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Economic costs of motor vehicle emissions in China: A case study
Transportation Research Part D 11 (2006) 216–226 www.elsevier.com/locate/trd
Economic costs of motor vehicle emissions in China: A case study Xin Deng Centre for Regulation and Market Analysis, School of Commerce, University of South Australia, GPO Box 2471, Adelaide, SA 5001, Australia
Abstract The last decade has witnessed a dramatic increase in the number of motor vehicles in China. Motor vehicles have become an increasingly important contributor to air pollution in major Chinese cities. While research interest in vehicular pollution in China has increased in recent years, there is little research on evaluating monetary costs of this pollution. This paper uses Beijing as a case study to evaluate the magnitudes of air pollution concerning motor vehicles. A monetary estimation of air pollution in regard to motor vehicles is presented on the basis of data for Beijing in 2000. Two methods— willingness-to-pay and human capital methods—are used to analyse the high and low points of estimation. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: Monetary evaluation; Air pollution; Road transport; China
1. Introduction The last decade has witnessed a dramatic increase in the number of motor vehicles in China, vehicles have risen four-fold in 25 years, China is now the fourth largest motor vehicle producer and the world’s third largest consumer. In 2003, the number of motor vehicles and motorcycles was 24.21 million and 59.29 million respectively, and forecast to rise 90 million and 192 million by 2020 (Li, 2004). This growth in the number of motor vehicle has serious economic and social implications for Chinese society and the economy. It will affect significantly urban lifestyle, and generate huge economic opportunities for various industries. On the other hand, the vehicle fleet’s rapid growth presents a challenge to urban authorities in that air quality may seriously deteriorate and traffic congestion will increase. Various measures, including new regulations and standards, have been introduced to address these issues. However, it is hard to know how effective these measures are without information regarding the magnitude of the economic damage caused by motor vehicles. Ironically, motor vehicle-related externalities are the result of the Chinese government’s efforts to raise the standard of living. Indeed, the most affluent super large cities suffer these external costs more than elsewhere in China. Several factors account for this. First, the vast majority of vehicles used in China are driven in major
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Table 1 Vehicle emissions in Beijing Vehicle category
Car Mini van Jeep LDGT HDGE MC
Units
g/km g/km g/km g/km g/kmh g/km
Average emission factors CO
HC
NOx
43.6 25.3 33.5 51.7 164.6 14.4
4.3 5.7 6.2 9.5 29.6 2.0
1.3 2.1 3.2 4.6 17.3 0.1
US model year of similar emission level 69–71 74–78 74–78 71–74 70 85–88
Note: LDGE—light duty gasoline truck, HDGE—heavy duty gasoline engine, MC—Motorcycle. Source: (Hao et al., 2000).
cities, and most private motor vehicles are registered there. Beijing, for example, accounted for 8.8% of the number of privately-owned vehicles in China in 2003, while its population accounted for only 1.1% of the population (National Bureau of Statistics of China, 2004). This is not only because residents in large cities are more affluent than rural residents, but also because the road infrastructure is much better developed. Second, less efficient technology makes the pollution level per vehicle much higher in China than in developed countries. Walsh (1996) estimates that the carbon monoxide (CO) and hydrocarbon (HC) emission levels of some domestically designed and manufactured engines are about 10–20 times the levels emitted from controlled vehicles in the US or Japan. He and Cheng (2000) also point out that the average emission factor per vehicle in China is several times higher than vehicle emissions in industrialized countries. Hao et al. (2000) show that the average emission levels of motor vehicles in Beijing in the late 1990s were equivalent to those in the US in the late 1970s (Table 1). Additionally, the fuel consumption of some vehicles is between 50% and 100% greater that the same type of vehicle manufactured in Western countries (He and Cheng, 2000). A survey of 3187 car owners shows that 46.3% of owners of medium to low class cars1 were unhappy with the noise level, and 39.2% complained about their car’s anti-shake function (Chen and Duan, 2001). While new standards for cars have been introduced in many large cities, and various measures, including installing catalytic converters, have been used to improve older vehicles’ environmental performance, emission levels are still substantially higher than international standards. Third, there is the high population density. The environment’s ability to ‘clean’ itself is much weaker in situations of high population density and many tall buildings; thus the interactions among different external factors are more likely to create a vicious circle. For example, a high accident rate worsens congestion, and low driving speed due to congestion results in higher levels of pollution. Tests conducted in China show that the emission level of carbon monoxide (CO) and hydrocarbon (HC) at speeds of 24 km/h are 60.5% and 73.8% higher than at the speed of 45 km/h (Fu et al., 2001). 2. The environmental problem 2.1. Urban air quality Air pollution is one of China’s most pressing environmental problems. This is mainly due to the rapidly deteriorating air quality in many large Chinese cities. The World Health Organisation (WHO) issues a list of the 10 most polluted cities in the world every year. In 1995, three Chinese cities—Beijing, Lanzhou and Taiyuan—were on this list (He and Cheng, 2000). In 2000, 9 out of the 10 cities with the worst air pollution in the world were from China (Sun, 2001). The World Health Organization (1999) annual mean guidelines for air quality standards are 90 lgm per cubic meter for total suspended particulates (TSP), and 50 lgm per cubic meter for sulphur dioxide (SO2) and nitrogen oxides (NOx). Table 2 shows that almost all major Chinese cities listed have exceeded the 1
Medium to lower class cars in this survey cover 10 models of five domestically made cars: Santana, Red Flag, Jetta, Citroen and Lingyang (Chen and Duan, 2001).
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Table 2 Air pollution level of selected cities Country
City
Total suspended particulates (lg/m3) 1995a
Sulphur dioxide (lg/m3) 1998b
Nitrogen dioxide (lg/m3) 1998b
China
Anshan Beijing Changchun Chengdu Chongqing Dalian Guangzhou Guiyang Harbin Jinan Kunming Lanzhou Nanchang Qingdao Shanghai Shengyang Taiyuan Tianjin Urumqi Wuhan Zhengzhou Calcutta Delhi Mumbai Jakarta Tehran Milan Mexico City Bangkok
305 377 381 366 320 185 295 330 359 472 253 732 279 – 246 374 568 306 515 211 474 375 415 240 271 248 77 279 223
115 90 21 77 340 61 57 424 23 132 19 102 69 190 53 99 211 82 60 40 63 49 24 33 – 209 31 74 11
88 122 64 74 70 100 136 53 30 45 33 104 29 64 73 73 55 50 70 43 95 34 41 39 – – 248 130 23
India
Indonesia Iran Italy Mexico Thailand
Source: World Development Indicators 2001. a Data are for the most recent year available in 1990–1995. Most are for 1995. b Data are for the most recent year available in 1990–1998. Most are for 1995.
pollutant level set by the WHO and the level of TSP of most is over 200 lgm per cubic meter. The TSP level in Lanzhou is as high as 732 lgm per cubic meter; more than 8 times the WHO’s standards, and twice as high as some well known polluted cities, such as Mexico City, Bangkok and Tehran. The level of SO2 varies greatly between cities, but only 4 cities conformed to the WHO’s standards. The level of SO2 in Guiyang and Chongqing are as high as 424 and 340 lgm per cubic metre, which are 7–8 times the WHO’s standards. The level of NOx is lower than the other two pollutants, but is still significantly higher than the WHO’s standards in most cases. 2.2. Air pollution from motor vehicles Motor vehicle emissions have become an important source of ambient air pollution. Walsh (2000) estimates that mobile sources are contributing approximately 45–60% of the NOx emissions and about 85% of the CO emissions in typical Chinese cities. Some have argued that urban air pollution in cities is shifting from a predominantly coal-burning type to a coal-vehicle mixed type or even a vehicular pollution dominant type (Fu et al., 2001; Shao and Zhang, 2001). The rapid increase of vehicular emission is especially obvious in some large cities. Motor vehicles accounted for 82.7% of CO and 42.9% of NOx emissions in Beijing in 1998, rising from 76.8% and 40.2% in 1995 (Department of Environmental Science and Engineering, 1999). Vehicles in Shanghai were estimated to have emitted 197,000 and 49,000 tons of CO and NOx in 1996, accounting for 86% and 56% of the total emissions of these two pollutants (Lu, 1998). Motor vehicles specifically contributed
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Table 3 National Ambient Air Quality Standards Pollutant (lg/m3)
SO2 TSP PM10 NOx NO2 CO O3
Time period
Annual average Annual average Annual average Annual average Annual average Daily average Hourly average
National Ambient Air Quality Standards Class one
Class two
Class three
20 80 40 50 40 4000 120
60 200 100 50 40 4000 160
100 300 150 100 80 6000 200
WHO’s Standard
50 90 50
Source: State Environment Protection Administration (GB 3095-1996). World Health Organisation Web site: www.who.int.
