CANADA - UNITED STATES
Transboundary PM
Science Assessment
>ji\ lr
The report was undertaken by the Canada-U.S.
Subcommittee on Scientific Co-operation, in support of the
Canada-U.S. Air Quality Agreement
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This report is available electronically at:
http://www.msc-smc.ec.gc.ca/saib
http://www.epa.gov/airmarkt/usca/index.html
Additional hard copies may be obtained from:
Science Assessment and Integration Branch
Atmospheric and Climate Science Directorate
Meteorological Service of Canada
4905 Dufferin Street
Toronto, Ontario CANADA M3H 5T4
(416) 739-4433
ฉ Minister, Public Works and Government Services, 2004
ISBN: 0-662-38678-7
Catalogue No. En56-203/2004E
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CANADA - UNITED STATES
TRANSBOUNDARY PARTICULATE MATTER
SCIENCE ASSESSMENT
A REPORT BY THE
CAN AD A-U.S. AIR QUALITY COMMITTEE
SUBCOMMITTEE 2: SCIENTIFIC COOPERATION
DECEMBER 2Q04
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Acknowledgments
The following individuals have contributed to the preparation of this report:
1 CANADA
UNITED STATES OF AMERICA 1
Keith Puckett, Co-chair of SC2
William Russo, Co-chair of SC2
Heather Morrison, Secretariat of SC2
Laurel Schultz, USEPA
Carrie Lillyman, Environment Canada
Fred Dimmick, USEPA
Bob Vet, Environment Canada
Tom Braverman, USEPA
Jeff Brook, Environment Canada
Joe Tikvart, USEPA
Chul-Un Ro, Environment Canada
Bill Kuykendal, USEPA
Louis-Philippe Crevier, Environment Canada
Neil Frank, USEPA
Sophie Cousineau, Environment Canada
Rich Poirot, VTDEC
Mike Moran, Environment Canada
Nash Gerald, USEPA
Paul Makar, Environment Canada
John Bachmann, USEPA
Veronique Bouchet, Environment Canada
Donna Kenski, Lake Michigan Air Directors Consortium
David Niemi, Environment Canada
Rob Wilson, USEPA
Marc Deslauriers, Environment Canada
Alan Rush, USEPA
Tom Dann, Environment Canada
Mark Schmidt, USEPA
Julie Dion, Environment Canada
Jeff West, USEPA
David Waugh, Environment Canada
Colin di Cenzo, Environment Canada
Ann McMillan, Environment Canada
Harry Hirvonen, Canadian Forest Service
" T^3
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Canada - United States Transboundary PM Science Assessment
In March, 2003, this report underwent an external scientific peer review. The following individuals
reviewed the report:
DR. PRAVEEN AMAR
Director, Science and Policy
NESCAUM, Boston, USA.
DR. WEIMIN JIANG
Research Officer, National Research Council of Canada
Ottawa, Canada
DR. JACK McCONNELL
Professor, Department of Earth and Space Science and Engineering
York University, Toronto, Canada
DR. ARMISTEAD RUSSELL
Professor, Environmental Engineering
Georgia Institute of Technology, Atlanta, USA.
DR. BRET SCHICHTEL
National Park Service, Air Resource Division
Denver, USA.
VI
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Table of Contents
Summary xv
1. Introduction I
2. Foundation for the Trans boundary PM Issue in North America 3
2.1. PM is recognized as an important health concern 3
2.2. High ambient levels of PM and its precursors are observed in North America 4
2.3. Precursors of PM generally contribute to the acidification of ecosystems 4
2.4. PM and its precursors are a significant cause of visibility impairment 5
2.5. PM and its precursors can be transported long distances 6
2.6. PM and its precursors are transported between the United States and Canada 6
2.7. Reductions in S02 are likely to result in reductions in PM2 5, visibility impairment
and acid deposition 7
3. Ambient Observations in Border Regions 9
3.1. Levels of and Trends in PM2 5 9
3.1.1. Integrated Observations between Canada and the United States 9
3.1.2. Canada 13
3.1.3. United States 14
3.1.3.1. Spatial Variations in Annual Average PM2 5 Concentrations across
the United States 14
3.1.3.2. Annual Means of PM2 5 at U.S. FRM Sites by Region 15
3.1.3.3. Annual Means of PM2 5 at U.S. FRM Sites within 300 km of Border by Region ..15
3.1.3.4. Annual Means of PM2 5 at U.S. IMPROVE Sites by Region 16
3.1.3.5. Three year Annual Means and 98th Percentiles (2000-2002) of PM2 5 for
U.S. Sites (FRM & IMPROVE ) within 200 km of the Canadian Border 16
3.1.3.6. Long-term Trends in PM2 5 17
3.2. Ambient Characterization of PM2 5 18
3.2.1. Canada 18
3.2.1.1. Chemical Composition of the Organic Fraction of PM2 5 19
3.2.2. United States 20
3.3. Levels of Sulphate and Nitrate Deposition 23
3.3.1. Wet Sulphate Deposition and Critical Load Exceedances 23
3.3.2. Wet Nitrate Deposition 24
3.4 Key Science Messages 25
4. Emissions 27
4.1. Development of Emission Inventories 27
4.1.1. Development of Canadian and U.S. Emission Inventories for REMSAD and AURAMS 27
4.1.1.1. Base Year Inventories 27
4.1.1.2. Base Case Inventories for 2010 and 2020 27
4.1.1.3. Control Case Inventories for 2010 and 2020 28
4.1.2. Processing of Canadian and U.S. Emission Inventories for REMSAD and AURAMS 29
4.1.2.1. Processing of Emission Inventories for REMSAD 29
4.1.2.2. Processing of Emission Inventories for AURAMS 29
4.1.3. Development and Processing of Emission Inventories used for CMAQ 30
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Canada - United States Transboundary PM Science Assessment
4.2. Description of Emissions in the United States and Canada 30
4.2.1. Emissions used in AURAMS and REMSAD 30
4.3 Key Science Messages 40
5. Air Quality Model Applications 41
5.1. Results of REMSAD Control Strategy Modelling 41
5.1.1. REMSAD Results 42
5.1.2. Conclusions 57
5.2. Results of AURAMS Control Strategy Modelling 57
5.2.1. Model Set-up, Emission Files and Post-Processing 58
5.2.2. Evaluation of Emission Reduction Impacts 59
5.2.2.1. Winter Period 59
5.2.2.2. Summer Period 65
5.2.3. Comparison with REMSAD results 66
5.2.4. Summary and Conclusions 71
5.3. Results of CMAQ Modelling in the Georgia Basin - Puget Sound Region 72
5.3.1. Qualitative Analysis of Simulations for the 2000 Base Case 73
5.3.1.1. Summer PM2 5 73
5.3.1.2. Winter PM2.5 73
5.3.2. Significance of Transboundary Transport 74
5.3.2.1. Qualitative Analysis of the No-U.S. Anthropogenic Emissions Scenarios 74
5.3.2.2. Qualitative Analysis of the No-Canadian Anthropogenic Emissions Scenarios ..74
5.3.2.3. Summary and Conclusions 75
5.3.3. Impacts of Forecast Emissions for 2010 and 2020 75
5.3.3.1. Qualitative Analysis of Simulations for the 2010 Forecast 75
5.3.3.2. Qualitative Analysis of Simulations for the 2020 Forecast 76
5.3.3.3. Summary and Conclusions 76
5.4 Co-benefits of Emission Reductions 76
5.5 Key Science Messages 79
6. Relationships between Sources and Ambient Levels of PM 81
6.1. Attributing Sources to Ambient Levels of PM2 5 81
6.1.1. Observational Receptor-Oriented Analyses 81
6.1.1.1. Quantifying the Transboundary Transport of PM2 5 using a
Geographic Information System 81
6.1.1.2. Sources of PM2 5 to Urban Areas in the United States 83
6.1.1.3. Sources of PM2 5 to Eastern North America 84
6.1.1.4. Back Trajectory Analysis of PM2 5 Transport to Eastern Canada 84
6.1.1.5. Sources of PM to Glacier National Park, Montana 85
6.1.1.6. Sources of PM and Acid Rain Precursors to Southwestern Ontario: Study 1 85
6.1.1.7. Sources of PM and Acid Rain Precursors to Southwestern Ontario: Study 2 89
6.1.1.8. Sources of PM2 5 to Southern Quebec 89
6.1.1.9. Sources of PM2 5 to Nova Scotia and New Brunswick 89
6.1.2. Positive Matrix Factorization 91
6.1.2.1. Sources of PM to Toronto, Ontario and Vancouver, British Columbia 91
6.1.2.2. Comparability of Receptor Model Results on PM2 5 Sources in Toronto 92
6.1.2.3. PMF and Back Trajectory Analysis at Eight U.S. Cities 96
6.1.2.4. Compilation of PM2 5 Source Apportionment Studies from the United States ..97
6.1.2.5. Source Locations and Time Series Analyses of PM in U.S. Cities 98
6.1.3. Satellite Observations 99
6.1.3.1. Impact of PM from Forest Fires to Eastern North America 99
6.2 Key Science Messages 99
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Table of contents
7. Conclusions 101
8. References 105
Appendix: REMSAD and AURAMS Model Performance 111
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Canada - United States Transboundary PM Science Assessment
LIST OF TABLES
Table 2.1: Ambient Air Quality Objectives and Standards for PM2 5 4
Table 4.1: Country-total anthropogenic emissions for PM and PM precursors on the REMSAD
domain for the 2010 base, 2010 control, 2020 base, and 2020 control inventory scenarios
used as REMSAD input 31
Table 4.2: Country-total anthropogenic emissions for PM and PM precursors on the AURAMS
domain for the 1996, 2010 base, 2010 control, 2020 base, and 2020 control inventory
scenarios used as AURAMS input 31
Table 5.1: Characteristics of ten AURAMS simulations 59
Table 5.2: Percent differences between scenario emissions of primary PM2 5 and PM precursors
on the AURAMS domain for three pairs of scenarios 59
Table 6.1: Average concentration and percent mass selected State contributions to Class I areas 83
Table 6.2: Proportions (percent) of PM2 5 mass with respect to 3-day back-trajectory at
950hPa (1999-2002) 89
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Table of contents
LIST OF FIGURES
Figure 2.1: Average PM2 5 concentrations 5
Figure 2.2: 3-day back-trajectories arriving at Simcoe, Ontario, for the warm season
(May-September), 1998 and 1999 6
Figure 3.1: Mean annual concentration of PM2 5 at Canadian dichot and U.S. FRM monitors
in the border region for the data years 2000-2003 9
Figure 3.2: 98th percentile PM2 5 concentrations at Canadian TEOM and U.S. FRM sites
for the data years 2000-2002 10
Figure 3.3: Long-term trends in the precursor gases S02 and particulate SOJ at rural
CAPMoN and CASTNet sites, 1989-2002 11
Figure 3.4: Trends in total nitrate (gaseous HNO3 and particulate NO^) and
particulate NHJ at rural CAPMoN and CASTNet sites, 1989-2002 12
Figure 3.5: Trend in annual median PM2 5, 1984-2002 (median, 75th, 25th percentile) 13
Figure 3.6: Three year mean, 10th and 98th percentile PM2 5 concentrations, 1997-1999 13
Figure 3.7: The 98th percentile of Canadian 24-hour PM2 5 concentrations in 2001 14
Figure 3.8: U.S. regions used for data analysis purposes 14
Figure 3.9: County-level maximum annual mean PM2 5 concentrations, averaged over three years, 2000-2002 15
Figure 3.10: Annual PM2 5 means at U.S. FRM sites by region, over three years, 2000-2002 15
Figure 3.11: Annual means of PM2 5 at U.S. FRM sites within 300 km of the Canadian
border by region, over three years, 2000-2002 16
Figure 3.12: Annual PM2 5 means at rural U.S. IMPROVE sites by region 16
Figure 3.13: 3-year annual means and 98th percentiles (2000-2002) for U.S. sites
within 200 km of the border (FRM) 17
Figure 3.14: Average measured annual PM25 concentration trend at IMPROVE sites, 1992-2001 17
Figure 3.15: The fractional chemical composition of PM2 5 at various urban sites
based on 1995-98 NAPS dichot data 18
Figure 3.16: PM2 5 speciation data for NAPS network sites in Canada September 2001-August 2002 19
Figure 3.17: The relative composition of PM2 5 mass at Egbert (ON) during (a) a wintertime
PM2 5 episode December 30, 1995, and (b) a summertime episode June 11, 1999 20
Figure 3.18: Annual average composition of PM2 5 in the United States by region 21
Figure 3.19: Summary of urban speciation data for PM2 5 in the United States (EPA Speciation Network) 22
Figure 3.20: Summary of rural speciation data (IMPROVE network) 22
Figure 3.21: Seasonal variation in PM species for selected urban areas in the United States 23
Figure 3.22: Spatial distribution of wet SOJ deposition (kg/ha/yr) in eastern North America, 1996-2001 24
Figure 3.23: Five-year (1996-2000) mean wet deposition exceedance of critical SOJ
loads (kg SOJ /ha/yr) for 95% lake protection level 24
Figure 3.24: Spatial distribution of wet NO3 deposition (kg/ha/yr) in eastern North America, 1996-2001 25
Figure 4. la: 1996 Summer weekday S02 emissions for Canada and the United States 32
Figure 4.1b: 2010 Summer weekday base case S02 emissions for Canada and the United States 33
Figure 4. lc: 2010 Summer weekday reductions in S02 emissions for Canada and the United States 33
Figure 4.2a: 2020 Summer weekday base case S02 emissions for Canada and the United States 34
Figure 4.2b: 2020 Summer weekday reductions in S02 emissions for Canada and the United States 34
Figure 4.3a: 1996 Winter weekday NOx emissions for Canada and the United States 35
Figure 4.3b: 2010 Winter weekday base case NOx emissions for Canada and the United States 35
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Canada - United States Transboundary PM Science Assessment
Figure 4.3c: 2010 Winter weekday reductions in NOx emissions for Canada and the United States 36
Figure 4.4a: 2020 Winter weekday base case NOx emissions for Canada and the United States 36
Figure 4.4b: 2020 Winter weekday reductions in NOx emissions for Canada and the United States 37
Figure 4.5a: 1996 Summer weekday NH3 emissions for Canada and the United States 37
Figure 4.5b: 1996 Winter weekday NH3 emissions for Canada and the United States 38
Figure 4.6a: 2010 Summer weekday base case NH3 emissions for Canada and the United States 38
Figure 4.6b: 2010 Winter weekday base case NH3 emissions for Canada and the United States 39
Figure 4.7a: 2020 Summer weekday base case NH3 emissions for Canada and the United States 39
Figure 4.7b: 2020 Winter weekday base case NH3 emissions for Canada and the United States 40
Figure 5.1: REMSAD modelling domain (-36x36 km2) 42
Figure 5.2a: Annual average PM2 5 concentrations 2010 base case 44
Figure 5.2b: Reductions in annual PM2 5 concentrations from controls in 2010 44
Figure 5.3a: Annual average PM2 5 concentrations 2020 base case 45
Figure 5.3b: Reductions in annual PM2 5 concentrations from controls in 2020 45
Figure 5.4a: January average PM2 5 concentrations 2020 base case 46
Figure 5.4b: Reductions in January PM2 5 concentrations from controls in 2020 46
Figure 5.5a: July average PM2 5 concentrations 2020 base case 47
Figure 5.5b: Reductions in July PM2 5 concentrations from controls in 2020 47
Figure 5.6a: Annual average SOJ concentrations 2020 base case 48
Figure 5.6b: Reductions in annual SOJ concentrations from controls in 2020 48
Figure 5.7a: January average SOJ concentrations 2020 base case 49
Figure 5.7b: Reductions in January SOJ concentrations from controls in 2020 49
Figure 5.8a: July average SOJ concentrations 2020 base case 50
Figure 5.8b: Reductions in July SOJ concentrations from controls in 2020 50
Figure 5.9a: Annual average NO3 concentrations 2020 base case 51
Figure 5.9b: Reductions in annual NO3 concentrations from controls in 2020 51
Figure 5.10a: January average NO3 concentrations 2020 base case 52
Figure 5.10b: Reductions in January NO3 concentrations from controls in 2020 52
Figure 5.1 la: July average NO3 concentrations 2020 base case 53
Figure 5.1 lb: Reductions in July NO3 concentrations from controls in 2020 53
Figure 5.12a: Annual average NHJ concentrations 2020 base case 54
Figure 5.12b: Reductions in annual NHJ concentrations from controls in 2020 54
Figure 5.13a: January average NHJ concentrations 2020 base case 55
Figure 5.13b: Reductions in January NHJ concentrations from controls in 2020 55
Figure 5.14a: January average NHJ concentrations 2020 base case 56
Figure 5.14b: Reductions in January NHJ concentrations from controls in 2020 56
Figure 5.15: AURAMS domain for all simulations (85x105 grid points, Ax=42 km) 58
Figure 5.16: Nine-day-average PM2 5 mass concentration field and PM2 5 inorganic
chemical component concentration fields predicted by AURAMS for the
Feb. 7-15, 1998 winter period for the "2010 base" case emissions 61
Figure 5.17: Nine-day-average PM2 5 mass concentration difference field and PM2 5 inorganic
chemical component concentration difference fields predicted by AURAMS for the
Feb. 7-15, 1998 winter period for the "2010 control" case minus the "2010 base" case 62
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Table of contents
Figure 5.18: Same as Figure 5.16 but for the "2020 base" case emissions 63
Figure 5.19: Same as Figure 5.17 but for the "2020 control" case minus the "2020 base" case 64
Figure 5.20: Eleven-day-average PM2 5 mass concentration field and PM2 5 inorganic
chemical component concentration fields predicted by AURAMS for the July 8-18,
1995 summer period for the "2010 base" case emissions 67
Figure 5.21: Eleven-day-average PM2 5 mass concentration difference field and PM2 5 inorganic
chemical component concentration difference fields predicted by AURAMS for the
July 8-18, 1995 summer period for the "2010 control" case minus the "2010 base" case 68
Figure 5.22: Same as Figure 5.20 but for the "2020 base" case emissions 69
Figure 5.23: Same as Figure 5.21 but for the "2020 control" case minus the "2020 base" case 70
Figure 5.24: Geographical references and domain extents for the CMAQ model 72
Figure 5.25: PM2 5 concentrations for the August, 2001 summer base case, predicted over the
CMAQ domain on a 4x4 km2 grid 73
Figure 5.26: Peak ozone concentration difference field at 15 m height for the July 12-15,
1995 summer period for the "2020 control" case minus the "2020 base" case 77
Figure 5.27: Annual reduction in SOJ wet deposition from additional U.S. and Canadian
controls (2020 control vs. base) 77
Figure 5.28: Annual reduction in N03 wet deposition from additional U.S. and Canadian
controls (2020 control vs. base) 78
Figure 5.29: Aerosol light extinction (in Mitt1 ) for the haziest 20 percent days and contribution
by individual particulate matter constituents, based onl997-1999 IMPROVE data 78
Figure 6.1: Average concentrations of PM2 5 and components (pg/m3) by state and province 82
Figure 6.2: Urban Excess Analysis for SO J , NHJ , N03, TCM and crustal material for 13 urban
areas in the United States 84
Figure 6.3: Combined QTBA plot derived using 2000 and 2001 TEOM PM2 5 measurements
for the warm months (May-September) 85
Figure 6.4: Sectors used to categorize 3-day back-trajectories of air masses at Longwoods, Ontario 86
Figure 6.5: Long-term trends and median concentrations of S02, particle SOJ and particle N03 in
air at Longwoods, Ontario associated with three-day back trajectories from Canada,
the United States and "Not Attributable" (N/A) to either sector 87
Figure 6.6: Long-term trends and median concentrations of pH, SOJ and NOs in precipitation
at Longwoods, Ontario associated with 72-hour back trajectories from Canada, the
United States and "Not Attributable" (N/A) to either sector 88
Figure 6.7: The geometric mean concentration of S02, SO J and TN03 measured in air at
Longwoods, ON (1983-2000) for the particular subset of air mass trajectories that
passed through that grid square 90
Figure 6.8: PM2 5 top and bottom quartile back-trajectory climatology events (based on 1999-2001 data) 91
Figure 6.9: Percent contribution, by component, to PM2 5 mass observed in a) Toronto and
b) Vancouver as determined using PMF-MLR 92
Figure 6.10: Annual average modelled PM2 5 contributions in Toronto, (February 2000 - February 2001)
using UNMIX (a) and PMF (b) receptor modelling techniques 93
Figure 6.11: Average day of week variations in UNMIX motor vehicle sources 93
Figure 6.12: Seasonal variations in Toronto PMF & UNMIX source contributions 93
Figure 6.13: UNMIX motor vehicle and coal-related sources vs. local surface wind speed and direction 94
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Canada - United States Transboundary PM Science Assessment
Figure 6.14: Incremental probability fields for coal-related sources at Toronto and other eastern sites 94
Figure 6.15: Incremental probability fields and day-of-week patterns in Toronto NH4N03 "sources." 95
Figure 6.16: Summary of major Toronto source regions and influences on daily PM2 5 mass concentrations 95
Figure 6.17: Sulphate source region plot for Source 1, (NH4)2S04, at Milwaukee, WI 96
Figure 6.18: Pie charts of the source apportionment results for various locations in the United States 97
Figure 6.19: The composites of MODIS-derived aerosol optical depth and cloud optical depth
superimposed over continuous PM2 5 monitors for July 6th and 7th, 2002 98
XIV
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Summary
The Canada-U.S. Air Quality Agreement was estab-
lished to provide "a practical and effective instru-
ment to address shared concerns regarding trans-
boundary air pollution". Initially the Agreement was
intended to address the primary pollutants respon-
sible for acid rain. However, the Agreement also con-
firmed the commitment of the United States and
Canada to consult on, and develop, the means to
address other transboundary air pollution issues,
including particulate matter.
The Subcommittee on Scientific Cooperation, of
the Air Quality Committee, was charged to summa-
rize and understand the current knowledge of the
transboundary transport of PM and PM precursors
between Canada and the United States in a scien-
tific Assessment. The seven key objectives can be
summarized as:
The Assessment represents a significant co-opera-
tive effort between scientists in Canada and the
United States, and in several cases, the informa-
tion provided is the first presentation of joint sci-
entific results. The report contains findings on
ambient levels, data analyses, and the application
of modelling tools in both Canada and the United
States. This Assessment will provide the initial sci-
entific knowledge required to determine the need
for a PM annex pursuant to the Air Quality
Agreement.
KEY FINDINGS
THE TRANSBOUNDARY TRANSPORT OF
PM CAN CONTRIBUTE TO ABOVE AVER-
AGE PM LEVELS IN BOTH CANADA AND
THE U.S.
Current ambient levels of PM2 5 in the border
regions exceed the standards set for PM2 5 in
several regions of both Canada and the United
States. In the United States, these sites are pri-
marily in urban areas. The eastern portion of
the border domain (i.e., northeastern United
States, Industrial Midwest, and the Windsor-
Quebec City corridor) exhibits levels that
exceed the 15 pg/m3 annual standard in the
United States and the 30 pg/m3 98th per-
centile three-year average Canadian standard
for the time periods evaluated.
PM2 5 is transported across the border region
between Canada and the United States, lead-
ing to elevated concentrations of PM2 5 in
both countries. Most of the analyses point to
sulphur dioxide as a primarily regional con-
tributor and nitrogen oxides as both a local
and regional contributor to PM2 5, while
Objective 1: To identify whether or not there
is a fine PM problem in the border region;
Objective 2: To identify the extent of the
problem;
Objective 3: To describe the PM issue in
terms of geographic regions;
Objective 4: To identify PM precursors of
concern on a regional or sub-regional basis;
Objective 5: To describe sources (or source
regions) of PM and PM precursors;
Objective 6: To describe the characteristics
of the emissions of PM and PM precursors;
and,
Objective 7: To identify the impact of emis-
sion reduction scenarios on PM levels.
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Canada - United States Transboundary PM Science Assessment
organic/black carbon and other PM con-
stituents tend to be more local in nature.
Canadian provinces have been found to con-
tribute to PM2 5 measured at several Class 1
areas in the United States, while the transport
of PM2 5 and PM precursors across the border
region leads to 'above average' PM2 5 concen-
trations in eastern Canada.
In the Georgia Basin - Puget Sound region,
impacts from transboundary transport occur
along the border (within + 50 km) with some
frequency; however, the incidence of long-
range/regional transport (over 100 km) was
low.
PM LEVELS VARY SIGNIFICANTLY OVER
GEOGRAPHIC REGIONS
Elevated concentrations of PM2 5 are found
more often in the following regions: northeast-
ern United States, Industrial Midwest, south-
western Ontario and the northwestern United
States. Most areas of both Canada and the
United States are subject to elevated concen-
trations during episodic conditions.
Urban concentrations of PM2 5 are higher than
rural concentrations in all regions of both
Canada and the United States; however, rural
sites can exhibit very high PM2 5 levels during
large-scale PM episodes.
The highest particle sulphate and nitrate con-
centrations are found in areas with high sul-
phur dioxide and nitrogen oxide emissions.
Such areas include the northeastern United
States and southwestern Ontario.
THERE ARE MANY SOURCES OF PM AND
PM PRECURSORS
Local motor vehicle sources (and small nearby
smelter or industrial sources) have a relatively
constant influence on PM2 5 concentrations in
Toronto, and are most evident on the cleanest
days (which also tend to occur with northerly
wind flows). Coal-related sources have a sub-
stantial transboundary contribution from the
United States, and are particularly important
on days of high PM2 5 concentration.
A region of high density emissions from coal
fired utilities exists in the northeastern United
States, which influences PM2 5 concentrations.
A similar analysis for ammonium nitrate indi-
cates a more widespread source region, in the
northeastern United States as well as the
north-central United States, a region of high
agricultural ammonia emissions.
Components and contributing sources to
PM2 5 identified in both Vancouver and
Toronto include secondary nitrate, regional
transport of coal combustion products, diesel
motor vehicles, secondary organic acids and
road dust.
Natural sources of PM (i.e., forest fires and bio-
genic sources) can also influence ambient air
quality. Satellite observations confirm the
impact of Canadian forest fire events on U.S.
aerosol optical depth.
EMISSION REDUCTION SCENARIOS FOR
PM AND PM PRECURSORS WERE EVALU-
ATED USING AIR QUALITY MODELS
Emissions of sulphur dioxide and nitrogen
oxides are projected to decrease while emis-
sions of ammonia, volatile organic compounds
and carbon monoxide are projected to increase
between base case and control case scenarios.
Sulphur dioxide, nitrogen oxides and ammonia
emissions, and their contributions to PM2 5
levels vary seasonally.
Emissions of sulphur dioxide and nitrogen
oxides under all considered scenarios are con-
centrated in the Industrial Midwest, northeast-
ern United States and southern Ontario, while
emissions of ammonia are concentrated fur-
ther west in the central Midwest region.
XVI
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Summary
U.S. and Canadian controls that are expected
to be implemented result in maximum annual
reductions of PM2 5 of 1.8 pg/m3 in 2010 and
2.3 pg/m3 in 2020. The reductions vary tempo-
rally and spatially.
Proposed additional sulphur dioxide and
nitrogen oxide emission reductions should
provide additional reductions in ambient
PM2 5 levels in eastern North America. The
observed PM2 5 reductions may vary by sea-
son and depend strongly on reductions in par-
ticle sulphate mass.
Simultaneous reductions in both sulphur
dioxide and nitrogen oxides may also provide
concurrent reductions in particle ammonium,
due to the reduction of gaseous sulphur diox-
ide and nitrogen oxides available to react with
gaseous ammonia.
Reductions in sulphur dioxide emissions that
are not accompanied by adequate nitrogen
oxide emissions may result in nitrate increas-
es in some areas. Reductions in nitrogen
oxide emissions will correspond to decreases
in particle nitrate mass in some parts of east-
ern North America but increases in other areas
due to nitrate substitution (i.e. for sulphate
reductions in ammonia-limited locations, the
replacement of sulphate by nitrate in the par-
ticle phase). There is significance placed on
the role of ammonia in this relationship, sug-
gesting there may be value in investigating
possible benefits due to gaseous ammonia
emission reductions in conjunction with sul-
phur dioxide and nitrogen oxide emission
reductions.
THERE ARE LINKAGES BETWEEN PM
AND OTHER AIR QUALITY ISSUES
Ambient levels of PM precursors also con-
tribute to the wet deposition of nitrate and
sulphate, and resulting ecosystem acidifica-
tion. The highest levels of deposition are
located in the northeastern United States and
eastern Canada, particularly in the border
regions.
Co-benefits of emission reduction scenarios
include reduced ground-level ozone levels,
reductions in nitrate and sulphate deposition,
and improved visibility.
CONCLUSION
The results of the Canada-United States
Transboundary PM Assessment indicate that there
is a significant relationship between the emissions
of PM and PM precursors and elevated PM levels in
both Canada and the United States. The trans-
boundary transport of PM and PM precursors can
be significant enough in some regions to poten-
tially compromise the attainment of national stan-
dards. The information presented in this
Assessment provides the scientific foundation to
support the future development of joint strategies
under a PM Annex pursuant to the Agreement.
XVII
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Chapter
INTRODUCTION
On March 13, 1991, the President of the United
States and the Prime Minister of Canada
signed the Canada-U.S. Air Quality Agreement
(hereafter referred to as the Agreement). The pur-
pose of the Agreement was to establish "a practical
and effective instrument to address shared con-
cerns regarding transboundary air pollution". At
the time of inception, the Agreement was intended
to address the primary pollutants responsible for
acid rain. However, the Agreement also confirmed
the commitment of the United States and Canada
to consult on, and develop, the means to address
other transboundary air pollution issues.
In 1997, in response to shared concerns over
the transboundary transport of ozone and fine par-
ticulate matter (PM), Canada and the United
States signed a "Commitment to Develop a Joint
Plan of Action for Addressing Transboundary Air
Pollution." The commitment articulated the intent
of the Parties to jointly address the shared prob-
lems of ground-level ozone and PM within the
framework of the Agreement.
Stemming from this Commitment, the Parties
signed a Joint Work Plan for Transboundary Fine
Inhalable Particles in June 1998. The Joint Work
Plan described the steps necessary to institute
"comparable and harmonized analytical tools to
enable the assessment of transboundary trans-
port, trends and analysis regarding fine inhalable
particles in the transboundary region". To facili-
tate this process, the Subcommittee on Scientific
Cooperation, or Subcommittee 2 (SC2), of the Air
Quality Committee held three bi-national work-
shops between 1999 and 2003. In addition to facil-
itating the institution of comparable and harmo-
nized analytical tools, SC2 sought to understand
the scientific information needs of the bi-national
policy community, as articulated by the
Subcommittee on Program Monitoring and
Reporting, or Subcommittee 1 (SCI), and plan and
deliver a scientific assessment of the transbound-
ary transport of PM. During this process, Canada
and the United States agreed to include acid rain
and visibility endpoints in the Assessment where
possible, in recognition of the fact that reductions
in PM and ozone precursors can also affect acid
rain and visibility.
As a cumulative result of the three bi-national
workshops, and of discussions therein, seven key
objectives were identified for the Transboundary
PM Science Assessment:
Objective 1: To identify whether or not there
is a fine PM problem in the border regions
(ambient observations versus standards)
with a focus on health, visibility and environ-
mental endpoints;
Objective 2: To identify the extent of the
problem (if standards are exceeded, by how
much, where and when are they exceeded);
Objective 3: To describe the PM issue in
terms of geographic regions (i.e. west, cen-
tral, east);
Objective 4: To identify PM precursors of
concern on a regional or sub-regional basis;
Objective 5: To describe sources (or source
regions) of PM and PM precursors in the con-
text of geographic regions (i.e., west, central,
east);
Objective 6: To describe emissions of PM
precursors, the spatial distribution of emis-
sions and the transport characteristics of
these emissions; and,
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Canada - United States Transboundary PM Science Assessment
Objective 7: To identify the impact of current
and proposed emission reduction scenarios
on fine PM levels in North America.
The process undertaken for this Assessment
includes an initial overview of the PM issue in
North America, as determined primarily by the
2003 NARSTO PM Science Assessment. This back-
ground is then expanded by examining ambient
observations and emission information, perform-
ing air quality model applications, and analyzing
sources and their corresponding PM levels, specif-
ic to the transboundary region. Each of these
steps concludes with a summary of the key science
messages learned from the analyses; these key sci-
ence messages are then applied in the conclusions
in order to address the objectives listed above.
The Assessment is intended to synthesize the
current state of knowledge on the transboundary
transport of fine inhalable particles, in keeping
with the information needs of the bi-national
policy community. In fulfilling this purpose, this
Assessment and its conclusions are consistent
with the requirements of the 1998 Joint Work Plan
for PM. The conclusions of this Assessment will
provide the scientific support required to deter-
mine the need for a PM annex pursuant to the
Agreement.
2
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Chapter
2
FOUNDATION FOR THE TRANSBOUNDARY PM
ISSUE IN NORTH AMERICA1
Seven key features of the PM issue have provid-
ed the impetus for this Transboundary PM
Science Assessment. These key features are listed
below and explored in greater detail in this chapter:
PM is recognized as an important health
concern.
High ambient levels of PM and its precursors
are observed in North America.
Precursors of PM generally contribute to the
acidification of ecosystems.
PM and its precursors are a significant cause
of visibility impairment.
PM and its precursors can be transported long
distances.
PM and its precursors are transported
between the United States and Canada.
Reductions in S02 are likely to result in reduc-
tions in PM2 5, acid deposition, and visibility
impairment.
2.1 PM IS RECOGNIZED AS
AN IMPORTANT HEALTH
CONCERN
PM has been recognized as an important health
concern in both the United States and Canada.
Recent health studies in both countries indicate
an association between adverse health outcomes,
especially of the cardio-respiratory system, and
short- and long-term exposures to ambient PM,
particularly PM2 5. In recognition of these health
outcomes, both countries have committed to
addressing the PM air-quality problem within their
own territories (e.g., Canada-Wide Standard for
PM2 5, U.S. Clean Air Act). Furthermore, Canada
and the United States have developed objectives
and standards for ambient PM (Table 2.1).
