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Circulation and relationship between pollutant sources and atmospheric composition in the Himalayan region
G. CaloriARIANET, Milano and CGRER, U. of Iowa
D. Anfossi, P.Malguzzi, S. Trini CastelliCNR ISAC (Institute of atmospheric sciences and climate)
Mountains, witnesses of global changes. Research in the Himalaya and Karakoram: SHARE-Asia ProjectRome, 16-17 November 2005
Cover
Outline
The case of sulfur – evidences from RAINS-Asia project:
Project within SHARE-Asia / ABC
Outline
focus on Indian sub-continent
& Himalayan area
what happened ?
which sources ?
how year-by-year meteo affects ?
intra-annual phenomena ?
• modelled historical trends
• relationships with sources
• interannual variability
• seasonality
RAINS-Asia Project
RAINS-Asia Project
Sponsored by World Bank, ADB and others
Asian, American and European institutes
Main purpose: integrated assessement modelling (energy projections, control technologies & costs, atmospheric dispersion, impacts)
RAINS-Asia domain & regions
SO2 emi spatial distrib
SO2 emissions, spatial distribution(area and large point sources, year 1990)
6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0
- 1 0
0
1 0
2 0
3 0
4 0
5 0
Area sources(ton/yr)
18 to 500
500 to 1000
1000 to 5000
5000 to 10000
10000 to 15000
15000 to 30000
30000 to 100000
100000 to 833600
SO2 em issions - RAINS-ASIA 1995 & FSU 1990
1 0
6 0 0 0 0 0
LPS (ton/yr)
Streets D.G., Amann M., Bhatti N., Cofala J., Green C. (1995): Chapter 4: RAINS-Asia: An Assessment Model for Air Pollution in Asia, Phase-I Final Report.
Streets D.G., Tsai N.Y., Waldhoff S.T., Akimoto H., Oka K. (1999): Sulfur dioxide emission trends for Asian countries, 1985-1995. Workshop on the Transport of Air Pollutants in Asia, Interim Report, International Institute for Applied System Analysis, Laxenburg (Austria), July 22-23, 1999.
Ryaboshanko A.G., Brukhanov P.A., Gromov S.A., Proshina Y.V., Afinogenova O.G. (1996): Anthropogenic emissions of oxidized sulfur and nitrogen into the atmosphere of the former Soviet Union in 1985 and 1990. Report CM-89, Dept. of Meteorology, Stockholm University.
Andres R.J., Kasgnoc A.D. (1998): A time-averaged inventory of subaerial volcanic sulfur emissions, Journal of Geophysical Research, Vol. 103, pp. 25251-25261.
What happened?
What happened ?
Emission trends 1975-2000
Estimated Asia-wide past trends of SO2 annual emissions1975-2000
0
10000
20000
30000
40000
1975 1980 1985 1990 1995 2000
Year
Gg
S/y
r
ASIA East Asia
Southeast Asia Indian subcontinent
0
5000
10000
15000
20000
25000
30000
35000
1975 1980 1985 1990 1995 2000
Year
Gg
S/y
rP.R. China India
Japan * 10 Malaysia * 100
Rep. of Korea * 10 Kong Kong
Sea lanes
Carmichael G.R., Streets D.G., Calori G., Amann M., Jacobson M. Z., Hansen J., Ueda H. (2002) Changing trends in sulfur emissions in Asia: implications for acid deposition, air pollution, and climate. Environmental Science and Technology 36(22), 4707-4713.
Modelling framework
Modelling framework
• ATMOS-2 3D Lagrangian puff model with multiple layers• linear S chemistry• dry and wet deposition
• meteorology: NCEP re-analyses
• year-by-year emission inventory: diffuse and large point sources
• time frame: 1990-1998 year-by-year, 1975-2000 every 5th year
CGRER – Centre for Global and Regional Environmental Research (Carmichael et al.)