to 76% and 44% of the total emission of CO and NOx in 1995 (Cheng, 1997). Shao and Zhang (2001) estimate that vehicular emissions contributed 84% of CO and 25% of NOx in 1995. These figures could increase to 96% and 45% in 2010 if remediation policies are not implemented. Another sign of motor vehicles’ increasing contribution to air pollution is the rising level of NOx emissions in urban areas. While the ambient SO2 levels declined significantly and TSP levels dropped slightly in many urban areas between 1991 and 1998, NOx levels increased, reflecting the growing impact of vehicular emissions (World Bank, 2001). Fewer cities complied with class two National Ambient Air Quality Standards (NAAQS)—Table 3—for NOx in 1998 than in 1991. The World Bank (2001) estimates that total human exposure to ambient NOx levels above class two increased almost 60% during that period, with virtually all of the increase occurring in the 32 largest cities. Several studies have demonstrated a correlation between automobile emissions and elevated blood-lead levels in children in China (Li et al., 1992, 1994). Studies conducted in Shanghai also show that a newborn child’s risk of lead poisoning is associated with proximity to a major traffic way, along with other factors such as a family member’s exposure to lead at work, and household and neighbourhood coal combustion (Shen et al., 1996). Anecdotal evidence suggests that ambient lead levels have been rising over the past decade as vehicle use has increased (World Bank, 1997). The average lead concentration increased 12-fold between 1988 and 1995. In a heavy traffic area of Taiyuan, the capital of Shanxi Province, ambient lead concentration increased from 0.625 in 1990 to 1.803 in 1993 (Chen, 1995). The limited data available on fine particles (PM10 and PM2.5),2 suggest that the ambient PM level in many Chinese cities is a serious potential problem (Fu et al., 2001; He and Cheng, 2000). A study in 1995 estimated that the total exhaust PM10 and PM2.5 from motor vehicles in Beijing were 2445 tons and 1890 tons respectively, and by 1998 these levels had increased to 3359 tons and 2694 tons; a growth of 37.4% and 42.5% growth in three years (Wu et al., 2002). 3. Methodology The methodology used for estimating vehicle emission cost is based on studies conducted in other countries (Fisher et al., 2002; Sommer et al., 1999) as well as in China (World Bank, 1997). In particular it looks at Beijing in 2000. 3.1. Sample cities Beijing is the capital of China and has some unique features in terms of road infrastructure and vehicle ownership. The road system is composed of rings with radial arteries. The road around the Forbidden City is named the first ring, and ring roads beyond are the second, third, fourth and fifth ring roads according 2
PM10 refers to particulate matter with an aerodynamic diameter of 10 micrometres or less. PM2.5 consists of particulate matter with an aerodynamic diameter of 2.5 lm or less.
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Table 4 List of major policies targeting motor vehicle emissions launched by Beijing Municipal Government Year
Key policies
1995 1996 1997 1998
Implementing new emission standards for light vehicles New vehicles that do not reach the emission standards are not allowed to be sold Phasing out leaded petrol Scrapping 38,000 vehicles Implementing 18 urgent policies targeting coal-burning, vehicle emissions, and dust From Jan 1st, implementing new emission standards for light vehicles that are equivalent to European standards in the early 1990s Installing vacuum time delay valve for vehicles that were registered before 1995 Modifying 120,000 vehicles that were registered after 1995 Scrapping more than 30,000 vehicles 1st and 2nd stage air pollution control Applying new standards for heavy vehicles, diesel vehicles, agricultural vehicles and motorcycles Converting 26,000 taxis and buses into dual-fuel vehicles 3rd to 5th stage air pollution control Implementing environmental protection labelling system Vehicles without environmental protection label are not allowed to be on the road Implementing 2nd stage emission standards for light vehicles on August 1st New vehicles that have not reached the 2nd stage emission standards are not allowed to be sold and registered in Beijing Implementing 2nd stage emission standards for heavy motor vehicles and motorcycles
1999
2000
2001 2002 2003 2004
Source: Beijing Environment Protection Bureau, 1995–2005.
to distance from the centre of the city. The fourth ring road was fully operational in late 2000, the construction of the fifth ring road is completed, and work on the sixth ring road is scheduled to start in the near future. The area within the third ring is the city’s core, and most of the political and commercial institutions are located within it. Administratively, Beijing can be divided into three parts according to distance from the Central Business District (CBD). The city area comprises four districts: Dongcheng, Chongwen, Xicheng and Xuanwu. Most of this area is within the second ring road. Inner suburban Beijing comprises Chaoyang, Fengtai, Shijingshan and Haidian and is mainly within the third ring road. The remaining 10 suburbs are in outer suburban Beijing. Beijing has the largest motor vehicle fleet of any city in China and the vehicle fleet has increased from 784,300 in 1997 to 1.63 million in 2003. In 2003 Beijing accounted for more than 10% of newly registered civil passenger vehicles nationwide (National Bureau of Statistics of China, 1998, 2004). This dramatic increase presents a huge challenge for local authorities. Faced with rapidly deteriorating air quality, since the mid1990s, the Beijing municipal government has conducted aggressive campaigns targeting air pollution, and vehicle emission was one of the major concerns (Beijing Environment Protection Bureau, 1995–2005). Table 4 shows the new emission standards introduced almost every year over the decade. Emission standards for light vehicles, for example, were updated in 1995, 1999 and 2002, well ahead of the timetable set by the State Environmental Protection Administration. Furthermore, Beijing has been introducing various measures to reduce vehicle emissions, including scrapping vehicles, phasing out leaded petrol, installing vacuum time delay valves, modifying vehicles, and regular vehicle inspections. While there is not enough data to show a link between the introduction of new standards and improvements in air quality, we can observe an improvement in air quality over a number of years (Table 5). However, for over one third of each year, air quality in Beijing is still well below the national standards, and despite such aggressive policies, by 2003 Beijing was only ranked 27th out of 31 capital cities in terms of air quality (National Bureau of Statistics of China, 2004). Current emission standards in Beijing are comparable to Euro II—emission standards adopted by European countries in the late 1990s. Even if new standards are introduced, however, they are unlikely to have much impact on existing vehicles because a significant proportion of these were purchased in the last five years,3 and it is unlikely that they could be scrapped in the near future. While it is possible to further upgrade 3
56% of private vehicles and 39% of civil vehicles were purchase between 1999 and 2003 (calculated from China Statistical Yearbook 2004).
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Table 5 Air Quality in Beijing Year
SO2 (mg/m3)
CO2 (mg/m3)
CO (mg/m3)
PM10 (mg/m3)
TSP (mg/m3)
Proportion of days that air quality reaches Grade II of National Standards (%)
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
0.083 0.061 0.058 n.a 0.012 0.080 0.071 0.064 0.067 0.061 0.055
n.a n.a n.a n.a 0.074 0.077 0.071 0.071 0.076 0.072 0.071
n.a n.a n.a n.a 3.3 2.9 2.7 2.6 2.5 2.4 2.2
n.a n.a n.a n.a
0.337 0.337 0.323 n.a 0.378 0.364 0.353 0.370 0.373 n.a n.a
n.a n.a n.a n.a 15.4 (55.8a) n.a. (75a) 48.4 50.7 55.6 61.4 62.5
0.180 0.162 0.165 0.166 0.141 0.149
Source: Beijing Environmental Status Report (1994–2004). Numbers under each pollutant category are annual daily average figure for metropolitan areas. a The figures in the brackets indicate proportion of days that air quality reaches Grade III of National Standards (%).