1 Unless cited as otherwise, the primary source of information for this chapter is the report by NARSTO entitled "Particulate Matter
Science for Policy Makers: A NARSTO Assessment." In February 2003, NARSTO, a cooperative public-private sector organization of
Canada, Mexico and the United States, produced this report. The assessment of PM science presents a concise and comprehen-
sive discussion of the current understanding of airborne particulate matter among atmospheric scientists. The goal of the NARSTO
assessment was to provide policy makers with relevant and needed scientific information and as such, the assessment focused on
two primary objectives: the interpretation of complex and new atmospheric science so that it is useful for the management of PM:
and, informing exposure and health scientists about the atmospheric science of PM. While meeting these primary objectives, the
NARSTO assessment summarizes science relevant to the transboundary transport of PM between Canada and the United States.
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Canada - United States Transboundary PM Science Assessment
Table 2.1 Ambient Air Quality Objectives and Standards for PM2 5.
United States
Canada
Averaging Time
National Ambient Air Quality
Standards
Canada-Wide Standard
Annual
15 pg/m3 based upon the 3-year
average of the annual arithmetic
mean concentration.
24 hour
65 pg/m3 based upon the 3-year
average of the 98th percentile of
24-hr average concentrations.
30 pg/m3 based upon the 98th percentile
of a 24-hr average, measured over three
consecutive years.
Visibility
Improve visibility on the haziest
days and ensure no degradation on
the clearest days, with the ultimate
goal of reaching natural background
conditions in 60 years.
2.2 HIGH AMBIENT LEVELS OF
PM AND ITS PRECURSORS
ARE OBSERVED IN NORTH
America
The highest annual-mean PM2 5 concentrations
are found in urban areas throughout North
America, particularly in California, the southeast-
ern United States, and the large urban centres of
southeastern Canada (Figure 2.1).
PM2 5 mass measurements typically exhibit
concentration frequency distributions that are
dominated by a large number of low values and a
smaller number of high concentrations. Annual
average PM2 5 concentrations can vary by up to a
factor of two across distances of 50 to 100 km in
some large metropolitan regions. In California,
the southeastern United States, the northeastern
United States, and the Ohio River Valley-Great
Lakes states, annual-mean PM2 5 mass concentra-
tions at about half of the urban sites exceeded the
U.S. 3-year average annual-mean PM2 5 mass stan-
dard of 15 pg/m3 in 1999 and 2000. In Canada, 24-
hour average concentrations greater than 30 pg/m3
occur over most of southern Ontario and Quebec
approximately 2 percent of the year.
Locally observed PM is composed of multiple
chemical constituents, largely organic carbon
(OC), sulphate (SO=), black carbon (BC) and
nitrate (NO-^ in combinations that differ by geo-
graphic region. PM composition is influenced by
sources and seasonal meteorology, and has sub-
stantial regional contributions. Typically, SOj is a
major fraction of PM2 5 in eastern North America
while NOj is a major component in California.
Nitrate concentrations across North America are
greater in the winter compared to the summer, and
urban concentrations are greater than rural con-
centrations in eastern North America.
2.3 PRECURSORS OF PM
GENERALLY CONTRIBUTE
TO THE ACIDIFICATION OF
ECOSYSTEMS
Wet and dry deposition of SOj and NO3 con-
tributes to the acidification of ecosystems.
Although the most commonly used measures of
4
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chapter 2
Figure 2.1- Average F>M2 g
concentrations. The U.$;. data
are from FEM monitors at sites
in the EPA AIRS database for
July 1998 through July 20OOj
Canadian data are from TEOM
and dichotomous samplers
operating from 1995 through
2000. The currently available
data from sites in Mexico
ฆrepresented less than one year
of sampling and were excluded
from the computation of annual
averages.^ Spot diameter varies
in proportion to concentration.
(Sotira:: R. Husar,:pers. comm.):
Annual PM2.5 Mass Concentration
>, .91* * A
f^Staions;
R AIRSFRM 1007, 1938-OC
ฆV f~- Canada TEOM 43.1995-00
I Canada Dichol 24,1995-00
Annual PM2 5. j.ig/m3
>15 '
ฆc 10-15
Ji <10
acid deposition focus on wet deposition of SOj
and NO3 , research in south-central Ontario indi-
cates that approximately 40% of the total deposi-
tion of sulphur and nitrogen occurs in the form of
dry deposition (Sirois et al., 2001). These acidify-
ing pollutants have been shown to damage terres-
trial and aquatic ecosystems and susceptible
materials at levels measured frequently in Canada
and the northeastern United States.
The geographic region most affected by acid
deposition is southeastern Canada and the north-
eastern United States; east of Manitoba and south
of 52 degrees latitude. The relative contribution of
the sources of acid deposition (local versus long-
range) is area-dependent, however, the majority of
acid deposition in southeastern Canada originates
from long-range transport, as does a significant
proportion: of the deposition in the northeastern
United States.
2.4 PM AND ITS PRECURSORS
ARE A SIGNIFICANT
CAUSE OF VISIBILITY
IMPAIRMENT.
Optically, PM interferes with visibility by either
absorbing or scattering visible light. Light scatter-
ing is roughly proportional to the mass concentra-
tion of fine particles, while light absorption is
roughly proportional to the mass concentration of
the light-absorbing species. The impairment of
visibility that results from the absorption or scat-
tering of light reduces the distance to which one
can see and decreases the .apparent contrast and
colour of distant objects, causing a washed out or
hazy appearance.
The light extinction effects of PM vary with
particle size, chemical composition, and humidity.
The particles with the greatest influence on visibil-
ity are fine particles of the same scale as the wave-
lengths of visible light (approximately 0.3 to 1 mm
in diameter). These particles are generally com-
posed of SO= and NO3 salts, OC, or BC.
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Canada - United States Transboundary PM Science Assessment
2.5 PM AND ITS PRECURSORS
CAN BE TRANSPORTED
LONG DISTANCES.
PM can remain in the atmosphere for days to a few
weeks, depending on the size and rate at which it
is removed from the atmosphere (e.g., by precipi-
tation). Particles in any given area may originate
locally or from sources hundreds to thousands of
kilometers away. Particles can also be formed dur-
ing atmospheric transport from precursor gases
originating from either local or long-range sources.
Both local and regional emissions: underlie
local ambient concentrations in many urban areas,
Regional contributions from sources distant from
eastern North American urban sites (including
upwind urban areas) can account for 50 to 75 per-
cent of the total observed PM2 5 mass concentra-
tion within a specific urban area.
2.6 PM AND ITS PRECURSORS
ARE TRANSPORTED
BETWEEN THE UNITED
STATES AND CANADA.
The NARSTO PM Assessment described two studies
in Canada and the United States that demonstrate
the transboundary transport of PM and its
precursors.
Brook et al. (2002) traced 3-day back-trajecto-
ries of air masses arriving at Simcoe, ON during
the warm season (May-September) of 1998 and
1999 (Figure 2.2). These back-trajectories were
divided into categories based on the concentration
of PM2 5 measured at Simcoe and the directionality
of the contributing air mass. This analysis resulted
in three "source-receptor" categories: 1) "low"
PM2 5 (6 hour averages of 6.8 pg/m3) category,
characterized by north-south airflows, 2) "high"
(22.4 pg/m3) PM2 5 category, characterized by
Figure 2.2- 3-day hack-trajectories arriving at Simcoe. Ontario, for the warm season (May^Septemfeerj, 1998 and 1999.
(The sectors shown represent a) northerly flow over predominantly Canadian source regions and b) southerly flow over
U.Ssource regions. Corresponding median PMa g concentrations are a) Sector 1: 3.8 fig/m3 and
b) Sector 2: 20.3 pg/m3).
6
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chapter 2
south-north airflows, and 3) "unclassified high"
(>30 pg/m3) PM2 5 category. Category three air
masses were characterized by very short transport
distances, indicating stagnant conditions in the
Midwest and Great Lakes Region. Air mass trajec-
tories associated with high levels of PM2 5 fre-
quently crossed the border between Canada and
the United States.
During 1977-1978, a field study was conducted
in eastern North America to assess the transport
and fate of SOJ. The Sulphate Regional
Experiment (SURE) found a correlation between
air flow patterns and SOj aerosol concentrations.
In general, regional PM episodes were character-
ized by the presence of a quasi-stationary high-
pressure ridge oriented in an east-west direction
across Virginia and North Carolina. Higher con-
centrations of SOj at locations in southern
Ontario were linked to transport from the mid-
western and southern United States.
2.7 REDUCTIONS IN S02 ARE
LIKELY TO RESULT IN
REDUCTIONS IN PM^ 5,
VISIBILITY IMPAIRMENT
AND ACID DEPOSITION.
PM, visibility impairment and acid deposition are
related through common emissions and precur-
sors, production pathways and meteorological
processes. Consequently, the typical response of
PM, visibility (by extension of the response of PM),
and acid rain to reductions in S02 and other pol-
lutants (i.e., NOx) have been derived. These rela-
tionships indicate that a reduction in the emis-
sions of S02 is likely to result in reductions in the
SOj component of PM, total PM2 5 mass, visibili-
ty impairment and acid deposition.
For example, in the last decade, there have
been substantial reductions in emissions of S02 in
North America. In southeastern Canada, these
reductions have resulted in a general decline in
SOJ concentrations in precipitation but with a rel-
atively smaller compensating increase in pH (often
attributed to a parallel decline in base cation con-
centrations). Similarly, lakes in the affected
regions of southeastern Canada generally exhibit
declining SO= trends in response to emission
reductions but, as yet, they are not exhibiting
widespread increases in pH or alkalinity. The only
exceptions to these observations are lakes located
near smelters that have dramatically reduced
emissions.
In the eastern United States, wet and dry sul-
phur deposition (and the acidity associated with
sulphur deposition) has also declined with reduc-
tions of S02 emissions (Butler et al., 2001; Likens
et al., 2001; Dutkiewicz et al., 2000; Lynch et al.,
2000; Shannon, 1999). Strong correlations, near
linear, between large scale S02 emission reduc-
tions and large reductions in SO= concentrations
in precipitation have been noted for the northeast-
ern United States, one of the areas most affected
by acid deposition (Butler et al., 2003). Some of
the greatest reductions in wet SOj deposition
occurred in the Mid-Appalachian region, including
Maryland, New York, West Virginia, Virginia, and
most of Pennsylvania. Wet SOj deposition
decreased more than 8 kilograms/hectare (kg/ha)
from rates observed throughout the early 1990s in
much of the Ohio River Valley and northeastern
United States. Other less dramatic reductions
were observed across much of New England, por-
tions of the southern Appalachian Mountains and
in the Midwest, most notably Indiana and Illinois.
These reductions are primarily attributed to the
reduction in SOj from emission sources located in
the Ohio River Valley following implementation of
Title IV of the 1990 Clean Air Act Amendments.
Freshwater monitoring in eastern U.S. lakes and
streams indicates measurable improvements in
surface water chemistry (lower SOj concentrations
and decreases in acidity) concomitant with reduc-
tions in SOj deposition (Stoddard et al., 2003).
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Canada - United States Transboundary PM Science Assessment
In three of the five areas studied, one-quarter
to one-third of lakes and streams previously affect-
ed by acid rain are no longer acidic, although they
are still highly sensitive to future changes in depo-
sition. In other areas, signs of recovery are not yet
evident, suggesting that additional reductions will
assist further ecosystem recovery. Increases in the
Acid Neutralizing Capacity of surface waters, an
indicator of aquatic ecosystem recovery, were evi-
dent in three of the regions (Adirondacks,
Northern Appalachian Plateau and Upper
Midwest) and was unchanged in New England and
the Ridge/Blue Ridge region of the southeast U.S.
A review of the state of acid deposition sci-
ence in Canada, completed in 1997, suggested that
a 75 percent reduction in emissions of S02,
beyond that agreed to in the 1991 Canada-U.S. Air
Quality Agreement, is required to mitigate the
effects of acid deposition on eastern Canadian
ecosystems. Recent assessments of acid deposi-
tion science in the United States have concluded
that further reductions of SOj deposition beyond
levels achieved by the Title IV S02 emission reduc-
tions are necessary to protect aquatic ecosystems
from further deterioration in the southeast and
achieve ecosystem recovery in the northeast.
8
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Chapter
3,
AMBIENT OBSERVATIONS IN BORDER REGIONS
3.1 LEVELS OF AND TRENDS
IN PM _
. O
3.1.1 Integrated Observations between
Canada and the United States.
Levels of PM and PM precursors are monitored
and reported across the United States and Canada.
Monitoring techniques vary between the two coun-
tries,, but wherever possible in this Assessment,
efforts have been made to account for differences
in techniques and combine monitoring results to
provide a more comprehensive view of PM levels in
the border regions. Figure 3.1 illustrates mean
annual PM2 s concentrations at Canadian dichoto-
mous (dichot) and U.S. Federal Reference Method
(FRM) sites. Annual levels of PM2 5 are as high as
18 ug/m3 in the northeastern United States, but
are consistently lower than 12 [ig/m3 in the mid-
continental States. The bi-national map in Figure
3.1 shows few monitoring sites; north of the
Canada-U.S. border due to differences in sampling
frequency between the two countries.
When Canadian hourly TEOM observations-
are included in the database, a more detailed pic-
ture of ambient levels can be achieved. The 98th
percentile values for the years 2000-2002 are
shown in Figure 3.2. The northeastern United
States is again a region of high ambient PM2 5
levels,, with 98th percentile values in excess of
30 yg/m3 at a majority of the sites. Canadian loca-
tions- exhibit generally lower levels of PM2 5,
although concentrations greater than 30 pg/m3
occur in several regions of the country for the years
2000-2002, particularly in the Windsor-Quebec City
corridor.
Time trends of gaseous S02, particle SOj, par-
ticle NHj and total nitrate (HN03 + NOj) concen-
trations were investigated at a number of
rural/remote sites in the eastern United States and
Canada from 1989 to 2002 (Figures 3.3 and 3.4).
Canadian measurements were made by the
Canadian Air and Precipitation Monitoring
Network (CAPMoN), and U.S. measurements by
Canada Dichot
and US FRM
PM2.5 Monitors
2000 -2003 mean
10-<=12
12 -<=15
15 ,<=18
y-
Figure 3.1 - Mean annual con-
centration of PMg 5 at
Canadian dichot and U.0, FRM
monitors in the border region
for the data years 2000-200%.
(Notr- 07([i,f< li.:ir sit^s are years
2000-2002 not all sites include
IliO 'e [ nit fears of d ata 1.
9
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Canada - United States Transboundary PM Science Assessment
Canada TEOM
and US FRM
PM2.5 p98 00-02
ilelTEOM monitor
the Clean Air Status and Trends Network
(CASTNet). The two networks use similar filter-
pack sampling technology, but the Canadian meas-
urements are 24-hour average concentrations-
while the U.S. measurements are weekly-average
concentrations. This difference has no significant
impact on the comparability of the trends, The
time trends shown in the figures were produced
using a Kernel smoothing technique. The Kernel
smoothing technique uses: a moving weighted-
mean smoother. The weighting function has a
maximum value at the center of the moving data
window and a value of zero at the edges of the
window.
Figure 3.3 shows time trends for S02 and par-
ticle SOj at seven CASTNet and six CAPMoN sites
for the period 1989 to 2002. The highest S02 and
SOj concentrations are observed in regions with
high S02 emissions (i.e., Indiana, Ohio,
Pennsylvania) while in contrast, the lowest con-
centrations occur in the northernmost and east-
ernmost regions of Canada, at sites distant from
major emission source areas. Consistent with the
large decline in eastern North American S02 emis-
sions during the 1990s:, all of the Canadian and
U.S. sites showed marked decreases in ambient
S02 and SOj concentrations between the early
and late 1990s. At most sites, the SOj and S02
trends lines follow each other closely with both
Figure; 3,2 - 98th percentile
PM j I concentrations at
Canadian TEOM and U.S. FRM
sites for the data years-
2000-2002,
(C an.'t'li.ir sil'-'s do n[ >I. all
include three full years
of data) :
species beginning their downward drop around
1989-91. At some sites (Vincennes, IN; Deer Creek,
OH; Prince Edward; VA), however, the decline in
SOj concentrations occurred two or three years
later than the decline in S02 concentrations. This
may be due to the close proximity of sources with
rapidly declining emissions, whereas particle SOj
concentrations may not decline as rapidly due to
relatively larger distances between the sources and
receptors. The S02 and SOj trends at Canadian
sites generally level off around 1998-2000 while
most U.S. sites continue a downward trend, with
SOj leveling off at only a few sites.
Particle NHJ .and total NOj concentration
trends are shown in Figure 3.4 for the same time
period, 1989 to 2002. Total NO^ is defined here as
the sum of gaseous HNOs and particle NO3 , both
reaction products of NOx. Figure 3.4 indicates that
particle NH+ concentrations in Canada remained
roughly constant throughout the period while U.S.
concentrations generally decreased between the
early and late 1990s., Ammonium concentrations
were considerably higher in the United States in
comparison to Canada, with the exception of the
site at Longwoods, which is located in a major
agricultural region of southwestern Ontario, a
large source of NH3 emissions.
Total NOg concentrations remained roughly
constant, throughout the 1989-2002 time period at
IO
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chapter 3
[micromoles/m3]
Ann Arbor
CAPMoN and CASTNet Air Concentrations
Figure 3 J - Long-term trends in the precursor-gases SOซ [green) and particulate SO^ (blue ) at rural CAPMoN and
CASTNet sites, 1989-2002,
1 1
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Canada - United States Transboundary PM Science Assessment
[micromoles/m3]
NHl HNOo+NO
Sutton , QU
HM03+ HO 3
HM03* M03
Vincormcs , IN
HM03+ N03
CAPMoN and CASTNet Air Concentrations
Figure 3.4 - Trends in total nitrate: {gaseous HNOs and particulate NOg) (green) and particulate NHJ (blue) at rural
CAPMoN and CASTNet sites, 1989-2002,
12
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chapter 3
all Canadian sites. Canadian sites also had lower
total NO3 concentrations than the U.S. locations
throughout the measurement period. In contrast,
trends at the U.S. sites were not consistent and
varied from site to site, some showing higher con-
centrations in the late 1990s compared to the early
1990s, some showing decreased concentrations in
the late 1990s and others showing no change. The
variability in the trends at the U.S. sites is possibly
a reflection of changing NOx emissions at near- to
medium-distance sources whereas the trends at
the Canadian sites may reflect NOx emissions
from more distant sources.
3.1.2 Canada
PM2 5 data typically exhibit strongly skewed fre-
quency distributions, characterized by a large
number of low values and a small number of high
values. It has been shown that the accuracy of the
estimated annual means and maxima decreases
with decreasing sampling frequency. Hence, the
mean and extreme values of PM2 5 measurements
from the NAPS (National Air Pollution Surveillance
Network) dichot network will generally be biased
low because of the l-in-6-day sampling regime.
Errors in the NAPS annual means have been esti-
mated to be about 10 percent. Errors in the annu-
al maxima have been estimated to range from 30
to 50 percent (WGAQOG, 1999). Extreme values
along the tails of the frequency distributions are
often of special interest because they are associat-
ed with high concentration PM episodes.
Figure 3.5 shows the trend in annual median
PM2 5 mass at 11 urban NAPS network sites across
Canada from 1984 to 2002. Overall, there is a
slight decreasing trend in median PM2 5 mass over
time, although the 98th percentile values have
declined significantly. Data collected between
1984 to the mid-1990s show a decreasing trend,
however; from the mid-1990s onward, the median
mass of PM2 5 is relatively stable. The reasons for
these trends are not entirely clear, but the
decrease earlier in the data record may be due to
S02 reductions from acid rain control programs
that occurred in the late 1980s and early 1990s (see
Figure 3.3).
~Z Non-Outlier Max
Non-Outlier Min
~ 75%
25%
^ Median
1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
1985 1987 1989 1991 1993 1995 1997 1999 2001
Figure 3.5 - Trend in annual median PM, 5, 1984-2002
(median, 75th, 25th percentile). Data are from dichoto-
mous samplers.
R - Rural
* - 95-97 Data
ฃ i ฃ 2 3 I ! 5
PzzFszzt
3j O ฃ ฃ Z Q
O c s
zjoooc>ฃฃ
X>oiZOqXC
Figure 3.6 - Three-year mean, 10th and 98th percentile
PM, 5 concentrations, 1997-1999. (Except at sites
marked with an *, where the period is 1995-1997. The
solid line shows the current Canada-Wide Standard
(CWS) for PM, 5 of 30 pg/m3, expressed as a three
year average of 98th percentile 24-hour values.
Victoria data are considered incomplete. Data are from
dichotomous samplers.
Figure 3.6 shows three-year PM2 5 averages
across Canada for the years 1997 through 1999.
The 98th percentile concentrations ranged from a
minimum of 16.5 pg/m3 at a site in Victoria, to
a maximum of 40 pg/m3 at Egbert, Ontario.
Measurement data indicate that in eastern
Canada, urban and 'point-source influenced' sites
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Canada - United States Transboundary PM Science Assessment
B.C.
Alberta ;
Sas
Man
Ontario
c.
Quebec
N.B.
Nfld.
i
r ;
ฆ
J
ฆ.% *
I
i *
i
Urban Sites
Rural Sites
Figure 3.7 - The 98th percentile of Canadian 24-hour
PM, | concentratibns in 2QQ1. Sites shown are from
west to east. The Canada-Wi<3e Standard numerical
target of,30 yg/ffiฎ is shown by the solid line. Data are
from continuous TEOM samplers.
Figure 3,8 - U.S regions used for data analysis
purposes.
generally experience higher PM2 3 concentrations
than do rural and remote sites. This pattern has
also; been observed in Alberta by Cheng et al.
(2000). However, rural sites can also experience
very high PM2ซ levels during large-scale PM
episodes,, often comparable to levels observed at
urban locations.
Figure 3.7 presents the one-year 98th per-
centile values of 24-hour PM2 5 concentrations in
2001 at monitoring sites that satisfied the 75 per-
cent NAPS data completeness criterion (or had a
98th percentile > 30pg/m3 as per the Canada-Wide
Standard Achievement document), shown by loca-
tion from west to east. In 2001, 98th percentile val-
ues were greater than 30 pg/m5 (shown by the red
line in Figure 3.7) at seventeen sites.. All of these
seventeen sites are in urban areas except for the
rural site of Simcoe, Ontario. Outside of Ontario
and Quebec, only Prince George recorded a 98th
percentile value greater than 30 pg/m3.
U.S. EPA's Air Quality System (AOS) as of April
2003, are presented here. PM2 5 data from the net-
work for Interagency Monitoring of Protected
Visual Environments (IMPROVE) are also
presented. Many data summaries are presented by
region, as shown in Figure 3.8, for understanding
potential differences in the characteristics of PM in
different parts of the United States, Four of these
regions border Canada.
Following the establishment of new ambient
standards for PM2 5 in 1997. the U.S. EPA led a
national effort to deploy and operate over 1000
PM2 5 monitors. The U.S. EPA has analyzed the
available data collected by this network from 2000-
2002. Data from the monitors were screened for
completeness with the purpose of avoiding sea-
sonal bias. To be included in these analyses, a
monitor needed to record at least a full year of
data, defined as either 4, 8, or 12 consecutive quar-
ters with eleven or more observations per quarter.
3.1.3 United States
The U.S. EPA and the states have been using a
national network to measure PM2 5 concentra-
tions since 1999. Summaries through the end of
2002, based on data publicly available from the
3.1.3.1 Spatial Variations in Annual Average
PM2 5 Concentrations across the United States
Figures 3.9 is a national map depicting county-
level annual mean PM2 5 concentrations from the
U.S. FRM network. The monitor with the highest
Northwest
California
Southwest
14
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chapter 3
Annual Means at U.S. FRM Sites, by Region (lower regions not shown)
Whiskers display 90"
and 10th percentiles
Dots identify
distribution means
Completeness
criteria: 11 + samples
per quarter
HI regions (n= 821) N orthwest (n=116) Upper Mid vest (n=72) I rid. M ictoest (n=204) N oitheast (n=132)
PM Concentration (pgdn )
6 $3 couiflai
-or- I2
IS-:or- II
Figure 3:9 * County-leyel maximum annual mean
PM2 i concentrations, averaged over three years,
2000-2002.
Figure:!,10 - Annual PS%J means at U.S. FRM sites by
region over thres years, 2000-2002. The box identifies
the inter-quartile range, the ling in the middle
shows the median, whiskers display 90th and 10th
percentiles, and dots identify the distribution means.
concentration in each monitored county is used to
represent the value in that county. The map and
box plots show that many locations in the eastern
United States and in California had annual mean
PM2 5, concentrations above 15 ug/m3.
Annual mean PM2 5 concentrations were
above 18 ug/m3 in several urban areas throughout
the eastern United States, including Atlanta,
Birmingham. Chicago, Cincinnati, Cleveland.
Detroit, Indianapolis, Knoxville, Louisville,
Pittsburgh, and St, Louis. Los Angeles and the
central valley of California were also above
18 ug/m3,: Sites in the upper Midwest, Southwest,
and Northwest regions of the United States had
generally lower annual mean PM2 5 concentra-
tions, most below 12 ug/m3.
3.1.3.2 Annual Means of PM2 5 at U.S. FRM Sites
by Region
The annual PM2 5 mean concentrations across;
the northern regions of the United States range
from about 6 to 18 ug/m3, with a median of about
13 lig/m3. The 98th percentiles of the distribution
of 24-hour average concentrations range from
about 8 to 94 pg/m3, with a median of about
33 pg/m3. Figure 3.10 shows 3 years of annual
mean concentrations at FRM sites, for the data
years 2000-2002. Most FRM sites are urban
('Urban and Center City' or 'Suburban') according
to AQS definitions; FRM sites sample every day,
every 3rd day or every 6th day, with the predomi-
nant measurements being every 3rd day,
The left-most graph in Figure 3.10 shows the
three years of data for all sites in the United States
(irrespective of region) and the four other plots
show the northern U.S. regions bordering Canada.
PM2 5 concentrations decreased approximately
7 percent nationwide but the northern United
States did not see such a decrease. Except for the
Industrial Midwest, concentrations in the northern
regions have been much flatter. Average PM2 5
levels are lower than the U.S. averages in all north-
ern regions except for the Industrial Midwest
(Detroit. Cleveland).
3.1.3.3 Annual Means of PM2 5 at U.S. FRM Sites
within 300 km of Border by Region
Figure 3.11 focuses on U.S. FRM sites within 300
km of the Canadian border. This boundary was rec-
ommended based on various analyses of correla-
tion distance, back trajectories, and source attribu-
tion analysis. The left-most plot shows PM2 5 con-
15
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Canada - United States Transboundary PM Science Assessment
Annual Means at U.S. FRM Sites Within 300 km of the Canadian Border, by Region
II
Whiskers display 90ฎ
and 10th percentiles
ฆ Dots identiiy
distribution means
Completeness
criteria: 11 + samples
per quarter
'00 '01 '02 '00 '01 '02 '00 '01 '02 '00 '01 '02 '00 '01 '02
M regions (n=158) Northwest (n=32) Upper Midwest (n=10) Ind. Midwest (n=77) Northeast (n=38)
Figure 3.11 - Annual mean PM2 5 at U.S. FRM sites
within 300 km of the Canadian border by region, over
three years, 2000-2002.
Annual Means at U.S. IMPROVE Sites, by Region
(lower reaions not shown)
IT
Ii
J,
I I
Wtuskorsdis
play
90* and 10th
percentiles
Dots identify
distribution means
CompJeteness
criteria: It*
sampJaa pe< quarter
Al SntajSjrwi] MoriW^ Uซ*f W'H Ind (n-ai hwmmi 1/1-il
Figure t.12- Annual PM2 5 means at rural U.S..
IMPROVE sites by region.
centrations at all U.S. sites within 300 km of the
border. This figure includes all of the sites in the 4
plots to the right (with one exception) since none
of the 'southern' regions have points that close.
The exception is one site (Alaska) which is not
included in a region, but meets the completeness
criterion. Mean PM2 5 concentrations for all sites,
(within 300 km) are relatively flat with the
Industrial Midwest driving the 'all regions' plot
since about half of the 158 sites are located there.
Sites in the Northwest show a large decline,
-22 percent (in average mean PM2 5 concentra-
tions) from 2000 to 2002. The 10 sites closest to
the Canadian border show a decline in mean
PM2 5 of 10 percent.
3.1.3.4 Annual Means of PM25 at U.S. IMPROVE
Sites by Region
Figure 3.12 shows the U.S. annual mean PM2 5 at
the rural IMPROVE network sites for the data years
2000-2002. PM2 5 levels are relatively unchanged
over the three years, with a slight increase in the
middle year (with the exception of the Northwest
region). Annual mean concentrations declined
from 1998 to 2001 at the three sites in the
Industrial Midwest. Annual mean levels of PM2 5
at sites in the Northwest and Upper Midwest are
consistent with national averages (at IMPROVE
sites), The levels in the two eastern regions, par-
ticularly the Industrial Midwest, are higher on aver-
age than the other sites.
3.1.3.5 Three year Annual Means and 98"'
Percentiles (2000-2002) of PM2 5 for U.S. Sites
(FRM) within 200 km of the Canadian Border
Figure 3.13 shows 3-year average 98th percentile
(triangle) and 3-year average annual mean (dot)
concentrations of PM2 5 at "border' sites. The data
for FRM sites are for the years 2000-2002. The dis-
tance criterion of 'within 200 km of the border' is
useful to show relationships, while removing any
significant clutter observed on the figures when
the distance from the border is increased. Sites
are shown (left to right) in a west-to-east longitude
order while the vertical lines separate the regions.
The first site (left-most) in the Northwest is really
located in Alaska (undefined region). The dashed
horizontal line at 15 |ig/m3 corresponds to the
annual U.S. National Ambient Air Quality Standard
for PM2 5. Numerous FRM sites in the Industrial
Midwest have annual means over the standard.
Only 1 site elsewhere (Northwest; Libby, Montana)
exceeds the annual standard. PM2 5 concentra-
tions measured at the IMPROVE sites (mean and
98th), while not displayed, are below most of the
concentrations measured at the FRM sites, as
expected from the rural and urban comparison.
16
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CHAPTER 3
60
45
30
15
3-year annual mean displayed as dot 3-year average 98*1 percentile identified by star.
West to East (longitude) order
200k distance used in lieu of 300k to reduce dataset
A
A
A
A A
A A
a\ Aฑk
J, * * >
ฐo % C?
V^/ashington Montana Minn Michigan
Ohio
#% ฃ
New York VT
Maine
Figure; 3.13 - 3-year
annual means (ciotsji
and 98th percentiles
(triangles) (2QWMO02)
for U:S, sites within 200
km of the border (FRM)
Washington D.C. Site 9 Eastern Sites -*-23 Western Sites
Figure; Ss 14 - Average
measured annual PM, :g
concentration trend at
IMPROVE sites, 1992-
2t!01. To be included
sites must have&of
1 i valid years of data;
missing years are inter-
polated. Measured mass
represents measurement
from the filter.
3.1.3.6 Long-term Trends in PM2 5
Figure 3,14 shows the composite long-term trend
(1992-2001) at 9 eastern sites, 23 western sites,
and 1 urban site in Washington, D.C, all from the
IMPROVE network. At the rural eastern sites,
measured PM2 5 decreased about 16 percent from
1992 to 2001. At the rural western sites PM2 5
decreased about 10 percent from 1992 to 2001. At
the Washington, D.C. site, the annual average
PM2 5 concentration in 2001 was about 30 percent
lower than the 10-year peak in 1994.
17
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Canada - United States Transboundary PM Science Assessment
3.2 Ambient Characterization
of PM
3.2.1 Canada
There are significant differences in the chemical
composition of PM across Canada, resulting from
differences in contributing sources. Toward the
goal of effectively managing the emission and for-
mation of PM, recent work has sought to deter-
mine the chemical composition of PM at urban
sites (Brook et al., 1997, 1999; Brook and Dann,
1999). Analyses of PM2 5, collected at 14 cities
across Canada, indicate that seven major chemical
fractions are present (Figure 3.15). In approximate
order of size from largest to smallest, these frac-
tions are "undetermined" (generally assumed to be
black and organic carbon), SOj, NHJ, soil, NOg,
sodium chloride (NaCl) and "other" (thought to be
major ions, metals and possibly water, not allocated
to the other components).
Figure 3.16 shows the contribution of SO=,
NO3, NHJ and Total Carbonaceous Mass (TCM) to
PM2 5 concentrations across Canada. TCM com-
prises a large component of PM2 5 in Canada,
along with SOj, NO3 , and NHJ.
In these figures, TCM is estimated as:
(Organic Carbon Mass (OCM) + Black Carbon (BC) j
OCM is estimated as measured and blank-
corrected Organic Carbon (OC) multiplied by 1.40
to convert OC to OCM. Crustal concentrations are
estimated using the IMPROVE method.
The composition of PM2 5 varies seasonally
and has been examined at a rural site (Egbert,
Ontario) during both winter and summer "high
PM" episodic conditions (Figure 3.17). In the win-
ter episode, the seven major fractions of PM2 5
from largest to smallest were N03", NHJ, SOj,
organic carbon compounds, black carbon, soil and
other (major ions and metals not allocated to the
other components). In the summer episode, the
seven major fractions in descending order of size
were SOj, NHJ, organic carbon compounds, NO"3,
soil, black carbon and other. These data suggest
100%
90% 4
80% \
70%
60%
50%
40%
30%
20%
10% 4
(7.2) (7.4) (7.3) (8.5) (8.7) (7.4) (13.4115.4) (10.3) (11.8) (13.1) (8.7) (11.6) (9.3) (15.0) (12.3) (17.9110.9) (7.7) (5.5) (7.0) (7.1)
0%
Ct Cฃ >"
LU LU Ct
> >
ZD ZD
o o
o o
<
0
0 Ct
LU O
CL 00
Z Q
<
o
< <
> >
000
000
cm cm cm
000
< <
LU LU
cm cm
< <
LU LU
cm cm
ฃ
o
o
X X
o o
oooooฃ$$
X
<
<
X
ZD
0
< <
(f) (f)
ZD
o
en
<
o
~ Undetermined
~ Other
~ NaCl
~ NH4
~ N03
~ S04
~ Soil
Figure 3.15 - The fractional chemical composition of PM2 5 at various urban sites based on 1995-98 NAPS dichot data.