Monthly SOx fields
Calculated monthly S fields
Examples: years 1990 - 95(using year-specific emissions and meteorologies)
SO2 concentration SO4 concentration
Modelled historical trends (1)
Modelled historical trends (1)
7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0
Lon
-20
-10
0
10
20
30
40
Lat
Total sulfur depositions - Year 2000
1 0
2 0
5 0
1 0 0
2 0 0
5 0 0
1 0 0 0
1 5 0 0
2 0 0 0
2 5 0 0
3 0 0 0
4 0 0 0
m g(S) / m 2 / yr
7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0
L o n
- 2 0
- 1 0
0
1 0
2 0
3 0
4 0
Lat
-50
0
50
100
200
300
10000
%
Total S depositions: 1975-2000 % change
Em issions as of 7.3.2000
Total S deposition for year 2000Relative change of annual total S dep.
in 1975-2000 period
(both computed using year-specific emissions and meteorology)
Carmichael G.R., Streets D.G., Calori G., Amann M., Jacobson M. Z., Hansen J., Ueda H. (2002) Changing trends in sulfur emissions in Asia: implications for acid deposition, air pollution, and climate. Environmental Science and Technology 36(22), 4707-4713.
Modelled historical trends (2)
Modelled historical trends (2)
7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0
Lon
-20
-10
0
10
20
30
40
Lat
1975 - 80
7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0
L o n
- 2 0
- 1 0
0
1 0
2 0
3 0
4 0
Lat
1985 - 90
Relative changes of annual total S deposition due to changes in S-emissions only
-50
-25
0
25
50
75
100
10000
% change
7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0
Lon
-20
-10
0
10
20
30
40
Lat
1995 - 2000
(computed using estimated year-specific S-emissions but 1990 meteorology)
Which sources?
Which sources ?
Country-to-country S-R relationships
Country-to-country S-R relationships
Calculated annual total S deposition for selected countries and % contributions of the contributing source areas - 1975 - 2000
(using year-specific emissions and meteorologies)
Japan
0
50
100
150
200
250
300
350
400
450
1975 1980 1985 1990 1995 2000
Year
To
tal d
ep
osi
tion
(G
g S
/yr)
Republic of Korea
0
50
100
150
200
250
300
1975 1980 1985 1990 1995 2000
Year
To
tal d
ep
osi
tion
(G
g S
/yr)
Malaysia
0
20
40
60
80
100
120
1975 1980 1985 1990 1995 2000
YearT
ota
l de
po
sitio
n (
Gg
S/y
r)
Hong Kong, China
0
2
4
6
8
10
12
14
16
18
20
1975 1980 1985 1990 1995 2000
Year
Tot
al d
epos
ition
(Gg
S/y
r)
0
2000
4000
6000
8000
10000
12000
1975 1980
Volcanoes Sea lanes Taiwan
Hong Kong Malaysia Singapore
Indonesia P.R. Korea Rep. of Korea
Japan P.R. China
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1975 1980 1985 1990 1995 2000
Year
Con
trib
utio
n
0
5000
10000
15000
20000
25000
30000
35000
40000
Tot
al d
ep.
(Gg
S/y
r)
INDI - PUNJ
PAKI - PUNJ
INDI - WHIM
PAKI - NMWP
INDI - UTPRINDI - HARY
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1975 1980 1985 1990 1995 2000
Year
Con
trib
utio
n
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
Tot
al d
ep.
(Gg
S/y
r)
INDI - PUNJ
PAKI - PUNJ
INDI - UTPR
INDI - BIHA
INDI - BENG
NEPA
INDI - HARY
graph S-R rel for Indian subcontinent
Indian subcontinent: trends and S-R relationships
Calculated annual total S deposition for selected regions/countries and % contributions of the contributing source areas - 1975 - 2000
(using year-specific emissions and meteorologies)
India, “W Himalaya” Nepal
UttarPradesh
India, “E Himalaya”
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1975 1980 1985 1990 1995 2000
Year
Con
trib
utio
n
0
20000
40000
60000
80000
100000
120000
140000
160000T
otal
dep
. (G
g S
/yr)
INDI - UTPR
INDI - MAPR
INDI - BIHA INDI - HARYINDI - PUNJ
INDI - DELHINDI - RAJA
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1975 1980 1985 1990 1995 2000
Year
Con
trib
utio
n
0
10000
20000
30000
40000
50000
60000
70000
80000
Tot
al d
ep.
(Gg
S/y
r)
INDI - EHIM
INDI - UTPR
INDI - BIHA
INDI - BENG
BANG
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
1975 1980 1985 1990 1995 2000
Year
Con
trib
utio
n
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
Tot
al d
ep.