technology, it will become much more difficult for local authorities to further improve air quality via this channel unless there is a technical breakthrough. 3.2. Evaluation methods A problem with using existing research, especially studies carried out in other countries, is the transferability of existing estimates to China. While most of the values are adjusted to fit China, there remains a problem of how to make the adjustment. We adopt two principles. One is the ‘‘at-least’’ principle, i.e. selecting the lowest value where a number of estimates are available. This ensures that the estimates are conservative. The other is the ‘‘at-best’’ principle, i.e. selecting the best possible method of transfer. The value of statistical life for China, for example, may be obtained by transferring other countries’ estimates. The basic adjustment method is to compare the Gross National Income (GNI) data for China with the GNI of other countries. This means using the ratio of China’s GNI and the target countries’ GNI to adjust the value estimated based on the situation in the target countries. This kind of adjustment is inevitably subject to criticisms of simplicity. However, a survey of 68 studies by Miller (2000) suggests that the income-elasticity of values across countries is roughly 1, suggesting it is reasonable to convert the values using the income ratio. Moreover, the World Bank also recommends this adjustment method in the absence of local estimates (World Bank Group, 1998). It is worth noting that none of the adjustment methods is perfect, given the differences between countries, the different time periods, and the scarcity of information about China. 4. Monetary costs of motor vehicle emissions This study follow the methodologies used in WHO (Sommer et al., 1999) and World Bank (1997) works. The WHO study estimated health costs due to road traffic related air pollution for three European countries: Austria, France and Switzerland. The World Bank study estimated total environmental costs in China. Air pollution costs form an important part of environmental costs. Both adopt a dose–response function, a willingness-to-pay method, and use PM10 as the indicative pollutant, however, the estimate of the function for the studies differs, as do the monetary valuations for deaths and illness. This is reasonable given the differences between China and the European countries. The major social costs of air pollution are negative human health effects. While road transport generates a mix of different pollutants, it is not possible to attribute a single health effect to one specific pollutant. An ‘‘indicator pollutant’’ is therefore used as a base to measure relevant health impacts of air pollution. Numerous epidemiological studies on the health effects of fine particles show that the association between ambient levels of fine particles and human health effects is statistically significant, and cannot be explained
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by confounding factors (Koch (2000). Given the available epidemiological data, PM10 is regarded as an important indicator for the health risks posed by pollution (Ku¨nzli et al., 1999). In fact, PM10 is reported to be the most prominent pollutant for the majority of China’s cities that have daily air quality reports. Normally, there are three steps to evaluate motor vehicle-related health costs in monetary term. First, an assessment on the exposure of the residential population is needed. Ideally, the results should describe the levels of concentration to which the number of people living in each geographical unit are exposed, and the road transport’s share of the pollution level. Second, an epidemiological study evaluating the exposure–response relationship between air pollution and effects on health should be conducted. The study should provide the number of cases of morbidity and mortality attributable to air pollution. Last, the quantified health impacts have to be converted into monetary terms via an adequate method. 4.1. Population exposure We adopt the annual average level of ambient concentration of PM10 in Beijing as a base to assess the exposure of its residential population. Beijing started to publish data on annual average daily concentration of PM10 in 1999 (Beijing Environment Protection Bureau, 2001). This is calculated on the basis of data from 13 monitoring sites, however, detailed information on the annual ambient concentration of PM10 of each site cannot be obtained.4 While there are a few studies of particles in some Chinese cities, none of them provides data for every part of a designated city; some give partial coverage (He et al., 2001) others compare monitoring sites in several cities (Wei et al., 1999). Moreover, most of the studies focus on the composition of fine particles, and do not provide information on the exposure of the residents. Since it is not possible to obtain information on population exposure from current research, estimates are based on other countries. The WHO’s study showed that around 60% of the population are exposed to a level equal to, or higher than, the average level of PM10. While the figure might be higher, given the significantly higher level of PM10, as a conservative estimate, we assume that 60% of the population in Beijing were exposed to an ambient of PM10 concentration level at 162 lg/m3 in 2000. The WHO study estimates that the share of PM10 concentration attributable to road transportation increases with the level of total PM10 concentration. The road traffic’s share rises from 28%, with a total PM10 concentration level of less than 10 lg/m3, to 58% with a total PM10 concentration level higher than 40 lg/m3 (Filliger et al., 1999). As a general rule, European studies suggest that the road traffic share of secondary particles is equivalent to the portion of SO2, NOx and NH3 emission caused by traffic (EMEP, 1998). If we follow that rule, the share of motor vehicles to total PM10 pollution would be higher than 40%, which is similar to the figure that previous studies suggest as the contribution of motor vehicles to NOx emission in Beijing (He and Cheng, 2000). China’s situation is, however, different from European countries. While the PM10 concentration in Beijing is much higher than 40 lg/m3, even 58% could be an overestimation. The quality of the natural environment in most European countries is superior to China. Some common pollution sources in China, such as coal combustion and mineral dust do not often have a significant impact on the environment in Europe. A study of particulate pollution in Xi’an, the capital of Shaanxi Province, estimates that motor vehicle emissions contributed about 25% of PM10, while the shares of the other two sources were 24% and 22%, respectively (Zhuang et al., 2000). With a much larger motor vehicle fleet,5 motor vehicles’ contribution to PM10 should be higher in Beijing, however, 30% is used as a conservative estimate. 4.2. Dose–response function The second step is to find out the exposure–response relationship between the pollutant and health effects. A number of epidemiological studies on air pollution and health effects have been conducted in China. Their results showed that ambient air pollution had acute and chronic effects on mortality, morbidity, hospital
4 5
The Department of Environment Monitoring in the Beijing Environment Bureau indicates that each site’s data is confidential. The number of motor vehicles in 2000 Shaanxi province was 364,700; about one third of that in Beijing.
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admissions, clinical symptoms, and lung function changes. Based on this, an exposure–response function has been devised by different research groups (Chen et al., 2004). There are some studies on the statistical relationship between air pollution and health outcomes in several Chinese cities. However, only one study analysed the health impacts of fine particulates, and it found a 40% increase of cardiovascular disease mortality resulting from a 100 lg/m3 increase in ambient concentration of particulates (World Bank, 1996). Other studies have mainly examined the relationship between daily mortality and two pollutants: SO2 and TSP (Xu et al., 2000). While these studies show that air pollution has some impact on health, they do not provide enough information to develop a dose–response function. The dose–response function of PM10 presented by the World Bank (1997) estimated the number of additional deaths or cases per 1 million people for a 1 lg/m3 increase in ambient concentration of PM10. The WHO based its estimation on relative risk estimates (Sommer et al., 1999). Both studies discussed similar diseases. Due to the lack of relevant epidemiological data in China, we are unable to convert the relative risk estimated by the WHO into numbers of additional cases. however, a comparison between the World Bank’s estimates for China and the WHO’s estimates for three European countries (Ku¨nzli et al., 1999) suggests a lower mortality and a higher morbidity rate in the World Bank’s work (Table 6); the number of additional deaths per one million people for every 1 lg/m3 increase in ambient concentrations of PM10 is 6, according the latter. The WHO’s study estimated that the number of premature fatalities increase by 4.3% for every 10 lg/m3 PM10 increment. Based on the mortality rate caused by disease in urban areas in China in 2000 (National Bureau of Statistics of China, 2001) and the World Bank Group (1998), the number of premature fatalities caused by every 1 lg/ m3 PM10 increment should be 26 in 1 million people. The WHO’s estimation for three European countries ranged from 33.7 to 37.4 (Sommer et al., 1999). 4.3. Monetary valuation The most controversial part of the estimation is the monetary valuation of the health effects that can be based on two approaches: willingness-to-pay and cost methods. The former assesses the amount people are willing to pay to reduce the risk of illness or death. Contingent valuation surveys, wage risk studies and consumer behaviour studies may be used to determine a value of willingness-to-pay. The cost approach values mortality and morbidity impacts according to the loss in income (or production) plus out-of-pocket expenditures. The human capital approach used by the World Bank (1997) is a cost approach. While the human capital approach has the advantage of simplicity, it may seriously underestimate costs, as the lives of those without income can be valued at zero, which is not realistic. As a result, the preferred approach to
Table 6 Health impacts of PM10 Health impactsa
The WB’s estimation for Chinab
Relative risk estimated by the WHOc
Increment estimated by the WHO for Franced
Mortality (deaths) Respiratory hospital admissions (cases) Cardiovascular hospital admissions (cases) Emergency room visits (cases) Restricted activity days (days) Lower respiratory infection/child asthma (cases) Asthma attacks (cases) Bronchitis (cases) Chronic bronchitis (cases) Respiratory symptoms (cases)
6 12 n.a 235 57,500 23 2608 n.a 61 183,000
1.043 1.0131 1.0125 n.a 1.094 1.044 1.039 1.306 1.098 n.a
34 15 21 n.a 26,370 260 619 483 39.4 n.a
a
Number of additional deaths, cases, or days per 1 million people for every 1 lg/m3 increase in ambient concentrations of PM10. Source: The World Bank (1997), estimates are based on China. c Source: (Ku¨nzli et al., 1999), estimates are based on Austria, France and Switzerland. d Original estimates were based on 10 lg/m3 increase in ambient concentrations of PM10. They were converted assuming a linear relationship between PM10 and health effects. b
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Table 7 Health costs of road transport Health impacts
Mortality (deaths) Respiratory hospital admissions (cases) Emergency room visits (cases) Restricted activity days (days) Lower respiratory infection/ child asthma (cases) Asthma attacks (cases) Chronic bronchitis (cases) Respiratory symptoms (cases) Total costs a
Cases attributable to road traffica
Monetary valuation of mortality and morbidity (USD)
Costs attributable to road traffic (1 mil USD)
Willingness-to-pay
Human capital
Willingness-to-pay
1876 3751
105,000 966
15,650 496
196.935 3.624
Human capital 29.353 1.859
73,460 17,974,224 7190
73 12 23
40 4 23
5.363 215.691 0.165
2.948 72.767 0.163
815,248 19,068 57,204,922
7 25,644 1
7 2087 1
5.707 488.988 57.205 973.677
5.690 39.796 57.205 209.781
Calculated based on the assumption of 60% urban population exposure in Beijing in 2000.
