Implications for GHG Emissions of Evolving
Patterns of Stove and Fuel Use in China's
Rural Households
Jonathan Sinton, Kirk Smith, and Rufus Edwards
University of California, Berkeley and Irvine
Presented at:
Mitigation of air pollution and climate change in China
October 17-19, 2004
Oslo, Norway
1
Topics
• Trends in fuel use in China’s rural
households
• Trends in stove design and usage patterns
• Methods of estimating global warming
potential from stove use
• Daily and seasonal variations
• Next steps
2
Trends in fuel use
3
Data sources limited
• National Bureau of Statistics
• Surveys by Ministry of Agriculture
• Disparate studies undertaken by various
research groups
• No detailed regular national surveys of
energy use in households, rural or urban.
4
Shares of energy use by type in rural households, 2002
Coal
LPG
Other oil
Electricity
Crop wastes
40%
60%
Wood
Coal gas & biogas
China
Shaanxi
Hubei
Zhejiang
0%
20%
80%
100%
share of household energy
Source: NBS, 2004.
5
…but different sources give different data.
Rural households,
shares of energy use
Coal
LPG
Other oil
Electricity
Crop wastes
Wood
Biogas
China
Shaanxi
MOA
(1998
data)
Hubei
Zhejiang
0%
20%
40%
60%
80%
100%
share of household energy
Coal
LPG
Other oil
Electricity
Crop wastes
Wood
Coal gas & biogas
China
NBS
(1999
data)
Shaanxi
Hubei
Zhejiang
0%
20%
40%
60%
share of household energy
80%
100%6
Data generated from review of
China's improved stoves programs
• Multiple research objectives:
–
–
–
–
Stove Programs
Stove Function
Indoor Air Quality
Health
• Surveys conducted 2002-2003, analysis ongoing.
• Participating organizations:
– The Institute for Global Health and the School of Public Health,
University of California, San Francisco and Berkeley
– China Centers for Disease Control
– Renmin University
– Tsinghua University
• Funding:
– Household Energy and Health Program of the Shell Foundation
– Fogarty International Center, Bethesda MD
7
Lake
Baikal
RUSSIA
KAZAKHSTAN
Hailar
Heilongjiang
Lake
Balkhash
Qiqihar
Harbin
MONGOLIA
Karamay
Changc hun
Kulja
Nei Mongol
Urumqi
Jilin
KYRGYZSTAN
Shenyang
Liaoning
Kashgar
NORTH
KOREA
Hebei
Xinjiang
Hohhot
Beijing
AFG.
Dalian
Yumen
Tianjin
PAK.
Shijiazhuang
Taiyuan
Yinc huan
Ningxia
Golmud
Xining
Shanxi
Jinan
Lanzhou
Shandong
Qinghai
Gansu
Shiqunhe
Xi'an
Henan
Xizang
Anhui
Nanjing
Shanghai
Hefei
Hubei
Wuhan
Sic huan
Chengdu
Yellow
Sea
Jiangsu
Zhengzhou
Shaanxi
Lhasa
SOUTH
KOREA
Yantai
Qingdao
Hangzhou
Zhejiang
Chongqing
Nanchang
NEPAL
East China
Sea
Changsha
Jiangxi
BHUTAN
Hunan
Guizhou
INDIA
Fuzhou
Guiyang
Fujian
Xiamen
BANGLADESH
Kunming
Guangxi
Yunnan
Hong Kong
(U.K.)
MYANMAR
National Capital
City
International Boundary
Provinc ial Boundary
Provinc e Name
Disputed Boundary
VIETNAM
LAOS
Bay of
Bengal
Haikou
Hainan
Hunan
South China
Sea
THAILAND
500 km
0
TAIWAN
Nanning
China
Xi'an
Guangdong
Guangzhou
PHILIPPINES
500 Miles
CAMBODIA
8
Village Biomass Storage
9
Mixed Fuels
10
Main cooking fuels varied significantly
by region in survey results.
100%
80%
Charcoal
Biogas
60%
Electricity
LPG
40%
Coal
Crop residues
20%
Wood
0%
Zhejiang
Hubei
Shaanxi
Total Sample
11
Space heating fuels varied substantially
as well, and revealed a surprising reliance
on charcoal.