(Gg
S/y
r)
INDI - BENG
INDI - UTPR
INDI - BIHA
INDI - EHIM
BANG
Bhutan
maps of S-R rel for Indian subcontinent (1)
S-R relationships for Indian subcontinent
% of deposition from the contributing source areas(avg. 1985 - 1997 using year-specific emissions and meteorologies)
India, “W Himalaya”Nepal
Uttar Pradesh
maps of S-R rel for Indian subcontinent (2)
S-R relationships for Indian subcontinent
% of deposition from the contributing source areas(avg. 1985 - 1997 using year-specific emissions and meteorologies)
Bhutan India, “E Himalaya”
How year-by-year meteo affects?
How year-by-year meteorology affects ?
Interannual variability (1)
Interannual variability (1)
Year-by-year relative deviation of country total depositions (normalized to 1990 emissions levels)
Brunei
Calori G., Carmichael G.R., Street D., Thongboonchoo N., Guttikunda S.K. (2001) Interannual variability in sulfur deposition in Asia. J. of Global Environment Engineering 7, 1-6.
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 97
Vietnam
85 90 91 92 93 94 95 96 97
Burma
-30%
-20%
-10%
0%
10%
20%
30%
Indonesia
Laos
-30%
-20%
-10%
0%
10%
20%
30%
Malaysia Singapore
-30%
-20%
-10%
0%
10%
20%
30%
Thailand
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 97
Cambodia
85 90 91 92 93 94 95 96 97
Year
85 90 91 92 93 94 95 96 97
Year
85 90 91 92 93 94 95 96 97
Year
85 90 91 92 93 94 95 96 97
Year
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 97
Bangladesh
-30%
-20%
-10%
0%
10%
20%
30%
Bhutan
India
Nepal
-30%
-20%
-10%
0%
10%
20%
30%
Pakistan
Sri Lanka
85 90 91 92 93 94 95 96 97
Year
85 90 91 92 93 94 95 96 97
Year
85 90 91 92 93 94 95 96 97
Year
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 97
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 97
Philippines
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 9785 90 91 92 93 94 95 96 97
Year
China
Hong Kong
-30%
-20%
-10%
0%
10%
20%
30%
J apan
-30%
-20%
-10%
0%
10%
20%
30%
North Korea
South Korea
Mongolia
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 97
85 90 91 92 93 94 95 96 97
Year
85 90 91 92 93 94 95 96 97
Year
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 97
-30%
-20%
-10%0%
10%
20%
30%
85 90 91 92 93 94 95 96 97
Interannual variability (2)
Interannual variability (2)
Standard dev. of yearly total deposition(calculated with 1990 emission levels,
normalized respect to the average of 1985-97 values)
7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0- 2 0
- 1 0
0
1 0
2 0
3 0
4 0
Normalized sigma of yearly total S depositions (1990 emission levels)
0
3
6
9
12
15
18
21
24
27
30
%6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0 1 4 0 1 5 0 1 6 0
- 2 0
- 1 0
0
1 0
2 0
3 0
4 0
5 0
Normalized sigma of yearly total precipitations
02468101214161820222426283032343638401000
%
Standard dev. of yearly total precipitation(normalized with respect to the average of 1985-97 values)
Intra-annual phenomena?
Intra-annual phenomena ?
Seasonality: 1 - Nepal
Seasonality (1)
Nepal(constant – 1990 – emissions and year-specific meteorologies)
India -> Nepal
0
2
4
6
8
10
12
14
SPR SUM FAL WIN
Tota
l S d
ep (G
g)
Pakistan -> Nepal
0
0.2
0.4
0.6
0.8
1
1.2
SPR SUM FAL WIN
Tota
l S d
ep (G
g)
Nepal -> Nepal
0
0.2
0.4
0.6
0.8
1
1.2
1.4
SPR SUM FAL WIN
Tota
l S d
ep (G
g)
0
0.2
0.4
0.6
0.8
1
1.2
SPR SUM FAL WIN
90
91
92
93
94
95
96
97
Guttikunda S.K., Thongboonchoo N., Arndt R.L., Calori G., Carmichael G.R., Streets D.G. (2001) Sulfur deposition in Asia: seasonal behavior and contributions from various energy sectors. Water Air and Soil Pollution 131 (1/4), 383-406.
South Asian Monsoonal flow
Summer wind flow Winter wind flow
Source: Aguado, E and Burt, J.E., Understanding Weather and Climate, 3rd ed., Pearson Education, Inc., New Jersey, 2004.