environmental damage evaluation has shifted from the human capital to the willingness-to-pay approach. The human capital approach, however is used here as an indicator as a lower limit. The World Bank study used an indirect approach to the problem by converting relevant data from the US, and in the absence of local data, this seems to be the best way to address this issue. As discussed, the dose–response function of the World Bank and the WHO studies cover similar diseases (Table 6). This study follows the dose–response function recommended by the World Bank (1998) but the values used are converted from the WHO’s estimates, except for values of emergency room visits, bronchitis and respiratory symptoms, which are not covered by the WHO’s dose–response function. The reasons for abandoning the values used in the original World Bank study for willingness-to-pay estimates are three-fold. First, the WHO’s estimation was based on studies of various countries, and hence may represent a more comprehensive estimation. Second, the World Bank’s estimates were conducted in 1995, and since then per capita income in China has increased considerably. Finally, the original valuations were based on the whole nation. Since both the per capita GDP and the wages in Beijing were much higher than China’s national average,6 the valuation should be much higher in both willingness-to-pay and human capital approaches. As the World Bank’s estimates derived from the human capital approach were based on the nationwide average wage rate in 1995, these estimates have to be revised to reflect the difference between the nationwide average wage rate in 1995 and Beijing’s wage rate in 2000. The WHO’s estimation is converted firstly by using per capita GNI of China and the European Union in 2000. It is then adjusted by the ratio of Beijing’s per capita GDP to that of the national average for China. As a result, the conversion factor for Beijing is 0.1227; multiplied by the values estimated by the WHO, this yields a value of statistical life of $171,640 for Beijing. This is based on the figure of €1.4 million estimated by the WHO. Following the WHO’s method, the original value of life is discounted at the rate of 60% to take into account that most victims of air pollution are aged people, and that their willingness-to-pay for preventing fatalities will decline after a certain age. Therefore the figure adopted for is $105,000. Two matters need further clarification. One is whether this result is an overestimation. Miller (2000) suggests that the value of statistical life is typically about 120 times GDP per capita after reviewing 68 studies spread across 13 countries. If this is the case, the value of life in Beijing should be $324,723 in 2000, which is nearly double the estimate obtained used here. The other issue is whether it is necessary to further adjust the value by the per capita GDP of Beijing. If the values are to be used for decision-making across regions, it may seem unfair and politically unwise to vary the value of statistical life between residents of different regions, however, the purpose of this estimate is to provide information on the magnitude of external costs
6
In 2000, per capita GDP in Beijing was RMB22,460, while the national average was RMB7,078; and the average wage in Beijing was RMB16,350, while the national average was RMB9,371 (all at current prices).
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concerning motor vehicles in Beijing. Adjustment is, therefore, necessary to reflect the higher willingness-topay value due to higher income. Table 7 shows the health costs attributable to road traffic. Under the assumptions that 60% of the urban population was exposed to air pollution and that air pollution from motor vehicles killed 1876 people in Beijing in 2000, while the number of people killed in road accidents was 1470 in the same year. Road traffic also accounted for 3751 cases of respiratory hospital admissions and 19,068 cases of chronic bronchitis. In Beijing in 2000, the costs attributable to road transport were $974 million according to the willingness-to-pay approach and $210 million according to the human capital approach. In both approaches the costs of morbidity were predominant, accounting for 80% of the total costs according to the willingness-to-pay, and 86% according to the human capital approach. By comparison, in the WHO’s study the mortality costs predominate, and amounted to between 70% and 75% of the costs (Sommer et al., 1999). In Beijing in 2000, the total costs of air pollution caused by road transport were equivalent to 3.26% of GDP, according to the willingness-to-pay approach and 0.7% following the human capital approach respectively. The first figure may be treated as the high end of the estimation, and the other as the low end. These estimates are still conservative; apart from the reasons discussed, Ying et al. (2002) looking at urban air pollution sources in Beijing found that the PM10 and NOx exposure efficiency7 of transport are the highest of all pollution sources indicating that transport may cause more damage than other pollution sources with the same amount of pollutants emitted. Further, while the ambient level of PM10 in three European countries stood between 21 and 26, air pollution related costs were estimated to be between 1.5 and 3.25 of GNI in these countries. Finally, one would expect that the figure for Beijing would be much higher than for China as a whole because motor vehicle ownership levels are higher than most other cities. References Beijing Environment Protection Bureau, 1995–2005. Report on the State of Environment of Beijing (1994–2004). Beijing Environment Protection Bureau, Beijing. Chen, S.L., 1995. China Vehicle Pollution Management: Challenges and Prospects. Chongqing Environmental Bureau, Chongqing (in Chinese). Chen, Y.S., Duan, Y.D., 2001. Survey revealed that cars between low and medium price range need to improve from eight aspects, China Automobile, November 13, (in Chinese). Chen, B., Hong, C., Kan, H., 2004. Exposures and health outcomes from outdoor air pollutants, China. Toxicology 198, 291–300. Cheng, C.H., 1997. Pollution load of vehicular exhaust in shanghai (in Chinese). Shanghai Environmental Sciences 16, 26–29. Department of Environmental Science and Engineering, 1999. Research Report of Planning of Vehicle Emission Pollution Control in Beijing City. Tsinghua University, Beijing. EMEP, 1998. Long-Range Transport of Fine Secondary Particles. Norwegian Meteorological Institute, Oslo. Filliger, P., Puybonnieux-Texierh, V., Schneideri, J., 1999. PM10 Population Exposure: Technical Report on Air Pollution. World Health Organisation, London. Fisher, G.W., Rolfe, K.A., Kjellstrom, T., Woodward, A., Petersen, A., Shrestha, R., King, D., 2002. Health Effects Due to Motor Vehicle Air Pollution in New Zealand. Ministry of Transport, Wellington. Fu, L.X., Hao, J.M., He, D.Q., He, K.B., 2001. Assessment of vehicular pollution in China. Journal of Air and Waste Management Association 51, 658–668. Hao, J.M., He, D.Q., Wu, Y., Fu, L.X., He, K.B., 2000. A study of the emission and concentration distribution of vehicular pollutants in the urban area of Beijing. Atmospheric Environment 34, 453–465. He, K.B., Cheng, C., 2000. Present and future pollution from urban transport in China. China Environment Series: Woodrow Wilson Center, Washington, DC. He, K.B., Yang, F.M., Ma, Y.l., Zhang, Q., Yao, X.H., Chan, C.K., Cadle, S., Chan, T., Mulawa, P., 2001. The characteristics of PM2.5 in Beijing, China. Atmospheric Environment 35, 4959–4970. Koch, M., 2000. Airborne Fine Particulates in the Environment: A Review of Health Effect Studies, Monitoring Data and Emission Inventories. International Institute for Applied Systems Analysis, Luxemburg. Ku¨nzli, N., Kaiserb, R., Medinab, S., Studnickac, M., Chaneld, O., Filligere, P., Herry, M., Puybonnieux-Texierh, V., Que´nel, P., Schneideri, J., Seethalerj, R., Vergnaudk, J.-C., Sommer, H., 1999. Health Costs Due to Road Traffic-Related Air Pollution, Air Pollution Attributable Cases. An Impact Assessment Project of Austria, France and Switzerland. World Health Organisation, London.
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Exposure efficiency is defined as the proportion of pollutants that is absorbed by the human body (Ying et al., 2002). The higher the efficiency is, the more damage it causes on human health.
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Li, X., 2004. Current situation and policies of motor vehicle emission in China. Accessed. 2004:Dec 2. State Environment Protection Administration, Department of Pollution Control, Beijing. (in Chinese). Available form:. Li, G.H., Gu, W.X., Wang, D.M., 1992. Effect of lead pollution on IQ in children. China Journal of Preventive Medicine 26, 380–381. Li, G.H., Gu, W.X., Yu, M., 1994. Effect of lead pollution on blood Pb, Cu, Zn and SOD in primary schoolers. China Public Health 10, 204–205. Lu, S.Y., 1998. Vehicular pollution control strategies in shanghai (in Chinese). Environmental Science 17, 1–3. Miller, T.R., 2000. Variations between countries in values of statistical life. Journal of Transport Economics and Policy 34, 169–188. National Bureau of Statistics of China, 1998. China Statistical Yearbook. China Statistical Publishing House, Beijing. National Bureau of Statistics of China, 2001. China Statistical Yearbook. China Statistical Publishing House, Beijing. National Bureau of Statistics of China, 2004. China Statistical Yearbook. China Statistical Publishing House, Beijing. Shao, M., Zhang, Y.H., 2001. Current air quality problem and control strategies for vehicular emissions in China. The Future of Personal Transport in China, Washington, DC. Shen, X.M., Rosen, J.F., Guo, D., Wu, S.M., 1996. Childhood lead poisoning in China. Science of the Total Environment 181, 101–109. Sommer, H., Seethaler, R., Chanel, O., Herry, M., Masson, S., Vergnaud, J.-C., 1999. Health Costs Due to Road Traffic-Related Air Pollution—An Impact Assessment Project of Austria, France and Switzerland (Economics Evaluation—Technical Report on Economy). World Health Organization, London. Sun, C.J., 2001. Paying for the Environment in China: The Growing Role of the Market. Woodrow Wilson Centre, Washington DC. Walsh, M.P., 1996. Motor vehicle pollution control in China: an urban challenge. In: Stares, S., Liu, Z. (Eds.), China’s Urban Transport Development Strategy. World Bank, Washington, DC. Walsh, M.P., 2000. Transportation and the environment in China. China Environment Series, Washington, DC. Wei, F., Teng, E., Wu, G., Hu, W., Wilson, W.E., Chanpman, R.S., Pau, J.C., Zhang, J., 1999. Ambient concentrations and elemental compositions of PM10 and PM2.5 in four Chinese cities. Environmental Science and Technology 33, 4188–4193. World Bank, 1996. China: Chongqing Industrial Pollution Control and Reform Project (Staff Appraisal Report). World Bank, Wahington DC. World Bank, 1997. Clear Water, Blue Skies: China’s Environment in the New Century. World Bank, Washington, DC. World Bank, 2001. China: Air, Land and Water. World Bank, Washington. World Bank Group, 1998. The effects of pollution on health: the economic toll. In: Pollution Prevention and Abatement Handbook. World Bank, Washington DC. World Health Organization, 1999. Air Quality Guidelines. World Health Organization, Geneva. Wu, Y., Hao, J.M., Li, W., Fu, L.X., 2002. Calculating emissions of exhaust particulate matter from motor vehicles with part5 model. Environmental Science (Huan Jing Ke Xue) 23, 6–10. Xu, Z.Y., Gao, J., Dockery, D.W., Chen, Y.D., 2000. Air pollution and daily mortality in Shenyang, China. Archives of Environmental Health 55, 115–124. Ying, G.X., Lu, Y.Q., Hao, J.M., Yu, X.C., He, K.B., 2002. Exposure efficiencies of urban air pollution sources in Beijing. Urban Environment and Urban Ecology 15, 33–35. Zhuang, Y.H., Liu, S.J., Zhang, K.S., Fan, X.Y., Zhang, W., Fan, M.H., Han, S.H., 2000. Capacity development for ambient particulate emissions control in Xi’an. In: Raufer, R., Zhuang, Y.H., Tang, X.Y. (Eds.), Urban air pollution control in China. CICETE, Beijing.