(In parentheses are the mean mass concentrations in |ig/m3. The "Undetermined" component is assumed to consist of
black and organic carbon. The "Other" component consists of the major ions, metals and possibly water not allocated
to the other components.)
18
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chapter 3
Yellowkriife, NW Territi
E d m oi i to n
Quebe
peg ottaw1
Vancouver
Windsor
Victoria
S irn coe
Halifax
Hamilton
Pt. Petre Toronto
Figure j;l6 - PM2 ซ speciation data for NAPS network sites in Canada September 2001 -August 2002. Size of pie-graphs
indicates average PM,. s- concentration for the time period evaluated.
that episodic conditions at this rural site are
driven by secondary NO3 formation in the winter
season, and secondary SOj formation in the
summer. In addition to the differences observed
in PM2 5 composition between seasons, it is
suggested that there are major differences in PM
composition between urban and rural sites-.
Samples of PM2 5 from urban sites in Canada have
higher average fractions of black and organic
carbon and lower fractions Of SOj and NO3 than
rural sites. This is consistently attributed to the
increased contribution of the mobile source sector
(including on-road, off-road and diesel vehicles) in
urban areas.
3.2.1.T Chemical Composition of the Organic
Fraction of PM2 5
Of the organic mass that is chemically resolved in
measurements, it is estimated that primary carbon
is a larger component of the mass compared with
the products of VOC oxidation. To date, it is pos-
sible to identify only 10 to 20 percent of the organ-
ic species composing the total organic carbon frac-
tion of PM; however, monitoring technology for
this fraction is evolving. At present, measurement
information is insufficient for determining whether
the unresolved portion of the organic mass origi-
nates as direct organic particle emissions, VOC
emissions that condense directly to particles, p"
19
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Canada - United States Transboundary PM Science Assessment
Figure 3.17 - The relative
composition of PM, 5 mass at
Egbert (ON) during (a) a winter-
time PM, 5 episode December
30, 1995, and (b) a summertime
episode June 1 1, 1999. (The data
are from the GAViM (Guelph
Aerosol and Visibility
Monitoring) program
(Njedley et al., 2003).)
(a)
30 December 1995
(b)
11 June 1999
Orqanics
5.4%
Black Carbon
1.5%
S04
13.9%
Other
0.2%
NH4
22.0%
~ Soil
~ S04
~ N03
~ NH4
~ Black Carbon
~ Organics
Other
N03
56.0%
PM2.5 = 32 /ig/m3
Organics
9.0%
Black Carbon
2.9%
NH4
23.9%
Other
0.3%
S04
53.0%
PM2.5 = 32 pg/m3
the condensation of VOC oxidation products. Of
the resolved portion of organic mass composing
PM, researchers have identified organic acids, fatty
acids, polycyclic aromatic hydrocarbons, petrole-
um biomarkers and straight-chain alkanes (Rogge
et al., 1993; Schauer et al., 1996). In Canada,
recent work has allowed the identification of each
of these groups of compounds by various analyti-
cal techniques; however, the application of these
techniques to ambient data is in the initial stages
(Blanchard et al., 2002).
3.2.2 United States
Atmospheric PM2 5 is composed of many different
chemical components that vary by location, time
of day, and time of year. Recent data from the rural
IMPROVE network and from the urban speciation
network provide indications of regional differences
in composition for PM2 5.
Figures 3.18 shows the composition of annual
average PM2 5 mass collected recently at several
sites in nine different regions. Figure 3.18 identi-
fies NHJ as a separate component of PM2 5 mass;
however, it is associated with either SO= or N03
(as (NH4)2S04 or NH4N03) roughly in proportion
to the amount of SOj and N03 indicated.
In general, fine-fraction particles in the east-
ern U.S. regions are dominated by carbon com-
pounds (TCM) and (NH4)2S04. In the western U.S.
regions, fine-fraction particles have a greater mass
of carbon compounds. With the exception of rural
locations in the desert west region, crustal materi-
al is a very small portion of fine-fraction particles.
The NH4N03 component is more prevalent in
urban aerosols than in rural aerosols, especially in
the California region, but also in the Industrial
Midwest and Northeast, and is an indication of
population-driven NOx sources, such as trans-
portation activity and combustion sources.
Similarly, the carbon component by estimated
mass is larger in urban areas compared to
surrounding rural areas and is an indication of
local contributing sources.
Figures 3.19 and 3.20 illustrate how SOj,
N03", and TCM (black and organic carbon) along
with other components, contribute to PM2 5 con-
centrations across the United States. These maps
represent the year with the most data where data
analysis has been completed: September 2001 -
August 2002.
20
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chapter 3
Regionalized Urban Speciation Patterns
Annual Average: Sep 2001 -Aug 2002
I Crustal Q Nitrate ~ Ammonium ~ Sulfate
~ TCM(h-1.4)
Figure 3.18 - Annual average composition of PM2 5 in the United States by region (Urban data from the EPA Speciation
Trends Network).
The U.S. EPA speciation data in Figure 3.19
illustrate that sites in urban areas generally have
higher annual PM2 5 concentrations than the rural
stations shown in Figure 3.20. Urban sites in the
East include a large percentage of TCM, SOj, and
associated NHJ, whereas., urban sites in the
Midwest and far West include a large percentage of
TCM and NOg. These patterns are also evident at
the Canadian locations (Figure 3.16). There are,
however, several sites in southern California where
the NOg fraction is of equal or greater proportion
than the carbon fraction.
The IMPROVE data in Figure 3.20 illustrate
that PM2 5 levels in the rural areas are highest in
the eastern United States and southern California,
as indicated by the larger circles. Sulphates and
associated NH4+dominate the east, with TCM as
the next most prevalent component. Sulphate
concentrations in the east largely result from S02
emissions from coal-fired power plants.- In
California and in the Midwest, TCM and NOginake
up most of the measured PM2 5.
Sulphates play a major role in the East,
Midwest, and South. Nitrates contribute to PM2 5
mass most in the Midwest and Northern locations,
Sites closest to the Canadian border (the North
Plains and Northwest sub-regions) are seen to
have relatively lower annual PM2 5 mass and con-
tain mostly carbon, SOj, and NO^, in that order.
For the domain of sites investigated, it is also seen
that the highest mass sites (for the year in ques-
tion) are in the East Coast, Northeast, and
Midwest.
Figure 3.21 shows seasonal variations for the
same grouping of urban and rural sites. In urban
areas, SOj and carbon dominate PM2 5 mass in
the summer season while NOj and TCM dominate
wintertime PM2 5 mass. Fall and spring show tran-
sitional amounts of each of the species when com-
pared to the summer and winter concentrations.
There is more NO^in the spring when compared to
the fall and higher TCM in the fall compared to the
spring.
2.1
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Canada - United States Transboundary PM Science Assessment
Ammonium
Nitrate
TCM
6.20
18.69
31.18
J
Figure 3.19 * Summary of urban speciation data for PM25 in the United States ;(EPA Speciation Network). Size of pie
graphs indicates average PM, s Concentration for the time period evaluated.
A
Sulfate
&
Ammonium
&
Nitrate
&
TCM
~
Crustal
o
00
1.71 7.91 14.11
Figure 3.20 - Summary of rural speciation data (IMPROVE network). Size of pie graphs indicates average PM, ซ
concentration for the time period evaluated.
22
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chapter 3
Select Urban Sites from EPA Speciation Network
Fall: Sep 2001-Nov 2001
sI 111
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g e
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I ! 11 ! I 11 f ;
z ง r
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MASS ~ Ammonium El TCM (k=1.4) ฆ Crustal
l~1 Sulfate ฆ Nitrate
Select Urban Sites from EPA Speciation Network
Winter: Dec 2001 -Feb 2002
S 0.6
tf f 1 1
# * I I '
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ฆ ฃ3. J s s s r a s | a a s | = ฆ 8 s - s b 8 g j
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2 " m n i i 84"
MASS Q Ammonium H TCM (k=1.4) ฆ Crustal
O Sulfate H Nitrate
CO I
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Select Urban Sites from EPA Speciation Network
Spring: Mar2002-May2002
I II II II II I III I III I III I II I I I I I I I I
ifli i9i!iRiPilili}jiiIilKi'li|iiiiili|i^spililiAi|iปiiini|iliiiPi
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s ; ; S 2 s 2 2 s : : ; S : 8 2 ! s S 5 ฆ S s 2 ! i = 8 8 I
11!!! 1 f 1111 j f! 11 n i j I i 1! 11 i1! || j
I4IIJ ! " 2iSB)5S8iฐ; s | "*
MASS ~ Ammonium^ TCM (k=1.4)H Crustal
f~l Sulfate ฆ Nitrate
18
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Select Urban Sites from EPA Speciation Network
Summer: Jun 2002-Aug 2002
I I I I laLIJaLI.IJ
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Canada - United States Transboundary PM Science Assessment
I
20
15
10
Figure 3.22 - Spatial distribution of wet SO^
deposition (kg/ha/yr) in eastern North America,
1996-2001.
Figure 3.23 - Five-year (1996-2000) mean wet deposi-
tion exceedanceof critical SO4 loads (kg SOj/ha/yr)
for 95% lake protection level.
Ohio River Valley. When compared to the critical
loads for wet SOj deposition in eastern Canada1,
large areas of eastern Canada are receiving wet SOj
deposition in excess of critical loads (Figure 3.23).
There has been a decrease in observed lake
acidity near Sudbury, Ontario as a result of sub-
stantial reductions in S02 emissions from local
smelters and other sources outside the region.
However, in other areas of Ontario, Quebec and
Atlantic Canada, there has been a lack of change in
acidity and acid neutralizing capacity. This is partly
a result of the long-term depletion of base cations
in watershed soils, which control lake chemistry as
well as forest health. It is predicted that with cur-
rent emission reduction commitments., an area of
almost 800,000 km2 in southeastern Canada will
receive harmful levels of acid deposition in 2010.
Canada If currently using a geochemical
model, Model of Acidification of Groundwater in
Catchments (MAGIC), to analyze the current status
of lakes, rivers and forest soils and to predict
recovery timelines. The predicted response of lakes
and rivers to a hypothetical 50-percent S02 reduc-
tion scenario, despite a quick pH recovery, is a
base cation recovery lag time of 100 years (Clair et
aL 2003), The recovery period is predicted to be
much slower for forests.
3.3.2 Wet Nitrate Deposition
Nitrogen is a growth-limiting nutrient which is
taken up and retained by vegetation. However, in
many watersheds, prolonged NOj deposition has
resulted in soil acidification. It is possible that
even with reduced SOj deposition received by
ecosystems, the effects of continued NOg acidifica-
tion on forest and aquatic ecosystems will coun-
5-Year (I9%-20()0) Mean XS04 Wet Deposition Exceedance (kg/ha/vr)
*
1 Critical load values for wetSOy deposition to aquatic ecosystems in eastern Canada were estimated in 1990 (RMCC , 1990),. Values
were estimated using the- average geochemical characteristics of tertiary watersheds and assigning, a protection level for lakes ฎf
95%. Areas with critical load values of lgss than 8 kg/ha/yr are considered to be very sensitive to acidification. It should he noted
however, that the use of wet SOJ deposition as; the primary environmental criterion for ecosystem protection has two limitations.
First, because the concurrent deposition of nitrate ions and base, cations has not been included, such a criterion considers'only1
residual SO^ deposition rather than the more general issue of residual acidification. The second limitation concerns the use.of wet
deposition information only. In eastern Canada, depending on the distance downwind from source regions, up to an additional 40%
of sulphur (and other chemical speciesj is dry deposited, contributing to acidification.
24
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chapter 3
5 ~
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Chapter
EMISSIONS
4.1 DEVELOPMENT OF
Emission inventories
4.1.1 Development of Canadian and
U.S. Emission Inventories for
REMSAD and AURAMS
National annual and seasonal emission invento-
ries for Canada and the United States were devel-
oped for application with the Regional Modelling
System for Aerosols and Deposition (REMSAD)
and A Unified Regional Air Quality Modelling
System (AURAMS). Applications of the two air-
quality models were employed to examine the
effects of U.S. and Canadian emission control
strategies on ambient concentrations of PM2 5 in
North America in 2010 and 2020. The purpose of
this section is to describe the assumptions used to
develop the emission inventories and the emis-
sion files used in these model applications.
The emission inventories developed by
Environment Canada and the U.S. EPA to support
these analyses include the following:
1995/1996 Base Year;
2010 Base Case;
2010 Control Case;
2020 Base Case; and
2020 Control Case.
4.1.1.1 Base Year Inventories
The Canadian 1995 comprehensive Criteria Air
Contaminants (CAC) emission inventory, version 2,
and the U.S. 1996 National Emission Inventory
(NEI) version 3.12 (EPA, 2001) were used for the
model applications. These inventories include
reported air pollutant emissions for oxides of
nitrogen (NOx), volatile organic compounds
(VOC), carbon monoxide (CO), oxides of sulphur
(SOx), primary particulate matter with an aero-
dynamic diameter less than or equal to 10 micro-
meters and 2.5 micrometers (PM10 and PM2 5)
and ammonia (NH3). The inventories include all
stationary, mobile and other sources that emit cri-
teria air pollutants. The specifics of the invento-
ries are discussed below.
CANADA: The Canadian 1995 CAC inventory
version 2 is produced via a collaborative effort
between Environment Canada and the provincial
and territorial governments. Due to confidentiality
issues, Canadian point sources were processed by
an outside consultant to maintain the confiden-
tiality of the information. Temporal profiles for
sources and sectors were made available for the
inventory processing. Mobile emissions in the
Canadian inventories were calculated using a
hybrid MOBILE 5C model, incorporating many new
MOBILE6 features for the on-road transportation
sector for 1995 and future years. Emission infor-
mation was then converted into a format compati-
ble with the REMSAD model.
UNITED STATES: The NEI is a national data-
base of air emission information with input from
numerous state and local air agencies, tribes, and
industry. The national inventories for this analysis
were prepared for the 48 contiguous states at the
county-level for on-highway mobile sources, elec-
tric generating units (EGUs), non-EGU point
sources, stationary area sources, and non-road
sources. The inventories do not include the states
of Alaska and Hawaii. The inventories contain
annual and typical summer season-day emissions
for the pollutants.
4.1.1.2 Base Case Inventories for 2010 and 2020
CANADA: To project CAC emissions to 2010 and
2020, annual growth factors are applied to the 1995
emissions for each industrial sector at the provin-
cial level. The growth factors are calculated from
surrogate data or from indicators obtained from
27
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Canada - United States Transboundary PM Science Assessment
Natural Resources Canada (NRCan) report
"Canada's Emissions Outlook: An Update,
December 1999". The national CAC forecast is the
sum of the provincial and territorial forecasts.
Environment Canada "grew" the 1995
Canadian inventory to 2010 and 2020 using the
Canadian CAC emission forecast scenario by
province and sector. The changes from the base
case to the future case scenario were then backed
out of the resulting files. The base case 2010 and
2020 inventories incorporate all of the emission
reduction measures that are already in place.
These include: Tier 1 and NLEV vehicles, Tier 2,
and heavy duty vehicle NMHC, NOx, PM standards,
and low sulphur on-road diesel and gasoline.
Inputs from provincial and territorial governments
and private industry were incorporated into the
forecast.
UNITED STATES: The 2010 and 2020 projec-
tion year base case files were calculated using
methods and models designed to support the U.S.
EPA's Proposed Program for Low-Emission
Nonroad Diesel Engines and Fuel (68 FR 28327)
and the Clear Skies Initiative (EPA, 2003a).
Included in the development of these estimates
was an adjusted version of EPA's MOBILE 5B
model, accounting for changes anticipated at the
time of this analysis to be included in the first
release of MOBILE 6, the March 2002 version of
EPA's NONROAD model, and for stationary, point,
and area sources, inventories (2020) and interpola-
tions from projected inventories (2010) as
designed to support the proposed nonroad rule
(EPA, 2003b). The emission projection files were
estimated using the 1996 base-year emission
inventory by applying growth and control factors
developed to simulate economic changes and con-
trol programs in place for each respective projec-
tion year and were designed to include the specif-
ic Clean Air Act Amendments emission reduction
measures promulgated and proposed by the U.S.
EPA at the time of the nonroad rule's publication
in the Federal Register.
Projection-year unit-level output files from the
EPA Modelling Applications 2003 version of the
Integrated Planning Model (IPM) were generated by
the U.S. EPA for the EGU sector base case for 2010
and 2020. Included in the base case runs were a
court-remanded version of the Regional Transport
NOx SIP Call reductions and state-specific emis-
sion caps in Connecticut, Massachusetts, Missouri,
New Hampshire, North Carolina, Texas, and
Wisconsin. The IPM files include heat input, S02
emissions, NOx emissions, and unit characteristics
such as prime mover (boiler, gas turbine), primary
fuel, boiler type, and firing type. In order to com-
plete the file to include all criteria pollutants and
data elements necessary to process the EGU sector
through an emission model, the U.S. EPA added to
the parsed IPM files emissions for VOC, CO, PM10,
PM2 5, and NH3 as well as physical characteristic
data elements needed for modelling (e.g., county
codes, coordinates, and stack parameters).
The base case assumptions between the U.S.
and Canadian 2010 and 2020 non-road and non-
EGU point source emissions differed slightly as a
result of the timing of the generation of these files.
The overall impact of these differences is believed
to be insignificant and therefore did not warrant
the rerun of the emission and air-quality models
for this analysis.
4.1.1.3 Control Case Inventories for 2010 and 2020
Control cases for Canadian and U.S. emissions are
based on proposed legislation or reduction initia-
tives that would further reduce emissions of con-
taminants that lead to ambient PM, acid deposi-
tion, and ground-level ozone.
CANADA: The control scenario for Canada
includes further reductions in 2010 and 2020 emis-
sions of S02 and NOx as part of the Canada-Wide
Standards for Particulate Matter and Ozone, and
the Canada-Wide Acid Rain Strategy. The 2010 and
2020 emissions were produced by "growing" the
1995 base year inventory to the required years
using Environment Canada's CAC forecast. Due to
time considerations, the inventory was "grown" by
province and sector. Due to a lack of information,
the NH3 portion of the inventory was held con-
stant for the 1995, 2010 and 2020 data years (data
on Canadian NH3 trends for the 1995-2000 period
are expected to be available in fall 2004).
28
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chapter 4
UNITED STATES: The control scenario
modelled for this analysis is based on the Clear
Skies Initiative in the United States. The proposed
Clear Skies legislation would create a mandatory
program that would reduce power plant emissions
of S02, NOx, and mercury by setting a national cap
on each pollutant. As in the base case, projection
year unit-level output files from the EPA Modelling
Applications 2003 version of IPM were generated
by the U.S. EPA for the EGU sector control case for
2010 and 2020.
Clear Skies was proposed in response to a
growing need for an emission reduction plan that
will protect human health and the environment
while providing regulatory certainty to the indus-
try. Currently, the Clear Skies initiative has been
modified and is now known as the Clean Air
Interstate Rule. More information and a complete
technical analysis of the 2003 proposed Clear Skies
legislation are now available at http://www.epa.gov/
clearskies/. Information on the Clean Air Interstate
Rule can be found at http://www.epa.gov/air/
interstateairquality/index.html.
4.1.2 Processing of Canadian and U.S.
Emission Inventories for REMSAD
and AURAMS
4.1.2.1 Processing of Emission Inventories for REMSAD
The emission files that were used in the REMSAD
air-quality model runs were processed through the
Sparse Matrix Operator Kernel Emissions
(SMOKE) Modelling System for annual meteoro-
logical episodes on a 36-km square domain cover-
ing Canada and the United States. A description of
SMOKE and the formats of its various required
inputs can be found at http://www.emc.mcnc.org/
products/smoke/.
Modifications were made to the emission-
inventory input files processed with SMOKE in
order to adjust the emission estimates to better
match the regional modelling objectives and spa-
tial scales and to provide a consistent basis
between base and projection year modelling
results for the development of relative reduction
factors (RRF).
One modification to the emissions processed
through SMOKE was the application of a crustal
PM transport factor to some fugitive dust emis-
sions. The purpose of this subgrid-scale adjust-
ment factor was to account for the fugitive dust
that is emitted into the atmosphere but is then
removed near the source (i.e., not all suspendable
particles are transported long distances: Watson
and Chow, 2000: Countess et al., 2001). For the
SMOKE input files, a factor of 25 percent (75 per-
cent reduction) was applied to PM10 and PM2 5 for
the SCCs associated with fugitive dust activities in
Canada and the United States. In addition, emis-
sions from wind erosion of natural geogenic
sources, on-site residential incineration, and for-
est wildfire emissions were excluded from the
modelling files due to their episodic nature or
unpredictability in future year emission estimates.
This assumption is not unreasonable given that
the focus of the future-year scenarios considered
in this study are emission control strategies for
two PM precursor gases, S02 and NOx. Although
prescribed fire activity was capped at base year lev-
els in the U.S. inventory, this practice was not
applied to Canadian emissions of the same source
category.
A third modification relates to NH3 emissions.
The default seasonal temporal profile for NH3
emissions from agricultural activities used by
SMOKE is uniform or the same for each season,
which is clearly unrealistic. This profile was
replaced by one from EPA's Office of Research
and Development based on the results of inverse
modelling using observed NHJ wet concentrations
(Gilliland et al., 2003). U.S. NH3 emissions from
livestock activities were seasonally distributed
using the new seasonal temporal profile, although
this practice was not applied to Canadian emis-
sions of the same source categories (EPA, 2001).
4.1.2.2 Processing of Emission Inventories for
AURAMS
The Canadian AURAMS model data was processed
in a different manner from REMSAD. Due to time
and other constraints, the Canadian 1990 emission
information that was contained in the model emis-
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Canada - United States Transboundary PM Science Assessment
sion files was adjusted to reflect the 1995
Canadian and 1996 U.S. emission inventories by
considering provincial and sectoral changes from
1990 to 1995. The result is that emission levels
used correspond to 1995 and 1996 levels but the
spatial distribution of emissions is based on the
1990 Canadian and U.S. emission inventories.
Some of the limitations of this process are that:
1990 inventories were distributed more on a
population basis than later inventories, which
use more spatial gridding surrogates;
The same scaling factors were applied to all
provincial and state sources within sectors,
which may have resulted in unrealistic emis-
sions for some sources, given the larger number
of point sources in later year inventories.
The AURAMS domain considered is shown in
Chapter 5, Figure 5.15. The gas-phase chemistry
mechanism considered is the ADOM-II mecha-
nism. As well, six primary PM chemical compo-
nents are considered: SOJ, N03", NHJ, BC, OC,
and crustal material.
4.1.3 Development and Processing of
Emissions used for CMAQ
The emission model selected to provide CMAQ
with the required temporal, spatial, and speciation
data was SMOKE, version 1.3. To the extent possi-
ble, the base year for emission data used in this
study was 2000. When year 2000 data were
unavailable, 1995 data were "grown" to the year
2000. U.S. data for 1996 were used alongside
Canadian data for 1995. U.S. data for 2002 were
used together with Canadian data for 2000, and
where 2002 data were unavailable, 1999 data were
used. Point, area, mobile (including marine), and
biogenic emission datasets were prepared (RWDI,
2003a) at a resolution of 4-km. For the 12-km res-
olution simulations with CMAQ, the emission data
were simply aggregated upward. Emission data
were assembled for both the summer and winter
periods. As with the REMSAD and AURAMS appli-
cations, wildfire emissions were not used due to
their episodic nature.
It should be noted that there are differences
between the lower Fraser Valley emission data
used in the model and those in the final version of
the GVRD year 2000 inventory. These small differ-
ences are the result of updated information and
improved emission estimates that were not avail-
able at the time of preparation of the model input
datasets. To gain insight into the impacts of trans-
boundary transport of air pollutants, two emission
scenarios were derived from the 2000 base case
emissions. In the first, all U.S. anthropogenic
sources were removed while in the second, all
Canadian anthropogenic sources were removed
(RWDI, 2003b). To gain insight into the impacts on
ambient air quality of future emissions, forecasted
emission inventories for the years 2010 and 2020
were prepared (RWDI, 2003c).
4.2 DESCRIPTION OF
Emissions in the
United states and
Canada
4.2.1 Emissions Used in AURAMS and
REMSAD
Table 4.1 lists the total emissions of PM2 5, PM10,
PMc (coarse fraction PM) and their precursors for
both Canada and the United States on an annual
basis, used as input into the REMSAD model.
Table 4.2 shows the same numbers for PM and PM
precursors, used as input into the AURAMS model.
These emissions are aggregated by state and
province, and summed to give annual totals for
each country. Between the base year of 1996 and
the forecasted year 2010, S02, NOx, and VOC emis-
sions are all expected to decrease significantly
in both countries, whereas NH3 emissions are
expected to increase slightly in the United States
(Canadian NH3 emissions were held constant). For
the future-year scenarios, NOx and S02 emissions
in both countries are projected to decrease signifi-
cantly, while CO, VOCs and NH3 change only slightly
between the base case and control scenarios.
30
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chapter 4
Table 4.1 Country-total anthropogenic emissions for PM and PM precursors on the REMSAD domain for
the 1996, 2010 base, 2010 control, 2020 base, and 2020 control inventory scenarios used as
REMSAD input. Units are in kilotons per year (and NOx as N02). Note: Canadian 1996 totals
do not include point sources.
Canada
United States
Pollutant
1996
2010b
2010c
2020b
2020c
1996
2010b
2010c
2020b
2020c
CO
12,808
8,266
8,266
9,045
9,045
94,804
87,777
87,785
98,216
98,236
NOx
3,023
2,262
2,184
2,183
1,994
24,653
17,733
15,968
14,578
12,313
VOC
2,928
2,391
2,370
2,542
2,507
18,245
13,803
13,802
13,899
13,898
nh3
578
578
578
578
578
4,838
5,001
5,001
5,230
5,230
S02
2,563
2,017
1,858
1,843
1,692
18,423
15,306
11,735
14,678
10,074
PM10
5,125
2,194
2,194
2,582
2,582
9,724
9,391
9,391
9,568
9,568
pm25
1,021
660
660
729
729
3,678
3,358
3,358
3,378
3,378
PMC
4,104
1,534
1,534
1,853
1,853
6,046
6,033
6,033
6,190
6,189
Table 4.2 Country-total anthropogenic emissions for PM and PM precursors on the AURAMS domain
for the 1996, 2010 base, 2010 control, 2020 base, and 2020 control inventory scenarios used
as AURAMS input. Units are in kilotons per year (and NOx as N02).
Canada
United States
Pollutant
1996
2010b
2010c
2020b
2020c
1996
2010b
2010c
2020b
2020c
CO
7,916
5,290
5,298
5,797
5,807
73,935
69,201
69,209
77,728
77,746
NOx
1,461
1,105
1,047
1,009
937
20,116
14,277
12,796
11,726
9,776
VOC
1,440
1,236
1,181
1,343
1,271
14,565
11,110
11,109
11,218
11,217
nh3
305
305
305
305
305
3,898
4,087
4,087
4,277
4,277
S02
1,702
1,520
1,335
1,373
1,165
16,715
13,943
10,424
13,227
8,720
PM10
1,239
1,656
1,654
1,920
1,916
7,172
6,993
6,993
7,149
7,149
pm25
320
403
401
447
443
2,740
2,494
2,494
2,511
2,511
PMC
919
1,253
1,253
1,473
1,473
4,432
4,499
4,499
4,638
4,638
Emission inputs to REMSAD and AURAMS for
S02, NOx, NH3, PM2 5, VOC, CO and PM10 for the
1996 base case and the 2010 and 2020 base and
control cases are shown visually in Figures 4.1
through 4.7. The anticipated additional U.S. and
Canadian control programs result in a significant
reduction in S02 and NOx emissions. Summer
weekday S02 emission input to REMSAD for the
1996 base year is provided in Figure 4.1a. Summer
weekday base-case S02 emission input to REM-
SAD for 2010 and 2020 is provided in Figures 4.1b
and 4.2a, where summer refers to June, July, and
August and summer weekday is an average of
Mondays to Fridays throughout these three
months. Summer seasonal S02 emissions are
illustrated because emissions of S02 lead to the
formation of particle SOj and summer concentra-
tions of SOj exceed winter concentrations. Winter
weekday NOx emissions for the 1996 base year are
illustrated in Figure 4.3a. Winter weekday base-
case NOx emission input to REMSAD for 2010 and
2020 are provided in Figures 4.3b and 4.4a. Winter
NOx emissions are shown as NOx emissions lead
to the formation of particle nitrate, and winter
31
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Canada - United States Transboundary PM Science Assessment
ambient concentrations of particle nitrate are
higher than summer concentrations. Summer and
winter NHa emissions for the 1996 base year are
shown in Figures 4.5a and 4.5b. Summer base-
case NH3 emission inputs for 2010 and 2020 are
provided in Figures 4.6a and 4,7a. Emissions of
ammonia are significant due to the role of ammo-
nia in the formation of ammonium sulphate and
ammonium nitrate.
The reduction in summer weekday S02 emis-
sions with the additional U.S. and Canadian con-
trols for 2010 and 2020 are shown in Figures 4.1c
and 4.2b. The reduction in winter weekday NOx
emissions with the additional U.S. and Canadian
controls are shown in Figures 4.3c and 4.4b. Only
reductions for these two PM precursors are shown
because the additional control measures for 2020,
discussed in Section 4.1.1.3, are concerned only
with these two pollutants (plus mercury for the
proposed Clear Skies legislation). Note that the
reductions in both S02 and NOx are concentrated
in the eastern half of the domain, which suggests
that the atmospheric response to these reductions
will also be concentrated in this region. Winter
base-case NH3 emission inputs for 2010 and 2020
are provided in Figures 4.6b and 4.7b. The emis-
sions of NH3 in the winter season are significant
because they are involved with the reaction of NOx
emissions to form particle ammonium nitrate.
Winter MEL emission inputs are significantly less
than summer NH3 emission inputs, particularly in
the U.S. portion of the domain.
Base Case S02 Emissions
0.000
Tons/Day
1996 Summer Weekday
m=199G_summer_so2.pave.new
800.00099
100.000
ZOO .000
100.000
50.000
20.000
10.000
5.000
2.000
1.000
January 1,0 0:00:00
Min= 0.000 at (1,1), Max= 937.948 at (106,56)
156
Figure 4.1a ฆ 1996
Summer weekday
S02 emissions for
Canada and the
United States;.
32
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chapter 4
15.000
2.000
1.000
u 0.000
tons/day
PAVE
MCfic
Min=
Hour: 00
0.000 at (1,1), Max= 773.069 at(106,56)
800.00099
400.000
200.000
100.000
50.000
20.000
10.000
Base Case S02 Emissions
2010 Summer Weekday
o=b10sum.ioapi
"J
Q-!_ ^ -
Figure 4. lb - 2010
Su mmer weekday
base case SQa
emissions for
Canada and the
United States.
Reduction in S02 Emissions from US/Canada Controls
2010 Summer Weekday
m=c10sum.ioapi, o=b10sum.ioapi
0.000 99
-1.000
-2.000
-5.000
-10.000
-20.000
-50.000
-100.000
-200.000
-400.000
u -800.000
tons/day
PAVE
by.
Hour: 00
Min=-656.482 at (106,56), Max= 48.351 at (101,40)
Figure 4.1c - 2010
Summer Weekday
reductions in $02
emissions for
Canada and the
United States.
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Canada - United States Transboundary PM Science Assessment
800.00099
400.000
Z00.000
100.000
50.000
20.000
10.000
5.000
2.000
1.000
0.000 1
tons/day
PAVE
MCifc
Base Case S02 Emissions
2020 Summer Weekday
c=b20sum.ioapi
Hour: 00
Min= 0.000 at(1,1), Max= 718.091 at(10S,56)
"i
v
Figure 4.2a - 202(3
Summer weekday
base case S02:-
emissiofis for
Canada arid the
United States,
Reduction in SO2 Emissions from US/Canada Controls
Summer Weekday (2020 Control -2020 Base)
i=c20sum.ioapi, k=b20sum.ioapi
0.000 99
-1.000
-2.000
-5.000
-10.000
-20.000
-50.000
-100.000
-200.000
-400.000
u -800.000 1
tons/day
1
156
by nuur.uu
(CfiC Min=-S37.967 at (106,56), Max= 31.439 at (89,63)
Figure 4.2b - 2020
Summer weekday
reductions in SCX,
emissions for
Canada and the
United States.
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chapter 4
Base Case NOx Emissions
1996 Winter Weekday
d=1996_wi nte r_n ox. p ave
500.00099
250.000
50.000
BO .000
40.000
20.000
10.000
5.000
2.000
1.000
0.000
January 1,0 0:00:00
Min= 0.000 at (1,1 J, Max= 709.046 at (89,60)
156
Figure 4.3a - 1996
Winter weekday
NO^.emissiens for
Canada and the
United States.
Base Case NOx Emissions
2010 Winter Weekday
h=b10wtr.ioapi
500.00099
J
250.000
150.000
80.000
40.000
20.000
10.000
5.000
2.000
1.000
0.000
tons/day
Hour: 00
Min= 0.000 at (1,1), Max= 547.459 at (89,60)
156
Figure 4.3b - 2010
Winter weekday
base case NOx
emissions for
Canada and the
United States.
35
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Canada - United States Transboundary PM Science Assessment
Reduction in NOx Emissions from US/Canada Controls
Winter Weekday (2010 Control -2010 Base)
f=c10wtr.ioapi, h=b10vrtr.ioapi
0.000 99
-0.500
1.000
-2.000
-4.000
B.000
15.000
30.000
50.000
-100.000
-200.000 i
tons/day i
PAVE
M[$C
Hour: 00
Min=-214.775 at(106,5G), Max= 14.022 at(75,31)
156
Figure 4.3c - 2010
Winter weekday
reductions in NOx
emissions for
Canada and the
United States,
0.000 1
tons/day
PAVE
Mcfc
Base Case NOx Emissions
2020 Winter Weekday
d=b20wtr.ioapi
500.00099
250.000
150.000
BO .000
40.000
20.000
10.000
5.000
2.000
1.000
Hour: 00
Min= 0.000 at (1,1), Max= 472.384 at (89,60)
156
Figure 4.4a - 2020
Winter weekday
base case NOx
emissions for
Canada and the
United States.