100%
No space
heating/ missing
80%
LPG & kerosene
Electricity
60%
Charcoal
40%
Coal
20%
Crop residues
0%
Zhejiang
Hubei
Shaanxi
Total Sample
Wood
12
Stove design and usage
13
Dissemination of improved stoves in rural China and
number of rural households
300
250
China Statistical Yearbook, 2001
Frequency (MILLION)
200
CERS and CAREI 2000
150
MOE/DOE 1998
Qiu et al.,1996
100
Smith et al.,1993
Lu Y., 1993
50
0
1975
1980
1985
1990
1995
2000
2005
Year
Source: Edwards & Smith, 2002
improved stoves
rural households
14
Improved Biomass Stoves in China
More than 180 million introduced since 1983
15
Bellows in traditional biomass stove, Zhejiang
16
Unvented biomass stove, concrete construction, Hubei
17
Open fires for boiling water, used in addition to other stoves, Hubei
18
“Semi-improved” biomass stove, Shaanxi
19
Improved biomass stove, Shaanxi
20
Traditional and improved coal heating stoves, Shaanxi
21
Traditional and improved coal cook stoves, Shaanxi
22
Portable coal briquette stove, Shaanxi
23
Store with coal stoves, Shaanxi
24
Multi-function coal stove, unvented
25
Coal heating
and cooking stove
with chimney
installed for winter,
Shaanxi
26
Cooking and heating
stove without
chimney,
Shaanxi
Also used for kang
(heated platform bed)
27
Continuous-feeding household
biomass gasifier stove - $90
28
percentage of households using stove type
Rates of ownership of different type of
stoves show distinct regional patterns.
80%
Zhejiang
Hubei
Shaanxi
70%
60%
50%
40%
30%
20%
10%
0%
Traditional Improved Open fire
biomass biomass
Coal (w/
flue)
Coal (w/o
flue)
LPG
Biogas
Other
29
Efficiencies of stoves vary across region
and across type—implying variations
also in emissions characteristics.
Improved biomass stove
Traditional stove (no flue)
Traditional (w/ flue but w/o grate)
0.16
0.14
Efficiency
0.12
0.10
0.08
0.06
0.04
0.02
0.00
Zhejiang
Hubei
Shaanx i
30
Estimating global warming
potential of stove emissions
31
Why? Biomass fuel emissions
are globally significant.
•
•
•
•
2-5% of CH4 emissions
6-15% of CO emissions
8-25% of hydrocarbon emissions
4-8% of all human-generated global
warming from gases
• Significant contributor of black
carbon (BC) emissions
32
Global
Carbon
Cycle
What goes
on here?
33
Work to date and ongoing
• Measure 55 climate-warming and health-damaging
pollutant emissions from 28 fuel/stove combinations
popular in rural and urban China simultaneously with
efficiency and other performance parameters. Funded by
USEPA, began in 1993.
• Independent review of China’s National Improved Stoves
Program (NISP), which introduced over 180 million
improved stoves in rural areas by the late 1990s. Funded by
Shell Foundation, began in 1999.
• Results for China of the global Comparative Risk
Assessment on health impacts of indoor and outdoor air
pollution.
• Study on fuel/stove combinations in India.
34
Triple Carbon-Balance Analysis
of a combustion device
• Energy
• Health
• Global Warming
Co-benefits Possible with any two
35
Carbon-balance Analysis:
Combustion
• Follow the fuel carbon
C f  CCO2  PIC
• PIC =
CCH 4  CCO  CTNMHC  CTSP
PIC = products of incomplete combustion
TNMHC = total non-methane hydrocarbons
TSP = total suspended particulates
36
Triple Carbon Balance:
Energy
(Smith, 1994)
37
Triple Carbon Balance:
Health (concentrations
of pollutants)
38
Triple Carbon Balance:
Global Warming Potential
39
Calculation of global warming
commitments
• 20-year GWP Smith et al 2000
Molar basis (per carbon atom)
CO2 1.0
CH4 22.6
CO 4.5
TNMHC 12
• 20-year GWP IPCC 1990
per kg relative to CO2
NOx 150
CH4 22.6
• Black carbon?
40
Global
Warming
Commitment
Meal
Figure
3.4.
GWC
per Per
MJ
Delivered
Weighted by Stove Distribution in India
Average Stove Energy Efficiency Shown by Fuel
Grams Carbon as CO2
1
10
100
1000
Biogas-57.4%
LPG-53.6%
Kerosene-49.5%
Wood-18.3%
Crop Residues-11.6%
Dung-9.0%
Nonrenewable
Warmin g fro m all GH Gs emitted :
Renewable
C O2, C H 4, C O, N MH C , N 2O
41
GWC = Global Warming Commitment
Kyoto GWC of different household fuels in
China: CO2+CH4
400
GWC g C as CO2 per MJ delivered
350
Non-renewable
300
250
200
150
100
50
0
Improved brick
Improved brick
Improved brick
Wheat residues
Brushwood
Fuel wood
GWC CO2
Portable metal
stove
Portable metal
stove
Unprocessed coal Regular briquettes
GWC CH4
gas burner
gas burner
LPG
NG (m3)
non-renewable
42
Total GWC of different household fuels in
China: CO2+CH4+CO+TNMHC+NOx
400
Non-renewable
GWC g C as CO2 per MJ delivered
350
300
250
200
150
100
50
0
Improved brick
Improved brick
Improved brick
Wheat residues
Brushwood
Fuel wood
GWC CO2
GWC CH4
GWC CO
Portable metal
stove
Portable metal
stove
Unprocessed coal Regular briquettes
GWC NOx
GWC TNMHC
gas burner
gas burner
LPG
NG (m3)
non-renewable
43
Emissions of CO and PM
45
100.0000
40
Error bars represent different stove types
10.0000
30
1.0000
25
20
0.1000
15
10
0.0100
5
0
0.0010
wheat
maize
brush wood fuel wood unprocessed honeycomb regular
coal
briquettes briquettes
CO g C
kerosene
LPG
CG(m3)
NG(m3)
TSP
44
TSP g per MJ delivered
CO as g Carbon per MJ delivered
35
Seasonal patterns
45
Seasonal variabilithy in fuels &
stove use is significant
• Highly diverse fuel usage patterns in these regions in
China.
