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Air pollution and the energy ladder in asian cities
energy Vol. 19, No. 5, pp. 587-600, 1994 Copyright 0 1994 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0360-5442/94 $7.00 + 0.00
Pergamon
AIR POLLUTION AND THE ENERGY LADDER IN ASIAN CITIES
KIRK R. SMI-l-H+ , MICHAEL G. API-ES, MA YUQINGI, WATHANA
W~N~~EKIAR-ITIRAT?
AND ASI-IWINI KuLKARNR
t ENV, East-West Center, Honolulu, HI 96848 $ EED, Lawrence Berkeley Lab, Berkeley, CA 94720 5 TI’EESA, Tsinghua University, Beijing lOO-084 1 SRI, Chulalongkom University, Bangkok 5 11ERG, Systems Research Institute, 17A Gultekdi, Pune 411-037 (Received 10 June, 1993)
Abstract-Household fuel switching from lower to higher quality fuels, i.e. movement up the “energy ladder,” generally leads to substantially lower emissions of health-damaging pollutants. The extent to which human ex osuies are reduced is difficult to predict, however, because ijf inferactions due to penetration of outdoor poYlutants into homes and vice versa. In order to help answer the uestion of how much exposures might be reduced by movement up the ener ollution study covering particulates ladder, a three-tit (PMIO), nitrogen dioxide (N02), anCFcarbon monoxide (C& in and near households spanning the most important current ste s in each city’s energy ladder. Ste s examined were biomass-kerosene-gas in Pune, India; coal-gas in Beijing, C/&a; and charcoal-gas in Bangkok ‘l%ailand . In most instances, 24hour sampling was conducted and some personal monitoring was undertaken d&g cooking periods. Preliminary calculations of the exposure and health implications of fuel switching are presented.
I. HOUSEHOLD
FUELS AND AIR POLLUTION EXPOSURES
Since fuel combustion is generally the most important cause of health-damaging air pollution in cities, urban energy policy decisions related to fuels and fuel-using appliances, e.g., pricing, taxing, investment, and regulation, should consider the resulting impacts on air quality.’ This is true not only for fuels used by vehicles, power plants, factories and other significant outdoor air pollution combustion sources, but also for household fuels used in cooking and heating stoves. The importance of these small sources is due not only to their sometimes significant contribution to ambient concentrations, but also to their relatively high exposure effectiveness (EE), defined as the fraction of the emitted pollution from a source that actually makes its way into people’s breathing zones. Indeed, long-term failure to address household stoves was one of the principal factors that led to the infamous and deadly London smog of 1952.2 Because household sources emit directly into the places and at the times of human occupancy, they often have EEs that are tens or hundreds of times greater than those of large-scale outdoor sources. 3 Thus, even relatively small sources of emissions can have a big impact on exoosure& which, of course, are the more accurate indicators of potential health impacts. 4 Individual exposure is a function of the air pollutant concentration, e.g., parts-per-million (ppm), and the duration that someone experiences it. An example of the resulting unit, thus, is ppm-hours. Population exposure includes the number of people involved, with such units as ppm-person-hours. Trends in household fuel use can be conveniently discussed by reference to the conceptual framework called the “energy ladder.” For illustration, Fig. 1 shows the household energy ladder most typical of South Asia. (As discussed below, some of the ladder rungs are somewhat different in other parts of developing Asia.) As one moves up the ladder, the cleanliness, efficiency, and convenience of the fuels tend to increase, along with their costs.5 History has shown that people will generally move up the ladder when they have the opportunity and resources to do so. Long ago, all of humanity started at the center of the ladder, with wood. Roughly half the world has been able to move up to the modem fuels. The other half of the population still bums wood or has been forced down to + Author for correspondence 587
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KIRK R. SMITH et al
inferior biomass fuels, the diversion of which can have deleterious effects on local soil quality.
Development Fig. 1. Household energy ladder typical in South Asia. Although there have not been many studies of the air pollution emissions from fuel/stove combinations of importance in the developing world, the available data indicate that, in general, movement up the ladder results in fewer emissions of health-damaging pollutants.6 Changes in exoosures however, will depend also on the EE of the stove/house combination. For example, even with no change in fuel, replacing an un-flued (open) stove by one with a flue or chimney need not result in any less emission in order to substantially reduce exposure. This occurs by releasing much of the smoke, a mixture of gases, particles, and droplets, outside instead of indoors and thus decreasing the EE. Some of the smoke exiting through a flue, however, may also return inside as well as enter nearby houses, Changes in fuel (movement along the energy ladder) may also have impacts on the EE and local outdoor air quality as well as on the magnitude of emissions. Consequently, the net changes in exposures due to shifts in fuels, ventilation, behavior, or stoves are quite difficult to predict.
As part of the Asian Urban Energy and Air Pollution Network studies of household energy, air pollution monitoring was conducted in three cities at different levels of development and with somewhat different energy ladders. The purpose of these pilot studies was to assess the impact of the principal shifts in household fuel that were ongoing in each city: charcoal to bottled gas (LPG) in Bangkok; vented coal to three types of gas in Beijing; and biomass to kerosene to LPG in Pune. As much as possible, the measurements were oriented toward determinations of exposures rather than just ambient concentrations. See the three city reports for more details of these studies, including statistical analyses.7,8,g Following a common training course, monitoring teams in each city chose 60 households stratified by fuel type through a clustered random sampling technique from the same household lists used for the energy surveys. As much as possible, the same sampling and monitoring protocols were followed in each city. 10~1Many Beijing households contained
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space-heating stoves, however, unlike Bangkok and Beijing, the Pune household list was not entirely representative of the whole city, but focused more on the poor areas. Non-smoking households were selected and householders were asked to have guests refrain from smoking during the sampling periods. (For fuller discussions of the training program and protocols, see Ref. 10, and for the monitoring methods, equipment, and intra- and inter-country statistical analyses, see Ref. 11.) Table 1. Daily sampling protocol and total samples. Pollutant/ Location
Bangkok
Beijing
PM-10 indoor
Bach home. Total of 51.
Each home. Total of 58 samples.
Each home. Total of 61 samples.
PM-10 outdoor
One sampler for 2 homes near to and one for 1 home far from main road. Total of 34.
Clustered. One sampler for 3 homes. Total of 48 samples.
Each home. Total of 61 samples.
PM-10 personal
Three cooks per day. Total of 51 samples.
One cook per day. Total of 20 samples.
At separate session from indoor and outdoor. Total of 37 samples.
CO indoor
One home per day. Total of 17 samples.
One home per day before and after personal sampling. Total of 20 samples.
One home per day prior to personal sampling. Total of 30 samples.
CO outdoor
Three homes per day prior to personal sampling.
One home per day prior to personal sampling. Total of 20 samples.
One home per day prior to personal sampling. Total of 30 samples.
CO personal
One cook per day. Total of 17 samples.
One cook per day. Total of 20 samples.
One cook per day.
NO, indoor
All 3 homes for 10 clusters. Total of 30 samples.
One or two homes per day paired with outdoor. Total of 31 samples.
One, two or three homes per day paired with outdoor sampler. Total of 24 samples.
NO, outdoor
One site near and one site far from main road in 10 clusters. Total of 20 samples.
One or two homes per day paired with indoor. Total of 30 samples.
One, two or three homes per day paired with indoor sampler. Total of 24 samples.
SO, indoor
No measurements
Used in homes where personal monitoring was conducted. Total of 20 samples.
No measurements
So, outdoor
No measurements
One sample for a cluster of homes where personal monitoring was conducted. Total of 7 samples.
