Update on Asian Studies Related to Emissions and Modeling

Gregory R. CarmichaelDepartment of Chemical & Biochemical Engineering

Center for Global & Regional Environmental Research and theUniversity of Iowa

Topics Reported

• Recent advances in emissions estimates• Long-term sulfur deposition calculation• Update on model intercomparison study• Completed passive sampler pilot project

Sources of airborne pollution in Asia are many: home cooking, power generation, industry, traffic, and biomass burning

Methodology for Asian Emission Estimates

Methodology for Asian Emission Estimates

Energy Use

RAINS-AsiaModel

EmissionControls

Activitydata

Other human activities

Biomassburning

Natural emissions

Biogenic, Volcanic...Emission

factors, Regulations

Anthropogenic emissions

“Total” emissions

Organization of emissions dataOrganization of emissions data

National (23 countries)

Regional (94 regions)

Urban (22 cities)

Point (355 sources)

Historical:75-95(5-yr)

Current:90-00(1-yr)

Projections:95-30(5-yr)

TRACE-P Species for year 2000:

SO2, NOx, CO2, CO, CH4, NMVOC (19 classes), BC, OC, NH3

1° x 1° down to1 km x 1 km

Lat/long

Griddedemissions

The TRACE-P/Ace-Asia emission inventory shows the important sources of each type of

air pollutant in Asia

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

SO2 NOx CO2 CO CH4 NMVOC BC OC NH3

BiomassburningOther

Agriculture

PowergenerationTransportation

Residential

Industry

Seasonality of emissions of the different species has been studied for China

Seasonality by Species

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AugSept Oct

Nov Dec Jan

Feb

MarApril

MayJu

ne July

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tion

of A

nnua

l Em

issi

ons BC

CO

NMVOC

SO2

NOx

Seasonality by Species

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Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul

Frac

tion

of A

nnua

l Em

issi

ons

NH3CH4

Mainly combustion-related species

Mainly evaporation-related species

This is an example of TRACE-P SO2 emissions at 30 sec. resolution for the Pearl River Delta

Guangzhou

Macau/Zhuhai

Shenzhen

Hong Kong

Zhongshan

Boxed area ~ 150 km x 150 km

30 sec = ~ 0.7 km

Biomass burning treatment combines country survey data with AVHRR analysis to give long-term average or

“typical” burning amounts

Comparison of country surveys with various AVHRR fire-count adjustments reveals problem areas for further investigation

-5.0

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sigm

a

Xinjiang

Mongolia

Indonesia Vietnam

fire count > country surveys

fire count < country surveys

India

It remains difficult to make the linkbetween satellite observations

of fire and atmospheric emissions

The Importance of Fossil, Biofuels and Open Burning Varies by Region

Uncertainty analysis has revealed wide differencesin our knowledge of the emissions of particular

species in particular parts of Asia …

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China Japan Other EastAsia

SoutheastAsia

India OtherSouth Asia

Ships All Asia

(95%

Con

fiden

ce In

terv

al,

? )SO2

NOx

CO2

CO

CH4

VOC

BC

OC

NH3

Distribution of Percent Primary Non-carbonaceous PM2.5 Emissions --How to distinguish from dust?

Pink – DUST; Brown-Blue BC

R o n B r o w no b s e r v e d h i g h A O D

i n J a p a n S e a

1 4

1 2

1 0

8

6

4

2

0

El A

l &

Ca (u

g/m

3)

1 0 51 009 59 08 580J d a y ( UT C)

4 0 0

3 0 0

2 0 0

1 0 0

0

DUST_C

FORS (ug

/m

3)

t o t El Al 'DUS T- f i n e _ CFORS' 'DUS T- a l l _ CFORS ' t o t El Ca

T a k l a m a k a n

G o b i

L o g 1 0 ( D u s t )

A O D

O b s e r v e d A l a n d m o d e l d u s t

L i d a r E x t .O f R o n B r o w n= 0 . 2 / k m

R e c e n t E x p e r i m e n t s ( T r a c e - P , A c e - A s i a ) a r e P r o v i d i n g D a t a t o T e s t / I m p r o v e D u s t M o d e l i n g / P r o c e s s e s

E.Q.