• In approx 250 homes in the IAP database:
– In Winter, 28 different fuel combinations used in the kitchens
– In Summer, 34 different fuel combinations in the kitchens.
– Multiple fuels used in the majority of the houses in the database
during both the winter and the summer.
– In houses that were measured in both seasons in Shaanxi there was
a shift in the fuel usage patterns between seasons.
46
Summer
Season 1 Summer
25
20
15
KITLIV
10
K
5
Note: biomass and
agricultural residues
feature strongly;
Kitchens higher than
living rooms
ts
uc l
od a
pr Grco
al LhPa
co ,c PG
s
re
l ,L
ag coa
s,
ue
re
id
ag
esal
l ro
ra ,c
tu es
ul r
g
al
ric a
caol
ag
acor l
,
ci gh oa
sw,
c
rdet s,
go re
,ao g
ig w ,a
l
tw wi g
oa
dt
,c
ig res
oo
w
,tw g
og ,a
dl ig
oo ,tw
w l og
d
oo
w
FUELTYPE
1 1
5 5
1 1
1 1
2 1
1 1
3 3
1 1
1 1
4 4
6 6
1 1
N=
47
L
0
Winter
Season 2 Winter
Note: Overall range
of levels higher
than in summer;
Livingrooms higher
than kitchens
65
60
55
50
45
40
35
30
25
20
15
10
5
0
KITLIV
K
5
8
3
3
1 1
6
7
6
8
1
2
1
2
5 6
1
1
L
g
,a
ig
P
,L
al
co
4 4
w
dt
oo
1
G
GG
aLlP P
so, l ,L
recoa
ag ,c
s
re
ue
ag
id
esal
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G
ras,
ture ,LP
ulg
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,
ag
ig
w
l
dt
la
cao
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w
cso,
r,e
gi g
t,wa
idg
owo
dwt
s
oo
re
w
w
N=
FUELTYPE
48
Improved stoves and indoor air
levels
• In the summer, improved stoves were associated with
significantly lower PM4 indoor concentrations for biomass
fuel combinations which would be burned in the same stove
(wood logs wood twigs and crop residues).
Wood logs, wood twigs and agricultural residues
T-Test Improved stove versus traditional
Variable
PM4 concentration
HOBO CO median
Method
Satterthwaite
Pooled
Variances
Unequal
Equal
DF
75.5(63,88)
11(6,7)
Difference(1-2)
115.94
1.1546
t Value
Pr > |t|
3.64 0.0005
3.59 0.0042
49
Three examples of different stove usage patterns
(CO levels in the kitchens)
a) Elevated levels during cooking events
50
b) Elevated levels during the night
51
c) continually elevated levels during the day and night
52
Next steps
53
Work in progress: Estimation of
seasonal variation in GWP
• Calculation and analysis ongoing.
• Expect to find variation in GWP among
regions, times of day, and seasons.
• How much would results have to vary to be
considered significant?
• For example, could we ignore seasonal
fluctuations of 25%? Would models have to
be revised to account for larger fluctuations?
54
Potential policy implications: Cobenefit calculations
• Current co-benefit calculations do not incorporate
seasonal changes in fuel use.
• Emissions from both living areas and kitchens must
be considered.
• Health and GWP impacts of interventions may differ
seasonally in independent ways.
• If shift in cooking fuels also results in increased
space heating using more-polluting solid fuels, then
desired reductions in GWP may not be realized.
• Plumes of pollution downwind of rural areas may
vary seasonally in both concentration and
composition.
55
Implications for research: Improve
characterization of rural fuels & stoves
• Institute regular household energy surveys
– Nationally representative
– Stocks of stoves in addition to other energyusing devices (NBS surveys already cover
electrical appliances)
– Ideally coordinate between MOA and NBS
• Requires high-level commitment,
coordination
56
More implications for research:
Gathering of data on seasonal variations
• Survey work should include monthly
observations for at least one full year
• Field monitoring of stoves under normal
operating conditions is key
• Surveys will need:
– Low-cost, monitoring and analytic methods
– Locally based survey teams
– Strong coordinator
57
Thank you
58