36
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chapter 4
I
Reduction in NOx Emissions from US/Canada Controls
Winter Weekday (2020 Control - 2020 Base)
b=c20wtr.ioapi, d=b20wtr.ioapi
0.000 99
-0.500
-1.000
-2.000
-4.000
8.000
15.000
30.000
50.000
-100.000
^ -200.000 1
tons/day
PAVE
MCiSc
Hour: 00
Min=-217.544 at (106,56), Max=
4.680 at (62,77)
156
Figure 4.4b - 202D
Winter weekday
reductions in NO
emissions for
Canada and thฉ
United Stateฎ--
0.000 1
Tons/Day 1
Base Case NH3 Emissions
1996 Summer Weekday
e=199G_s u m me r_n h3. p ave
200.00099
100.000
50.000
20.000
10.000
5.000
2.000
1.000
156
January 1,0 0:00:00
Min= 0.000 at (1,1), Max= 140.621 at (83,25)
Figure 4.5a ป 1996
Summer weekday
N.H3. emissions for
Canada and the
United Statesv
37
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Canada - United States Transboundary PM Science Assessment
0.000 1
Tons/Day 1
Base Case NH3 Emissions
1996 Winter Weekday
f=1996_wi nte r_n h3. p ave
200.00099
100.000
50.000
20.000
10.000
5.000
2.000
1.000
January 1,0 0:00:00
Min= 0.000 at (1,1), Max= 139.731 at (83,25)
156
Figure 4.5b - 1996
Winter weekday
NHS emissions fe
Canada and the
United States.
0.000 1
tons/day
PAVE
Melt
Base Case NH3 Emissions
2010 Summer Weekday
h=b10sum.ioapi
200.00099
5
100.000
50.000
20.000
10.000
5.000
2.000
1.000
156
Hour: 00
Min= 0.000 at (1,1), Max= 165.425 at (83,25)
Figure 4.6a - 2010
Summer weekday
base case NH3
emissions for
Canadaand the
United States.
38
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chapter 4
0.000 1
tons/day
Base Case NH3 Emissions
2010 Winter Weekday
I=b10wtr.ioapi
200.00099
i
100.000
50.000
20.000
0.000
5.000
2.000
1.000
January 1,0 0:00:00
Min= 0.000 at (2,2), Max= 164.514 at (83,25)
156
Figure 4.6b - 20IS
Winter weekday
base case NHS
emissions for
Canada and the
United States.
LJ 0.000 1
tons/day
PAVE
b|
MCfic
Base Case NH3 Emissions
2020 Summer Weekday
d=b20sum.ioapi
200.00099
100.000
50.000
20.000
10.000
5.000
2.000
1.000
156
Hour: 00
Min= 0.000 at (1,1}, Max= 182.723 at (83,25)
Figure 4.7a -1020
Summer Weekday
base case Mils
emissions for
Canada and thfi
United States.
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Canada - United States Transboundary PM Science Assessment
^ 0.000 1
tons/day 1
PAVE
McSc
Base Case NH3 Emissions
2020 Winter Weekday
I=b20wtr.ioapi
200.00099
100.000
50.000
20.000
10.000
5.000
2.000
1.000
156
Hour: 00
Min= 0.000 at (1,1), Max= 181.767 at (83,25)
Figure 4.7b - 2020
Winter weekday
base case: NH-3
emissions lor
Canada and the
United States,
4.3 KEY SCIENCE MESSAGES
Emission inventory information was combined
for both Canada and the United States to pro-
vide input to two multi-pollutant models
(AURAMS and REMSAD) for both base case and
control scenarios for the years 2010 and 2020.
Emissions of S02 and NOx are projected to
decrease while NH3, VOCsand CO increase in
the future-year base cases. S02 and NOx emis-
sions are projected to decrease further with the
future-year control scenarios (2010 and 2020).
Emissions of S02 and NOx under all consid-
ered scenarios are concentrated in the
Industrial Midwest Northeastern United States
and Southern Ontario, while emissions of NH3
are typically Concentrated further west in the
central Midwest region.
The emissions of S0Ol NO
and NH3, and their
contributions to PM2 5 levels vary seasonally.
NH3 emissions and biogenic NOx (and VOC)
emissions have the largest seasonal variations.
40
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Chapter
AIR-QUALITY MODEL APPLICATIONS
Three emission-based PM air-quality models
have been applied to address Objective 7 of
this Assessment: "To identify the impact of current and
proposed emission reduction scenarios on fine PM levels in
North America". The first air-quality model, REM-
SAD, was run for one year (1996) for a domain
including the 48 contiguous U.S. states, southern
Canada, and northern Mexico for the 1996 base
case and four future-year emission control strategy
scenarios (described in Chapter 4). REMSAD-pre-
dicted fields are presented for January and July
1996 as well as for the entire year to illustrate the
impact of seasonality on PM2 5 mass and chemical
composition for the different scenarios. The sec-
ond model, AURAMS, was run for the same five
scenarios as REMSAD for one 2-week winter peri-
od and one 2-week summer period on a domain
roughly corresponding to the eastern half of the
REMSAD domain. As recommended in the
NARSTO PM Assessment (Seigneur and Moran,
2003), the application of two different air-quality
models to the same scenarios permits the similar-
ity and consistency of the predictions of both mod-
els to be examined. The third model, CMAQ, was
used on a smaller domain to investigate both (a) a
base scenario and two future-year emission sce-
narios and (b) the role of transboundary transport
in the western border region comprised of
Washington state and southwestern British
Columbia. A winter period and a summer period
were considered using CMAQ.
As discussed in Chapter 4, the two pairs of
future-year emission control strategy scenarios
considered by REMSAD and AURAMS differed
principally in the emissions of two PM gaseous
precursors, S02 and NOx. Emissions of VOCs, CO,
NH3, and primary PM changed by less than 1 per-
cent between the 2010 and 2020 scenario pairs
(see Tables 4.1 and 4.2). As a consequence, the
analysis of the model results presented for REM-
SAD and AURAMS focus on changes in total PM2 5
mass and on three inorganic PM components:
S04, N03, and NH4. Concentrations of other PM
chemical components such as crustal material and
black carbon should not differ for these scenarios,
although secondary organic aerosol formation can
be indirectly affected through the impact of NOx
emission changes on oxidant concentrations. For
the CMAQ future-year emission scenarios, on the
other hand, emissions of both primary PM and PM
gaseous precursors were changed, so attention is
focused on predicted changes in PM2 5 total mass.
Results from REMSAD and AURAMS are
presented first followed by results from CMAQ.
REMSAD and AURAMS model predictions are
compared with ambient measurements for the
base case scenario in the Appendix in order to pro-
vide an indication of model skill and the uncertainty
associated with predictions of different PM com-
ponents. The model results in general are in
agreement with the recent conclusions of Seigneur
and Moran (2003), that state-of-the-science PM air
quality models perform reasonably well in predict-
ing the inorganic chemical components of PM2 5,
with greater certainty for SO J than for NHJ (due to
greater emissions uncertainties) and NOj (due to
complexities of gas-particle partitioning for this
semi-volatile component).
5.1 RESULTS OF REMSAD
CONTROL STRATEGY
MODELLING
The Regional Modelling System for Aerosols and
Deposition (REMSAD) Version 7.06 (ICF Kaiser,
2002) model was used as a tool for simulating
base year and future air quality concentrations.
Five one-year model runs were performed with
REMSAD using 1996 meteorology. These runs
41
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Canada - United States Transboundary PM Science Assessment
were: (1) 1996 base case, (2) 2010 base case, (3)
2020 base case, (4) 2010 control case, and (5) 2020
control case. The 1996 base case results were used
to evaluate the performance Of REM SAD in pre-
dicting observed concentrations in 1996. The
results of this model performance evaluation are
provided in the Appendix. Existing controls (i.e.
legislation/ agreements) in each country were
included in the 2010 and 2020 base case runs while
the 2010 and 2020 control runs contain additional
anticipated controls for each country (as described
in Chapter 4). The REMSAD model was used to
estimate hourly air-quality concentrations and
acid deposition for an entire year for each model
run. This section reports results for the 2010
annual PM2 5 concentration and the 2020 annual,
January, and July PM2 5, SOJ, N03", and NHJ
concentrations. The modelling domain used in
REMSAD is shown in Figure 5.1.
5.1.1 REMSAD Results
Annual average ambient PM2 5 concentrations for
the 2010 base case are provided in Figure 5.2a
while annual. lanuary, and July average PM2 5 con-
centrations for the 2020 base case are provided in
Figures 5.3a, 5.4a, and 5.5a. Annual, lanuary, and
July average particle SOj concentrations for the
2020 base case are provided in Figures 5.6a, 5.7a,
and 5.8a and annual, January, and July average par-
ticle NOgConcentrations for the 2020 base case are
shown in Figures 5.9a, 5.10a, and 5.11a. Annual,
January, and July average NHJ concentrations for
the 2020 base case are illustrated in Figures 5.12a,
5.13a, and 5.14a. Figure 5.2b shows annual average
PM2 5 air quality concentration reductions for
2010 that result from the implementation of con-
trols in the United States and Canada. Annual,
January, and July average PM2 5 concentration
reductions for the 2020 scenario are provided in
Figures 5.3b, 5.4b, and 5.5b. Annual, January, and
July average SOj concentration reductions that
result from U.S. and Canadian controls in 2020 are
shown in Figures 5.6b, 5.7b and 5.8b while Figures
5.9b, 5.10b, and 5.11b illustrate annual, January,
and July average particle NO~ concentration reduc-
tions that result from U.S. and Canadian controls
in 2020. Annual, January, and July average NHJ
concentration reductions that result from the 2020
controls are shown in Figures 5.12b, 5.13b and
5.14b. Many1 control measures already underway
Figure 5.1 - REMSAD modelling
domain (-36x36 km2), Grid
squares eneampass 1/2 degree:
longitude, 1/3 degree latitudes
g-W range; 54 degrees W - 13?
degrees W; N^S range:
22 degrees N - 55 degrees N.
Vertical extent: Ground to
16,200 meters flOOmb) with
12 layers,
42
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chapter 5
are incorporated into the 2010 and 2020 base case
air quality results while the reductions predicted by
the model result from additional U.S. and Canadian
controls that are expected to be implemented.
In the 2010 and 2020 base cases, areas of the
United States and Canada are above the U.S.
annual air-quality standard of 15 pg/m3. Some of
the higher PM2 5 concentrations in large Canadian
cities result from a large quantity of unpaved road
dust emissions being spatially allocated by popu-
lation. This could be corrected by spatially allocat-
ing these emissions to actual unpaved roadways.
U.S. and Canadian controls that are expected to be
implemented result in a maximum annual PM2 5
reduction of 1.8 pg/m3 in 2010 and 2.3 pg/m3 in
2020 with the maximum annual reductions pre-
dicted in Pennsylvania. Larger reductions in
PM2 5 concentrations occur however, over shorter
averaging periods. The spatial pattern for the
January average 2020 control case reduction of
PM2 5 mass is similar to the spatial pattern for the
January particle N03 reduction while the spatial
pattern for the July average 2020 control case
reduction of PM2 5 is similar to the spatial pattern
for the SOj reduction. The maximum January
average PM2 5 reduction in 2020 is 1.8 pg/m3 and
the maximum reduction in July average PM2 5
mass is 3.3 pg/m3. The 2010 and 2020 control
cases will result in significantly more areas below
the U.S. annual standard of 15 pg/m3, but several
areas in the eastern United States and Canada will
remain above the U.S. standard.
The base case maximum annual S04 concen-
tration in 2020 is predicted to be 4.9 pg/m3. U.S.
and Canadian controls that are expected to be
implemented in 2020 result in annual reductions
of SOJ concentrations of up to 1.4 pg/m3 with the
maximum reductions predicted in Pennsylvania.
SOj concentrations and predicted reductions in
S04 with the additional U.S. and Canadian con-
trols are much higher in July than in January. The
maximum base case 2020 January average SOj air
quality concentration is predicted to be 2.3 pg/m3
while the maximum July average S04 concentra-
tion is predicted to be 7.0 pg/m3. The 2020 control
case results in a maximum reduction of January
average SOJ concentration of 0.6 pg/m3 and a
maximum reduction of July average SOj concen-
trations of 2.4 pg/m3.
The maximum annual particle NOj concentra-
tion in 2020 is predicted to be 4.2 pg/m3. U.S. and
Canadian controls that are expected to be imple-
mented result in annual reductions of particle NO"3
concentrations up to 0.6 pg/m3 in 2020 with the
maximum annual reduction located in Indiana.
Particle NO"3concentrations and the corresponding
reduction in particle NOjwith the additional U.S.
and Canadian controls are much higher in January
than July. The maximum base case 2020 January
average particle N03 concentration is predicted to
be 5.9 pg/m3 and the maximum July average parti-
cle NOjconcentration is predicted to be 2.4 pg/m3.
The 2020 control case results in a maximum reduc-
tion of January average particle N03" concentra-
tions of 1.1 pg/m3 and a maximum reduction
of July average particle N03" concentrations of
0.4 pg/m3.
The maximum annual NHJ concentration is
2.8 pg/m3 in 2020. U.S. and Canadian controls that
are expected to be implemented result in predict-
ed annual reductions of NHJ concentrations of up
to 0.6 pg/m3 in 2020 with the maximum annual
reductions predicted in Pennsylvania. The spatial
pattern of NH+ concentration reductions is similar
to the spatial pattern of particle NO"3concentration
reductions in January and close to the spatial pat-
tern of sulphate concentration reductions in July.
This is a result of the majority of NH+ in winter
being associated with NH4N03 and the majority of
NHJ in the summer being associated with
(NH4)2S04. Larger reductions in NH3 with the
additional U.S. and Canadian controls in 2020 will
occur in the summer than in the winter. The 2020
control case results in a maximum January NHJ
concentration reduction of 0.4 pg/m3 and a July
maximum reduction of 0.8 pg/m3. The REMSAD
results are consistent with known atmospheric
chemistry relationships between SOj, N03 and
NHJ in both the summer and the winter seasons.
43
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Canada - United States Transboundary PM Science Assessment
Figure 5.2a - Annual
ฆaverage- PM, !
concentrations
2010 baBe-casei.
Figure 5.2b -
Reductions in
annual PMj g
cjincentrations
from controls
in 2010
PM2.5 Concentrations
LJ 0.000 1
ug/m3
PAVE
tcrlc
Annual 2010 Base Case
b=csa10be1p1_v706ext.ioapi
24.000 98
21.000
18.000
15.000
2.000
9.000
6.000
3.000
a
Hour: 00
Min= 0.298 at (155,2), Max= 51.001 at (131,93)
155
Reduction in PM2.5 Concentrations from US/Canada Controls
Annual Concentrations (2010 Control - 2010 Base)
b=csa10be1p1_v706ext.ioapi, c=csa10ce1 p1_v706ext.ioapi
-0.000 98
-0.300
-0.600
-0.900
1.200
-1.500
-1.800
2.100
-2.400
ug/m3
155
Hour: 00
Min= -1.818 at (105,55), Max= 0.005 at (18,45)
44
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chapter 5
PM2.5 Concentrations
18.000
15.000
12.000
2020 Annual Base Case
d=csa20be1p1_v706ext.ioapi
24.000 98
21.000
9.000
6.000
3.000
0.000
ug/m3
PAVE
MCifc
Min=
Hour: 00
0.295 at (155,2), Max= 54.882 at (131,93)
Figure 5.3a - Annual
average PM,. e
concentrations
2020 base easg-
Reduction in PM2.5 Concentrations from US/Canada Controls
Annual Concentrations (2020 Control - 2020 Base)
d=csa20be1 p1_v706ext.ioapi, e=csa20ce1p1_v70Gext.ioapi
-0.000 98
-0.300
-0.600
-0.900
-1.200
-1.500
-1.800
-2.100
-2.400
ug/m3
PAVE
by.
Hour: 00
Min= -2.301 at(112,55), Max= 0.001 at(2S,52)
Figure 5.3b -
Reductions in
annual PMj j
Concentrations
from controls
in 2020.
45
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Canada - United States Transboundary PM Science Assessment
LJ 0.000 1
ug/m3
PftVE
Mcfc
PM25 Concentrations
January 2020 Base Case
s=csa20be1 pi v706ext.01 .monavg.dat.ioapi
24.000 98
21.000
18.000
15.000
12.000
9.000
6.000
3.000
S
155
Hour: 00
Min= 0.196 at (155,2), Max= 50.980 at (117,71)
Figure 5..4a. -
January average
PM2 s concentra
tions n base
case.
Reduction in PM2.5 Concentrations with US/Canada Controls
January 2020 (Control - Base)
q=csa20ce1p1_v706ext.01.monavg.dat.ioapi, s=csa20be1 pi_v706ext.01 .monavg.dat.ioapi
-0.000 98
-0.300
-0.600
0.900
-1.200
-1.500
-1.800
-2.100
-2.400
ug/m3
155
Hour: 00
Min= -1.858 at(101,35), Max= 0.011 at(27,42)
Figure 5,4b -
ReduCtiotts in
January PM2j
conggntrations
from controls
'in
46
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chapter 5
PM2.5 Concentrations
18.000
15.000
12.000
9.000
6.000
3.000
pi 24.000 98
21.000
July 2020 Base Case
t=csa20be1p1_v706ext.07.moriavg.dat.ioapi
0.000
ug/m3
PAVE
tele
1
1 155
Hour: 00
Min= 0.194 at (155,2), Max= 46.473 at (131,93)
Figure 5.5a - July
average PML, a
concentrations
2020 base case.
Figure 5.5b -
Reductions in
July fiSfcjj
concentrations
from Controls
in 2020.
-1.800
Reduction in PM2.5 Concentrations with US/Canada Controls
July 2020 (Control - Base)
r=csa20ce1 p1_v706ext.07.monavg.dat.ioapi, t=csa20be1p1_v706ext.07.monavg.dat.ioapi
-0.000 98
I -1.200
' -1.500
-2.100
-2.400
ug/m3
PAVE
1
Hour: 00
Min= -3.308 at (111,52), Max= 0.010 at (18,76)
47
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Canada - United States Transboundary PM Science Assessment
Sulfate Concentrations
3.600
3.000
2.400
n 4.800 98
4.200
2020 Annual Base Case
=csa20be1 pi _v706ext.ioapi
Hour: 00
MCflu Min= 0.123 at (155,2), Max= 4.870 at (103,56)
d
1.800
1.200
0.600
u 0.000 i
ug/m3
V
IC'V"'-*.
Figure 5.6a - Annual
average: SOy
Concentrations
2020 base: case.
Reduction in Sulfate Concentrations from US/Canada Controls
Annual Concentrations (2020 Control - 2020 Base)
d=csa20be1 p1_v706ext.ioapi, e=csa20ce1p1_v706ext.ioapi
0.00 98
-0.20
-0.60
-0.80
-1.00
-1.20
-1.S0
ug/m3
PAVE
Hour: 00
Min= -1.41 at (106,56), Max= 0.02 at (48,45)
Figure 5.6b -
Reductions in
annual SO^
concentrations
from Controls
in 2020,
48
-------
chapter 5
0.000 1
ug/m3
PAVE
Mcifc
Sulfate Concentrations
January 2020 Base Case
s=csa20be1 p1 v706ext.01 .monavg.dat.ioapi
4.800 98
4.200
3.600
3.000
2.400
1.800
.200
0.600
Hour: 00
Min= 0.045 at (155,2), Max= 2.282 at (108,32)
155
Figure 5.7a - January
average SOj
concentrations
2020 base case.
Reduction in Sulfate Concentrations from US/Canada Controls
January 2020 (Control - Base)
q=csa20ce1p1_v706ext.01.monavg.dat.ioapi, s=csa20be1p1 v706ext.01.monavg.dat.ioapi
0.000 98
0.200
-0.400
-0.600
-0.800
-1.000
1.200
-1.400
-1.000
ug/m3
Hour: 00
Min= -0.558 at (129,35), Max= 0.005 at (48,45)
155
Figure 5.7b -
Reductions in
January SOj
concentrations
from controls
in 2020.
49
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Canada - United States Transboundary PM Science Assessment
0.000
ug/m3
PAVE
b!
Mcifc
Sulfate Concentrations
July 2020 Base Case
t=csa20be1p1 v706ext.07.monavg.dat.ioapi
4.800
4.200
3.600
3.000
2.400
1.800
1.200
0.600
155
Hour: 00
Min= 0.045 at (155,2), Max= 6.975 at (114,54)
Figure 5.8a - July
average S O j
oonsJSntrations
2020 base case.
Reduction in Sulfate Concentrations with US/Canada Controls
July 2020 (Control - Base)
r=csa20cel pi _v70Gext.07.monavg.dat.ioapi, t=csa20be1 p1_v706ext.07.monavg.dat.ioapi
0.000 98
-0.200
-0.400
-0.600
-0.800
1.000
1.200
1.400
1.600
ug/m3
155
Hour: 00
Min= -2.436 at (111,50), Max= 0.002 at (19,76)
Figure 5,8b .
Reductions in
JulySOj
cont^nttations
from controls
in 2020.
50
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chapter 5
fl
^ 0.000 1
ug/in3
PAVE
Mclc
Particle Nitrate Concentrations
2020 Annual Base Case
d=csa20be1 p1 _v706ext.ioapi
4.800 98
4.200
3.600
3.000
2.400
1.800
1.200
0.G00
155
Hour: 00
Min= 0.000 at (52,6), Max= 4.163 at (112,55)
Figure 5.9a - Annual
average NO^
concentrations
2020 base case.
Change in Nitrate Concentrations with US/Canada Controls
Annual Concentrations (2020 Control - 2020 Base)
d=csa20be1p1_v706ext.ioapi, e=csa20ce1p1_v70Gext.ioapi
I
0.150 98
0.050
0.050
0.150
0.250
0.350
0.450
0.550
0.650 1
ug/m3
PAVE
Hcfc
155
Hour: 00
Min= -0.640 at (90,53), Max= 0.089 at (121,57)
Figure 5.9b -
Reductions in
annual NO^,
concentrations
from controls
in 2020.
51
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Canada - United States Transboundary PM Science Assessment
n
0.000 1
ug/m3
PAVE
mcNc
Particle Nitrate Concentrations
January 2020 Base Case
s=csa20be1 p1 v706ext.01 .monavg.dat.ioapi
4.800 98
4.200
3.600
3.000
2.400
.800
1.200
0.600
s.
Hour: 00
Min= 0.000 at (154,3), Max= 5.925 at (101,35)
155
Figure 5.1.0a -
January average
NO J concentrations
2Q20 base case.
Change in Nitrate from US/Canada Controls
January 2020 (Control - Base)
q=csa20ce1p1_v706ext.01.monavg.dat.ioapi, s=csa20be1p1_v706ext.01.monavg.dat.ioapi
0.150 98
s
%
0.050
0.050
-0.150
-0.250
-0.350
0.450
-0.550
-0.650 1
ug/m3
PAVE
MCifc
Hour: 00
Min= -1.093 at (101,35), Max= 0.102 at (118,49)
155
Figure 5.1Db -
Reductions in
January N03
concentrations
from controls
in 2020.
52
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chapter 5
0.000 1
ug/m3
PAVE
MClfc
Particle Nitrate Concentrations
July 2020 Base Case
t=csa20be1 pi _v706ext.07.monavg.dat.ioapi
4.800 93
4.200
3.600
3.000
2.400
1.800
1.200
0.600
155
Hour: 00
Min= 0.000 at (153,4), Max= 2.375 at (29,36)
Figure 5.1 la - July
average 80J
concentrations
2020 base case,
Change in Nitrate Concentrations with US/Canada Controls
July 2020 (Control - Base)
r=csa20ce1p1_v706ext.07.monavg.dat.ioapi, t=csa20be1p1_v706ext.07.monavg.dat.ioapi
0.150 98
5
0.050
0.050
0.150
0.250
0.350
0.450
0.550
-0.650 1
ug/m3
PAVE
MCijc
Hour: 00
Min= -0.402 at(106,66), Max= 0.191 at(117,60)
155
Figure 5.1 lb -
Reductions in
July N03
concentrations
frorn controls
in 2020.
53
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Canada - United States Transboundary PM Science Assessment
Ammonium Concentrations
1.800
1.500
1.200
0.900
0.600
0.300
Hi 2.400 98
2.100
2020 Annual Base Case
d=csa20be1 p1_v706ext.ioapi
0.000 1
ug/m3
PAVE
mcNc
Hour: 00
Min= 0.028 at (155,2), Max= 2.756 at (114,54)
i
2_l
Figurfe5.12a-
Annual average
NHJ concentrations
2020 base case,
Figure 5.12b -
Reductions in
annual NHJ
concentrations
from controls
in 2020.
Reduction in Ammonium Concentrations from US/Canada Controls
1-0.10
-0.20
-0.30
-0.40
-0.50
-0.60
Annual Concentrations (2020 Control - 2020 Base)
d=csa20be1p1_v706ext.ioapi, e=csa20ce1p1_v706ext.ioapi
0.00 88
-0.70
u -0.80
ug/m3
PAVE
by.
1
Hour: 00
Min= -0.58 at (112,55), Max= 0.00 at (46,19)
ฆvv
v
54
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chapter 5
0
0.000 1
ug/m3
PftVE
MCffc
Ammonium Concentrations
January 2020 Base Case
s=csa20be1p1_v70Gext.01.monavg.dat.ioapi
2.400 98
2.100
1.800
1.500
1.200
0.900
0.600
0.300
155
Hour: 00
Min= 0.017 at (155,2), Max= 2.429 at (101,35)
Figure 5,13a -
January average
NHJ concentrations
2020-base case.
Reduction in Ammonium Concentrations with US/Canada Controls
January 2020 (Control - Base)
q=csa20ce1p1 _v706ext.01 .monavg.dat.ioapi, s=csa20be1p1_v706ext.01.monavg.dat.ioapi
o.ioo
-0.200
-0.300
-0.400
-0.500
-0.600
-o./oo
m -0.800 1
ug/m3
PAVE
MC&
Hour: 00
Min= -0.446 at (101,35), Max= 0.003 at (27,42)
Figure 5.13b -
Reductions in
January NHJ
concentrations
from controls
in 2020.
55
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Canada - United States Transboundary PM Science Assessment
a
0.000 1
ug/m3
PftVE
MC^C
Ammonium Concentrations
July 2020 Base Case
t=csa20be1 pi v706ext.07.monavg.dat.ioapi
2.400 98
3
Z.I 00
1.800
1.500
1.200
0.900
0.600
0.300
S
Hour: 00
Min= 0.017 at (155,2), Max= 2.930 at (114,54)
155
Figure 5.14a -
July average NHJ"
eortcentrations 2020-
base case.
Reduction in Ammonium Concentrations with US/Canada Controls
July 2020 (Control - Base)
r=csa20ce1p1_v706ext.07.monavg.dat.ioapi, t=csa20be1p1_v70Sext.07.monavg.dat.ioapi
0.000 98
0.100
0.200
0.300
0.400
0.500
0.600
-0.700
0.800 1
ug/m3
PAVE
M(Sc
Hour: 00
Min= -0.848 at (112,55), Max= 0.035 at (143,35)
Figure 5.14b -
Reductions in
July NHJ
concentrations
from controls
in 2020.
56
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chapter 5
5.1.2 Conclusions
PM2 5 concentrations are composed of SO= NOj,
NHJ, OC and BC, soil, and other components. The
U.S. and Canadian controls that are expected to be
implemented will reduce PM2 5 concentrations in
both countries in 2010 and 2020 although the
reduction is predicted to be larger in 2020 than
2010. The reductions in PM2 5 concentrations are
larger in the eastern portion of the modelling
domain than the western portion of the modelling
domain. Implementation of controls results in
S02 and NOx emissions reductions, with these
emissions reductions leading to corresponding
reductions in particle SO= and NOjconcentrations
in both the United States and Canada. Sulphate
concentrations are highest and are reduced more
significantly in the summer months while particle
NOj concentrations are highest and reduced more
significantly during the winter months. Although
NH3 emissions are not currently addressed in the
strategies that are expected to be implemented by
2020, NHJ concentrations are predicted to be
reduced in both countries. Ammonia emissions
participate in reactions with gaseous S02 and
NOx, resulting in the formation of (NH4)2S04 and
NH4N03 particles. When S02 and NOx are
reduced, there are fewer S02 and NOx emissions
available for NH3 emissions to react with to form
NHJ. Thus, reducing both S02 and NOx emis-
sions leads to a concurrent reduction in particle
NHJ concentrations in addition to ambient SOj
and NOj concentrations. The reduction in NHJ in
the winter months is dominated by NHJ associat-
ed with NH4N03 and the reduction in NH+ in the
summer months is dominated by NHJ associated
with (NH4)2S04. Since the future controls that are
expected to be implemented only reduce S02 and
NOx emissions, these controls will not reduce the
OC and BC, soil, and other components of PM2 5.
It is predicted that implementation of the U.S. and
Canadian controls will greatly reduce the areas in
both countries exceeding the U.S. annual standard
of 15 pg/m3.
5.2 RESULTS OF AURAMS
CONTROL STRATEGY
MODELLING
AURAMS (A Unified Regional Air-quality Modelling
System) is a new size- and composition-resolved,
episodic, regional PM modelling system devel-
oped by the Meteorological Service of Canada.
AURAMS (version 0.30a) was run for two 2-week
periods for the same five emission scenarios as
REMSAD in order to provide an independent eval-
uation of the relative impact of these scenarios.
Both a winter period and a summer period were
simulated to allow consideration of the seasonal
impact of the emission reductions. The winter
simulations span the period from the 1st to the
15th of February 1998; this period was chosen in
part because of the occurrence of a wintertime
regional PM episode during the second week (Vet
et al., 2001). The summer simulation spans the
period from the 1st to the 18th of July 1995; this
period includes a regional ozone episode (July 12-
15) that was also associated with high levels of PM
in both Canada and the United States. As well,
this episode occurred during the summer 1995
NARSTO Northeast ozone field campaign so
enhanced measurement data are available for the
period (e.g., Ryan et al., 1998).
While AURAMS is a more complex model than
REMSAD in a number of important respects,
including its representations of gas-phase chem-
istry (ADOM-II mechanism vs. micro-CB-IV mecha-
nism), heterogeneous chemistry (HETV vs. MARS-
A), and PM2 5 size distribution (8 size sections vs.
one size section), it is also much more demanding
computationally. For this report, AURAMS was run
for four weeks and five scenarios whereas REMSAD
was run for a one-year period for the same five sce-
narios. Given these differences in model sophisti-
cation and run length, it is of interest to see how
similar (qualitatively) the REMSAD and AURAMS
results and conclusions are for the same scenarios.
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Canada - United States Transboundary PM Science Assessment
Centre's variable-grid regional configuration to
provide the meteorological fields. The regional
GEM grid includes a uniform mesh with 24-km hor-
izontal grid spacing over North America and 28
vertical levels up to 10 hPa (about 30 km).
Horizontal interpolation of the meteorological
fields was required to go from the 24-km GEM grid
to the 42-km AURAMS grid as was vertical interpo-
lation to go from GEM's r| vertical coordinate to
AURAMS's modified Gal-Chen vertical coordinate.
GEM employed a 7.5-minute timestep, so that
AURAMS was presented with meteorological fields
from every second GEM timestep.
For each simulation period, one "present-day"
AURAMS base simulation was run along with four
future-year emission reduction scenario simula-
tions. In all, ten AURAMS simulations were avail-
able to be compared either to observations or to
each other. All of the future-year scenario runs
were identical in all respects to their present-day
base simulation except for the anthropogenic
emission files that were provided to the model.
As discussed in Chapter 4, ten different sets of
anthropogenic emissions files were constructed,
five for the winter period and five for the summer
period. For the two present-day base case simula-
tions, 1990 and 1995 Canadian and 1990 and 1996
U.S. emission-inventory data were used to produce
the emissions files. For the future-year emission
reduction scenarios, four sets of emissions files
were prepared for year 2010 and four for year 2020.
For each of these future years, there were two
"Approved" (or "base") emissions cases - one each
for winter and summer - and two "Proposed" (or
"control") cases. The "Approved" emission scenar-
ios contain only the effects of legislation that has
already passed in both the United States and
Canada. The "Proposed" cases add the effects of a
few major pieces of legislation still being debated in
either the United States or Canada (see Chapter 4).
A summary description of the ten cases is pre-
sented in Table 5.1 while Table 5.2 provides a sum-
mary of the relative differences in anthropogenic
primary PM2 5 and gaseous precursor emissions
between three scenario pairs (cf. Table 4.2). Note
from Table 5.2 that the change in emissions
5.2.1 Model Setup, Emission Files, and
Post-Processing
The horizontal modelling domain for all of the
AURAMS air-quality simulations is presented in
Figure 5.15. The horizontal domain is 85 by 105
grid points with 42 km grid spacing. In the vertical,
the model is set up with 29 levels up to about 22
km above ground. Nineteen of the levels are below
5 km. The model uses a 15-minute timestep.
Two sets of meteorological fields were pre-
pared to drive the AURAMS simulations, one set of
fields for the summer simulations and one for the
winter simulations. The Global Environmental
Multiscale (GEM) model (Cote et al., 1993; 1998a, b),
version 3.0.3 with version 3.8 of the physics pack-
age, was used in the Canadian Meteorological
Figure 5.15 - AURAMS domain for all simulations
(85x105 grid points, Ax=42 km). For each simulation
period, one "present-day" AURAMS base simulation
was run along with four future-year emission reduction
scenario simulations. In all, ten AURAMS simulations
were available to be compared either to observations
or to each other. All of the future-year scenario runs
were identical in all respects to their present-day base
simulation except for the anthropogenic emission files
that were provided to the model.
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chapter 5
Table 5.1 Characteristics of ten AURAMS simulations.