N30

E120E90 Rishiri

OkinawaFukuoka

Beijing

Nagasaki& Fukue

E150Harbin

Amami

TsukubaSado

Shanghai

Hachijo

Ogasawara

Tarukawa

Qingdao

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

SO 2 emissions - RAINS-ASIA 1995 & FSU 1990

1 0

6 0 0 0 0 0

LPS (ton/yr)

-100%

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100%

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500%

1975 1980 1985 1990 1995 2000

Year

Em

issi

on %

cha

nge

P.R. China

India

Japan

Malaysia

Pakistan

Republic of Korea

Singapore

Sea lanes

SULFUR EMISSIONS IN ASIA ARE CHANGING,

REGION BY REGION, IN DIFFERENT WAYS

We have analyzed sulfur deposition in Asia over last 25 yrs

Uncertainty in the Source-Receptor Relationships

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Contribution (%)

Varia

bility

(%)

INDI -> LAOS

VOLC -> INDOKORN -> KORS

CHIN -> J APATHAI -> CAMB

INDI -> BANG

INDI -> MYAN

FSU -> MONGCHIN -> CAMB

INDI -> BHUT

INDI -> INDI

CHIN -> CAMB

Interannual Variability (10-yrs)

Effect of Interannual Meteorological Variability on Sulfur Deposition can be Much Larger than

Changes in Emissions!

China

-30%-20%-10%

0%10%20%30%

85 90 91 92 93 94 95 96 97 98 99

Year

Japan

-30%-20%-10%

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85 90 91 92 93 94 95 96 97 98 99

Year

Is there climate feedback link?

•Need to assess inter-model variability.•The MICS-ASIA Study: Model InterComparison of Long-Range Transport and Sulfur Deposition in East Asia

How Robust Are The Source-Receptor Relationships?

Many different models with important similarities and differences:Lagrangian, Eulerian, Hybrid, etc.

Participant(s) Organization Model name Model type

Main model focus

S.-B. Kim,T.-Y. Lee, K-Y. Ma 

Dept of Atmospheric Sciences, Yonsei University, Seoul (Korea)

YU-SADM (Yonsei Univ.-

Sulfur Acid Dep. Model)

3D Eulerian

Long-term period or episodic estimation of sulfur sources contributions

H. Hayami, Y. Ichikawa 

CRIEPI (Japan) CRIEPI trajectory model

Lagrangian

1-layer

Long-term evaluation  

H. Hayami, O. Hertel,Y. Ichikawa 

CRIEPI (Japan) and National Env. Research Institute (Denmark)

ACDEP ASIA Lagrangian

1-layer

Long-term evaluation

I. Uno,E.S. Jang 

Research Institute for Applied Mech., Kyushu Univ, Fukuoka (Japan)

RIAM version of RAMS on-line tracer model

3D Eulerian

Episodic and long-term simulation for chemical climate studies

Y. Ikeda, R. Yasuda, H. Nakaminami

Osaka Prefecture University (Japan)

OPU-Model (Osaka

Prefecture Univ.)

3D Eulerian

Long-term deposition

S.Y. Cho, G. Carmichael

CGRER, University of Iowa

STEM 3D Eulerian

Episodic and long-term studies

G. Calori, G. Carmichael

CGRER, University of Iowa

ATMOS-2 Lagrangian

multi-layer

Long-term conc. and depositions of sulfur in Asia. Source-receptor relationships.

M. Engardt Swedish Meteorological and Hydrological Institute

MATCH 3D Eulerian

Long-term concentrations and depositions of ozone and acidifying substances

Uncertainty in the Source-Receptor Relationships

Receptor 4 - Komae (Japan)

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100%

1 2 3 4 5 6 7 8

NW ASIA

SE ASIA

TAIWAN

S CHINA

C-E CHINA

NE CHINA

N & S KOREA

JAPAN

Inter-model VariabilityReceptor 12 - Yangyang (Korea)

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Receptor 16 - Nanjing (China)

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100%

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Passive Sampler Network – one way to increase coverage and participation

SO2 Results – Annual Averages

NH3 Results – Annual Averages

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Lin A

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ands

fonte

in

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1 0 0

NH3/S

O 2 ra

tio

0.01

0.1

1

10

100

0.01 0.1 1 10 100

SO2(ppb)

NH3(ppb)

NH3/SO2 Ratios – Annual Averages

O3 Results – Annual Averages

http://www.cgrer.uiowa.edu/people/carmichael/GURME/GURME.html

On-going Activities• Continued needs to improve emission estimates• Follow-on activities related to model inter-

comparison• Interest in expanding base-line measurements –

e.g., ABC study• Closer linkages between urban/regional/global

scales and health,air quality, climate communities• WMO-GURME

T he U n iversity o f Iow a , U S A

A ir Q u ality

ControlStrategiesControl

StrategiesEmissions

DistributionEmissions

DistributionAir Q uality

ModelAir Q uality

ModelPollutant

DistributionPollutant

Distribution

MeteorologyMeteorology

AtmosphericChemistry

AtmosphericChemistry

Air Q uality I mpacts• health and welf are• secondary impacts• population exposure

