Global Inventories
of carbonaceous aerosols
Tami C. Bond
University of Illinois at Urbana-Champaign

2 May 2005
IPCC Aerosol Meeting
Geneva, Switzerlandoutline
1. estimating emissions
a. particular challenges of carbonaceous aerosols
b. inventory procedure & brief resultsc. major uncertainties
2. a brief history of inventories
a. present dilemma
3. work on the future (from D. Streets)
not here (and needed):secondary anthropogenic aerosol biogenic aerosolBC/OC emission challenge harder than species with Emission estimation
bounded emissions (CO2, SO2)
 similar to process-dependent
species (NOx, CO) Model validation

 harder than well-mixed species

 Chemistry-optics

 harder than single species (CO2,CH4, even SO4=)

connection

1a. some challenges(CO2, CH4)
 similar to species with short
lifetimes (SO2/SO4=, CO)Variability in different
burning of the same fuelImage: NationalGeographic

1a. some challenges

Variability between similar sources
Emission rate (g/kg)

Response toregulation

5
dynamometer tests

4

regulations

3

example:example:dieseldiesel engines
engines2101970

1980

1990

2000

Buses in one city

From Yanowitz et al., 2000

From Faiz et al., 1996

1a. some challenges

Diesel engines are constrained to lean equivalence ratios because of the sootlimit—the point at which “excessive soot” begins to form [8]. This limit is apparent in theVariability of a single source

figure for values of φ greater than about 0.6 when engine speed is about 600 RPM. At
higher speeds, the acceptable φ is even lower, because the particles have less time tooxidize.
The valuefactorof EIabs atand
800 RPM,φ =0.6 wasgreater than 40 m2 kg-1.
emissionaerosol
type

depends on burning conditionsindustrial
industrialoil
oilboiler
boiler
4600-700 RPM
700-800 RPM
800-900 RPM

0.60.6

3

102
2

0.2
0.2
0.0
0.0
01
00
0.0

0.2

0.4

Equivalence
Ratio
ratio
Equivalence

0.6

0.8

turndown event

0.4
0.4

15

600-700 RPM
700-800 RPM
800-900 RPM

Fraction of observations
Fraction of observations

150.8
0.8

3

EFPM (g/kg)

2/kg)
AbsorptionEIabsemission(m 2/kg(mat 550nm )indirect-injection
dieselindirect-injectiondieselengine
engine
20

0.0

0.2

012
12
Absorption emission (m2/kgfuel)Absorption emission (m2/kg fuel)

0.4

0.6

0.8

Equivalence Ratio

Figure 7- 1. Emission of absorption (left) and mass (right) from Caterpillar engine.

1a. some challenges

33

global inventory procedure
emission from one technology= fuel use x PM emission factor x characteristics



activity levels (usually fuel)International Energy Agency, United Nations, etc.

emission factors (vary by fuel/technology) characteristics (also vary by fuel/technology)
BC fraction Removal by control devices
 Size (affects optical properties)
technology divisions

division into >100 fuel+technology categories
 regionally-distinct technology divisions
total emissions = sum over technologies
1b. estimation procedureglobal sources
Bond, Streets et al., JGR 109, D14203, doi:10.1029/2003JD003697
PowerIndustry
Transport: Road
Transport: Non-road
Residential: Other
Residential: Coal
Residential: BiofuelBlack carbon

North America
Central/South America
Europe, Former USSR
Asia, Middle East, Pacific
AfricaFraction "contained"

Total
0%

25%

50%

75%

100%% of global "contained"

Organic carbon

PowerNorth America

Industry
Transport: Road
Transport: Non-road

Central/South America

Residential: Other
Residential: Coal
Residential: BiofuelEurope, Former USSR
Asia, Middle East, Pacific
AfricaFraction "contained"
Total% of global "contained"
0%1b. estimation procedure

25%

50%

75%

100%

Estimating uncertainties
activityfactors
EF forfuel/sector

high case haslarger contributionof polluting activity

emissionfactors
1.
2.
3.
4.

combine c.i.
assuming
asymmetric
distribution&independence

combine confidence
intervals assuming
linear dependence& asymmetric
distribution

process differences?
assume lognormal
estimate expected value & c.i.
combine characteristics
assuming independence

1b. estimation procedure

sectoralemissionssectoralenergy data
each fuel/sector has
own uncertainty

total
emissionsasymmetric
distribution,
independence

uncertainties
 inventory contains full uncertainty propagation(activity estimates, emission factors, etc)

of course, there are many guesses

SectorContained combustion
Agri waste/residential
Anim waste/residential
Coal/industrial
Diesel/off-road
Coal/cokemaking
Coal/residential
Diesel/on-road
Diesel/residential
Gasoline/transport
Wood/charcoal prod
Wood/industrial
Wood/residential

N.America S/C America Europe Former USSR
Asia
BC OC BC OC BC OC BC OC BC OCAfricaBC OC

12122
12
122222222
1
122
12
111111122
12
1
12
112
112
1

Uncertainty > 25% of total “containedcombustion” emission estimate for region

1c. major uncertainties

22222221111122212
112
112
12
1122
112222221Uncertainty > 10%122
11

Open biomass burning

IssuesIssuesÆ
Æ Quantities
Quantities ofof vegetative
vegetative
mattermatter burnedburnedÆ
Æ Emission
Emission factors
factors variablevariablewithwith combustion
combustion conditions;conditions;notnot represented
represented