South Asian Monsoonal flow
Seasonality: 2 - Bhutan
Seasonality (2)
Bhutan(constant – 1990 – emissions and year-specific meteorologies)
0
0.2
0.4
0.6
0.8
1
1.2
SPR SUM FAL WIN
90
91
92
93
94
95
96
97
India -> Bhutan
0
0.5
1
1.5
2
2.5
SPR SUM FAL WIN
Tota
l S d
ep (G
g)
Pakistan -> Bhutan
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
SPR SUM FAL WIN
Tota
l S d
ep (G
g)
Nepal -> Bhutan
00.010.020.030.040.050.060.070.08
SPR SUM FAL WIN
Tota
l S d
ep (G
g)
Proposal: contribution to SHARE-Asia / ABC
Contribution to SHARE-Asia / ABC
Purpose: investigate source-receptor relationships at hi res. (e.g. 20 km) & mountain-plain exchange mechanisms in different seasons
Project proposal:
Study of circulation and relationships between pollutant sources and atmospheric composition in the Himalayan area
CNR-ISAC/TO - Domenico Anfossi et al.
CNR-ISAC/BO - Piero Malguzzi et al.
ARIANET Milano - Giuseppe Calori et al.
Tools_ ISAC/TO
Modelling tools (1)
Chernobyl
TRAJETN forward/backward trajectories MILORD Lagrangian Particle Stochastic model
Tools_ ISAC/BO
Modelling tools (2)
BOLAM limited area meteorological model
• Primitive equations in sigma vertical coordinates with split-explicit time scheme
• Radiation: infrared and solar, interacting with clouds (Ritter & Geleyn and ECMWF RRTM - Morcrette)
• Vertical diffusion (surface layer and PBL parameterization) based on E-l closure of the turbulent stresses
• Surface thermal and water balance including soil and vegetation scheme (in coop. with the Hydrometeorological Institute of Russia – Pressman, 2002)
• Explicit microphysical scheme with 5 hydrometeors (cloud ice, cloud water, rain, snow, hail/graupel), modified from Schultz (1995) and Drofa (2001)
• Convective parameterization: Emanuel or Kain-Fritsch scheme
Western Pacific Typhoon “Flo”COMPARE Project (WMO-WGNE)(Nagata et al, J. Met. Soc. Japan, 2001)
BOLAM
Observed
Tools_ ARIANET
Modelling tools (3)
Isosurfaces at 5,10,20 ug/m3
FARM 3D CTM
Derived from STEM (Carmichael et al.)
SAPRC90/99 mechanismAerosols: Binkowsky modal module
PM10 concentrations computed with RAMS+FARM CTM
for RAINS-Italy Projects
The website is located at http://nas.cgrer.uiowa.edu/ABC/abc-90x60-current/pmenu.html. It provided real time forecasts for up to 4 days of relevant meteorological parameters, air-mass tracers indicating the source and age of a given air-mass and three dimensional concentration profiles of aerosols, radicals and other trace gases. The publicly available website was set up such that it was very user friendly and scientists were able to get 4-dimensional animated forecasts at the click of a mouse button.
STEM&CFORS forecast (ABC_APMEX Intensive, fall 2004)
STEM & CFORS 80 km forecasts (CGRER)
ABC APMEX Intensive (October / November 2004)
Courtesy of B. Adhikary and G. Carmichael
Post-Monsoon EXperiment
STEM BC emissions
Streets, D.G., Bond, T.C., Carmichael, G.R., Fernandes, S.D., Fu, Q., Klimont, H.Z., Nelson, S.M., Tsai, N.Y., Wang, M.Q., Woo, J.H., Yarber, K.F., An inventory of gaseous and primary aerosol emissions in Asia in the year 2000, J. Geophysical Research. 108 (D21), 8809, (2003), 1-23.
Courtesy of B. Adhikary and G. Carmichael
STEM forecasts
Sulfate concentration
STEM model forecasts
Source-related air mass tracers
Courtesy of B. Adhikary and G. Carmichael
Proposal: contribution to SHARE-Asia / ABC
Contribution to SHARE-Asia / ABC
CNR/ISAC-ARIANET project outline:
• focus on events revealed by (high altitude) monitoring network and model forecasts (e.g. STEM & CFORS 80 km)
• sources screening with back-trajectories
• 3D meteo and chemical-transport modelling of gases and aerosols
• analysis of source-receptor relationships and mechanisms
Collaboration with CGRER
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