No measurements
As summarized in Table 1, four combustion-derived pollutants were monitored. Particulate matter below 10 t.trn (PMlO+ ) and carbon monoxide (CO) were measured indoors and outdoors over a 12-24 hour periods at the households, as well as with devices + PM-10 is the fraction of total suspended particulates (TSP)less than 10 microns in diameter. Because smaller particles penetrate deeper into the respiratory system, PM-10 is thought to be a better indicator of health hazard than TSP. Essentially all particulates derived from combustion are less than 10~ in size, while particulates derived from mechanical action, such as road dust, are larger.
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worn by the cook during one cooking session (personal monitoring). Nitrogen dioxide (NOJ was monitored by all teams both indoors and outdoors. (Because coal was being used, sulfur dioxide (So*) was monitored in some Chinese homes; the results are not reported here, but may be found in Refs. 8 and 11.) A short survey questionnaire was administered to each participating household. Due to resource constraints, equipment failure, logistics delays, and sample loss, the sample size is somewhat different for each city/pollutant/location combination, as detailed in Table 1. III. RESULTS The average concentrations and coefficients of variation (standard deviation divided by mean) of pollutants in each city for each fuel is shown in Tables 2a-c. For Pune, wood and agricultural residues are shown separately, and then combined together as ‘biomass” for comparisons with other fuels. In Beijing, the three types of gas are shown separately as well as together. In Bangkok, gas stove households and divided by the relative distance to the nearest major road as well as combined together. Table 2a. Pune energy ladder: measured mean concentrations (coefficients of variation). PM10 @g/m31
In
Fuel Ag-Resid
t
I Wood Biomass
I Kero
T
co(mgh3,
out
Cook
Cook
2800 (0.7)
2600 (0.2)
900+
5.0+
2000 (0.5)
920 (0.7)
1100 (0.5)
2100 (0.6)
3000 (0.6)
1100 (0.5)
480 (0.7)
340 (0.6)
530 (0.6)
250 (0.4)
250 (0.5)
420 (0.5)
Ill Ee’na%onal standard w=abov Bold = more than we times the national standard
Table 2b. Beijing energy ladder: measured mean concentrations (coefficients of variation).
T
PM10 (Clg/m3)
I
c0bgh3 Kitch
Jn
Nq out
Coal (vented)
550 (0.4)
f!k
Gas (a+b+c)
400 (0.5)
2.0 (1.2)
LPG
370 (0.6)
1.9 (1.0)
Coal Gas
420 (0.5)
li!iaaA Natural Gas
410 (0.6)
2.4 (1.2)
440 (0.6) 440 (0.4)
1600
II (E)
=a 0ZFE ional ndard lold = more than three times the national standard
(E)
h/m3)
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Air pollution and the energy ladder
Table 2c. Bangkok energy ladder: measured mean concentration (coefficients of variation). Fuel
PM10
@p/m31
r
CO Wg/m3,
I
Cook
(E, (“0:;) (FG, 1.6 (0.2)
1.6 (0.2)
;old = more than three times the national standard.
For comparison, Table 3 lists the relevant pollution standards of the three nations as well as those of the United States. The closest approximation to international standards, the World Health Organization (WHO) recommendations, are also listed. Since there are few indoor standards for households, ambient standards are shown. One might argue, however, that indoor standards should be more restrictive since they are more closely tied to exposure and more directly affect some of the most vulnerable members of the community, i.e. the very sick, old, and young who may not spend much time outdoors. Table 3. Ambient air pollution standards.
Nation
India’
TSP - Total Suspended Particulates @g/m3) Bh/D: 500/360; 200/ 140; loo/70
Carbon Monoxide (w/n+) 8h: 5; 2; 1
Nitrogen Dioxide @g/m3) Bh/D: 120/w; 80/60; 30/20
China%
D: (TSP/IP) 500/250; 300/150; 150/50
D: 6; 4; 4
A: 150; 100; 50
Thailand
A: 100 D: 330
8h: 20; lh: 50
lh: 320
USA
(PM-lo) A: 50 D: 150
8h: 10 lh: 40
A:
WHO (recommendations)
A: 40-60 D: loo-150
8h: 10 lh: 40
A: 50 D: 150
100
h 8 hours; lh=l hou @=mhalable particula , less than 15pm in ey: A-annual; D=dail) diameter-PMlO. + industrial and mixed use; residential, cultural, or rural; sensitive areas, e.g., national parks, tourists resorts, and national monuments. * Industrial districts and traffic centers; urban-residential, cultural, or rural; historical monuments, natural conservation, or tourist resorts. =
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KIRK R. SMITH
et al
Unfortunately, neither India nor Thailand have set standards for respirable particulates. Based on the experience of setting those standards in China and the United States, such standards would likely specify concentrations about half those shown for TSP. In their absence, however, comparisons here are made with the TSP standards. In Tables 2a-c all the means except the results of personal sampling of cooks were compared to the relevant national standard with the longest averaging time. Personal sampling values were compared to those standards with the shortest averaging time. In some cases, there was only one standard (see Table 3). As can be seen, many of the means are well above both the local standards and WHO recommended levels. The mean concentrations in Tables 2a-c shown in bold are more than three times higher than the most relevant national standard in each country.+ If the WHO levels were used for comparison, there would be little change for PMIO, since WHO levels are about as strict as these national standards. India and China, however, have relatively strict CO standards. Thus, comparison by WHO levels would essentially eliminate all the bold markings on CO means (i.e. more than 3 times larger) except in the bedroom of coal-burning homes in Beijing. Table 4 compares the outdoor measurements reported here to those reported by national and/or city ambient monitoring networks. PM10 levels measured outdoors near Bangkok homes are substantially higher than TSP levels determined by ambient stations in residential areas, particularly keeping in mind that PM10 levels are generally about half those for TSP. (In Bangkok, for example, they were reported to be 60%.)‘2 PM10 levels near Beijing houses definitely seem to be higher than indicated by the ambient measurements. For Pune, city-wide ambient values clearly considerably underestimate the concentrations near houses. Carbon monoxide levels measured in this study also seem to be somewhat higher than reported city-wide values. There are few data with which to compare, but our NO, levels do not seem to be much different from those reported from ambient stations. Table 4. Reported ambient concentrations compared to outdoor values measured in this study. All concentrations shown in pg/m 3. Since no city reports PMTO,TSP concentrations are shown.22-25 City
PMlO-S 250-1000’
TSP-R
co-s
NO,-S
NO,-R
CO-R
160-310%
15-50
lo-80
1100-2300
__
Beijing
410-550
200-500t
42-80
50
1500-11000
3400
Bangkok
280-450
100-2005
32
25
1600-3800
1000 (residential areas)
Key:
S = range of the mean outdoor concentrations determined in this study. R = ap roximate range of daily means reported in literature. + 2600 pg/m YYaround the three houses burning agricultural residues. $ Adjusted for season, i.e., instead of annual means, ambient levels were taken for the same month as the sampling was done in this study (Nov.-Dec.). 5 200 to 700 pg/m3
at street level.
As seen in Table 5, the indoor PM10 levels in Beijing are similar to or somewhat smaller than particulate concentrations measured by other studies in Chinese cities. The PM10 levels in the biomass-using homes of Pune are similar to those measured in other Indian homes using biomass.
+ Man standards are now set in statistical terms, e.g., that no more than 2% of daily means over a year should exceedr a certain level. For assessing equity among groups, some measure of the number of households above the standard would be relevant. For purposes of deterring potential health effects, however, mean population exposures are often more useful.