Economic costs of motor vehicle emissions in China: A case study Xin Deng Centre for Regulation and Market Analysis, School of Commerce, University of South Australia, GPO Box 2471, Adelaide, SA 5001, Australia
Abstract The last decade has witnessed a dramatic increase in the number of motor vehicles in China. Motor vehicles have become an increasingly important contributor to air pollution in major Chinese cities. While research interest in vehicular pollution in China has increased in recent years, there is little research on evaluating monetary costs of this pollution. This paper uses Beijing as a case study to evaluate the magnitudes of air pollution concerning motor vehicles. A monetary estimation of air pollution in regard to motor vehicles is presented on the basis of data for Beijing in 2000. Two methods— willingness-to-pay and human capital methods—are used to analyse the high and low points of estimation. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: Monetary evaluation; Air pollution; Road transport; China
1. Introduction The last decade has witnessed a dramatic increase in the number of motor vehicles in China, vehicles have risen four-fold in 25 years, China is now the fourth largest motor vehicle producer and the world’s third largest consumer. In 2003, the number of motor vehicles and motorcycles was 24.21 million and 59.29 million respectively, and forecast to rise 90 million and 192 million by 2020 (Li, 2004). This growth in the number of motor vehicle has serious economic and social implications for Chinese society and the economy. It will affect significantly urban lifestyle, and generate huge economic opportunities for various industries. On the other hand, the vehicle fleet’s rapid growth presents a challenge to urban authorities in that air quality may seriously deteriorate and traffic congestion will increase. Various measures, including new regulations and standards, have been introduced to address these issues. However, it is hard to know how effective these measures are without information regarding the magnitude of the economic damage caused by motor vehicles. Ironically, motor vehicle-related externalities are the result of the Chinese government’s efforts to raise the standard of living. Indeed, the most affluent super large cities suffer these external costs more than elsewhere in China. Several factors account for this. First, the vast majority of vehicles used in China are driven in major
E-mail address: [email protected] 1361-9209/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.trd.2006.02.004
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Table 1 Vehicle emissions in Beijing Vehicle category
Car Mini van Jeep LDGT HDGE MC
Units
g/km g/km g/km g/km g/kmh g/km
Average emission factors CO
HC
NOx
43.6 25.3 33.5 51.7 164.6 14.4
4.3 5.7 6.2 9.5 29.6 2.0
1.3 2.1 3.2 4.6 17.3 0.1
US model year of similar emission level 69–71 74–78 74–78 71–74 70 85–88
Note: LDGE—light duty gasoline truck, HDGE—heavy duty gasoline engine, MC—Motorcycle. Source: (Hao et al., 2000).
cities, and most private motor vehicles are registered there. Beijing, for example, accounted for 8.8% of the number of privately-owned vehicles in China in 2003, while its population accounted for only 1.1% of the population (National Bureau of Statistics of China, 2004). This is not only because residents in large cities are more affluent than rural residents, but also because the road infrastructure is much better developed. Second, less efficient technology makes the pollution level per vehicle much higher in China than in developed countries. Walsh (1996) estimates that the carbon monoxide (CO) and hydrocarbon (HC) emission levels of some domestically designed and manufactured engines are about 10–20 times the levels emitted from controlled vehicles in the US or Japan. He and Cheng (2000) also point out that the average emission factor per vehicle in China is several times higher than vehicle emissions in industrialized countries. Hao et al. (2000) show that the average emission levels of motor vehicles in Beijing in the late 1990s were equivalent to those in the US in the late 1970s (Table 1). Additionally, the fuel consumption of some vehicles is between 50% and 100% greater that the same type of vehicle manufactured in Western countries (He and Cheng, 2000). A survey of 3187 car owners shows that 46.3% of owners of medium to low class cars1 were unhappy with the noise level, and 39.2% complained about their car’s anti-shake function (Chen and Duan, 2001). While new standards for cars have been introduced in many large cities, and various measures, including installing catalytic converters, have been used to improve older vehicles’ environmental performance, emission levels are still substantially higher than international standards. Third, there is the high population density. The environment’s ability to ‘clean’ itself is much weaker in situations of high population density and many tall buildings; thus the interactions among different external factors are more likely to create a vicious circle. For example, a high accident rate worsens congestion, and low driving speed due to congestion results in higher levels of pollution. Tests conducted in China show that the emission level of carbon monoxide (CO) and hydrocarbon (HC) at speeds of 24 km/h are 60.5% and 73.8% higher than at the speed of 45 km/h (Fu et al., 2001). 2. The environmental problem 2.1. Urban air quality Air pollution is one of China’s most pressing environmental problems. This is mainly due to the rapidly deteriorating air quality in many large Chinese cities. The World Health Organisation (WHO) issues a list of the 10 most polluted cities in the world every year. In 1995, three Chinese cities—Beijing, Lanzhou and Taiyuan—were on this list (He and Cheng, 2000). In 2000, 9 out of the 10 cities with the worst air pollution in the world were from China (Sun, 2001). The World Health Organization (1999) annual mean guidelines for air quality standards are 90 lgm per cubic meter for total suspended particulates (TSP), and 50 lgm per cubic meter for sulphur dioxide (SO2) and nitrogen oxides (NOx). Table 2 shows that almost all major Chinese cities listed have exceeded the 1
Medium to lower class cars in this survey cover 10 models of five domestically made cars: Santana, Red Flag, Jetta, Citroen and Lingyang (Chen and Duan, 2001).
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Table 2 Air pollution level of selected cities Country
City
Total suspended particulates (lg/m3) 1995a
Sulphur dioxide (lg/m3) 1998b
Nitrogen dioxide (lg/m3) 1998b
China
Anshan Beijing Changchun Chengdu Chongqing Dalian Guangzhou Guiyang Harbin Jinan Kunming Lanzhou Nanchang Qingdao Shanghai Shengyang Taiyuan Tianjin Urumqi Wuhan Zhengzhou Calcutta Delhi Mumbai Jakarta Tehran Milan Mexico City Bangkok
305 377 381 366 320 185 295 330 359 472 253 732 279 – 246 374 568 306 515 211 474 375 415 240 271 248 77 279 223
115 90 21 77 340 61 57 424 23 132 19 102 69 190 53 99 211 82 60 40 63 49 24 33 – 209 31 74 11
88 122 64 74 70 100 136 53 30 45 33 104 29 64 73 73 55 50 70 43 95 34 41 39 – – 248 130 23
India
Indonesia Iran Italy Mexico Thailand
Source: World Development Indicators 2001. a Data are for the most recent year available in 1990–1995. Most are for 1995. b Data are for the most recent year available in 1990–1998. Most are for 1995.