Image: CSIRO

1c. major uncertainties

Transport sector
 on-road

IssuesIssuesestimated fleet emission factor(fleet information hard to findfor many countries)
 superemitters difference between
dynamometer measurements &real world off-road mobile/industrialestimated from fraction of fuelused in various sectors
 country treatment of reporting isinconsistent

1c. major uncertainties

Image: www.nada.org

Small industry
Image: Beverly Anderson

Kathmandu:
Brick Kilns

Xi’an:
Coal-Fired Fast Food

IssuesIssues limited measurements
 emission factors/

Image: Anil Raut,
Clean Energy Nepal

1c. major uncertainties

characteristics
 types of industrial use willingness to be measured

Domestic biofuel

IssuesIssues fuel quantities

haven’t been wellestimated even by energysector
 not just a “developing”country issue (per-capita
wood use in U.S. 50% ofthat in India)
Image: Don O’Neal,HELPS Int’l

1c. major uncertainties

 emission factors

many sources; difficult toestimate average measurement of aerosol
type (BC/OC) mostuncertainDomestic biofuel (II)20.0

Field measurements higher thanlab measurements

EF (g_PM/kg_fuel)15.0(Christoph Roden, UIUC, work in progress)

10.0

5.0

average of lab measurements

0.5

Houck compendium, 388 tests
Fine speciation, 11 tests

Test15

Test14

Test13

Test12

Test11

Test10

Test9Test8

Test7

Test6

Test5

Test4

Test3

Test1

0.0

Mass & speciation informationfrom different sources

Fraction of data

0.4
0.3
0.2
0.1
00.1

1

10PM emissions (g/kg)

1c. major uncertainties

1001000

A brief history of global inventories
1983 Turco
1993 Penner
1996 Cooke & Wilson
1996 Liousse
1999 Cooke et al2001 Andreae & Merlet
2004 Bond & Streets

2. inventory historyorder-of-magnitude estimatebased on fuel use
fossil fuel + biofuel
biomass/biofuel
emissions different by development
levelcomprehensive tabulation of biomass
emission factorsemissions different by technology

A brief history of global inventories
black carbon

1983 Turco
1993 Pennerorganic carbon

2.6-22
6.6 FF, 6 BB
24 (ratios w/sulfur)
1996 Cooke & Wilson 8 FF,6 BB
1996 Liousse
5.6 BB
45 BB
1999 Cooke et al
5.1 FF
10 FF
2001 Andreae & Merlet
4.8 BB
36 BB
2004 Bond & Streets 3.0 FF, 5.0 BB/BF 2.4 FF, 31 BB/BF(4.3-22)(17-77)2. inventory history

Why the reduction in FF emissions?
Bond (2004) vs Cooke (1999)
Differences are easily explained.
Coal, power generation (difference 1.5 Tg/yr)

We rely on measured BC fractions (<1%)
instead of guesses (25%)
On-road diesel (difference 1 Tg/yr)

We use emission measurements and World Bank studies
instead of assuming “developing countries have 5x higheremissions” (15 g/kg average PM emission factor)
Domestic diesel (difference 0.25 Tg/yr; large in Europe)

We do not apply emission factors for internal
combustion engines to external-combustion boilers
2. inventory history

The present dilemma “corrections” reduced emission estimatesfrom 14 Tg/yr to 8 Tg/yr models typically need more BC to match
observations… not less!
 measurement techniques
may be uncertain…
 …but probably not enoughto explain discrepancy.

2a. inventory dilemmaForecasting BC and OC emissions
From Bond etal., JGR, 2004

3. future carbonaceousHow fast will control technology improve?

Electrostatic precipitator,
high collection efficiency

Cyclone, lowcollection efficiency

3. future carbonaceous

-shaped
Representing time trends with SS-shaped
technology penetration curve
7.00

1996 current emission factor (Bond/Streets)

Emission rate (g/kg)

6.00
5.00

Shape depends onlifetime, build rate, etc.

4.00
3.00

“Net”
performancein 2030

2.00“Ultimate”
performance

1.00
0.00
16

3. future carbonaceous

1116

2126

Time (years)

3136

41

4651

BC emission changes between 1996 & 2030A1B
Technology improvement overwhelms energy growth!
(Gg)
Energygrowth

14000

Technology
improvement

ResidentialIndustry
Power

12000

Transport
10000

Biomass Burning

8000

6000

4000

2000

01996

1996
Bond/Streets

3. future carbonaceous

Energy Growth

Improved CEF

Changed Tech Splits

Changed EFPM

2030

Net 2030A1B

General decline in all cases
Results suggest we are headed for a world
with stable or lower primary aerosol emissions
BC/anthro

BC bioburn

OC/anthro

OC/bioburn

3. future carbonaceous

Main message
 Estimating emissions of carbonaceous

aerosols has challenges that may go
beyond previous IPCC inventories.
 Technology & other practice are important.
 More cooperation and information fromlocal knowledge is needed.