Air pollution
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ladder
Table 5. Urban indoor particulate concentrations in Asia. Location hdia Ahmedabad
Ahmedabad
Bombay
Period
Sample Size
cooking
32
1800 (1.1) Wood Charcoal Coal “Modem”
1600 (1.2) 550 (1.0) 2500 (0.9) 90 (1.6)
(Outside concent. about 500)
20 20 20 20 20
Wood Coal Kerosene
2700 (0.7) 1400 (0.7) 1100 (0.4) 500 (0.6) 490 (0.3)
24h living room
2 houses 12x each
CO0killg
Shanghai 15
Baodin Thailand Bangkok
Concentration (COV)
22 10 14 25
,!ixlla
Wuhan
Fuel
12
Kerosene
140 (0.4) 73 (0.4) (PM3.5)
Coal Piped Gas
1030-k; 850-b 510-k; 490-b
Coal Gas
290-k; 160-b 200-k; 150-b (PM3.5)
Coal
1500-k; 500-b 260-k; 260-b
Charcoal/
210 (PMlO) 490 (TSP)
Reference
Patel, et al 198426
Raiyani, et al 199327
GEMS, 198428
Smith, et al, 199329
Kungskulniti, et a130
Table 6 shows the results from several Asian indoor NO, studies. As might be expected, our measured 24-hour values in Pune are substantially lower than found in the cooking-period studies done in India. The Bangkok values are close to those reported in Hong Kong. Our Beijing findings seem to be substantially less than reported in Shanghai and Wuhan, but quite similar to the data taken in Nanjing. Unfortunately, publications of results often do not contain critical information, such as averaging time, that would make comparisons more reliable.
KIRK R. SMITH et al
594
Table 6. Urban indoor NO, concentrations Lma lion llxibl Ahmedabad
Ahmedabad
Bombay
Hong Kong
Period
cooking
Sample Size 32 22 10 14 25
Fuel
in Asia.
concen
Wood Charcoal Coal “Modern”
140 (2.3) 310 (1.3) 75 (0.5) 170 (1.0) 420 (0.9)
Patel, et al 1984z6
350 340 165 180 180
Raiyani, et al 199327
(0.6) (0.7) (0.5) (0.8) (0.9)
20 20 20 20 20
Wood Coal Kerosene
7-d kitchen
17
LPG & Kerosene
living mom
16
p, 24-h
319 mothers
Kerosene, LPG Piped Gas
39 32
362 children
Kerosene, LPG Piped Gas
37 37
Coal Piped Gas
260 50
cooking
china Shanghai
Reference
VW
Mahajan et al, 199031
97 (0.4)
62 (0.4)
Wuhan
30
Coal Gas
155 100
Nanjing
44
Coal Natural Gas
60-70 30-40
Thailand Bangkok
73
Charcoal LPG
30
Koo, et al, 199@2
Smith, et alI 199329
I
I Kungskulniti, et a130
IV. ENERGY LADDER The concentrations listed in Table 2c for Bangkok show some trends but no statistically significant differences according to fuel type, charcoal and gas. There does, however, seem to be an effect of distance from a main road for PM10 and CO. NO, values are remarkably similar in all locations. Data from the other two cities do show differences along the energy ladder, however. Shown for illustration in Fig. 2 are comparisons among fuels for both indoor and outdoor PM10 concentrations in Pune. Note the wfder confidence intervals (more variability) for the biomass households. For intercity comparisons along the energy ladder, the simplest approach is to accept gas as the control, i.e. that the concentrations in gas-using households are the best that can be expected in these cities (gas and charcoal together in Bangkok). If one also assumes that all the difference in concentrations is due to the difference in household fuels, it is possible to construct a concentration energy ladder across the three cities as shown in Fig. 3 for PM10
Air pollution
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ladder
and NO,.+ Note that net concentrations of both pollutants decline with movement up the energy ladder, although in different patterns. PM10 drops substantially between biomass and fossil fuels, while NO, does not drop so precipitously until moving from kerosene to coal. It may seem anomalous that Chinese coal is found to be cleaner than Indian kerosene. This is due to three factors: unlike kerosene stoves in Pune, most of the Chinese coal stoves were vented outdoors; the household coal used in Beijing is cleaned to some degree; simple Indian kerosene wick stoves have rather high emission factors.13
3.5 -
---n--l
Outdoor
i ‘0 a . S 3- _-__--__ = s”
,
I
-----__-___-__--__-
lridoor
-
2.5 -
-------8
LPG
Kerosene
Biomass
LPG
Kerosene
Biomass
Fuel Type
Fig. 2. Mean, median, and variation of indoor and outdoor PM10 measurements in Pune.
3000
-
2500
.!$ 2000 I! E 0’ g 1500 0 z $
1000
500
0,
I
AgResidues
Wood
Kerosene
Coal (vented)
Charcoal/LPG (by definition)
Fig. 3. Indoor 24-hour concentrations of PM10 and NO, along energy ladder across three cities. ’ This is done by subtracting the as value from each of the other values in each city before combining the cities together on one ladder in Figure P. The best single indicator would seem to be 24-hour inside measurements, which are used here. Unfortunately, the set of 24hour inside measurements for CO is incomplete.
KIRK R. SMITH et al
596
In reality, of course, indoor concentrations are also affected by local outdoor levels and, importantly, vice versa. Thus, the indoor and outdoor measurements at any one house will be affected by what the neighbors are doing, the density and arrangement of local housing, and the distance and strength of outdoor combustion sources. Focus on PMlO, however, should minimize the influence of household and street dust, which generally has larger diameters. To understand in detail how these factors affect exposures would require datagathering and model-building exercises far beyond what has been possible here. A simple model, however, can give some insights. To bracket the range of possible interactions between indoor and outdoor concentrations, we present estimates representing two assumptions: first that none of the local outdoor concentration is due to exfiltration from the inside (conservative model) and; second, that all of the local outdoor pollution above the outdoor levels outside gas-using houses comes from the inside (feedback model). Neither model considers the influence of household emissions from other neighborhoods. The two models determine daily exposure (E) in units of mg-h/m3 as follows: Econs= ti + [‘i - (c, + ‘11
(1)
is a conservative estimate and E feed= Q *
[ci-(cb
*p)l
is a result with feedback, where Ci = indoor concentration (mg/m3); C, local outdoor concentration; ti = time spent indoors (h/d); C, = estimated background outdoor concentration; P = penetration rate (the fraction of outdoor pollution coming indoors). For C, we use the mean outdoor concentration near homes with the cleanest gas fuel in each city. P depends on the pollutant and location, as indicated in Tables 7a,b. These represent guesses based on the type of housing in each city.‘%+ Table 7a. Estimated daily exposures from cooking fuel along energy ladder in Pune (P = 0.9 for PMlO; 0.95 for NO,).
WHO Recommendation
I
0.56
0.7
I
Table 7b. Estimated daily exposures from household fuel use along the energy ladder in Beijing (P = 0.7 for PMlO; 0.9 for NO,; 1.0 for CO). Fuel Coal (vented) Gas Chinese Standard /
WHO Recommendation
PM10 (mg-h/m3)
NO, (mg-h/m31
CO (mg-h/m3)
2.3 - 3.5
0.31 - 0.51
310 - 430
1.4
0.15
60
0.7/
0.7/
5U 140
0.56
0.7
+ We assume that Beijinghousin has a P for Ph410 similar to that measured in the U.S.A.,0.7 (Ref.14). To take intoaccount the much more openB ousing of Pune, we choose P=O.9. The effectiveP for gases is higher that for
particles depending on reactivity. See Tables 7a,b.