Description
Episode
Emission Year
Reductions Included
1995 summer base case
1-18 July 1995
1995 Can. / 1996 U.S.
None
2010 summer base case
1-18 July 1995
2010
Approved
2020 summer base case
1-18 July 1995
2020
Approved
2010 summer control case
1-18 July 1995
2010
Proposed
2020 summer control case
1-18 July 1995
2020
Proposed
1995 winter base case
1-15 February 1998
1995 Can. / 1996 U.S.
None
2010 winter base case
1-15 February 1998
2010
Approved
2020 winter base case
1-15 February 1998
2020
Approved
2010 winter control case
1-15 February 1998
2010
Proposed
2020 winter control case
1-15 February 1998
2020
Proposed
Table 5.2 Percent differences between scenario emissions of primary PM2 5 and PM precursors on the
AURAMS domain for three pairs of scenarios (based on Table 4.2). A positive value indicates
an increase in emissions in going from the first scenario to the second scenario of the pair.
Emitted
Pollutant
201 OB Vs. 2020B
Can. U.S. Dom.
201 OB Vs. 2010C
Can. U.S. Dom.
2020B Vs. 2020C
Can. U.S. Dom.
pm25
10.9
0.1
2.1
-0.6
0.0
-0.1
-0.9
0.0
-0.1
S02
-9.7
-5.1
-5.6
-12.2
-25.2
-23.9
-15.1
-34.1
-32.3
NOx
-8.7
-17.9
-17.2
-5.3
-10.4
-10.0
-7.2
-16.6
-15.9
VOC
8.7
1.0
1.7
-4.5
0.0
-0.5
-5.4
0.0
-0.6
nh3
0.0
4.7
4.3
0.0
0.0
0.0
0.0
0.0
0.0
between the 2010 base and 2020 base cases is
qualitatively different from the change in emis-
sions between the 2010 base and 2010 control and
the 2020 base and 2020 control scenario pairs.
More species have emission changes and in both
directions in this first pair of cases than in the
other two pairs of cases. For biogenic emissions,
winter and summer emissions files were produced
based on each of the two sets of meteorology. The
same wintertime biogenic emission files were used
for all five winter simulations and the same sum-
mertime biogenic emission files were used for all
five summer simulations.
Only the last part of each simulation was used
to evaluate model performance and/or summarize
results (see the Appendix for a performance evalu-
ation of AURAMS for the two present-day base
simulations). This allows enough time for
AURAMS to spin-up in the first week of each simu-
lation. A two-day spin-up period is usually
thought to be sufficient for ozone chemistry, but
previous experiments with AURAMS have shown
that four to five days may be needed to reach
steady state for particulate matter. Results from
the emission-reduction scenarios were averaged
for the last nine days of the winter period (Feb. 7-
15, 1998) and for the last 11 days of the summer
period (July 8-18, 1995).
5.2.2 Evaluation of Emission Reduction
Impacts
5.2.2.1 Winter Period
Figures 5.16 to 5.19 summarize the AURAMS
model results for the winter scenario simulations.
The four panels in Figures 5.16 and 5.18 show the
predicted ground-level PM2 5 mass and PM2 5
SOj, NHJ, and NOg concentration fields averaged
over the last nine days of the simulations (Feb. 7-15,
1998) for the 2010 and 2020 base cases, respectively.
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Canada - United States Transboundary PM Science Assessment
The same colour scheme used for the REMSAD PM
concentration plots in Section 5.1 has also been
used for the AURAMS PM concentration plots, but
note that the contour intervals selected for the
AURAMS plots are larger than those for the REM-
SAD plots. This choice is a consequence of the
shorter averaging time used for the episodic
AURAMS results (9 days vs. 91 days or 365 days),
which results in greater variability since the 9-day
period includes a PM2 5 episode and hence larger
maximum values. "Hotter" colours indicate higher
concentrations.
It is evident from inspection of Figures 5.16
and 5.18 that NH4N03 is predicted to be the dom-
inant inorganic compound in PM2 5 during this
period as the NH+ and PM2 5 mass fields have
similar distributions to the nitrate field. Sulphate
is present in the 3-5 |ig/m3 range in the Ohio Valley
and U.S. Southeast and is still the dominant inor-
ganic compound in the Southeast (e.g., Georgia,
Florida, Alabama). Note that the elevated PM2 5
levels predicted by AURAMS over the Atlantic
Ocean are not due to anthropogenic emissions but
rather are the result of sea-salt emissions from the
ocean in the presence of strong winter winds.
Note that as the predicted sea-salt emissions are
determined only by meteorology, they will be the
same for all of the winter simulations and hence
will cancel out in any difference calculations.
Table 5.2 shows that on a model-domain basis,
VOC, NH3, and primary PM2 5 emissions are
modestly larger for the 2020 base case than for the
2010 base case (2 percent, 4 percent, and 2 percent,
respectively) whereas S02 and NOx emissions are
smaller by 6 percent and 17 percent, respectively.
This would suggest a priori that PM2 5 SO= concen-
trations should be smaller for the 2020 base case
than for the 2010 base case while PM2 5 total mass,
PM2 5 N03, and PM2 5 NHJ concentrations might
either increase or decrease. Comparing Figures
5.16 and 5.18, we see that maximum PM2 5 mass
increases slightly, maximum PM2 5 NOj decreases
slightly, and maximum PM2 5 NHJ increases
slightly for the 2020 base case relative to the 2010
base case. However, maximum PM2 5 SOj also
increases even though S02 emissions have
decreased. Based on additional analysis, a likely
explanation for the predicted wintertime increase
in SOj concentration, despite the decrease in S02
emissions, is an increase in oxidant concentrations
(OH and 03) and hence in gas-phase and aqueous-
phase S02-to- SOj conversion due to the concomi-
tant decreases in NOx emissions. This explanation
is consistent with the predicted ground-level N02
and 03 fields south of the Great Lakes for these two
cases (not shown), for which the 2020 base N02
field is a few ppb higher than the 2020 control N02
field and the 2020 base 03 field is a few ppb lower
than the 2020 control 03 field, suggesting reduced
N02 titration of 03 in the 2020 control case. Other
studies have also suggested the possibility of such
nonlinear responses in SOj concentrations for
multiple emission reduction scenarios (e.g., Stein
and Lamb, 2002).
The four panels in Figures 5.17 and 5.19 show
the predicted ground-level PM2 5 mass and PM2 5
SOJ, NHJ, and N03 difference fields averaged over
the last nine days of the winter simulations (Feb.
7-15, 1998) for the 2010 control case minus the
2010 base case and for the 2020 control case minus
the 2020 base case, respectively. Again, the same
colour scheme used for the REMSAD PM concen-
tration difference plots in Section 5.1 has also
been used for the AURAMS PM concentration dif-
ference plots, but the contour intervals that have
been selected for the AURAMS plots are again
larger than those for the REMSAD plots. The con-
tour intervals are also slightly shifted. For the
PM2 5 mass and PM2 5 v and NHJ difference
fields, the colour "gray" corresponds to positive
differences, bluish colours indicate smaller nega-
tive differences, and the hotter colours indicate
larger negative differences. Note that a negative
difference indicates a reduction in going from the
base case to the control case (i.e., the predicted
control field is smaller in magnitude than the pre-
dicted base field). The PM2 5 N03 difference field
required special treatment because increases and
decreases of comparable magnitude are predicted
to occur for this field. Accordingly, the zero differ-
ence value maps to the light blue colour in the
middle of the colour bar.
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chapter 5
Figure 5.16 - Nine-daiy-average PM2 5 mass Concentration field and PM2 5 inorganic chemical component aDrteentration
fields predicted by AURAMS for the Pgb. 7-15, 1998 winter period for the "2010 base" case-ernissions: (a) top left panel -
PM2 s mass; (b) top right panel - Pf|3 5 SOJ mass; (cj lower left panel - PMj j NHjmass; :(d): lower right panel -
PM2 S: N03 mass. All fields are at 15 m height in units of jig/m%
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Canada - United States Transboundary PM Science Assessment
Figure 5.17 Nine-day-average PM 5 mass concentration difference field and PM2 5 inorganic chemical component
concentration difference fields predicted byAURAMS for the Feb. 7-15, 1998 winter period for the "201Q control" ease
minus the "2010 base" esse: (a) top left panel - PM2 -s mass; (b) top right panel - PMa ฎ SOj mass; (C); lower left panel
- PM2 5 NHJ mass-, (d); lower right panel - PM2 5 N03mass. All fields are at 15 m height in units: of |.ig/m3. Negative
values denote a reduction for the "2010 control" case relative to the "201Q base" casei
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chapter 5
ug/m3
Min = 0.00 at (58.94N, 73.01 W) Max = 34.01 at (41.69N, 87.86W)
Figure 5.18 - Same as Figure 5.16 but for the "2020 base" case emissions.
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Canada - United States Transboundary PM Science Assessment
Figure 5.19 - Same as Figure 5.17 but for the "2020 control" case minus the "2020 base"
PM2.5
ug/m3
0.0
-1.0
-2.0
-3.0
-4.0
-5.0
-6.0
-20.0 I
PM2.5
N03
ug/m3
PM2.5
S04
ug/m3
0.0
Min = -2.42 at (41.60N, 92.46W) Max = 1.32 at (36.74N, 86.68W)
Min = -0.55 at (41.60N, 92.46W) Max = 0.23 at (36.74N, 86.68W)
Min = -1.46 at (31.88N, 83.87W) Max = 0.50 at (42.89N, 95.96W)
Min = -1.89 at (41.65N, 92.90W)
Max = 1.57 at (36.74N, 86.68W)
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chapter 5
Comparison of the 2010 and 2020 winter con-
trol case simulations with the corresponding base
case simulations (Figures 5.17 and 5.19) indicates
that the additional S02 and NOx emissions reduc-
tions proposed beyond current (i.e., "Approved")
legislation result in a small net reduction in PM2 5
mass in the lower atmosphere in the winter in
much of the AURAMS domain, although small
PM2 5 mass increases up to 1 |ig/m3 are predicted
in the Ohio Valley. The explanation for such a non-
linear response when emissions of both S02 and
NOx have decreased significantly (by 24 percent
and 10 percent and by 32 percent and 16 percent,
respectively, on a domain basis) and emissions of
other species are effectively unchanged (see Table
5.2) can be seen from the behaviour of the three
PM2 5 inorganic ions.
Whereas PM2 5, SOj and NHJ experience
reductions in most of the domain, PM2 5 N03
behaves quite differently. The region east of the
Mississippi River, where SOj levels are high and
NHJ values are low (e.g., Figure 5.16 b-c), is known
to be NH3-limited. Large reductions in S02 emis-
sions in this region will result in reduced SOj
levels and may permit "N03 substitution", a phe-
nomenon where reductions in SOj concentration
may free up NH3 gas which can then react with
HN03 vapour to form NH4N03 (e.g., West et al.,
1999). When this occurs, the net result is a small-
er corresponding decrease or even an increase in
PM2 5 levels. West of the Mississippi River, on the
other hand, SOj levels are lower, NH4N03 occurs
more commonly, and decreases in NOx emissions
result in predicted decreases in particle N03levels.
The decreases are larger for the 2020 control-base
scenario pair, consistent with the larger NOx
reductions for this scenario.
5.2.2.2 Summer Period
Figures 5.20 to 5.23 summarize the AURAMS PM2 5
predictions for the summer episode simulations.
Figures 5.20 and 5.22 are summer-period counter-
parts to Figures 5.16 and 5.18 for the winter period;
the four panels in Figures 5.20 and 5.22 show the
predicted ground-level PM2 5 mass and PM2 5
SOj, NHJ, and N03concentration fields averaged
over the last 11 days of the simulations (July 8-18,
1995) for the 2010 and 2020 base cases, respective-
ly. The colour scheme and contour intervals are
the same for these two figures and are also identi-
cal to those used in the two winter-period figures,
allowing easy comparison of seasonal variations.
The relative contributions of particle SOj and
N03 are reversed for the summer period vis-a-vis
the winter period. It is clear from Figures 5.20 and
5.22 that SOj is predicted to be the dominant con-
stituent of PM2 5 during the summer over eastern
North America, with SOj contributing over half of
PM2 5 mass east of the Mississippi. (Note that the
SOj contours are exactly half the magnitude of the
PM2 5 contours.) Particle N03, on the other hand,
is predicted to be a minor component restricted to
a few areas with high NH3 emissions and lower
SOj levels. Note that the PM2 5 levels predicted
by AURAMS over the western Atlantic Ocean are
due to both transport of continental pollutants
and sea-salt emissions from the ocean surface.
The contribution of sea-salt emissions is also evi-
dent in northern Canada in Hudson Bay and James
Bay, where PM2 5 levels were predicted to be much
lower in this same area in the winter time due to the
presence of sea-ice cover (cf., Figures 5.16 and 5.18).
As noted in Section 5.2.2.1, Table 5.2 shows
that domain-total emissions of VOC, NH3, and pri-
mary PM2 5 are larger for the 2020 base case than
for the 2010 base case whereas S02 and NOx emis-
sions are smaller. This suggests a priori that PM2 5
S04 concentrations should be smaller for the 2020
base case relative to the 2010 base case while
PM2 5 total mass, PM2 5 N03, and PM2 5 NHJ
concentrations might either increase or decrease.
Comparing Figures 5.20 and 5.22, we see that max-
imum PM2 5 SOj does decrease for the 2020 base
case (by 3 |ig/m3), maximum PM2 5 NHJ decreas-
es slightly (by 0.1 |ig/m3), maximum PM2 5 N03
also decreases (by 1 |ig/m3), but maximum PM2 5
mass increases slightly (by 0.06 |ig/m3). The prob-
able explanation for the predicted increase in sum-
mer maximum PM2 5 mass, despite the decrease
in SO=, NO~, and NHJ concentrations, is a larger
increase in local primary PM2 5 emissions (see
Table 5.2).
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Canada - United States Transboundary PM Science Assessment
The four panels in Figures 5.21 and 5.23 show
the predicted ground-level PM2 5 mass and PM2 5
SOj, NHJ, and N03 difference fields averaged over
the last 11 days of the summer simulations (July 8-
18, 1995) for the 2010 control case minus the 2010
base case and for the 2020 control case minus the
2020 base case, respectively. Again, the colour
scheme and contour intervals for these two figures
are identical to those used in the two winter-peri-
od difference-field figures (Figures 5.17 and 5.19),
allowing easy comparison of seasonal variations.
Comparison of the 2010 and 2020 summer
control case simulations with the corresponding
base case simulations (Figures 5.17 and 5.19) indi-
cates that the additional S02 and NOx emissions
reductions proposed beyond current (i.e.,
"Approved") legislation result in reductions in
PM2 5 mass of up to over 6 |ig/m3 across most of
the AURAMS domain. These reductions are driven
by reductions in PM2 5 SO= mass and related but
much smaller reductions in PM2 5 NHJ mass.
Interestingly, as in the winter period, a small
increase in PM2 5 N03 concentration (in the 0.2-
1.0 |ig/m3 range) is predicted to occur in the U.S.
Northeast and the Atlantic and Gulf of Mexico
states in spite of the overall decreases in NOx
emissions for these two scenario pairs (10% and
16%, respectively). Again, as in the winter case, the
probable explanation for this is N03 substitution.
This explanation is supported by the differences
between Figures 5.21b and 5.23b and Figures 5.21 d
and 5.23d in the southeastern U.S. Comparing
Figures 5.21b and 5.23b, the predicted reduction in
SOj levels over Alabama and eastern Tennessee is
noticeably larger for the 2020 scenario pair than for
the 2010 scenario pair. This difference is consis-
tent with the geographic variations in the imposed
S02 emission reductions. If the S02 emission
reductions for the 2010 control-base scenario pair
and 2020 control-base scenario pair are tabulated
on a regional basis, the decreases in S02 emis-
sions for the 2010 and 2020 scenario pairs are 33
percent and 35 percent, respectively, for the states
near the Great Lakes (MI, OH, KY, IN, IL, WI), 35
percent and 43 percent for the northeastern U.S.
states, but 12 percent and 35 percent for the south-
eastern states (NC, SC, GA, FL, AL, MS, TN). The
relatively larger decrease in SOj concentrations in
the Southeast is then accompanied by a relatively
larger increase in PM2 5 N03 concentration in the
Southeast as compared to the U.S. Northeast or
Great Lakes regions.
5.2.3 Comparison with REMSAD Results
It is not appropriate to compare results from the two
sets of episodic AURAMS simulations directly with
the REMSAD 1996 annual results presented in
Section 5.1 due to issues of representativeness.
However, the monthly REMSAD results for January
and July 1996 that are also presented in Section 5.1
provide more suitable reference points and permit a
qualitative comparison between the two models'
predictions of seasonal differences in atmospheric
response to the same emission reductions. (A direct
comparison is still not appropriate since the simula-
tion periods and hence the meteorological condi-
tions are different.] This comparison can in turn
provide additional weight of evidence to support the
reasonableness of both models' predictions (when
two such independent models agree at least qualita-
tively with each other) or else raise questions when
the predictions disagree both quantitatively and
qualitatively (e.g., Seigneur and Moran, 2003).
For the 2020 base case in mid-winter, AURAMS
and REMSAD both predict NH4N03 to be the
dominant inorganic compound over eastern North
America (compare Figure 5.18 and Figures 5.4a,
5.7a, and 5.10a). Like AURAMS, REMSAD also pre-
dicts a west-to-east decrease in PM2 5 N03 differ-
ences across the U.S. Midwest and Ohio Valley for
January 1996 (see Figures 5.10b and 5.19d) and the
occurrence of some particle N03" increases (i.e.,
disbenefits) for NOx emission reductions.
For the 2020 base case in the summer,
AURAMS and REMSAD both predict PM2 5 SOj to
be the dominant inorganic species by mass (com-
pare Figure 5.22 and Figures 5.5a, 5.8a, and 5.1 la).
The AURAMS and REMSAD PM2 5 N03fields in the
summer have quite similar spatial patterns, char-
acterized by scattered pockets of elevated N03
along the southern shore of Lake Michigan, the
northern shore of Lake Erie, and in the Mississippi
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chapter 5
Figure 5 20 -: ElgSien-day-aVefage PM2-5 mass Concerttration field and PUL 5 inorganic chemical component
Concentration fields predicted by AURAMS for the July S-18, 1995 summer period for the "2010 base" rase emissions:
(a) top left panel - JWJB mass; (a) top right panel - PM j5 SOj mass; (c) lower left panel - PM, 5 NHJ mass; (d) lower
right panel - PM2 s Nt|g mass. All fields are at 15 m height in units of |Jg/m3.
S04
ug/rn3 I
Min = 0.00 at (60.57N, 83.03W) Max = 36.18 at (38.99W, 81.57W)
PM2.5
N03
ug/m3 I
17.5 |
Min = 0.00 at (24.92N, 80.36W) Max = 16.78 at (30.23N, 89.84W)
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Canada - United States Transboundary PM Science Assessment
PM2.5
ug/m3
35.0 |
Min = 0.17 at (63.16N, 93.45W) Max = 49.57 at (40.93N, 73.97W)
PM2.5
S04
ug/m3 I
17.5 |
Min = 0.00 at (60.57N, 83.03W) Max = 8.27 at (30.23N, 89.84W) Min = 0.00 at (24.92N, 80.36W) Max = 16.78 at (30.23N, 89.84W)
Figure 5.21 -: Eleven-day-average PM2 5 mass concentration difference field and PM2 5 inorganic chemical component
concentration difference fields predicted by AURAMS for the July 8-18, 1995 summer period for the "2010 control" case
minus the "2010 base" case: (a) top left panel - PM2 5 mass; (b) top right panel - PM2 5 SO^ mass; (c) lower left panel -
PM2 5 NHJ mass; (d) lower right panel - PM2 5 NO3 mass. All fields are at 15 m height in units of jag/m3. Negative values
denote a reduction for the "2010 control" case relative to the "2010 base" case.
.a
Min = 0.00 at (60.57N, 83.03W) Max = 36.18 at (38.99N, 81.57W)
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chapter 5
PM2.5
S04
ug/m3
Min = 0.17 at (63.16N, 93.45W) Max = 49.63 at (40.93N, 73.97W) Min = 0.00 at (60.57N, 83.03W) Max = 33.86 at (34.33N, 84.60W)
PM2.5
N03
ug/m3
Min = 0.00 at (60.57N, 83.03W) Max = 8.15 at (30.23N, 89.84W) Min = 0.00 at (24.52N, 79.17W) Max = 15.83 at (30.23N, 89.84W)
Figure 5,22 - Same, as Figure 5,20 but lor M "2020 base" case emissions.
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Canada - United States Transboundary PM Science Assessment
PM2.5
NH4
ug/m3
0.0
Min = -18.37 at (34.33N, 84.60W) Max = 1.64 at (27.91 N, 96.74W)
Min = -2.51 at (33.SON, 81.68W) Max = 0.18 at (34.50N, 78.03W)
Min = -19.01 at (34.33N, 84.60W) Max = 0.07 at(45.65N, 96.17W)
Max = 3.81 at (43.24N, 77.56W)
PM2.5
N03
ug/m3
= -1.04 at (33.08N, 89.98W)
Figure 5.23 < Same as Figure 5.21 but for thซ*2020 control" case minus the "2020 base" case.
70
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chapter 5
delta (Figures 5.11a and 5.22d). The spatial pat-
terns of the REMSAD 2020 control-base scenario
pair differences for July 1996 are also qualitatively
similar to the AURAMS difference fields for PM2 5
and PM2 5 SOj (Figure 5.5b vs. Figure 5.23a and
Figure 5.8b vs. Figure 5.23b, respectively), but less
so for PM2 5 NHJ (Figure 5.14b vs. Figure 5.23c)
and not at all for PM2 5 N03" (Figure 5.11b vs.
Figure 5.23d). The agreement for SOj changes and
disagreement for NOj changes between the two
models is consistent with current assessments of
PM model performance that uncertainties are larg-
er for NO"3 prediction than for SOj prediction (e.g.,
see Appendix).
Both AURAMS and REMSAD predict the maxi-
mum wintertime reductions in PM2 5 to be small-
er than, and to occur to the west of, the maximum
summertime reductions (Figure 5.19a vs. Figure
5.23a; Figure 5.4b vs. Figure 5.5b), although
AURAMS does not support the REMSAD predic-
tions of large wintertime reductions of PM2 5 in
the Carolinas. Finally, despite the mix of emission
increases and decreases between the 2010 base
and 2020 base cases (Table 5.2), both AURAMS
and REMSAD predict the PM2 5 mass to be larger
(on an annual basis) for the 2020 base case than
for the 2010 base case (Figures 5.2a and 5.3a and
Figures 5.20 and 5.22).
5.2.4 Summary and Conclusions
The AURAMS scenario simulations indicate that
proposed additional S02 and NOx emission
reductions should provide additional reductions in
ambient PM2 5 levels in eastern North America.
These reductions, however, are related most
strongly to reductions in PM2 5 SOj mass. Since
this species has a well known seasonal cycle, with
maximum values occurring in the summer and
minimum values occurring in the winter, it is likely
that the magnitude of the resulting PM2 5 mass
reductions will also vary by season. The AURAMS
simulations support this expectation. The
AURAMS simulations also predict that the largest
PM2 5 reductions may occur west of the
Mississippi in the winter but east of the
Mississippi in the summer.
The results are more complicated for SOx
emission reductions that are not accompanied by
adequate NOx emission reductions, since AURAMS
predicts that these will be associated with decreas-
es in PM2 5 NOj mass in some parts of eastern
North America but with increases in other areas due
to the phenomenon of nitrate substitution.
Nitrate substitution is in turn determined by exist-
ing ambient ammonia and sulphate levels and by
the magnitude of SOj reductions. The predicted
occurrence of NOjsubstitution suggests that there
may be value in investigating potential benefits
due to ammonia emission reductions in conjunc-
tion with S02 and NOx emission reductions (for
the 2010 and 2020 control-base scenario pairs con-
sidered here, NH3 emissions were held constant).
On the other hand, NOx emission reductions will
produce co-benefits in terms of reduced summer-
time ozone levels and reduced TN03 (i.e., the sum
of HNO3 and p-NOj) deposition to land surfaces
and to water bodies.
Comparisons of the AURAMS winter and sum-
mer predictions with REMSAD winter and summer
predictions showed good qualitative agreement or
consistency for all four PM fields and for both sea-
sons in terms of the atmospheric response to the
same emission reductions. That is, the two mod-
els predicted the same directional changes for all
species for both seasons and also the same rela-
tive rankings of the changes between species and
between seasons (e.g., changes in PM2 5 NHJ
mass are larger in the summer than the winter;
changes in PM2 5 NHJ mass are larger than
changes in PM2 5 NOj mass in the summer, etc).
And despite their very different treatments of
chemistry, both models predicted the occurrence
of PM2 5 NOj increases in both the winter and
summer seasons. On the other hand, the changes
predicted by AURAMS were always larger in magni-
tude than those predicted by REMSAD (consistent
with the shorter episodes and averaging periods
considered in the AURAMS modelling) and the
predicted spatial distributions were sometimes
quite different (e.g., summertime 2020 control-
base PM2 5 NOj differences).
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Canada - United States Transboundary PM Science Assessment
5.3 RESULTS OF CMAQ
MODELLING IN THE
Georgia Basin - Puget
Sound Region
The Community Multiscale Air Quality (EPA, 1999;
MCNC, 2001) modelling system was applied over
the Pacific Northwest to gain insight into the sig-
nificance of the transboundary transport of air pol-
lutants across- the international border separating
British Columbia and Washington State, and to
determine the impacts of forecast changes in pol-
lutant emissions expected by 2010 and 2020 on
ambient air quality in 2000.
The version of CMAQ used for this work is the
June 2001 version that was parallelised (RWDI,
2003a) for a PC/Linux cluster running Redhat Linux
v7.3. The photochemical mechanism used was the
*radm2_ae2_aq' mechanism. This mechanism was
selected in order to; be compatible with CMAQ
modelling being performed by others over the
Pacific Northwest. The CMAQ modelling domain
used encompasses the Pacific Northwest stretch-
ing from central Oregon to central British
Columbia and from western Idaho to the Pacific
Ocean, or in Other words an 800 km wide domain
straddling 500 km each side of the Canada/US
border with a domain resolution of 12 km. Nested
within this domain is a 4-km fine resolution sub-
domain centred over the Georgia Basin and Puget
Sound. Resolutions of this magnitude are
required in order to try to account for the complex
terrain and marine environments of the Pacific
Northwest. See Figure 5.24 for geographical refer-
ences and domain extents.
In this case, the CMAQ chemistry transport
model is driven using the MC2 (Mesoscale
Compressible Community) meteorological model.
MC2 is based on the Euler equations and is a fully
compressible non-hydrostatic model using gener-
alised terrain-following coordinates. Complete
descriptions of MC2 are available in Laprise
(1997). The MC2 meteorology is at a resolution of
3,3 km using version 4.9.1 of the MC2 dynamics
CMAQ 12km Domain
British
Columbia
f
"CMAQ 4km Domain^
%, % M
% % s
Vancouver FVRD 3 'ง
n #GVRD a ^
& JJncan Whatcom County
V,
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chapter 5
and version 3.7 of the RPN/CMC physics package.
This meteorology was then interpolated and repro-
jected onto the CMAQ grid and remapped for
ingest by meteorology/chemistry interface proces-
sor (MCIP) of CMAQ and for ingest by the SMOKE
emissions model.
The CMAQ simulations were performed using
meteorology for a typical summer period and for a
typical winter period. The summer period selected
was August 09-20, 2001. This period embraced a
dry blocking weather pattern of two regimes; a
stagnant phase, and a well-mixed phase. This
period coincided with the Pacific 2001 Field Study
(Li, 2001) from which there was a rich meteorolog-
ical and chemical dataset. The winter period
selected was December 01-13, 2002. This period
comprised a short stagnant phase, followed by a
weak blocking pattern, and ended with a transient,
well-mixed phase. For both summer and winter
periods, 2000 emissions inventory data were used.
There were no known significant anthropogenic
emission differences between 2000,2001, and 2002.
The Pacific 2001 field study dataset was used
to evaluate CMAQ performance over the Georgia
Basin-Puget Sound region. In spite of the complex
terrain and marine environment challenges of the
Pacific Northwest, it was felt that the CMAQ per-
formance was consistent with that found by others
in Canada and the United States. Overall, the
model performed well for predicting PM2 5 at both
the 12-km resolution and 4-km resolution
domains. It should be noted that the CMAQ "1+1"
particle mass was used as if it were PM2 5, even
though the difference can be substantial both con-
ceptually and quantitatively. Subsequent refer-
ences will not make this distinction.
Overall, the diurnal patterns and magnitude of
the modelled daily average PM2 5 levels were quite
good. In general, the 4-km PM2 5 results were bet-
ter than those for the 12-km domain, particularly at
night. This is believed to be the results of local
emission sources and the more heterogeneous
nature of PM2 5 as a regional pollutant compared to
ozone. Secondary particulate matter can form very
rapidly or slowly depending on the environmental
conditions and emission source characteristics.
5.3.1 Qualitative Analysis of Simulations
for the 2000 Base Case
5.3.1.1 Summer PM2 5
In the 12-km grid domain, PM2 5 starts to build up
in the vicinity of the major primary sources
(urban/industrial/marine areas) after about 24
hours of model 'spin-up'. The combination of sea
breeze and an onshore westerly flow pushes the
PM2 5 concentrations inland, toward the east away
from the urban and marine areas during the day-
time. And, mountain flows from the northeast
along the Fraser Valley push the pollutants back
toward the west during the night. This day-night
pattern in PM2 5, levels persists until the onset of
the well-mixed phase. In the 4-km simulations,
results are similar but show somewhat improved
resolution of focal hotspots near the sources of
primary PM2 5 emissions (Figure 5.25),
5.3.1.2 Winter PM2 5
During the model 'spin-up' and stagnant meteoro-
logical periods (December 01-07), PM2 5 levels
build up around and slightly downwind (east) of
the urbanized areas of the Greater Vancouver
Regional District (GVRD), Seattle, and Portland.
During the weak blocking period (December 07-
10), offshore flows and land breeze effects push the
urban plumes toward the west and over the Pacific
PM2J
PM 2.5 Concentration
Au^ut" 200 ' Com 4 hi
Figure 5.25 - PM2,5 Concentrations for the. August,
2601 summer base ease, predicted oyer the CMAQ
domain on a 4x4 km2 grid.
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Canada - United States Transboundary PM Science Assessment
Ocean. It is notable that during December 07-09,
high-concentrations of PM2 5, which originally
formed in the Seattle area and over the GVRD,
moved north and westward toward Vancouver
Island. This polluted air mass then spreads to the
northwest along the Strait of Georgia, westward
along the Juan de Fuca Strait, and over the south-
ern coast of Vancouver Island. The result was rela-
tively high PM2 5 levels over southern Vancouver
Island (e.g., Victoria, Duncan), the Strait of
Georgia, and the coastal area of the GVRD. In con-
trast to the local-scale impacts, these impacts are
more transboundary in nature. December 10-13 is
marked by a well-mixed phase with much stronger
southerly and southwest wind flows that effective-
ly purge the polluted air mass, resulting in signifi-
cantly lower PM2 5 levels throughout the 12-km
domain.
5.3.2 Significance of Transboundary
Transport
The approach used to look at the significance of
transboundary transport was to compare the ambi-
ent air concentrations of PM2 5 in the base case
scenarios (all emissions left on) with those that
resulted when either all of the Canadian anthro-
pogenic emissions ("NOCAN" scenario) or all of
the American anthropogenic emissions were
turned off ("NOUS" scenario). The comparisons
were carried out for the same typical summer and
winter periods identified for the base case. The
relationship between emissions and ambient air
quality is not linear although the simulations pro-
vide a reasonable indication of the relative
impacts associated with transboundary pollutant
transport.
5.3.2.1 Qualitative Analysis of the No-U.S.
Anthropogenic Emissions Scenario
Summer PM2 5: Biogenic and soil emissions of
VOCs, NOx and NH3 in the United States continue
to contribute to the formation of PM2 5 over the
U.S. portion of the domain. Due to onshore west-
erly flows, the PM2 5 plumes form over the
GVRD/FVRD (Fraser Valley Regional District) and
the Strait of Georgia (from marine emissions), then
move eastward along the Canada/U.S. border.
Peak NOUS PM2 5 levels in the GVRD from August
11-16 are lower (about 36 pg/m3) than what is seen
when the U.S. emissions are left on (about 50
pg/m3), which suggest that, under these meteoro-
logical conditions, U.S. emissions contribute to
precursor concentrations and resulting Canadian
ambient PM2 5 levels. However, this impact of
transboundary pollutant transport is relatively
short-ranged.
On several occasions, PM2 5 levels build up
over Juan de Fuca Strait and around the southern
tip of Vancouver Island before travelling southward
over the northern tip of the Olympic Peninsula and
Puget Sound. Marine emission sources and emis-
sions from Victoria are thought to play the major
role in this phenomenon. Emissions from the
GVRD can also be seen to drift southward and
impact northern Whatcom County.
Winter PM2 5: The model results for the NOUS
scenario show low PM2 5 levels in the United
States compared to the base case, except for on
December 02-03 when easterly winds change to
northerly winds for a period of time. During this
period, the PM2 5 plume moves from GVRD/FVRD
and Strait of Georgia to the northern tip of the
Olympic Peninsula and to Seattle. Other minor
intrusions into the United States occur all along
the valleys that line the Canada/U.S. border during
these periods. In contrast, the NOUS PM2 5 levels
over Vancouver Island are lower than the base
case, indicating that elevated PM2 5 levels from
the United States typically travelled northward
over Vancouver Island. On the other days during
this episode, there is little or no cross-boundary
impact from Canada to the United States due to
the predominantly easterly to southerly wind
flows.
5.3.2.2 Qualitative Analysis of the No-Canadian
Anthropogenic Emissions Scenario
Summer PM2 5: Due to the onshore westerly flow,
the urban PM2 5 plumes over and downwind of
Seattle and Portland move generally eastward, par-
allel to the Canada/U.S. border, resulting in rela-
tively little transboundary transport into the
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chapter 5
GVRD/FVRD and the southern portion of the Strait
of Georgia for a number of hours during the simu-
lation. However, at other times (such as during the
late afternoon of the last four to five days of the
episode) PM2 5 levels in north-central Washington
in the NOCAN simulation are much lower than the
base case results (about 15 to 20 pg/m3 lower).