Air Q uality I mpacts• health and welf are• secondary impacts• population exposure

Air Q uality Goals• technical f easibility• economic issues• robustness

Air Q uality Goals• technical f easibility• economic issues• robustness

Climate : Air Quality

Analysis Framework

The University of Iowa, USA

Characterization of Urban SignalsScience Support to Policy

UnderstandingUnderstandingUnderstanding

Field Experiments

Field Field ExperimentsExperiments Long-term

MonitoringLongLong-- termtermMonitoringMonitoring

Satellites &Data Systems Satellites &Satellites &

Data Systems Data Systems

Regional and Global Simulations

Regional and Global Regional and Global SimulationsSimulations

PollutionPredictionPollutionPollution

PredictionPrediction

PollutionDetectionPollutionPollutionDetectionDetection

Enhanced Enhanced Quality Quality of Lifeof Life

InformedInformedPolicyPolicy

DecisionsDecisions

ProcessProcessStudiesStudies UnderstandingUnderstandingUnderstanding

Field Experiments

Field Field ExperimentsExperiments Long-term

MonitoringLongLong-- termtermMonitoringMonitoring

Satellites &Data Systems Satellites &Satellites &

Data Systems Data Systems

Regional and Global Simulations

Regional and Global Regional and Global SimulationsSimulations

PollutionPredictionPollutionPollution

PredictionPrediction

PollutionDetectionPollutionPollutionDetectionDetection

Enhanced Enhanced Quality Quality of Lifeof Life

InformedInformedPolicyPolicy

DecisionsDecisions

ProcessProcessStudiesStudies

46

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1915

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17

05

101520253035404550

5-6 6-7 7-8 8-9 9-10 10-12 12-15 15-20 20-30 30-40

Population in millions

No o

f grid

cel

ls

Urban Environments are Key Drivers of Change

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Percentage contribution to total sulfur deposition due to SO2

emissions from megacities and major urban centers in Asia,

averaged over the period of 1975-2000

Estimated Source-Receptor Relations for Nitrate

Variation in Aerosols in Asian Outflow has Strong Latitudinal Gradient

Propane data from Blake et al.

Biomass burning treatment combines country survey data with AVHRR analysis to give long-term

average or “typical” burning amounts

Original two-year daily fire count data for 1999-2000

Nitrate Deposition is of Growing Importance

% of Total Deposition as Nitrate

Speciation of NMVOC reveals great differencesamong countries with different levels of

economic developmentNMVOC Fractions

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Species

Frac

tion

of to

tal

China India

Laos Japan

SO2 concentrations - 11-20 January

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5

10

15

20

ppb

SO4 concentrations - 11-20 January

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5

10

15

20

ug/m

3

SO4 wet depositions - 11-20 January

1

10

100

1000

ug/m

2

Comparison with monitoring data for the 11-20 January period.

Hourly profile

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Layer 3Layer 2Layer 1

Weekly profile

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MON TUE WED THU FRI SAT SUN

Layer 3

Layer 2

Layer 1

… and converted them into appropriate profiles for China for the three different emission layers (both

January and July)

Transboundary Pollution Issues are of Growing Importance

Japan

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1975 1980 1985 1990 1995 2000

Year

Dep

ositi

on c

ontri

butio

ns

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Tota

l dep

. (G

g S

/yr)

JAPA

CHIN

VOLC

KORS

SEAL

Tot

S-Deposition

RAINS-Asia –Carmichael et al., (2001)

Transboundary Pollution Issues are of Growing Importance

Japan

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1975 1980 1985 1990 1995 2000

Year

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ositi

on c

ontri

butio

ns

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350

400

450

Tota

l dep

. (G

g S

/yr)

JAPA

CHIN

VOLC

KORS

SEAL

Tot

S-Deposition

RAINS-Asia –Carmichael et al., (2001)

The Emissions Vary Greatly by Region – Reflecting Many Social/Economic Factors

Hourly Profile

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HR1 HR5 HR9 HR13 HR17 HR21

Industry(point)

Resident/Agriculture/Industry(Area)Off-road vehicle

Powerplant

Urban local vehicles

Series6

Series7

Series8

Series9

Series10

Series11

Series12

Series13

Series14

Series15

Series16

We studied hourly profiles of emissions for different source types

…

Daily Profile

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MON TUE WED THU FRI SAT SUN

Area

PP

Off-road Veh

Urban Veh

High way

Ind

… also daily profiles …