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Air pollution and the energy ladder
Tables 7a and b summarize the resulting estimates for the exposure from household fuels experienced by a person spending 14 hours at home per day in Pune and Beijing. If time/place data are known, i.e. how long people stay in each microenvironment during the day, more accurate exposure estimates can be made. Also shown are the 14-h exposureequivalents of the relevant national standards and WHO recommendations. Note that Pune LPG households easily meet the standards both for PM10 (TSP) and NO,. Neither biomass nor kerosene households meet the standards for PMlO, although NO, exposures lie within the, respectively, WHO and Indian levels. The Pune results using the conservative model are summarized in Fig. 4 where the vertical axis shows the ratio of the estimated exposures to the exposure-equivalents implied by the Indian standards. Note that a shift from biomass to kerosene brings Nor, but not PMlO, within the standards. A further shift to LPG is required to meet the PM10 standard. ,100
100
10 0 ‘E B
PM10 Ratio to Standard
I
-
NOZ Ratio to Standard
,l
1
0.1
.lO
Biomass
Kerosene
LPG
,O.l
Fig. 4. Estimated ratio of PM10 and NO, exposures to national standards along energy ladder in Pune. In Beijing (Table 7b), again only PM10 exposure-equivalents are consistently exceeded. Comparison with the standards shows an exceedence for CO only in coal-using households. The relatively high PM10 exposures for Beijing gas-using houses may indicate that a higher penetration rate (P) should be used in the equations above.
Coal
0
PM10 Ratio to Standarc
m
NO2 Ratio to Standard
m
CO Ratio to Standard
Gas
Fig. 5. Estimated ratio of PMlO, NO,, and CO exposures to national standards along energy ladder in Beijing.
598
KIRK R. SMITH et al
Fig. 5 summarizes the Beijing results for the conservative model in terms of the ratios to exposureequivalents of the Chinese standards. Note that although there is a significant improvement when moving from coal to gas, PM10 and CO exposures in gas-using households still remain above the standards. The NO, and CO exposures found in the households of these cities lie just (NO,) or substantially below (CO) the levels thought by most authorities to produce meaningful health effects.15 For PMlO, the situation is quite different because of the large exposures implied by the measured indoor concentrations. A number of recent analyses,16J7J* have been able to quantify the health response to increased concentrations at a few hundred pg/m3, which is lower than found in Beijing and much lower than in Pune. These and earlier studies have found increases of a few percent (l-7%) in daily mortality with each increase of 100 pg/m3 in daily particulate levels. I9 Ref. 19 found an increase in childhood acute respiratory disease of 1% per 1 pg/m3 of fine particulate matter, which would imply a lo-fold increase in some Pune households. It is unclear, however, how the exposures reflected by these outdoor ambient measurements in the United States and United Kingdom are related to the indoor The temporal patterns, size distributions, and chemical exposures determined here. compositions are also likely to be different. In the lack of other information, it is instructive to assume that they can be considered similar, i.e. the 100 lrg/m3 for a day used as a benchmark in these epidemiological studies done in developed countries is taken to be roughly equal to 2.4 mgh/m3d measured in our study of Asian households. Taking 4% increase in daily mortality per 2.4 mg-h/m3-d, implies that a community in Pune could reduce its daily mortality 2030% by switching from biomass to kerosene; or by 25-35% through going all the way to LPG. In Beijing, a switch to gas in coal-using households would apparently reduce daily mortality by 3-5%. In addition, this refers to the situation where only one community in the city switches. A major city-wide shift away from coal as a household fuel would presumably lower outdoor levels and their penetration indoors even further, thus increasing the health benefit substantially. It is not clear how well daily mortality measures the air pollution impact from chronic obstructive disease and lung cancer, which take many years to develop.20,t In addition, nonfatal illness from these illnesses as well as other important conditions that have air pollution as a risk factor, such as acute respiratory disease and adverse pregnancy outcomes, are not directly captured in daily mortality surveys. Much more so than in developed countries, these latter two conditions also lead to infant death, another potentially important impact from indoor air pollution.21
v. CONCLUSION There are still a number of factors that would need to be explored before detailed exposure assessments could be done for these Asian urban households. Sorting out the details of the relative influence of indoor and outdoor levels on total exposure would probably require 24-hour personal sampling in combination with the kind of microenvironment sampling done here. More attention would also be needed to the fuel use of the neighborhood, since the improvement for one house alone switching to clean fuel may not be great if no one else nearby joins in, i.e. neighborhood outdoor levels may remain high. The measurements taken during this study have allowed comparisons of air pollution concentrations and estimated exposures at different stages of the energy ladder between and within three cities at substantially different economic levels. It has shown that household fuel choice seems to have the most impact on air pollution exposures at the lowest level of development (Pune), intermediate at middle stages even with use of coal (Beijing), and least in the more economically advanced developing country, where fuel choice seems to have little or no impact (Bangkok). Finally, the results in each city would seem to indicate that true human exposures may be substantially higher than indicated by ambient monitoring stations. We are thankful for funding from the International Development Research Centre, Ottawa, Aknow wand the support and advice of its staff, D. Brooks and S. T ler. In addition, we thank J. Sathaye and G. Lu for help at critical points and M. Kollander and R. Clickner of the e SEPA for their roles in training the country teams. The country teams also benefitted from the advice of S. Edgerton, A. Ellegard, C. Huang, V. Joshi, L. Koo, N.
’ In China, lung cancer risk is strongly associated with indoor exposure from coal-fired stoves. See Ref. 20.
Air pollution
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599
Kungskulniti,R.P. Neupane, C.V. Raiyani, J. Ramakrishna, R. Song, S. Soderholm, J. Usin er, P.Young, and D. Zalle. We greatly appreciate the leadership and su port of J.G. Krishnaya, D. Qiu, and A. # ongsapich, as well as the patience and good will of the householders WI3 whom we worked.
REFERENCES 1. D.B. Brooks and H. Krugman, Energy Policy 18,838 (1990). 2. P. Brimblecombe, The Bio Smoke: A Historw of Air Pollution in London Stnce Medieval Timgg, Methuen, London (1987). 3. K.R. Smith, Ann. Rev. of Energy & Environ. 18,526 (in press 1993). 4. P.J. Lioy, Environ. Sci. and Tech. 24(7), 938 (1990). 5. Office of Technology Assessment, Fueling Development: Energy Technologiesfor Developing Countries, OTA-E-516, U.S. Govt. Printing Off. Washington, D.C. (1992). 6. K.R. Smith, Biomass Fuels. Air Pollution. and Health: A Global Review, Plenum, New York (1987). 7. A. Kulkami, J. Deshpande, and J.G. Krishnaya, “Modernization and the Search for Air Quality,” Systems Research Institute, Pune (1991). 8. Y. Ma and Q. Wang, “Indoor Air Pollution Survey in Beijing,” Urban Energy Consumption and Air Pollution Network (Asia), Tsinghua University, Institute for Techno-Economic and Energy Systems Analysis, Beijing (1991). 9. W. Wongsekiarttirat, “Indoor Air Pollution in Thailand,” Urban Energy Consumption and Air Pollution Network (Asia), Chulalongkom University Social Research Institute, Bangkok (1991). 10. K.R. Smith and M.G. Apte, “Urban Household Fuels and Air Pollution Exposures in Asia: Methods of Study,” Report to the International Development Research Centre, Ottawa, ENV, East-West Center, Honolulu (1992). 11. K.R. Smith, M.G. Apte, M. Yuqing, W. Wongsekiarttirat, and A. Kulkami, “Urban Air Pollution Exposures and the Asian Energy Ladder,” (in press). 12. Office of the National Environment Board, “Air and Noise Pollution in Thailand,” ##0703-33, ONEB, Bangkok (1989). 13. V. Joshi, “Evaluation of Performance of Cookstoves with Regard to Thermal Efficiency and Emissions,” Tata Energy Research Institute, Delhi (1987). 14. G.W. Traynor, M.G. Apte, B.V. Smith, and W.K. Porter, “Macromodel for Assessing Residential Concentrations of Combustion-Generated Pollutants,” LBL-28450, Lawrence Berkeley Lab, Univ. of Calif., Berkeley (1990). 15. J.M. Samet and J.D. Spengler, Indoor Air Pollution: A Health Persaective, Johns Hopkins University Press, Baltimore (1991). 16. J. Schwartz, Environ. Res. 56, 294 (1991). 17. J. Schwartz and D.W. Dockery, Am. Rev. Resp. Dis. 145, 600 (1992). 18. J. Schwartz and D.W. Dockery, Am. 1. Epidemiology 135, 12 (1992). 19. B.D. Ostro, Risk Analysis 9, 189 (1989). 20. K.R. Smith and Y. Liu, in J. Samet (ed.) The Epidemioiogy ofLung Cancer. pp. 151-184, Marcel Dekker, New York (in press). 21. K.R. Smith, Comments in Toxicol. (in press 1993). 22. Central Pollution Control Board, National Ambient Air Quality Statistics of India 1990, NAAQMS/3/1991-92, Delhi (1991). 23. Earthwatch, Urban Air Pollution in Megacities of the World, Published for United Nations Environment Programme and World Health Organization, Blackwell Pubs, Oxford (1992). 24. Global Environmental Monitoring System, Assessment of Urban Air Quality, United Nations Environment Programme and World Health Organization, Geneva (1988). 25. A. Arbhabhirama, D. Phantumvanit, J. Elkington, and P. Ingkasuwan, ‘Thailand Natural Resources Profile,” Thailand Development Research Institute, Bangkok (1987). 26. T.S. Patel, C.V. Raiyani, R.N. Mohan, A.L. Aggarwal, G.P. Kartha, and B.B. Chatterjee in B. Berglund, T. LindvalI and J. Sundell, eds., ‘Proceedings of Indoor Air ‘84” 4,295, Swedish Council for Building Research, Stockholm (1984). 27. C.V. Raiyani, S.H. Shah, N.M. Desai, K. Venkaiah, J. S. Patel, D. J. Parikh, and S.K. Kashyap, Atmos. Environ. 27A, 1643 (August 1993). 28. Global Environmental Monitoring System, “Human Exposure to Suspended Particulate Matter and Sulfate in Bombay, India,” EFP/84.66, WHO, Geneva (1984).