This suggests that a normally polluted air mass
from the Canadian side of the border, likely associ-
ated with marine emissions, moves southward into
the United States.
Winter PM2 5: The NOCAN simulation results
point to some unique transboundary phenomena.
From December 01-05, easterly flows dominate the
entire domain and the PM2 5 plumes formed over
the Seattle and Portland regions move offshore to
the west, over the Pacific Ocean. There are no sig-
nificant transboundary impacts from the United
States on Canada, except for the lower tip of
Vancouver Island (e.g. Victoria) and the GVRD area.
However during December 06-10, the wind
flow patterns veer to the southeast, causing the
PM2 5 plume from the Seattle region to move
northwestward across the straits of Georgia and
Juan de Fuca and over the southern coast of
Vancouver Island. Compared to the base case
results, the PM2 5 concentrations from NOCAN
simulations in these areas are quite high with
peaks of around 24 pg/m3 (i.e., about 50 to 60 per-
cent of base case levels can be attributed to trans-
port from the United States). There is relatively lit-
tle evidence of transboundary transport elsewhere
in the model domain.
5.3.2.3 Summary and Conclusions
The NOUS and NOCAN simulations indicate that,
for the specific meteorological and synoptic pat-
terns evaluated, local/urban-scale air quality
impacts from transboundary transport occur along
the border (within +50 km) with some frequency.
However, the incidence of long-range/regional
transport (over 100 km) is low. The long-range
transport results may be different for other study
periods with different meteorology. The winter
simulations are indicative of a bigger long-range
transport issue. For example, during December
06-10, with a southeast wind pattern, plumes travel
from the Seattle area to Vancouver Island. Due to
the combination of geography, nature of emis-
sions, and regional wind flow patterns, there is
little longer range transboundary transport evident
elsewhere in the model domain.
Based on these model results, there appear to
be different regimes of transboundary pollutant
transport that depend on the specific meteorologi-
cal conditions and geography of the region. Long-
range transport does occur, but less often than the
more local-scale transboundary transport. Local
transboundary transport occurs all along the British
Columbia/Washington border, particularly in the
vicinity of the GVRD and southern Vancouver Island.
5.3.3 Impacts of Forecast Emissions for
2010 and 2020
The approach used to determine the impacts of
forecast changes in pollutant emissions on ambi-
ent air quality was to substitute the 2000 anthro-
pogenic emissions with those forecasted for 2010
and 2020 and then compare changes in simulated
air quality.
Overall, carbon monoxide (CO), VOC, and NOx
emissions increase in Washington State but gener-
ally decrease in British Columbia for both the 2010
and 2020 scenario years. The overall decrease in
NOx emissions projected throughout British
Columbia results from decreased emissions from
mobile sources. Emissions of PM10 are projected
to increase generally in both Washington State and
British Columbia by 2010 and 2020 however, in the
FVRD a decrease is projected. Emissions of PM2 5
are projected to increase in Washington State by
the same percentage as the PM10 emissions, but
are expected to remain relatively unchanged in
British Columbia. Impacts associated with these
and other regional variations in emissions trends
can be seen in the CMAQ model results.
5.3.3.1 Qualitative Analysis of Simulations for the
2010 Forecast
Summer PM2 5: Overall, the 2010 PM2 5 pattern
is similar to 2000, with maximum PM2 5 levels
occurring in urban areas during the early morning
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Canada - United States Transboundary PM Science Assessment
when meteorological conditions are least
favourable for dispersion. In the GVRD, peak
1-hour PM2 5 concentrations increase by up to
20 |ig/m3 compared to 2000, predominantly due
the projected increase in primary PM2 5 emissions
in that area possibly along with increased NOx and
SOx from marine vessel emissions leading to
increased secondary formation of PM or with
decreased NOx from on-road vehicles..
Conversely, peak PM2 5 concentrations in the
FVRD decrease by up to 20 |ig/m3 due to the pro-
jected decrease in primary PM2 5 emissions at that
location. This occurs even though agricultural
emissions, and subsequent secondary PM forma-
tion, are increased. Near Seattle and Portland,
peak PM2 5 concentrations increase slightly (by
1 or 2 |ig/m3) which is consistent with the modest
projected increase in primary PM2 5 emissions
between the base case and 2010 scenarios.
Elsewhere in the model domain, peak PM2 5 con-
centrations exhibit relatively little change.
Winter PM2 5: Generally, the PM2 5 pattern in
the 2010 simulations is similar to 2000. The 2010
results show a modest increase in PM2 5 levels in
the large urban areas (generally less than about 10
|ig/m3) and a small increase downwind of the
urban areas. For December 01-05, easterly flows
dominate the entire domain and PM2 5 plumes
that form over the urban centres of Vancouver,
Seattle, and Portland move offshore to the west
and northwest. From December 06-10, the wind
regime is dominated by southeast flow, causing
PM2 5 from the Seattle and Puget Sound regions
to move northwest across the Strait of Georgia, the
Strait of Juan de Fuca, and southern Vancouver
Island. Increased PM2 5 concentrations in these
areas are predominantly due to the projected
increase in primary PM2 5 emissions in the urban
areas, particularly the GVRD. The GVRD levels are
potentially further enhanced due to secondary PM
formation from increased marine vessel emissions
of NOx and SOx or from decreased NOx emissions
from on-road vehicles. In the FVRD, the decrease
in PM2 5 levels that is predicted to occur (up to
about 15 |ig/m3) is consistent with the projected
reduction in primary PM emissions in that area.
Elsewhere in the domain, predicted changes in
PM2 5 concentrations are small.
5.3.3.2 Qualitative Analysis of Simulations for the
2020 Forecast
Summer and Winter PM2 5: The overall summer
PM2 5 pattern in the 2020 simulations is similar to
2010. In the GVRD, the increase in PM2 5 concen-
trations relative to the base case is more pro-
nounced (up to 30 |ig/m3 higher) than in 2010. The
overall winter PM2 5 pattern in 2020 is similar to
2010 but again the changes in emissions relative
to the base case are more pronounced.
5.3.3.3 Summary and Conclusions
The fairly drastic differences in emission growth or
decline by geographic region greatly affect the
model results. This is particularly evident in the
lower Fraser Valley, where projected emission
trends in the GVRD are different from those in the
FVRD. Peak PM2 5 levels are projected to increase
modestly in urban areas and increase slightly
downwind of urban areas throughout the domain
during both the summer and winter simulations.
This result is consistent with a projected increase
in primary PM2 5 emissions in urban areas. The
larger increase in the GVRD urban location may be
due to either the additional secondary PM forma-
tion from increased NOx/SOx emissions from
marine vessels or to decreased NOx emissions
from on-road vehicles. PM2 5 levels are predicted
to decrease significantly in the FVRD, as a result of
a projected large decrease in primary PM2 5 emis-
sions in that region.
5.4 CO-BENEFITS OF
Emission reductions
Reductions in emissions of PM2 5 precursors have
an impact on other air-quality issues such as
ground-level ozone, acid deposition and visibility.
Model applications for ground-level ozone and
acid deposition endpoints have been completed
by the U.S. and Canadian models for the same
time periods as discussed in sections 5.1 and 5.2.
The output from these simulations is not dis-
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chapter 5
Ozone
Max = 8.6 at (4Z.02N, 87.24W)
Min = -16.9 at(39.38N, 81.35W)
Figure 5.2<5 - Peak ozone concentration
difference, field at 15 m height for the
July 12-15, 1995 summer period for' the
"2020 Control" case minus the "2020 base"
case. The two peak ozone concentration
fields were constructed by averaging over
the afternoon period (15 - 21 UTC) for
4 days (July 12th to 15th) corresponding
to a regional Ozone episode.
Figure 5.27 -Annual
reduction in SCgj wet
deposition from additional
U.S,_and Canadian controls
(2020 control vs. base.]:.
Reduction in Sulfate Wet Deposition from US/Canada Controls
Annual Wet Deposition (2020 Control - 2020 Base)
O=csa20ce1p1_v706ext.2020.wet.yrsum.dat.ioapi, u=csa20be1 p1 v706ext.2020.wet.yrsum.dat.ioapi
0.00 98
. -0.75
I -1.50
-2.25
-3.00
-3.75
-4.50
-6.00
v
Hour: 00
Min= -6.66 at (101,55), Max- 0.00 at (49,6)
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Canada - United States Transboundary PM Science Assessment
Reduction in Nitrate Wet Deposition from US/Canada Controls
Annual Wet Deposition (2020 Control - 2020 Base)
O=csa20ce1p1_v706ext.2020.wet.yrsum.dat.ioapi, u=csa20be1 p1_v706ext.2020.wet.yrsum.dat.ioapi
0.00 98
-0.50
-1.00
-1.50
-2.00
-2.50
-3.00
-3.50
-4.00
kg/ha
PAVE
Hour: 00
Min= -4.45 at (110,66), Max= 0.02 at (19,74)
Eigure5.28 -
Annual reduction
in NOjwet
deposition from
additional O.S!
and Canadian
controls (2020:
control fe. base).
Eigure:5.29 -
Aerosol light
extinction
(in Mm"1) for the
haziest- 2-G percent
days and. contribu-
tion by individual
particulate matter
constituents, based
on 1997-1999
IMPRCS/E data
(USEPA, 1999).
Species
Sulfate
Nitrate
Organic Carbon
Elemental Carbon
Crustal Matter
78
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chapter 5
cussed in great detail in this report, but the link-
ages between emissions reductions and the result-
ing co-benefits for other air quality issues are key
considerations in the determination of appropriate
domestic and international policies.
Figure 5.26 shows reductions in peak ozone
levels of up to 5-10 ppb predicted by AURAMS to
result from NOx emission reductions between the
2020 control scenario and the 2020 base scenario.
In addition to reducing ozone and PM2 5 SOj
concentrations and, in much of eastern North
America, PM2 5 N03and NH+ concentrations, the
implementation of additional U.S. and Canadian
controls will result in significant reductions in SOj
wet deposition and TN03 wet deposition in 2010
and 2020. The annual reduction in 2020 SOj and
TN03 wet deposition predicted by REMSAD to
occur with the implementation of additional U.S.
and Canadian controls are provided in Figures 5.27
and 5.28, respectively. The reductions in wet dep-
osition are larger in the eastern portion of the
modelling domain than the western portion of the
modelling domain. These controls result in annu-
al reductions of SO= wet depositions that are up to
6.7 kg/ha in 2020. These controls also result in
annual reductions of N03 wet deposition that are
up to 4.5 kg/ha in 2020. The largest reductions in
SO= and TN03 wet deposition are located in Ohio,
Pennsylvania, western New York State, and south-
ern Ontario.
Figure 5.29 illustrates aerosol light extinction
for the 20 percent haziest days in the United
States. Sulphate is the most significant contribu-
tor to reduced visibility, due to the particle's abili-
ty to scatter light. A reduction in sulphur com-
pounds will result in improved visibility, particu-
larly for the northeast, where visibility reduction at
rural sites is the most significant.
5.5 KEY SCIENCE MESSAGES
Comparisons of the AURAMS and REMSAD
predictions showed good qualitative agreement
and consistency for all four PM fields and both
winter and summer in terms of the atmospher-
ic response to emission reductions, with the
exception of predicted responses in summer-
time PM2 5 N03 concentrations.
Proposed additional S02 and NOx emission
reductions should provide additional reduc-
tions in ambient PM2 5 levels in eastern North
America. The observed PM2 5 reductions may
vary by season.
SOx reductions that are not accompanied by
adequate NOx reductions may result in NOj
increases in some areas. Reductions in NOx
emissions will correspond to decreases in
PM2 5 N03mass in some parts of eastern North
America but increases in other areas due to
NOj substitution (i.e., for SO= reductions in
NH3-limited locations, the replacement of SOj
by NOj in the particle phase). There is signifi-
cance placed on the role of NH3 in this relation-
ship, suggesting there may be value in investi-
gating possible benefits due to NH3 emission
reductions in conjunction with S02 and NOx
emission reductions.
In the Georgia Basin - Puget Sound region,
episodic impacts from transboundary transport
occur along the border (within + 50 km) with
some frequency; however, the incidence of
long-range/regional transport (over 100 km)
was low. Peak PM2 5 levels are projected to
increase modestly in urban areas as well as
downwind of urban areas during both summer
and winter simulations
Co-benefits of emission reductions scenarios
include reduced ground-level ozone levels,
reductions in NO"3 and SOj wet deposition, and
improved visibility.
Additional model runs should be carried out to
confirm and extend the model results present-
ed in this chapter, such as annual runs of
AURAMS and CMAQ and additional annual
runs of REMSAD for a different meteorological
year.
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Chapter
RELATIONSHIPS BETWEEN
SOURCES AND AMBIENT LEVELS OF PM
6.1 attributing Sources to
ambient levels of
PM2.5
The complicated physical and chemical nature of
transport and transformation of PM precursors
requires advanced analytical techniques to charac-
terize PM levels. Direct observation of PM events
using satellite sensors can provide a qualitative
perspective. However, the process of attributing
sources to ambient levels of PM - that is, quantify-
ing the relationship between sources and meas-
ured ambient PM levels - is difficult. To facilitate
the determination of this relationship, three differ-
ent techniques have been employed: observation-
al receptor-oriented analyses, positive matrix fac-
torization (PMF) and principal component analy-
sis. All of these techniques use differences in
chemical composition, particle size, meteorology,
and spatial and temporal patterns, to identify
emission sources that influence particle composi-
tion and particle mass. The following sections dis-
cuss applications of these techniques in Canada
and the United States.
6.1.1 Observational Receptor-Oriented
Analyses
Many semi-quantitative methods can be used to
attribute sources to ambient levels of PM. These
observational receptor-oriented analyses include
time series analysis, spatial patterns, and concen-
tration directionality.
6.1.1.1 Quantifying the Transboundary Transport
of PM2 5 using a Geographic Information System
Speciated IMPROVE measurements for 17 Class 1
sites in the eastern United States were examined
in an analysis (Kenski, 2003) at the Lake Michigan
Air Directors Consortium. Three-day back trajecto-
ries for these sites were calculated using HYSPLIT
for the 5-year period from 1997 through 2001 (start
time of noon, start height of 200 m). Using
ArcView 3.2, hourly endpoints from the back trajec-
tories were plotted. Each endpoint (1 per hour, 72
per trajectory) is associated with concentrations
corresponding to the IMPROVE sample for the tra-
jectory start date. These concentrations are aver-
aged by state and province, as shown in Figure 6.1.
The data presented in Figure 6.1 indicate
which states are associated with high concentra-
tion air masses arriving at Class 1 areas, but do not
take into account the frequency with which air
masses traverse a particular area or state. States
that are closer to Class 1 sites will tend to con-
tribute more PM2 5 to those sites, because the air
masses spend more time over those nearby states
and emissions from nearby sources have less time
to disperse and deposit than emissions from
sources further away. These areas of more fre-
quent transport can be associated with PM2 5 con-
centrations that are high, low, or moderate. By
combining this frequency information with the
concentration information, this study derives an
average contribution to PM2 5 mass from each
state/province to the Class 1 areas.
For example, the percent contribution from
any state A to any Class 1 area can be estimated
from the set of trajectories originating at that Class
1 site as:
Avg-Concn.StateA No.endptsStateA ^ 1QQ
^AUStateSCOnCn* EndPtS">
Table 6.1 gives the average concentration and
percent PM2 5 mass contributed by selected states
and provinces to a sample of the Class 1 areas
examined (mass contributions greater than 5 per-
cent are highlighted).
81
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Canada - United States Transboundary PM Science Assessment
These results can be thought of as an indica-
tor combining the upwind status of a
state/province, the geographic size of the
state/province, and the magnitude of source emis-
sions within the state/province. A state or
province that is close to, and frequently upwind of.
multiple Class 1 areas- will generally contribute
more mass than states or provinces that are sel-
dom upwind, unless the concentration difference
is marked. For example, Minnesota contributes a
large percentage of mass to Boundary Waters (35.2
percent) although the average concentration asso-
ciated with air masses in Minnesota is less than 6
|ig/m3:,. Similarly the Canadian provinces make
significant contributions to the border-area Class 1
sites; Ontario provides about 16 percent of the
annual PM2 5 mags at Boundary Waters and
Quebec provides about 18 percent to Acadia. Ohio
and Pennsylvania are associated with high-con-
centration air masses at the three Class 1 sites
shown, but only make significant (>5 percent) con-
tributions to annual PM2 5 mass at the nearby
Dolly Sods Wilderness site.
In an exactly analogous manner, the contribu-
tion of each state and province to the joint set of
17 Class 1 .areas was derived (not shown),. The
results indicate that seme states associated with
high-concentration air masses nevertheless con-
tribute only a small amount of mass to the collec-
tive group of Class 1 sites? conversely, states (or
provinces) with low average concentrations can be
major mass contributors.
Average RM
I | 46.5.6
56-7 1
93.119
113-137
13 7 14 0
Average OC
I I 09
14-1.5
53-Jfi
Averago S04
I I '3-18
I I '6-?ป
2 7-34
34 -4 A
i .1 -1 y
ฆ>9-5?
Average EC
j j u .
03-03
D 3 - 0 4
04-05
M 0 8
05-08
Average NO3
] 0.2-0 3
03 0 4
04-05
05-0
05-08
08 11
Average Sail
Q2 - 03
03-03
0 3-04
ii.l l)^
n 5 - n ซ
9 6 1 1
Figure 6.1 - Average concentrations of PM2 5 and components (pg/m3) by state and province (IMPROVE sites shown
as blue dots). Each trajectory endpoint is associated with concentrations corresponding to the IMPROVE sample for
the trajectory start date.
82
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chapter 6
Table 6.1 Average concentration and percent mass selected state contributions to Class I areas (mass
contributions >5 percent are highlighted).
State/Province
Acadia
Boundary Waters
Dolly Sods
Cone.
%Mass
Cone.
%Mass
Cone.
%Mass
Illinois
10.8
0.4
9.5
1.7
8.7
1.6
Indiana
17.1
0.9
12.5
0.6
11.0
3.2
Iowa
7.6
0.2
8.1
5.0
8.5
0.9
Kentucky
11.8
0.5
14.0
8.6
Maine
5.6
12.6
8.6
0.1
Michigan
7.6
1.7
6.2
1.7
10.1
2.6
Minnesota
7.1
0.6
5.7
35.2
8.6
1.0
New Hampshire
8.6
2.0
New Jersey
18.9
1.0
8.4
0.1
New York
8.2
4.4
9.1
0.8
North Carolina
13.9
0.3
10.0
0.1
12.0
3.1
Ohio
10.6
1.2
12.8
0.2
11.5
8.8
Pennsylvania
13.2
3.0
10.9
5.1
Tennessee
9.9
0.2
13.4
4.9
Vermont
8.3
1.8
Virginia
14.2
0.9
11.8
7.6
West Virginia
18.4
0.5
10.0
0.1
14.0
26.4
Wisconsin
6.2
0.6
7.1
7.6
9.0
1.3
Provinces
Ontario
6.0
7.7
3.5
16.4
9.2
4.8
Quebec
4.9
17.8
2.4
0.2
6.6
0.7
6.1.1.2 Sources of PM2 5 to Urban Areas in the
United States
Rao et al. (2003) investigated the local and region-
al source contributions of PM2 5 to urban areas at
13 urban locations in the United States. The
'urban excess' for the 13 cities is presented in
Figure 6.2. Evaluating the differences between
urban and rural sites is a first indicator of local ver-
sus regional transport, as determined by 'excess' of
the components at urban sites in comparison to
rural sites. This analysis was accomplished by
matching urban sites to nearby rural sites and
comparing the appropriate concentrations of
chemical constituents and mass. Although there
is uncertainty in the measured mass and in meas-
urement protocols, it is clear that carbonaceous
mass is prevalent everywhere (average of
5.1 pg/m3) and is the major component of urban
excess at all of the sites studied. At the western
sites, the Total Carbon Material (TCM) urban
excess ranges from 4.5 to 10.5 pg/m3, whereas at
the eastern sites, TCM urban excess ranges from
2 to 5.4 pg/m3. Similarly, nitrates are prevalent
n the estimates for the north and west (2 to
6 pg/m3). Consistent with other studies that find
most SO= is associated with regional sources of
S02; the urban excess of this chemical component
is invariably small in the eastern United States.
These results indicate the regional nature of SOj
contribution to total PM2 5 mass and by implica-
tion the role of the transport of SOj associated
PM2.5.
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Canada - United States Transboundary PM Science Assessment
Figure 6.2 - Urban Excess
Analysis for SGj, NHJ, NOj,
TCM and crustal material for
13 urban areas in the United
States
(Nolo k=1.8 in opdef lo ronverl
mass into TCM).
Cteveiand
| Bronx
JL ,ndy
Fresno
Tulsa
Atlanta
2.3 8-t 1X2
6.1.1.3 Sources of PM2 5 to Eastern North America
An ensemble-trajectory analysis technique known
as Quantitative Transport Bias Analysis (QTBA;
Keeler and Samson, 1989) wag applied to deter-
mine which geographic areas systematically con-
tributed to above- and below-average fine particle
mass (PM2 5) over eastern North America (Brook
et al., 2004). Six-hour average measurements from
12 rural or suburban locations in eastern North
America, collected using the TEOM measurement
method, were individually associated with corre-
sponding 3-day back-trajectories for the warm sea-
sons (May through September) of 2000 and 2001.
Much of the populated area of northeastern
Canada and the United States was implicated in
the build-up of PM2 5 to "above average" concen-
trations (Figure 6.3). Average concentrations were
determined by calculating the mean concentration
at each of the sites during the warm seasons of
2000 and 2001. The finer structure of the QTBA
pattern indicated that transport from the Ohio
River Valley was most often associated with the
highest PM2 _ concentrations, particularly the
eastern portion of this area. In addition, air mass-
es traversing a relatively large area from southeast
Ohio to the western part of Virginia and the west-
ern Kentucky to central Tennessee area tend to
result in relatively high PM2 5 concentrations over
northeastern North America. These observation-
based findings are consistent with the spatial dis-
tribution of the major S02 and NOx point sources
(Figure 4.1a and Figure 4.3a).
6.1.1.4 Back-trajectory Analysis of PM2 5
Transport to Eastern Canada
Using hourly TEOM PM2 5 observations from
May-September Of the years 1998-2000, Brook et
al. (2002) have quantified the impact of various
transport directions on PM2 s concentrations in
eastern Canada using back-trajectory analysis.
Comparisons of PM2 5 levels at different sites
reveal that on average, the local contribution to
total PM2 5 in the Greater Toronto Area is approx-
imately 30 to 35 percent. This implies that the
regional or long-range contribution comprises the
remaining 65 to 70 percent. Furthermore, at sites
in eastern Canada, average PM2 5 concentrations
were 2 to 4 times greater under south/southwester-
ly flow than under northerly flow conditions during
May through September of 1998 and 1999 (see
84
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chapter 6
Figure 6.3 ฆ'Combined OTBA
plot derived using 2OT0 and
2001 TEOM PM,j g measure^
ments for the warm months
(May-September). The locations
of the 10 measurement sites
(receptors) are shown by stars
and the locations of the maxi-
mum OTBA values are indicated
by the black circles. QTBA val-
ues greater than 1.0 indicate a
high likelihood of air masses
passing over that area bringing
above-average warm-season
PM2 s to the receptor.
Figure 2.2). This observation suggests that the
majority of PM2 s at these locations is arriving
from the transport of PM2 5 and PM2 5 precursors
from sources: south of this region.
6.1.1.5 Sources of PM to Glacier National Park,
Montana
Trajectory Clustering/Time Series Analysis was
applied to Glacier National Park in Montana
(Sirois and Vet, pers.Comm.J, This preliminary
analysis identifies the potential influence of west-
ern Canadian and U.S. sources to visibility impair-
ment at Glacier National Park. Qualitatively, S02
sources in Alberta, Saskatchewan, Montana and
North Dakota contribute to SOj-induced low visi-
bility events at Glacier National Park. High con-
centrations; of NO| observed at the Park were asso-
ciated with westerly air flow from the
Vancouver/Seattle area. Total OC and total BC, the
major contributors to visibility impairment at the
Park, were associated with air flows from the
VancOuver/Seattle, Oregon, and Northern
California areas.
6.1.1.6 Sources of PM and Acid Rain Precursors to
Southwestern Ontario: Study 1
Trajectory Clustering/Time Series Analysis was
applied to observed concentrations of particle
SO J and NO3 in air, and tojpH, SOj and NOg in
precipitation at the Longwoods measurement site
of the Canadian Air and Precipitation Monitoring
Network (CAPMoN) in southwestern Ontario to
determine source-receptor relationships (Vet and
Sirois, pers.comm,). The technique combined 3-
day back-trajectories with daily PM and ion meas-
urements, The technique involved categorizing the
air mass trajectories into two geographical sectors
(Figure 6.4) and sorting the data at the Longwoods
site according to the sector that each trajectory fell
within. The criteria for categorizing the trajectories
were as follows: 1) if at least 70 percent of the
points along the trajectory path fell within a sector,
the trajectory was categorized as originating from
this sector; and 2) if less than 70 percent of the
points along a trajectory fell within a sector, the
trajectory was categorized as "not attributable"
(N/A). Figures 6.5 and 6.6 illustrate the long-term
trends and median concentrations of particle SOj
85
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Canada - United States Transboundary PM Science Assessment
and NO3 in air and pH, SOj and NO3 in precipita-
tion associated with trajectories from the
Canadian and U.S. sectors.
Air-. Results of this study for airborne S02 indi-
cate that concentrations in air masses originating
in Canada decreased markedly throughout the
period 1983-2001 while concentrations from U.S.
air masses gradually increased during the same
time period (Figure 6.5a, Note: logarithmic scale).
During this period, the median concentration of
S02 in air masses from the United States was
approximately 2.8 times greater than concentra-
tions in air masses from Canada (Figure 6.5b). The
amount of particle SOj in air masses from Canada
declined slightly while concentrations in air mass-
es from the U.S. remained relatively constant over
the 19-year time period (Figure 6.5c). Median con-
centrations of SOj in U.S. air masses were also 2.8
times greater than concentrations in air masses
from Canada (Figure 6.5d). Concentrations of total
NO3 (i.e., TNO3" = the sum of particle N03" and
gaseous HN03) in air masses from Canada
declined slightly between 1983-2001 while concen-
trations in air masses from the United States
increased from 1983 to 1992 and remained rela-
tively constant from 1992 to 2001 (Figure 6.5e).
Overall, the median concentration of TNOj in air
masses from the United States was three times
higher than concentrations in air masses from
Canada (Figure 6.5f).
Precipitationฆ. Results indicate that the pH of
precipitation associated with trajectories from
Canada increased during the 1980s, declined from
the late 1980s to mid-1990s and increased again
from the mid-1990s to 2001 (Figure 6.6a). The pH
of precipitation from U.S. air masses increased
slightly and gradually from 1983 to 2001 (Figure
6.6a). The median pH of precipitation from air
masses from the United States is significantly
lower than the pH of precipitation from air masses
that originate from the Canadian sector (Figure
6.6b). The amount of SOj in precipitation associ-
ated with trajectories from Canada declined during
the early 1980s to 1990, increased during the 1990s
and then declined more rapidly from 1997 to 2001
(Figure 6.6c). Sulphate levels in precipitation asso-
ciated with U.S. trajectories exhibited a more grad-
ual decline throughout the measurement period
(Figure 6.6c). The median concentration of SOj in
precipitation associated with the United States
was approximately twice that of trajectories origi-
nating from Canada (Figure 6.6d). The amount of
N03" in precipitation associated with trajectories
from Canada also declined during the early 1980s
to 1990 but leveled off between the 1990s and 2001
(Figure 6.6e). Nitrate levels in precipitation asso-
ciated with trajectories from the United States
remained relatively constant from the early 1980s
to 1999 and a slight decline from 1999 to 2001
(Figure 6.6e). The median concentration of NOj in
precipitation associated with trajectories from the
United States was approximately twice that of tra-
jectories originating from Canada (Figure 6.6f).
Figure 6.4 - Sectors used to categorize 3-day back-
trajectories of air masses at Longwoods, Ontario.
Light shading represents the Canadian sector.
Dark shading represents the U.S. sector.
86
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chapter 6
USA
N/A
1985
TNO," (ng/rrr)
Canada
U.S.A.
N/A
2848
7.39
8,14
1990 1995
SOj (ugW)
Canada U.S.A.
S02 (lig/rrr )
T
2000
N 1945 2885 1527
G. Mean 1.74 4.96 3.59
Median 1.82 5.52 3.95
N 1923
G. Mean 2.62
Median 2,91
Canada
d)
N 1955
G Mean 178
Median 1.83
2000
Figure 6.5 - Long-term trends and median concentrations of SO^ (a and b, respectively), particle SOj (c and d,
respectively), and particle NOj (e and f. respectively) in air at Longwoods, Ontario associated with three-day back
trajectories from Canada, the United States and "Not Attributable* (N/A) to either sector. The trend line in the box
plots connects the geometric means, the line dividing the boxes .represents the median, the upper and lower sides
of the boxes represent the 75th and 25th percentile of the data, respectively and the upper and lower bars on
the box plots represent the 75th percentile plus 1.5 times the inter-quartile range and the: 25th percentile minus
1,5 times the inter-quartile range, respectively.
87
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Canada - United States Transboundary PM Science Assessment
PH
-ii|iiir-
a)! v
' ' - Sr c - V ' V A ฆ* r
*. ;j ฆ " - f,'*'-;-y ;ฆ?'ฃ
U.S.A
b)
N 559
A. Mean 5.21
Median 5.10
1
1985
1990
1995
2000
1556
4.38
4.25
I
583
4.68
4.41
ฑ
x
10 =
101
10ฐ
10"1
102
10"3
S04= (mg/l)
TIII 1I 1I 1 1I| 1-
rItftf]
USA
Nfit
i iIJ i i rIi lj i I i ii i I i
1985 1990 1995 2000
d).
N 625
G. Mean 1.65
Median 1.70
T
10
100 r
10"
10
1650
3.32
329
T
642
2.55
2.66
io=r ~ l
t i JLi
:?
t t
ฆf
ฆ*
fr
Canada
USA.
N/A
N03" (mg/l)
10^
101
10ฐ
10"'
10"2
10"3
r
-iiii|iir
e)
k " 1 |L *( ฆป . r k ^ .r # 1* 9 -V"
: I -ฃ ** " "" "
. Canada
, USA r
MA
I 1 I I l E I I I I I I I I I l_
1985
1990
1995
2000
^ N 624
G Mean 1.58
Median 1.66
10
1645
3.34
3.22
639
3.43
3.40
r ;
r
' Xi
r
r
ฆ
r
pT Ti
ฆ+ ~ |
ฆ 1 i
U.S.A.
Figure 6.6 - Long-term trends and median concentrations of pH (a and b, respectively), SO^ (c and d, respectively)
and NOg (e and f, respectively) in precipitation at Longwoods, Ontario associated with 72-hour back trajectories
from Canada, the United States and "Not Attributable" (N/A) to either sector. The trend line in the box plots
connects the geometric means, the line dividing the boxes represents the median, the upper and lower sides of the
boxes represent the 75th and 25th percentile of the data, respectively and the upper and lower bars on the box plots
represent the 75th percentile plus 1.5 times the inter-quartile range and the 25th percentile minus 1.5 times the
inter-quartile range, respectively.
88
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chapter 6
6.1.1.7 Sources of PM and Acid Rain Precursors to
Southwestern Ontario: Study 2
An analysis was also performed to assess the
impact of Canadian versus U.S. emission sources
on air quality at Longwoods, Ontario (Vet et al.,
pers. comm.). The results, illustrated in Figure 6.7,
were generated by combining daily ambient air
concentrations at the Longwoods site with air
mass trajectories for the individual measurement
days. The method, developed by Seibert et al.
(1994), calculates for each grid square, the geo-
metric mean concentration of the chemical in air
measured at the Longwoods site for the particular
subset of trajectories that passed through that grid
square. Thus, the red squares on the figure identi-
fy those emission areas associated with the high-
est concentrations at Longwoods and the blue
areas identify those areas associated with the low-
est concentrations. Figure 6.7 illustrates that the
highest S02, SOj and TNOj concentrations meas-
ured at this site are associated with air transport-
ed from areas in the Midwest and northeastern
United States. These geographic regions are also
associated with high S02 and NOx emissions. In
contrast, the lowest concentrations occur when air
is transported from areas in Canada to the north
and east of the site. A similar analysis for precipi-
tation chemistry (not shown) indicates a more
complex pattern of emission sources affecting the
precipitation at Longwoods. High acidity at the
site is primarily associated with air transported
from the Ohio Valley. High concentrations of SOj
and NOj are associated with air transported from
the central and eastern United States, northern
Alberta and the central United States and northern
Alberta and Saskatchewan, respectively.
6.1.1.8 Sources of PM2 5 to Southern Quebec
Source-receptor relationships describing PM2 5
levels at a site in southern Quebec during July,
2001, were determined using the START (Suivi du
Transport Atmospherique Regional et
Transfrontalier) model (Dion, 2003). START uses
emission information and back-trajectories from
the Canadian Meteorological Centre to estimate
the origin of PM2 5 and its precursors within 72
hours for each back-trajectory. Application of the
model indicates that as ambient levels of PM2 5 at
the receptor site increase, the origin of pollutants
shifts from Quebec to Ontario to the United States.
As levels of PM2 5 decrease, the origin of pollu-
tants shifts back to primarily Quebec.
The model was also used to estimate the per-
centage of PM2 5 at St. Anicet in southern Quebec
originating from the United States, Ontario,
Quebec and other areas during the summer (May
to September) and winter (November to March)
seasons of 1999 and 2000 (Table 6.2). Results indi-
cated that the United States was a significant
source of PM2 5 at St. Anicet contributing slightly
greater than 50 percent of PM2 5 mass. Canadian
sources contributed the remaining PM2 5, with
Ontario contributing approximately a quarter, fol-
lowed by Quebec, with approximately 17 percent.