pollutant level set by the WHO and the level of TSP of most is over 200 lgm per cubic meter. The TSP level in Lanzhou is as high as 732 lgm per cubic meter; more than 8 times the WHO’s standards, and twice as high as some well known polluted cities, such as Mexico City, Bangkok and Tehran. The level of SO2 varies greatly between cities, but only 4 cities conformed to the WHO’s standards. The level of SO2 in Guiyang and Chongqing are as high as 424 and 340 lgm per cubic metre, which are 7–8 times the WHO’s standards. The level of NOx is lower than the other two pollutants, but is still significantly higher than the WHO’s standards in most cases. 2.2. Air pollution from motor vehicles Motor vehicle emissions have become an important source of ambient air pollution. Walsh (2000) estimates that mobile sources are contributing approximately 45–60% of the NOx emissions and about 85% of the CO emissions in typical Chinese cities. Some have argued that urban air pollution in cities is shifting from a predominantly coal-burning type to a coal-vehicle mixed type or even a vehicular pollution dominant type (Fu et al., 2001; Shao and Zhang, 2001). The rapid increase of vehicular emission is especially obvious in some large cities. Motor vehicles accounted for 82.7% of CO and 42.9% of NOx emissions in Beijing in 1998, rising from 76.8% and 40.2% in 1995 (Department of Environmental Science and Engineering, 1999). Vehicles in Shanghai were estimated to have emitted 197,000 and 49,000 tons of CO and NOx in 1996, accounting for 86% and 56% of the total emissions of these two pollutants (Lu, 1998). Motor vehicles specifically contributed
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Table 3 National Ambient Air Quality Standards Pollutant (lg/m3)
SO2 TSP PM10 NOx NO2 CO O3
Time period
Annual average Annual average Annual average Annual average Annual average Daily average Hourly average
National Ambient Air Quality Standards Class one
Class two
Class three
20 80 40 50 40 4000 120
60 200 100 50 40 4000 160
100 300 150 100 80 6000 200
WHO’s Standard
50 90 50
Source: State Environment Protection Administration (GB 3095-1996). World Health Organisation Web site: www.who.int.
to 76% and 44% of the total emission of CO and NOx in 1995 (Cheng, 1997). Shao and Zhang (2001) estimate that vehicular emissions contributed 84% of CO and 25% of NOx in 1995. These figures could increase to 96% and 45% in 2010 if remediation policies are not implemented. Another sign of motor vehicles’ increasing contribution to air pollution is the rising level of NOx emissions in urban areas. While the ambient SO2 levels declined significantly and TSP levels dropped slightly in many urban areas between 1991 and 1998, NOx levels increased, reflecting the growing impact of vehicular emissions (World Bank, 2001). Fewer cities complied with class two National Ambient Air Quality Standards (NAAQS)—Table 3—for NOx in 1998 than in 1991. The World Bank (2001) estimates that total human exposure to ambient NOx levels above class two increased almost 60% during that period, with virtually all of the increase occurring in the 32 largest cities. Several studies have demonstrated a correlation between automobile emissions and elevated blood-lead levels in children in China (Li et al., 1992, 1994). Studies conducted in Shanghai also show that a newborn child’s risk of lead poisoning is associated with proximity to a major traffic way, along with other factors such as a family member’s exposure to lead at work, and household and neighbourhood coal combustion (Shen et al., 1996). Anecdotal evidence suggests that ambient lead levels have been rising over the past decade as vehicle use has increased (World Bank, 1997). The average lead concentration increased 12-fold between 1988 and 1995. In a heavy traffic area of Taiyuan, the capital of Shanxi Province, ambient lead concentration increased from 0.625 in 1990 to 1.803 in 1993 (Chen, 1995). The limited data available on fine particles (PM10 and PM2.5),2 suggest that the ambient PM level in many Chinese cities is a serious potential problem (Fu et al., 2001; He and Cheng, 2000). A study in 1995 estimated that the total exhaust PM10 and PM2.5 from motor vehicles in Beijing were 2445 tons and 1890 tons respectively, and by 1998 these levels had increased to 3359 tons and 2694 tons; a growth of 37.4% and 42.5% growth in three years (Wu et al., 2002). 3. Methodology The methodology used for estimating vehicle emission cost is based on studies conducted in other countries (Fisher et al., 2002; Sommer et al., 1999) as well as in China (World Bank, 1997). In particular it looks at Beijing in 2000. 3.1. Sample cities Beijing is the capital of China and has some unique features in terms of road infrastructure and vehicle ownership. The road system is composed of rings with radial arteries. The road around the Forbidden City is named the first ring, and ring roads beyond are the second, third, fourth and fifth ring roads according 2
PM10 refers to particulate matter with an aerodynamic diameter of 10 micrometres or less. PM2.5 consists of particulate matter with an aerodynamic diameter of 2.5 lm or less.
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Table 4 List of major policies targeting motor vehicle emissions launched by Beijing Municipal Government Year
Key policies
1995 1996 1997 1998
Implementing new emission standards for light vehicles New vehicles that do not reach the emission standards are not allowed to be sold Phasing out leaded petrol Scrapping 38,000 vehicles Implementing 18 urgent policies targeting coal-burning, vehicle emissions, and dust From Jan 1st, implementing new emission standards for light vehicles that are equivalent to European standards in the early 1990s Installing vacuum time delay valve for vehicles that were registered before 1995 Modifying 120,000 vehicles that were registered after 1995 Scrapping more than 30,000 vehicles 1st and 2nd stage air pollution control Applying new standards for heavy vehicles, diesel vehicles, agricultural vehicles and motorcycles Converting 26,000 taxis and buses into dual-fuel vehicles 3rd to 5th stage air pollution control Implementing environmental protection labelling system Vehicles without environmental protection label are not allowed to be on the road Implementing 2nd stage emission standards for light vehicles on August 1st New vehicles that have not reached the 2nd stage emission standards are not allowed to be sold and registered in Beijing Implementing 2nd stage emission standards for heavy motor vehicles and motorcycles
1999
2000
2001 2002 2003 2004
Source: Beijing Environment Protection Bureau, 1995–2005.
to distance from the centre of the city. The fourth ring road was fully operational in late 2000, the construction of the fifth ring road is completed, and work on the sixth ring road is scheduled to start in the near future. The area within the third ring is the city’s core, and most of the political and commercial institutions are located within it. Administratively, Beijing can be divided into three parts according to distance from the Central Business District (CBD). The city area comprises four districts: Dongcheng, Chongwen, Xicheng and Xuanwu. Most of this area is within the second ring road. Inner suburban Beijing comprises Chaoyang, Fengtai, Shijingshan and Haidian and is mainly within the third ring road. The remaining 10 suburbs are in outer suburban Beijing. Beijing has the largest motor vehicle fleet of any city in China and the vehicle fleet has increased from 784,300 in 1997 to 1.63 million in 2003. In 2003 Beijing accounted for more than 10% of newly registered civil passenger vehicles nationwide (National Bureau of Statistics of China, 1998, 2004). This dramatic increase presents a huge challenge for local authorities. Faced with rapidly deteriorating air quality, since the mid1990s, the Beijing municipal government has conducted aggressive campaigns targeting air pollution, and vehicle emission was one of the major concerns (Beijing Environment Protection Bureau, 1995–2005). Table 4 shows the new emission standards introduced almost every year over the decade. Emission standards for light vehicles, for example, were updated in 1995, 1999 and 2002, well ahead of the timetable set by the State Environmental Protection Administration. Furthermore, Beijing has been introducing various measures to reduce vehicle emissions, including scrapping vehicles, phasing out leaded petrol, installing vacuum time delay valves, modifying vehicles, and regular vehicle inspections. While there is not enough data to show a link between the introduction of new standards and improvements in air quality, we can observe an improvement in air quality over a number of years (Table 5). However, for over one third of each year, air quality in Beijing is still well below the national standards, and despite such aggressive policies, by 2003 Beijing was only ranked 27th out of 31 capital cities in terms of air quality (National Bureau of Statistics of China, 2004). Current emission standards in Beijing are comparable to Euro II—emission standards adopted by European countries in the late 1990s. Even if new standards are introduced, however, they are unlikely to have much impact on existing vehicles because a significant proportion of these were purchased in the last five years,3 and it is unlikely that they could be scrapped in the near future. While it is possible to further upgrade 3
56% of private vehicles and 39% of civil vehicles were purchase between 1999 and 2003 (calculated from China Statistical Yearbook 2004).