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29. K.R. Smith and Others, “Indoor Air Pollution Database for China,” ENV, East-West Center (in press 1993) 30. N. Kungskulniti, C. Pulket, F.D. Miller, and K.R. Smith, Asia-Pacific J. ofPublic Health 5, 54 (1991). 31. V.S. Mahajan, D.J. Parekh, and J.M. Despande, in D. Walkinshaw, ed., “Proceedings of Indoor Air ‘90,” 2,549, Canada Mortgage and Housing Corp., Ottawa (1990). 32. L.C. KOO,J.H-C. Ho, C-Y. Ho, H. Matsuki, H. Shimizu, T. Mori, and S. Tominaga, Am. Rev. Resp. Dis. 141, 1119 (1990).
Pergamon
AIR POLLUTION AND THE ENERGY LADDER IN ASIAN CITIES
KIRK R. SMI-l-H+ , MICHAEL G. API-ES, MA YUQINGI, WATHANA
W~N~~EKIAR-ITIRAT?
AND ASI-IWINI KuLKARNR
t ENV, East-West Center, Honolulu, HI 96848 $ EED, Lawrence Berkeley Lab, Berkeley, CA 94720 5 TI’EESA, Tsinghua University, Beijing lOO-084 1 SRI, Chulalongkom University, Bangkok 5 11ERG, Systems Research Institute, 17A Gultekdi, Pune 411-037 (Received 10 June, 1993)
Abstract-Household fuel switching from lower to higher quality fuels, i.e. movement up the “energy ladder,” generally leads to substantially lower emissions of health-damaging pollutants. The extent to which human ex osuies are reduced is difficult to predict, however, because ijf inferactions due to penetration of outdoor poYlutants into homes and vice versa. In order to help answer the uestion of how much exposures might be reduced by movement up the ener ollution study covering particulates ladder, a three-tit (PMIO), nitrogen dioxide (N02), anCFcarbon monoxide (C& in and near households spanning the most important current ste s in each city’s energy ladder. Ste s examined were biomass-kerosene-gas in Pune, India; coal-gas in Beijing, C/&a; and charcoal-gas in Bangkok ‘l%ailand . In most instances, 24hour sampling was conducted and some personal monitoring was undertaken d&g cooking periods. Preliminary calculations of the exposure and health implications of fuel switching are presented.
I. HOUSEHOLD
FUELS AND AIR POLLUTION EXPOSURES
Since fuel combustion is generally the most important cause of health-damaging air pollution in cities, urban energy policy decisions related to fuels and fuel-using appliances, e.g., pricing, taxing, investment, and regulation, should consider the resulting impacts on air quality.’ This is true not only for fuels used by vehicles, power plants, factories and other significant outdoor air pollution combustion sources, but also for household fuels used in cooking and heating stoves. The importance of these small sources is due not only to their sometimes significant contribution to ambient concentrations, but also to their relatively high exposure effectiveness (EE), defined as the fraction of the emitted pollution from a source that actually makes its way into people’s breathing zones. Indeed, long-term failure to address household stoves was one of the principal factors that led to the infamous and deadly London smog of 1952.2 Because household sources emit directly into the places and at the times of human occupancy, they often have EEs that are tens or hundreds of times greater than those of large-scale outdoor sources. 3 Thus, even relatively small sources of emissions can have a big impact on exoosure& which, of course, are the more accurate indicators of potential health impacts. 4 Individual exposure is a function of the air pollutant concentration, e.g., parts-per-million (ppm), and the duration that someone experiences it. An example of the resulting unit, thus, is ppm-hours. Population exposure includes the number of people involved, with such units as ppm-person-hours. Trends in household fuel use can be conveniently discussed by reference to the conceptual framework called the “energy ladder.” For illustration, Fig. 1 shows the household energy ladder most typical of South Asia. (As discussed below, some of the ladder rungs are somewhat different in other parts of developing Asia.) As one moves up the ladder, the cleanliness, efficiency, and convenience of the fuels tend to increase, along with their costs.5 History has shown that people will generally move up the ladder when they have the opportunity and resources to do so. Long ago, all of humanity started at the center of the ladder, with wood. Roughly half the world has been able to move up to the modem fuels. The other half of the population still bums wood or has been forced down to + Author for correspondence 587
588
KIRK R. SMITH et al
inferior biomass fuels, the diversion of which can have deleterious effects on local soil quality.
Development Fig. 1. Household energy ladder typical in South Asia. Although there have not been many studies of the air pollution emissions from fuel/stove combinations of importance in the developing world, the available data indicate that, in general, movement up the ladder results in fewer emissions of health-damaging pollutants.6 Changes in exoosures however, will depend also on the EE of the stove/house combination. For example, even with no change in fuel, replacing an un-flued (open) stove by one with a flue or chimney need not result in any less emission in order to substantially reduce exposure. This occurs by releasing much of the smoke, a mixture of gases, particles, and droplets, outside instead of indoors and thus decreasing the EE. Some of the smoke exiting through a flue, however, may also return inside as well as enter nearby houses, Changes in fuel (movement along the energy ladder) may also have impacts on the EE and local outdoor air quality as well as on the magnitude of emissions. Consequently, the net changes in exposures due to shifts in fuels, ventilation, behavior, or stoves are quite difficult to predict.