Using this technique, the origin of PM2 5 did not
appear to vary substantially between the winter
and summer season.
Table 6.2 Proportions (percent) of PM2 5
mass with respect to 3-day back-
trajectories at 950hPa (1999-2002).
Season/
Region
U.S. Ontario
Quebec
Other
#traj
Summer
55 26
17
3
2410
Winter
57 24
17
3
2400
6.1.1.9 Sources of PM2 5 to Nova Scotia and New
Brunswick
PM2 5 data were used in conjunction with trajecto-
ry analyses to determine atmospheric transport
patterns at Kejimkujk National Park, NS and St.
Andrews, NB (Waugh et al., 2002). This analysis
used five-day back-trajectories, four times per day
between 1999 and 2001. Trajectories calculated for
this project were produced from the Canadian
Meteorological Centre Trajectory Model.
A non-parametric statistical analysis program
(SL-PSCF) was used to isolate the top ("polluted")
and bottom ("unpolluted") quartile events for
PM2 5. An event was defined as a 6-hour period
during which there was at least one hourly obser-
vation in the top or bottom 25th percentile. The
89
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Canada - United States Transboundary PM Science Assessment
Hg.m
20
10
9
8
7
6
5
4
3
2
0
-3
Hg.m
9.0
6.0
5.5
5.0
4.5
4.0
3.0
2.5
2.0
1.5
0.0
-3
TNOj"
(.ig.m
o.o
-3
Figure 6.7 - The geometric mean concentration of S02i SO4 and TNOJ measured in air at Lohgwoods, ON
(1983-2000) for the particular subset ฉf air mass trajectories that passed through that grid square.
90
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chapter 6
resulting dates and times of these events were
selected and attributed to appropriate trajectories.
This resulted in a subset of trajectories related to
both polluted (top 25th percentile) and unpolluted
(bottom 25th percentile) events.
The influence of the continental emission
source regions to the top 25th percentile PM2 5
concentrations at Kejimkujik (first panel on the
right) is shown by the darker black-red sections in
Figure 6.8. Results from the event climatology for
PM2 5 (Figure 6.8) also show the significance of
this region to the top 25th percentile concentra-
tions at St. Andrews. The investigation of the top
25th percentiles of the pollutants confirms the sig-
nificant impact of the emission areas of the east-
ern United States, southern Ontario and southern
Prairies on elevated concentrations at these two
sites in Nova Scotia and New Brunswick.
6.1.2 Positive Matrix Factorization
The application of Positive Matrix Factorization
(PMF) to air quality studies has become an
increasingly popular tool for elucidating source
apportionment (Yakovleva and Hopke, 1999;
Paterson et al., 1999; Prendes et al., 1999). Given
the appropriate PM2 5 dataset, one of the main
challenges in the application of PMF is to deter-
mine the number of source types contributing at a
given location. Identifying or "naming" the sources
contributing to the observed source types also
presents a challenge, and in both cases some sub-
jectivity is involved. The ideal solution is to utilize
multiple approaches (i.e., independent receptor
model types) and to look for consensus.
6.1.2.1 Sources of PM to Toronto, Ontario and
Vancouver, British Columbia
To better understand the processes influencing
PM2 5 concentration, and to determine its sources
and to learn more about its health effects, the
chemical composition of Toronto and Vancouver
PM2 5 was measured daily from January to
December 2001 and February 2000 to February
2001, respectively (Lee et al., 2003). Source appor-
tionment was undertaken using PMF. The PMF
analysis identified eight and six sources contribut-
ors to oi5
3:?6K3:f
ฎง:f!Sง:55
3:?s!o3:f
Figure 6.8 - PM, 5 top and bottom quartile back-
trajectory climatology events (based on 1999-2001
data). Kejimkujik data in the top two rows and
St. Andrews data in the bottom two rows. The figures
illustrate the frequencies with respect to climatology
using SL-PSCF.
91
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Canada - United States Transboundary PM Science Assessment
ing to PM2 5 in Toronto and Vancouver respective-
ly (Figure 6,9). In Toronto, the main components of
PM2 5 identified were coal combustion (30 per-
cent) related to regional transport, secondary NOg
(34 percent) related to both local and upwind
sources of NOx and NH3, secondary organic
aerosols and biomass burning (9 percent) and
motor vehicle traffic (9 percent). Coal combustion
was related to regional transport (both from
Canada and the United States) as there are no sig-
nificant emission sources of coal combustion in
the immediate area. As a result, the signal detect-
ed using the PMF analysis is related to transport
into the area from non-local sources. The other
detectable components- were road salt (winter),
road dust/soil (yearly), smelters or related indus-
try, and oil combustion. In Vancouver, the three
major components were secondary NH4N03 (49
percent), secondary organic acid with SOj (23 per-
cent), and motor vehicles (20 percent). The minor
components were road dust/soil, sea salt and oil
combustion. The average PM2 5 mass in Vancouver
was observed to be approximately 44 percent
lower than PM2 5 levels in Toronto, The total influ-
ence of localized vehicle-related sources was esti-
mated to be 36 percent and 51 percent in Toronto
and Vancouver respectively.
6.1.2.2 Comparability of Receptor Model Results on
PM2 5 Sources in Toronto
The raw data from Lee et al. were subsequently
conveyed to a team of U.S. analysts at the Vermont
Department Of Environmental Conservation,
where they were analyzed using a second receptor
model, UNMIX. The independent PMF and UNMIX
results were then compared, refined and revised
with local surface meteorological data and ensem-
ble backward trajectory techniques then applied to
help evaluate and interpret the results. Annual
average PM2 5 mass contributions from the result-
ing PMF and UNMIX sources are displayed in
Figure 6.10.
The average annual PM2 5 mass concentration
during this period was 14 |ig/m3 (just below the
level of the U.S. standard) , with maximum 24-hour
concentrations (98th percentile) of 35 |ig/m3 (just
above the Canadian standard). Both models
reproduced the measured annual and daily PM2 5
mass measurements in terms of the identified con-
tributors, which included smelters (5 percent),
(a)
Toronto H Summer 0Winter ฆ Total
Ammonium Secondary Organic Vehicles Road Road Salt Smelter Oil
fJitrate Coal Acids Dust/Soil Combustion
)
Vancouver ~ Summer DWinter BTotal
Ammonium Organic Vehicles Road Dust/Soil Sea Salt Oil Combustion
Nitrate Acid s/Sul fate
Figure 6.9 - Percent contribution.
by component, to PMj j mass
observed in a) Toronto and
b) Vancouver as determined
using PMKMLR,
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chapter 6
Figure 6.10 - Annual average modelled PM2 5
contributions in Toronto, (February 2000 - February
2001) using UNMIX (a) and PMF (b) receptor
modelling techniques
PMF Sources
UNMIX Sources
1(3 2n
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Canada - United States Transboundary PM Science Assessment
MV
Pnrnaiy Cost
(NH4J2604
Figured.13 - UNMIX motor
vehicle arid trial-related sources
vs. local surface wind speed
arid direction., Bluf shading
emphasizes directions from
which source influence-is
greatest at low wind speeds.
Pink shading emphasizes
directions where source
influence increases at all
wind speeds. Red shading
emphasizes directions from
which source influence,
increases at high wind speeds.
Figure 6.14 - Incremental
probability fields for coal-related
sources at Toronto and other
eastern sites,
coal-related sources to Toronto PM2 5. This coal-
related source can be split into three separate
components based on the PMF and UNMIX analy-
ses: primary coal (emitted from the source in par-
ticle phase), secondary (NH4)2S04 and acidic Sul-
phates/secondary organics, While there is not a
perfect correspondence in their upwind probability
fields, the most probable upwind locations for all
three sources are similar and converge on a U.S.
region of high-density emissions from coal-fired
utilities. In the right hand panel of Figure 6.14, the
probability fields for the three Toronto "coal-related"
sources are combined and compared (at similar
incremental probability contours of 0.002) with
Underhill,
ishinglori, DC,
Primary Co
Acidic Sulfates & Seconds
Secondary (NH4)2S04
ฆra*jSBSj
Upwind Probability Fields for 3 Upwind Probability Fields for "Coal Related"
"Coal Related" Toronto Sources Sources at 5 Northeastern Receptor sites
94
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chapter 6
dary Waters,
Great Smoky Mountains NP
Toronto NH4N03 Source
Increases 25% on
Weekcteys vs. Weekends
Total Coal 2ndaryN03 Total MV/
Averaged PMF and UNMIX Toronto Sources
Upv/ind Probability Fields for Ammonium Nitrate
Weekday Source Increases in Toronto
' -I. 1.MI-UIU,
Lye Brook VT
Figure 6.15 - Incremental probability fields and day-of-week patterns in Toronto NH4N03:"soukปs:"!
3 Coal Source
Ccmpenente
0.802
O.OSJ
0.004
Toronto Source Contribubons by Daily PM-2.5 Mass Category
;:i: :
_
ฆ
i
r
~ cnrlery seidj
DJWi2S04
ฆ Pnmory Coal
D 2 rotary WQ3
B^KI {2n|
O Snwtt #2
~ Road Dust
ฆ UซS41 MV
ฆ 0*ปMV
&-10 tO-20 20-30
PM-2.5 Mass Ccncentratcns (ug/rn3)
Upwind ProbabrSty Fซlds for Mapr Toronto Source Categories
Figure 6.16 - Summary of major "toronto source regions and influences on daily PMa ซ mass concentrations.
similar results from other recent studies which
have applied a similar combination of PMF and or
UNMIX receptor models and ensemble back trajec-
tory techniques. The consistency and convergence
of results from these different model applications
adds confidence to the Toronto results, and sug-
gests a common "universal donor" source region
influencing multiple receptor locations in the
Northeast transboundary region.
Certain features of the modelled NH4N0-3
component also suggest a complex "causality".
The left side of Figure 6.15 compares the incre-
mental probability field for the Toronto NH4N0s
sources: with those from other recent receptor
modelling studies at (rural) eastern U.S. sites.
There is a moderately strong degree of conver-
gence in the most common upwind areas for high
NOj from these widely separated receptor sites,
which suggests a critical influence from agricultural
(fertilizer and livestock) NH3 emissions in the
north-central U.S. "corn belt." However, as indicated
on the right side of Figure 6,15, there is a moder-
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Canada - United States Transboundary PM Science Assessment
ately strong weekday increase in the influence of
nitrate in Toronto, suggesting that local, as well as
more distant sources of NOx and/or NH3 are also
important contributors. The implied "co-causality"
here raises additional questions for control strate-
gy development. If aerosol NH4N03 is limited by
the availability of NH3, would reductions in S02
lead to reductions in aerosol SO= but increases in
aerosol N03"? If NH3 emissions were reduced,
would we expect to see decreases in aerosol N03,
but increases in SOj acidity and secondary organ-
ic aerosol formation?
Figure 6.16 summarizes the trajectory-based
upwind probability fields for the three major modelled
categories in Toronto, and also shows the relative
contributions from the UNMIX components on days
with different total fine mass concentrations.
Local motor vehicle sources (and small nearby
smelter or industrial sources) have a relatively
constant influence, and are most evident on the
cleanest days (which also tend to occur with
northerly wind flows). Secondary NH4N03,
formed when temperature conditions are
favourable, from precursor emissions of both local
and more distant (Canadian and U.S.) emission
sources, is the largest contributor to annual aver-
age fine mass and on days of moderate to high
PM2 5 concentrations. The coal-related source
influences have a substantial transboundary con-
tribution from U.S. sources, and are especially
important contributors on the days of highest
PM2 5 concentration.
6.1.2.3 PMF and Back Trajectory Analysis at Eight
U.S. Cities
Under contract, the U.S. EPA prepared a study of
eight cities using source apportionment and tra-
jectory analyses. The source apportionment analy-
sis at each of the eight cities provides evidence of
the types and locations of sources that are most
likely to be major contributors to PM2 5 mass at
each city. The source apportionment and back tra-
jectory studies used speciated PM2 5 data from
eight EPA Trend Sites located in Birmingham,
Alabama; Bronx, New York; Charlotte, North
Carolina; Houston, Texas; Indianapolis, Indiana;
Milwaukee, Wisconsin; St. Louis, Missouri; and
Washington, D.C. These sites are in urban areas,
and are expected to be affected by both local and
distant sources of PM. The results of both the
source apportionment and back trajectory analy-
ses are consistent with this expectation.
The preliminary source identifications were
based first on the chemical composition of the
PM2 5 profiles. These were then balanced against
the relative contribution of the source to the vari-
ous species and time series output. Second, local
monitoring personnel were contacted to discuss
potential sources of PM measured at the receptor.
Third, back trajectories were used to identify
source locations for sources that are 3 to 72 hours
upwind. Pollution roses were used to identify
source directions from local winds. Attempts were
made to verify that local point sources exist
approximately in the directions indicated.
For each site, the PM2 5 was apportioned into
six to eight components. There were several com-
monly identified contributors, including secondary
SOj (Figure 6.17), fireworks, industrial activities,
forest fires, diesel, and crustal matter. The PM2 5
apportioned to forest fires at the Washington, D.C
site was clearly linked to the July 2002 forest fires
in eastern Canada (see Section 6.1.3.1).
Milwaukee, Wl, Source 1
Source Contribution Function for High Source Strength
r
J ' I \ | * I J N
/ f 1A 7( A*
Lower Bound 0.00 ฆ 0.20
ฆ 0-25 ฆ 0.30
Figure 6.17 - Sulphate source region plot for Source 1,
(NH4)2S04, at Milwaukee, WI.
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chapter 6
Figure 6.18 - Pie charts of the
source apportionment .results
for various locations in the
United States. (Some charts
moved for clarity)
E KutefeCoiJ
aa KibBb
Mod Is
^ Hotiue Buring
^ IndutWal
IE CokM and SUI
~ Cmor/Not IdertHod
Back-trajectory analyses and wind/pollution
roses yield source location information for the
apportioned PM2 5 contributors. Nitrate sources
are associated with the Midwest farming regions
while the back-trajectory analyses for the oil-based
SOj component indicated large southern source
regions. The analysis for the SOj component is
complicated by the fact that some of the sources
seem to be related to high-pressure systems ป(as
evidenced by the clockwise swirl of many of the
back trajectories for the high source days).
Sulphate, from either eoal-or oil-based
sources, accounts for about one-third of PM2 5
mass. The next largest portion is either from NOj
components or mobile sources with all three of
these categories showing long-range transport
components. The smaller source:contributions are
more: site-specific, except for crustal dust. As-
many as eight source categories, including marine
influences, metal production, general industrial,
and fuel oil, are within the range of resolvability
with approximately one year of speciation data at
current levels of technology. Linking wind trajecto-
ries with the source apportionment results allows
one to develop source regions (i.e., geographic
regions with a high probability of being the origin
of the mass associated with a source profile).
These source regions provide evidence that at
least some of the particles associated with the
source profiles are likely transported over long dis-
tances. For example, the highest probability
source region for the coal combustion source pro-
file for Birmingham includes parts of the following
states: Missouri, Illinois, Indiana, Ohio, Kentucky,
Virginia, North Carolina, South Carolina, Alabama,
and Mississippi.
6.T.2.4 Compilation of PM2 5 Source
Apportionment Studies from the United States
The U.S. EPA summarized the findings of 27 source
apportionment studies covering over 30 locations.
The literature compilation found that contribu-
tions from secondary SOj and coal combustion
sources were the largest or one of the largest
sources of PM2 5 in nearly every study, often con-
tributing more than 50 percent of PM2 5 to the
receptor. Furthermore, these trajectory analyses
often pointed to source regions containing coal-
fired power plants. In addition, if the study time
frame was sufficiently long, secondary SOj and
coal combustion had different winter and summer
profiles- which were attributed to extremes of
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Canada - United States Transboundary PM Science Assessment
atmospheric chemistry between source regions and
receptors. Studies looking at longer time periods
observed reductions in contributions for some
sources (power plants, smelters), attributed to
reductions in emissions, fuel switching (from oil tO:
natural gas), and changes in meteorological condi-
tions (warm winters in late 1990s). For the western
locations, mobile sources and vegetative burning
tend to have larger contributions to total PM.
Figure 6.18 shows pie charts of the various appor-
tionment results for areas across the United States.
In general, the results from many of the stud-
ies were similar. A few receptors were studied
repeatedly, such as Underhill, Vermont, and
Brigantine, New Jersey, The contributors identified
are grouped into seven categories: SO=/coal,
mobile, NCfc biomass burning, industrial, crustal
and salt, and other/not identified. Note that in
Figure 6,18 the results from neighboring sites are
generally quite similar.
6.1.2.5 Source Locations and Time Series Analyses
in U.S. Cities
A number of studies have assessed sources of
observed PM2 5 in U.S. cities. In these studies,
PMF and UNMIX were either used individually or
in tandem to apportion sources to observed PM2 5
levels. All back trajectory analyses for sites in the
eastern United States associate the SOj compo-
nent of PM with the Ohio River Valley area. Several
studies noted transport across the Canadian bor-
der, specifically SOj from the midwestern United
States into Canada, and smelter emissions from
Canada into the northeastern United States. There
are plans to use the back-trajectory data to quanti-
fy the transport; however, these studies are not yet
complete. All of the studies looked at long-term
averages and most looked at seasonal (3-month)
averages. There was very little analysis of daily or
weekly events, with a few exceptions. (For the
most part, the studies considered are motivated by
long-term concerns, such as trends in regional
haze.) Lee et al. (2003 a) followed up on a crustal
source by identifying several days that were possi-
bly influenced by Saharan dust. Coutant et al.
(2002) mention the influence of fireworks in
Houston, Texas, Long (2002) studied a particular
event (2002 Winter Olympics) and documented
changes in the source proportions (mobile sources
were higher) and temporal changes (mobile
e 2002/0
r: 22
Figure:6,19 - The composites of MODIStder.ived aerosol optical depth (color) and cloud optical depth (black-white)
superimposed over continuous PM, g monitors (bars) for July 6th and 7th, 2GH2. The hourly PM2 5 mass concentration
is indicated by the height of the bar, while the color of the bar represents the 24-hour running average mass-
concentration color coded to the US EPA Air Quality Index The yellow to red colors of aerosol optical depth show
elevated aerosol concentrations and have been found to correlate strongly with PMa 6 levels. Note the elevated PM
associated with both measures of aerosol in Canada and the northeast United States,
98
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chapter 6
sources were evenly distributed instead of exhibit-
ing a diurnal pattern). In several cases where
datasets covering very long time periods were eval-
uated, reductions in emissions were observed from
power plants (Poirot et al., 2001), fuel oil (Lee et
al., 2003a), and smelters (Battye, 2002). These
were attributed to increased emission controls,
fuel switching (e.g., from oil to natural gas), and
meteorological conditions (e.g., warmer winters in
the late 1990s).
6.1.3 Satellite Observations
6.1.3.1 Impact of PM from Forest Fires to Eastern
North America
Direct observation of PM aerosol events using
satellite sensors can provide a qualitative perspec-
tive of sources and receptors of PM and PM precur-
sors. The boreal forest wildfires in southern
Quebec during the summer of 2002 produced large
amounts of aerosol loading within the lower tropo-
sphere. Meteorological conditions provided the
mechanism for southerly transport of particulate,
increasing ground level PM2 5 concentrations in
large portions of the eastern United States. Daily
aerosol optical depth values from the MODIS terra
satellite captured the transport of this smoke
across Canada and into the Northeastern United
States. Figure 6.19 shows the transport of the
smoke plume through eastern Canada on July 6th,
2002, and the subsequent transport of PM across
much of the northeastern United States on July
7th, 2002.
6.2 key science messages
PM2 5 is transported across the border region
between Canada and the United States, leading
to elevated concentrations of PM in both coun-
tries. Most of the analyses point to S02 and
NOx emissions as being primarily regional con-
tributors to PM, while organic/black carbon and
other PM constituents tend to be more local in
nature.
Carbonaceous mass is prevalent everywhere,
and is the major component of urban excess at
sites in the northeastern United States.
Consistent with other studies, most sulphates
are associated with regional sources of S02; the
urban excess of the SOj component is small.
Contributors to PM2 5 in both Vancouver and
Toronto include secondary nitrate, regional
transport of coal combustion products, diesel
motor vehicles, secondary organic acids and
road dust. Both the NH4N03 and coal combus-
tion components show seasonal variability.
Emissions from primary and secondary coal
and secondary organic acids are transported
greater distances in comparison to diesel vehi-
cles and road dust.
Local motor vehicle sources (and small nearby
smelter or industrial sources) have a relatively
constant influence on PM2 5 concentrations in
Toronto, and are most evident on the cleanest
days (which also tend to occur with northerly
wind flows). Coal-related sources have a sub-
stantial transboundary contribution from the
United States, and are especially important on
days of high PM2 5 concentration.
Natural sources of PM (i.e., forest fires) can also
influence ambient air quality. Satellite observa-
tions confirm the impact of Canadian forest fire
events on U.S. aerosol optical depth.
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Chapter
CONCLUSIONS
As a cumulative result of three bi-national work-
shops, and of discussions therein, seven key
objectives were identified for this Transboundary
Particulate Matter Science Assessment. These
objectives have been addressed using a combina-
tion of ambient observations, data analysis, and
application of modelling tools in both Canada and
the United States. In each step of the Assessment,
key science messages were captured to synthesize
the current state of knowledge on the transbound-
ary transport of PM2 5, in keeping with the infor-
mation needs of the bi-national policy community.
The conclusions of this Assessment focus the key
science messages on the seven objectives, and
thus provide scientific support for further regulato-
ry and technical programs.
OBJECTIVE 1 :
Is there a fine PM problem in the border
regions?
Current ambient levels of PM2 5 in the border
regions exceed the standards set for PM2 5 in
several regions of both Canada and the United
States. The eastern portion of the border
domain (i.e., northeastern United States,
Industrial Midwest, and the Windsor-Quebec
City corridor) exhibits levels that exceed the
15 pg/m3 annual standard in the United States
and the 30 pg/m3 98th percentile three-year
average Canadian standard for the time peri-
ods evaluated.
There are sites with elevated PM2 5 levels
(with very few sites exceeding either standard
for the time periods evaluated) in the Georgia
Basin - Puget Sound airshed, but the problem
is more confined, and the levels generally
lower than in the northeastern airshed.
PM2 5 is transported across the border region
between Canada and the United States, lead-
ing to elevated concentrations of PM2 5 in
both countries. Most of the analyses point to
S02 as a primarily regional contributor and
NOx as both a local and regional contributor
to PM2 5, while organic/black carbon and
other PM constituents tend to be more local in
nature. Carbonaceous mass is prevalent
everywhere, but is the major component of
urban excess at sites in the northeastern
United States.
Comparisons of PM2 5 levels at different sites
reveal that on average, the local contribution
to total PM2 5 in Toronto, Canada is approxi-
mately 30 to 35 percent. At sites in eastern
Canada (e.g., Chapter 2, Figure 2.2), average
PM2 5 concentrations were 2 to 4 times
greater under south/southwesterly flow com-
pared to northerly flow conditions. This
observation suggests that the majority of
PM2 5 at these locations is arriving from
sources south of this region.
Canadian provinces have been found to con-
tribute approximately 13 percent of PM2 5
measured at 17 Class 1 sites in the United
States, while the transport of PM2 5 and PM
precursors across the border region leads to
'above average' PM2 5 concentrations in eastern
Canada.
OBJECTIVE 2:
What is the extent of the problem (if stan-
dards are exceeded, by how much, where
and when are they exceeded)?
Current ambient levels of PM2 5 in the border
regions exceed the standards set for PM2 5 in
several regions of both Canada and the United
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Canada - United States Transboundary PM Science Assessment
States. Annual levels of PM2 5 are as high as
18 pg/m3 in the northeastern United States for
the period 2000-2003.
A large portion of sites in the eastern portion
of the border domain (i.e. northeastern United
States, Industrial Midwest and the Windsor-
Quebec City corridor) exhibit levels that also
exceed the 30 pg/m3 98th percentile three-
year average (of 24-hour values) Canadian
standard for the years 2000-2002. The 98th
percentile values are as high as 65 pg/m3 in
some areas of the northeastern United States.
No sites in western Canada exhibit levels that
exceed the U.S. or Canadian standards (with
the exception of one point-source-influenced
site in British Columbia) for the data included
in this Assessment.
PM2 5 concentrations are highest (on average)
in the winter (Dec, Jan, Feb) and summer
(June, July, Aug).
OBJECTIVE 3:
Does the PM issue vary geographically?
Elevated concentrations of PM2 5 are found
more often in the following regions: north-
eastern United States, Industrial Midwest,
southwestern Ontario and the northwestern
United States.
Areas in the midwestern United States and
Canada do not exhibit elevated average PM2 5
concentrations in comparison, but still record
high PM2 5 concentrations during episodic
conditions.
Urban concentrations of PM2 5 are higher
than rural concentrations in all regions of both
Canada and the United States; however, rural
sites can exhibit very high PM2 5 levels during
large-scale PM episodes.
OBJECTIVE 4:
What PM precursors are of most concern
regionally and sub-regionally?
The highest particle SOj and NO3 concentra-
tions are found in areas with high S02 and
NOx emissions. These areas include the
northeastern United States and southwestern
Ontario.
Levels of PM2 5 and PM precursors (S02,
NOx) have declined, particularly early on in
the data record however, since the mid-1990s,
levels of PM and PM precursors have generally
remained flat.
PM2 5 in the border region consists of, in
order of relative importance to annual PM2 5
levels, organic/black carbon, SOj, NHJ, NO3,
soil dust and trace elements. Secondary par-
ticulate (i.e., NHJ, NO3 and SOj) is found to
play a key role under episodic conditions in
Ontario. In the border region, organic and
black carbon and SO= are seen to be the dom-
inant species in summer, fall, and spring
PM2 5 aerosols. Nitrates are a major species
in the winter in the northeast and carbon is a
major species in the winter in the northwest.
Carbonaceous mass is prevalent everywhere,
and is the major component of urban excess
at sites in the northeastern United States.
Consistent with other studies, most sulphates
are associated with regional sources of S02;
the urban excess of the SOj component is
small.
Ambient levels of PM precursors also con-
tribute to the wet deposition of NO3 and SOj,
and resulting ecosystem acidification. The
highest levels of deposition are located in the
northeastern United States and eastern
Canada, particularly in the border regions.
In the western regions, fine particles have a
greater percentage of mass as carbon com-
pounds relative to the east, where secondary
components are more prevalent.
OBJECTIVE 5:
What are the sources (or source regions)
of PM and PM precursors in the context
of geographic regions (i.e., west, central,
east)?
Components and contributing sources to
PM2 5 identified in both Vancouver and
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chapter 7
Toronto include secondary N03", regional
transport of coal combustion products, diesel
motor vehicles, secondary organic acids and
road dust. Both the NH4N03 and coal com-
bustion contributors show seasonal variabili-
ty. Primary and secondary coal and secondary
organic acids are considered to be more
regional in nature in comparison to diesel
vehicles and road dust, which can be consid-
ered to be more local sources.
Local motor vehicle sources (and small nearby
smelter or industrial sources) have a relatively
constant influence on PM2 5 concentrations in
Toronto, and are most evident on the cleanest
days (which also tend to occur with northerly
wind flows). Coal-related sources have a sub-
stantial transboundary contribution from the
United States, and are particularly important
on days of high PM2 5 concentration.
Analysis of upwind probability fields for coal
related sources and NH4N03 in Toronto indi-
cates a region of high density emissions from
coal fired utilities in the northeastern United
States is influencing PM2 5 concentrations. A
similar analysis for NH4N03 indicates a more
widespread source region, in the northeastern
United States as well as the north-central
United States, a region of high agricultural
NH3 emissions.
Natural sources of PM (i.e., forest fires and
biogenic sources) can also influence ambient
air quality. Satellite observations confirm the
impact of Canadian forest fire events on U.S.
aerosol optical depth.
Emissions from the northeastern United
States and southern Canada have an impact
on PM2 5 levels in many areas of the two
countries, including as far east as Nova Scotia
and New Brunswick, particularly influencing
the top 25th percentile of PM2 5 concentra-
tions in these regions.
Visibility is impaired at Glacier National Park,
Montana, as a result of particle N03, SOj and
organic carbon from source regions in both
Canada and the United States.
Transport of S04 from the midwestern United
States to Canada was observed in several
studies. As well, smelter emissions from
Canada were observed to contribute to PM
levels in the United States in several studies.
Source-receptor analyses indicate that there
are several areas which contribute to elevated
PM levels in eastern North America. These
areas include, but are not limited to, the
following:
Air masses originating from a relatively
large area from southeast Ohio to the
western part of Virginia and western
Kentucky to central Tennessee tended to
result in relatively high PM2 5 concentra-
tions over northeastern North America.
The Windsor-Quebec City Corridor
The U.S Midwest and Boston to
Washington corridor
The Ohio River Valley
Northern Alberta and Saskatchewan and
the central United States (Montana, North
Dakota)
Vancouver/Seattle, Oregon and northern
California
The Georgia Basin - Puget Sound airshed is
relatively small; hence, sources and receptors
of PM and PM precursors, responsible for the
majority of transboundary transport, are found
throughout the region.
The precise contribution of U.S. versus
Canadian sources to air-quality levels (specifi-
cally PM) in the two respective countries is not
addressed in detail in this Assessment. More
specific model applications and source-recep-
tor analyses are recommended.
OBJECTIVE 6:
How are PM precursor emissions spatially
distributed, and what are the transport
characteristics of these emissions?
Emissions of S02 and NOx are projected to
decrease while emissions of NH3, VOCs and
CO are projected to increase between the base
case and control scenarios.
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Canada - United States Transboundary PM Science Assessment
Emissions of S02 and NOx under all consid-
ered scenarios are concentrated in the
Industrial Midwest, northeastern United
States and southern Ontario, while emissions
of NH3 are concentrated further west in the
central Midwest region.
The emissions of S02, NOx and NH3, and
their contributions to PM2 5 levels vary
seasonally.
Transport of PM and PM precursors from the
Ohio River Valley has been observed to be
associated with the highest PM2 5 concentra-
tions observed in the heavily populated areas
in eastern Canada and the northeastern
United States. These observation-based find-
ings are consistent with the spatial distribu-
tion of the main S02 emissions sources and
the major NOx point sources.
Trajectory analyses (Ch. 6) indicate that
there is significant transport of PM and
PM-precursors across the Canada-U.S. border.
OBJECTIVE 7:
What are the impacts of current and
proposed emission reductions scenarios
on fine PM levels in North America?
U.S. and Canadian controls that are expected
to be implemented result in maximum annual
reductions of PM2 5 of 1.8 pg/m3 in 2010 and
2.3 pg/m3 in 2020. The reductions vary tempo-
rally and spatially, with larger reductions in
the eastern portion of the REMSAD modelling
domain.
Proposed additional S02 and NOx emission
reductions should provide additional reduc-
tions in ambient PM2 5 levels in eastern North
America. The observed PM2 5 reductions may
vary by season and depend strongly on reduc-
tions in PM2 5 SOj mass.
Simultaneous reductions in both S02 and
NOx may also provide concurrent reductions
in NHJ, due to the reduction of gaseous S02
and NOx available to react with gaseous NH3.
Reductions in NOx emissions will correspond
to decreases in PM2 5 N03mass in some parts
of eastern North America but increases in
other areas due to N03 substitution. There is
significance placed on the role of NH3 in this
relationship, suggesting there may be value in
investigating possible benefits due to NH3
emission reductions in conjunction with S02
and NOx emission reductions.
Comparisons of the AURAMS and REMSAD
predictions showed good qualitative agree-
ment and consistency for all four PM fields
and both seasons in terms of the atmospheric
response to emission reductions.
In the Georgia Basin - Puget Sound region,
impacts from transboundary transport occur
along the border (within + 50 km) with
some frequency; however, the incidence of
long-range/regional transport (over 100 km)
was low. Peak PM2 5 levels are projected to
increase modestly in urban areas as well as
downwind of urban areas during both summer
and winter simulations
Co-benefits of emission reduction scenarios
include reduced ground-level ozone levels,
reductions in NO~ and SO= deposition, and
improved visibility.
104
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Appendix
REMSAD AND AURAMS MODEL PERFORMANCE
AI.O REMSAD MODEL
PERFORMANCE
Scatter plots displaying REMSAD model perform-
ance for the 1996 base case are shown on the
following pages. The REMSAD base case was run
using 1996 meteorology and emissions. The
PM2 5 and PM2 5 components (SOj, N03, NHJ,
OC, BC, and soil) predicted by REMSAD were then
compared to available ambient monitoring data
for 1996. The scatter plots contain model-predict-
ed concentrations at the grid cell where an air-
quality monitor is located versus the observed
monitoring site concentrations for the averaging
period of interest. The following scatter plots are
generally for seasonal averaging periods. In addi-
tion, PM2 5 scatter plots are provided for an annu-
al averaging period to coincide with the U.S. air-
quality standard for PM2 5. Scatter plots for
the United States are provided primarily for
the Interagency Monitoring of Protected Visual
Environments (IMPROVE) network, which
contained measurements of PM2 5, SO=, particle
NO3, OC, BC, and soil. Also, scatter plots for SOj
and total NOjfrom the Clean Air Status and Trends
Network (CASTNET) are provided for the United
States. Scatter plots are provided for the Canadian
National Air Pollution Surveillance (NAPS) moni-
toring network for PM2 5, SOj, NOj, and NHJ. In
addition, scatter plots are provided from the
Canadian Air and Precipitation Monitoring
Network (CAPMoN) for SOj, NO3, and NH+ Note
that NAPS is represented by NAP in the scatter
plot headings and CAPMoN is represented by
CAPM in the scatter plot headings.
The annual PM2 5 concentrations predicted by
REMSAD are generally within 30% of observed val-
ues at the eastern IMPROVE monitoring sites with-
out much bias toward over or under-prediction. At
the western IMPROVE monitoring sites, there is a
bias toward model under-prediction of annual
PM2 5 concentrations. The majority of model-pre-
dicted seasonal averages at the eastern IMPROVE
sites are generally within 30% of the observed sea-
sonal averages. The western IMPROVE sites show
a seasonal bias towards model under-prediction in
all seasons with the strongest under-prediction
bias in the summer. The annual PM2 5 concentra-
tions predicted by REMSAD at the NAPS sites
show a bias toward over-prediction at both the
eastern and western monitors with the over-pre-
dictions generally significantly less than 100%.