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Table 5 Air Quality in Beijing Year
SO2 (mg/m3)
CO2 (mg/m3)
CO (mg/m3)
PM10 (mg/m3)
TSP (mg/m3)
Proportion of days that air quality reaches Grade II of National Standards (%)
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
0.083 0.061 0.058 n.a 0.012 0.080 0.071 0.064 0.067 0.061 0.055
n.a n.a n.a n.a 0.074 0.077 0.071 0.071 0.076 0.072 0.071
n.a n.a n.a n.a 3.3 2.9 2.7 2.6 2.5 2.4 2.2
n.a n.a n.a n.a
0.337 0.337 0.323 n.a 0.378 0.364 0.353 0.370 0.373 n.a n.a
n.a n.a n.a n.a 15.4 (55.8a) n.a. (75a) 48.4 50.7 55.6 61.4 62.5
0.180 0.162 0.165 0.166 0.141 0.149
Source: Beijing Environmental Status Report (1994–2004). Numbers under each pollutant category are annual daily average figure for metropolitan areas. a The figures in the brackets indicate proportion of days that air quality reaches Grade III of National Standards (%).
technology, it will become much more difficult for local authorities to further improve air quality via this channel unless there is a technical breakthrough. 3.2. Evaluation methods A problem with using existing research, especially studies carried out in other countries, is the transferability of existing estimates to China. While most of the values are adjusted to fit China, there remains a problem of how to make the adjustment. We adopt two principles. One is the ‘‘at-least’’ principle, i.e. selecting the lowest value where a number of estimates are available. This ensures that the estimates are conservative. The other is the ‘‘at-best’’ principle, i.e. selecting the best possible method of transfer. The value of statistical life for China, for example, may be obtained by transferring other countries’ estimates. The basic adjustment method is to compare the Gross National Income (GNI) data for China with the GNI of other countries. This means using the ratio of China’s GNI and the target countries’ GNI to adjust the value estimated based on the situation in the target countries. This kind of adjustment is inevitably subject to criticisms of simplicity. However, a survey of 68 studies by Miller (2000) suggests that the income-elasticity of values across countries is roughly 1, suggesting it is reasonable to convert the values using the income ratio. Moreover, the World Bank also recommends this adjustment method in the absence of local estimates (World Bank Group, 1998). It is worth noting that none of the adjustment methods is perfect, given the differences between countries, the different time periods, and the scarcity of information about China. 4. Monetary costs of motor vehicle emissions This study follow the methodologies used in WHO (Sommer et al., 1999) and World Bank (1997) works. The WHO study estimated health costs due to road traffic related air pollution for three European countries: Austria, France and Switzerland. The World Bank study estimated total environmental costs in China. Air pollution costs form an important part of environmental costs. Both adopt a dose–response function, a willingness-to-pay method, and use PM10 as the indicative pollutant, however, the estimate of the function for the studies differs, as do the monetary valuations for deaths and illness. This is reasonable given the differences between China and the European countries. The major social costs of air pollution are negative human health effects. While road transport generates a mix of different pollutants, it is not possible to attribute a single health effect to one specific pollutant. An ‘‘indicator pollutant’’ is therefore used as a base to measure relevant health impacts of air pollution. Numerous epidemiological studies on the health effects of fine particles show that the association between ambient levels of fine particles and human health effects is statistically significant, and cannot be explained
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by confounding factors (Koch (2000). Given the available epidemiological data, PM10 is regarded as an important indicator for the health risks posed by pollution (Ku¨nzli et al., 1999). In fact, PM10 is reported to be the most prominent pollutant for the majority of China’s cities that have daily air quality reports. Normally, there are three steps to evaluate motor vehicle-related health costs in monetary term. First, an assessment on the exposure of the residential population is needed. Ideally, the results should describe the levels of concentration to which the number of people living in each geographical unit are exposed, and the road transport’s share of the pollution level. Second, an epidemiological study evaluating the exposure–response relationship between air pollution and effects on health should be conducted. The study should provide the number of cases of morbidity and mortality attributable to air pollution. Last, the quantified health impacts have to be converted into monetary terms via an adequate method. 4.1. Population exposure We adopt the annual average level of ambient concentration of PM10 in Beijing as a base to assess the exposure of its residential population. Beijing started to publish data on annual average daily concentration of PM10 in 1999 (Beijing Environment Protection Bureau, 2001). This is calculated on the basis of data from 13 monitoring sites, however, detailed information on the annual ambient concentration of PM10 of each site cannot be obtained.4 While there are a few studies of particles in some Chinese cities, none of them provides data for every part of a designated city; some give partial coverage (He et al., 2001) others compare monitoring sites in several cities (Wei et al., 1999). Moreover, most of the studies focus on the composition of fine particles, and do not provide information on the exposure of the residents. Since it is not possible to obtain information on population exposure from current research, estimates are based on other countries. The WHO’s study showed that around 60% of the population are exposed to a level equal to, or higher than, the average level of PM10. While the figure might be higher, given the significantly higher level of PM10, as a conservative estimate, we assume that 60% of the population in Beijing were exposed to an ambient of PM10 concentration level at 162 lg/m3 in 2000. The WHO study estimates that the share of PM10 concentration attributable to road transportation increases with the level of total PM10 concentration. The road traffic’s share rises from 28%, with a total PM10 concentration level of less than 10 lg/m3, to 58% with a total PM10 concentration level higher than 40 lg/m3 (Filliger et al., 1999). As a general rule, European studies suggest that the road traffic share of secondary particles is equivalent to the portion of SO2, NOx and NH3 emission caused by traffic (EMEP, 1998). If we follow that rule, the share of motor vehicles to total PM10 pollution would be higher than 40%, which is similar to the figure that previous studies suggest as the contribution of motor vehicles to NOx emission in Beijing (He and Cheng, 2000). China’s situation is, however, different from European countries. While the PM10 concentration in Beijing is much higher than 40 lg/m3, even 58% could be an overestimation. The quality of the natural environment in most European countries is superior to China. Some common pollution sources in China, such as coal combustion and mineral dust do not often have a significant impact on the environment in Europe. A study of particulate pollution in Xi’an, the capital of Shaanxi Province, estimates that motor vehicle emissions contributed about 25% of PM10, while the shares of the other two sources were 24% and 22%, respectively (Zhuang et al., 2000). With a much larger motor vehicle fleet,5 motor vehicles’ contribution to PM10 should be higher in Beijing, however, 30% is used as a conservative estimate. 4.2. Dose–response function The second step is to find out the exposure–response relationship between the pollutant and health effects. A number of epidemiological studies on air pollution and health effects have been conducted in China. Their results showed that ambient air pollution had acute and chronic effects on mortality, morbidity, hospital
4 5
The Department of Environment Monitoring in the Beijing Environment Bureau indicates that each site’s data is confidential. The number of motor vehicles in 2000 Shaanxi province was 364,700; about one third of that in Beijing.
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admissions, clinical symptoms, and lung function changes. Based on this, an exposure–response function has been devised by different research groups (Chen et al., 2004). There are some studies on the statistical relationship between air pollution and health outcomes in several Chinese cities. However, only one study analysed the health impacts of fine particulates, and it found a 40% increase of cardiovascular disease mortality resulting from a 100 lg/m3 increase in ambient concentration of particulates (World Bank, 1996). Other studies have mainly examined the relationship between daily mortality and two pollutants: SO2 and TSP (Xu et al., 2000). While these studies show that air pollution has some impact on health, they do not provide enough information to develop a dose–response function. The dose–response function of PM10 presented by the World Bank (1997) estimated the number of additional deaths or cases per 1 million people for a 1 lg/m3 increase in ambient concentration of PM10. The WHO based its estimation on relative risk estimates (Sommer et al., 1999). Both studies discussed similar diseases. Due to the lack of relevant epidemiological data in China, we are unable to convert the relative risk estimated by the WHO into numbers of additional cases. however, a comparison between the World Bank’s estimates for China and the WHO’s estimates for three European countries (Ku¨nzli et al., 1999) suggests a lower mortality and a higher morbidity rate in the World Bank’s work (Table 6); the number of additional deaths per one million people for every 1 lg/m3 increase in ambient concentrations of PM10 is 6, according the latter. The WHO’s study estimated that the number of premature fatalities increase by 4.3% for every 10 lg/m3 PM10 increment. Based on the mortality rate caused by disease in urban areas in China in 2000 (National Bureau of Statistics of China, 2001) and the World Bank Group (1998), the number of premature fatalities caused by every 1 lg/ m3 PM10 increment should be 26 in 1 million people. The WHO’s estimation for three European countries ranged from 33.7 to 37.4 (Sommer et al., 1999). 4.3. Monetary valuation The most controversial part of the estimation is the monetary valuation of the health effects that can be based on two approaches: willingness-to-pay and cost methods. The former assesses the amount people are willing to pay to reduce the risk of illness or death. Contingent valuation surveys, wage risk studies and consumer behaviour studies may be used to determine a value of willingness-to-pay. The cost approach values mortality and morbidity impacts according to the loss in income (or production) plus out-of-pocket expenditures. The human capital approach used by the World Bank (1997) is a cost approach. While the human capital approach has the advantage of simplicity, it may seriously underestimate costs, as the lives of those without income can be valued at zero, which is not realistic. As a result, the preferred approach to
Table 6 Health impacts of PM10 Health impactsa
The WB’s estimation for Chinab
Relative risk estimated by the WHOc
Increment estimated by the WHO for Franced
Mortality (deaths) Respiratory hospital admissions (cases) Cardiovascular hospital admissions (cases) Emergency room visits (cases) Restricted activity days (days) Lower respiratory infection/child asthma (cases) Asthma attacks (cases) Bronchitis (cases) Chronic bronchitis (cases) Respiratory symptoms (cases)
6 12 n.a 235 57,500 23 2608 n.a 61 183,000
1.043 1.0131 1.0125 n.a 1.094 1.044 1.039 1.306 1.098 n.a
34 15 21 n.a 26,370 260 619 483 39.4 n.a
a
Number of additional deaths, cases, or days per 1 million people for every 1 lg/m3 increase in ambient concentrations of PM10. Source: The World Bank (1997), estimates are based on China. c Source: (Ku¨nzli et al., 1999), estimates are based on Austria, France and Switzerland. d Original estimates were based on 10 lg/m3 increase in ambient concentrations of PM10. They were converted assuming a linear relationship between PM10 and health effects. b
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Table 7 Health costs of road transport Health impacts
Mortality (deaths) Respiratory hospital admissions (cases) Emergency room visits (cases) Restricted activity days (days) Lower respiratory infection/ child asthma (cases) Asthma attacks (cases) Chronic bronchitis (cases) Respiratory symptoms (cases) Total costs a
Cases attributable to road traffica
Monetary valuation of mortality and morbidity (USD)
Costs attributable to road traffic (1 mil USD)
Willingness-to-pay
Human capital
Willingness-to-pay
1876 3751
105,000 966
15,650 496
196.935 3.624
Human capital 29.353 1.859
73,460 17,974,224 7190
73 12 23
40 4 23
5.363 215.691 0.165
2.948 72.767 0.163
815,248 19,068 57,204,922
7 25,644 1
7 2087 1
5.707 488.988 57.205 973.677
5.690 39.796 57.205 209.781
Calculated based on the assumption of 60% urban population exposure in Beijing in 2000.
