 2.15 in Phase II. The MOE values did not
change between Phases I and II.
One would think that the range of values would have
decreased in a set of transfer matrix elements since a stan-
dardized set of model input data was used in Phase II... Such
was not the case for those sets of matrix values having the
greatest range in Phase I. Uncertainties and variations in
the parameterization schemes used in the models undoubtedly
are factors in the wide range of values.
Based on the Phase I and Phase II transfer matrices,
one cannot justify labeling a given model as useless,
(i.e. one that consistently produces extremes values).
Indeed one cannot fully evaluate evaluate the model results
using the transfer matrices, since one cannot completely
assess the accuracy of the individual matrix element values
themselves. Measured annual wet sulfur deposition data
-------
5.3-4
for 1978 were available and are listed in Table 5-4 for each
of the receptor areas considered in the transfer matrix. This
tables shows the Phase I and II estimates by the OME-LRT and
AES-LRT models are the same while the estimates by the ASTRAP,
ENAMAP and RCDM models changed significantly due to use of
1978 meteorology and the Phase II S02 emissions inventory and
some changes to the input parameters. In general,. the Phase
II estimates by the OME-LRT, MEP-TRANS and MCARLO models are
within +50% of the observed values/ while the estimates for
the AES-LRT and RCDM models are within about +_75% of the
observed values. The ASTRAP and ENAMAP model estimates are
generally much higher than the observed values at all the
targeted sensitive areas. All the models show a general
tendency to over-predict the observed wet sulfur depositions
in the targeted sensitive areas except for the MCARLO model.
These preliminary evaluation results will be used by the
modelers to refine their input parameters and check their
model results before starting the second round of model
evaluation (see Section 6).
-------
Table 5-4: Preliminary Model Estimates and Observations of Annual Wet Sulfur Deposition
(kg.S.ha.~Jyr~l) at the Nine Targeted Sensitive Areas
Phase I Phase II
Sensitive Obs.*1'
Areas Values
1 B. Waters 3
2
3
4
5
6
7
8
9
Algoma
Muskoka
Quebec
S.N. Scotia
Vt., N.H.
Adirondacks
Pennsylvania
Smokies
3
6
5
3
7
7
12
7
' Canadian
OWE*
3
5
7
6
7
8
8
17
7
AES
2
10
18
9
6
13
16
34
17
United States
RCDM
16
20
23
17
10
15
19
27
18
ASTRAP
7
16
21
17
12
15
19
25
17
ENAMAP
10
6
19
1
11
4
3
21
8
Canadian
OWE*
3
5
7
6
7
8
8
17
7
AES
2
10
18
9
6
13
16
34
17
MEP
1
6
10
6
3
8
9
16
7
United
States
ASTRAP ENAMAP
2 0.7
17
25
24
5
.21
31
52
36
5
7
13
0
19
27
71
35
RCDM MCARLO
4 0.8
8
15
10
7
9
13
21
12
3
5
5
1
5
6
7
6
tn
•
u>
01
*Background of 2 Kg.S.ha.~-'-yr.~1 added £o MOE values
(1) Source: Interpolated from a map prepared by the National Atmospheric Deposition
Program (1981) based on data for March 1979 to March 1980.
-------
5.4-1
5.4 Unification of Transfer Matrices
In the previous subsection, the difference in transfer
matrices generated from five regional models were highlighted.
These differences are expected since the five models differ
in their treatment of input data; the parameterizations of
diffusion, dry and wet deposition, transformation of SC>2 to
304, and the distribution of source emissions. The differences
in transfer matrices really reflect the uncertainties we have
in how best to parameterize all the physical processes and the
result of taking different approaches by independent modelers.
Although the practicality of a single, unified transfer
matrix is recognized, the Modeling Subgroup had strong reser-
vations about the generation and application of a unified
transfer matrix at this time. Because no matter how it is
generated, a unified transfer matrix could be-very misleading.-
As an alternative, the Subgroup suggested all seven Phase-II
transfer matrices be used in assessment iterations. After
the model evaluation work has been completed in Phase III,
the Subgroup may be able to recommend to Work Group 2 the
use of one or more model transfer matrices. The application
of all seven transfer matrices to a given emission scenario
would provide for a measure of the variation in results that
one would not get by just applying a single or a unified
transfer matrix.
-------
6-1
6. Conclusions and Future Plans
While there is still no general agreement within the
modeling community as to (1) the proper method and (2) the
statistics to be used for intercomparison and evaluation of
models/ the Modeling Subgroup has selected a common basis
for performing these tasks for the eight participating models.
It is generally accepted that one should expect model
predictions to deviate from measurements because a practical
model cannot incorporate even our current understanding of
the relevant physical processes and our available monitoring
data bases are insufficient to estimate the ensemble average
which the model is designed to predict. However, the uncer-
tainties in model predictions can be quantified from the
differences between model predictions and observations (the
residuals).
While the application of regional models is constrained
by the uncertainties inherent in them, such constraints can
be alleviated to a significant degree by requiring the modelers
to quantify these uncertainties, and taking these into account
in any application. When transfer matrices are used for
analyses, some of the uncertainties in the transfer matrix
elements can be assessed by using the transfer matrix from
more than one model and by using probabilistic techniques of
analysis which will be developed during Phase III. Other
uncertainties should be quantifiable after further model
evaluation efforts are completed.
-------
6-2
In Phase II, a complete set of evaluation statistics was
completed by only one model, while the monthly and annual
residuals were computed at 9 to 20 sites by three of the
eight models. The other four models are expected to complete
this preliminary evaluation by September. So far no single
model has emerged as clearly superior or inferior to the
others from this first of three rounds of model evaluation.
The evaluation has primarily served to reveal (1) the
deficiencies in the monitoring data bases/ (2) the need for
some changes in input parameters for some of the models, and
(3) the need to use at least one more year of independent data
for model evaluation.
In addition, most of the participating, modelers completed
detailed sensitivity analyses by varying each input parameter
separately within the limits normally used for long-range
transport modeling with either (1) actual meteorology and
emissions or (2) a hypothetical source-receptor situation and
simulated meteorology. These sensitivity analyses, which are
documented in the individual Model Profiles, provide a more
complete understanding of the workings of each model and will
be useful for incorporating uncertainty into any decision
making process.
The annual transfer matrices for Phases I and II were
intercompared and, interestingly, the use of standardized
inputs did not reduce the range of variation among models
-------
6-3
for some of the transfer matrix elements expressed in 2 of
the 3 standards forms, namely absolute values of concentration
or deposition and values normalized by unit emissions of
sulfur. However, the transfer matrix elements expressed as a
percentage contribution from a source region to a receptor
area were generally in much better agreement among the models.
However, as additional refinements will be made to most of the
models and a new set of source-receptor regions will be used
during Phase III, it is premature to draw any general conclu-
sions at this time. These variations in transfer matrix
coefficients reflect the current uncertainties in how best to
parameterize all the physical processes and are the result of
different approaches by independent modelers. Although the
desirability of a single, unified transfer matrix was recog-
nized, the Modeling Subgroup has reservations about the
generation and application of a unified matrix at this time
because, no matter how it is generated, its interpretation
is open to some question.
During Phase III, the Modeling Subgroup plans to do the
following:
(1) continue its evaluation and application of long-term
regional models and consolidate the results;
(2) enlarge the modeling domain to include the entire
continental U.S. and western Canadian provinces;
-------
6-4
(3) run the models using the unified SC>2 emissions inven-
tory on a state (multi-state)/ province (sub-province)
basis and unify, if possible, the transfer matrices;
(4) run the models on additional periods of meteorological
logical data to assess the natural variability of the
transfer matrix coefficients insofar as is possible;
and
(5) address the issues raised by the peer review and
analyses processes.
In addition, the Modeling Subgroup has outlined the steps
for three complete rounds of model evaluation (see Table 6-1)
and is urging the participating modelers to complete at least
the first eight steps. The purpose of the first two rounds
of model evaluations is to determine the ability of the
participating models to simulate current conditions. The
purpose of the third round of model evaluation is to investi-
gate the predictive ability of the participating models on a
significantly different SO2 emissions field.
-------
6-5
Table 6-1. Steps in the Model Evaluation Process
1. Develop terms of reference for model evaluation on eastern
North America.
2. Run participating models using the agreed-upon data bases
for the year 1978.
3. Evaluate the models against the 1978 monitoring data using
the agreed-upon statistics (first round).
4. Analyze and intercompare the 1978 model evaluation statis-
tics and transfer matrices.
5. Refine and improve the models based on the first round of
model evaluation.
6. Review and possibly revise the terms of reference for the
second round of model evaluation.
7. Evaluate the models against the 1979 monitoring data using
the final parameterizations and other specifications and
using the agreed-upon statistics (second round).
8. Analyze and intercompare the 1979 model evaluation statis-
tics and transfer matrices.
*9. Develop terms of reference for a model evaluation on
Western Europe.
*10. Run the participating models using the agreed upon data
bases for Western Europe.
*11. Evaluate the models against the Western European monitoring
data using the agreed-upon statistics (third round).
*12. Analyze and intercompare the models based on the third
round of model evaluation.
13. Prepare a statement on the state-of-the-art of LRT models
based on the three rounds of model evaluation for inclusion
in the Phase III final report to the Coordinating Committee,
* Optional
-------
R-l
REFERENCES
Anlauf, K. G., et al., 1980: Atmospheric Transport of Particulate
Sulphate and Ozone into the Toronto Region and Its Correlation
with Visibility,- Atmospheric Pollution 1980, Proceedings of
the 14th International Colloquim, Paris, France, May.
Anthes, R. A., 1978: Boundary Layers in Numerical Weather
Prediction, Proceedings of Workshop on the Planetary Boundary
Layer, Boulder, Colorado, August. .
Barrie, L. A., 1981: The Prediction of Rain Acidity and SC>2
Scavenging in Eastern North America, A.tmo.s,.. Ejiy.irjon.. , ,15, 31.
Benkeley, C. W. and Mills, M. T. 1980: Development and
Validation of a Simple Regional Climatological Dispersion
Model for Nitrogen Oxides, Report Prepared for Argonne National
Laboratories by Teknekron Research, Inc., November.
Benkowitz, C., 1979: Compiling a Multistate Emissions Inventory,
propkhayen, National. Lab.or.a.tory/MA.P3S. Report, J^^26843_,^Upton, .
New York.
Bhumralkar, C. M., et al., 1980: ENAMAP-1 Long-Term Air
Pollution Model: Adaption and Application to Eastern North
America. U. S. Environmental Protection Agency, EPA-600/4-80-
039, July.
Bolin, B. and Persson, C., 1975: Regional Dispersion and
Deposition of Atmospheric Pollutants with Particular Application
to Sulfur Pollution over Western Europe, TeJ..lus, ,2,7, 281-310.
CAPITA, 1981: Progress Report on Sulfur and Nitrogen
over the Eastern North American Airshed: Sources, Concentration,
Depositions and Budgets,, submitted to U. S. EPA Office of Research
and Development by the Center for Air Pollution Impact and
Trend Analysis, St. Louis, MO., January.
Choquette, P. and Vena, F., 1980: Canadian S02 Emissions
Information Package, Report Prepared by the Air Pollution Control
Directorate, Environment Canada, Ottawa, Canada, August.
Chung, Y. S., 1977: Sources and Sinks of Photochemical Ozone
(03) in the Boundary Layer, Proceedings of the Fourth International
Clean Air Congrees, Tokoyo, 138.
Clark, T. L. 1980: Annual Anthropogenic Pollutant Emissions in
the United States and Southern Canada East of the Rocky Mountains,
Atmos. Environ., 14., .9.61-970.
-------
R-2
Csanady, G. T., 1969: Diffusion in An Ekman Layer, A^mos. gci.
26.,_ 414-426. ''
Dana, M. T., et al., 1975: Rain Scavenging of S02 and Sulfate
from Power Plant Plumes, 3. Geophys^JRes. , 80, 4119-4129.
Dingle, A. N. and Lee Y., 1973: An Analysis of In-Cloud
Scavenging, .J... Appl,. Me.teor* , 12, 1295-1302.
Eliassen, A., 1978: The OECD Study of Long-Range Transport
_gf Air Pollutants: Long-range Transport Modeling, A.tmos.
.E'nyirpn. , 9., 425-429.
Eliassen, A., and Saltbones, J. 1975: Decay and Transformation
Rates for SC>2, As Estimated from Emissions Data, Trajectories
and Measured Air Concentrations, Atmps... Environ.., .9, 425-4.29.
Englemann, R. J., 1970: Scavenging Prediction Using Ratios
of Concentrations in Air and Precipitation, AEC Symp. Ser.
Pr e c,i p.i t,a.t.i.on .S.c,ay e ng.i.ng / 475-484. ___ _
Fay, J. A. and Rosenzweig, J. J. , 1980: An Analytical
Diffusion Model for Long Distance Transport of Air Pollutants,
Atmos.. Environ . , 1,4 , 355-365. • ; _____ ._ ___
Fisher, B. E. A., 1978: The Calculation of Long-Term Sulfur
Deposition in Europe, Atpipjs^. JEny.iron. , .1.2, 489-501.
Garland, J. A., 1978: Dry and Wet Removal of. Sulfur from the
Atmosphere, Atmos ^. Ejnv,iron • t X2, 349-362.
Gillani, N. V., et al. 1978: Project MISTT: Kinetics of
Particulate Sulfur Formation in a Power Plant Plume Out to
300 km., Atmos... En.y4.rpn. , ,1.2, 589-598. __
Heffter, J. L. , 1980: The ARL Atmospheric Transport and
Diffusion Model, NOAA Tech. Memo. ERL ARL-81, Silver Springs,
MD.
Heffter, J. L. and Ferber G. J. , 1977: Development and
Verification of the ARL Regional-Continental Transport and
Dispersion Model, Proc. Joint Conf. on Appl. of Air Poll.
Meteor., Salt Lake City, UT, American Meteorological Society,
Boston, MA.
Hicks, B. B. and Shannon, J. D. , 1979: A Method for Modeling
the Deposition of Sulfur By Precipitation On a Regional Scale,
J... Appl... Meteor* , 1£, 1415-1420.
Hoecker, W. M., 1977: Accuracy of Various Techniques for
Estimating Boundary-Layer Trajectories, J., Appl... Me.te.or. ,
1.6, 374-383.
-------
R-3
Hoecker, W. H. , 1979: Accuracy of Various Techniques for Estimating
Boundary-Layer Trajectores, J. Appl. Meteor., 16, 374.
Johnson, W. B., et al., 1978: Long-Term Regional Patterns and
Transfrentier Exchanges of Airborne Sulfur Pollution in Europe,
Atmos. Environ., 12, 511-527.
Judging Air Quality Model Performance, A Summary of the
Workshop on Dispersion Model Performance, Woods Hole, MA,
September 8-11, 1980, American Meteorological Society,
Boston, MA, 40 pp.
Klemm, H. A. and Brennan, R. J., 1981: Emissions Inventory
for the SURE Region, Final Report to the Electric Power
Research Institute from the GCA Corporation, Bedford, MA,
April.
La Fleur, R. J., 1981: Letter on Sulfate Data for 1978 and
1979 from Eastern Canada, dated January 26.
Lamb, R. G., 1980: Mathmetical Principles of Turbulent Diffusion
Modeling, in Atmospheric Planetary Boundary Layer Physics,
Elsevier Publishing, Amsterdam.
Lyons, W. A., 1980: Evidence of Transport of Hazy Air Masses
from Satellite Imagery, Annal. N. Y. Acad. of Sci., 338,
418-433.
Mayerhofer, P., 1980: A Precipitation Data Gridding Program
for Regional Air Quality Simulation Models: Program Description .
and Users Guide, Report Prepared for the Acid Rain Assessment
Team, Office of Research and Development, U. S. EPA, Washington,
D. C., December 1980.
Maul, P. R., 1978: Preliminary Estimates of the Washout
Coefficient for Sulfur Dioxide Using Data from an East Midlands
Ground Level Monitoring Network, Atmos. Environ., 12, 2515-2517.
McNaughton, D. J. and Scott, B. C., 1980: Modeling Evidence
of Incloud Transformation of Sulfur Dioxide to Sulfate, J.
Air Poll. Cont. Assoc., 30, 272-273.
Mueller, P. K. , 1981: Letter on SURE Phase II SC>2 Data, dated
March 16 and follow-up conversation.
Niemann, B. L., et al, 1979: Application of a Regional Transport
Model to the Simulation of Multi-Scale Sulfate Episodes Over
the Eastern United States and Canada, in Proceedings of the
WMO Symposium on the Long-Range Transport of Pollutants and
Its Relation to General Circulation Including Stratospheric/
Tropospheric Exchange Processes, October 1-5, Sofia, Bulgaria.
-------
R-4
Niemann, B. L., et al, 1980: Initial Evaluation of Regional
Transport and Subregional Dispersion Models for Sulfur Dioxide
and Fine Particulates, Proceedings of the Second Joint AMS/APCA
Conference on Applications of Air Pollution Meteorology,
March 24-27, New Orleans, LA.
Niemann, B. L. and Summers, P. W., 1981: Variability of
Meteorological Periods Used in Regional Air Quality Simulation
Models, Memorandum Prepared for the Modeling Subgroup of Work
Group 2, May.
Olson, M. P., et al., 1978: A Trajectory Model Applied to
the Long-Range Transport of Air Pollutants, LRTAP 78-4,
Atmospheric Environment Service, Downsview, Ontario.
Olson, M. P., et al., 1979: A Concentration/Deposition Model
Applied to the Canadian Long-Range Transport of Air Pollutants
Project, LRTAP 79-5, Atmospheric Environment Service, Downsview,
Ontario.
Patterson, D. E., et al, (1981) Monte Carlo Simulation of
Daily Regional Sulfur Distribution: Comparison with SURE
Sulfate Data and Visual range Observations During August
1977, J. Appl. Meteor., 2£, 70-86.
Peterssen, S., 1956: Weather Analysis and Forecasting,
McGraw-Hill, New York.
Research Guidelines for Regional Modeling of Fine Particulates,
Acid Deposition and Visibility, Report of a Workshop Held at
Port Deposit, Maryland, U. S. EPA, Office of Research and
Development, June 1980, 422p.
Rodhe, H. and Grandell, J., 1972: On the Removal Time of
Aerosol Particles from the Atmosphere by Precipitation
Scavenging, Tellus, 24, 442-454.
Rutherford, I.D., 1977: An Operational Three Dimensional
Multivariate Statistical Objective Analysis Scheme, Issue
#1, Notes Scientifiques et Techniques, RPN, Atmospheric
Environment Service, Dorval, PQ.
Samson, P. J., 1980: Trajectory Analysis of Summertime
Sulfate Concentrations in the Northeastern United States,
J. Appl. Meteor., 19, 1382-1394.
Scott, B. C., 1978: Parameterization of Sulfate Removal by
Precipitation, J. Appl. Meteor., 17, 1375-1389.
-------
R-5
Scott, B. C., 1980: Predictions of in-Cloud Conversion Rates
of S02 to 804 Based Upon a Simple Chemical and Dynamical
Model, in Proceedings of the Second Joint AMS/APCA Conference
on Applications of Air Pollution Meteorology, March 28, 1980,
New Orleans, LA, 389-396.
Second Report of the United States - Canada Research
Consultation Group on the Long-Range Transport of Air Pollutants,
A. P. Altshuller and G. A. McBean, Co-Chairman, November
1980, 40pp.
Shannon, J. D., 1979: The Advanced Statistical Trajectory
Regional Air Pollution Model, in Proceedings of the Fourth
Symposium on Turbulence, Diffusion, and Air Pollution, January
15-18, Reno, Nevada, American Meteorological Society, Boston,
MA.
Shannon, J. D., 1979: A Model of Regional Long-Term Average
Sulfur Atmospheric Pollution, Surface Removal, and Net
Horizontal Flux, Atmos. Environ. 15, 689-701.
Shannon, J. D., 1981: Examination of the Relative Importance
of Primary Emission Versus Secondary Production of Atmospheric
Sulfate, Paper submitted to U. S. EPA Environmental Sciences
Research Laboratory, 26 pp.
Shiehr C. M., et al., 1979: Estimated Dry Deposition Velo-
cities of Sulfur Over the Eastern United States and Surrounding
Regions, Atmos. Environ., 13, 1361-1368.
Slinn, W. G. N., et al., 1979: Wet and Dry and Resuspension
of AFCT/TFCT Fuel Processing Radionuclides. U. S. Department
of "Energy Final Report SR-0980-10, by the Air__RejsjDurc.es
Center, Oregon State University, Corvallis, Oregon.
Smith, F. B. and Hunt, R. D., 1979: The Dispersion of Sulfur
Pollutants Over Western Europe, Phil. Trans. R._ Soc. Lond.,
A.290, 523-542. ~T
Smith, F. B., 1980: The significance of Wet and Dry Synoptic
Regions on Long-Range Transport of Pollution and Its Deposition,
Atmos. Environ., 15, 863-873. _ .__.___..
Sykes, R. I. and Hatton L., 1976: Computation of Horizontal
Trajectories Based on the Surface Geostrophic Wind, Atmos.
'Environ. , 10, 925.
Tennekes, H., 1977: The General Circulation of Two-Dimensional
Turbulent Flow on a Beta plane, J. Atmos. Sci. , 34, 702-712.
-------
R-6
Voldner, E. C., et al., 1980: Comparison Between Measured
and Computed Concentrations of Sulphur Compounds in Eastern
North America. AQRB-80-0003T (LRTAP-02), Atmospheric Envi-
ronment Service, Downsview, Ontario (To be published in
Journal of Geophysical Research, 1981).
Voldner, E. C., et al., 1980: A Preliminary Canadian Emissions
Inventory for Sulphur and Nitrogen Oxides, Atmos. Environ., 14,
419-428T •
Walmsley, J. L., et al., 1981: Sensitivity Tests with a
Trajectory Model, to be published in the Air Quality Research
Branch Report Series, Atmospheric Environment Service, Downsview,
Weisman, B., 1980: Long Range Transport Model for Sulphur,
73rd Annual Meeting of the Air Pollution Control Association,
Montreal.
Wilson, W. E. and Gillani, N. V., 1979: Transformation
During Transport: A State-of-the-Art Survey of the Conversion
of S02 to Sulfate, in WMO Symposium on the Long-Range Transport
of Pollutants and Its Relation to General Circulation Including
Stratospheric/Tropospheric Exchange Processes, 1-5 October,
Sofia, Bulgaria,
-------
APPENDIX A
List of Modeling Subgroup Reports and Other Documents
-------
A-l
List of Modeling Subgroup Reports and Other Documents
July 10, 1981
.S.ubgrjo.up Rep.or.t3
1. AES-LRT Model Profile
2. ASTRAP Model Profile
3. ENAMAP Model Profile
4. OME-LRT Model Profile
5. RCDM-2 Model Profile
6. UMACID Model Profile
7. MEP-TRANS Model Profile
8. CAPITA-Monte Carlo Model Profile
.other. Po.cuments
5/15/81 2-5
5/12/81 2-6
6/30/81 2-7
3/31/81 2-8
7/10/81 - 2-9
6/24/81 (Interim) 2-10
6/30/81 (Interim) 2-11
6/30/81 (Interim-) 2-12
Proposed Plan for the Intercomparison and Evaluation of
Regional Air Quality Simulation Models in Support of Work
Group 2 in Phase II (Smith and Whelpdale) December 15, 1980
(Revised January 14, 1981)
Status Report on LRTAP Modeling Activity by the Atmospheric
Sciences and Analysis Work Group #2 Prepared for the EMEP
(Coorperative Programs for the Monitoring and Evaluation
of Long Range Transmission of Air Pollutants in Europe-ECE
Meeting), 30 March - 1 April, 1981, Reading, UK (Young and
Niemann) March 20, 1981
Processing U.S. and Canadian Hourly Precipitation Data for
Use in Model Intercomparison (Mayerhofer) April 14, 1981
Variability of Meteorological Periods Used in.Regional Air
Quality Simulation Models (Niemann and Summers) May 1981
Limitations To The Use of Long Range Transport Models in the
Western U.S. (Kleinman) February 5, 1981
-------
APPENDIX B
Transfer Matrices for the Phase II Data Bases
-------
B-l
TABLE OF CONTENTS
Map of Eastern North America Showing the 11 Major Source
Regions and 9 Sensitive Areas Used in the Phase II Transfer
Matrices
Key to the 11 Source Regions and 9 Sensitive Areas
FIRST AGREED UPON FORMAT
Comparison of Transfer Matrix Absolute Values by Model for 11
Source Regions and 9 Receptor Areas
SO2 Concentrations (ug/nr)
SO* Concentrations (ug/nr)
Dry Sulfur Deposition (kgS/ha/yr)
Wet Sulfur Deposition (kgS/ha/yr)
Total Sulfur Deposition (kgS/ha/yr)
Means and Standard Deviations of Absolute Values Over all
Models for 11 Source Regions and 9 Receptor Areas (same para-
meters and units as above)
Comparison of Transfer Matrix Percentage Contribution Values
by Model for 11 Source Regions and 9 Receptor Areas (same
parameters as above, but units are all %)
Means and Standard Deviations of Percentage Contributions
Over All Models for 11 Source Regions and 9 Receptor Areas
(same parameters as above, but units are all %)
SECOND AGREED UPON FORMAT
Comparison of Transfer Matrix Values by Model in Absolute,
Percentage, and Unit Form for All 9 Receptor Areas in Each
of 11 Source Regions
NOTE: The annual matrix elements for the ASTRAP, ENAMAP and
MCARLO models are based on the mean of the equivalent
January and July 1978 elements.
-------
B-2
Map of East-
ern North America Showing
the 11 Major Source Regions
(JLQ- shaded and the rest
east of the 'Mississippi
River) and 9 Sensitive
Areas Used in_the Phase II
Transfer Matrices
-------
B-3
Table B-l. Key to the 11 Source Regions and 9 Sensitive Areas
Source Regions
1 Michigan 1
2 Illinois-Indiana 2
3 Ohio 3
4 Pennsylvania 4
5 New York to Maine 5
6 Kentucky-Tennessee 6
7 West Virginia to North Carolina 7
8 Rest of Eastern U.S. (Florida 8
to Missouri to Minnesota)
9
9 Ontario
10 Quebec
11 Atlantic Provinces
Sensitive Areas
Boundary Waters
Algoma.
Muskoka
Quebec
Southern Nova Scotia
Vermont-New Hampshire
Adirondacks
Western Pennsylvania
Smokies
-------
B-4
Comparison of Transfer Matrix Absolute Values by Model
for 11 Source Regions and 9 Receptor Areas
-------
COMPARISON OF TRANSFER MATRIX VALUES BY MODEL
AMB S02
2
I
2
2
2
2
2
a
a
a
5
5
5
5
5
S
5
7
7
7
7
7
7
7
8
0
8
8
8
8
8
9
9
9
9
9
9
9
to
to
10
10
10
to
10
11
11
11
11
11
11
11
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
£NA*AP
RCDM
MOE
AfcS
HEP
MCARL
ASTRAP
ENAMAP
HCOM
MOE
AES
M£P
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCAHL
ASTRAP
ENAMAP
RCDH
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDH
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
HEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
KCARL
ASTRAP
ENAMAP
NCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
HtP
MCARL
o.ot
0.61
0,52
0.08
0.16
0.09
0.09
0.01
0.0
o.ao
0,07
0.07
0.02
0.01
0,00
0,0
0,16
0,04
0.0
0.01
0.0
0.0
0,0
0,05
0.03
0.0
0.0
0.0
0,00
0,0
0,03
0.02
0,01
0,0
0,0
0.00
0.0
0.18
0.03
0.0
0.01
0.0
. 0.00
0.0
0.07
0.02
0.0
0.0
0.0
0.10
1.01
0.71
0.12
0.53
0.30
0,11
0.01
0,09
0.30
0,10
0.11
0.04
1,51
0.00
0.0
0.04
0.06
0.08
0.01
0,04
0.0
0.0
0.00
0.01
0.0
0,0
0.0
0,64
4,45
1,87
0.73
2.87
1.18
t.71
0.13
0.75-
0,61
0.33
0,71
0,19
0.36
0,05
0,19
0,51
0.22
0.14
0.07
0.12
0,01
0,04
0.26
0.17
0,06
0.04
0,04
0.00
O.OS
0.15
0.10
0.12
0,03
0.03
0.02
0,13
0.25
0,11
0.07
0.02
0.04
0,00
0.06
0.22
0.10
0,02
0.01
0.02
0.12
1.19
0.42
0.65
0.61
0.33
0.20
13.78
24,18
2.86
1.0
2.54
3.81
3.62
0.06
0,07
0.19
0.32
0.91
0,31
0.26
0.0
0.0
0.02
0.03
0.0
0.0
0.0
1.11
12.28
2.80
1.66
4.47
1.53
1.49
0.23
2.31
0.85
0.47
0.76
0.29
0.43
0.19
2.50
1,78
0.50
1.17
0,97
0.73
0.08
0.78
1.69
0.45
0.71
0.48
0.50
0.02
0.3S
1.06
0.34
0.56
0.40
0.61
0.05
1.07
0.42
0.18
0.27
0.07
0.09
0.02
0.46
0.93
0.22
0.16
0.11
0.10
0,11
0.96
0,26
0.53
0.26
0.13
0.14
10.53
26.62
4.24
3.14
12.36
7.51
1.66
0.30
1.24
0.51
0.64
2.02
0,94
0.66
0.0
0.0
0.06
0.07
0.00
0.02
0.03
0.14
3.88
1.33
0.48
0.80
0.27
0.58
0.06
1.92
0.42
0.18
0.15
0.07
0.24
0,07
2.20
0.80
0.24
0.37
0,18
0,48
0.11
1.95
1.00
0,28
0.47
0.28
0.50
0.15
1.94
0.69
0.39
0.95
0.77
0.84
0.02
0.18
0.20
0.10
0.04
0.02
0.09
0.02
0.53
0.48
0.16
0.16
0.05
0.13
0.03
0.32
0.15
0,19
0.05
0.03
0.06
0.61
8.78
3.21
1.78
1.69
0.75
0.99
10.46
13.80
1.16
3.00
6.67
6.47
3.79
0.00
1.42
0,18
0.2B
0.26
0.18
0.14
0.12
0.0
0.40
0.54
0.38
0,08
0.10
0,05
0.0
0,14
0.21
O.li
0.02
0.05
0.07
0.0
0.32
0.38
0.32
0,09
0.08
0.22
0,0
0.61
0.58
0,40
0.25
0.06
0.76
0.0
0,97
t.77
4.20
1.89
0,18
0,02
0.0
0.07
0.14
0.04
0.02
0.01
0.08
0.0
0.25
0.38
0.18
0.07
0,02
0.02
0.0
O.OS
0.17
0,03
0,02
0.01
0.20
0.0
0,97
0,86
0.78
0,27
0,13
0,66
0.0
5.33
1.21
2.35
1.12
0,50
2.24
0.0
2.03
1.38
13.66
8.20
2.91
0.36
2.43
0,54
0.86
1.05
0.32
0.72
0.13
0.66
0.22
0.29
0.26
o.oe
0.29
0.19
1.62
0.59
0,46
0,73
0.27
0,64
0,60
3.44
1.49
0,60
1.25
0.59
0.81
2.39
9.36
2.71
1.03
2.01
1.99
8.22
0.05
0,05
0.13
0,16
0.12
O.OS
0.05
0.13
1.16
0,59
0.32
0.38
0.11
0.17
0.04
0,19
0.07
0,26
0.07
0.03
0,08
0.91
6.38
1.14
1.85
2.65
0.85
0.91
5.29
11.09
1.62
6.02
13.08
10.60
0.51
0.01
31.90
0.63
0.29
0.13
0.09
0.10
0,64
5.39
0.99
1.42
1.40
0.42
t.oe
0.19
1.11
0,41
0,43
0.42
0.13
0.58
0.31
2.74
1.15
0.74
1,35
0.50
1.52
0.78
6.56
2.85
0.96
2.25
1.11
2.12
1.83
10.61
3.77
1.53
3.29
2.10
5.63
0,07
0.08
0.25
0.22
0.22
0.07
0.15
0.13
2.17
1,08
0.45
0.64
0.18
0.28
0.06
0.21
0.13
0.36
0.13
0.04
0.14
1.81
10.03
1.88
2.06
4.11
1.64
0.96
1.42
4.05
0.99
1.15
3.87
4,03
0.14
0.00
5.90
0.22
0,16
0.09
O.OS
0.03
1.11
6.60
1.29
3.15
3.75
1.13
0.64
0.68
2.99
1.16
1.25
1.21
0.31
0.77
3.16
15.85
4,04
3.87
9.05
3.59
2.20
13.91
31.49
2.96
11.06
21.73
16.84
16.16
0.08
5.06
0.89
0.69
0.56
0.83
0.87
0.46
2.80
1.10
0.71
1.27
0.25
0.39
3.88
30.76
6.37
1.69
3.03
1.33
1.15
0.15
0.36
0.38
0.59
0.44
0.11
0.13
0.23
3.34
0.71
0.94
2.39
1.45
0.43
0.03
0.12.
0.16
0.18
0.29
0.19
0.24
0,0
0,74
0.02
0,05
0.0
O.OS
0.01
0,10
1,03
0.29
0,15
0.16
0.16
0.43
0.58
7.50
0.99
0.78
1.66
1.56
1.10
0.22
3.64
0.77
0.37
0,78
0.72
0.49
0.02
1.39
0.22
0.16
0.12
0.16
0.06
0.00
0.52
0.09
0,06
0,04
0,02
0.01
13.90
22.52
2.65
3.17
9.30
e.2£
9.27
0,06
10,16
0,91
0.27
0.88
3.09
0.44
0.92
4.66
1.64
1.87
3.06
0.46
0.45
0,02
1.33
0.06
0.06
0.08
0.07
0,16
0.00
o.to
0.03
0.03
0.02
0.03
0.02
0.0
0,39
0.00
0.01
0.0
0,0
0.0
-------
COMPARISON OF TRANSFER MATRIX VALUES BY HQOEL
AMB S0«
1
1
2
2
2
2
2
2
2
J
3
3
3
3
3
3
a
a
a
o
a
a
a
5
5
5
5
5
S
5
6
6
7
T
7
7
7
7
7
S
a
a
a
a
a
a
9
to
10
10
to
10
10
10
11
11
11
11
11
11
11
ASTRAP
ENAHAP
ROOM
HOE
AES
HEP
HCARL
ASTRAP
ENAHAP
RCDH
HOE
AES
MEP
MCARL
ASTRAP
ENAHAP
RCDH
HOE
AES
HEP
HCAHL
ASTRAP
ENAHAP
RCDM
HOE
AES
HEP
HCARL
ASTRAP
ENAHAP
RCDH
HOE
AES
HEP
HCARL
ASTRAP
ENAHAP
RCDH
HOE
AES
HEP
HCAHL
ASTRAP
ENAHAP
RCDH
HOE
AES
HEP
HCARL
ASTRAP
ENAHAP
HCD*
HOE
AES
HEP
HCARL
ASTHAP
ENAMAP
RCDH
MOE
AES
HEP
HCARL
ASTRAP
ENAHAP
RCDH
HOE
AES
HEP
HCARL
ASTRAP
ENAHAP
RCDN
HOE
AES
MEP
MCAHL
0.01
0.78
0.07
0,08
0,10 .
0.16
0,06
0,01
0,0
0,46
0,08
0.02
0,06
0,01
0,00
0,0
0.25
0,06
0.0
0.01
0.0
0.0
0.0
0.10
0.05
0.0
0.01
0.0
0.00
0.0
0.06
0.03
0.01
0.0
0.0
0,00
0.0
0.33
0.05
0.0
0.01
0.0
0.00
0.0
0.15
0.00
0.0
0.0
0.0
0,04
1.05
O.U6
0.09
0.11
0.29
0.06
0.01
0.34
0.27
0,09
P. OS
0.14
0.21
0.00
0.0
0,09
0.07
0.13
0.01
0.01
0.0
0,0
0.01
0.02
0.0
0.0
0,0
0.31
3.07
1.00
0.30
0,45
1.28
0.51
0.15
1.16
0.65
0.21
0.37
0.35
0.22
0.06
0,17
0,54
0.15
0,00
0.13
0,08
0.01
O.Ob
0,29
0,13
0,03
0.00
0.03
0.00
0,07
0,19
0,09
0.07
0.03
0.01
0,03
0,2ft
O.tt2
0.11
0,04
0,03
0,04
0,01
0,06
0,33
0,09
0,0
0,01
0,01
0,11
1.67
0,43
0,26
0,27
0.50
0,11
2.01
8.68
0.86
0.35
0.67
1.42
0.50
0.02
0.05
0.25
0.17
0.42
0,51
0,10
0,0
0.0
0.03
0.04
0.0
0.03
0.0
0.76
9.27
1.36
0.54
1.80
1.91
0.61
0.20
0.03
0.84
0,28
0,01
0.4B
0.2B
0.20
2.13
1.09
0.26
0,59
1.22
0.33
o.oa
0.77
0.97
0.20
0.29
0,53
0.21
0.01
0.47
0.58
0.18
0.22
0.20
0.18
0.06
2.60
0.58
0.16
0.12
0.12
0.10
0.03
0.51
0.76
0.16
0.07
0.15
0.09
0.11
2.05
0.40
0.27
0.20
0.26
0.09
2.41
10.86
1.23
0.70
2.36
0,36
0.67
0,09
1.31
0,49
0.27
0,85
1.15
0.28
0,0
0,0
0,07
0,07
0,0
0,06
0,01
0.18
6.5b
1.05
0.30
0.55
0.66
0.32
O.OB
5.00
0.59
0.17
0.12
0.13
0.20
0.11
5.13
0,79
0,19
0.16
0.2B
0,33
o.ia
2.51
0.70
0,21
0.19
0.09
0.34
0.16
2.23
0.60
0,22
0.31
0.73
0.35
0.02
1.00
0.39
0.11
. 0.01
0.03
0.11
O.OS
1.58
0.57
0.15
0,05
0,08
0.14
0.04
0.96
0.29
0.16
0.05
0.07
0,05
0.62
9.34
1.30
0.61
0,99
1.25
0.40
3.15
5,35
0,70
0.73
1.27
2.75
0.61
0.00
1.18
0.15
0.15
0.13
0.12
0.06
O.OB
0.0
0.61
0.35
0.06
0.25
0.06
O.OS
0.0
0.30
0.20
0.11
0,00
0.04
0.09
0.0
0.52
0,27
0.3J
0.23
O.OS
0.27
0.0
0.67
0.34
0.34
0.69
0,05
0,56
0,0
0,70
0.57
1.25
2. SB
0,08
0.02
0.0
0.22
0,15
0.04
0.02
0.01
0.11
0.0
0.43
0.26
0.13
o.ia
0.02
0.02
0.0
0.16
0.17
0.05
0.05
0.01
0.19
0.0
0.91
0,45
0.79.
0.56
0.08
0.51
0.0
1.15
0.08
1.21
1.74
0.20
0.41
0.0
0.66
0.39
0.55
2.30
0.21
0.27
3.86
0.72
0.43
o.eo
0.76
0.32
.0.10
1.75
0.04
0.23
0.22
0.12
0.17
0.24
3,47
0,70
0,28
0,01
0.52
0,28
0,60
3.54
1.06
0.32
0.50
0,87
0.36
0.91
3.23
1.16
0,36
0.55
1.00
0.63
0.07
0.50
0.31
0.15
0,06
0.06
0.07
0.19
1.90
0.69
0.21
0.17
0.17
0.15
0.05
0.90
0.20
0.20
0.07
0.06
O.OS
0.67
5,90
0.96
0.60
1.42
1.03
0.37
1.12
6,67
0,89
0,79
1.89
3.63
0.20
0.00
5.63
0,00
0.16
0.04
0,07
0.04
0.06
6.00
0.94
0.56
0.94
0.86
0.40
0.20
2.79
0.61
0.29
0.34
0.21
0.28
0.35
0.52
0.99
0.36
0.60
0.76
0.09
0,65
0.56
1.27
0.40
0.90
1.16
0.52
0.58
2.90
1.12
0.43
0.70
1.07
0.37
0.10
0.77
0.45
0.19
0.11
0.10
0.16
0.18
2.96
0.89
0.25
0.27
0.23
0.20
0.07
0.75
0.28
0.24
0.13
0.06
0.09
0.97
7.29
1.09
0.64
1.89
2.04
0.33
0.41
2.71
0.72
0.38
1.45
2.44
0.17
0.00
J.27
0.19
0.11
0.04
0.05
0.01
0,06
7.15
0.93
0.81
1.57
1.63
0.26
0.05
5,00
0.97
0.52
0.71
0,07
0.32
1.2«
8.03
1.04
0.84
2.30
3.11
0.63
2.66
6.65
1.04
1.27
2.51
a. 96
0.91
0.03
3.29
0.57
0.26
0.18
0.70
0.23
0,44
5.50
0.9i
0.36
0.56
0.41
0.26
1,39
11.35
I. 00
0.47
0.89
1.22
0.43
0.12
1.17
0.52
0.32
0.28
0.20
o.oa
0,09
4.17
0,57
0.34
1.06
1.98
0.17
0.02
0.07
0.30
0.14
0.17
0.40
0.10
0.0
2.12
0.00
0.06
0.0
0.03
0.0
0.06
2.47
0.35
0.13
0.25
0,48
0.20
0.25
6,75
0,76
0.35
1.28
1.91
0.43
0.12
3.75
0.58
0.20
O.fcl
1.57
0.22
0.01
1.47
0.25
0.12
0.11
0.54
O.OS
0.00
1.06
0.14
0,06
0.02
0.05
0.01
2.67
11.30
1.21
0,71
2,60
0.77
O.'BS
0,03
6.67
0.62
0.15
0.70
2.00
0,17
0.02
J.91
0.80
0,45
1.15
0,73
0.20
0.01
2.46
0.15
0.07
0.11
0.28
0.09
0.00
0.55
0.10
0.04
0.04
0.12
0.01
0.0
1.41
0.01
0.02
0.0
0.01
0.0
-------
COMPARISON OF TRANSFER MATRIX VALUES BV MODEL
DRV SUL
1
t
2
2
2
2
2
2
a
5
5
5
7
7
7
7
7
7
7
6
8
e
8
e
e
8
10
to
10
10
10
10
10
11
11
11
It
11
11
11
ASTRAP
ENAMAP
RCDM
HOE
AES
MEP
HCARL
ASTRAP
ENAHAP
RCDM
MOE
AES
MEP
MCARt
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCA ML
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
M£P
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCANL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MtP
MCARL
ASTRAP
ENAMAP
HCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
KCDM
MOE
AES
MEP
MCARL
0.01
0.18
0,69
0.07
0.10
0.11
0.10
0.01
0.0
0.58
0,06
O.OS
0.02
0,01
0,00
0.0
0.27
0.03
0.0
0.01
0.0
0.0
0.0
0.09
0.03
0.0
0.01
0.0
0.00
0.0
0.05
0,02
0.0
0.0
0.0
0.00
0.0
0.32
0.03
0.0
0.01
0.0
0.00
0.0
0.13
0.02
0.0
0.0
0.0
0.07
0.26
0.86
0.10
0,03
0.30
0,10
0.01
0,05
0.40
0,09
0.10
0.06
o.so
0,00
0,0
0.08
O.OS
0,0
0.01
0.03
0,0
0,0
0,00
0.01
0.0
0.0
0.0
0.64
0.82
2. 19
0,59
2.26
1.25
1.53
0.16
0.2D
0.86
0.27
0.62
0.16
0,36
0.06
0.04
0.72
0.18
0.13
0,08
0.13
0.01
0,01
0.37
0,1"
0.10
0.03
0.03
0.00
0.01
0.23
o.oe
0,08
0.03
0.03
0.02
o.04
0.42
0.10
0.07
0.02
0.04
0.00
0,01
0.36
0,08
0.0
0.01
0.02
0.13
0.33
0,58
0.53
0.51
0.30
0.17
5.95
0.09
3,04
0,91
2.03
2.5«
1.06
0.03
0.01
0.29
0.26
0,77
0,39
0.16
0.0
0.0
0.03
0.03
0.0
0.01
0.0
1.27
2.96
3.20
1.34
3.70
1.27
1.13
0.26
0.81
1.17
0.38
0.62
0.23
0.38
0.23
0.53
2.13
o.ai
0,97
1.02
0.66
0.09
0.21
1.95
0,37
0,58
0.46
0,50
0.02
0.11
1.24
0.28
4.50
0.32
0.50
0.06
0.44
0.65
0,15
0.21
0.07
0.11
0,03
0.12
1.20
0.18
0.16
0.12
0.12
0.12
0.37
0.42
0.43
0.24
0.11
0.11
7.45
4,94
4.46
2.51
9,95
5.99
1.54
0.18
0.34
0.69
0.52
1.73
0,87
0,52
0.0
0.0
0,09
0,06
0,0
0.03
0,01
0.18
1.47
1.71
0.39
0.72
0,23
0.41
0.07
0.91
0.66
0.15
0.15
0,05
0.22
0.09
0,94
1.10
0.20
0.29
0.17
0.44
0.17
0,56
1.26
0.23
0.39
0.28
0.56
0.19
0.54
1.09
0.32
0.75
0.81
0,05
0,02
0.15
0.36
0.08
0.0
0.02
0.10
0.04
0.27
0.71
0.10
0.16
0.05
0.16
0.03
0.17
0.27
0.16
0.05
0.03
0.05
0.73
2.52
3.55
1.44
1.42
0.65
0.82
6.46
2.54
1.36
2.41
5.39
4.94
1.36
0,00
0.32
0.23
0.23
0.43
0.16
O.OS
0.09
0.0
0,65
0,44
0,31
0,07
0.06
0,05
0,0
0,28
0,18
0,10
0.01
0,03
0,06
0,0
0,53
0,31
0,29
0,08
0,05
0.26
0.0
0.87
0.46
0.39
0.24
0.05
0,76
0.0
1.23
1.43
3.49
1.60
0.14
0,02
0,0
0.16
0,12
0,07
0,01
0,01
0.10 .
0.0
0.43
0.31
0.16
0.06
0,02
0,01
o.o
0.12
0.15
0.03
0.01
0.01
0.20
0.0
1.31
0.70
0.71
0.23
0,09
0,63
0.0
5.43
0.96
I. '3
0.98
0.32
0.94
0.0
2.18
1.11
10.64
5.29
O.SO
0.32
0.62
0.82
0.70
0.92
0.29
0.45
0.13
0.31
0.40
0.24
0.21
O.OS
0.22
0.23
0.71
0.86
0.36
0.63
0.25
0.44
0.76
1,05
1.65
0.49
1.07
0.56
0.91
1.63
U«
3.02
0.64
1.66
1.67
1.80
0.06
0.07
0.26
0.13
0.07
0.04
0.07
0.17
0.40
0.86
0.26
0.33
0.10
0.19
0.04
0.15
0.16
0.22
0.05
0.02
0.05
0.86
1.56
1.49
1.49
2.23
0.73
0.59
2.54
2.35
1.90
4.79
10.60
6.99
0.33
0.00
4,89
0,76
0.23
0,0
0.09
O.OS
0.61
1.54
1.34
1.15
1.23
0.36
0.70
0.20
0.53
0.65
0.36
0.36
0.09
0.44
0.37
1.04
1.51
0.60
. 1.13
0.42
1.21
0.97
1.63
3.20
0.77
1.65
1.04
1.63
1.42
2.00
3.96
1.23
2.66
1.77
0.98
0.09
0.12
0.43
0.1«
0.21
0.05
0,20
0.18
0.73
1.40
0.36
0.49
0.17
0.34
0.06
0.12
0.25
0.30
0.11
0.03
0.10
1.66
2.27
2.23
1.67
3.45
1.38
0.64
0.90
0.93
1.24
0.93
3.28
3.16
0.25
0.00
1.23
0.29
0.13
0.0
0.04
0.01
0.62
1.69 .
1.61
2.53
3.06
0.90
0,43
0.58
1.06
1.53
1.01
1.03
0.23
O.SS
2.53
3.27
4,36
3.10
7.39
2.74
1.63
7.52
5.17 .
3.20
6,80
17.41
11.14
2.39
0.06
1.16
1.06
0.56
O.SO
0.79
0.60
0.49
1.11
1.43
0.56
1.06
0.21
0,44
3,45.
6,07
6.50
1.35
2.45
1.23 .
1.12
0.13
0.21
0.59
0.48
0.37
0.06 .
0.09
0.15-
1.02
0.92
0.76
2.03
l.4t
0.26
0.02
0.06
0.31
0.15
0.19
0.24
0.13
0,0
0.42
0.04
0.05
0.0
0.04
0.0
0.07
0.44
0.42
0.13
0.10
0.16
0.25
0,40
1,90
1.26
0.63
1.45
1.03
0.66
0.17
1.06
0.97
0,30
0.67
0.61
0.33
0.01
0.42
0.31
0.13
0,10
0.16
0.05
0.00
0.22
0.15
O.OS
0.0
0.02
0.01
7.26
4.59
3.00
2,53
7.62
5.70
2.01
0.05
2.47
1.12
0.22
0.74
1.99
0.31
0.76
1.1T
•1.90
1.50
2.54
0.39
0,36
0.01
0,46
0.14
0,05
0.10
0.08
0.10
0.00
0.08
0.06
0.02
0.0
0.03
0.01
0.0
0.26
0.00
0.01
0.0
0.0
0.0
-------
COMPARISON OF TRANSFER MATRIX VALUES BY MODEL
WET SUL
2
2
2
2
2
2
2
4
0
tt
a
a
a
«
5
5
5
5
5
5
S
6
6
6
6
6
6
6
7
7
7
7
7
7
7
8
8
8
8
8
6
8
to
to
10
to
10
10
to
11
11
11
It
11
11
11
ASTRAP
ENAMAP
RCDM
MOE
AES
HEP
MCARL
ASTRAP
ENAMAP
RCbM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCD1
MOE
AES
MEP
MCARL
»STRAP
ENAMAP
RCDM
MOE
AES
MEP
MCAHL
ASTRAP
ENAMAP
RCDM
MOE
AES
M£P
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
hOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
AS1RAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
HOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
0.06
o.oa
0.30
0.07
0.21
0,14
O.Ob
0,07
0.0
0.25
0.06
0.05
0.05
0,01
0,02
0,0
0.11
0,04
0,0
0.01
0.0
0.0
0.0
0.04
0.03
0.0
0.01
0.0
0.00
0.00
0.02
0,02
0.0
0.0
0.0
0.03
0.0
0.14
0.03
0.0
0.01
0.0
0.00
0,0
O.Ob
0.03
0.0
0.01
0,0
0,24
0.12
0.37
0.09
0.24
0.23
O.Ob
0.04
0.02
0.17
0.08
0,10
0.07
0,20
0.00
0.0
0.03
0.06
0.0
0.03
0,01
0.0
0.0
0.00
0.01
0.0
0.0
0.0
1.47
0.71
0.94
0.43
2.36
It24
0.50
0.61
0.11
0,37
0.23
1.2«
0.32
0.23
0,31
0.00
0.31
0.16
0.25
0.14
0.08
0,14
0.00
0,16
0.13
0.29
o.oe
0.03
0.02
0.01
0.10
0,06
0.17
0.05
0.01
0.22
0.00
0.18
0.10
0.14
0,05
0.04
0.05
0,0
0.15
0.08
0.0
0,02
0.01
0.36
0.15
0.25
0.38
0.61
0.34
0.11
5.43
1.45
1.30
0,62
1.83
2.17
0.47
0,19
0,00
0.12
0.20
0.19
0.34
0.09
0.0
0.0
0.01
0.03
0.0
0,01
0.0
3.44
1.40
1.37
0.92
3.19
1.27
0.61
1.02
0.58
0.50
0.31
1.14
0.31
0.2B
0,75
0.02
0.91
0.32
1.85
0.95
0.33
0.48
0.0
0,84
0.29
1.26
0.60
0.20
0.12
0.04
0.53
0.22
0.50
0.66
0.17
0.40
0.03
0.28
0.14
0.71
0.09
0.10
0.25
0.0
0.51
0.16
0.33
0.16
0.09
0.37
0.02
0.18
0.33
0.27
0,12
0,09
6.89
1.41
1.91
1.63
3.35
2.81
0.61
0.65
0.00
0.30
0.38
0,56
O.U9
0.28
0.0
0.0
0.0"
0.0»>
0.0
0.06
0.01
1.10
1.32
0.73
0.33
1.03
0,16
0.33
0.71
0.59
0.26
0.15
0.31
0.06
0.20
0.92
0,75
0.47
o.ie
0.46
0.23
0.33
0.74
0.73
0.54
0.21
0.68
0.45
0.34
1.36
0,60
0,47
0.26
1.53
1.24
0.35
0,14
0.05
0,16
0.09
0.07
0.03
0.11
0.37
0,38
0,30
0,13
0.33
0.09
0.14
0.12
0.06
0.12
0.15
0.05
0.02
0.05
2.15
1.61
1.52
1.00
1.73
0.72
0,44
7.71
0,90
0,59
1,58
2.89
3.53
0.56
0.02
0.07
0.10
0.18
0.43
0.30
0.05
0.20
0,0
0.28
0.37
0.31
0,08
0,06
0.12
0.0
0.12
0.16
0.10
0,02
0,04
0.25
0.0
0.23
0.26
0,21
0,06
0.05
0.52
0.0
0,37
0,39
0.29
0,20
0,05
0,59
o.o
0.53
0,98
1,99
1.06
0.06
0,04
0.0
0,07
0,13
0.07
0.01
0.01
0.26
0.0
0.16
0.27
0.25
0.05
0.02
0.03
0,0
0.05
0.15
0.03
0.01
0.01
0.16
0,0
0.56
0.55
0.61
0.14
0.06
0.25
0.0
2.33
0.71
0.96
0.57
0.21
0.87
0.0
0.93
0,75
2.55
1.42
0.17
1.03
0.73
0.35
0.54
0.72
0.25
0.31
0,70
0,46
0,17
0.22
0.26
0.12
0,17
0,83
0,99
0.36
0.31
1.01
0,33
0.27
1.94
1.55
0,79
0.38
t.T5
0.83
0.36
3.02
1.63
1.30
0.59
2.24
2.29
0.52
0.52
0.12
0.11
0.13
0,21
0,04
0.07
0.84
0,83
0.37
0.22
0.90
0.22
0.15
0.15
0.12
0.07
0.20
0.06
0.03
0.05
1.16
1.20
0.64
1,04
1.62
0.69
0.37
1.54
3.06
0.61
2,99
3.26
3.15
0.20
0.03
5.76
0.33
0.19
0.0
0.19
0.04
2.33
1.35
0.57
0.63
1.13
0.42
0,40
1.16
0.35
0.28
0.30
0.36
0.13
0.26
1.79
0.90
0.65
0.46
1.34
0.47
0.47
2,15
3.91
1.37
0.57
2.24
1.26
0.50
2.94
3.46
1.7J
0.63
2.41
1.89
0.29
0.96
0.17
0.19
0.17
0.42
0.06
0.16
1.03
1.77
0.60
0.29
1.14
0.26
0.20
0.26
0.15
0.11
0.25
0.13
0.05
0,09
2.18
1.75
0,95
1.14
2.03
1.56
0.32
2.11
1.35
0.53
0.65
t.54
1,87
0,17
0.00
5.39
0.12
0.12
0.0
o.to
0.01
1.06-
1.56
0.69
1.66
1.75
0.66
0.27
1.04
1.12
0.66
0.74
1.14
0.17
0.32
3.91
7.24
1.88
1.99
4.75
1.97
0.61
12.16
12.82
1.37
5.42
7.88
6.46
0.68
0.31
3.37
0.46
0.40
0.42
0.63
0.22
1.30
1.16
0.61
0.45
1.48
0.16
0.26
5.98
7.73-
2.79
0.91
3.52
1.25
0.42
0.32
0.19-
0.25
0.39
0.53
0.05
0.08
0.25
0.53-
0.39
0.54
1.22
0.99
0.17
0.12
0.03
0.13
0.13
0.19
0.16
0.10
0.0
0.35
0.02
0.05
0.0
0.07
0.0
0.07
0.79
0.16
0.12
0.10
0.11
0,20
0.00
0,56
0,54
0.47
0.77
0.38
0.43
0.24
0.23
0.42
0.24
0.25
0.29
0.23
0.04
0.24
0.13
0.12
0.0
0.16
0.05
0.01
0.06
0.06
0.05
0.0
0.01
0.01
8.17
3.91
1.29
1.64
3.10
2.01
0.75
0.13
2.73
0.48
0,18
0,49
0,75
0,17
2.74
3.05
0.61
0.99
2.46
0.29
0.20
0.02
0.25
0.06
0.05
0.0
0.05
0.09
0.00
0.03
0.03
0.03
0.0
0.0
0.01
0.0
0.09
0.00
0.02
0.0
0.0
0.0
-------
COMPARISON OF TRANSFER MATRIX VALUES BY MODEL
TOT SUL
t
2
2
2
2
2
2
2
3
3
3
3
3
3
3
a
a
a
a
4
4
4
s
5
5
5
5
5
S
T
T
7
7
7
7
7
6
6
a
8
B
8
8
9
10
10
10
10
10
10
10
11
11
11
11
11
11
11
A3TRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAHAP
RCOM
HOE
AES
HEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAfAP
RCDM
MOE
ACS
M£P
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCAHL
ASTRAP
ENAMAP
RCOM
MOE
AfcS
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
0.07
0,22
0.99
0,13
0.31
0.25
0.16
0,09
0.0
0.82
0.12
0.10
0.07
0,04
0,02
0,0
0.38
0,08
0.0
0,02
0.01
0,0
0,0
0,13
0.06
0.0
0.02
0.0
0.00
0.00
0.08
0.04
0.0
0.01
0,0
0.03
0.0
0.45
0,06
0,0
0,02
0.0
0.00
0.0
0,19
0.04
0,0
0,01
0.0
0.31
0.40
1.23
0,19
0.67
0.53
0,16
0,05
0.07
0.57
0.17
0.20
0.13
0.69
0.00
0.0
0.11
0.11
0.0
0.04
0.04
0.0
0.0
0.01
0.02
0.0
0.0
0.0
2.11
1.53
3.12
1.02
4.62
2.46
2.04
0.78
0.31
1.23
0.50
1.06
0.49
0.59
0.36
0.04
1.02
0.34
0.38
0.22
0.20
0.15
0.01
0.53
0.27
0,39
0,11
0.05
0.02
0,02
0.33
0.16
0.25
0,08
0.04
0.24
0.04
0.60
0.19
0.21
0.07
0.08
0.05
0,01
o.s;
0.16
0.0
0.04
0.04
O.S1
0.48
0.83
0,91
1.12
0.65
0.28
11.37
5. 54
4.34
1.S3
3.86
4.71
1.52
0,23
0.01
0,42
0.46
0.96
0,73
0,27
0.0
0.0
0.04
0.06
0.0
0.01
0.0
«.71
4,36
4.58
2.26
6.89
2.54
1.74
1.29
1.3'
1.67
0.69
1.76
0.54
0,67
0.98
0.55
3.05
0.73
2.81
1,97
0.98
0.58
0.21
2.79
0.66
1.85
1.06
0.71
0,14
0,15
1.77
0.50
1.00
0.98
0.67
0.45
0.47
0.93
0.29
0.92
4.16
0.21
0.28
0.12
1.71
0.34
0.49
0.28
0.20
0,49
0.39
0.60
0.76
0.51
0.23
0.19
14,34
6.35
6.37
4.14
13.30
8.80
2.15
0,83
0.35
0.99
0.90
2.31
1.36
0.80
0,0
0.0
0.13
0.12
0.0
0.09
0.03
1.27
2.80
2.44
0.72
1. 75
0.41
0.75
0.78
1.51
0.94
0.30
0.46
0.13
0.41
1.01
1.68
1.58
0.38
0,76
0.40
0,77
0,91
t.29
1.79
0.44
1.07
0.73
0,90
1.57
l.lfl
1.56
0.58
2.08
2.04
1.21
0.16
0.19
0.52
0.17
0,07
0.05
0.22
0.41
0.64
1.01
0.27
0,49
0,15
0.30
0.15
0.25
0.39
0.30
0,11
0,05
0.11
2.87
4.13
5.07
2.44
3.15
1.37
1.26
16.17
3.44
1.98
3,98
8,29
8.47
1.92
0.02
0.39
0.33
0.41
0.85
0.46
0.14
0.29
0.0
0.93
0.82
0,62
0,15
0.14
0.17
0.0
0,41
0,35
0.21
0.03
0,06
0.34
0.0
0.76
0,59
0.50
0.16
0.11
0.76
0.0
1.24
0,87
0,66
0,44
0.10
1.37
0,0
1,76
2,41
5.48
2,66
0,22
0,06
0,0
0,24
0,25
0,14
0,03
0,03
0,36
0,0
0.61
0,58
0,41
0,11
0,04
0,05
0.0
0.17
0.29
0,05
0,02
0,02
0.36
0,0
1,87
1.25
1.32
0.37
0.16
0.89
0,0
7.75
1.69
2.69
1.55
0.53
1.81
0.0
3.11
1.86
13,19
6,71
0.68
1.35
1.55
1.18
1.24
1.64
0.53
0.76
0.83
0,76
0.57
0.46
0.46
0.17
0.39
1.06
1.70
1.25
0,69
1.64
0,56
0.71
2.70
2.60
2.65
0.87
2.82
l.«l
1.27
4.95
3.36
4.32
l.«3
3.90
4.16
2.31
0.56
0.20
0.37
0.27
0.26
0.06
0.14
1.01
1.23
1.23
0,46
1.23
0.32
0.34
0.20
0.26
0.22
0.41
0.13
0.05
0.11
2.06
2,78
2,13
2.54
3.86
1.62
0.96
4,06
5.41
2.72
7.78
13.67
10.14
0.52
0.03
10,67
1.08
0.42
0.0
0.26
0,09
2.94
2.69
1.92
1.96
2.36
0.80
1.10
1.37
0.66
0.93
0.66
0.72
0.22
0.73
2.15
1.94
2.16
1.07
2.46
0.89
1.69
3.12
5.54
4.56
1.34
4.09
2.31
2.32
4.36
5.46
5.69
2.06
5.07
3.67
1.26
1.05
0.29
0.62
0,36
0.63
0.12
0.36
1.21
2.50
2.00
0.66
1.64
0,45
0,55
0.33
0.27
0.35
0.55
0.24
0.06
0.19
3.84
4,03
3.18
2.81
5.46
2.94
0.96
3.01
2.28
1.77
1.57
4.82
5.05
0.41
0.00
6.62
0.42
0.25
0.0
0.14
0.03
1.90
3.26
2.30
4.19
4.83
1.56
0.69
1.62
2.18
2.19.
1.75
2.17
0.40
0,87
6.45
10.51
6.26
5.09
12.14
4.70
2.24
19.69
17,99
4.57
14.22
25,29
17,61
3.07
0.36
4.52
1.54
0.96
0.91
1.42
0.81
1,79
2.26
2.05
1.02
2.54
0.39
0,70
9,43
13.91
9,29
2.26
5.97
2.47
1.54
0.44
0.40
0.84
0.87
0.91
0.13
0.18
0.40
1.55
1.31
1.30
3.25
2.40
0.45
0.14
0.11
0,44
0.28
0.39
0.40
0.23
0.0
0.77
0.05
0.10
0.0
0.11
0.01
0.14
1.24
0.61
0.2S
0.21
0.27
0.46
o.eo
2.46
1.80
1.10
2.22
l.«2
1.11
0.42
1.31
1.39
0.54
0.92
0.90
0.55
0.05
0.66
0.45
0.25
0.10
0.32
0.09
0.01
0.28
0.21
0.10
0,0
0.03
0.03
15.43
8,50
4,26
«.17
10.72
7.71
2.77
0.18
5.21
1 ..60
0.40
1.23
2.74
0.49
3.52
4.23
2.71
2.48
5.00
0,68
0.59
0.03
0.70
0.21
0.10
0.10
0.13
0.19
0.00
0.12
0.11
0.05
0.0
0.03
0.03
0.0
0.34
0.01
0.03
0.0
0.0
0.0
-------
B-5
Means and Standard Deviations of Absolute Values Over All
Models for 11 Source Regions and 9 Receptor Areas
-------
MEANS OF ALL 7 MODELS FOR AMB 802
1
2
3
a-
5
6
r
e*
9-
10
li
0.23
0.00
0.03
0.01
0,01
0,03
0,01
0.07
0.31
0.03
0,00
1.92
0.44
0,18
0.09
0.07
0.09
0,06
0,50
7,42
0,30
0.01
s.«
0,76
1.12
0.67
0.48
0.31
0.28
0,34
9.89
0.93
0.03
1,06
0.43
0,62
0.66
0.85
0.09
0.22
0.12
2.54
6.40
0,35
0.23
0.00
0.18
0.31
1.39
0.04
0.14
0.04
0.46
1.59
4.35
0.90
0,27
0,64
1.25
3.96
0,09
0.41
0.11
2.10
6.60
«.7S
1.62
0.47
1.19
2.37
4.11
0.15
0.70
0.15
3.21
2.28
0.92
2.52
1.20
5.97
16.31
1.29
1.00
6,89
0.31
1.35
0,18
0,13
0.33
2.02
1.00
0.30
0.11
9.87
2.26
1.87
0.26
0,03
0.06
STANDARD DEVIATION VALUES FOR AMB 802
1
2
3
4
5
6
7
»
9
10
11
0.24
0.14
0.06
0.02
. 0,01
0,07
0,03
0.48
0,54
0,03
0.00
1.35
0.25
0,16
0,09
0.06
0,08
0,00
0.36
8.49
0.29
0,01
3,99
0.72
0.79
0.50
0.32
0.36
0,31
0,31
8.11
0,57
0,03
1.30
0.67
0.74
0,64
0.56
0.07
0.20
0,11
2,89
4,42
0,48
0.20
0.08
0.15
0.24
i.«3
0,05
0.14
0.06
0,40
1.80
4.85
0.73
0.19
0,47
1,03
3,36 •
0,05
0,37
0,09
2,00
5,02
11,98
1.70
0.32
0.01
2,00
3.19
0.00
0.72
0.11
3.16
1.62
2.20
2.1"
0.86
4.08
0.06
1.69
0.88
10.6*
0.18
1.13
0.06
0.27
0.33
2.«5
1.19
0.48
0.18
6.79
3.63
1.54
0.47
0.03
0.15
-------
MEANS OF ALL 7 MODELS FOR AMB so«
1
2
J
4
5
6
7
8
9
10
It-
0.24
0,09
O.OS
0,02
0.01
0.06
0,05
0,30
0.16
o.oa
0,00
1,05
0.44
0,17
0,08
0,07
0.14
0,07
0.46
2.07
0,22
0.01
2.33
0.94
0.63
0.43
0.26
0.53
0.25
0,48
3.23
0.63
0,03
1.38
0,90
1,00
0,67
0,66
0,24
0,37
0,23
2,06
2.06
0,26
0.26
0.11
0.21
0.34
0.83
0.07
0,16
0.06
0.43
0.76
0.65
1.02
0.44
0.85
1.04
1.16
0,17
0,50
0,22
1.63
2.20
0.93
l.«5
0.67
1.16
1.35
1.03
0.27
0.72
0.23
2.04
1.16
0.53
1.63
1.21
2.57
2.86
0,75
1.21
2.45
0,39
1.20
0.23
0.32
0.56
1.67
1.01
0.36
0.19
3.45
1.48
1.10
0.45
0.12
0.21
STANDARD DEVIATION VALUES FOR AMB 304
1
2
3
4
5
6
7
6
9
10
1 1
0,28
0.16
0,09
0.04
0.02
0.12
0,06
0,36
0,12
0,05
0,01
1.13
0.36
0,17
0,10
0,07
0.16
0,12
0.54
2.97
0,19
0,02
3.11
1,38
0.70
0.30
0.20
0.93
0.27
0.70
3.60
0.47
0.04
2.31
1,82
1,84
0,84
0.72
0,36
0,56
0.33
3.22
1,77
0,41
0.23
0.12
0.16
0.27
0.86
0.08
0.15
0.07
0.35
0.63
0.76
1.27
0.59
1.17
1.13
0.97
0.17
0.65
0.31
1.93
2.30
2.16
2.02
0.94
1.50
1.46
0.89
0.25
1.03
0.24
2.40
1.04
1.21
2.40
1.70
2.72
2.16
1.14
1.91
3,94
0,38
1.47
0.17
0.79
0.85
2.31
1.31
0.52
0.39
3.7.4
2.36
1.28
0,69
0.19
0,53
-------
MEANS OF ALL 7 MODELS FOR DRY SUL
1
2
J
4
5
6
7
0
9
10
11
0,18
0.10
0.04
0.02
0,01
O.OS
0.02
0.31
0.17
0,02
0.00
1.33
0.38
0.19
0.10
0,07
0,10
0.07
0.36
2.80
0.27
0.01
2.12
0.55
0.8S
0.60
0.42
0,24
0,26
0.26
5,26
ff.69
0.03
0.73
0.32
0.46
0.49
0.65
0,10
0.22
0.11
1.59
3,78
0,21
0,23
0,09
0,19
0,33
1.24
0.06
0,15
0,05
0,46
U47
2,95
0,62
0,22
0,50
0,96
1.82
0,10
0.33
0.10
1.28
«.21
0.86
0.99
0.38
0,90
1.61
2.01
0.18
0,52
0.14
1.90
1.53
0,24
1,58
0,86
3,58
7,95
0,68
0.76
3.17
0.28
0,94
0,16
0.08
0.22
1.05
0.59
0.17
0,06
4,67
0,99
1.24
0.13
0.03
0.04
STANDARD DEVIATION VALUES FOR DRY SUL
t
2
3
4
S
6
7
I
9~
to
11
0.23
0.21
0,10
0,03
0,02
0.12
0,05
0.28
0.19
0.03
0.00
0,70
0.26
0,24
0,13
0,08
0,14
0.13
0.18
1.77
0.26
0,01
1.11
0.34
0.63
0,62
0.40
0.22
0.41
0,15
2,87
0,51
0.04
0.62
0,33
0,40
0,37
0,32
0,13
0,23 •
0.09
1,08
2,61
0,14
0,24
0,10
0,19
0,29
1,17
0.06
0.16
0,06
0,47
1.85
3,81
0.26
0.11
0.24
0.45
0.64
0.08
0.25
0,07
0,58
3,55
1,80
0.43-
0.19
0.44
0,82
1.03
0,13
0.43
0.10
0.88
1.20
0.45
0.96
0.43
1.88
5,19
0.37
0,44
2,29
0,20
0.65 -
0.10
0.15
0,15
0,52
0,35
0.15
0.09
2,27
0.*3
0.80
0.15
0.03
0,10
-------
MEANS OF AIL 7 MODELS FOR HET SUL
I
2
3
a
5
6
7
8-
9
to
11
0.12
0.07
0.03
o.ot
0.01
0.03
0.01
0.19
0.10
0.02
0.00
1,09
0.44
0.10
0.12
0.06
0.10
0,04
0.32
1.90
0.16
0.01
1,74
0.59
0.73
0.52
0,32
0.25
0,21
0.20
2.66
0.38
0,02
0.72
0.33
0.40
0.53
0,00
0,09
0,25
0.00
1.31
2.54
0,16
0.19
0.00
0.16
0.26
0.75
0.05
0.15
0,04
0.30
0.72
0,96
0,56
0,30
0.59
1.09
1.66
0.17
0.50
0.10
0,99
2.15
0.94
1.00
0.41
0.07
1.72
i.»3
0,30
0,76
0,15
l.«2
1.17
0.02
1.10
0.7«
3,19
6,60
0,03
0,70
3.23
0.26
0,50
0,12
0.07
0.23
0.51
0.27
0.11
0.03
2.98
0.71
1.51
0.07
0.02
0.01
STANDARD DEVIATION VALUES FOR NET SUL
1
2
3
4
5
6
7
0
9
10
11
0,10
0.00
0,04
0,02
0.01
0.05
0.02
0.11
0,06
0,02
0,01
0,60
0.30
0,12
0,10
0.06
O.OS
0,06
0,17
1,67
0,11
0,01
i.ii
0.35
0.60
0.43
0.24
0.24
0.17
0.13
2.07
0.22
0.03
0.45
0.23
0-.27
0,21
0,49
0,05
0,12
0.05
0.61
2.55
0.15
0.14
0.06
0.11
0.19
0.60
O.OS
0.12
0.05
0.26
0.70
0.05
0.20
0.21
0.34
0.65
0.93
0,16
0,34
0,06
0.41
1.20
2.14
0.60
0.34
0.52
1.10
1.12
0.31
0.50
0.00
0.66
0.73
2.02
0.5S
0.39
2.26
«.7S
1.13
0.53
2.75
0.17
0.39
0,05
0,13
0,25
0.14
0.07
0.06
0.03
2.53
0.92
1,21
0.00
0.02
0.03
-------
MEANS OF ALL 7 MODELS FOR TOT SUL
1
2
3
4
5
6
7
a
9
to
u
0.30
0.18
0.07
0.03
0.02
0.08
0.04
0.50
0.27
0.04
0.00
2,«2
0,82
0.37
0.22
0.13
0,21
0,12
0,68
4.70
0.44
0,02
S.«7
l.l«
i.se
1.12
0.74
0.49
0.49
0.4S
7.»2
1.08
0.05
lt«S
0.65
0.94
1.02
1.46
0.20
0,47
0,19
2,90
6.32
0.37
0.42
0.17
0.35
0.59
1.99
0.11
0.30
0.09
0.76
2.19
3.9t
1.16
0.52
1,09
2. OS
3.48
0.27
0.83
0,20
2.28
6.36
1.80
2.00
0.79
1.77
3.33
3.94
0.49
1.29
0.29
3.32
2.70
1.07
2.68
1.60
6.77
14.63
1.50
1.54
6.40
0.54
1,52
0.28
0.1S
0.45
1.56
0.86
0.27
0.09
7.65
1.69
2.74
0.21
0,05
0.05
STANDARD DEVIATION VALUES FOR TOT SUL
1
2
3
4
5
6
7
8
9
10
U
0.31
0.29
O.i4
0,05
0.03
0.16
0.07
0.37
0.25
0.05
0.01
1.18
0.54
0.31
0,19
0,12
0,19
0,18
0.29
3,32
0,32
0,03
1.60
0,50
1.03
0.90
0.57
0.32
0.55
0.20
4.54
0.62
0.06
0.91
0.47
0,52
0,43
0,53
0.15
0,29
0,12
1.39
5.12
0,26
0.36
0.16
0.28
0.44
1,84
0,10
0.25
0.11
0.71
2.63
4.64
0.41
0.23
0.46
0,83
1.21
0.17
0.43
0.12
0.92
4.59
3.93
0.62
0,34
0,59
1.48
1.71
0.31
0.79
0.15
1.38
1.72
2.46
• 1.46
0.71
3.44
8,11
1.39
0,83
4,63
0,33
1,02
0.13
0,28
0.38
0.62
0.38
0,22
0,11
4.43
1.78
1.66
0.23
0.05
0.13
-------
B-6
Comparison of Transfer Matrix Percentage Contribution Values
by Model for 11 Source Regions and 9 Receptor Areas
-------
COMPARISON OF TRANSFER- HATRIX PERCENTAGES BY MODEL
AMB 502
2
2
2
2
2
2
2
0
4
4
a
4
4
4
5
5
5
5
5
5
S
6
b
6
6
6
6
6
7
7
7
7
7
7
7
B
8
8
8
8
8
8
10
to
10
10
10
10
10
11
11
11
11
11
11
11
ASTRAP
ENAMAP
RCDM
MOE
AES
HEP
MCAHL
ASTRAP
ENAMAP
RCOH
HOE
AES
HEP
HCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
M£P
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
HEP
MCARL
ASTRAP
ENAMAP
HCDM
MOE
AES
HEP
MCARL
ASTRAP
ENAMAP
RCOM
HOE
AES
HEP
MCARL
ASTRAP
ENAMAP
RCOH
MOE
AES
M£P
MCARL
ASTRAP
ENAMAP
RCOM
HOE
AES
HEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
M£P
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
HEP
MCARL
AS1RAP
ENAMAP
HCOM
MOE
AES
MEP
MCARL
2.08
7.13
6.95
4,98
4.56
4.63
2.02
5.83
. 0.0
16.99
13.86
6.42
3.30
0.66
0.64
0.0
6.05
7.54
0,0
1.51
0.0
0.0
0.0
1.02
2.93
0.0
0.0
0.0
0.00
0.0
0.61
2.20
0.38
0,0
0.0
1.03
0.0
5.74
1.72
0,0
1.24
0.0
0.00
0.0
2.26
3.29
0.0
0.0
0.0
65.79
90.66
51.57
42.36
79.99
84.68
16.26
4.59
2.01
7.76
12.93
6.02
a.OO
79,13
0.03
0.0
0.63
5.06
2.63
0.63
1.32
0.0
0.0
0.01
0.14
0.0
0.0
0.0
2.21
7.22
12.32
7,65
18.52
10,02
14.31
1.07
3.91
12.81
11.16
14,76
5.18
9.66
0.47
0.92
9.82
6,69
2.63
1.75
2.95
0.05
0.10
2.49
2.60
0.55
0.50
0,49
0.01
0.13
1.67
1.76
1.30
0.42
0.42
0.20
0,49
3.89
2.88
1.10
0.41
0.61
0.02
0,21
3.07
2.«2
0.2S
0.20
0.40
2.23
10.59
15.21
37,64
21.77
15.37
9.J8
93.10
76.28
36.76
23.03
31.68
62.92
58.91
0.24
0.13
1.54
4.09
7.19
3.24
2.86
0.0
0.0
0.02
0,07
0.0
0,0
0,0
4.59
13,50
9,64
10.01
10.81
6.49
8.04
3.03
8.14
9.56
9.00
5.89
3.94
7.05
2.27
8,09
18.36
8.66
6,30
12.09
11.59
0.50
1.25
8,70
4,00
2,52
2.96
3.96
0.12
0.64
6.16
3.44
2.27
2.82
5.46
0.53
2.62
3.53
2.59
1.56
0.71
1.17
0.19
1.1"
7.73
3.13
0.94
l.M
1.28
2.56
5.79
4.92
17.38
3.51
3.02
4.14
64.67
56.91
26.93
36.76
56.12
61.91
51.02
1.54
1.67
2.20
1.75
6.02
4.90
5,84
0.0
0,0
0,04
0.06
0.02
0.02
0.03
0.95
6.43
7.36
4.10
4,75
2.16
0.23
1.23
10.20
7.36
4.96
2.65
1.60
6.26
1.27
10.72
13.05
6.05
6.44
4.20
11.08
1.09
0.73
6.05
3.56
4.06
3.29
5.96
1.63
5,36
8,17
5.60
9.34
10.26
11.37
0.30
0.72
2.60
1.97
0.60
0.39
1.76
0.37
2,06
6.37
3,32
2.19
0.95
2.52
0.95
2.95
4.56
8.79
1,48
1.32
2.66
7.82
28.26
34. UO
29. 6«
19.4J
11.67
15.65
64.39
26.09
7.65
31.55
48.57
63.65
37.86
0.00
0.«6
0.19
0.46
0.30
0.26
0.22
2.90
0,0
2.62
0.56
2.22
1.03
4,09
3.81
o.o
3.19
5,60
2.03
0.83
6.56
5,36
0.0
6.60
9,50
5,56
3.02
9.62
7.92
o.o
6.29
7.26
3.75
0.73
3.60
31.08
0.0
11.35
25.03
00.87
00.59
12.25
1.16
0.0
1.21
2.94
0.59
0.62
0.96
4.49
0.0
0.26
7.69
2.50
2,15
1.95
2.12
0.0
1.93
8,09
1.11
1.02
2.20
9.64
0.0
13.32
1°.20
6.86
6.77
10.30
20.17
o.o
06.25
12.62
16.88
17.76
25.13
10,97
0.0
2.81
2.30
15.60
20,66
33.25
2,83
3.67
3.30
0,06
3.27
I. SO
3.31
3.19
3.20
0.35
0.83
2.59
1.23
0.27
0.50
7,21
10.72
6.98
6,66
3.82
6.64
6.91
7.62
13.55
0.51
5.70
0,16
5.45
31.43
23.56
28.02
8.89
10,45
15.93
62.82
0.95
0.16
1.92
1.96
0.90
0.56
0.55
2.37
0.19
8.77
3.66
2.80
1.26
1.86
1,84
1.60
2.40
7.00
1.19
0,79
2.01
10.00
18.75
13.78
16,59
16.10
7.95
6.12
31,98
20.60
12.39
36.20
50.20
62.66
2.86
0.01
9.02
0.76
0.29
0.08
0.08
0,09
5.14
7.06
3.97
7.91
0.51
2.56
0.48
0.98
0,64
5.27
7.73
0.33
2.54
7.72
7.36
10.50
13.56
12.12
12.60
8.97
19.55
9.16
12.58
16.60
7.79
10.63
9.92
12.90
20.50
23.12
25.22
10.16
17.67
21.32
38.69
1.02
0.26
2.00
2.97
1.70
1.03
1.50
2.04
6.76
10.31
5.69
4.90
2.61
2.76
2.72
1.50
2,76
10,97
2.22
1.30
3.19
28.27
25.52
14.66
22.4}
25.61
19.45
7.75
13.99
6.51
0.87
7.85
15.37
30.21
2.20
0.00
1.51
0.17
0.18
0,05
0.06
0.02
2.07
3.20
2.91
6.71
4,43
2.05
1.59
4,89
0.65
6.56
6.53
0.57
2.15
6.10
20.77
22.60
26.86
20.20
31.00
22.86
16.08
05.56
22.39
0.79
30,59
37,59
53,05
5*. 67
0.30
a. 10
3.30
2.05
1. 10
2.99
3.60
2.06
3.27
5.96
3.63
3.60
1.30
2.33
20.60
35.53
30.23
8.50
8,52
6.65
6.00
1.62
0.96
0.71
6.93
2.85
1.31
1.77
0.96
3.15
3.13
3,89
5.07
6.11
2.06
0.09
0.07
0.51
0.47
0.02
0.51
n.73
0.0
0.07
0.01
0.02
0.0
0.02
0.00
0.20
0.70
1.19
0.67
0.33
0.43
1.36
4,46
16,53
13.21
10.96
10.76
13.34
11.10
1.50
7.36
9.45
0.77
0.62
5.60
0.55
0.06
1.00
1.32
1.01
0.35
0.63
0.28
0.00
0.59
0.63
0.12
O.io
0.0V
0.05
81.00
37.24
26.66
33.57
05.23
53.10
70.0*5
0.37
16.61
9.06
2.66
0.25
19.60
3.31
12,22
17.65
37.60
05.11
33.90
6.72
7.60
0.09
1.78
0.67
0.49
O.J2
0,36
0.98
0,00
0.06
0.16
0.10
0.05
O.IO
0.06
0.0
0,05
0,00
0.01
0.0
0.0
0.0
-------
COMPARISON OF TRANSFER MATRIX PERCENTAGES BY MODEL
AHB SOtt
1
1
2
2
2
2
2
2
2
3
J
3
3
3
3
3
a
u
«
a
a
u
a
5
5
5
5
5
5
5
6
7
7
7
7
7
7
7
6
8
a
e
6
6
a
10
10
10
10
to
10
10
u
u
11
11
11
11
u
ASTHAP
ENAMAP
RCOM
HUE
AES
HEP
MCARL
ASTRAP
ENAMAP
RCDM
HOE
*es
MEP
MCARL
ASTRAP
ENAMAP
RCOM
HOE
AES
MEP
HCARL
ASTRAP
ENAMAP
HCOH
HOE
AES
MEP
MCAHL
ASTRAP
ENAMAP
HCOH
HOE
AES
HEP
"CAUL
ASTRAP
ENAHAP
HCO«
HOE
AES
MEP
HCARL
ASTRAP
ENAHAP
RCOM
MOE
AES
HEP
HCAKL
ASTRAP
ENAMAP
RCDH
HOE
AES
HEP
HCARL
ASTRAP
ENAMAP
HCDM
MOE
AES
HtP
MCARL
ASTRAP
ENAHAP
RCOH
HOE
AES
MEP
MCARL
ASTRAP
ENAMAP
HCOM
MOE
its
MEP
MCARL
2.72
10,83
6.50
5.11
9.54
6.97
7.13
12.97
0.0
20.46
15.75
6. IS
6.36
3.81
1.61
0.0
10,18
10,23
o.o
1.26
0,0
0.0
0.0
1.96
a, 29
0.0
0,64
0,0
0,00
0.0
1.57
3.65
1.26
0,0
0.0
2.25
0.0
10.96
7.31
0.0
1,05
0,0
0.01
0.0
0.90
5.54
0,0
0.0
0,0
76.06
79,69
34.64
31.63
56,48
69,26
39,09
u,34
9,26
7,16
10,94
9.16
11.66
48. SI
0.04
0.0
1.S5
5,06
15,39
0,54
1.46
0.0
0.0
0.01
0,26
0,0
0,0
0,0
6.06
9.96
6.68
6.59
8.54
14.02
15.31
8.51
10.72.
16.12
14.66
22.21
12.30
21.19
3.11
1.08
13.74
9.92
2.33
4,19
7,07
0.27
0.26
3.73
4.13
0.61
0.64
1.32
0.07
0.32
2,79
3.22
2.35
0.55
0.50
1.14
1.95
8.77
5.92
1.60
0,79
2,69
0.26
0.42
6.76
4.67
0.0
0.26
0.71
10.94
26.23
20.25
30.96
27.68
30.05
16.12
69,15
48,49
11,42
15.05
24,62
30,26
29,20
0.45
0.17
2.70
4,47
9,84
6,87
3.69
0,0
0.0
0.05
0.19
0,0
0.06
0.0
9.58
12.90
7.59
7.98
14.33
9.49
10.73
9.69
18.00
15.06
13.11
10.19
7.65
15.80
7.42
8.72
17.86
11.44
13.47
17.83
17.08
1.45
1.57
7,09
5,16
3.33
3.86
5.42
0.26
1.10
5.41
4.32
2.60
1.65
5,27
1.92
8,70
7,85
5,53
2.25
1.43
4.23
0.88
1.70
10.07
5.53
1.36
1.77
3.77
7,91
15.67
12.34
21.60
8.45
7.09
8.69
59,36
29,39
13,30
20,21
35,69
42,13
22,92
1.55
2.24
5,33
4,91
8.12
7.02
6,06
0,0
0.0
0,06
0.20
0.0
0.06
0.03
2.67
8.07
7.16
5.25
9.02
6.40
5,82
3.64
19.67
12.97
9.54
6,46
4.04
11.66
4,76
18.52
15.83
9.66
7.83
7.98
17.64
3.90
4.52
7.40
5.30
4,64
6,96
9.06
3,87
4.56
6,83
6,54
8.32
11,78
10,59
0,66
2.95
6,41
4,76
0.26
0,70
4,81
1.70
4,62
9,21
6.07
1,90
1.65
6,05
2,89
6,44
10.93
15,41
4,29
5.72
4.98
16,03
22.29
17.24
20.95
31.45
23.57
15.55
57,66
8,07
5.83
15.79
25.41
32.77
13.63
0.00
0,26
0.20
0.53
0,11
0.23
0.21
2.55
0.0
5.50
5.20
5.71
2.51
5,40
4.92
0,0
9,67
9,59
4.29
1.19
11.55
7,69
0,0
13.85
11.95
11.29
6.25
13,24
11.83
0,0
6.61
7.52
6.16
9.34
6.60
27.95
o.o
11.07
14.22
25,60
39.66
11,99
1.74
0.0
4,67
5.51
1.26
0.44
2.17
8.05
0.0
'.U
9,17
3.84
3,96
4,26
2,54
o.o
7,69
13,88
3.06
2.53
4,94
11,29
0,0
15,81
13.05
19.01
10,42
14,01
18.83
0.0
12.64
8,76
16.42
19,75
22.13
2.40
0.0
1.16
1.1°
1.53
«,15
5.70
3.68
6.25
5.02
5.86
7.72
5.16
6.35
6.02
9.06
9.78
10.05
6,70
2.63
10.82
9.52
16,55
15.16
11.32
11,54
10.43
16.35
12.66
8.4t
10,84
6.37
7.00
8.70
10,48
20,45
6,71
13.57
8.53
8,79
15,90
20.82
2.37
1.95
5.18
S.08
1.51
0.98
5.34
6.0J
7.51
11.43
6.98
3.94
2.76
7.08
3,44
8.03
7.70
15.05
5.95
2.24
5.44
17.40
18.58
13.09
17.00
26.62
18.97
14.26
18.43
13.26
7.69
13.35
22.35
32.11
4,86
0.01
1.85
0.54
0.42
0.06
0,09
0.16
6.19
8.44
S.44
7.04
6.95
5.56
6.32
8.74
12.60
11.23
11.59
8,00
4.36
14.20
13.61
16,70
16.60
13.32
13.96
14.46
22.79
12.69
9.44
10.76
' 7.41
9.86
11.00
12.05
12.96
6.69
10.80
8.95
8.63
11.53
9.74
5.35
2.60
6.20
5.67
2.02
1.56
6.09
5.77
9.99
12.25
7.58
4.77
5.54
7.52
4.99
5.80
8.96
16.53
5.23
2.84
7,80
25.04
19.96
12.24
15.69
27.30
25.67
10.15
6.67
4.69
5.11
5.93
13.21
19.41
3.30
0.00
0.90
0.22
0.26
0.06
0.06
0.03
3.11
6.00
4.50
6.79
7.19
5.42
3.51
9,86
13,57
15.06
14.16
10.37
5.02
13.88
24.81.
20.82
20.43 *
20.91
30.86
30.43
25.05
26.45
6.16
7.35
15.63
16.82
24.19
16.03
0.39
4.60
4.61
3.71
1.39
3.86
5.18
7.13
11.11
10.80
7.24
6.20
3,26
8.46
22.48
22.67"
16. IT
9.47
9.69
9.66
13.83
".37
5.«1
13.85
14.96
7.10
3.65
5.93
1.25
6.61
5,«1
5.57
9.38
12.61
4.47
0.13
0.49
1.79
1.43
0.97
1.64
1.66
0.0
0.35
0.03
0.10
0.0
0.02
0.0
0.60
2.26
2.42
1.90
1.19
1.45
5.27
6.02
19,81
16.65
16.21
19,66
18.55
22.53
3.54
10.10
11.76
8.73
6.67
13.98
10.57
0.10
1.97
2.54
2.61
0.75
2.40
1.20
0.02
1.62
1.63
1.56
0.13
0.25
0.27
63.83
24.88
20.09
24.73
30.01
34,75
34. M
0.75
14.51
10.10
5.37
6.04
14.41
6.61
22. 93
19.60
31.75
36.08
30.28
12.12
17.92
0.22
4.37
1.96
1.97
1.04
1.65
2.66
0.01
0.62
0.67
0.75
0.23
0.45
0.20
0.0
0.25
0.01
0.07
0.0
0.01
0,0
-------
COMPARISON OF TRANSFER MATRIX PERCENTAGES BY MODEL
DRY SUL
2
2
2
2
2
2
2
3
3
3
3
3
3
3
4
0
4
a
4
a
a
5
5
5
5
5
5
5
7
7
7
7
7
7
7
8
e
8
8
8
6
8
9
9
10
10
10
10
10
10
10
11
11
11
11
11
11
11
ASTRAP
ENAMAP
RCOM
MOE
AES
HEP
MCA»L
ASTRAP
ENAMAP
RCQM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTKAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
KCDM
MOE
AES
MEP
MCARL
1.86
10.00
6.80
4.99
3.66
5.45
5.92
7.19
0.0
18.12
13.96
5.89
3.18
1.90
0.85
0.0
7.66
7.71
0.0
1.46
0.0
0.0
0.0
1.33
3.01
0.0
0.73
0.0
0.00
0.0
0.86
2.29
0.0
0.0
0.0
1.20
0.0
7.«3
4.68
0.0
1.19
0.0
0.01
0.0
3.14
3.03
0.0
0,0
0.0
85.13
84.82
46.15
41.70
83.43
81.59
32.46
3.73
5.18
7.57
12.81
7.03
5.79
57.54
0.03
0.0
0,93
5.06
0.0
0.61
2.18
0.0
0.0
0.01
0.14
0,0
0.0
0,0
4.64
7.14
11.32
7.62
17,73
13.45
23.55
3.83
5.55
14,27
11.28
15.59
6.21
17,78
1.25
0.96
10.90
6.79
2,91
2.53
5.89
0.11
0.12
2.83
2.65
1.12
0.47
0.66
0.03
0,17
1,96
1.81
1.08
0.54
0,77
0,43
0.81
5.23
2.97
1.33
0.52
1.48
0.08
0.25
4.36
2.49
0.0
0,26
0.73
5.24
15.81
16.60
37,43
21.84
17.70
14,36
84,08
69.04
30,62
22.78
30.97
S3. 14
31.74
0.31
0.14
1.85
4.10
7.43
5.16
3.03
0.0
0,0
0.03
0.07
0.0
0.02
0.0
6.83
14.10
9.30
9,95
10,91
6.35
10.61
4,59
12.34
10.88
9.11
5,86
3.69
11.45
3,64
7.41
16.24
8.93
8.36
15.00
18.24
0.74
1.47
8.31
4.03
2.52
3.37
6.89
0,14
0.67
6.00
3.06
2.45
2.66
7.82
0,75
5.05
4.56
2,67
1,50
0.84
2.49
0,34
1.37
8.29
3.20
1.15
I.u3
2.68
3.54
9,66
6.70
17.49
3.89
3.02
5.67
78.20
45.73
25.19
36.33
57.06
56.26
28.13
1.22
2.00
2.47
4.75
6.29
5.35
6.00
0.0
0.0
0.05
0,09
0.0
0.03
0.02
«.M
7.80
7.30
4.14
5.12
3.22
4,65
1,63
15.50
8,97
5,10
3.53
1,55
8.00
2.07
14.56
13.85
6,16
6.15
4,83
l«,67
1.86
4.38
7.86
3.61
4.06
3.97
9.30
2. "I
4.79
7,78
5,63
8,65
13.03
16.04
0.37
1.86
3.73
2,06
0.0
0.47
2.73
0.70
3.34
7.19
3.40
2.77
1,15
4.32
1.26
4.97
6.40
9.00
2.08
1.59
3.11
10.58
25.95
29.46
29,37
19,66
12.22
IB. 07
77.81
16.53
7.27
31.06
47.18
58.66
16.95
0.00
0,33
0.20
0.«7
0.59
0.30
0,18
2.42
0,0
3.57
4.58
2,14
1.12
4,28
3.85
0.0
5.02
5,94
2.30
0.51
6.86
6,27
0.0
8,65
9,59
6.00
3,76
10,49
9.71
0.0
7,00
T.27
3,96
5.62
5,23
33,55
0,0
11,27
24.63
40.28
42.55
16.62
1,25
0,0
2.19
3,03
1,18
0,38
1.72
5,98
0,0
5,63
7.75
2.70
2.28
3,39
1.98
0.0
3.56
8.31
1.02
0.88
J.9J
9,95
0.0
14,02
14.16
9.59
7.15
12.48
20,25
0,0
36,75
12.48
16.43
19.24
28,05
4,76
0,0
2.34
2.26
14,42
16,52
6.97
2.89
4,74
3,65
4.49
3,51
1,86
4,67
3,77
5.87
6.02
4.95
2,51
1.03
7.64
6.08
12.12
12.09
7.09
7.02
«,71
14.01
9.97
8.93
12.71
4.56
5.95
5.44
14.44
27,19
16.90
23.57
6.86
10.46
19.93
32.44
1.31
1.03
2.93
2.04
0.64
0.62
1.82
3.63
5.59
9.59
3.96
2.95
1.52
4,89
2.09
4.66
4.03
7.59
l.U
0,70
2.97
15.21
17.85
13.57
18,55
16,46
9,09
12.42
27.85
16.76
10.94
37.59
49.37
55.00
4.39
0,01
5.55
0.69
0.29
0.0
0.11
0.11
5.33
7.53
4.35
7.88
4.77
2.78
5.23
5.68
6.27
6.61
7.85
4.46
2.11
10.55
9,41
14,65
14,40
12.16
12.90
9.04
26,60
12.40
11.64
15.24
7.78
10.48
11.16
20.05
20.59
16.24
21.50
14.01
17.11
21.56
12.20
1.88
1.39
3.38
3.05
1.97
0,88
3,60
3.68
6.46
10.81
5.94
4.51
2.96
6.05
3.06
3.30
4.36
11.13
2.27
1.20
4.10
26.26
21.55
14.04
22.23
25.96
19.64
9.30
9.71
5.58
4.93
7.79
15.57
28.60
2.30
0,00
1.17
0.18
0.18
0.0
0.06
0.01
2.59
3.79
3.21
6.72
4.46
2.63
2,62
5.91
7.63
9.79
8.62
4.79
2.15
10.75
23.54
21.56
25.64
24,18
31.46
23.52
29.21
34,63
16.97
9.33
34,26
36.93
47,67
21.35
0.30
4.31
3.56
2.47
1.20
3.84
6.09
3.71
5,96
6.67
3.69
3.66
1.48
6,45
2S.91
32.35
30.82
8,56
8.45
ft. 54
16.24
2.19
2.57
6.44
7.06
2.97
1.26
3.01
0.94
4.45
3.56
3.92
5.71
6,00
3.32
0.06
0.22
0.75
0.49
0.34
0.66
0.97
0,0
0.16
0.01
0.02
0.0
0.02
0.0
0.28
1.26
1.48
0.70
0.25
0.61
2.20
5.39
17,34
14.06
11.07
11.29
12.56
19.21
2.13
9.06
9.98
4,65
4,81
6.82
8,55
0,06
1.76
1.60
1.04
0.35
0.69
0.65
0.01
1,04
0.66
0.44
0.0
0.13
0.15
73,49
31.49
25.13
33.40
44.04
52.13
42.59
0.52
16.76
9.30
2.91
4.27
16.00
6.50
18.02
16,34
36.27
44,93
33.91
8.13
18.35
0.11
2,52
0.98
0.52
0.46
0.59
1.71
0.00
0.29
0.33
0.15
0.0
0.14
0.11
0.0
0.14
0.00
0,01
0.0
0.0
0.0
-------
COMPARISON OF TRANSFER MATRIX PERCENTAGES BY MODEL
HET 3UL
1
1
t
1
1
1
1
2
2
2
2
2
2
2
3
3
3
3
3
3
3
4
o
a
4
a
a
a
S
S
5
5
5
5
S
T
T
T
r
7
7
7
e
e
e
8
6
e
10
10
10
10
10
10
10
u
11
u
it
u
u
11
ASTRAP
ENAMAP
RCDM
MOE
AES
HEP
KCAHL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCAKL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
HEP
MCAHU
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCAHL
ASTRAP
ENAMAP
hCD*
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARt
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARt
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
NEP
«CA«t
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
HCARt
3.13
4,93
6.80
S.Ott
10.89
7,66
7.30
13.21
0.0
16.12
11.85
8,77
8.78
3.90
3.10
0.0
7.66
8.95
0.0
1.61
0.0
0.0
0.0
1.33
3.64
0.0
0.80
0.0
0.00
0.00
0.86
2.96
0.0
0.0
0.0
0.19
0.0
7.03
6.08
0.0
1.32
0.0
0.00
0.0
3.10
4.47
0.0
1.30
0.0
71.74
68.73
46.15
J6.8S
69,88
69.05
00.02
u.se
6.34
7.57
11,68
10.46
7,05
17.29
0.04
0.0
0.93
5,06
0.0
2.02
1.09
0.0
0.0
0.01
0.21
0.0
0.0
0.0
8,10
14,93
11.32
7.27
15.46
12.98
15.23
10,89.
7.00
10,27
12.32
26.00
10.75
22.08
4.97
0,27
10.90
7.76
0,65
0.31
7.17
1.12
0.00
2.83
3.11
2.80
1.23
1.30
0.18
0.20
1.98
2.25
1.81
0.87
0.51
2.90
0,16
5,23
3.91
2.22
1,26
2,93
0,66
0,0
0.38
3,20
0.0
0.50
0.73
11.56
17.36
16.60
35.39
22.05
19,52
16.38
58,30
S9.65
30,62
20.43
23.25
04.16
27,85
1.30
0,00
1.65
«.21
1.55
4.36
J.37
0.0
0.0
0,03
0.11
0.0
o.oe
0.0
12.07
22.10
9.30
9.37
12.20
6,84
11.02
11,66
29.04
10,68
10,18
13.95
6.92
16,23
7.99
0.66
18.24
9.58
20.81
19,04
17.53
2.56
0.0
8,31
0.33
7.10
6.12
5.30
0.75
0.95
6,00
3,69
3.16
7.64
S.tl
3.45
1.14
0.56
3,«7
6.50
1.51
0.35
2.18
0.0
8.29
3.ea
2.98
2.65
3,67
7.27
2.10
6.70
16.55
5.61
0,58
8.92
OS. 56
03.31
25.19
32,10
20.95
36.03
21.03
2.86
0.06
2,«7
1.77
2.72
4.J9
6.22
0,0
0.0
0,05
0,12
0.0
0.06
0.00
0,38
10.06
7.30
0,07
6.93
1.79
6.06
9.10
10,46
8.97
6,51
6,70
2.56
11.77
10.78
16.66
13.85
7.32
'.17
6,70
17,81
0.35
6.13
7,66
4.13
6,73
6.56
9.15
9.18
7.57
7.76
5.69
10.92
20.56
10.69
1.35
0.87
3.73
2.92
1.10
0.72
0.86
3.55
6.79
7.19
0.25
5.25
2.10
6.11
2.65
3.10
6.00
11.02
1.96
1.09
5.03
16.71
23.77
29.46
26.59
22.60
13,96
15.70
37,92
6,42
7.27
26.01
23.97
03.26
12.63
0.02
0.10
C.JO
0,«9
0.56
O.Sb
0.18
0.21
0.0
3.57
0.79
3.52
2,06
5.36
7,98
0.0
5.02
7.20
3,78
1.65
11.50
15,66
o.o
8.65
10.01
7.04
6.06
13.19
16.06
0.0
7,00
7.34
0,66
7.55
6.57
20,65
0,0
11.27
21.00
37,63
05,41
11, 94
2.20
0.0
2.19
3.92
t.93
0,62
2,16
12.96
0.0
5.63
8.20
6.66
3.06
0.27
3.65
0.0
3.56
10,30
1.67
I. 01
0,92
6,49
0,0
10.02
13.72
13.51
7.01
13,95
6.53
0,0
36,75
11.16
13.50
16,03
23.10
3.55
0.0
2.30
1.66
5.69
7,14
2,96
4.71
3.62
3.85
4,76
3.01
1.91
6,00
10.22
7.31
6,02
.6.21
3.93
2.95
11.32
11.14
14.33
12,09
8.07
10.06
7.03
16.09
13.00
11.20
12.71
4,94
12.17
9.32
10.96
22,99
13.00
23.57
6.65
17.70
29.19
17,96
5,76
1.06
2.93
2.61
2.01
0.74
3.50
9.10
9.73
9.59
0.66
10.15
0.01
7.01
3.69
3.21
0.03
9.02
2.06
1.26
5.69
10.51
11.48
13.57
17.60
10.96
13,25
10.90
8,65
18.60
10,94
32.30
19,09
29,65
5.10
0,02
5.56
0,69
0.32
0,0
0,28
0,16
7.17
0.76
0.35
7.60
0.70
3.07
6.57
11.52
4,02
6.81
6.90
0.86
3.05
10.76
16.22
9.02
14.00
12.46
16,57
10.11
22.72
9.71
20.34
IS. 20
7.64
13.75
13.72
12.05
IS. 12
20.04
21.50
12.60
16.81
23.00
7.93
7.12
1.06
3.36
3.60
0.27
1.06
6.33
7.57
14.90
10.81
6.01
11.02
0.87
7.62
0.06
2.90
4.36
12.72
3.07
2.00
6.11
13.09
12.06
10.00
20.29
16.56
22.16
10.23
8.00
5.69
0.93
7.26
7.90
16,60
3.03
0,00
3.70
0.16
0.21
0.0
0.10
0.03
1.99
2.10
3.21
6.63
3.56
2.83
3.67
6.16
4.83
9.79
9.49
7.03
2.34
14.73
21.32
28.70
25.64
23.36
28.05
24.63
25.70
33.03
25.30
9.33
31.60
23.55
40.58
10,30
0.94
7.55
3.58
2.67
1.01
0,09
5.25
5.79
3.75
6.87
0.29
7.26
l.»6
P. 97
26,36
24.80
30.82
8.62
17.05
12.75
14.34
3.22
1.38
6.40
8,43
5.97
1.16
6.29
0.91
1.39
3.56
«.17
0.83
B.2S
4.74
0.26
0.06 *
0.75
0.66
0,06
0,80
1.76
0.0
0.09
0.01
0.04
0.0
0.06
0,0
0.20
2.15
1.08
0.96
0.00
1.02
3.02
3.02
4.90
10.06
12.05
9,76
11.35
23.62
1.94
l.M
9.96
5.64
2.91
7.94
11.56
0.14
0.95
1.60
1.38
0.0
2,I»
1.26
0.04
0.27
0.66
0.69
0.0
0.15
0.29
52.90
25.46
25.13
31.09
29.35
45, n
30,91
o.do
17.63
9.30
3.02
4.59
16. bl
6.93
00.41
45.37
36.27
43.21"
52, 9*
10, 81"
16,79
0,09
1.30
0.96
0,60
0,0
0,91
3.00
0.01
0.11
0,33
0.28
0.0
0,0
0.21
0,0
0,05
0.00
0,02
0.0
0.0
0.0
-------
COMPARISON OF TRANSFER MATRIX PERCENTAGES BY MODEL
TOT SUL
1
2
2
2
2
2
2
2
a
5
5
5
5
5
5
S
6
6
7
7
7
7
7
7
7
8
8
8
8
8
8
8
10
10
10
10
10
10
10
11
11
11
11
11
11
11
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCO"
MOE
AES
MEP
MCAHL
ASTRAP
ENAMAP
HCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
NOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCOM
HOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCD*
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
HCDN
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
HCOM
MOE
AES
MEP
MCARL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
hCARL
ASTRAP
ENAMAP
HCDM
MOE
AES
HEP
MCARL
2.88
6.57
6,80
5.01
6. 56
6.48
6.19
12.01
0.0
18.12
14,42
7,05
S.62
a. 96
2.65
0.0
7.66
8.34
0.0
1.52
1.14
0.0
0.0
1.33
3.33
0.0
0.76
0.0
0.00
0.00
0,86
2.63
0.0
n.aj
0.0
3.59
0.0
7.43
5.49
0.0
1.25
0.0
0.00
0.0
3.14
3.95
0.0
0.62
0.0
74,42
85.93
06.15
39.26
77.98
75,31
33.93
4.41
5.51
7.57
12,34
B. 41
6.55
51.88
0,03
0.0
0.93
5.06
0.0
1.27
1.90
0.0
0.0
0.01
o.ib
0.0
0.0
0.0
6,61
9.41
11.32
7,47
16.50
13.13
20.87
7.84
6.09
14.27
11.73
21.27
8.32
19,37
3.36
0.76
10.90
7.21
3.97
3.43
6.02
0.66
0.09
2.83
2.85
2.03
0.65
0.75
0,12
0,16
1,96
2.00
1.06
0.71
0.68
1,83
0.63
5.23
3.3d
1.82
0.89
1.97
0.41
0.18
4,38
2.82
0.0
0.50
0,97
8.84
16.26
16,60
36,55
21.95
18.86
15.72
69.43
66.31
30.62
21.76
26.76
48.51
30.25
0,87
0.10
1.85
«. 15
4.?2
4.75
3.40
0.0
0.0
0.03
0.09
0.0
0.01
0.0
10.21
15.95
9.30
9.71
11.47
7.39
10,79
8,94
16,30
10.86
9.56
9.38
5.04
13.33
6.24
5.89
16.24
9.21
J3.79
16,86
17,66
1.83
1.13
8.31
4.16
«. Si
«.52
6.46
0.51
0.89
6.00
3.56
2.76
4.75
6.92
2.37
4.14
4.56
3.01
3.68
1.12
3.13
l.«4
1.05
8,29
3.47
1.94
1.94
2.95
5.77
7.92
6.70
17,94
4,64
3.67
6.46
60, U8
45.17
25.19
34.54
43.09
49.60
25.94
2.22
1.55
2.17
4.76
a. 73
4.66
6.10
0,0
0.0
0.05
0,10
0,0
0,05
0.04
3.31
8,73
7.30
4.28
6,05
2.01
5.23
6.50
15.06
8,97
5.71
5,16
2.05
».»7
7.74
15.42
13.85
6.67
7.70
5.77
15,76
3.46
5,92
7.66
3.84
5.43
5.25
9.20
6.62
5.93
7.78
5.75
11.97
16.66
14,04
1.01
1,46
3.73
2.44
0.59
0.59
3.69
2.56
1.75
7.19
3.77
4.04
1.75
4.98
2.16
4.22
6.40
9.88
2.03
1.35
4.21
14.57
25.05
29.46
28.16
21.19
13.07
17.08
51.82
13.20
7.27
29.03
35.26
51,07
16.45
0.01
0,24
0.20
0,«7
0.56
0.41
0.19
3.41
0,0
3,57
4,68
2.66
1.47
5.51
6.14
o.o
5.02
6.52
2.86
0.95
T.57
11.48
0.0
6.65
9,95
6.39
4.63
12.73
13.22
0.0
7.00
7.30
4.31
6.34
5.77
26.41
0.0
11.27
23.01
39.35
43.54
14.41
1.60
0.0
2.19
3.«3
1.46
0.71
2.64
9.84
0.0
5.63
7.97
4.20
2.57
3,75
2,90
0,0
3,56
9.20
1.26
1.06
4.32
8,04
0,0
14.02
13,97
11,07
7,08
12.24
12.66
o.o
36.75
11.89
15,32
16,73
25,63
4.10
0,0
2.34
2.09
11.12
12,90
5.23
4,09
4,13
3,65
4.60
3.46
1.85
5.40
6.03
6.65
6,02
5.46
3.14
1.90
6.89
9.42
13.32
12.09
7.50
10,15
5.95
14,83
11.96
10.16
12.71
4.72
8.71
7.21
13.22
24.41
15.03
23.57
8,79
13.69
24.15
27.31
4.25
1.26
2.93
2.36
1.43
0.67
2.39
7.24
7.»3
9.59
4.26
6.15
2.66
5.75
3.28
3.87
4.03
8.36
1.54
0,96
4.29
12.11
14.41
13.57
16.24
15,80
10,99
13.26
15.17
17.75
10.94
35.36
35,9?
43,47
4,54
0.02
5.57
0,69
0.30
0,0
0.19
0.12
6.69
5.94
4,35
7.76
4,75
2.92
5.64
9.99
5.61
6.81
6.31
4.66
2.58
12.01
14.44
11.71
14.40
12.29
14.66
9.56
25,46
10.41
16.66
15.24
7,72
12.05
12.37
17.44
16,55
16,67
21.50
13.41
16.96
22.32
10.75
5.76
1.43
3.38
3.39
3.07
1.06
4.44
6.56
12.20
10.81
6.14
7.63
3.91
6.71
4.10
3,09
4.36
11.61
2,65
1.60
5.34
17.05
16.07
14.04
21.40
21.45
20,89
9.57
6.45
5.76
4,93
7.57
11,91
22.66
2.58
0.00
2.66
o.ia
0.19
o.o
0.10
0.03
2.22
2.74
3.21
6.66
4.09
2.71
2.95
6.07
5.89
9.79
8.97
5.89
2.23
11.92
22,14
26.02
25.64
23.86
30.21
24.02
28.14
33,70
22.19
9.33
33.22
31.38
44.85
19.22
0.70
6.33
3.58
2.55
1.29
4.11
5.76
5.02
a.S*
6,87
3.93
5.17
1.63
7.19
26.19
27.64
30.62
8.58
12.02
10.21
15.65
2.84
1.63
6.44
7.61
4.22
1.24
4.22
0.92
2.54
3.56
4.02
5.35
8.11
3.74
0.20
0.12
0.75
0.56
0.40
0.65
1.21
0.0
0.13
0.01
0.03
0.0
0.04
0.01
0.23
1.72
1.48
0.60
0,31
0.73
2.66
4,19
10,96
14.06
11.47
10.71
12.28
20.59
2.01
5.35
9.96
5.17
4.09
7.14
9.35
0.11
1.34
1.60
1.18
0,21
1.27
0,76
0.03
0,65
0.86
0,54
0,0
0,13
0.29
60.94
28.40
25.13
32.62
36,79
50.03"
36.54
0.72
17,21
9.30
3.11
4.39
17,58
6,74
31.67
32.20
36.27
44,23
41.21
10,06
18.71
0,09
1.90
0.96
0.65
0.30
0.66
2.14
0,01
0,20
0.33
0.21
0.0
0.10
0.21
0.0
0.09
0.00
0.02
0.0
0.0
0.0
-------
B-7
Means and Standard Deviations of Percentage Contributions
Over All Models for 11 Source Regions and 9 Receptor Areas
-------
MEANS OF ALL 7 MODELS FOR AMB 802
i
2
5
ft
S
6
7
e
9
10
ii
4,66
6.75
2.31
0.56
0.46
1.62
0.79
64.50
16.63
1.47
0.02
10.32
8.42
3.60
0.97
0.82
1.40
1.00
16.00
54,70
2.76
0.01
9.04
6.72
9.94
3.42
2.99
1.64
2.23
5.90
54.05
3.84
0.03
4.28
4.95
7.61
4.39
7.39
1.20
2.54
3,25
20.96
43.14
0.27
2.52
3.17
5.72
4.79
23,06
1.07
3.29
2.42
9.02
19,83
10.80
3,20
3,38
6,94
6,84
25,87
1,01
3,59
2,46
13,90
31,28
1.53
5.09
5.32
11.99
11.40
23.55
1.61
5,10
3,53
20.56
11.58
0.29
3.39
5.64
23.54
37.46
2.56
3.23
17.30
2.91
3,54
0.40
0.02
0.70
11,49
5,42
0,72
0.27
49.61
6.01
23,01
0,67
0,09
0,01
STANDARD DEVIATION VALUES FOR AMB 302
1
2
3
4
5
fr
7
8
9
10
11
1,96
6,44
3,26
1.11
0.81
2,41
1,38
28,23
27,78
1.82
0.05
5,32
4,96
3.41
1.10
0.75
1.42
1.37
11.31
25,40
2,46
0,03
2,94
2.51
4.90
2,67
2.27
1.15
2.59
5.18
18.09
1.97
0.03
2.23
3.25
4.27
2.19
3,39
0.92
1.95
2.74
9,99
25,12
0,16
1.61
2.44
3.38
2.69
15,73
0,92
2.46
2.62
4.72
14.05
9.39
0,89
1.23
2.35
3.20
18.40
0.69
2.51
2.24
4.46
21.10
3.49
1.63
1.66
3.62
2.99
7.82
0.89
2.87
3,35
7.25
9.48
0.54
1.70
2.31
4.79
17.23
1.38
1,46
12,93
2.17
1.80
0,24
0.02
0.43
3.70
2.48
0.53
0.27
19.95
7,42
15.62
0.56
0.05
0.02
-------
MEANS OF ALL 7 MODELS FOR AMB 800
1
2
3
4
5
6
7
a
9
10
11
6.97
9.65
S.33
0.98
0.90
3,08
1.51
55.64
1«.«7
3.«3
0.04
9.68
15.39
5.98
1.59
1.40
3.29
1.90
23.46
33.03
4.03
0.04
10.37
12.82
13.40
3.99
2.97
4.56
3.58
11.68
31.86
<».72
0.05
6.34
9.71
11,78
5.97
7.50
2.97
4.49
6.95
21.30
22.74
0.27
3.81
5.89
9.21
7.18
18.64
2.26
5.49
4.95
11.94
14.36
1.98
5,72
7.87
12.98
9.21
13,82
2.89
6.50
6.55
17,99
16.01
0,45
6.57
10.10
16.23
10.46
9.93
3.93
7.34
7.45
19.44
8.33
0.22
5.22
11,71
24,76
16.67
3,39
7.75
14,85
7,90
6.53
1,16
0,07
1,87
17.38
9.62
1.65
0.79
33.27
8.54
24.38
2.01
0.45
O.OS
STANDARD DEVIATION VALUES FOR AMB 804
1
2
3
4
5
6
7
a
9
10
11
2.68
7,14
4,74
1.63
1.37
«.35
2.57
20.30
15.21
5.55
0.10
3.54
5.27
4.51
1.64
1.33
2,96
2.74
7.31
19.61
3.45
0.07
2.49
3.72
«.37
2.07
2.07
2,92
3.29
5.31
15.51
2.52
0.07
2.07
5.67
5.47
1.88
2.94
2.42
2.85
4.57
5.32
18.07
0,17
2.21
4.48
4.91
3.70
13,20
2.08
3.42
4,60
6.00
7.82
1.50
1.27
2.91
2.95
2.24
5,43
1.71
2.78
4.32
4.38
•».25
0.65
1.03
3.31
3.49
1.76
2.02
2.01
3.01
4.47
6.89
5.83
0.32
1.57
3,54
4,45
7,24
1,80
2,71
5,84
4,60
3.70
0,65
0.13
0.86
4.62
3.25
0.98
0,78
14.52
4.96
a. 59
1.33
0.32
0.09
END OF JOB
-------
MEANS OF ALL 7 MODELS FOR DRY SUL
1
2
3
a
s
6-
7
8
9
10
it
5.52
7.18
2.52
0.72
0.45
2,10
0,9«
65,04
14,20
1.26
0.02
12.21
10.64
4.46
!•!«
0.91
1.82
1.17
18.43
46,05
3.15
0,02
9.72
8.27
11.40
3.90
3.3«
2.55
2.64
7.14
46,99
4,01
0.03
4.65
6,33
8,90
5.01
8,36
1.60
3.27
4,06
20.76
36.78
0,30
2.59
3.50
6.39
5.54
24.13
1.39
3.96
2.81
9.62
19,03
6.76
3.74
4,54
9.02
8,86
19.91
1.48
4.59
3.31
14,74
28,84
0,97
5,41
6.53
14.19
12.68
17.60
2.31
6.06
4.20
20.14
10.64
0.23
3.72
7.09
25.59
28,77
3.11
4.55
18.69
3,65
4,27
0.53
0.03
0,97
12.99
6.60
0,91
0.37
43.27
8.32
25.42
0.99
0.15
0.02
STANDARD DEVIATION VALUES FOR DRY SUL
1
2
3
4
5
6
7
8-
*
10
11
2,55
6.62
3.57
1.13
0.87
2.92
1.60
23.70
19.31
1,85
0,05
6,65
5,49
3,59
1.15
0.76
1.73
1.66
9,78
23.23
2.65
0.03
2.62
3.53
5.74
2.78
2.73
1.71
2.67
5.10
18.92
2.07
0.03
2.40
4,97
5.29
2.61
4.78
1.38
2,15
2,87
7,77
25,51
0,20
1.68
2.66
3.65
3.05
15,77
1.04
2.63
2.81
4.95
11.61
6.37
1.09
2.26
3.62
3.78
8.59
0.84
2.57
2.38
3.32
19.35
2,04
1.78
2.75
5.91
3.94
3.74
1,0 tt
2.77
3.24
6.59
8.98
0.42
1,50
3,01
3,52
13,31
1.96
1.94
10.82
2,20
2.19
0,34
0,07
0.71
4,53
2.82
0.62
0,42
16,12
6,78
13,07
0.85
0.13
0.05
-------
MEANS OF ALL, r MODELS FOR NET SUL
1
f
5
4
5
6
7
6
9
10
It
6.54
9.66
3.05
0.62
0.55
2.72
1.27
60.35
13.65
1.36
0.03
12.19
14,07
5.75
1.77
1.12
2.66
1.36
20.13
37.75
2.36
0.02
12.19
14.21
13.49
4.82
3.90
3.57
3.40
7.66
33.37
3.33
0,04
5.66
6.59
11.76
6.70
10.95
2.23
5.04
4.47
21.26
22.84
0.30
3.36
5.31
«.72
7.06
21.16
1.87
5.83
3.64
9.81
15.59
3.S7
4.10
6,65
11.94
10.62
19.07
2.80
7,81
4,23
13,79
17,77
1.01
5,47
7.71
14,56
13.21
16.77
3.92
9.11
5.38
15.50
7.75
0.61
3.46
7.62
25.44
25.40
3.70-
5.54
19,25
4.70
3,96
0.69
0,03
1,36
11.31
5,97
1,07
0.33
34,32
8,47
35,98
1.02
0.13
0.01
STANDARD DEVIATION VALUES FOR NET SUL
1
2
3
4
5
6
7
6
9
10
11
2.49
6.31
3.79
1.35
1.11
3.16
1.83
19,45
15.04
1.82
0.08
3.41
6.80
3.32
1.16
0.88
1.66
1.73
7.45
16.34
1.64
0,04
4.61
7.33
7.45
2.83
2.55
1.84
2.52
5.25
10.28
1.97
0.05
2.63
3,86
4,43
1.89
5.14
1.62
1.83
3.41
5.90
14.22
0.23
1.82
3.94
5.12
4.76
15,80
1.26
4.11
3.37
5.46
11.97
2.40
1.40
3.07
3.34
2.80
6.85
1.61
2.53
2,70
2.42
10.38
2.03
1.67
4.28
«.5*
4.09
s.sr
2.26
3.4*
3.76
4.40
4.33
1.3*
1,56
4,01
2.63
10.90
2.30
2.41
6,16
2.79
2,45
0.55
0,04
1.11
6.65
3.97
0.78
0,33
10.54
6.M
14,10
i.o
-------
MEANS OF ALL 7 MODELS FOR TOT 8UL
t
2
3
n
5
6
7
8
9
to
11
6.07
6.91
3.04
0,77
0.56
2.54
1.10
61.85
13.81
1.31
0.03
12.19
12.70
S.09
1.44
1.02
2.25
1.32
19.26
41.95
2.76
0.02
10.69
10.49
12.59
4.42
3.63
3.14
3.01
7.59
40.60
3.81
0.03
5.27
7.52
10.42
5.85
9,65
1.93
4.15
4.32
21.23
29.16
0.30
3.04
4.15
7.69
6.28
22.57
1.76
4.65
3.19
9,49
17,28
5.40
3.91
5.73
10.47
9.82
19.56
2.18
6,21
3,76
14,05
23.31
0.99
5.44
7.17
14.65
13.13
17.17
3.22
7,74
4.71
17.21
9.13
0.45
3.51
7.25
25,72
27,70
3,47
4,91
18,73
4.05
4.03
0,56
0.03
1.13
12.04
6.16
0.93
0.36
39.21
8.44
30.62
0.96
0.15
0.02
STANDARD DEVIATION VALUES FOR TOT 8UL
1
2
3
4
5
6
7
8
9 -
10
It
1.76
6.23
3.51
1.24
0.97
3,02
1.70
21.27
16.96
1.61
0.07
5.11
5,68
3,29
1.12
0.80
1.56
1.65
8.60
19.56
1.82
0.03
2.66
3,56
5.42
2.48
2,44
1.16
2.47
«.77
12.88
1.71
0.04
2.31
4.12
4.39
2.06
4.36
1,37
1.77
3.00
6.56
17.92
0.20
1.87
2.92
4,40.
3,94
15,49
1,19
3.31
3.05
4.96
11.58
4.63
1.10
2. SO
3,17
3.13
6,96
1,20
2.30
2.40
2,41
14,60
2,03
1.59
3.21
5.12
3.51
4.15
1.63
2.86
3.36
4.45
6.66
0.96
1.51
3,20
2.75
11.65
2.13
1.87
9.23
2.3*
2.26
0.38
0,04
0.87
4.87
2.86
0.58
0.33
12.57
6.69
12.23
0,76
0.12
0.03
-------
B-8
Comparison of Transfer Matrix Values by Model in Absolute,
Percentage/ and Unit Form for All 9 Receptor Areas in Each
of 11 Source Regions
-------
TRANSFER MATRIX DISPLAYS
SOURCE HEGIONi 1
SCtNAKIOl
ABSOLUTE
i
AMB S02> AMB 804'
REC
2
2
2
2
2
2
2
3
4
4
4
4
4
4
4
5
5
5
5
5
5
6
6
7
7
7
7
7
7
7
6
6
MODEL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCAHLO
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCAHLO
ASTHAP
ENAMAP
RCUM
MOE
AES
MEP
MCAHLO
ASTRAP
ENAMAP
RCOM
MOE
AE8
MEP
MCARLO
ASTHAP
ENAMAP
RCOM
MOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
nOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
HCAHLO
ASTRAP
ENAMAP
A
0,01
0,56
0.50
0,06
0,16
0,09
0.09
0.61
4.26
1,60
0,70
2,75
1,13
1.64
1.07
11.79
2.69
1.60
4.29
1.47
1.43
0,14
3.73
1.28
• 0,46
0,77
0,26
0,50
0.11
0.0
0,38
0.52
0.37
0.06
0.10
0.34
2.33
0.51
0.83
1.01
0,31
0.69
0.61
5.16
'0.95
1.37
1,34
'0.40
'1.04
1.06
•6.34
A
' i
0,01
0.75
0.45
0.08
0,10
0.15
0.06
0.33
3.33
0.96
0.29
0.43
1.23
0.49
0.73
6,90
1.31
0.52
1.77
1.63
0.59
0.17
6,31
1.01
0.29
0,53
0,63
0.31
0.08
0.0
0.59
0.34
0.44
0.24
0,06
0,26
3.71
0.69
0.41
0.'77
0.73
0.31
0.45
5,76
0.90
0.54
0.90
'0.83
0.36
0.44
6.67
1
DKY S
B
0.01
oi.ie
Oi,67
0.06
0,10
0,11
0.10
0.61
0.79
2.10
0.57
2.17
1.20
1.47
1.21
2.64
3.07
1.28
3.55
1.22
1.08
0.17
1.42
1.64
0,36
0,69
0.22
0.39
0.09
0.0
0,62
0.42
0.30
O.P7
P. 06
P. 31
P. 7 8
P. 79
0.67
0.69
0.28
0.43
0.59
1.48
1.29
1.11
1.16
.0,36
0.67
0,79
'.»•*>
i 1
i i
MET S TOTAL 3
B'
0.05
0.03
0.29
0.07
0.20
0.13
0.06
1 ,"1
0.66
0.90
0,42
2.27
1.19
0.46
3.30
1.34
1.32
0.89
3.06
1.22
0.59
1.05
1.27
0,70
0.31
P'!l7
0.32
0.19
0.0
0.27
0.36
0,30
P. 06
P. 06
P. 99
0.70
0.34
0.52
0.69
0.24
0,30
'2.23
1.29
0.55
0,60
,1 .09
0.40
0,38
1.03
,1.50
Bi
0,06
0.21
0,95
0.13
0.30
0.24
0,15
2.02
1'.47
3.00
0.96
4,44
2.38
1.96
4.52
4.19
4.39
2.17
6.61
2.44
1.67
1.22
2.69
2.34
0.69
1.66
0.39
0,72
0.26
0.0
0.69
q.78
0.59
0.14
0,13
1.3P
1.49
1.13
1.19
1.56
0.51
P. '73
2.62
2,78
1.64
1.9P
2.27
0.77
1,06
.1 ,8?
3.13
I '
1 • ., i
PERCENTAGE
AM8 SG2 AHB S04
! C
' 1
2.0B<
7.13
6.95
4,96
4.56
4.63
2.42
2.21
7.22
12.32
7.65
18.52
10.02
14,31
4,59
13,50
9.84
10.01
10.61
6.49
8,04
0,95
6,43
7,36
4,10
4.75
2,16
4,23
2,90
o.o
, 2.82
4.56
2.22
1.03
4.09
2.83
3.67
3.34
4.46
3.27
1.54
3.31
S.1'4
7,P6
3.97
7.91
t 4,51
i 2,56
4,48
. 2,47
3.2P
C
2,72
10,63
6.50
5.11
9.54
6.97
7.13
6.06
9.96
8.66
6.59
b.54
14.02
15.31
9.58
12,90
7.59
7.96
14.33
9.49
10.73
2.67
6.07
7.16
5.25
9,02
6.40
5.«2
2.55
0.0
5.50
5.20
5.71
2.31
5,40
3.68
6.25
5.02
5.66
7.72
?•»'*
6.35
6.19
6.44
5.44
7.04
, P. 95
5.56
6,32.
3. SI
' 6.00
DHY 5
C
1,86
10.00
6,60
4,99
3,66
5.45
5.92
4,64
7.14
11.32
7,62
17.73
13.45
23.55
6.63
14.10
9.30
9.95
10.91
6.35
10.61
1.31
7,80
7,30
4,14
5,12
2.22
4.65
2.42
0.0
3.57
4.58
2.14
1.12
4.28
2.69
4.74
3.65
4.49
3,51
1.66
4.87
5.33
7.53
'4.35
, 7.66
4,77
2,7*
5,23
2,59
3,79
UNIT
HET S TOTAL S AMB 502 AMU 804
C
3.13
4.93
6.60
5.04
10.69
7.66
7.30
6.10
14.93
11.32
7.27
15.46
12.96
15.23
12.47
22.10
9.30
9.37
12.20
6,64
11.02
4.38
10.06
7.30
4.47
6.93
1.79
6.06
4.21
0.0
3.57
4.79
3.52
2.06
5.3,8
4.71
3.62
3.85
4.76
3.41
l.?l
6.44
, 7.17
1 4.78
' 4.35
7.60
' 4.74
, 3.07
16.57
1.99
2.'lO
C
2.66
8.57
6.80
5.01
.56
,48
,19
.61
.41
11.32
7,47
16.50
13.13
20.87
10.21
15.95
9.30
9.71
11.47
7.39
IP, 79
3.31
8.73
7.30
4,26
6,05
2,01
5.23
3.41
0.0
3.57
4,. 68
2.66
1.47
5.51
4.09
4.13
3.85
4.6P
3.46
1.65
S.'40
6.69
5.94
4.35
, 7.76
4.75
2.92
5,6a
2,22
2.74
A/D
0.01
0,61
0,52
0,06
0,16
0,09
0.09
0,64
4,45
1.67
0,73
2.67
1,18
1.71
l.H
12,26
2.80
1.66
4,47
1.53
1.49
0,14
3,88
1.33
0,4ft
0,60
0.27
0.52
0.12
o.o
0.40
0.54
0.36
0.08
0,1,0
0.36
2.43
0,54
0,66
1.05
0.32
0,72
0,64
5.39
0.99
1 .42
,1.40
.0.42
1,06
1,11
6,60
A/0
0,01
0.78
0.47
0.08
0,10
0,16
0,06
0,34
3,47
1.00
0.30
0.45
1.28
0.51
0.76
9.27
1.36
0,54
1.84
1.91
0.61
0.16
6,58
1,05
0,30
0.55
0.66
0.32
0.08
o.o
0.61
0.35
0.46
0,25
0,06
0,27
3,86
9.72
0.43
6.60
0.76
6,32
.0.46
6.00
0.94
0.56
,6.94
0,86
0.40
Pe06
7,15
DKY 3
B/D
0.01
0,16
0.69
0.07
0,10
0.11
P. 10
0,64
P. 62
2.19
0.59
2.26
1.25
1.53
1.27
2.96
3.2P
1.34
3.70
1.27
1.13
0.18
1.47
1.71
0.39
0.72
0.23
0.41
0.09
0.0
P. 65
P. 44
P. 31
P.P7
P. 06
0,32
0.82
0.62
0.7P
0,92
0.29
0.45
0.61
1.54
1.34
1.15
1.23
0.38
0.70
0.82
1,69
i
i
NET 8 TOTAL 8
B/D
0,06
0.04
0.30
0.07
0.21
0.14
P. 06
1.47
0.71
0.94
0.43
2.36
1.24
0,50
3.44
1.40
1.37
0,92
3.19
1.27
P. 61
1.10
1.32
P.73
P. 33
1.03
0,18
0.33
P. 20
0.0
0.28
0.37
0.31
0.08
0,06
1.03
0,73
P. 35
P. 54
0.72
P. 25
6.31
2.33
1.35
P. 57
0.63
1.13
6.42
0,40
1.08
1,56
B/D
O.P7
P. 22
0,99
P. 13
0,31
P. 25
0,16
2.11
1.53
3,12
1,02
4,62
2.46
2.04
4.71
fl.36
4.58
2.26
6.89
2.54
1.74
1.27
2,80
2,44
0.72
1,75
P. 41
P. 75
P. 29
P.O
0,93
0,82
P. 62
P. 15
P. 14
,35
.55
.18
.24
.64
P. 53
P. 76
2.94
2.69
1.92
1,98
2.36
0,60
1.10
1.90
3.26
-------
d RCDH
6 HOC
6 AtS
d HEP
e MCARLO
9 ASTRAP
9 ENAMAP
9 KCDM
9 MOE
9 AES
9 HEP
9 MCARLO
1.2-4
3.03
3.60
1.06
0,61
0.09
0.98
0.27
0.15
0.16
0.15
0,01
O.B9
0.77
1.51
1.56
0.25
0.06
2.37
0,34
0.13
0.24
0.46
0,19
1.55
2,«3
2,96
0.66
0.41
O.Ob
0.43
U.41
0.12
0.10
0.15
0,24
0,66
1.60
1.60
0,63
0,26
0,07
0,76
P.17
0,12
0,10
0.11
0,19
2.21
4.02
4.64
1.50
0.66
0.13
1.19
0.56
0.24
0.20
0.26
0.44
2.91
6.71
4,43
2.45
1.59
0.24
0.70
1.19
0.67
0.33
0.43
1.36
4.50
6.79
7.19
S.U2
3.51
0.60
2.26
2.42
1.90
1.19
l.«5
3.27
3.21
6,72
«.46
2,63
2.62
0.26
1.26
1,4*
0.70
0.25
0.61
2,20
3.21
6,61
3.56
2,»3
3.«7
0,20
2.15
1.46
0,96
0.40
1.02
3.42
3.21
6.66
4.09
2.71
2.95
0.23
1.72
1.46
0,60
0.31
0.73
2.66
1.2"
3.15
3.75
1.13
0.64
0.10
1.03
0,29
0,15
0,16
0.16
0.43
0.93
0,81
1,57
1.63
0.26
0.06
2.47
0.35
0.13
0,25
0,46
0,20
1,61
2.53
3. OB
0.90
0.43
0.07
0,44
0.42
0,13
0.10
0.16
0,25
0,69
1,66
1.75
0,66
0,27
0.07
0.79
o.ie
0.12
0.10
0.11
0,20
2.30
4.19
4,63
1.56
0,69
0,14
1.24
0.61
0.25
0,21
0.27
0,46
A — UG/M**3
B — KG/HA/VR
C — X
0 — TG 8/YR
-------
TKAUSFEH MATRIX OISPLAY8
SOURTE REGION!
SCENARIO!
ABSOLUTE
I
AMB 502 AH8 SOU
REC
1
1
1
1
1
1
1
Z
2
2
2
2
2
2
3
3
3
3
3
3
3
4
4
4
4
4
4
4
5
S
5
5
5
5
5
6
6
6
6
6
6
6
7
7
7
7
7
7
7
e
8
MODEL
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARLO
ASTHAP
ENAMAP
KCDM
MOE
AES
HEP
MCARLO
ASTRAP
ENAMAP
RCDM
HOE
AES
MEP
MCARLO
ASTRAP
E^AMAP
RCOM
M0£
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
HOE
AES
MEP
CCARLO
ASTRAP
ENAMAP
KCOM
MOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
KCOM
MOE
AES
hEP
KARLO
ASTRAP
ENAMAP
A
0.03
0.0
1.22
0.21
0,22
0,06
0,03
0.41
2.31
1.67
1.02
2,1''
0.59
1.11
0,70
7.11
2,61
1,44
2.34
0.89
1.32
O.lfl
5.91
1.28
0.56
0.46
0.22
0.74
0.1S
0.0
0.43
0.66
0.33
0.06
0.1S
0.39
2.03
0.67
0.90
0.79
0.25
0.89
0,59
3.41
1.26
1.34
1.29
0.40
1.79
2.10
9.21
A
0.03
0.0
1.41
0.24
0.06
0.16
0.03
0,46
3.56
2.01
0,65
1.13
1.06
0.66
0.75
12.41
2.59
0.85
1.26
1.48
0.86
0.23
15.39
1.63
0.52
0.39
0.40
0,62
0.16
0.0
1.04
0.62
0.33
0.12
0.12
0.43
,5.39
'l.34
0.71
0.67
0.37
0.52
0,63
6,60
1,66
0,6,9
,1.03
0,65
0.86
, 1.^.0
15.52
PERCENTAGE
DKY S
B
0.03
0.0
1.77
0.10
0.16,
O.Oo
0,03
0.51
0.61
2.65
0.84
1.91
0.55
l.H
0.62
2.49
3,60
1.16
1.91
0.71
1.17
0.21
2.81
2,02
0.47
0.48
0.15
0.68
0,14
0.0
0,67
0,55
0.32
0.03
0.09
0.41
0,97
1.23
0,74
0,64
0,15
0.63
0.62
1.63
2,01
,1.10
1.11
0,28
1.35
1.80
3.27
MET S TOTAL S AMB S02
B
0.23
0,0
0.76
0,19
0.16
0.15
0.03
1,89
0,34 -
1.13
0.70
3,82
0,99
0.71
3.14
1.79
1,54
0,96
3.50
0,95
0.66
2.1»
1,63
0.66
0.46
0.95
1 0.25
0,62
0.37
o.o
0.37
0,54
0.32
0,06
0,12
2.14
l.«2
0.53
0.68
0,79
P.37
0.52
3.58
1.09
0.86
0.94
1.11
0.40
0.86
,3.19
,3.44
B
0.26|
0,0
2.54
0.37
0.32
0.22
0.12
2.40
0.95
3.76
1.54
5.72
1.51
1.62
3.96
4.26
5.14
2.14
5.41
1.66
2.06
2.39
4,64
2.68
0.92
1.43
0.40
1.26
0.51
0.0
1.25
U09
0.64
0.09
0.18
2.55
2.39
1.76
l.<»2
1.43
0.52
1.20
4.21
2.72
2.68
2.04
2.23
0.68
2.25
4.99
6.72
C
5.63
0.0
16,99
13,86
6.42
3.30
0.66
1.47
3.91
12.61
11,16
14.76
5,18
9.66
3.03
8.14
9.56
9.00
5,89
3.94
7.45
1.23
10.20
7,36
4.96
2.65
1,60
6,26
3.61
0,0
3,19
5.80
2.0.3
0.83
6.56
3.19
, 3.20
. ,4.35
4.63
2.59
1.23
,4.27
4.98
, 4.64
! 5,27
,7.73
4.33
2.54
7.72
«.,»9
4.65
AMB 804
C
12.97
0.0
2,0.46
15.75
*.15
8.36
3.81
6.51
10,72
16.12
14.68
22.21
12.30
21.19
9.89
18.00
15.08
13.11
10.19
7.65
15.60
3.64
19.67
12.97
9.54
6.46
4.04
11.66
4.92
0.0
, 9.67
9.59
4.29
1.19
11.55
6.02
9.08
9.78
10.05
6.70
2.63
10.82
. ».74
,12.60
ill. 23
11.59
, 6.00
,4.36
14.20
, 9.6B
,13.57
DRY S
C
7.19
0.0
16.12
13.98
5.69
3.10
1.90
3.63
5.55
14.27
11.28
15.59
6.21
17.7D
4.59
12.34
10.60
9.11
5.66
3.69
11.45
1.63
15.50
6.97
5.10
3.53
1.55
6.00
3.*5
0.0
5.02
5.94
2.30
0.51
6.6*
3.77
, 5.87
, 6.02
4.95
2.51
1.03
7,64
5,68
, P.27
. 6.6J
7,85
4,4n
2,11
10.55
5.91
7,63
UNIT
MET S TOTAL S AMB 802 AMB 804
C
13.21
0.0
16.12
14.85
8.77
b.76
3.90
10.89
7.40
14.27
12.32
26.00
10.75
22.48
11.66
29.44
10.88
10.16
13,95
6,92
16,23
9.10
14.48
8.97
6.51
6.70
2.56
11.77
7.98
0.0
5.02
7.24
3.76
1.65
11.5.0
10.22
7.31
6.02
6.21
3.93
2.95
11.32
11.52
4.02
6.«1
8.94
4.66
' 3.05
,14.76
6.16
, 4,83
C
12.01
0.0
16.12
14,42
7.05
5.82
4.96
7.84
6.09
14.27
11.73
21.27
6.32
19.37
6.94
16.30
10,88
9.56
9.38
5.04
13.33
6.50
15.08
8,97
5.71
5.16
2.05
9.17
6.14
0.0
5.02
6.52
2,86
0.95
, 7.57
6,03
6. ,6 5
. 6.02
5,48
3.14
1.90
8,89
9,99
. 5.81
i ,6.61
,6.31
4.66
2.58
12.01
6.07
5.89
A/D
0,01
0.0 ,
0,40,
0,07'
0,07
0.02
0,01
0,13
0.75
0,61
0.3J
0,71
0,19
0,36'
0,23
2.31
0,65
0,47
0,76
0,29
0.43
0,06
1.92
0,42
0,18
0.15
0,07
0.24
0,05
0.0
0,14
0.21
0.11
0,02
0,05
0.11
0,66
0.22
0.29
0.26
P.°,8
P. 2.9
0.19
i.M
0,41
0.43
0.42
0.13
0.58
0,6,8
2,99
A/0
0,01
0,0
0,46
0.06
0,02
0,06
0,01
0.15
1.16
0.65
0.21
0.37
0.35
0.22
0,24
4.03
0.64
0.28
0.41
0.48
0,26
0.06
5.00
0,59
0,17
0.12
0,13
0.20
0,05
0.0
0.34
0.20
0.11
0,04
0,04
0.14
1.75
0.44
0.23
0.22
0.12
0.17
0.20
2.79
0.61
0,29
0.34
0.21
0.26
0.45
5,04
DRY 8
B/0
O.Oi
0.0
0.58
0.06
0,05
0.02
o.oi
0.16
0.20
0,86
0,27
0,62
0,18
0,36
0.26
0.61
1.17
0.38
0.62
0.23
0.3,8
0.07
0,9.1
0,66
0,15
0,15
0.05
0.22
0.05
0.0
0.26
0.16
0.10
0.01
0.03
0.13
0,31
0,40
0,24
0.21
0.0,5
0.22
0.20
0.53
0.6S
0.36
0.36
0.09
0,44
0.5,6
1 .,06
NET 8 TOTAL 8
B/0
0.07
0.0
0.25
0.06
0,05
0,05
0,01
0..61
0,11
0,17
0,23
i.24
0.32
0.23
1.02
0,56
O.SO
0.31
ft. 14
0.31
0.28
0.71
0.59
0,26
0,15
0,31
0.08
0,20
0.12
0.0
0,12
0,16
0,10
0.02
0,04
0,70
0,46
0,17
0,22
0.26
0.12
0.17
1,16
0.35
0.28
0.30
0.36
0.13
0.28
1,04
1.12
B/D
0,09
0,0
0.82
0.12
0.10
0.07
0,04
0,7B
0.11
1.21
0,50
1.86
0,49
0,59
1.29
1.39
1.67
0.69
1.76
0,54
0,67
0.76
1.51
0.94
0,10
0,46
0.11
0.41
0.17
0.0
0,41
9«35
0.21
0.01
0,06
0.81
0.78
0.57
0.46
0,46
0,17
0,19
1.17
,0.88
0.91
,0.66
0.72
0.22
,0.71
1.62
2.16
-------
(
1
<
1
(
I
1
A «
0 «
c •
0 <
J KCDM
} hOE
} AES
} KEP
1 MCAftlO
> ASTHAP
ENAMAP
KCUM
MOE
AES
HEP
t MCAHLO
— UG/M**3
— KG/HA/Yfc
.- X
•• TG 8/YR
3.64
3.64
3.72
0,95
2.37
1.77
23.09
3,04
2.39
5.12
4.60
3.39
2.99
1.61
2.16
1.45
0,99
0.76
£0.76
2,35
1.07
3.93
5.66
1.32
4.72 .
3.12 <
3,16 :
0.71 <
1.69 (
1.23
5.64
3,66
1,94
4,45 i
3.17 1
2.09
i.02
2.2V
1.50
J.52
).99
1.22
1.74
1.66
.45
5.36
1.17
1.32
6.74
5.40
6.68
1.23
2.66
2.45
7.58
5.54
3.39
6.84
4.37
3.42
6.56
6.53
4.57
2.15
6.14
4,48
16.53
13,21
10,96
10,78
13.34
11.14
15,06
14.16
10.37
5.02
13.66
8.02
19.61
16,65
16.21
19.66
18.55
22.53
9.79
6.02
4,79
2.15
10.75
5.39
17,34
14.06
11.07
11.29
12.56
19.21
9,79
9.49
7.43
2.34
14.73
3.42
4.90
14.06
12.05
9.76
11.35
23,62
9,79
6.97
5,89
2.23
11.92
4,19
10.96
14,06
11.47
10.71
12.26
20.59
1.25
1.21
0.31
0.77
o.5b
7,50
0.99
0,76
1,66
1.56
1.10
0,97
0.52
0,71
0.47
0.32
0.25
6.75
0.76
0.35
1.28
1.91
0,43
1.53
1.01
1.03
0,23
0,55
0.40
1,90
1.26
0.63
1.45
1.03
0,66
0,66
0,74
1.14
0.17
0,32
0.40
0.56
0,5tt
0.47
0.77
0.36
0,43
2.19
1.75
2.17
0.40
0.87
0,80
2.46
1.80
1.10
2.22
1.42
1.11
-------
TRANSFER MATRIX DISPLAYS
SOURCE REGIONI 3
SCENAR10I
ABSOLUTE
AHB S02 AMB ,804
REC
1
1
2
2
2
2
2
2
2
3
3
3
3
3
3
3
4
4
4
4
4
4
4
5
5
5
5
5
5
,5
;*
;*
6
6
6
6
6
7
7
7
7
7
7
7
8
8
MODEL
ASTRAP
ENAMAP
RCDH
HOE
AES
HEP
HCARLO
ASTRAP
ENAMAP
RCDH
HOE
AES
HEP
HCARLO
ASTRAP
ENAMAP
RCOM
HOE
AES
HEP
HCARLO
ASTRAP
ENAHAP
RCDM
HOE
AES
MEP
HCARLO
ASTRAP
ENAMAP
RCDM
MOE
AES
HEP
HCARLO
ASTRAP
ENAMAP
RCDM
HOE
AES
HEP
HCARLO
ASTRAP
ENAHAP
KCDH
HOE
AES
hEP
HCARLO
ASTRAP
ENAMAP
A
i
0,00
o.o
0,46
0.11
0.0
0.03
0,0
0,13
0.55
1.43
0,61
0.39
0,20
0.34
0.53
7.07
5.02
1.41
3.31
2.74
2.06
0.19
6.22
2.27
0,68
1.04
0.51
1.36
0.21
0.0
0.90
1.07
0.91
0.25
0.23
0.55
4,58
1.65
1.30
2.05
0,76
1.81
0.60
7.73
3.24
2,09
3,61
1.41
4,29
8.92
44,74
i A:
0.00
o.o
0.70
0.16
0.0
0.03
0,0
0,17
0.49
1.52
0,44
0.12
0.37
0.23
0.56
6.02
3.07
0,74
1,66
3.44
0.93
0,31
14,49
2.23
0.54
0.46
0.79
0.93
0,25
o.o
1.40
0.77
0.68
0,65
0.14
0,68
9.61
2.08
0.79
1.15
1.47
0.79
0,98
12.76
2.79
1.02
l.bO
2.15
1.38
3.51
23.60
1
DR.Y S
»,
I
o,,oo.
0,0
0.75
0,10
0,0
0,03
0.0.
0.17
0.11
2.02
0.51
0,36
0.23
0,37
0,65
1.50
6,03
1,15
2,73
2,68
1.86
0.27
2,64
3,12
0,56
0.83
0,40
1.24
0.23
0.0
1.51
0,89
0.63
0.23
0.14
0,66
2,00
2. ,48
1,07
l,7t>
0.71
1.24
1.03
2.93
4.2,0
1.70
3.20
1.19
3.42
.7.16
'.25
, PERCENTAGE
WET S TOTAL S AMB S02 AMB, S04,
. B.
0.05
0.0
0,.32>
Oj.1*
0.0
0..03,
o,,o
,0.66
0.01
0.87
0.44
0.71
0.40
0.23
2.12
0.05
2.56
0.91
5.22
2.66
0.93
2.56
2,10
1.34
0.52
, 1.30
0.65
0,93,
0,72
0.0
0.65
0.78
0,59
0.23
0,14
2.34
2. ,79
.1..06
0,06
2,65
0.93
0.76
5.0,5
2.55
, .63
.31
3.79
.33
.33
1 .05
20.44
, B
0,06
0,0
1.07
0,21.
0,0
0.06,
0,03
1,03
0,12
2.89
0.95
1,07
0,62
0,56
2.76
1.55
8.61
2,06
7.95
5.56
, 2»77
2.65
4.75
4.45
1.08
2,13
1.13
2.17
0.95
0.0
2.15
1.67
1.42
0.45
P.31
2.99
(4,7,9
3.5,4
1.95
4.62
1.6,4
,2.00
6. ,06
5.40
6.09
,3.01
7.00
2.51
4.77
1.6.20
29,6,9
C
0.64
fl.o
6.. 45
.7.5,4
,0.0
1.51
0.0
0.47
0.92
9.62
6,69
2.63
1.75
2.95
2.27
0.09
16.36
6.66
6.34
12.09
11,59
1.27
10,72
13.05
6.05
6.44
4,24
11,48
5.36
o.o
6.60
9.50
5.56
3.42
9.62
4.50
7.21
10.72
6.96
.6.68
3.82
8.64
7.36
10.54
13.56
12.12
12.60
8.97
18.55
20,77
2,2,60
, c
i
|1.6l,
'o.o
10.18
1,0.23
,0.0
il.2»
0.0
3.11,
1.48
13.74
9,92
2,33
4,19
7,07
7.42
6.72
17.86
11.44
13.47
17.83
17.00
4.76
18.52
15.83
9,b6
7,83
7,98
17,64
7,69
0.0
13.85
11.95
11.29
6.25
U.24
9.52
16.55
15.16
11.32
1,1.54
10.43
16., 3,5
13.61
16.70
16.60
13,32
13. ,96
1.4.46
22,79.
24,81
20.62-
DRY S
C,
0.85
0.0
7,66
7.71
0.0
1.46
0.0
1.25
0.96
10,90
6.79
2,91
2.53
5.69
3,64
7,41
18,24
8,93
A. 30
15.00
18.24
2,07
14,56
13.65
6.16
6.15
4.83
14.67
6.27
0.0
6.65
9.59
6.00
3.76
10.49
6.08
12.12
12.09
7.09
7. 02
4.71
14.01
9.41
,14.65
1.4.40
12.16
12.90
9.P4
26.60
23,54
.21,56
UNIT
HET S TOTAL S AMB 502 AMB S04
C
,
3.10
0.0
7,66
6,95
,0,0
1.61
0,0
4.97
0.27
10.90
7,76
4.65
4.31
7.17
7.99
0.86
16.24
9.58
20.01
19.44
17.53
10.70
16.66
13.05
7.32
9.17
6.74
17.01
15.60
0.0
0.65
10.41
7,04
6.06
13.19
11.14
14.33
12.09
6.07
1,4,06
7.43
16.49
16.22
, 9,42
14.40
12.46
16.57
10. .11
22.72
2S.J2
20.70
C
,
,2.65
o.o
7.66
,0.34
0.0
1.52
1.14
3.36
0.76
10,90
7.21
3.97
3.43
6.02
6.24
5.09
16.24
9.21
13.79
16.66
17,88
7.74
15.42
13.05
6.67
7.70
5.77
15.70
11.40
0.0
8.65
9,95
6,39
4.63
12.73
9.42
13.32
12.09
7.50
1,0.15
5.95
14.83
14.44
11.71
14.40
12.29
14.66
9.56
25.48
22.1(1
26.02
A/0
0,00,
o.o
0.16
0.04
o.o
0,01
0,0
0,05
0.19
0,51
0,22
0.14
0.07
0.12
0.19
2.50
1.78
0,50
1.17
0.97
0,73
0,07
2,20
0.60
0,24
0.37
0.10
0.40
0,07
0.0
0.32
0,38
0.32
0.09
P. 06
0.19
1.62
0.59
0.46
0.73
0.27
0.64
0.31
2.74
1.15
0.7<4
1.35
0.50
I. ,52
3.16
15.05
A/D
0,00
o.o
0.25
0.06
o.o
0,01
0,0
0.06
0.17
0.54
0.15
0.04
0.13
0.08
0,20
2.13
1.09
0.26
0.59
1.22
0.33
o.ii
5.13
0.79
0.19
0,16
0.26
0.33
0.09
o.o
0.52
0.27
0.31
0,23
0.05
0.24
3,47
0,74
P. 20
P. 41
0.52
P. 28
0.35
4.52
0,99
0.36
0.64
0.76
0.49
1,24
».43
DRY S
B/D
0.00
0.0
0.27
0.03
0.0
0.01
0.0
0.06
0,04
0,72
0,18
0.13
0,06
0,13
0.23
0.53
2.13
0.41
0.97
1.02
0.66
0.09
0.94
1.10
0.20
0.29
0.17
0,44
0.08
0.0
0.53
0.31
0,29
0.06
0.05
0.23
0.71
0.88
0.38
0,63
0.25
0.44
0.37
1.04
1.51
0.60
1.13
0.42
1.21
2,53
3,27
HET S TOTAL 8
B/D
0.02
0,0
0,11
0,04
0,0
0.01
0.0
0.31
0,00
0,31
0,16
0.25
0.14
0,08
0,75
0,02
0.91
0,32
1.65
0,95
0.33
0,92
0,75
0,47
0,18
0,46
0,23
0.33
0.25
0,0
0,23
0,20
0,21
0.00
0.05
0.03
0,99
0.38
0.31
1.01
0,33
0,27
1.79
0,90
0,65
0,46
1.34
0,47
0,47
3,91
7.24
B/D
0.02
0,0
0.38
0.08
0.0
0,02
O.OS
0,36
0.04
1.02
0.34
0.30
0.22
0.20
0.96
0.55
3.05
0.73
2.61
1.97
0,90
1.01
1.68
1.58
0.38
0.76
0.40
0.77
0,34
0.0
0.76
0,59
0.50
0.16
0.11
1.06
1,70
1.25
0.69
1.64
0.58
0.71
2*15
1.94
2.16
1.07
2.48
C.89
1.69
6,45
10,5}
-------
6 KCOH
0 hOE
8 AE3
6 ht!P
6 MCAKLO
A5TRAP
ENAHAP
KCDM
HOE
AE3
nEP
ciCARlO
11. «2
10,93
25.54
10fi4
6.21
O.bl
10.26
2.17
1.04
2. !<»
2.03
1.38
4. Ob
2.36
6.49
6,76
1.78
0,34
10,59
1.64
O.S7
1.73
4.43
0.62
12.36
6.74
20,67
7.74
4.60
0.49
3.05
2.75
0.65
1.90
1.72
0,93
b,30
5.63
13.40
5.56
1.72
0,69
0.64
l.itt
0,68
0,71
0.62
0.65
17.66
14.37
34.27
13.27
6.32
1.10
3.70
3.93
1.53
2.61
2.54
1.55
26.66
24.24
31,40
22,86
10.06
1.54
7.36
9.45
4.77
«.62
5.64
4.55
20.43
20.91
30.68
30.43
25.05
3.54
10.10
11.76
6.73
6.67
13,98
10.57
25.64
24. |h
31.46
23.52
29.21
2,13
9,06
9,96
4.65
4,61
6.62
8.55
25,64
23,34
26.45
24.63
25.74
1.94
1.62
9.98
5.64
2.91
7,94
11.58
25.64
23.66
30.21
24.02
26.14
2.01
5.35
9,98
5.17
4.09
7.14
9.35
4.04
3.67
9.05
3.59
2.20
0.22
3.64
0,77
0.37
0,76
0.72
0,49
1,44
0.64
2,30
3,11
0,63
0.12
3.75
0.58
0.20
0.61
1.57
0.22
4.38
3.10
7.39
2.74
1.63
0.17
1.06
0.97
0.30
0.67
0.61
0.33
1.86
1.99
4.75
1.97
0,61
0.24
0,23
0.42
0.24
0.25
0,29
0,23
6.26
5.09
12.14
4,70
2,24
0.42
1.31
i.39
0.54
0.92
0,90
0.55
A •- UG/M**3
B — KG/HA/YH
C — X
D — TG S/YR
-------
TRANSFER MATRIX.DISPLAYS
SOURCE REGION! 4 . SCENARIOS
ABSOLUTE
PERCENTAGE
UNIT
AM8 802 AMb S04
REC
2
2
2
2
2
2
2
4
4
4
4
4
4
4
5
5
5
5
5
5
5
'6
'6
6
6
6
6
'6
7
7
7
7
7
7
7
a
6
HOOEL
ASTRAP
ENAMAP
RCDM
HOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
HOE
AES
HEP
MCAHLO
ASTRAP
ENAMAP
RCOM
HOE
AES
HEP
MCARLQ
ASTRAP
ENAMAP
HCOM
MOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
MOt
AES
MEP
MCARLO
ASTKAP
ENAMAP
A
0.0
0.0
0,07
0,04
0,0
0,0
0.0
0,01
O.Ob
0,36
0,24
0.06
0,06
0,06
0.12
1.10
2,38
0.64
1.00
0,66
0,70
0,16
2.74
1.40
0.40
0,66
0,39
0,70
0,30
0.0
0,65
0.82
0.62
0,35
0.06
0.64
4.64
2.09
0.64
1.75
0,63
1.14
1.10
9.23
4.0i
1.35
3.16
l.bb
2. 98
19 .'57
4:4 ,'3 1
. A
0.0
0.0
0.14
0.07
0.0
0.01
0,0
0,01
0,09
0,41
0,16
0.04
0,06
0.04
0.11
1.09
1.22
0.34
0.41
0.75
0,30
0,25
3.54
1,04
0.29
0.27
0,69
0.46
0,36
0,0
0.94
0.49
0.46
0.97
0.07
0,91
4.98
1.49
0.45
0,70
1.22
0.51
0.91
6.U4
1.79
0,57
1.27
1.63
0.73
3.74
'9. 35
DRY S
B
0,0
0.0
0.13
0.04
0,0
0,01
0,0
0.01
0.01
0.52
0.20
0,14
0,04
0,04
0.13
0,30
2,75
0.52
0,62
0,65
0,70
0,24
0.79
1.77
0.33
0,55
0,39
0.79
0,36
0,0
1.22
0,67
0,55
0,34
0,07
1,07
1,44
2,61
0,68
1.51.
0.32
t,2«
1,36
2.29
4.51
1,09
2,60
1.40
2.5'H
10. '59
7.27
NET S TOTAL S AHb S02 AMb 504
B
0.0
0.0
0,06
0.05
0,0
0.01
o.o
0.19
0.00
0.22
0.18
0.41
0.11
0.04
0,68
0.0
1.18
0.41
1,76
0.64
0.28
1.04
1.03
0,76
0.29
0.96
0.63
0.48
0.74
o.o
0.52
0.55
0.41
0.26
0.07
2.73
2.19
1.12
0.54
2.46
1.17
0.51
3.02
5.51
1.93
0 ,80
3.15
1 ,!*0
'0,70
17.12
ie.;o5
: 8
0.0
0,0
0.19
0,09
0.0
0.03
0,0
0,21
0.01
0.75
0.37
0.55
0.15
0,07
0.61
0,30
3.93
0,93
2.60
,49
,00
.28
.82
.53
.62
.51
.03
.27
.10
0,0
1,74
1,22
0.96
0.62
0.14
3.80
3.66
3.72
1.22
3.97
1,98
1.79
4.3'b
7,6'0
6,44
1 .'69
5,75
3. '2,5
3.26
27.70
25,32
C
0.0
0,0
1,02
2.9J
0,0
0.0
o.o
0.05
0.10
2,49
2,60
0.55
0.50
0,49
0.50
1,25
8,70
4.00
2.52
2.98
3,96
1,09
4,73
8,05
3.56
4,06
3.29
5,96
7.92
0.0
6.29
7,26
3,75
«.73
3.60
6.91
7,62
l'3.55
4. SI
5.70
4.16
5.45
9.18
12.54
16,60
7.79
10.63
9.92
12.90
45,56
22.39
C
0,0
0.0
1.96
4.29
o.o
0.64
0.0
0.27
0.26
3.73
4.13
0.61
0.64
1.32
1.45
1.57
7.09
5.18
3.33
3.86
5.42
3.90
4.52
7,40
5,30
4,64
6,96
9.06
11.63
0,0
8.61
7.52
6.16
9.34
6,60
12,66
6.41
l'O.B4
6.37
7.00
6.70
10.40
12.69
9.44
10,76
7.41
9.66
U.oo
l'2.05.
2,6,45
8.16
DRY S
C
0,0
0,0
1.33
3,01
0,0
0,73
0.0
0.11
0.12
2.63
2.65
1.12
0.47
0.66
0.74
l.<»7
6,31
4,03
2.52
3.37
6.69
1.66
4.JB
7,66
3.61
4,06
3,97
9,30
9.71
0,0
7,00
7.27
3,96'
5.62
5.23
9.97
e.93
l'2,7l
4.5fc
5.95
5.44
14.44
12.'4'0
11.64
15. 2«
7.7H
10.4f>.
ll.lt-
20.05
3.5
4.5H
1.27
0.40
0,90
1,16
0.52
2,66
6.65
DRY S
B/D
0.0
0.0
0,09
0.03
0,0
0,01
0,0
0,01
0,01
0.37
0.14
0,10
0,03
0.03
0.09
0.21
1.95
0,37
0,56
0,46
0,50
0.17
0,56
1.26
0.23
0.39
0,26
0.56
0,26
0,0
0,67
0.46
0.39
0.24
0,05
0.76
l.OS
1.85
0.49
1.07
0.56
0.91
0.97
1.63
3.20
0.77
i.*»5
1.04
1.8}
7.52
5.17
MET 8 TOTAL 3
B/D
0.0
0.0
0,04
0,03
0.0
0,01
0.0
0.14
0.00
0.16
0.13
0.29
0.08
0.03
0,48
0.0
0.64
0.29
1.26
0,60
0,20
0.74
0.73
0.54
0.21
0.66
0.45
0.34
0.52
0.0
0.37
0,39
0,29
0.20
0,05
1.94
1.55
0.79
0.38
1.75
0.83
0.36
2.15
3.91
1,37
0.57
2.24
1.26
0.50
12,16
12.82
B/D
0.0
0.0
0.13
0,06
0.0
0,02
0.0
0.15
0.01
0.53
0,27
0,39
Oj.ll
0,05
0,58
0.21
2,79
0.66
1.65
1,06
0.71
0.91
1.29
1.79
0,44
1,07
0,73
0.90
0,78
0.0
1.24
Q.87
0,68
Oe44
0,10
2,70
2.60
2.65
0,87
2.82
1.41
1.27
3.12
5.54
4,58
1.34
4,09
2.31
2,32
J9.69
17.99
-------
6 ROOM
8 KOE
0 AES
a HEP
« MCARtO
9 ASTRAP
9 ENAMAP
9 KCDM
9 HOE
9 AES
9 M£P
9 MCARLO
4.16
IS. 60
30.58
23.70
22.74
0.02
1.95
0.30
0.22
0.16
0.23
0.08
1,46
1.78
3.53
6.98
1.28
0,01
2.07
0,35
0,17
0.15
0.76
0,07
-«.50
12.39
24,50
15.68
3.36
0.01
0.59
0,44
o.ld
0.14
0.23
0.07
1.93
7,62
11,09
9.09
0,96
0,05
0,34
0,19
0.17
0,0
0,23
0,07
6,43
20,01
35,59
24.78
4.32
0,07
0,93
0.63
0.35
0,14
0.45
0.13
9,79
34,59
37.59
53.45
58, 67
0.06
1.40
1,32
1.01
0.35
0,63
0.28
7,35
15.63
16.82
24.19
18.03
0,10
l.*7
2,54
2,61
0.75
2,40
1.20,
«.33
34,28
36.93
47.67
21.35
0.06
1,76
1,60
1,04
0.35
0,89
0.65
9.33
31.64
23.55
40.58
14.30
0.14
0.95
1,60
1.38
0.0
2,18
1.26
9.33
33.22
31.38
44. 85
19.22
0.11
1.34
1.60
1.18
0.21
1,27
0,76
2,96
11.08
21,73
16.64
16,16
0,02
1.39
0,22
0.16
0,12
0.16
0.06
1.04
1.27
2,51
4,96
0.91
0,01
1.47
0,25
0.12
0.11
0,54
0.05
3,20 ,
8,80
17.41
11.14
2.39
0.01
0,42
0,31
0.13
0.10
0,16
0,05
1.37
5.42
7. 86
6,46
0.68
0.04
0.24
0.13
0.12
0.0
0.16
0,05
4,57
14.22
25.29
17.61
3.07
0.05
0.66
0,45
0,25
0.10
0.32
0,09
A •• UG/h**3
B •- KG/HA/YR
C « X
0 — TC 5/TR
-------
TRANSFER MATRIX DISPLAYS
1
SOURCE HEGIONJ 5 SCENARIOl
ABSOLUTE
AMB 502 AMB S04
NEC
1
1
1
1
1
1
1
2
2
2
2
2
2
2
3
3
4
4
4
4
4
4
4
S
5
5
5
5
5
5
6
6
6
6
6
6
6
7
7
7
7
7
7
,7
b
8
MODEL
ASTRAP
ENAHAP
RCDM
HOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
MOF
AES
HEP
MCARLO
ASTRAP
ENAHAP
RCDM
HOE
AES
HEP
MCARLO
ASTRAP
ENAMAP
RCDM
HOC
AES
HEP
MCARLO
ASTRAP
ENAMAP
RCOH
HOE
AES
HEP
MCARLO
ASTRAP
ENAMAP
fcCDM
HOE
AES
MEP
hCARLO
ASTKAP
ENAHA-P
RCOM
HOE
AES
htP
MCAKLO
4S1«AP
ENAP.AP
A
0.00
0.0
0.04
0.03
0,01
0,0
0.0
0,00
0,07
0.24
0.16
0,20
0,05
0,05
0.03
0.56
1.69
0,55
0,90
0,64
0.97
0.24
3.11
1.42
0,63
1. 51
1.23
1.34
1.21
0,0
1 .54,
2.83
6.72
3.02
0.29
3.82
14.96
4.32
1.65
3.21
3,18
13.14
2.92
16.96
6. ,02
2.45
5,26
3.3o
9.00
0,13
8.11
A
0.00
0.0
0.09
0.06
o.oi.
o.o
0.0
0,00
0,11
0.31
0.14
0.12
0.05
0.02
0.02
0.76
0.93
0.26
0.35
0.32
0.29
0.25
3.57
0,96
0.36
0.49
1.17
0.56
0.69
0.0
1.19
0.92
1.99
4.12
0.13
1.46
5.16
1.66
0.60
0.68
2.24
1.01
0 .,9,3
4.70
1.79
0.68
1.11
1.71
o,b5
5.27
3.87
4.56
6.63
6.54
6.32
11.76
10,59
27.95
0.0
11.07
1«.22
25.60
39.66
11.99
20.45
(8.71
13.57
,8.53
6.79
15.90
20.82
12.96
6.69
10.60
fl.95
6.63
11. S3
9,74.
iO.39
4.64
DRY S
C
0.00
.0.0
0.86
2.29
0,0
o.o
0.0
0,03
0.17
1.96
1,61
1,08
0.54
0.77
0,14
0,87
6.00
3.46
2.45
2.66
7,82
2,41
4,79
7,78
5,63
8,65
13.03
16.04
33.55
0.0
11.27
24,63
40.28
42.55
16.62
27.19
16.90
23.57
8.68
10.46
19. V3
32.44
20.54
16.24
21.50
1.4.01
17.11
21.56
12.20
0,30
**,3l
UNIT
NET S TOTAL S AMB SU2 AMb 504
C
0,00
0.00
0.66
2.96
o.o
0.0
0.0
0.18
0.20
1.96
2.25
1,81
0.67
0.51
0.75
0.95
6.00
3.69
3.18
7.64
5.11
9.18
7.57
7.78
5.89
14.92
20.58
10.69
20.65
0.0
11.27
21.00
37.63
45.41
11.94
22.99
13.44
23.57
8.65
17.70
29,19
17.,V6
15.12
20.44
21.50
12.60
16.81
23.00
7.93
0.94
7.55
C
0,00
o.oo
0.66
2,63
0.0
0.43
0.0
0.12
0.16
1.96
2.00
1 .46
0.71
0.66
0.51
0.89
6,00
3.56
2.76
4.75
6.92
6.62
5.93
7.76
5.75
11.97
16.66
14,04
26.41
0.0
11.27
23.01
39,35
43.54
14.41
24.41
15.03
23.57
6.79
13.69
24.15
27.31
16.55
18.67
21.50
13.41
16.96
22.32
10.75
o./o
6.33
A/D
0,00
0.0
0.03
0.02
0.01
w.o
o.o
o.oo
0,05
0.15
0,10
0,12
0.03
0.03
0.02
0.35
1.06
0,34
0,5.6
0,40
0,01
0.15
1.94
0.89
0.39
0.95
0.77
0.64
0.76
0.0
0.97
1.77
4,20
1.89
0,18
2.39
9.36
2.71
1.03
2.01
1.99
6.22
1,83
10,|t>l
3.77
l.W
3.29
2.10
5.63
0.06
5,06
A/D
0.00
0,0
0.06
0.03
0.01
o.o
o.o
o.oo
0.07
0.19
0,09
0,07
0.03
0.01
0.01
0.47
0.56
0.16
0,22
0,20
0.18
0.16
2.23
0,60
0.22
0,31
0,73
0.35
0.56
0.0
0,74
0,57
1.25
2.58
0.08
0.91
3.23
1.16
0.38
0.55
1.40
0.63
0.56
2.94
1.12
0.43
0.70
1.07
0,37
0.03
3.29
DRV 8
e/D
0,00
0,0
0,05
0,02
0,0
0,0
0,0
0,00
0.01
0.23
0,06
0,06
0,03
0,03
0,02
0.11
1.24
0,26
0,50
0,32
0,50
0,19
0,54
1,09
0.32
0.75
0.81
0.65
0.78
o.o
1.23
1.43
3,49
1,60
0.14
1.63
1.75
3.02
0.64
1.66
1.87
1.60
1 ,42
2.00
3.96
1.23
2.66
1.77
0.96
0.06
1.16
NET S TOTAL 8
B/D
0,00
0,00
0,02
0.02
0,0
0,0
0.0
0,02
0.01
0.10
0,06
0.17
0.05
0,01
0.12
0.04
0,53
0,22
0.50
0.66
0.17
1.38
0.60
0,47
0.26
1.33
1.24
0.35
0.59
0.0
0.53
0.98
1.99
1.06
0.08
3.02
1.63
1.30
0.59
2.24
2,29
0,52
2.94
3.46
1.71
0.63
2.41
1.89
0,29
0,31
3.37
8/0
0.00
0.00
0.08
0.04
0.0
0.0}
0.0
0.02
0.02
0.33
0.16
0.25
0.08
0.04
0.14
0,15
1.77
0.50
1.00
0.98
0.67
1.57
1.14
1.56
0.58
2.08
2.04
1.21
1.37
0.0
1.76
2.41
5,48
2,66
0.22
4.85
3.38
4.32
1.43
3.90
4.16
2,31
4.36
5,46
5.69
2.06
5.07
3.67
i.,26
0.36
4.52
-------
6 RCDH
6 *OE
e AES
6 HEP
6 hCARLO
ASTRAP
ENAMAP
RCDM
MOfc
AES
HEP
MCARUO
1.42
1.10
0,93
l.*3
1.39
0.00
0,62
0,14
0,09
0,07
0,03
w 0 w •
0,02
0,91
0.02
0,29
1.12
0,37
0,00
1,70
0,23
0,10
0,03
0,06
0.02
1.72
0,69
0,60
1.26
0,96
0.00
0.3S
0.24
0.06
0,0
0,03
0.02
0.74
0.64
0.66
1.01
0.35
0.01
0,10
0,10
0.06
o.o
0.02
0.02
2,46
1.54
1.46
2.27
1.29
0.02
0.45
0.34
0.16
0,0
0.05
0,05
3,34
2.45
l.H
2.99
3.60
0.00
0.59
0.63
0.42
0.14
0,09
0,05
4.M
3.71
1.39
3.66
S.l«
0.02
1.62
1.63
i.se
0.13
0,25
0,27
3,56.
2,47
1,20
3.64
6,09
0.01
1.04
0.66
0,44
0.0
0.13
0.15
3.56
2,67
!.«»
4.49
5.25
0.04
0.27
0.66
0.69
o.o
0.15
0.29
3.58
2.5b
1.29
«.ll
5.76
0.03
0.65
0,66
0,54
0.0
0.13
0.29
0,69
0.69
0.56
0,63
0,67
0.00
0.52
0,09
0.06
0.04
0.02
0.01
0,57
0,26
0.18
0,70
0.23
0.00
1.06
0.14
0.06
0,02
0.05
0.01
1,06
0,56
0,50
0,79
0.60
0.00
0.22
0.15
0.05
0.0
0.02
0.01
0,46
0,40
0,42
0,63
0,22
0,01
0.06
0,06
0,05
0.0
0,01
0.01
i.S«
0,96
0,91
l.«
0.81
0,01
0,28
0.21
0,10
0,0
0.03
0,03
A « UG/M**3
8 •- KG/HA/Yft
C — X
0 — TG 8/VR
-------
TRANSFER MATRIX DISPLAYS
SOURCE REblONl 6 , . SCEHARIOj
ABSOLUTE
AMB S02 AMB 504
REC
2
2
2
2
2
2
2
3
4
4
4
4
4
4
4
5
5
5
5
5
5
5
'b
b
b
b
b
b
b
7
7
7
7
7
7
7
B
B
MODEL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
hCAKLO
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCDM
nO£
AES
MEP
MCARLO
ASTRAP
ENAMAP
RCOM
MOE
AES
hEP
MCARLO
ASTRAP
ENAMAP
SCUM
hOE
AES
MEP
MCAKLO
ASTKAP
tNAMAP
RCDM
MOE
AES
MEP
fCAKLO
ASTKAP
tNAMAP
A •
0.01
0.0
0.41
0.07
0.0
0.02
0,0
0.06
0.29
0.57
0.26
0.16
0,05
0,09
0.12
2.46
0.96
0.41
0.62
0.16
0.21
0.04
0.42
0.46
0.22
0.10
0.05
0.21
0.04
0.0
0.16
0.33
0.10
0.05
0.02
0.12
0.11
0.30
O.Jb
0.26
0.12
0.12
0,17
0.19
0.57
0.51
0,50
O.lb
0.35
l.Oo
6.4H
;A
0.01
0.0
0.76
0.11
0,0
0.02
0.0
0.06
0.65
0,97
0.26
0.06
0.07
0.09
0.15
6.00
1.35
0,36
0.28
0.28
0.23
0.06
2.31
0.90
0.26
0.02
0.07
0.25
0.06
0.0
0,50
0.36
0.10
0.05
0.02
0.17
1.16
0.71
0.36
0.13
0.14
O.lb
0.24
1.77
1.03
0.43
0.26
0.21
0.37
1.01
12.71
DRY S
B
0.01
0.0
0.73
0,06
0,0
0,02
0,0
0,06
0,09
0,97
0,22
0.16
0.05
0,09
0,13
1,02
1.51
0,34
0.49
0,16
0.25
0.05
0,34
0,64
0.19
0.0
0.05
0.23
0.05
0.0
0.38
0.28
0.16
0.02
0.02
0,14
0.17
0.60
0.31
U, 16
0.09
0.16
0.21
U.27
1.00
0.43
O.U9
0.12
O.U6
1.13
2. 55
PERCENTAGE
NET S TOTAL S AMB SU2 AMU S04
B
0.07
0,0
0.31
0,06
0,0
0.02
0.0
0.50
0.01
0.42
0.22
0.33
0.12
0.09
0.91
0,07'
0,65
0,33
1,63
0.21
0.23
0.32
0.11
0.36
0.21
0|07
0.25.
0.10
0,0
0,16
0,29
0,16
0,02
0,02
1.21
0.28
0.26
0.31
0,49
0.09
0.16
2.22
0.40
0,43
0.40
0.98
0.14
0.37
3,00
2.67
B
0.08
0.0
1.04
0,14
0.0
0.05
0.0
0.56
0.10
1.38
0,44
0.49
0.16
0.18
1.05
1.09
2.15
0.67
2.12
0.37
0.49
0.37
0.45
1.20
0.39
0.16
0.12
0.51
0.15
0.0
0.54
0.57
0.33
0.07
0.07
1.35
0.45
0,66
0,61
0.65
0.16
0.32
2.42
O.'b7
1.43
0,63
1.47
0.26
0.63
4.13
5.23
C
1.03
0.0
5,74
4,72
o.o
1.24
0,0
0,20
0.49
3.89
2.68
1.10
0.41
0.81
0.53
2,82
3.53
2.59
1,56
0.71
1,17
0,30
0.72
2,64
1.97
0.60
0.39
1.76
1.16
0.0
1.21
2.94
0.59
0.62
,0.98
0.95
0.18
1 .92
1.96
0.90
0.56
0.55
OJ2b
2.40
2.97
1.7,0
1.03
i.sb
2.48
3»27
C
2.25
0.0
10.96
7.31
0.0
1.05
0.0
1.14
I ,95
8,77
5.92
1,60
0,79
2.89
1.92
b,70
7.85
5.53
2.25
4I23
0.68
2.95
6.41
4.76
0.26
0.70
4.81
1.74
0.0
4.67
5.51
1.26
0.44
2.17
2.37
1.95
5.18
5.06
1.31
0.98
3.34
3.35
2.60
6.20
5.67
2.02
1.5o
6.99
7,S3
ii.n
DRY S
C
1.20
0.0
7,43
4,66
0,0
1.19
0.0
0.43
0,61
5,23
2.97
1.33
0.52
1,46
0.75
5.05
4.56
2.67
1.50
0,64
2.49
0.37
1.86
3.73
2.06
0.0
0.47
2.73
1.25
0.0
2.19
3.03
1.16
0.38
1.72
1.31
1.03
2.93
2.04
0.64
0.62
1,62
1.88
1.39
3.36
3.05
1.97
0.66
3.60
3071
5.9b
UNIT ,
MET 3 10TAL S A
C
4.19
0,0
7,43
6,06
0.0
1B32
0.0
2.90
0.16
5.23
3.91
2.22
1.26
2.93
3.45
1.14
4.56
3,47
6.50
1.51
4.35
1.35
0.87
3.73
2.92
1.14
0.72
4.66
2.24
0,0
2,19
3.92
1.93
0.62
2.16
5.76
1.46
2.93
2.61
2.41
0.74
3.50
7.12
1.46
3.38
3.64
4.27
1.06
6.33
5.79
3.75
C
3.59
0,0
7,43
5,49
0,0
1,25
0,0
1,83
0.63
5.23
3.36
1.82
0.69
1.97
2.37
4.14
4.56
3,01
3,68
1,12
3.13
1.01
1.46
3.73
2.44
0.59
0,59
3.69
1.60
0.0
2.19
3,43
1.46
0.71
2.84
4.25
1.26
2.93
2.3b
1.43
0.67
2.39
5,76
1.43
3.36
3.39
3.07
.1.06
4.44
5.02
4.58
Mb §02 AMB S04
A/D
0,00
0,0
0,18
0.03
0.0
0,01
o.o
0,02
0.13
0.25
0.11
0.07
0.02
0.04
0.05
1.07
0,42
0,16
0,27
0,07
0,09
0.02
0,18
0,20
0,10
0,04
0,02
0,09
0,02
0.0
0.07
0.14
0,04
0,02
0,01
0,05
0.05
0.13
O.lb
0.12
0.05
0.05
0,07
0,08
0.25
0,22
0.22
0.07
0.15
00«6
2,69
A/D
0.00
0,0
0,33
0.05
0.0
0,01
0,0
0,03
0,26 ,
0,42
0.11
0.04
0,03
0,04
0,06
2,60
0.58
0,16
0,12
0.12
0.10
0,02
1.00
0,39
0,11
0,01
0,03
0,11
0,02
0,0
0.22
0,15
0,04
0,02
0.01
0,07
0,50
0,31
0,15
O.Oo
0,06
0,07
o.io
0.77
0,45
0.19
0.11
0,10
0,16
0044
5.50
DRY S
B/D
0.00
0,0
0.32
0.03
0.0
0,01
0,0
0.02
0.04
0.42
0.10
0.07
0.02
0.04
0.06
0,44
0.6S
0.15
0.21
0,07
0,11
0,02
0.15
0.36
o.oa
o.o
0,02
0.10
0.02
0,0
0,16
0,12
0,07
0.01
0.01
0.06
0.07
0.26
0.13
0.07
0,04
0,07
0,09
0.12
0.43
0.19
0.21
0.05
0,20
0.49
1.11
WET S TOTAL 8
B/0
0.03
0,0
0,14
0,03
0,0
0.01
o.o
0.22
0.00
0.16
0,10
0.14
0.05
0.04
0.40
0,03
0,26
0,14
0,71
0,09
0,10
0.14
0,05
0.16
0,09
0,07
0.03
0,11
0,04
0,0
0,07
0,13
0.07
0.01
0.01
6.52
0.12
0.11
0.13
0.21
0.04
0.07
0.96
0.17
0.19
0,17
0.42
0.06
0,16
1,30
1,16
B/0
0.03
0.0
0,45
0,06
0,0
0.02
0,0
0,24
0.04
0,60
0,19
0.21
0.07
0.06
0,45
0,«7
0.93
0.29
0.92
0.16
0.21
0.16
0.19
0.52
0,17
0.07
0.05
0.22
0,06
0.0
0.24
0,25
0.14
0.03
0,03
0.58
0,20
0,37
0.27
0.28
0,06
0.14
1.05
0.29
0,62
0.36
0,63
0.12
0,36
1,79
2,26
-------
8 ROOM
fl HOE
8 AES
it HEP
6 MCARLO
9 ASTRAP
9 ENAHAP
RCUM
HOE
AES
HEP
HCARLO
2.53
1.64
2.93
0.58
0.90
32. 12
52.01
6.1J
7.32
21.49
19.13
21.41
2.14
0.83
1.30
0.95
0.60
6.17
26.10
2.60
1.63
5.99
11. 02
2.03
1.31
1.33
2,44
0.49
1.02
16.77
10.61
6,93
5.85
17.59
13,17
4.64
1.42
1.03
3.42
0,42
0,60
18,86
9,02
2.97
3.79
7.17
4,64
1.73
4,74
2,37
5.86
0.90
1.62
35.64
19.63
9.90
9.64
24,76
17.81
6.40
5.96
3.63
3,60
1.30
2.33
61.00
37,24
26.66
33.57
45.23
53.10
70.45
10. HO
7.24
6.20
3.26
6.46
63.83
24.60
20.09
20.73
30,01
34.75
34.50
6,67
3.69
3.66
1.48
6,45
73,49
31.49
25.13
33.40
44.64
52.13
42,59
6.B7
4.29
7.26
1.66
6.97
52.90
25.46
25.13
31.49
29,35
45,02
30.91
6.67
3.93
S.J7
1.63
7.19
60.94
26.40
25.13
32.62
38.79
50.03
36.54
1.10
0.71
1.27
0.25
0.39
13,90
22.52
2.65
3.17
9,30
6,26
9.27
0.93
0,36
0,56
0,41
0.26
2.67
11.30
1.21
0.71
2.60
«.77
0,66
1.43
0.56
1.06
0.21
0.44
7.26
4.59
3,00
2,53
7,62
5.70
2.01
0,61
0,45
i.48
0.16
0.26
e.i7
3.91
1.29
1.64
3.10
2.01
0,75
2,05
1,02
2.5«
0.39
0,70
15. 43
0,50
4,26
4.17
10,72
7,71
2,77
A — UG/M**3
b « KG/HA/YR
C « X
0 « TG S/YR
-------
TRANSFER MATRIX DISPLAYS
SOURCE REGION! 7 ' SCENARIOS
ABSOLUTE
AHB S02 AHB SOU
REC MODEL
i ASTRAP
ENAHAP
HCOH
HOE
AES
hEP
1 HCARLO
2 ASTRAP
2 tNAMAP
2 RCDH
2 HOE
2 AtS
2 rtEP
2 MCARLO
3 ASTRAP
3 ENAHAP
3 RCOH
3 HOE
3 AES
3 HEP
3 HCARLO
4 ASTRAP
4 ENAMAP
t RCDH
4 HOE
4 AES
4 hEP
4 HCARLO
5 ASTRAP
5 ENAHAP
S RCOH
5 HOE
S AES
5 HEP
S MCARLO
6 ASTRAP
6 ENAHAP
6 RCDH
'6 HOE
6 AES
6 HEP
6 HCAHLO
7 ASTRAP
7 ENAHAP
7 RCDH
7 HOE
7 AES
7 HEP
7 HCARLO
6 ASTRAP
6 ENAHAP
A
0.00
0.0
*» • "
0.16
V f • v
0,05
0.0
W Q W
0.0
" B
0.0
w • w
0.01
• "
0.13
0.51
w 9 m
0.22
0.04
w • ^
0.02
w • "
0.05
^ • w
0.04
1.04
2.11
• t • •
0.50
9 9
0,37
V
0.25
w • w
0.23
•
0.05
1(21
1.11
MI
0.35
™ »
0.11
W f • •
0,30
0,17
0.0
0,56
0,87
0,41
0,16
0,05
0,29
2.66
l!'M
0.72
0.66
0,25
0.39
0.29
4 ,96
2,4'6
1.02
1,16
0,41
0.64
6,67
70,32
A
0.00
0.0 i
w y v i
0,34
0.06
0.0
0.0
0.0
0.01
0.14
0,75
0.21
0.0
0,02
0.02
0.07
1.17
1.73
0.36
0*17
0.34
0.21
0.11
3.61
1(30
0.33
0,11
0(16
0,32
0,26
0,0
0,96
0.59
0.30
0,41
0,05
0,43
4,33
1.57
0,49
0.39
0.39
0.34
0,42
6,81
2,03
t
0.56
0.62
0,53
0.46
3.18
2.5.92
DRY S
6
0.00
0.0
• "
0,31
0,04
0,0
o.o
0,0
0,01
0.03
0,61
0,19
0.0
0,02
0,05
0,06
0,28
2,74
0,41
0.37
0,27
0,27
0,09
0,61
Ie62
0.31
0,37
0,11
W J B V
0,37
0,22
0,0
0,96
0,72
0,37
o,i a
0.05
0.39
0.92
1.97
0,59
0,75
0.23
0,43
0.4'0
1.67
'3.20
0.63
I
1.12
0.39
6.78
7.»«
13. ,67
i i ! PERCENTAGE
NET S TOTAL S AHB 802 AHB S04
, B
0,00
0.0
0,13
0.06
0,0 ,
0.02
0.0
0.11
0,0
0.35
0.19
0.0
0.05
0.02
0,56
0,0
1.17
0,36
0,75
0.37
0,21
0.65
0.66
0.69
0.30
0.75
' 0.21
0,32
0,59
0,0
0,42
0.62
0.56 '
0,11
0,05
1,91
1,69
0.84
0.51
2.05
0.50
0.34
2^36
4.03
1.37
0.!67
2,61
0.64
0,46
13,66
17, ,67
B
0,00
0.0
0.44
0,10
0.0
Oi,02
0.0
0.13
0.03
1.16
0.37
0,0
0,09
0,09
0.64
0.2B
3,92
0.76
1,12
0.64
0.46
0,94
1.4*
2.31
0.61
1.12
0.34
0.69
0.62
0.0
1.40
1.33
0.93
0,25
0.09
2.30
2.01
2.61
1.11
2.60
0.73
0.78
2.76
5.71
4.57
1.50
3.74
1.03
1.26
21.53
3.1.54
C
0,00
o.o
2,26
3.29
0.0
0.0 .
0.0
0.02
0.2i
3,47
2.42
0.25
0.20
0.40
0.19
1.19
7.73
3.13
0,94
1.11
1.28
0,37
2.06
6,37
3.32
2.19
0,95
2.52
4,49
0.0
4.26
7.69
2.50
2,15
l.*5
?.37
4.19
8.77
3.88
2,80
1.26
1.66
2.4,4
6.7*
10.31
5,89
4,90
2.*1
2,76
2,0 , ,6 ft
35. S3
C
0,01
0.0
4,96
5.54
0.0
0,0
0,0
0.26
0,42
6,76
4.67
0.0
0.26
0.71
0,66
1.70
10.07
5,53
1.36
1.77
3.77
1.70
4.62
9.21
6,07
1.90
1,65
6.05
6.05
0.0
9.13
9.17
3.64
3.96
4.28
6.01
7.31
11.43
6.98
3.94
2.76
7.08
5.77
9,99
12.23
7.56
«.77
3.54
7.52
22,46
22.67
DRV S
C
0.01
0.0
3,14
3.43
0.0
0.0
0.0
0,06
0.25
4.36
2,49
0,0
0,26
0.73
0,34
1.37
6.29
3.20
1,15
1.43
2.66
0,70
3.34
7.19
3.40
2,77
1.15
4.32
5.96
0.0
5.63
7.75
2.70
2.26
3.39
3.63
5.59
9,59
3.96
2.95
1.52
4.69
3.66
6.48
10.61
5,94
4.51
2.96
6.05
25.91
32.35
UNIT
NET S TOTAL S AHB 802 AHB S04
c
0,00
0.0
3.14
4.47
0.0
1.30
0.0
0.66
0.0
4.36
3.24
0.0
0.50
0.73
2.18
0,0
8,29
3.64
2.98
2.65
3.67
3.55
6.79
7.19
4.25
5.25
2.14
6.11
12,96
o.o
5.63
6,24
6.66
3,06
«.27
9.10
9.73
9.59
4.66
10,15
4.01
7.41
7.57
14, VO
10.61
6.41
11.42
4.07
7.82
26,36
24.60
C
0,00
0.0
3.14
3,95
0.0
0.62
0.0
0.41
0.16
4,36
2,62
0.0
0.50
0.97
1.44
1.05
8.29
3.47
1,94
1.94
2.95
2.56
«.75
7.19
3.77
4,04
1.75
4,98
9,64
0.0
5.63
7.97
4.20
2.57
3.75
7.24
7,63
9,59
4.26
6.15
2.66
5.75
6.56
12.20
10.61
6.14
7.83
3.91
6.71
2.6,19
27.64
A/D
0.00
o.o
0.07
0,02
0,0
0,0
o.o
0,00
0.06
0.22
0.10
0.02
0.01
0.02
0.02
0.46
0.93
0,22
0.16
0.11
0.10
0.02
0.53
0.46
0,16
0,16
o.os
0.13
0.06
o.o
0,25
0,36
0,16
0,07
0,02
0,13
1.16
0,59
0.32
0,36
0.11
0,17
0,13
?.17
1.08
0,45
0,6,4
0,18
0,26
3,66
30. 7ft
A/D
0.00
o.o
0.15
0.04
0.0
0.0
0.0
0,01
0,06
0.33
0.09
o.o
0.01
0,01
0,03
0,51
0,76
0.16
0,07
0.15
0.09
O.OS
1.58
0.57
0.15
0.05
0.08
0.14
0,11
0.0
0.43
0.26
0.13
0.18
0,02
0,19
1.90
0,69
0,21
0.17
0.17
O.lb
0.16
2.98
0,89
0.25
0.2,7
0.23
0.20
1,39
11.35
DhY 8
B/D
0.00
0,0
0.13
0.02
0.0
0.0
0.0
0.00
0,01
0,36
0,06
0.0
O.Oi
0,02
0.03
0.12
1,20
0.18
0.16
0.12
0.12
0.04
0.27
0,71
0.14
0,16
O.OS
0.16
0.10
0,0
0.43
0,31
0.16
0.06
0.02
0.17
0,40
0,66
0.26
0.33
0.10
0.19
0.18
0.73
1.40
0.36
0,4,9
0.17
0.34
3.45
6.07
NET 3 TOTAL S
B/D
0.00
0,0
0,06
0,03
0,0
0,01
0.0
0.05
0,0
0.15
0,06
0,0
0,02
0,01
0,25
0.0
0.51
0.16
0,33
0,16
0,09
0,37
0,36
0,30
0,13
0,33
0,09
0,14
0,26
0,0
0,16
0,27
0,25
0,05
0,02
0,84
0,83
0.37
0,22
0,90
0,22
0.15
1,03
1.77
0,60
0,29
l.l«
0,26
0.20
5,98
7,73
B/D
0.00
0,0
0,19
0,04
0.0
0.01
9,0
O.OS
0,01
0.51
0.16
0,0
0,04
0.04
0.26
0,12
1.71
0,34
0,49
0,26
0,20
0.41
0.64
1.01
0,27
0.49
0.15
0,30
0.36
0.0
0,61
0.58
0.41
0.11
0.04
i.oi
1.23
1.23
0.48
1.23
0.32
0,34
1.21
2.50
2.00
0.66
1.64
0.45
0,55
9,43
13,81
-------
6
6
8
8
8
9
KCUM
HOE
AES
HEP
HCANLO
ASTKAP
ENAHAP
RCDM
HOE
AtS
HEP
HCAKLO
14.5-j
3.85
6.93
3.04
2,63
0.15
23.20
2.06
0.62
2.02
7.06
1.01
3.21
l.oa
2.04
2.79
0.98
0.07
15.23
1.41
0.35
l.ol
4.57
0.39
14.66
3.09
S.60
2.81
2.56
0,12
5.65
2.56
0.51
1,68
4.55
0,71
6.37
2.08
8.03
2.86
0,96
0,30
6.25
1.10
0.41
1.12
1.71
0.39
21.23
5.17
13.64
5.64
3.52
0.42
11.89
3.66
0.92
2.80
6.26
1.12
34.23
8.54
tt.52
6.65
6.80
0.37
16.61
9.06
2,66
4.25
19.60
3.31
16.17
9.4J
9.69
9.66
13.83
0.75
14.51-
10.10
5.37
8.04
14.41
6.61
30.82
8.56
8.45
8.54
16.24
0.52
16.76
9.30
2.91
4.27
ltt.00
6.50
30.02
8.62
17.05
12.75
14.34
0,64
17,63
9.30
3.«2
4.59
16.61
6.93
30.82
8.56
12.02
10.21
15.65
0.72
17.21
9,30
3.11
4.39
17.56
6.74
6,37
1.69
3.U3
1.33
1.15
0.06
10.16
0.91
0,27
0.68
3.09
0.44
1.40
0.47
0.69
1.22
0.43
0,03
6.67
0.62
0.15
0.70
2.00
0.17
6.50
1.35
2.45
1.23
1.12
0.05
2.47
1.12
0.22
0.74
1.99
0.31
2.79
0,91
3.52
1.25
0.42
0.13
2.73
0.48
0.18
0.49
0.75
0.17
9.29
2.26
5.97
2.47
1.54
0,16
5.21
1.60
0,40
1.23
2.74
0.49
A -«• UG/M**3
B — KG/HA/YR
C — *
0 — TG S/YR
-------
TRANSFER MATRIX UISHLAYS
SOUHCE REGIUNI 6
SCENARIO!
ABSOLUTE
AMD 302 AMU S04,
REC
2
2
2
2
2
2
2
H
4
4
4
4
4
4
5
5
5
5
5
5
S
6
6
.6
6
6
6
6
7
7
7
7
7
7
7
a
0
MODEL
ASTRAP
ENAMAP
RCDM
MOE
AES
MEP
MCARLO
ASTKAP
ENAMAP
RCDM
HOE
AES
MEP
MCARLO
ASTKAP
ENAMAP
RCDM
MOE
AES
MEP
MCANLO
ASTRAP
ENAMAP
HCDM
MOE
AES
MEP
MCARLO
ASTRAP
tNAlAP
RCDM
MOE
AES
MEP
MCARLO
ASTKAP
ENAMAP
RCDM
MOE
AES
MEP
MCARLO
ASTKAP
ENAMAP
RCDM
rtOE
AES
MEP
MCAKLO
ASTRAP
ENAMAP
A
0,5)0
7,42
3.71
0.64
2.77
1,58
0.56
0.62
6.27
2.22
3.44
3.24
1.74
1.05
0.59
5.06
1.35
2.77
1.39
0.66
0.74
0.14
1.71
0,79
• 0,99
0,24
0,16
0.32
0,06
0.0
0,26
0.91
0.16
0.11
0.05
0.22
1.01
0.37
1.36
,0.37
0.16
0.42
0,33
1,10
0,66
1,90
0,66
0.21
0,74
0.76
,1.91
A
0.20
5.51
2.40
0.48
0.60
1.53
0.32
0,59
8,77
2.25
1.36
1.41
2.65
0.56
0.60
10.61
2.12
1.40
1.04
1.37
0,47
0.19
5.04
1.54
0.84
0.25
0.37
0.26
0.06
0,0
0,b2
0,90
0,24
0,26
0.05
0.2.5
4,76
1.06
1.06
0.39
0.32
0.26
0,36
3.95
,1.49
1.26
O.o6
0.42
0,47
0.62
6. ,16
' 1
DRY S
H,
0.37
1,49
4,.S2
0.53
2,25
1.58
0.53
0.69
1.75
3.06
2.79
2,67
1.58
0.90
0.63
1.95
2.21
2.26
1.27
0.56
0.58
0,16
0,90
1,44
0,82
0.28
0,16
0,26
0.07
0,0
0,62
0.77
0.14
0,05
0.05
,0.23
0.77
0.63
1.14
0.28
0.11
0.26
,0.34
0.65
1.29
1.56
,0,56
0.16
O.b}
i0.67
1.10
, PERCENTAGE
NET S TOTAL S AMB S02 AMb SU4
b
1.25
0.61
1.94
0.46
1.27
1.21
0.32
2,01
0.79
1.32
2.02
3.24
1.79
0.58
1.93
0.13
0.95
1.75
1.41
0.63
0,47
0,64
0.40
0.62
0.78
Q.28
0.11
0.26
0.17
o.o
0.27
0.77
0.14
0.05
,0.05
0.82
,0.62
0.35
|1.03
,0.42
0.16
0.2.6
1.39
0.60
0.55
1.33
0.70
0.26
,0,47
1.67
0,96
B
1;.62
2,11
6.46
1.01
3.52
2.79
0.64
2.70,
2.53
4.40
4.61
5.91
3.42
1.47
2.56
2.08
3.16
4,01
2.67
1.21
1,00
0.60 .
1.30
2.05
1,60
0,56
0.26
0,58
0.24
0.0
0,69 ,
1.54
0.26
0.11
,0.11
1.0,4
1.39
1.16
2.17
0.70
0.26
0.56
1.73
1.45
1.84
2.69
,1.27
,0.42
1.00
2.33
2. ,09
.. c
65,79
90.66
5l'.57
42.36
79.99
64,. 66
16.26
2.21
10.59
15.21
37.64
21.77
15,37
9,18
2.56
5.79
4.92
17.38
3.51
3.02
4.14
0.95
2.95
4.56
6,79
1.46
1.32
2.68
2.12
o.o
1.93
8.09
1.11
1.42
2.24
1.84
,1.60
2.40
7.40
1.19
, 0.79
2.01
1 2.72
, 1.50
2.76
10.97
2.22
1.34
3.19
1.82
0.96
C
76.06
79,89
34, »4
31.63,
58,46
69,28
39,09
10.94
26,23
20.25
30.96
27,68
30.05
18.12
7.91
15.67
12.34
21.60
8.45
7.09
6.69
2.69
6.44
10,93
15.41
4.29
3.72
4.96
2.54
0,0
7.69
13.66
3.08
2.53
4.94
3.44
6.03
7.70
15,05
3.95
2.24
5.44
4.99
5.60
6.96
16.53
5.23
. 2.64
7.B0
. 4,37
5,41
DRY S
C
85,13
64,62
46.15
41.70
B3.43
81.59
32,4,6
5.24
15.41
16.60
37.43
21.64
17.70
14.36
3.54
9.66
6.70
17.49
3.89
3.02
5.67
1.26
4.97
6.40
9,00
2.08
1.59
3.11
1.96
0.0
3, 56
8,11
1.02
0.68
3.91
2.09
4.66
4.03
7.59
1.11
0.70
2.97
3.06
i 3.30
4.36
11.13
2.27
1.20
4.10
-------
0 HCDH
8 WOE
0 AES
0 HEP
0 HCARLO
ASTKAP
ENAMAP
RCUH
HOE
AES
HEP
9 HCARLO
2.00
3.12
2.32
0.5»
0.66
4.65
24.65
0,66
9,03
16.12
2.42
2.37
2.75
1.71
1.49
1.05
0.42
2.22
20.56
4.42
2.30
6.05
3,04
1.05
3.10
2.55
1.97
0,42
0,47
O.H
6,ia
10.00
7.07
13,36
2,05
2.00
1.33
2.03
2.01
0,26
0.42
14.41
16,00
4.29
5.20
12,94
1.53
1.05
4,43
4,50
4.70
0,60
0,95
10.52
22.26
14,29
13.07
26.31
3.50
3.11
«.7l
«»,«
2,05
1.31
1.77
12.22
17.65
37.64
45.11
33.94
6,72
7,00
13.05
14,90
7.10
3,65
5.93
22.93
19,60
31.75
36,00
30,20
12.12
17.92
6.44
7.06
2.97
1.20
3.01
10.02
10.34
36.27
44.93
33.91
0,13
10.35
6.44
0.43
5.97
1.18
6.29
40.41
45.37
36.27
43.21
52,99
14,61
10,79
6.44
7.61
«.22
1.24
4,22
31.67
32.20
36,27
44.23
41.21
10.06
10.71
0.30
0.59
0,44
0.11
0,13
0.92
4,60
1.64
1.67
3,06
0,46
0,45
0,52
0.32
0.20
0.20
0,00
0.42
3.91
0.04
0.45
1.15
0,73
0.20
0,59
0.40
0.37
0.00
0.09
0,70
1.17
1.90
1.50
2.54
0.39
0.39
0,25
0.39
0.53
0,05
0,00
2.74
3,05
0,01
0,99
2,46
0.29
0.20
0.64
0.07
0.91
0.13
0,18
3. 52
4.23
2,71
2.40
5.00
0,66
0.59
A »• UG/H**3
B -• KG/HA/YR
c — x
0 « TG 8/YR
-------
THANSftH NATK1X DISPLAYS
SOURCE REGIONl 9
SCENARIO!
ABSOLUTE
i
AM8 802 AMU S04
REC MODEL
ASTRAP
ENAMAP
KCOrt
MOE
AES
HEP
HCAHLO
2 ASTHAP
2 ENAHAP
2 RCDM
2 MOE
2 AES
2 »EP
2 MCARLO
3 ASTHAP
3 ENAMAP
3 RCOM
3 HOE
3 AES
3 HEP
3 HCAKLO
4 ASTHAP
4 ENAMAP
4 RCOh
4 hOE
4 AES
4 HEP
4 MCARLO
5 ASTRAP
5 ENAMAP
5 RCDrt
5 HOt
5 AES
5 HEP
5 HCARLO
'6 ASTRAP
6 ENAHAP
6 RCOH
6 MOE
6 AES
6 HEP
6 HCAKLO
7 *STRAP
7 ENAMAP
7 RCOH
7 MOE
7 AES
7 MEP
7 MCARLO
6 ASTRAP
6 ENAHAP
. . A
0.03
0.16
0,56
0.20
0.21
0.07
2.62
25.72
45.14
5.37
2.11
4,74
7.11
6,76
19,67
49.70
7.91
5.66
23.07
14.02
9.07
1.14
16.39
5.99
3.33
3. IS
1.40
1.65
0.37
0.0
1.61
1.61
1.46
0.50
0.24
1.70
11.91
2.13
3.46
4.95
1.59
1.70
3.37
16,72
3.50
3.67
7,68
3.06
1.79
0.42
6.23
A
0.01
0.64
0.50
0.17
0.09
0,26
0,39
3,75
16.21
1.60
0.66
It25
2.65
0.93
4.50
20.27
2.29
1.31
4,40
6.14
1.25
1.16
17.44
2.43
1.14
1.66
2.33
0.62
0,36
0.0
1.69
0.64
1.46
1.06
0.15
1.24
11,01
1.79
1.19
2,65
2.67
0,69
1,80
13.61
2.03
1.20
3.53
3, pi
0.62
0.16
7.79
URY S
i B
< i
0.02
0.0V
0.74
0.16
0.19
0.11
0.93
11.10
7-,63
5.66
1.70
3.79
4,74
1.96
13.90
9.22
d.33
(4.69
16,57
11.10
2,66
1,36
4.71
6.62
2.69
2.65
1.21
1,53
0.37
0.0
2,44
1.31
1.33
0,43
0.17
1,64
2.95
2.76
2.79
4.17
1.36
1.10
' '3,10
4.24
4.16
3.12
6.44
'2. 56
',».»9
0.2fl
1.91
i
PERCENTAGE ;
NET 5 TOTAL 9 AMB 502 AHB SU4
B
0,06
0.04
0.32
0,15
0,19
0.13
0.37
10.13
2.71
2,43
1.17
3.41
4.05
0,68
12.87
2.63
3.57
3.03
6.25
5,25
1.14
4.01
3,00
2.84
1.67
3,. 22
1.34
0.62
0.30
0.0
1.05
1.03
1.14
0.26
0,15
2.21
2.23
l.l'
i.;95
3. '03
1.66
, °«>9
4.07
3.27
1.78
2.13
3.79
2,91
0.6,0
0.47
P.99
B
1 1
0,10
0,14
1.06
0.32
0.36
0,24
1.29
21.23
10.34
8.11
2.66
7.20
a. 79
2.64
26.77
11.66
11.90
7.72
24.63
16.43
4.01
5.37
7,71
9,46
4,56
5.86
2.56
2,35
0.67
0,0
3.49
2,, 34
2.46
0.69
0,30
3. '6 4
5.18
3.97
4.73
7,20
,3.02
!i.79
, 7, .18
7.51
5.94
5.24
10.23
5.49
1.79
, 0.76
2,90
C
4,59
2,01
7,76
12.93
6.02
4.00
79,13
93.10
76,28
36,76
23.03
31,68
62,92
SB. 91
84.67
56,91
28,93
36.76
50,12
61,91
51,02
7.62
26.26
34.40
29,64
19,43
11.67
15,65
9.64
o.o
13.32
14,2'0
8.06
6,77
1,0.34
14.00
1.8.75
13,76
16.59
16.10
, 7»9S
8.12
26.27
25.52
14.66
22.43
25.61
19,45
7.75
0.98
3.15
i C
4,34
9.2»
7. id
10.94
9.16
11.66
46.51
69.15
46.49
14.42
15.05
24.62
30.26
29.20
59.36
29.39
13.30
20.21
35.69
42.13
22.92
16.03
22.29
17.24
20.95
31.45
23.57
15,55
11,29
0.0
15,61
13,05
19.01
10.42
14.01
17.40
16,58
13.09
17,00
26.62
18.97
14.28
25.04
19,96
'12.24
15.69
27,30
25.67
10.1*.
1.25
, P.B1
PHY S
C
I
3,73
5.16
7.57
12.61
7.03
5.79
57.54
84.06
69.04
30,62
22.78
30.97
53,14
31.74
76.20
45.73
25.19
30.33
57.06
56.26
28.13
10.5?
25.95
29.40
29.37
19.66
12.22
16.07
9.95
0.0
14.02
14.16
9.59
7.15
12.46
15.21
17,65
13.57
18.55
16.46
9.09
12.42
28,26
21.55
14.04
22.23
25,96
19,64
9.30
oev«
4,45
UNIT
MET S TOTAL S AMB 502 AMB 804
C
4.58
6.34
7.57
ll.es
10.46
7.45
47.29
56.30
59.65
30.62
20.43
23.25
44.18
27.85
48.56
43,31
25.19
32.10
24.95
36,03
21.43
16.71
23.77
29.46
26.59
22,64
13.96
15.70
6,49
0.0
14.02
13.72
13.51
7,01
13.95
10.51
11.46
13.57
17.80
14.98
13.25
14,94
13.09
12.08
14.04
20.29
16.56
22.18
10.23
0.91
1.39
C
I
4,41
5.51
7.57
12.34
6.41
6.55
51.86
69.43
66.31
30.62
21.76
26.76
46.51
30.25
60.46
45.17
25.19
34.54
43.09
49,80
25.94
14.57
25.05
29.46
26.16
21.19
13.07
17.06
8.04
0.0
14.02
13.97
11.07
7.06
12.24
12.11
14.41
13,57
16,24
15.60
10.99
13.26
17.05
16.07
14.04
21.40
21.45
20.69
9.57
0,92
2.54
A/0
I
0.01
0,09
0,30
0,10
0,11
0.04
1.51
13.76
24,18
2.66
1.13
2.54
3,81
3.62
10.53
26,62
4.24
3.14
12.36
7,51
4.86
0.61
8.76
3.21
1.78
l.*9
0.75
0.99
0,20
o.o
0.97
0.86
0,76
0.27
0.13
0.91
6.J6
1.14
I.fl5
2.65
0,65
, 0,91
1.81
10.03
1.68
2. Op
4.11
1,64
0,96
0.23
3.34
A/0
0,01
0,34
0.27
0.09
0,05
0,14
0,21
2.01
6,66
0,66
0,35
0,67
1.42
0.50
2.41
10.86
1.23
0.70
2.36
4.36
0.67'
0.62
9,34
1.30
0.61
0,99
1.25
0,44
0.19
o.o
0.91
0,45
0.79
0.56
0,08
0,67
5,90
0,96
0,64
1.42
1.43
0.37
0,97
7.29
1,09
0,64
1.89
2.04
0.33
Oe09
.1.17
DRY S
B/D
0,01
0.05
0.40
0.09
0.10
0.06
0.50
5,95
4,09
3,04
0.91
2.03
2.54
1.06
7.45
4.94
4.46
2.51
9,95
5.99
1.54
0.73
2.52
3,55
1.44
1,42
0,65
0.62
0.20
0.0
1.31
0.70
0,71
0.23
0.09
0,68
1.56
1.49
1.49
2.23
0.73
0.59
1.66
2.27
2,23
1,67
3.45
1.38
0.64
0,15
1.02
MET 8 TOTAL 3
8/0
0.04
0,02
0.17
0,06
0,10
0.07
0,20
5,43
1.45
1,30
0,62
1,63
2,17
0,47
6,69
1,41
1.91
1.63
3.35
2.61
0.61
2.15
1.61
1.52
1,00
1,73
0.72
0,44
0,16
0.0
0.56
0,55
0,61
0,14
0,08
S.16
1.20
0.64
1.04
1,62
0,69
0.37
2,16
1.75
0.95
1.14
2,03
1.56
0.32
0,25
0.53
6/0
0,05
0,07
0.57
0,17
0,20
0,13
0,69
11.37
5.54
4,34
1,53
3,66
4,71
1.52
14,34
6.35
6,37
4,14
13.30
6,60
2.15
2,67
4.13
5,07
2.44
3.15
1.37
1.26
0.36
0,0
1,87
1,25
1.32
0.37
0.16
2.06
2.78
2.13
2.54
3.86
1.62
0.96
3,84
4,03
3.18
2,81
5,48
2,94
0,96
0,40
1,55
-------
e KCUH
e HUE
6 AES
6 HEP
6 MCAKLO
9 ASTHAP
9 tNAMAP
9 KCUH
9 HOE
9 AES
9 HEP
9 MCAHLO
1.33
1.75
a. 45
2.71
0,60
0,04
2.46
0,16
0,11
o.is
0.15
0.30
1,07
0,64
1.97
3.70
0.32
0.02
4.59
0.28
0.13
0.21
0,52
0.17
1.72
1.^2
3.79
2.63
0.52
0,02
0,65
0.27
0,09
0.19
0.15
0,19
0.74
1. 01
2.27
1.85
0,32
0,03
0,46
0.12
0,10
o.o
0,09
0.17
2,45
2.42
6,07
4,46
0,64
0.05
1,31
0.39
0,19
0.19
0.24
0,35
3.1J
3,69
5,47
6,11
2.08
0,09
1.76
0,67
0,49
0.32
0.36
0,98
5.41
S.57
9,36
12,81
4.47
0.22
4.37
1,96
1.97
1.04
1,65
2.86
3.56
1.92
5.71
6,00
3.32
0.11
2.52
0.98
0.52
0.48 •
0.59
1.71
3.56
1.17
4.83
8,25
4,74
0.09
1.30
0.98
0.64
0.0
0,91
3.00
3.5b
4.02
5.35
6.11
3.74
0.0V
1,90
0.96
0.65
0,30
0.66
2.14
0.71
0,94
2,39
1.45
0,43
0,02
1,33
0.06
0,06
0,08
0.07
0,16
0.57
0.34
1.06
1.96
0.17
0.01
2.46
0.15
0.07
0.11
0.26
0,09
0.92
0.76
2.03
1.01
0.28
0.01
0.46
0.14
0.05
0.10
0.06
0.10
0.39
0.54
1.22
0.99
0,17
0.02
0.25
0.06
0,05
0.0
0.05
0,09
1.31
1.30
3.25
2.40
0,45
0,03
0.70
0.21
0,10
0,10
0,13
™ 9 " w
0.19
A — UG/M**3
B « KG/HA/YK
C — X
D •• T6 S/YR
-------
TRANSFER HATPIN DISPLAYS
SOURCE. REGION! 10
SCENARIO*
ABSOLUTE
PERCENTAGE
UNIT
/
1C MODEL
1 ASTRAP
1 ENAMAP
HCDM
MOE
AES
MEP
MCARLO
2 ASTRAP
2 ENAMAP
2 RCDH
2 MOE
2 AES
2 HEP
2 hCARLO
ASTRAP
ENAMAP
RCDM
HOE
AES
HEP
MCARLO
4 ASTRAP
4 ENAMAP
4 RCDM
4 MOE
4 AES
4 MEP
4 MCARLO
5 ASTRAP
5 ENAMAP
5 RCOM
5 HOE
5 AES
5 MEP
5 MCARLO
ASTRAP
ENAMAP
RCOM
MOE
AES
MEP
MCAkLO
7 ASTRAP
7 fcNAMAP
7 RCOM
7 MOE
7 AES
7 MEP
7 MCARLO
a ASTRAP
8 ENAMAP
1Mb 302 A
A
0.00
0.0
0,05
0,06
0.09
0.01
0.05
0.07
0.06
0.22
0.37
1.07
0.37
0.33
0.36
1.46
0.60
0.76
2.39
1.11
1.04
12.35
16.29
1.37
•3,54
7.87
7.63
4,47
0.77
0,0
6,29
1,43
2,77
1.32
0.59
3.89
13.06
1.91
7.10
15.44
12.51
0.60
1.67
4.76
1,16
1.3*
4.57
4.7*
0.52
,0.04
0,14
Mb 504
A
0.00
0,0
0.11
0.08
0.16
0.01
o.oi
0.02
0,06
0,30
0.20
0.50
0.60
0.12
0,10
1.55
0,57
0,32
1.00
1.36
0,33
3.71
6,31
0,62
0.06
1.50
3.24
0,72
0.6Q
0.0
1.35
0,57
1,43
2.05
0.24
1.32
7.07
1.05
0.94
2.23
4 ,5'2
0.24
0.48
3.20
0.65
0.45
1.71
2.9b
0.20
0.02
0.55
DRY S
B
0,00
0.0
0.09
0.06
0,0
0,01
0,04
0,04
0,02
0.34
0.31
0,91
0,46
0,19
0.22
0,40
0.62
0,61
2,05
1.03
0.61
9.99
3,00
1.63
2.84
6.37
5.03
1.60
0.75
0.0
6,41
1.15
2.27
1.16
0.38
3.00
2.77
2.24
5.65
12. SO
8.25
0.39
1.07
1.10
1,46
1.09
3.67
3.75
0.29
0.02
0.09
NET S 1
B
0.00
o.o
0,04
0,07
0,0
0.04;
0.01
0.23
0.00
0.15
0,24
0.23
0.40
0.11
0.76
0,00
0.35
0,45
0,68
0.58
0.33
9,09
1.06
0.70
1.66
3.41
4.17
0.66
0.30
o.o
2.75
0.84
1.14
0.67
0.25
1.02
3,61
0.96
3.53
3.67
3.7,2
0.24
2,49
1.59
0,63
0.7ib
1.02
2.21
0.20
0,14
0,04
rOTAL S <
, 8
0,00
0,0
0,13
0,13
0.0
0.05
O.OS
0.27
0,02
0,49
0,55
1,14
0.86
0.32
0.96
0,41
1.17
1.06
2.73
1.60
0.94
19.08
4.06
2.33
4,70
9,78
9,99
2.27
1,05
0.0
9,15
1.99
U61
0,63
4.02
6.39
3.20
9.18
16.37
11.96
0.61
3.56
2.69
2.09
i »6,6
5 .60
5.96
0.46
0 . 1,7
.0 .,13
MB S02
C
0.03
0.0
0.63
5.06
2.63
0,63
1.32
0.24
0.13
1.54
4.09
7.19
3.24
2.68
1.54
1.67
2.20
4,75
6.02
4,90
5.64
84,39
28,09
7.85
31.55
40.57
63.65
37.86
20.17
0,0
46,25
12.62
16.68
17.76
25.13
31.90
20.60
12.39
30.20
50.2,4
62.66
2.88
13.99
fa. 51
4.87
7.05
15.37
30.21
,2.24
,0,09
0.07
1MB S04
C
0.04
0.0
1.55
5.06
15,39
0.54
1.46
0.45
0.17
2.70
4.47
9.84
6.67
3,69
1.33
2.24
3.33
4.91
6.12
7,02
6,06
57.66
8.07
5.83
15.79
25.41
32.77
13.63
18.83
0.0
12.64
8,76
16.42
19.75
22.13
10.43
13.20
7.69
13,35
22.35
32.11
4.06
6.67
4.69
5.11
5.VS
13,21
19.41
3,3.0.
0,13
.0,49
OHY S
C
0.03
0.0
0.93
5.06
0.0
0.61
2.16
0.31
.0,14
1.05
4.10
7.43
5.16
3.03
1.22
2,00
2,47
4.75
6,29
5,35
6.00
77.81
16.53
7.27
31.06
47.10
56.60
16.95
20.25
0,0
36,75
12.4ft
16.43
19.2
13.50
10.03
23.14
f.toS
Ib.hO
10.94
32.34
IV, 09
29,65
5.10
0.00
,S,89
4,93
7.20
7.94
16.00
3.a3
0,28
0.06
fOTAL 3 t
C
0,03
0,0
0.93
5.06
0.0
1.27
1.90
0.87
0.10
1.85
4.15
4.22
4.75
3.40
2.22
1.55
2.47
4.76
4.73
4,66
6,10
51,62
13.20
7.27
29.03
35.26
51,07
16,45
12.66
0.0
36.75
11.89
15.32
18.73
25.63
15.17
17.75
10.94
35.38
35.92
43,47
4.54
6. 45
5.76
4.93
7.57
11.91
22. 6«
2.50
0.20
0.12
kMB 302 A
A/D
0.00
o.o
0.04
0,06
0,06
0,01
0.04
0.06
0,07
0,19
0.32
0.91
0.31
0,28
0,30
1,24
0,51
0,64
2.02
0.94
0,68
10.46
13,60
1.16
3,00
6,67
6,47
3.79
0.66
o.o
5.33
1 .21
2.35
1.12
0.50
3.29
11.09
1.02
6.02
13.08
10.60
0.51
1,42
4.05
0.99
1,15
3.07
4,03
0,44
0,03
0.12
Mb S04
A/D
0,00
o.o
0.09
0.07
0.13
0,01
0,01
0,02
0.05
0.25
0.17
0.42
0,51
0,10
0,09
1.31
0,49
0,27
0,85
1.15
0.28
3.15
5.35
0.70
0.73
1.27
2.75
0.61
0,51
0.0
1.15
0.46
1.21
1.74
0,20
1.12
6.67
0.69
0.79
1 .89
3.83
0.20
0.41
2.71
P. 72
0.36
1.45
2.44
0.17
0,02
0,47
DRY S
B/D
0.00
0.0
0,08
0,05
0.0
0,01
0.03
0.03
0,01
0,29
0,26
0.77
0.39
0.16
0.16
0,34
0.69
0.52
1.73
0.67
0.52
6,46
2.54
1.36
2.41
5.39
4,94
1.36
0.63
0.0
5,43
0.98
1.93
0.90
0.32
2.54
2.35
1.90
4.79
10.60
6.99
0.33
0.90
0.93
1.24
0.93
3.2d
3.18
0.25
0.02
0.06
HET 8 1
B/D
0,00
o.o
0,03
0.06
0.0
0.03
0.01
0.19
0.00
0.12
0.20
0.19
0.34
0.09
0.65
0.00
0.30
0.38
0.56
0.49
0,28
7.71
0,90
0,59
1.58
2.89
3.53
0,56
0.25
o.o
2.33
0,71
0.96
0.57
0.21
1.54
3.06
0.81
2.99
3.26
3.15
0.20
2.11
1.35
0.53
0.65
1.54
1.67
0.17
0,12
0.03
OTAL 8
B/D
0.00
0,0
0.11
0.11
0.0
0.04
0.04
0,23
0.01
0,42
0,46
0.96
0.73
0.27
0.83
0,35
0,99
0,90
2.31
1.36
0.60
16,17
3.44
1.96
3,96
6,29
8,47
1,92
0,89
0.0
7,75
J.69
2,89
1.55
0,53
4,08
5,41
2,72
7.78
13,87
10,14
0.52
3.01
2.26
1.77
1.57
4,82
5.05
0,41
0,14
0.11
-------
8 HCDM
6 HOE
B AfcS
e HEP
6 HCARLO
9 A5TKAP
9 ENAMAP
9 ROOM
9 HOE
9 AES
9 HEP
9 hCAKLO
0.22
0,21
0.34
0.22
0.26
0.00
0.11
0,04
0.03
0.02
0,04
0.02
0.36
0.16
0.20
0.47
0,12
0.00
0,o5
0.12
0.05
0.05
0.14
0.01
O.ib
0.18
0.23
0.26
0.15
0.00
0.10
0.09
0.03
0.0
0,04
0,01
0.16
0.16
0,23
0.19
0.12
0.00
0,04
0.04
0.03
0,0
0,0
0,01
0,52
0.34
0.45
0.47
0.27 .
0.00
0,14
0.13
0.06
0.0
0.04
0.04
0.51
0.47
0.42
0.51
0,73
0.00
O.OB
0.16
0.14
0.05
0.10
0.06
1.79
l.«
0.97
1,64
1.66
0,01
0.62
0.67
0.75
0.23
0.45
0.20
0.75
0.49
0.34
0,66
0.97
0.00
0,29
0.33
0.15
0.0
0.14
0.11
0.75
0.66
0.46
0.64
1.76
0,01
0.11
0.33
0.2S
o.o
0.0
0.21
0.75
0.56
0.40
0.85
1.21
0.01
0.20
0.33
0.21
0.0
0.10
0.21
0.16
0,16
0.29
0.19
0.24
0.00
0,10
0,03
0,03
0.02
0.03
0,02
0,30
0,14
0.17
0.40
0.10
0.00
0.55
0.10
0,04
0.04
0.12
0,01
0.31
0,15
0,19
0.24
0.13
0.00
0.06
0.06
0.02
0.0
0.03
0,01
0,13
0.13
0,19
0.16
0.10
0.00
0.03
0.03
0.03
0,0
0,0
0,01
0.44
0.26
0,39
0.40
0.23
0.00
0.12
0,11
0,05
0,0
0.03
0.03
A -• UG/M**3
B -- KG/HA/YR
C « X
0 « T6 S/VR
-------
TNANSFEh MATRIX DISPLAYS
SOUKCE KEGIONI 11 SCENAKIOl
ABSOLUTE
Ahb S02 AMb S04
NEC
2
2
2
2
2
2
2
3
3
3
3
3
3
3
-------
tt KCUM
8 MOE
6 AE5
0 HEP
6 MCARLO
9 ASTKAP
9 ENAMAP
9 RCDM
9 hOE
9 AES
9 HEP
9 MCAKLO
0,00
0.01
0.0
0.01
0,00
0.0
0.07
0.00
0,00
0.0
0.0
0.0
0.01
0.01
0.0
0.01
0,0
0.0
0.26
0.00
0.00
0.0
0,00
0.0
0.01
0.01
0,0
0.01
0,0
0,0
0.05
0,00
0,00
0.0
o.o
0.0
0,00
0.01
0.0
0,01
0,0
0.0
0.02
0.00
0.00
0,0
0.0
o.o
0.01
0,02
0.0
0.02
0,00
0.0
0.06
0.00
0,00
0,0
o.o
0,0
0.01
0,02
o.o
0.02
0.00
0.0
0.05
0.00
0.01
0.0
o.o
0,0
0.03
0.10
0,0
0.02
0.0
0.0
0,25
o.os
0,07
0,0
0.01
o.o
0,01
0.02
0.0
0.02
0.0
0.0
0.14
0.00
0.01
0.0
0,0
0.0
0.01
0.04
0.0
0.06
0.0
0.0
0.05
0.00
0.02
0,0
0.0
0,0
0.01
0.03
0,0
0,0«
0.01
.0.0
0,09
0.00
0,02
0.0
0.0
0,0
0.02
0,05
0,0
0.05
0,01
o.o
0,39
0.00
0.01
o.o
o.o
o.o
0.04
0.06
o.o
0.03
o.o
o.o
1.41
0.01
0.02
o.o
0.01
0,0
0,04
o.os
0.0
0,04
0.0
0.0
0.26
0,00
0.01
0,0
0,0
0,0
0.02
0.05
0.0
0.07
0.0
0,0
0.09
0.00
0.02
0.0
0,0
0.0
0.05
0.10
0.0
0.11
0.01
0.0
•V J W
0.34
0.0}
0.03
0.0
o.o
0.0
A •>• UG/M**3
B -• KG/MA/tK
C « X
0 — TG SXVR
-------
Appendix C
Initial Inventory-of Mesoscale Models
-------
TABLE
Model Developer and Name
NCAA Air Resources
Laboratory AJRL/MTQF
Drexel University, NCAR,
Brookhaven National.
Laboratory DU-NCAR-BNL/
LAMPS
EPA Meteorology-Laboratory
EPA/RAQSM
Environmental Research
and Technology, Inc.
ERT/MESOPLUME
Environirental Research
and Technology, Inc.
ERT/MESCPUFF
Environmental Research
and Technology
ERT/MESOGRID
Lawrence Livermore
Laboratory
LLL/ADPIC
Battelle Pacific North-
west Laboratory
PNL/STRAM
Systems Applications,
Inc.
SAI/RTM
Systems Applications,
Inc.
SAI/ROM
. INVENTORY OF MESOSCALE AIR QUALITY SIMULATIONS MODELS
References Model Type
Kreitzburg and Leach Eulerian/Primitive
(1978) equation (3-D)
Lamb (1980)
Eulerian (3-D)
Benkley and Bass (1979) Advective Lagrangian
(source-oriented puff
segment)
Bass et al. (1979)
Morris et al (1979)
Lange (1978)
Hales et al. (1977)
Durran et al. (1979)
Stewart, et al. (1981)
Advective Lagrangian
(source-oriented puff)
Eulerian (3-D)
Adveetive Lagrangiarr
(source-oriented—
plume segment)
Long or Short
Term Assessment
Draxler (1977, 1979) Advective Lagrangian Short term
(source-oriented puff)
Short term
Short term
Short term
Short term
Short term
Eulerian/particle-in- Short term
cell (3-D)
Short term
Eulerian (2-1/2-Layer) Short term
Wbjcik et al. (1978) Euleeian (2 1/2-Layer) Short term
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