The REMSAD-predicted seasonal PM2 5 concen-
trations at the NAPS sites also show a bias
towards over-prediction. The summer season has
the least bias toward over-prediction at the eastern
NAPS sites where model predicted PM2 5 concen-
trations are generally within 30% of the observed
PM2 5 concentrations.
The seasonal SOj concentrations at the east-
ern IMPROVE sites are generally within 30% of the
observed seasonal concentrations for all seasons.
The western IMPROVE monitors generally show
the model-predicted seasonal SOj concentrations
to be biased toward under-prediction. The seasonal
SOJ scatter plots for the CASTNET dry deposition
monitoring network show model-predicted sea-
sonal SOj concentrations to generally be within
30% of observed SO= concentrations at the eastern
monitors. In the winter, when there are substan-
tially fewer monitors and observed SOj concentra-
tions are much lower than the other seasons, there
is a somewhat larger percentage bias toward
under-prediction at the eastern CASTNET moni-
tors. The western CASTNET dry deposition scatter
plots show a bias toward SOj concentration
under-prediction for all seasons. The seasonal
REMSAD model predicted SOj concentrations are
generally within 30% of the monitored SOj con-
1 1 1
-------
Canada - United States Transboundary PM Science Assessment
centrations for the eastern NAPS Canadian moni-
toring sites. The largest percent bias toward under-
prediction for the eastern NAPS sites is in the win-
ter when observed SO= concentrations are lowest.
The model predicted SOj concentrations at all the
western NAPS sites are biased toward under-pre-
diction. Seasonal model predicted SOj concen-
trations at the eastern CAPMoN sites are generally
within 30% of observed monitored concentrations.
As has been seen at the other SOj monitoring net-
works, the greatest bias toward under-prediction at
the eastern CAPMoN monitors is in the winter
when SOj concentrations are lowest. The model-
predicted SOj concentrations at the western
CAPMoN sites show a bias toward under-predic-
tion.
Seasonal model-predicted particle N03" con-
centrations at the eastern IMPROVE sites are
biased high for every season with the least bias
occurring in the summer. Seasonal model-predict-
ed particle N03" concentrations at the western
IMPROVE monitors are generally unbiased, except
in the summer where they are biased low.
Seasonal model-predicted particle NOj concentra-
tions at the eastern and western NAPS sites are
biased high with the least bias at the western sites
in the winter. The REMSAD model-predicted parti-
cle NOj concentrations at the CAPMoN sites do
not show the strong over-prediction of particle
NOj shown at the other monitoring networks. The
majority of model-predicted particle NOj concen-
trations at the eastern CAPMoN sites are within
30% of the observed values in each season except
the summer where there is a significant under-pre-
diction of observed NOj concentrations. Seasonal
NOj concentrations are generally under-predicted
by the model at the western CAPMoN sites. The
CASTNET DRY scatter plot is for total NOj, which
consists of particle NOj plus NOj from gaseous
HNO3. The IMPROVE, NAPS, and CAPMoN scatter
plots are for only particle NOj. The majority of the
seasonal total NOj concentrations predicted by
REMSAD at the eastern CASTNET sites are within
a factor of two of the observed concentrations with
the largest over-prediction bias in the fall. The
model-predicted seasonal total N03" concentra-
tions show a bias toward under-prediction at the
western CASTNET sites.
REMSAD tends to over-predict NHJ concen-
trations at the at the eastern NAPS sites for all sea-
sons except the summer. In the summer, the pre-
dicted NHJ concentrations are generally within
30% of observed NHJ concentrations at the east-
ern NAPS sites. There is a tendency for the model
to over-predict NHJ concentrations at the western
NAPS sites for all seasons except winter. The
majority of seasonal NHJ concentrations predict-
ed by the model at the eastern and western
CAPMoN sites are within 30% of observed NHJ
concentrations.
The majority of the model-predicted seasonal
OC concentrations at the eastern IMPROVE moni-
toring sites are within 30% of observed seasonal
OC concentrations with the summer displaying a
somewhat larger over-prediction bias. There does
not appear to be a substantial bias toward under-
or over-prediction of the model-predicted season-
al organic concentrations at the western IMPROVE
sites. However, at any single western IMPROVE
monitoring site, the model can over or under-pre-
dict the seasonal organic carbon concentration by
a factor of two or more.
The scatter plots of model-predicted BC con-
centrations at the eastern IMPROVE sites show lit-
tle bias toward over- or under-prediction. The
majority of the eastern IMPROVE sites show sea-
sonal model-predicted BC within 30% of observed
seasonal BC concentrations. At the western
IMPROVE monitor sites, the seasonal scatter plots
do not show a distinctive bias toward under- or
over-prediction.
The model significantly over-predicts the soil
concentrations at the eastern IMPROVE monitor-
ing sites for all seasons. At the western IMPROVE
monitoring sites, the model is bias toward over-
predicting the soil concentrations for winter and
fall and under-predicting the soil concentrations
for summer and spring.
1 12
-------
appendix
PM2.5
1995 IMPROVE vs. REMSAD
Annua
20
15
10
5
0
D
5
10
15
20
Monitor Value (ug/m3)
" Oris in One Ime
"-I-1 5CW fns
O Eoatem Monltoea
O Wbebarn Monitors
MbdalRun: REM SAP v7DB6Xt
Ono ta OnB IfriB
+/- 30* line
1 ฆ+1 DP*/SDji fna
o Eoatiarn Monltora
O waetorn ManPtora
Modal Run: REN BAD nrdtureZp1_v70Be
Tffm paga arMttod on D4FEB20
PM 2.5
1996 NAP Canadian Sites vs. REMSAD
Annua
Monitor Value (ug/m3)
Fall Winter
S04
1996 IMPROVE vs. REMSAD
Spring Summer
Monitor Value (wq/mSj
Hoots* Vrtue (ug/nj)
" One ia ftiE line
1 +/- 3Qป lina
--H QCBt/SCK ifnfl
O Eo9teKtn Monitoca
O Western MonftoKS
Mattel Win: REMSAD IIrซsura?p 1_v7DBaxt
T_S04
1 99B CASTNET DRY vs. REMSAD
Spring Summer
Monitor Value (vq/mJj
Hon Vrtwe (ug/n-j)
" One ia ftiE Ifne
1 +/- 30s lina
--H QCBt/SCK ifna
O Eo9tem Monitoca
O western Monftocs
Mattel Win: REMSAD nr1_v?0Baxt
1 13
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Canada - United States Transboundary PM Science Assessment
S04
1 996 NAP Canadian Sites vs. REMSAD
Spring Summer
Fall
Monto rvalue (ug/mCi)
" One to One II
" ' ฆ+/- 3a* line
+100ป/50?s line
Winter
Monitor Value (ug/ mO)
S04
1996 CAPM Canadian Sites vs. REMSAD
Spring Summer
One to One lin
" ' ฆ+/ 30r. line
+1DDk/-5Dk lii
N 0 3
1 996 IMPROVE vs. REMSAD
Spring Summer
Fall
One to One lin
" ' +/- 30r. line
--MOO*/-50* lii
Winter
Eastern
O Western
N 0 3
1996 NAP Canadian Sites vs. REMSAD
Spring Summer
Fall
One to One line
" ' ฆ+/- 30?: line
+1QQx/50s line
Winter
1 14
-------
appendix
N 0 3
1996 CAPM Canadian Sites vs. REMSAD
Spring Summer
Winter
Monitor Value (ug/m3)
One to One line
+/- 30* line
+100?:/5DX line
O Eastern Monitors
O Western Monitors
This page created on 10DCT2003
T N05
1996 CASTNET DRY vs. REMSAD
Spring Summer
Winter
(ug/m3)
(ug/m3)
O Eastern
' +/- 30r. lin
ฆ-I-100V-50'!
nrdsure2p1_
N H 4
1996 NAP Canadian Sites vs. REMSAD
Spring Summer
Winter
One to One line
+/ 30k line
+100k/-50* line
| O Eastern Monitors |
This page created on D4FEB2TO4
N H 4
1996 CAPM Canadian Sites vs. REMSAD
Spring Summer
Winter
; i
One to One line
' +/- 30* line
-MOOx/50X line
1 15
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Canada - United States Transboundary PM Science Assessment
OMC
1 996 IMPROVE vs. REMSAD
EC
1 996 IMPROVE vs. REMSAD
A2.0 AURAMS EVALUATION
FOR TWO BASE CASES
A2.1 Data Availability
Model evaluation for both of the AURAMS base
cases (1-15 February 1998; 1-18 July 1995) was
complicated by the relatively small number of
PM2 5 measurements available. While a signifi-
cant number of ozone measurement stations were
in operation for these two periods, the opposite
was true for the PM2 5 species. This problem was
compounded by the fact that some PM networks
sample less frequently than daily. As an example,
prior to 2000 the IMPROVE network only made
measurements on Wednesdays and Saturdays.
Such non-daily sampling complicates evaluation
of multi-day model simulations, since the most
intense days of a pollution episode could occur on
a day with significantly fewer stations reporting.
For example, Figure A. 1 compares the PM2 5 meas-
urements from 24-hour filters that are available for
Saturday, July 1st and Sunday, July 2nd, 1995; the
stations available on each day are colour-coded
according to the measured concentration of
PM2 5. The figure shows that U.S. PM2 5 measure-
ments are available for July 1st but not for July 2nd.
There were also more PM2 5 measurements
available for the winter 1998 period than for the
summer 1995 period, including more hourly meas-
urements. As a consequence, the PM2 5 perform-
ance evaluation for the summer will be somewhat
more qualitative as compared to the winter evalu-
ation. Table A. 1 summarizes the Canadian and
U.S. measurement networks used to evaluate both
episodes (see also Chapter 3) for PM2 5 mass,
PM2 5 inorganic chemical components, and ozone.
Note the heterogeneity of the different measure-
ment sets. Note too that the hourly PM2 5 meas-
urements avoid the problem of intermittent non-
daily sampling as they are obtained from continu-
ous instruments (TEOMs).
AURAMS performance is considered here for
both ozone and PM2 5 so as to take advantage of
the better spatial and temporal coverage of the
ozone monitoring networks. Given that the future-
year emission reductions discussed in Chapter 4
1 16
-------
Appendix
will impact both ground-level ozone and particu-
late matter, and given that secondary PM2 5 pro-
duction and gas-phase photochemistry are closely
linked, it is natural to consider both pollutants
together.
A2.2 Model Evaluation for Winter 1998
Figure A.2 shows observed and modelled time
series of PM2 5 mass from February 7th until
February 14th, 1998 at three locations in south-
eastern Canada: Kitchener, Ontario (2a);
PM2.5
ug/m3
July 1st 1995
&
PM2.5
ugm3
ฆ
J
4
28
21
11
7
0
July 1st 1995
Figure A-1 - Maps of stations -reporting 24-hour total PM2 5-concentrations for two consecutive- July 199-5 days.
21 stations reported on July 1st-compared to only 9 stations reporting on July 2nd.
104** UV absorption Hourly n.a.
AIRS
520**
TEOM
Hourly
10"
2.5"
386*, 520**
UV absorption
Hourly
n.a.
"available for summer case only, "available for winter case only
n.a. = non available, n.d. = non determined
Table A.1 Data networks available for model evaluation for two AURAMS simulation periods.
Species Measured (size cut in ^m)
Network # Stations Type Frequency S04= N03" NH+ EC OC PM,0 PMa 5 03
CAPMoN 9*. 7** 24-hr filters Daily n.d. n.d. n.d.
CAAMP* 5 24-hr filters Daily 2.1* 2.1* 2.1* 10* 2.5*
GAViM 2 24-hr filters 2/7days 2.6 2.6 2.6 2.5
IMPROVE 18 24-hr filters 2/7 days 2.6 2.6 2.6 2.6 2.6 10 2.5
NAPS 56*,93** 24-hr filters 1/6 days ฎ.6 2.6 2.6 2 5
104** TEOM Hourly 10" 2.5**
1 17
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Canada - United States Transboundary PM Science Assessment
Kftchenef, Wes! Avenue Station (Ont.),
Modeled PM.,
Observed PM,
Hamilton Beasley Park Station (Ont.)
Modeled PMn j|
Observed PMa 'I
OS/02 IOJD2 11ซa 12/02 13/02 1-WJ2
00.00 00.00 00 00 00:00 00:00 00:00
07ฉ2 08/02 09A32 10.-02 11/02 12/02
0000 00 00 0000 COOO 0000 00:00
Montreal. Drummond Station (Que l
Modeled PMrt
150
140
130
120
110
100
00
80
70
80
50
40
20
10
00 00
00:00
00 00
COOO
00 00
00:00
Figure A-2 - Time series of modelled and observed PM, s from February 7th to 14th 1998 for (a) Kitchener; Ontario-.,
(b) Hamilton; Ontario, and (e) Montreal; Quetee; Solid line: AURAMS simulation pgXntffi Dashed line;
Observations (jLig/m3),
Hamilton, Ontario (2b): and Montreal, Quebec
(2c), This period is of interest because of the
strong PM2 5 episode that occurred in eastern
Canada, beginning on February 9th in Kitchener
and Hamilton and on February 10th in Montreal.
Hourly PM2 5 concentrations as high as 70 |ag/m3,
were measured at the two Ontario stations while
the peak observed PM2 5 concentration for
Montreal was over 130 |ig/m3, AURAMS is able tO:
predict the observed day-to-day variation in parti-
cle mass over this one-week period, giving a good
representation of the mid-week increase in particle
mass., The modelled time traces are much
smoother than the continuous measurement
record, which can be attributed, at least in part, ta
the spatial resolution of AURAMS of 42 km. At this
resolution, AURAMS can only capture some Of the
features that are measured at a particular point,
due to fine-scale variations in meteorology and
emissions (i.e., point vs. grid-volume incommen-
surability). Note too that the TEOM measure-
ments are likely to be biased low, especially at
night, due to the impact of the heated inlet on
semi-volatile PM components entering the instru-
ment from wintertime ambient conditions.
Figure A.3 shows the corresponding ozone
time series plot for Hamilton. Ontario. The PM2 5
episode was reflected in the ozone concentration
time series by very low ozone levels, possibly as ,a
result of enhanced N02 titration associated with
1 18
-------
Appendix
Hamilton, Beasley Park Station (OnL)
Modeled Ozorw
Observed Ozor>e
07i"02 0&02 09/02 10/02 11/02 12/02 13X12 14/02
0000 00:00 0000 0000 0000 0000 0000 00:00
Ctota
Figure A.3 s Time serifฎ of modelled and observed
ozone (ppb) for Hamilton; Ontario from February 7th
to 14th 1998- Solid line: AURAMS simulation; dashed
linei observations.
stagnant conditions, AURAMS again tracked the
changes in ozone concentration very well.
Model-vs-measurement scatter plots of hourly
ozone and hourly PM2 5 concentrations are shown
in Figure A.4 for this same one-week period. On
the left, the ozone scatter plot shows a bias
towards under-prediction of hourly ozone concen-
trations (slope of 0.63,) and an R2 value of 0.48.
The PM2 5 scatter plot also shows an overall bias
to under-prediction (slope of 0.65), but some of
the smallest value can be grossly over-predicted,
driving the offset of the regression line to a value
of 10.5 |ag/m3 (see Table A.2). For PM2 5 the R2
value is 0,26. Note that hourly PM2 5 concentra-
tions as high as 160 |ag/m3 were both observed and
modelled for this period. A summary of the per-
formance statistics corresponding to Figure A.4 is
given in Table A.2.
Figures A.5 and A.6 present scatter plots com-
paring observed and predicted daily mass concen-
trations for PM2 5 and its three inorganic chemical
components for two sets of PM2 5 samples: the
IMPROVE and GAViM PM2 5 measurements were
reported for ambient conditions (Figure A.5)
whereas the NAPS PM2 s measurements were
reported at STP (Figure A.6). AURAMS PM predic-
tions are for .ambient conditions, but an STP con-
version was done in the preparation of Figure A.6
to allow a direct comparison with the NAPS data.
Note that particle NH+ was not measured by the
IMPROVE network for that time period but was
measured by the GAViM network. These plots are
characterized by relatively few measurements (see
Table A.3) and large scatter, particularly for the
three chemical components, but such scatter is:
characteristic of comparisons of air-quality model
predictions made for such short averaging periods..
Aside from one or tw outliers, agreement is bet-
ter than an order-of-magnitude, and there seems
to be a tendency to under-predict S04 and over-
predict NOs. Predictions of total PM2 5 mass do
not display much bias. Note too that the time aver-
aging associated with daily measurements rather
than hourly measurements does reduce scatter
(e.g., Figure A.4b vs, Figure A.6a). The performance
statistics corresponding to Figures A.5 and A.6 are
provided in Tables A.3 and A.4. Interestingly, a rel-
atively high R2 and a low RMSE are obtained for
the N03" PM component when comparing with
IMPROVE and GAViM measurements, whereas the
situation is reversed when comparing with the
NAPS observations. The number of speciated
NAPS data for that period is very limited, however,
which limits the meaningfulness of the statistics.
Table A.2 Performance statistics for hourly ozone and PM2 5 mass at all stations over the domain
from February 7th to 14th 1998. (where m number of observed values; R2: correlation coeffi-
cient; RMSE; root mean square error; NME: normalized mean error; MB: mean bias; NMB:
normalized mean bias (Kang et al., 2003))
Species n R2 aobs" RMSE NME MB NMB curve fitting equation
Hourly 03 34060 0.48 170 206 129 12.0 42.7 -5.2 -24.2 mod = 0.63 obs + 2.80
Hourly PM2 5 2739 0.26 582 360 232 22.0 61.4 2.8 13.1 mod = 0.65 obs +10.50
Legend: * variance of model data, "variance of observation data, ""covariance
1 19
-------
Canada - United States Transboundary PM Science Assessment
Model
Model
0 10 20 30 40 50 60 70 30 90 100 110 120 130 140 150 160
Hourly PM25 (ug/m3) Obs
Hourly Ozone (ppb)
Figure A-4 - Scatter plots for hourly ozone: (left panel) and hourly PM,. [right panel) at all stations over the domain for
all hours from February 7th to 14th 1998. Gray lines are 10:7, 1.1, 7:10 and 2:1, 1.1, 1:2 model-to-observation ratio lines
in left and right panels, respectively.
Table A.3 Performance statistics for PM2 5 mass:, PM2 5 S04, PM2 5 NH4, and PM2 5 N03
concentrations at all available IMPROVE and GAViM stations over the AURAMS domain
for all days from February 7th 00Z to 14th 00Z 1998. (see Table A.2 for definitions).
Species
n
R2
^mod
ฃ*obs
"mod-obs
RMSE
NME
MB
NMB curve fitting equation
PM2,s mass
31
0.23
297
19
36
15.9
67.1
3.2
29.0
mod = 1.87 obs - 6.37
PMj 5 SO4
30
0.02
1.8
3.4
0.3
2.4
59.4
-1.1
ฆ37.1
mod = 0.09 obs + 1.66
pm2.5 nh4
8
0.36
22
0.4
1.9
5.2
276.1
2.8
260.4
mod = 4.28 obs - 0.73
pm2.5no3
30
0.42
67
1.5
6.5
8.2
294.2
3.4
271.4
mod = 4.33 obs - 0.78
Legend: * variance of model data, "variance of observation data, ""covariance
120
-------
appendix
10 20 30 40 50 60 70 80
Particulate Matter fine fraction (ug/m3)
2 3 4 5 6 7 8
Sulfate fine fraction (ug/m3)
Model
16
Model
45
Ammonium fine fraction (ug/m3) Nitrate fine fraction (ug/m3)
Model
100
Model
11
Figure A.5 - Scatter plots of daily (a) PM, 5 mass, (b) PM, 5 SOJ, (c) PM, 5 NHJ, and (d) PM, 5 NOs concentrations at
all available IMPROVE and GAViM stations over the AURAMS domain for all days from February 7th 00Z to 14th 00Z
1998. Units are |.ig/m3 at ambient conditions. The black line is a best-fit line and the gray lines are 2:1, 1:1 and 1:2
model-to-observation ratio lines.
121
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Canada - United States Transboundary PM Science Assessment
Particulate Matter fine fraction (ug/m3)
Sulfate fine fraction (ug/m3)
Ammonium fine fraction (ug/m3)
Nitrate fine fraction (ug/m3)
Figure A.6: - Same as Figure A5 but for Canadian NAPS-stations and Hg/m3 at STP.
Table A.4 Performance statistics for PM2 5 mass, PM2 5 SOj, PM2 5 NH j, and PM2 5 NOg concentrations
at all available Canadian NAPS stations over the AURAMS domain for all days from February
7th 00Z tฉ-: 14th 00Z 1998. (see Table A.2 for definitions)
Species
n
R2
"mod
"obs
"mod-obs
RMSE
NME
MB
NMB curve fitting equation
PM3 5 mass
27
0.33
563
252
215
20.5
43.3
6.0
16.0
mod = 0.85 obs + 11.62
PM^ 5 SO4
7
0.24
2.3
4.1
-1.5
4.9
63.1
-3.9
-54.5
mod = -0.37 obs + 5.80
pm2.5 nh4
7
0.01
13
1.6
-0.5
5.2
78.4
3.6
67.9
mod = -0.29 obs + 9.76
pmz5 no3
7
0.01
126
15
-3.9
19.6
172.1
15.3
172.1
mod = -0.26 obs + 26.59
Legend: * variance of model data, ""variance of observation data, '"covariance
122
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Appendix
A2.3 Model Evaluation for Summer 1995
Figure A.7 presents time series erf modelled and
observed ground-level ozone for two stations in
the Windsor-Quebec City corridor for a ten-day
period July 8th to 17th, 1995. The left panel is for
a station in London, Ontario while the right panel
is for a station at St-Anicet, Quebec, west of
Montreal. This period includes both episodic and
130
London AqI S'te (Ont.)
Modeled Ozone
Observed Ozone
Sainl-Antcet (Qu6.)
Modeled Ozone
Observed Ozone
too
120
110
100
ฃ
a
c
o
1
i
60
c
8
50
03
c
40
C;
!%i
o
40
30
20
08/07
00:00
11/07
00:00
14/07
0000
14/07
00:00
/07
00
17/07
00 00
Date
Figure A-7 - Time series of modelled and observed ozone for London, Ontario (left panel) and Saint-Anieet, Quebec
(right panel) from July 8th to 16th 1995. Solid line: AURAMS prediction; dashed line: observations. All values in ppb.
Model
Model
Hourly PM25 (ug/m3)
Hourly Ozone (ppb)
Figure A-8 - Scatter plots for 6zsone at all stations over the domain for all hour's from July 8th to 11th 1995 (left panel)
and from July 12th to 15th (right panel). Gray lines are 10.7, 1:1 and 7:10 model-to-6bservation ratio lines. All values in
ppb.
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Canada - United States Transboundary PM Science Assessment
Table A.5 Performance statistics for hourly ozone at all stations over the domain from July 8th to 11th and
July 12th to 15th 1995. (see T&ble 2 for definitions)
Species n R2 c^' (Wous RMSE NME MB NMB curve fitting equation
Hourly 03 (left) 40437 0.39 396 488 273 21.4 48.8 11.0 31.6 mod = 0.56 obs + 26.35
Hourly 03 (right) 39913 0.50 745 849 561 23.8 40.3 9.9 21.1 mod = 0.66 obs + 25.91
Legend: * variance of model data, "variance of observation data, *"covariance
non-episodic conditions: ozone concentrations
above 80 ppb were observed on July 13th and 14th
at both stations. Both panels show that the ozone
levels simulated by AURAMS during the worst days
of the period (July 12th to 15th) are in better agree-
ment with the observations than for the four pre-
ceding days. AURAMS over-predicts ozone at the
beginning of the period but improves with time as
the observed episode becomes more intense. This
behaviour can also be seen in Figure A.8, which
presents two scatter plots of modelled vs.
observed ozone. The left panel covers the pre-
episode period from July 7th to 11111 while the right
panel covers the period from July 12th to the 15th,
the four days with the highest ozone concentra-
tions. The two scatter plots are for all stations in
the domain at all available hours. The slope of the
best-fit line increases from 0.56 to 0.66 for the July
7-11 period vs. the July 12-15 period while the R2
value between AURAMS-predicted and observed
hourly ozone improves from 0.39 to 0.50. The com-
plete Set of performance Statistics is provided in
Table A.5. For the episode period, observed hourly
ozone levels reach over 180 ppb and predicted
levels reach about 150 ppb.
Figure A.9 shows an image of the AURAMS
predicted ground-level ozone field for July 14th
1995 at 2100 UTC at the height of the episode with
the observations for that time superimposed as
colored circles at the measurement locations. In
this figure, matching colours indicate good agree-
ment with the measurements. There is generally
good agreement between the model and the
observations. Observed and modelled values are
similar in the peak areas and we see the same pat-
terns in the modelled field as in the observations,
This figure is representative of the level of agree-
ment between model and observations for the
afternoon and early evening period. Figures A.7
and A.9 lead us to conclude that AURAMS repro-
duces the afternoon and evening portion of the
diurnal cycle of ground-level ozone well but tends
to over-predict during the night and morning
hours.
Figures A. 10 and A. 11 show scatter plots com-
paring observed and predicted daily mass concen-
trations for PM2 5 and its three inorganic chemical
components for the eight-day period from July 8th
to the 15tfl, As noted above, the number of meas-
urements available for PM2 5 comparisons is con-
siderably less than that available for ozone,
despite the fact that additional measurements
Vzone
Figure A.9 - AURAMS simulated ground-level o^one for
2100 UTC (1700 |DT) on July 14th 1995. Observations
yalid.for this hour are-represented by the circles-
Values are in ppb.
124
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appendix
Model
45
Model
33
5 10 IS 20 25 30 35 40
Particulate Matter fine fraction (ug/m3)
6 fl 12 1S 18 21 24 27
Sulfate fine traction (ug/m3)
Model
2X1
Ammonium fine fraction (ug/m3)
Nitrate fine fraction (ug/m3)
Model
2.0
Figure A.10 - Scatterplots of daily (a) PM, 5 mass, (b) PM, 5 SOJ, (c) PM, 5 NHJ, and (d) PM, 5 NOs concentrations
at all available IMPROVE, GAViM and CAAMP stations over the AURAMS domain for all days from July 8th 00Z to July
16th 00Z, 1995. Units are |.ig/m3 at ambient conditions. The black line is a best-fit line and the gray lines are 2:1, 1:1
and 1:2 model-to-observation ratio lines.
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Canada - United States Transboundary PM Science Assessment
Ammonium fine fraction (ug/m3)
Nitrate fine fraction (ug/m3)
Mode
Particulate Matter fine fraction (ug/m3)
Model
10
Model
50
45
40
35
30
25
20
15
10
5
0
0
Model
16
5 10 15 20 25 30 35 40 45 50
Sulfate fine fraction (ug/m3) obs
Figure A. 11 - Same as Figure A. 10 but for Canadian NAPS-stations and pg/ffl3 at STP.
Table A.6 Performance statistics for PM2 5 mass, PM2 5 SOj, PM2 5 NH j, and PM2 5 NOj concentrations
at all available IMPROVE, GAViM and CAAMP stations over the AURAMS domain for all days
from July 8th 00Z to 16th 00Z 1995. (see Table A.2 for definitions)
Species
n
R2
^mod
ฎobs
^mod-obs
RMSE NME
MB
NMB
curve fitting equation
PM2 5 mass
66
0.26
70
94
42
9.1
38.5
-1.0
-5.8
mod - 0.44 obs + 8.74
PM2 5 SO4
32
0.60
65
10
20
9.1
110.4
6.8
108.4
mod = 1,97 obs + 0.66
pm25 nh4
1
-
-
-
-
-
-
-
-
-
PM2 5 NO3
32
0.01
0.12
0.10
-0.01
0.5
105
-0.2
-65.6
mod = -0.08 obs + 0 14
Legend: * variance of model data, "variance of observation data, "'covariance
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appendix
Table A.7 Performance statistics for PM2 5 mass, PM2 5 SOj, PM2 5 NHJ, and PM2 5 NOj concentrations
at all available Canadian NAPS stations over the AURAMS domain for all days from July 8th
00Z to 16th 00Z 1995. (see Table A.2 for definitions)
Species
n
R2
^mod
ฎobs
ฎmod-obs
RMSE
NME
MB
NMB
curve fitting equation
PMa 5 mass
42
0.19
80
141
46
11.4
41.8
-0.2
-0.9
mod = 0,33 obs + 13.17
PM2 5 SO4
51
0.02
62
33
6.9
9.2
85.2
2.1
31.2
mod = 0.21 obs + 7.28
PM2 5 nh4
51
0.24
2.7
3.6
1.5
1.8
59.5
-0.3
-13.1
mod = 0.42 obs + 0.91
PM2 5 NO3
39
0.01
9.2
0.02
0.03
3.4
1669
1.6
1622
mod = 1.80 obs + 1.53
Legend: * variance of model data, "variance of observation data, ""covariance
from the CAAMP network are available for this
period. Model performance is similar to the winter
case (cf. Figures A.5 and A.6), but in the summer
AURAMS appears overall to over-predict S04 and
under-predict N03, opposite behaviour to the win-
ter case. Again, predictions of total PM2 5 mass
are not strongly biased.
The performance statistics corresponding to
Figures A. 10 and A. 11 are provided in Tables A.6
and A.7. Although the agreement with NOj meas-
urements in the summer is poor, it should be
noted that the NOj measurements have a higher
degree of uncertainty than those for particulate
SO= and NHJ due to the volatility of particulate
NOj. NAPS dichotomous NO^data for 1995 in par-
ticular, are known to be biased low compare to
other NO3 sampling methods by as much as 50%
due to volatility problems (Brook and Dann, 1999),
which may account for some of the discrepancies
in Figure A. 1 Id.
Finally, Figure A. 12 compares a satellite visible
image taken at 2308 UTC on July 10th 1995 with the
AURAMS predicted PM2 5 concentration field at 15
m height at 2300 UTC. The zones highlighted on
the satellite image correspond to locations where
haze due to near-surface particles in suspension is
visible. Qualitatively, we can see that the model
reproduces the general patterns of the satellite
image. Comparison to earlier and subsequent
satellite images (not shown), display the same
kind of general agreement throughout the episode.
A2.4 Summary of AURAMS performance
evaluation
The evaluation presented above showed that
AURAMS is able to simulate the main features of
ozone and PM mass air concentrations under very
different meteorological conditions. Generally
AURAMS performed better for the winter case,
although the increased amount of observed data
for the winter case may introduce some bias.
During the summer case, AURAMS consistent-
ly over-predicted ozone concentrations in the
lower range while under-predicting the peak val-
ues, a behaviour that is consistent with other oxi-
dant models behavior during summer episodes
(e.g. Byun and Dennis, 1995; MSC, 1997).
Interestingly, AURAMS did not show the same ten-
dency for the winter season when all observed val-
ues are in the same 0 to 50 ppbv range. This differ-
ence could be due to a combined effect of
AURAMS spatial resolution (42 km) and a decrease
in the regional representativeness of the measure-
ment sites at night, during summertime events,
when the stability close to the surface is strong.
Further investigation is however needed to confirm
this hypothesis.
AURAMS is able to reproduce the PM mass
within a factor of two for both the winter and the
summer case considered, but over-predicts partic-
ulate SO= and under-predicts NOj and NHJ in the
summer case while exhibiting the opposite behav-
iour for the winter case. Based on the present
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Canada - United States Transboundary PM Science Assessment
comparisons with observations, AURAMS pro-
duces reasonable simulations of particulate SOj
and NHJ, but the level of agreement for particulate
NO3 is less satisfactory. As explained in the previ-
ous section, however, N03~ measurements also:
have a much higher degree of uncertainty, especial-
ly for periods as far back as 1995. However,
AURAMS's ability to simulate the concentrations of
the various inorganic PM components is also simi-
lar to what has been reported for other aerosol and
oxidant models (e.g. Mebust et al., 2003), including
the lower performance skill for particulate N03~.
Finally it should be kept in mind that the evalua-
tion of AURAMS was: focused on two relatively
short periods, therefore little to no averaging was
done when comparing with observations.
Figure A. 12 - Comparison of AURAMS KSS^J output
with satellite imagery. Top: Visible satellite image
valid at 2SOS UTC on July 10th 1995, Bottom: AURAMS
PM2:5 output in the lower levels valid at 2SQ0- UTC.
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The Subcommittee on Scientific Co-operation (Subcommittee 2), of the Canada-US Air Quality
Committee deals with activities of scientific and technical cooperation under Annex II of the Air
Quality Agreement (1991). The members of the Subcommittee are as follows:
CANADA
Keith Puckett, Environment Canada, Co-Chair
Richard Bennett, B.C. Ministry of Water, Land and Air Protection
Lawrence Cheng, Alberta Environment
Fred Conway, Environment Canada
Chris Daly, Nova Scotia Environment and Labour
Tom Dann, Environment Canada
Dennis Herod, Environment Canada
Harry Hirvonen, Canadian Forest Service
Michel Jean, Environment Canada
Dean Jeffries, Environment Canada
Richard Leduc, Ministere de l'environnement du Quebec
Ling Liu, Health Canada
Janet Mullins, Environment Canada
Carmelita Olivotto, Environment Canada
Neville Reid, Ontario Ministry of Environment
UNITED STATES
William Russo, USEPA, Co-Chair
Robbins Church, USEPA
Robin Dennis, USEPA
Robert Devlin, USEPA
Neil Frank, USEPA
Rick Haeuber, USEPA
Robert Kotchenruther, USEPA
Rich Poirot, Vermont Department of Environmental Conservation
Mark Scruggs, National Park Service
Mary Striegel, National Center for Preservation Technology and Training
Joe Tikvart, USEPA
Borys Tkacz, USDA Forest Service
Jeff West, USEPA
William Wilson, USEPA
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