As part of the Asian Urban Energy and Air Pollution Network studies of household energy, air pollution monitoring was conducted in three cities at different levels of development and with somewhat different energy ladders. The purpose of these pilot studies was to assess the impact of the principal shifts in household fuel that were ongoing in each city: charcoal to bottled gas (LPG) in Bangkok; vented coal to three types of gas in Beijing; and biomass to kerosene to LPG in Pune. As much as possible, the measurements were oriented toward determinations of exposures rather than just ambient concentrations. See the three city reports for more details of these studies, including statistical analyses.7,8,g Following a common training course, monitoring teams in each city chose 60 households stratified by fuel type through a clustered random sampling technique from the same household lists used for the energy surveys. As much as possible, the same sampling and monitoring protocols were followed in each city. 10~1Many Beijing households contained
589
Air pollution and the energy ladder
space-heating stoves, however, unlike Bangkok and Beijing, the Pune household list was not entirely representative of the whole city, but focused more on the poor areas. Non-smoking households were selected and householders were asked to have guests refrain from smoking during the sampling periods. (For fuller discussions of the training program and protocols, see Ref. 10, and for the monitoring methods, equipment, and intra- and inter-country statistical analyses, see Ref. 11.) Table 1. Daily sampling protocol and total samples. Pollutant/ Location
Bangkok
Beijing
PM-10 indoor
Bach home. Total of 51.
Each home. Total of 58 samples.
Each home. Total of 61 samples.
PM-10 outdoor
One sampler for 2 homes near to and one for 1 home far from main road. Total of 34.
Clustered. One sampler for 3 homes. Total of 48 samples.
Each home. Total of 61 samples.
PM-10 personal
Three cooks per day. Total of 51 samples.
One cook per day. Total of 20 samples.
At separate session from indoor and outdoor. Total of 37 samples.
CO indoor
One home per day. Total of 17 samples.
One home per day before and after personal sampling. Total of 20 samples.
One home per day prior to personal sampling. Total of 30 samples.
CO outdoor
Three homes per day prior to personal sampling.
One home per day prior to personal sampling. Total of 20 samples.
One home per day prior to personal sampling. Total of 30 samples.
CO personal
One cook per day. Total of 17 samples.
One cook per day. Total of 20 samples.
One cook per day.
NO, indoor
All 3 homes for 10 clusters. Total of 30 samples.
One or two homes per day paired with outdoor. Total of 31 samples.
One, two or three homes per day paired with outdoor sampler. Total of 24 samples.
NO, outdoor
One site near and one site far from main road in 10 clusters. Total of 20 samples.
One or two homes per day paired with indoor. Total of 30 samples.
One, two or three homes per day paired with indoor sampler. Total of 24 samples.
SO, indoor
No measurements
Used in homes where personal monitoring was conducted. Total of 20 samples.
No measurements
So, outdoor
No measurements
One sample for a cluster of homes where personal monitoring was conducted. Total of 7 samples.
No measurements
As summarized in Table 1, four combustion-derived pollutants were monitored. Particulate matter below 10 t.trn (PMlO+ ) and carbon monoxide (CO) were measured indoors and outdoors over a 12-24 hour periods at the households, as well as with devices + PM-10 is the fraction of total suspended particulates (TSP)less than 10 microns in diameter. Because smaller particles penetrate deeper into the respiratory system, PM-10 is thought to be a better indicator of health hazard than TSP. Essentially all particulates derived from combustion are less than 10~ in size, while particulates derived from mechanical action, such as road dust, are larger.
KIRK R. SMITH et al
590
worn by the cook during one cooking session (personal monitoring). Nitrogen dioxide (NOJ was monitored by all teams both indoors and outdoors. (Because coal was being used, sulfur dioxide (So*) was monitored in some Chinese homes; the results are not reported here, but may be found in Refs. 8 and 11.) A short survey questionnaire was administered to each participating household. Due to resource constraints, equipment failure, logistics delays, and sample loss, the sample size is somewhat different for each city/pollutant/location combination, as detailed in Table 1. III. RESULTS The average concentrations and coefficients of variation (standard deviation divided by mean) of pollutants in each city for each fuel is shown in Tables 2a-c. For Pune, wood and agricultural residues are shown separately, and then combined together as ‘biomass” for comparisons with other fuels. In Beijing, the three types of gas are shown separately as well as together. In Bangkok, gas stove households and divided by the relative distance to the nearest major road as well as combined together. Table 2a. Pune energy ladder: measured mean concentrations (coefficients of variation). PM10 @g/m31
In
Fuel Ag-Resid
t
I Wood Biomass
I Kero
T
co(mgh3,
out
Cook
Cook
2800 (0.7)
2600 (0.2)
900+
5.0+
2000 (0.5)
920 (0.7)
1100 (0.5)
2100 (0.6)
3000 (0.6)
1100 (0.5)
480 (0.7)
340 (0.6)
530 (0.6)
250 (0.4)
250 (0.5)
420 (0.5)
Ill Ee’na%onal standard w=abov Bold = more than we times the national standard
Table 2b. Beijing energy ladder: measured mean concentrations (coefficients of variation).
T
PM10 (Clg/m3)
I
c0bgh3 Kitch
Jn
Nq out
Coal (vented)
550 (0.4)
f!k
Gas (a+b+c)
400 (0.5)
2.0 (1.2)
LPG
370 (0.6)
1.9 (1.0)
Coal Gas
420 (0.5)
li!iaaA Natural Gas
410 (0.6)
2.4 (1.2)
440 (0.6) 440 (0.4)
1600
II (E)
=a 0ZFE ional ndard lold = more than three times the national standard
(E)
h/m3)
591
Air pollution and the energy ladder
Table 2c. Bangkok energy ladder: measured mean concentration (coefficients of variation). Fuel
PM10
@p/m31
r
CO Wg/m3,
I
Cook
(E, (“0:;) (FG, 1.6 (0.2)
1.6 (0.2)
;old = more than three times the national standard.
For comparison, Table 3 lists the relevant pollution standards of the three nations as well as those of the United States. The closest approximation to international standards, the World Health Organization (WHO) recommendations, are also listed. Since there are few indoor standards for households, ambient standards are shown. One might argue, however, that indoor standards should be more restrictive since they are more closely tied to exposure and more directly affect some of the most vulnerable members of the community, i.e. the very sick, old, and young who may not spend much time outdoors. Table 3. Ambient air pollution standards.
Nation
India’
TSP - Total Suspended Particulates @g/m3) Bh/D: 500/360; 200/ 140; loo/70
Carbon Monoxide (w/n+) 8h: 5; 2; 1
Nitrogen Dioxide @g/m3) Bh/D: 120/w; 80/60; 30/20
China%
D: (TSP/IP) 500/250; 300/150; 150/50
D: 6; 4; 4
A: 150; 100; 50
Thailand
A: 100 D: 330
8h: 20; lh: 50
lh: 320
USA
(PM-lo) A: 50 D: 150
8h: 10 lh: 40
A:
WHO (recommendations)
A: 40-60 D: loo-150
8h: 10 lh: 40
A: 50 D: 150
100
h 8 hours; lh=l hou @=mhalable particula , less than 15pm in ey: A-annual; D=dail) diameter-PMlO. + industrial and mixed use; residential, cultural, or rural; sensitive areas, e.g., national parks, tourists resorts, and national monuments. * Industrial districts and traffic centers; urban-residential, cultural, or rural; historical monuments, natural conservation, or tourist resorts. =
592
KIRK R. SMITH
et al
Unfortunately, neither India nor Thailand have set standards for respirable particulates. Based on the experience of setting those standards in China and the United States, such standards would likely specify concentrations about half those shown for TSP. In their absence, however, comparisons here are made with the TSP standards. In Tables 2a-c all the means except the results of personal sampling of cooks were compared to the relevant national standard with the longest averaging time. Personal sampling values were compared to those standards with the shortest averaging time. In some cases, there was only one standard (see Table 3). As can be seen, many of the means are well above both the local standards and WHO recommended levels. The mean concentrations in Tables 2a-c shown in bold are more than three times higher than the most relevant national standard in each country.+ If the WHO levels were used for comparison, there would be little change for PMIO, since WHO levels are about as strict as these national standards. India and China, however, have relatively strict CO standards. Thus, comparison by WHO levels would essentially eliminate all the bold markings on CO means (i.e. more than 3 times larger) except in the bedroom of coal-burning homes in Beijing. Table 4 compares the outdoor measurements reported here to those reported by national and/or city ambient monitoring networks. PM10 levels measured outdoors near Bangkok homes are substantially higher than TSP levels determined by ambient stations in residential areas, particularly keeping in mind that PM10 levels are generally about half those for TSP. (In Bangkok, for example, they were reported to be 60%.)‘2 PM10 levels near Beijing houses definitely seem to be higher than indicated by the ambient measurements. For Pune, city-wide ambient values clearly considerably underestimate the concentrations near houses. Carbon monoxide levels measured in this study also seem to be somewhat higher than reported city-wide values. There are few data with which to compare, but our NO, levels do not seem to be much different from those reported from ambient stations. Table 4. Reported ambient concentrations compared to outdoor values measured in this study. All concentrations shown in pg/m 3. Since no city reports PMTO,TSP concentrations are shown.22-25 City
PMlO-S 250-1000’
TSP-R
co-s
NO,-S
NO,-R
CO-R
160-310%
15-50
lo-80
1100-2300
__
Beijing
410-550
200-500t
42-80
50
1500-11000
3400
Bangkok
280-450
100-2005
32
25
1600-3800
1000 (residential areas)
Key:
S = range of the mean outdoor concentrations determined in this study. R = ap roximate range of daily means reported in literature. + 2600 pg/m YYaround the three houses burning agricultural residues. $ Adjusted for season, i.e., instead of annual means, ambient levels were taken for the same month as the sampling was done in this study (Nov.-Dec.). 5 200 to 700 pg/m3
at street level.
As seen in Table 5, the indoor PM10 levels in Beijing are similar to or somewhat smaller than particulate concentrations measured by other studies in Chinese cities. The PM10 levels in the biomass-using homes of Pune are similar to those measured in other Indian homes using biomass.
+ Man standards are now set in statistical terms, e.g., that no more than 2% of daily means over a year should exceedr a certain level. For assessing equity among groups, some measure of the number of households above the standard would be relevant. For purposes of deterring potential health effects, however, mean population exposures are often more useful.
Air pollution
and the energy
593
ladder
Table 5. Urban indoor particulate concentrations in Asia. Location hdia Ahmedabad
Ahmedabad
Bombay
Period
Sample Size
cooking
32
1800 (1.1) Wood Charcoal Coal “Modem”
1600 (1.2) 550 (1.0) 2500 (0.9) 90 (1.6)
(Outside concent. about 500)
20 20 20 20 20
Wood Coal Kerosene
2700 (0.7) 1400 (0.7) 1100 (0.4) 500 (0.6) 490 (0.3)
24h living room
2 houses 12x each
CO0killg
Shanghai 15
Baodin Thailand Bangkok
Concentration (COV)
22 10 14 25
,!ixlla
Wuhan
Fuel
12
Kerosene
140 (0.4) 73 (0.4) (PM3.5)
Coal Piped Gas
1030-k; 850-b 510-k; 490-b
Coal Gas
290-k; 160-b 200-k; 150-b (PM3.5)
Coal
1500-k; 500-b 260-k; 260-b
Charcoal/
210 (PMlO) 490 (TSP)
Reference
Patel, et al 198426
Raiyani, et al 199327
GEMS, 198428
Smith, et al, 199329
Kungskulniti, et a130
Table 6 shows the results from several Asian indoor NO, studies. As might be expected, our measured 24-hour values in Pune are substantially lower than found in the cooking-period studies done in India. The Bangkok values are close to those reported in Hong Kong. Our Beijing findings seem to be substantially less than reported in Shanghai and Wuhan, but quite similar to the data taken in Nanjing. Unfortunately, publications of results often do not contain critical information, such as averaging time, that would make comparisons more reliable.
KIRK R. SMITH et al
594
Table 6. Urban indoor NO, concentrations Lma lion llxibl Ahmedabad
Ahmedabad
Bombay
Hong Kong
Period
cooking
Sample Size 32 22 10 14 25
Fuel
in Asia.
concen
Wood Charcoal Coal “Modern”
140 (2.3) 310 (1.3) 75 (0.5) 170 (1.0) 420 (0.9)
Patel, et al 1984z6
350 340 165 180 180
Raiyani, et al 199327
(0.6) (0.7) (0.5) (0.8) (0.9)
20 20 20 20 20
Wood Coal Kerosene
7-d kitchen
17
LPG & Kerosene
living mom
16
p, 24-h
319 mothers
Kerosene, LPG Piped Gas
39 32
362 children
Kerosene, LPG Piped Gas
37 37
Coal Piped Gas
260 50
cooking
china Shanghai
Reference
VW
Mahajan et al, 199031
97 (0.4)
62 (0.4)
Wuhan
30
Coal Gas
155 100
Nanjing
44
Coal Natural Gas
60-70 30-40
Thailand Bangkok
73
Charcoal LPG
30
Koo, et al, 199@2
Smith, et alI 199329
I
I Kungskulniti, et a130
IV. ENERGY LADDER The concentrations listed in Table 2c for Bangkok show some trends but no statistically significant differences according to fuel type, charcoal and gas. There does, however, seem to be an effect of distance from a main road for PM10 and CO. NO, values are remarkably similar in all locations. Data from the other two cities do show differences along the energy ladder, however. Shown for illustration in Fig. 2 are comparisons among fuels for both indoor and outdoor PM10 concentrations in Pune. Note the wfder confidence intervals (more variability) for the biomass households. For intercity comparisons along the energy ladder, the simplest approach is to accept gas as the control, i.e. that the concentrations in gas-using households are the best that can be expected in these cities (gas and charcoal together in Bangkok). If one also assumes that all the difference in concentrations is due to the difference in household fuels, it is possible to construct a concentration energy ladder across the three cities as shown in Fig. 3 for PM10
Air pollution
and the energy
595
ladder
and NO,.+ Note that net concentrations of both pollutants decline with movement up the energy ladder, although in different patterns. PM10 drops substantially between biomass and fossil fuels, while NO, does not drop so precipitously until moving from kerosene to coal. It may seem anomalous that Chinese coal is found to be cleaner than Indian kerosene. This is due to three factors: unlike kerosene stoves in Pune, most of the Chinese coal stoves were vented outdoors; the household coal used in Beijing is cleaned to some degree; simple Indian kerosene wick stoves have rather high emission factors.13
3.5 -
---n--l
Outdoor
i ‘0 a . S 3- _-__--__ = s”
,
I
-----__-___-__--__-
lridoor
-
2.5 -
-------8
LPG
Kerosene
Biomass
LPG
Kerosene
Biomass
Fuel Type
Fig. 2. Mean, median, and variation of indoor and outdoor PM10 measurements in Pune.
3000
-
2500
.!$ 2000 I! E 0’ g 1500 0 z $
1000
500
0,
I
AgResidues
Wood
Kerosene
Coal (vented)
Charcoal/LPG (by definition)
Fig. 3. Indoor 24-hour concentrations of PM10 and NO, along energy ladder across three cities. ’ This is done by subtracting the as value from each of the other values in each city before combining the cities together on one ladder in Figure P. The best single indicator would seem to be 24-hour inside measurements, which are used here. Unfortunately, the set of 24hour inside measurements for CO is incomplete.
KIRK R. SMITH et al
596
In reality, of course, indoor concentrations are also affected by local outdoor levels and, importantly, vice versa. Thus, the indoor and outdoor measurements at any one house will be affected by what the neighbors are doing, the density and arrangement of local housing, and the distance and strength of outdoor combustion sources. Focus on PMlO, however, should minimize the influence of household and street dust, which generally has larger diameters. To understand in detail how these factors affect exposures would require datagathering and model-building exercises far beyond what has been possible here. A simple model, however, can give some insights. To bracket the range of possible interactions between indoor and outdoor concentrations, we present estimates representing two assumptions: first that none of the local outdoor concentration is due to exfiltration from the inside (conservative model) and; second, that all of the local outdoor pollution above the outdoor levels outside gas-using houses comes from the inside (feedback model). Neither model considers the influence of household emissions from other neighborhoods. The two models determine daily exposure (E) in units of mg-h/m3 as follows: Econs= ti + [‘i - (c, + ‘11
(1)
is a conservative estimate and E feed= Q *
[ci-(cb
*p)l
is a result with feedback, where Ci = indoor concentration (mg/m3); C, local outdoor concentration; ti = time spent indoors (h/d); C, = estimated background outdoor concentration; P = penetration rate (the fraction of outdoor pollution coming indoors). For C, we use the mean outdoor concentration near homes with the cleanest gas fuel in each city. P depends on the pollutant and location, as indicated in Tables 7a,b. These represent guesses based on the type of housing in each city.‘%+ Table 7a. Estimated daily exposures from cooking fuel along energy ladder in Pune (P = 0.9 for PMlO; 0.95 for NO,).
WHO Recommendation
I
0.56
0.7
I
Table 7b. Estimated daily exposures from household fuel use along the energy ladder in Beijing (P = 0.7 for PMlO; 0.9 for NO,; 1.0 for CO). Fuel Coal (vented) Gas Chinese Standard /
WHO Recommendation
PM10 (mg-h/m3)
NO, (mg-h/m31
CO (mg-h/m3)
2.3 - 3.5
0.31 - 0.51
310 - 430
1.4
0.15
60
0.7/
0.7/
5U 140
0.56
0.7
+ We assume that Beijinghousin has a P for Ph410 similar to that measured in the U.S.A.,0.7 (Ref.14). To take intoaccount the much more openB ousing of Pune, we choose P=O.9. The effectiveP for gases is higher that for
particles depending on reactivity. See Tables 7a,b.
597
Air pollution and the energy ladder
Tables 7a and b summarize the resulting estimates for the exposure from household fuels experienced by a person spending 14 hours at home per day in Pune and Beijing. If time/place data are known, i.e. how long people stay in each microenvironment during the day, more accurate exposure estimates can be made. Also shown are the 14-h exposureequivalents of the relevant national standards and WHO recommendations. Note that Pune LPG households easily meet the standards both for PM10 (TSP) and NO,. Neither biomass nor kerosene households meet the standards for PMlO, although NO, exposures lie within the, respectively, WHO and Indian levels. The Pune results using the conservative model are summarized in Fig. 4 where the vertical axis shows the ratio of the estimated exposures to the exposure-equivalents implied by the Indian standards. Note that a shift from biomass to kerosene brings Nor, but not PMlO, within the standards. A further shift to LPG is required to meet the PM10 standard. ,100
100
10 0 ‘E B
PM10 Ratio to Standard
I
-
NOZ Ratio to Standard
,l
1
0.1
.lO
Biomass
Kerosene
LPG
,O.l
Fig. 4. Estimated ratio of PM10 and NO, exposures to national standards along energy ladder in Pune. In Beijing (Table 7b), again only PM10 exposure-equivalents are consistently exceeded. Comparison with the standards shows an exceedence for CO only in coal-using households. The relatively high PM10 exposures for Beijing gas-using houses may indicate that a higher penetration rate (P) should be used in the equations above.
Coal
0
PM10 Ratio to Standarc
m
NO2 Ratio to Standard
m
CO Ratio to Standard
Gas
Fig. 5. Estimated ratio of PMlO, NO,, and CO exposures to national standards along energy ladder in Beijing.
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Fig. 5 summarizes the Beijing results for the conservative model in terms of the ratios to exposureequivalents of the Chinese standards. Note that although there is a significant improvement when moving from coal to gas, PM10 and CO exposures in gas-using households still remain above the standards. The NO, and CO exposures found in the households of these cities lie just (NO,) or substantially below (CO) the levels thought by most authorities to produce meaningful health effects.15 For PMlO, the situation is quite different because of the large exposures implied by the measured indoor concentrations. A number of recent analyses,16J7J* have been able to quantify the health response to increased concentrations at a few hundred pg/m3, which is lower than found in Beijing and much lower than in Pune. These and earlier studies have found increases of a few percent (l-7%) in daily mortality with each increase of 100 pg/m3 in daily particulate levels. I9 Ref. 19 found an increase in childhood acute respiratory disease of 1% per 1 pg/m3 of fine particulate matter, which would imply a lo-fold increase in some Pune households. It is unclear, however, how the exposures reflected by these outdoor ambient measurements in the United States and United Kingdom are related to the indoor The temporal patterns, size distributions, and chemical exposures determined here. compositions are also likely to be different. In the lack of other information, it is instructive to assume that they can be considered similar, i.e. the 100 lrg/m3 for a day used as a benchmark in these epidemiological studies done in developed countries is taken to be roughly equal to 2.4 mgh/m3d measured in our study of Asian households. Taking 4% increase in daily mortality per 2.4 mg-h/m3-d, implies that a community in Pune could reduce its daily mortality 2030% by switching from biomass to kerosene; or by 25-35% through going all the way to LPG. In Beijing, a switch to gas in coal-using households would apparently reduce daily mortality by 3-5%. In addition, this refers to the situation where only one community in the city switches. A major city-wide shift away from coal as a household fuel would presumably lower outdoor levels and their penetration indoors even further, thus increasing the health benefit substantially. It is not clear how well daily mortality measures the air pollution impact from chronic obstructive disease and lung cancer, which take many years to develop.20,t In addition, nonfatal illness from these illnesses as well as other important conditions that have air pollution as a risk factor, such as acute respiratory disease and adverse pregnancy outcomes, are not directly captured in daily mortality surveys. Much more so than in developed countries, these latter two conditions also lead to infant death, another potentially important impact from indoor air pollution.21
v. CONCLUSION There are still a number of factors that would need to be explored before detailed exposure assessments could be done for these Asian urban households. Sorting out the details of the relative influence of indoor and outdoor levels on total exposure would probably require 24-hour personal sampling in combination with the kind of microenvironment sampling done here. More attention would also be needed to the fuel use of the neighborhood, since the improvement for one house alone switching to clean fuel may not be great if no one else nearby joins in, i.e. neighborhood outdoor levels may remain high. The measurements taken during this study have allowed comparisons of air pollution concentrations and estimated exposures at different stages of the energy ladder between and within three cities at substantially different economic levels. It has shown that household fuel choice seems to have the most impact on air pollution exposures at the lowest level of development (Pune), intermediate at middle stages even with use of coal (Beijing), and least in the more economically advanced developing country, where fuel choice seems to have little or no impact (Bangkok). Finally, the results in each city would seem to indicate that true human exposures may be substantially higher than indicated by ambient monitoring stations. We are thankful for funding from the International Development Research Centre, Ottawa, Aknow wand the support and advice of its staff, D. Brooks and S. T ler. In addition, we thank J. Sathaye and G. Lu for help at critical points and M. Kollander and R. Clickner of the e SEPA for their roles in training the country teams. The country teams also benefitted from the advice of S. Edgerton, A. Ellegard, C. Huang, V. Joshi, L. Koo, N.
’ In China, lung cancer risk is strongly associated with indoor exposure from coal-fired stoves. See Ref. 20.
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and the energy ladder
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Kungskulniti,R.P. Neupane, C.V. Raiyani, J. Ramakrishna, R. Song, S. Soderholm, J. Usin er, P.Young, and D. Zalle. We greatly appreciate the leadership and su port of J.G. Krishnaya, D. Qiu, and A. # ongsapich, as well as the patience and good will of the householders WI3 whom we worked.
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