environmental damage evaluation has shifted from the human capital to the willingness-to-pay approach. The human capital approach, however is used here as an indicator as a lower limit. The World Bank study used an indirect approach to the problem by converting relevant data from the US, and in the absence of local data, this seems to be the best way to address this issue. As discussed, the dose–response function of the World Bank and the WHO studies cover similar diseases (Table 6). This study follows the dose–response function recommended by the World Bank (1998) but the values used are converted from the WHO’s estimates, except for values of emergency room visits, bronchitis and respiratory symptoms, which are not covered by the WHO’s dose–response function. The reasons for abandoning the values used in the original World Bank study for willingness-to-pay estimates are three-fold. First, the WHO’s estimation was based on studies of various countries, and hence may represent a more comprehensive estimation. Second, the World Bank’s estimates were conducted in 1995, and since then per capita income in China has increased considerably. Finally, the original valuations were based on the whole nation. Since both the per capita GDP and the wages in Beijing were much higher than China’s national average,6 the valuation should be much higher in both willingness-to-pay and human capital approaches. As the World Bank’s estimates derived from the human capital approach were based on the nationwide average wage rate in 1995, these estimates have to be revised to reflect the difference between the nationwide average wage rate in 1995 and Beijing’s wage rate in 2000. The WHO’s estimation is converted firstly by using per capita GNI of China and the European Union in 2000. It is then adjusted by the ratio of Beijing’s per capita GDP to that of the national average for China. As a result, the conversion factor for Beijing is 0.1227; multiplied by the values estimated by the WHO, this yields a value of statistical life of $171,640 for Beijing. This is based on the figure of €1.4 million estimated by the WHO. Following the WHO’s method, the original value of life is discounted at the rate of 60% to take into account that most victims of air pollution are aged people, and that their willingness-to-pay for preventing fatalities will decline after a certain age. Therefore the figure adopted for is $105,000. Two matters need further clarification. One is whether this result is an overestimation. Miller (2000) suggests that the value of statistical life is typically about 120 times GDP per capita after reviewing 68 studies spread across 13 countries. If this is the case, the value of life in Beijing should be $324,723 in 2000, which is nearly double the estimate obtained used here. The other issue is whether it is necessary to further adjust the value by the per capita GDP of Beijing. If the values are to be used for decision-making across regions, it may seem unfair and politically unwise to vary the value of statistical life between residents of different regions, however, the purpose of this estimate is to provide information on the magnitude of external costs
6
In 2000, per capita GDP in Beijing was RMB22,460, while the national average was RMB7,078; and the average wage in Beijing was RMB16,350, while the national average was RMB9,371 (all at current prices).
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concerning motor vehicles in Beijing. Adjustment is, therefore, necessary to reflect the higher willingness-topay value due to higher income. Table 7 shows the health costs attributable to road traffic. Under the assumptions that 60% of the urban population was exposed to air pollution and that air pollution from motor vehicles killed 1876 people in Beijing in 2000, while the number of people killed in road accidents was 1470 in the same year. Road traffic also accounted for 3751 cases of respiratory hospital admissions and 19,068 cases of chronic bronchitis. In Beijing in 2000, the costs attributable to road transport were $974 million according to the willingness-to-pay approach and $210 million according to the human capital approach. In both approaches the costs of morbidity were predominant, accounting for 80% of the total costs according to the willingness-to-pay, and 86% according to the human capital approach. By comparison, in the WHO’s study the mortality costs predominate, and amounted to between 70% and 75% of the costs (Sommer et al., 1999). In Beijing in 2000, the total costs of air pollution caused by road transport were equivalent to 3.26% of GDP, according to the willingness-to-pay approach and 0.7% following the human capital approach respectively. The first figure may be treated as the high end of the estimation, and the other as the low end. These estimates are still conservative; apart from the reasons discussed, Ying et al. (2002) looking at urban air pollution sources in Beijing found that the PM10 and NOx exposure efficiency7 of transport are the highest of all pollution sources indicating that transport may cause more damage than other pollution sources with the same amount of pollutants emitted. Further, while the ambient level of PM10 in three European countries stood between 21 and 26, air pollution related costs were estimated to be between 1.5 and 3.25 of GNI in these countries. Finally, one would expect that the figure for Beijing would be much higher than for China as a whole because motor vehicle ownership levels are higher than most other cities. References Beijing Environment Protection Bureau, 1995–2005. Report on the State of Environment of Beijing (1994–2004). Beijing Environment Protection Bureau, Beijing. Chen, S.L., 1995. China Vehicle Pollution Management: Challenges and Prospects. Chongqing Environmental Bureau, Chongqing (in Chinese). Chen, Y.S., Duan, Y.D., 2001. Survey revealed that cars between low and medium price range need to improve from eight aspects, China Automobile, November 13, (in Chinese). Chen, B., Hong, C., Kan, H., 2004. Exposures and health outcomes from outdoor air pollutants, China. Toxicology 198, 291–300. Cheng, C.H., 1997. Pollution load of vehicular exhaust in shanghai (in Chinese). Shanghai Environmental Sciences 16, 26–29. Department of Environmental Science and Engineering, 1999. Research Report of Planning of Vehicle Emission Pollution Control in Beijing City. Tsinghua University, Beijing. EMEP, 1998. Long-Range Transport of Fine Secondary Particles. Norwegian Meteorological Institute, Oslo. Filliger, P., Puybonnieux-Texierh, V., Schneideri, J., 1999. PM10 Population Exposure: Technical Report on Air Pollution. World Health Organisation, London. Fisher, G.W., Rolfe, K.A., Kjellstrom, T., Woodward, A., Petersen, A., Shrestha, R., King, D., 2002. Health Effects Due to Motor Vehicle Air Pollution in New Zealand. Ministry of Transport, Wellington. Fu, L.X., Hao, J.M., He, D.Q., He, K.B., 2001. Assessment of vehicular pollution in China. Journal of Air and Waste Management Association 51, 658–668. Hao, J.M., He, D.Q., Wu, Y., Fu, L.X., He, K.B., 2000. A study of the emission and concentration distribution of vehicular pollutants in the urban area of Beijing. Atmospheric Environment 34, 453–465. He, K.B., Cheng, C., 2000. Present and future pollution from urban transport in China. China Environment Series: Woodrow Wilson Center, Washington, DC. He, K.B., Yang, F.M., Ma, Y.l., Zhang, Q., Yao, X.H., Chan, C.K., Cadle, S., Chan, T., Mulawa, P., 2001. The characteristics of PM2.5 in Beijing, China. Atmospheric Environment 35, 4959–4970. Koch, M., 2000. Airborne Fine Particulates in the Environment: A Review of Health Effect Studies, Monitoring Data and Emission Inventories. International Institute for Applied Systems Analysis, Luxemburg. Ku¨nzli, N., Kaiserb, R., Medinab, S., Studnickac, M., Chaneld, O., Filligere, P., Herry, M., Puybonnieux-Texierh, V., Que´nel, P., Schneideri, J., Seethalerj, R., Vergnaudk, J.-C., Sommer, H., 1999. Health Costs Due to Road Traffic-Related Air Pollution, Air Pollution Attributable Cases. An Impact Assessment Project of Austria, France and Switzerland. World Health Organisation, London.
7
Exposure efficiency is defined as the proportion of pollutants that is absorbed by the human body (Ying et al., 2002). The higher the efficiency is, the more damage it causes on human health.
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Li, X., 2004. Current situation and policies of motor vehicle emission in China. Accessed. 2004:Dec 2. State Environment Protection Administration, Department of Pollution Control, Beijing. (in Chinese). Available form: