Article pubs.acs.org/est
Black Carbon Emissions in China from 1949 to 2050 Rong Wang,† Shu Tao,*,† Wentao Wang,† Junfeng Liu,† Huizhong Shen,† Guofeng Shen,† Bin Wang,† Xiaopeng Liu,† Wei Li,† Ye Huang,† Yanyan Zhang,† Yan Lu,† Han Chen,† Yuanchen Chen,† Chen Wang,† Dan Zhu,† Xilong Wang,† Bengang Li,† Wenxin Liu,† and Jianmin Ma‡ †
Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China Air Quality Research Division, Science and Technology Branch, Environment Canada, 4905 Dufferin Street, Toronto, Ontario M3H 5T4, Canada
‡
S Supporting Information *
ABSTRACT: Black carbon (BC) emissions from China are of global concern. A new BC emission inventory (PKU-BC(China)) has been developed with the following improvements: (1) The emission factor database was updated; (2) a 0.1° × 0.1° gridded map was produced for 2007 based on county-level proxies; (3) time trends were derived for 1949−2007 and predicted for 2008−2050; and (4) the uncertainties associated with the inventory were quantified. It was estimated that 1957 Gg of BC were emitted in China in 2007, which is greater than previously reported. Residential coal combustion was the largest source, followed by residential biofuel burning, coke production, diesel vehicles, and brick kilns. By using a county-level disaggregation method, spatial bias in province-level disaggregation, mainly due to uneven per capita emissions within provinces, was reduced by 42.5%. Emissions increased steadily since 1949 until leveling off in the mid-1990s, due to a series of technological advances and to socioeconomic progress. BC emissions in China in 2050 are predicted to be 920−2183 Gg/yr under various scenarios; and the industrial and transportation sectors stand to benefit the most from technological improvements.
■
INTRODUCTION Black carbon (BC) is released into the environment during incomplete combustion of carbonaceous fuel, and is a major concern because of its impacts on climate systems.1,2 Asia contributea more than half of global anthropogenic BC emissions and China was the largest emitter, due to its large population, substantial fuel consumption, and often-inefficient combustion conditions.3,4 BC emissions in Asia have also been identified as a major cause of the changing monsoon,5 the occurrence of the atmospheric brown cloud,6 and the retreat of Tibetan glaciers.7 In addition, mitigation strategies designed to reduce BC emissions can complement CO2-focused climate change mitigation efforts in the region.2,8 BC emission in China has been estimated previously based on emission factors (EFBC, mass of BC emitted per mass fuel consumed or product produced) and energy consumption data. Estimated annual BC emissions in China varied from 1049 to 1811 Gg between 1995 and 2006.3,4,9−15 The large variations in EF BC reported in the literature and the lack of EF BC measurements, especially in developing countries, were the major sources of uncertainty in the previous emission inventories.3,4 In fact, many EFBC used in previous inventories were converted from particulate matter (PM) measurements and BC/PM ratios.3,9,10 Recently, more progress in EFBC characterization has been made by direct measurements or modeling; new measurements characterizing EFBC for motor vehicles and residential biomass fuel burning in developing © 2012 American Chemical Society
countries were found to be higher than those previously estimated.16,17 Two regression equations have been developed to model the variations in EFBC for motor vehicles among countries and over time based on socioeconomic parameters.18 These new developments provide an opportunity to improve BC emission inventories. In addition, BC emissions were sometimes spatially disaggregated using population proxies at national or provincial-level;3,4,9−12,14,15 however, if development is dramatically unbalanced at the national or subnational level, it can lead to high spatial bias in these maps.13,19 The objective of this study was to develop a new BC emission inventory for China (PKU-BC(China)), including a 0.1° × 0.1° gridded map for 2007 based on county proxies and a time series of BC emissions from 1949 to 2050. Effort was also made to reduce overall uncertainty by subdividing major source categories by the specific combustion technologies used and providing detailed emissions information for each;3 and by using the model to predict EFBC for motor vehicles based on per-capita gross domestic product (GDPc).18 The 2007 emission map was compared with a province-level disaggregated map and two previously reported inventories.4,12 Finally, Received: Revised: Accepted: Published: 7595
January 29, 2012 June 9, 2012 June 25, 2012 June 25, 2012 dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
Environmental Science & Technology
Article
39 subtype sources (Table S1), and emissions were estimated for each. Quantification of the Technology Divisions. Coal consumption in power stations (7 types), industrial boilers (4 types), and centralized heating boilers (4 types) were further divided by specific emission-related technology. For example, industrial boilers were divided into three subcategories: fluidized-bed/electrostatic precipitator, stokers with control devices, or stokers without control device. The fraction of coal consumption in each individual technology subcategory, for a given year, was calculated using S-shaped curves used in the previous inventories.31−33 The equation and input parameters are listed in Table S2. The fact that many control devices might not be operating at all times was taken into account.34,35 Xu reported that scrubbers were not in operation 20% of the time in China; 35 The National Development and Reform Commission lists noncompliance rates of 60%.36 Based on these estimates, a median value of 40 ± 20% (uniform distribution) noncompliance was used in this study, for control devices in power plants, industrial boilers, and centralized heating systems. Since tunnel kilns are not common for brick production in China, a constant fraction of 10% in all brick kilns was used.37 For coke ovens, the ratio of beehive to recovery battery was derived from CESY (national, 1949−2000) 22 and the Association of Iron and Steel Industry (provincial, 2001− 2007).38 It was assumed that beehive coking was gradually phased out from 2007 to 2010.39 CESY ratios of residential chunk coal to briquette combustion were used for all provinces from 1985 to 2007.22 Without data for other years available, the ratios reported for 1985 and 2007 were applied to all years before 1985 and after 2007, respectively. The fraction of gasoline used by two-stroke engine vehicles for each province was calculated based on the number proportions of cars, motorcycles, and other vehicles in all gasoline vehicles between 1998 and 2007.40 The fraction in 1990 was applied to the years before 1990, and the fraction after 2007 was derived from the prediction by Huo et al.24,26,41 For both gasoline and diesel vehicles, it was assumed that 20% of vehicles were super emitters with abnormally high emissions.3 Provincial-level fuel consumption in 1985, 1995, 2005, and 2007 is listed in Table S3; the national fuel consumption in China from 1949 to 2050 (5-year interval) is listed in Table S4. EFBC. EFBC values for normal gasoline (four-stroke) and diesel vehicles were predicted at the provincial (2000−2007), county (2007), and national (other years) levels, using two regression models.18 The original vehicle EFBC compiled for model development can be found in the literature.18 It was assumed that the EFBC for two-stroke gasoline vehicles were 5 times that of four-stroke vehicles3 and the EFBC for super emitters were 3.8 times that of the normal vehicles.18 With very limited measured EFBC available for motor vehicles, relatively high uncertainty in EFBC for motor vehicles is expected and more measurements of various vehicle types are needed in the future. For the remaining sources, a relationship was observed between EF of fine particles (EFPM) for recovery coking and GDPc. A regression model was developed to predict EFPM (Figure S2), which was converted to EFBC using the fraction (0.9) of BC in fine particles emitted during recovery coking.42 For other emission sources, a literature review was conducted to collect relevant EFBC. All the EFBC used in the inventory are summarized in Table S1. The data set includes both BC (optically measured) and EC (elemental carbon, thermally
implications of the inventory are discussed, focusing on BC emission-related energy policy and climate mitigation strategy.
■
METHODOLOGY BC Emission Sources and Energy Consumption Statistics. Twenty-two BC emission sources including both anthropogenic and natural sources (savanna and forest fires), are included in PKU-BC(China) and listed in Table S1, together with EFBC values, references, and the detailed data sources for coke production, open-fire agricultural waste burning, and wildfires. For the remaining sources, the following fuel consumption data were used: national data from the United Nations Statistics Division (1949−1970),20 national data from the International Energy Agency (IEA) (1971− 1979),21 provincial data from the China Energy Statistics Yearbook (CESY) (1980−2007),22 and predicted national data from the National Long-term Development Plan (NLDP) (2008−2050).23 In addition, predicted oil consumption for use in motor vehicles between 2008 and 2050, based on series of socioeconomic variables by Hou et al.,24−26 were used to develop the inventory. County-level fuel consumption in 2007 was derived for 2373 counties using a set of provincial data-based regression models.19 By comparing fuel consumption data (1980−2007) from IEA21 and CESY provincial statistics,22 it was found that IEA statistics underestimated coal consumption in the residential and industrial sectors from 1988 to 2007, petroleum consumption by motor vehicles from 2003 to 2007, and coke production from 1980 to 1996 (Figure S1), because the fuel produced or consumed by local units has not been taken into account. The IEA statistics are based on national statistics from the Energy Research Institute, which are provided by key state energy producers. As a result, the use of coal from small local mines is included in the provincial statistics, but not in the national statistics.27 Similarly, consumption of oil by a large number of nonstate-owned small refineries before 2003 was counted only in the provincial statistics, but not by the national statistics.28,29 In addition, a large number of small-scaled beehive coke ovens operating in the 1990s were missed in the national statistics.28 As a result, the total energy consumption based on provincial data in CESY were higher than that in IEA statistics with a relative difference of 14.6−39.6%. The possible underestimation of national emission statistics has been corroborated by NOx emission trends based on the energy statistics and observed by the satellite images.12,30 Considering the information presented here, provincial fuel consumption data provided by CESY for 1980−2007 were used in this study. Of the 22 sources considered, BC emissions from coal combustion in power stations, industrial boilers, brick kilns, coke ovens, centralized heating boilers, and residential stoves was strongly affected by process type or abatement technology, resulting in a wide range of EFBC. This was also true for motor vehicles. These source categories were further divided into technology subcategories. For example, coke production was divided into the subcategories of beehive and recovery battery ovens; and coal-fueled industrial boiler use was divided into 4 subcategories: fluidized-bed furnaces with electrostatic precipitators, stokers with cyclone, scrubbers, or no control device at all. Similarly, motor vehicles using either diesel or gasoline were classified into two subcategories (normal and super emitters), while gasoline vehicles were further allocated to two-stroke and four-stroke vehicle subcategories. As a result, there are a total of 7596
dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
Environmental Science & Technology
Article
Figure 1. Comparison of relative contributions from various sources to total BC emissions between China and other countries/regions including India, North America, and Africa. Detailed source types are provided for China’s inventory; data are available only for major source types for the other countries/regions.3.
firewood, and crop residues. Urban population47 was used as a proxy for coal consumption in urban households and centralized heating boilers, as well as aviation kerosene consumption. CO emissions48 from road transportation were used as a proxy for on-road motor vehicles. Finally, total population49 was used as a proxy for all other sources except for wildfires. The 0.5° × 0.5° GFED data for forest and grassland fires were further disaggregated to 0.1° × 0.1°, using vegetation biomass as a proxy.50,51 This reanalyzed product was used to estimate wildfire BC emissions across China in 2007. For the period 2008 to 2050, annual BC emissions from anthropogenic sources in China were predicted for baseline and low-carbon scenarios based on fuel consumption data from NLDP.23 For motor vehicles (diesel and gasoline) and recovery coke production, EFBC were predicted by using the regression models listed above and the GDPc published by the World Bank.52 Small-scaled brick kilns have recently begun to be phased out in many places in China.53 The phase-out period used in this study began in 2010 and had a transition time of 50 years. It is anticipated that new regulations for off-road diesel machinery, similar to those in the U.S., will be in force in China in 2020 (ten years later than U.S.). Implementation of these regulations is expected to result in an 80% reduction of PM (also BC) emissions.54 Two S-shaped curves were used to quantify the fraction of small-scaled brick kilns and off-road diesel machinery projected to meet the new regulations, and the parameters are listed in Table S2. Since the quantification of these technological advances was highly uncertain, two other scenarios (baseline-high, low-carbon-high) were also calculated for comparison with the EFBC and all technology divisions held at 2007 levels. Uncertainty Analysis. A Monte Carlo simulation (10 000 runs) was conducted to characterize the uncertainty of the
measured). Although the ratio of EC to BC varies with the nature and aging of the deposited particles,43 EC was used as an equivalent to BC in this study, following common practice in the literature.3 A few outliers were detected using Grubb’s test after log-transformation (α = 0.05) and removed from the database (listed in Table S1), since the reported EFBC are lognormally distributed (p > 0.20) (Figure S3). Specially, for residential sectors, the data collected come from measurements conducted in China or other developing countries of similar technology status. EFBC for coke production and brick kilns, the two most important industrial sources of BC, have unfortunately never been directly measured in China. In PKUBC(China), EFBC for coke production were converted from previously reported EFPM that were measured in China44,45 and the reported fraction of BC in PM emitted during coke production.3 For brick production, the EFBC used in previous inventories were adopted.3 A relatively large variation in the EFBC for these two sources was assumed in uncertainty analysis (Table S1). For the five coal combustion sources that were divided into technology subcategories, individual EFBC were compiled for each subcategory. Development of BC Emission Inventory. Based on the fuel consumption and EFBC data compiled, annual BC emissions in China were calculated from 1949 to 1979; annual BC emissions were calculated by province from 1980 to 2006 and for all 2373 counties in 2007. County-level 2007 BC emission data were further disaggregated into 0.1° × 0.1° grids using various proxies, with the exception of 151 major power stations (78% of total coal consumption in all power stations), for which emissions were directly allocated to individual grids based on their geographic positions46 (Table S5). Rural population47 was used as a proxy for open-burning of agricultural waste and rural residential burning of coal, 7597
dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
Environmental Science & Technology
Article
Figure 2. BC emission map of China at 0.1° × 0.1° for year 2007. East and West China are separated by a dashed line from Qiqihar, Yinchuan, to Kunming. Major emission areas are marked.
last century, low-quality chunk coals with relatively high EFBC are still widely used.18 Among industrial activities, coke production ranked highest in BC emissions (341 Gg BC), of which 233 Gg was from beehive coke ovens. BC emissions from motor vehicles were primarily from diesel engines (85%). Generally, the source distribution pattern of BC in China was similar to that in India, but very different from those in African countries, where wildfires dominate the emission totals, or those in developed countries, where motor vehicles contribute to more than half of the total emissions3 (Figure 1). Geographical Distribution of BC Emission in China. BC emissions in 2373 counties were calculated for the year of 2007 and further disaggregated to 0.1° × 0.1° grids (Figure 2). Average emission densities in eastern China (0.437 Mg/ (km2·yr)) were more than 1 order of magnitude higher than those in the West (0.033 Mg/(km2·yr)); the two regions are separated by a dashed line extending from Qiqihar, Yinchuan, to Kunming (Figure 2). Contributions of residential coal (34%) and coke production (19%) in western China were much higher than those in the East (21 and 7.6%, respectively). Very high emission densities can be found in the North China Plain, Northeast Plain, Shanxi Highland, Henan Mountains, and Sichuan Basin-Guizhou Plateau. Relatively high BC emissions can be found in almost all large cities (including Urumqi in remote west), where population, vehicles, and industries are concentrated. High emissions can also be found in populated rural areas, such as those in the provinces of Shandong, Henan, Shanxi, and Sichuan, where rural solid fuel burning and coke ovens are the major sources.19 To evaluate the improvement of the county-level disaggregation method, a mock-up emission inventory (PROBC(China), for anthropogenic sources) was established using the same methods as were used to create PKU-BC; however, provincial fuel data and proxies were applied, rather than county-level data and proxies. Results from PRO-BC(China) were compared to the standard PKU-BC. In the comparison, a relative difference was defined as RD = (E1 − E2)/((E1 + E2)/ 2), where E1 and E2 are the total anthropogenic BC emissions
inventory based on the variations in fuel consumption and EFBC. For fuel consumption, uniform distributions with fixed coefficients of deviation (5 and 10% for the periods before and after 2008, respectively) were assumed.12,55 Log-normal distribution was adopted for EFBC with variation coefficients listed in Table S1. Medians and R50 were calculated to quantify the emissions and characterize the uncertainties.
■
RESULTS AND DISCUSSION BC Emissions in China in 2007. According to PKUBC(China), annual BC emissions in China were 1957 Gg (median, 1238−3077 Gg as R50) in 2007, among which 988, 646, 50.7, 188, and 77.7 Gg were from residential, industry, power plants, transportation, and outdoor biomass burning, respectively. Total emissions, as estimated in this study for 2007, were higher than that reported by Bond et al. (1489 Gg, all sources, 1996),3 Cao et al. (1499 Gg, all sources, 2000),11 Ohara et al. (1137 Gg, anthropogenic source, 2003),12 and Zhang et al. (1811 Gg, without biomass burning, 2006).4 This is largely due to the updated EFBC for residential fuels, industrial activities, and motor vehicles, as well as the inclusion of biomass burning sources and a noncompliance rate of control technologies in the PKU-BC(China) inventory. However, the lack of sufficient EFBC measurements is still a major source of uncertainty in the inventory. For many important emission sources, including coke production, brick kilns, and small-capacity industrial boilers, making additional EFBC measurements in China in the future could help to improve the inventory significantly. Relative contributions of various sources are presented in Figure 1. The major sources were residential coal (28.0%), residential biomass (22.7%), coke production (17.6%), diesel vehicles (8.2%), and brick kilns (7.4%). Residential use of solid fuels, including coal, firewood, and crop residues, contributed to more than half of the total BC emissions in China, and 83% of them occurred in rural areas. Coal is used widely in Chinese households for cooking and heating. Although chunk coal was increasingly replaced with honeycomb briquettes at the end of 7598
dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
Environmental Science & Technology
Article
Figure 3. Geographic (A) and frequency (B) distributions of RDs calculated to demonstrate the improvement of using county-level disaggregation over provincial disaggregation. A positive (negative) RD indicates an underestimation (overestimation) of the county’s emissions by using the provincial disaggregation approach (PRO-BC(China)).
Figure 4. Geographic distributions of RDs of anthropogenic BC emissions between the PKU-BC(China) (2007) and REAS (2003) (A) and between the PKU-BC(China) and INTEX-B (2006) (B). For comparison, PKU-BC(China) was downscaled to 0.5° × 0.5°. A positive (negative) RD indicates relatively high (low) value in the PKU-BC(China) model.
in counties. E1 and E2 are the emissions for each county in the PKU-BC and PRO-BC, respectively. According to the definition, the higher the absolute RDs are, the larger the spatial bias of the provincial disaggregation. Geographic and frequency distributions of RDs for all counties are shown in Figure 3. The average absolute RD for all counties was 42.5%; absolute RDs of 30% of the counties were greater than 50%, indicating a substantial reduction in spatial bias by using the county fuel data. Large RDs were often found in the provinces where development status varied dramatically spatially, such as Inner Mongolia, Qinghai, and Hainan.19 PKU-BC(China) (2007) was also compared with two previously developed inventories, REAS12 (anthropogenic, 0.5° × 0.5°, 2003) and INTEX-B4 (anthropogenic, 0.5° × 0.5°, 2006), both of which are based on provincial proxies. Although there are 1−4 years of difference in the data considered, the spatial pattern is not expected to change significantly. This time, RDs were calculated at 0.5° × 0.5° resolution, and E1 and E2 are the anthropogenic BC emissions in each 0.5° × 0.5° grid cell in the PKU-BC(China) and REAS or INTEX-B inventory, respectively. The results are mapped in Figure 4. Significant differences in BC emissions in many areas can be seen between the PKU-BC(China) and the two inventories. Very high RDs in Tibet and Xinjiang were likely
due to the lack of data for these areas in previous inventories. The positive RDs in northern China (Figure 4A) are primarily attributable to the relatively high EFBC for residential solid fuels used in this study. The negative RDs in southeast China (Figure 4B) likely resulted from the different motor vehicle EFBC applied to various counties in our model. In addition, high emission density abnormalities in counties within a province can only be revealed by the county disaggregation-based PKUBC(China) model. For example, very high emissions at Yulin, where a large volume of coal was produced and consumed,56 was averaged within Shanxi by REAS and INTEX-B. Similarly, negative RDs in dozens of counties in the Great Khingan area are likely due to the relatively low per capita fuel consumption in this forest area.19 The geographic distribution of the emissions has implications for the spatial distribution of BC in ambient air and its effect on climate forcing. BC emitted in southern China has high potential to contribute to the Atmospheric Brown Cloud in East Asia,6 while emissions occurring in Northeast China could be transported to the Arctic by high-altitude airflow, causing snow/ice albedo change there.57,58 The high-resolution inventory developed in this study can help to identify the fate and long-range transport pathways of BC emitted from China. As a simple example, results of forward air mass trajectories 7599
dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
Environmental Science & Technology
Article
Figure 5. Time series of annual BC emissions in China. (A) The calculated annual total BC emissions from 1949 to 2007. The emission estimation and uncertainty are shown as a median value (curve) and R50 (shaded area, for total emissions) derived from a Monte Carlo simulation. For comparison, emissions previously estimated are marked as red (total) or green (anthropogenic) circles.3,4,9−12 (B) Annual BC emissions (medians) from residential, industry, transportation, wildfires, and other sectors (including power generation and agricultural waste burned in fields).
Figure 6. Time series of annual BC emissions in China from 1949 to 2050. (A) Calculated annual anthropogenic BC emissions in China for 4 scenarios: baseline, low-carbon, baseline-high, and low-carbon-high. Mitigated emissions, between the baseline-high and low-carbon scenarios, are shown as the shaded area, underscoring the high uncertainty associated with technology development. (B) Annual BC emissions from residential, industry, transportation, and other sectors (including power generation and agricultural waste burned in fields) under the baseline-high (solid lines) and low-carbon (dotted lines) scenarios. The mitigated emissions between baseline-high and low-carbon scenarios are shown as the shaded area.
burning accounted for 40−50% of total emissions, mostly due to wildfires in Africa and South America.3 Despite the fact that EFBC for motor vehicles have decreased in recent years,61 total BC emissions from vehicles have increased steadily during the past decade due to rapid growth of the vehicle fleet. With the time series available, annual emissions were compared to results previously reported in the literature for the same years.3,4,9−12 Estimated total or anthropogenic BC emissions in this study were 2−55% higher than the corresponding estimations in previous inventories (Figure 5A), mainly because EFBC were updated and noncompliance of control facilities was taken into consideration in this study. Prediction of BC Emissions in China. Anthropogenic BC emissions from 2007 to 2050 were predicted under various scenarios (Figure 6A). The annual emissions are also listed in Table S6. It was estimated that BC emissions in China in 2050 would be 2183, 1663, 1338, and 920 Gg/yr in the baseline-high, low-carbon-high, baseline, and low-carbon scenarios, respectively. Under the baseline-high scenario, the total BC emissions in China would increase to a peak of 2273 Gg/yr (1376−3719 as R50) in 2041 due to the increase of BC emissions from motor vehicles (by a factor of 3.6), off-road diesel machineries (by a factor of 3.1), coal combustions in industrial boilers and power plants (by a factor of 1.8), brick production (by a factor of 1.6), and coke production (by a factor of 2.4). These increases result directly from greater fuel consumption.23 If either the low-carbon strategy (low-carbon-high scenario) or technology improvement (baseline scenario) were implemented alone, total BC emissions in China would be reduced by 92 or 29 Gg/yr in 2010, 394 or 583 Gg/yr in 2020, 476 or
demonstrated that BC from high emission areas of Sichuan Basin-Guizhou Highland were largely transported eastward (Figure S4). Such a high-resolution inventory is necessary for atmospheric transport modeling of BC and will also be useful in evaluating health impacts associated with BC because it better accounts for source−receptor relationships. Temporal Trends of BC Emissions in China. Annual BC emissions from various sources in China were calculated based on the historical fuel consumption data for a period from 1949 to 2007. The results are shown in Figure 5, and the annual emissions are listed in Table S6. Annual BC emissions increased monotonically from 1949 (341 Gg/yr) to 1996 (2189 Gg/yr), following the rapid increases in population and per capital energy consumption. Since 1996, annual emissions have risen and fallen (Figure 5A). As shown in Figure 5B, emissions from the residential sector have declined since 1990, as a result of three major factors: rapid urbanization producing a decline in China’s rural population; coal stoves being replaced with liquid petroleum gas/natural gas (LPG/NG) stoves; and expanded use of centralized heating systems. 59 Most importantly, beehive coke ovens were gradually phased out after the enforcement of the Coal Law in 1996,39 which is the main reason that industrial BC emissions have declined from their peak (550 Gg) in 1996. Although a campaign to promote biogas in rural China has existed for years, there are not enough data to quantitatively assess its influence on energy usage in rural China.60 Forest and savannah fires account for a relatively small fraction of total BC emissions in China and had limited influence on the temporal trend. This is very different from the global BC emissions situation, in which outdoor biomass 7600
dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
Environmental Science & Technology 583 Gg/yr in 2030, 519 or 765 Gg/yr in 2040, and 520 or 845 Gg/yr in 2050, respectively. If the low-carbon strategy and technology improvement were implemented together (lowcarbon scenario), the mitigated emissions would reach totals of 158, 988, and 1263 Gg/yr in 2010, 2030, and 2050, respectively. Mitigation measures would be most effective for industry and transportation, two sectors for which the effects of technology improvement are significant (Figure 6B). For example, by moving from the baseline-high to baseline scenario, BC emissions can be reduced by 190 and 664 Gg in 2050 in the industry and transportation sectors. It should be noted that future predictions are associated with high uncertainty, because technology development will not keep in steady step and emerging technologies may lead to a fast decrease in EFs over a short period of time in the future. A good example is the diesel particulate filter used on motor vehicles, which can result in a rapid reduction of associated emissions over a short period of time if widely implemented.62 Implications. With the largest population, its rapid industrialization, and a strong dependence on coal, China is the world’s largest source of BC emissions. Fortunately, BC emissions in China have leveled off during the last two decades, as a result of coal stoves being replaced with LPG/NG and beehive coke ovens being phased out. Although more and more rural residents have moved and will move to cities due to rapid urbanization, there will continue to be a very large rural population in China for decades to come; and solid fuels including crop residues, firewood, and coal will remain primary energy sources in rural areas.63 To reduce BC emissions from these sources, it is necessary to develop and distribute simple, inexpensive, practical, and effective low-technology options, which can make more efficient use of solid fuels and reduce emissions of pollutants at the same time. Among these techniques, biogas is used by more and more rural families and the government subsidy for biogas digesters has increased rapidly. (Some 13 000 000 biogas tanks had been put in use by 2003.)64 However, it is important to control the leakage of methane from biogas generators; otherwise, the beneficial climate effect of mitigating BC by using biogas could be partly offset by increased methane emissions.65 Another simple but effective approach to reduce BC emissions is to promote socalled “improved” biomass burning stoves. It has been demonstrated that such a campaign can help to reduce emissions of pollutants substantially by increasing solid fuel combustion efficiency.60 Biomass pellets and stalk gasifying furnaces are two examples of technologies that can improve the efficiency of biomass fuel use.66,67 Application of these techniques can reduce emissions of BC, CO2 and many other pollutants.
■
ACKNOWLEDGMENTS
■
REFERENCES
Funding for this study was provided by the National Natural Science Foundation of China (41130754). We thank Zoë Chafe (University of California, Berkeley: Energy and Resources Group) for offering useful comments and polishing the English of the manuscript.
(1) Ramanathan, V.; Carmichael, G. Global and regional climate changes due to black carbon. Nat. Geosci. 2008, 1, 221−227. (2) Bond, T. C.; Zarzycki, C.; Flanner, M. G.; Koch, D. M. Quantifying immediate radiative forcing by black carbon and organic matter with the Specific Forcing Pulse. Atmos. Chem. Phys. 2011, 11, 1505−1525. (3) Bond, T. C.; Streets, D. G.; Yarber, K. F.; Nelson, S. M.; Woo, J. H.; Klimont, Z. A technology-based global inventory of black and organic carbon emissions from combustion. J. Geophys. Res. Atmos. 2004, 109, D14203. (4) Zhang, Q.; Streets, D. G.; Carmichael, G. R.; He, K.; Huo, H.; Kannari, A.; Klimont, Z.; Park, I.; Reddy, S.; Fu, J. S.; Chen, D.; Duan, L.; Lei, Y.; Wang, L.; Yao, Z. Asian emissions in 2006 for the NASA INTEX-B mission. Atmos. Chem. Phys. 2009, 9, 4081−4139. (5) Cowan, T.; Cai, W. The impact of Asian and non-Asian anthropogenic aerosols on 20th century Asian summer monsoon. Geophys. Res. Let. 2011, 38, L11703. (6) Nakajima, T.; Yoon, S. C.; Ramanathan, V.; Shi, G. Y.; Takemura, T.; Higurashi, A.; Takamura, T.; Aoki, K.; Sohn, B. J.; Kim, S. W.; Tsuruta, H.; Sugimoto, N.; Shimizu, A.; Tanimoto, H.; Sawa, Y.; Lin, N. H.; Lee, C. T.; Goto, D.; Schutgens, N. Overview of the Atmospheric Brown Cloud East Asian Regional Experiment 2005 and a study of the aerosol direct radiative forcing in East Asia. J. Geophys. Res. Atmos. 2007, 112, D24S91. (7) Xu, B. Q.; Cao, J. J.; Hansen, J.; Yao, T. D.; Joswia, D. R.; Wang, N. L.; Wu, G. J.; Wang, M.; Zhao, H. B.; Yang, W.; Liu, X. Q.; He, J. Q. Black soot and the survival of Tibetan glaciers. Proc. Natl. Acad. Sci. U.S.A. 2009, 106, 22114−22118. (8) Shindell, D.; et al. Simultaneously mitigating near-term climate change and improving human health and food security. Science 2012, 335, 183−189. (9) Streets, D. G.; Shalini, G.; Waldhoff, S. T.; Wang, M. Q.; Bond, T. C.; Bo, Y. Y. Black carbon emissions in China. Atmos. Environ. 2001, 35, 4281−4296. (10) Streets, D. G.; Bond, T. C.; Carmichael, G. R.; Fernandes, S. D.; Fu, Q.; He, D.; Klimont, Z.; Nelson, S. M.; Tsai, N. Y.; Wang, M. Q.; Woo, J. H.; Yarber, K. F. An inventory of gaseous and primary aerosol emissions in Asia in the year 2000. J. Geophys. Res. Atmos. 2003, 108, 8809. (11) Cao, G. L.; Zhang, X. Y.; Zheng, F. C. Inventory of black carbon and organic carbon emissions from China. Atmos. Environ. 2006, 40, 6516−6527. (12) Ohara, T.; Akimoto, H.; Kurokawa, J.; Horii, N.; Yamaji, K.; Yan, X.; Hayasaka, T. An Asian emisison inventory of anthropogenic emission sources for the period 1980−2020. Atmos. Chem. Phys. 2007, 7, 4419−4444. (13) Qin, Y.; Xie, S. D. Estimation of county-level black carbon emissions and its spatial distribution in China in 2000. Atmos. Environ. 2011, 45, 6995−7004. (14) Klimont, Z.; et al. Projections of SO2, NOx and carbonaceous aerosols emissions in Asia. Tellus 2009, 61B, 602−617. (15) Lu, Z.; Zhang, Q.; Streets, D. G. Sulfur dioxide and primary carbonaceous aerosol emissions in China and India, 1996−2010. Atmos. Chem. Phys. 2011, 11, 9839−9864. (16) Subramanian, R.; Winijkul, E.; Bond, T. C.; Thiansathit, W.; Oanh, N. T. K.; Paw-armart, I.; Duleep, K. G. Climate-relevant properties of diesel particulate emissions: results from a piggyback study in Bangkok, Thailand. Environ. Sci. Technol. 2009, 43, 4213− 4218.
ASSOCIATED CONTENT
S Supporting Information *
Tables S1−S6, Figures S1−S4. This material is available free of charge via the Internet at http://pubs.acs.org.
■
■
Article
AUTHOR INFORMATION
Corresponding Author
*Phone and fax: 0086-10-62751938; email:
[email protected]. Notes
The authors declare no competing financial interest. 7601
dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
Environmental Science & Technology
Article
(17) Shen, G. F.; Yang, Y. F.; Wang, W.; Tao, S.; Zhu, C.; Min, Y. J.; Xue, M.; Ding, J. N.; Wang, B.; Wang, R.; Shen, H. Z.; Li, W.; Wang, X. L.; Russell, A. G. Emission factors of particulate matter and black carbon for crop residues and coals burned in typical household stoves in China. Environ. Sci. Technol. 2010, 44, 7157−7162. (18) Wang, R.; Tao, S.; Shen, H. Z.; Wang, X. L.; Li, B. G.; Shen, G. F.; Wang, B.; Li, W.; Liu, X. P.; Huang, Y.; Zhang, Y. Y.; Lu, Y.; Ouyang, H. L. Global emission of black carbon from motor vehicles from 1960 to 2030. Environ. Sci. Technol. 2012, 46, 1278−1284. (19) Zhang, Y. X.; Tao, S.; Cao, J.; Coveney, R. M. Emission of polycyclic aromatic hydrocarbons in China by county. Environ. Sci. Technol. 2007, 41, 683−687. (20) United Nations Statistics Division. United Nations Energy Statistics, 1950−1995; New York, 1995. (21) International Energy Agency. Energy Statistics of Non-OECD Countries 1970−2006; Paris, 2008. (22) National Bureau of Statistics and National Energy Administration. China Energy Statistical Yearbook, 1986, 1989−2008; China Statistics Press: Beijing, 2009. (23) National Development and Reform Commission and Development Research Center of the State Council. 2050 China Energy and CO2 Emissions Report; Science Press: Beijing, 2009. (24) Huo, H.; Zhang, Q.; He, K. Vehicle-use intensity in China: Current status and future trend. Energy Policy 2012, 43, 6−16. (25) Huo, H.; Wang, M. Modeling future vehicle sales and stock in China. Energy Policy 2012, 43, 17−29. (26) Huo, H.; Wang, M.; Zhang, X.; He, K.; Gong, H. M.; Jiang, K.; Jin, Y.; Shi, Y.; Yu, X. Projection of energy use and greenhouse gas emissions by motor vehicles in China: Policy options and impacts. Energy Policy 2012, No. doi 10.1016/j.enpol.2011.09.065. (27) Horii, N.; Gu, S. H. Transformation of China’s Energy Industries in Market Transition and Its Prospects; Institute of Developing Economies: China, 2001; pp 23−62. (28) Sinton, J. E. Accuracy and reliability of China’s Energy Statistics. China Econ. Rev. 2001, 12, 373−383. (29) Zhang, L. A.; Jia, Z. P. Investigation and analysis of the status quo for Chinese petroleum refining industry. Pet. Refin. Eng. 2004, 9, 1−4. (30) Akimoto, H.; Ohara, T.; Kurokawa, J.; Horii, N. Verification of energy consumption in China during 1996−2003 by using satellite observational data. Atmos. Environ. 2006, 40, 7663−7667. (31) Bond, T. C.; Streets, D. G.; Yarber, K. F.; Nelson, S. M.; Woo, J. H.; Klimont, Z. A technology-based global inventory of black and organic carbon emissions from combustion. J. Geophys. Res. Atmos. 2004, 109, D14203 DOI: 10.1029/2003JD003697. (32) Streets, D. G.; Bond, T. C.; Lee, T.; Jang, C. On the future of carbonaceous aerosol emissions. J. Geophys. Res. Atmos. 2004, 109, D24212 DOI: 10.1029/2004JD004902. (33) Grubler, A.; Nakicenovic, N.; Victor, D. G. Dynamics of energy technologies and global change. Energy Policy 1999, 27, 247−280. (34) Raufer, R.; Li, S. Y. Emissions trading in China: A conceptual 'leapfrog' approach? Energy 2009, 34, 904−912. (35) Xu, Y. Improvements in the operation of SO2 scrubbers in China’s coal power plants. Environ. Sci. Technol. 2011, 45, 380−385. (36) Sun, X. Authorities work on SO2 trade system; 2006; http:// www.chinadaily.com.cn/china/ 2006-09/14/content_688449.htm (accessed May 1, 2011). (37) Luo, N. Research on Environmental Impact of Sintered Brick Production in China. Master dissertation, Beijing University of Technology, Beijing, 2009. (38) Association of Iron and Steel Industry. Coke Production Database in China; Beijing, 2010; http://www.chinaisa.org.cn/ (accessed May 1, 2011). (39) Zhang, Y. X.; Dou, H.; Chang, B.; Wei, Z. C.; Qiu, W. X.; Liu, S. Z.; Liu, W. X.; Tao, S. Emission of polycyclic aromatic hydrocarbons from indoor straw burning and emission inventory updating in China. Ann. N.Y. Acad. Sci. 2008, 1140, 218−227. (40) China Automobile Industry Association. China Automotive Industry Yearbook, 1985−2008; China Machine Press: Beijing, 2008.
(41) Huo, H.; Wang, M.; Johnson, L.; He, D. Projection of Chinese motor vehicle growth, oil demand, and CO2 emissions through 2050. Transp. Res. Rec. 2007, 2038, 69−77. (42) Kupiainen, K.; Klimont, Z. Primary Emissions of Submicron and Carbonaceous Particles in Europe and the Potential for their Control; Interim Report IR-040079; International Institute for Applied Systems Analysis: Laxenburg, Austria, 2004. (43) Kim Oanh, N. T.; Thiansathit, W.; Bond, T. C.; Subramanian, R.; Winijkul, E.; Paw-armart, I. Compositional characterization of PM2.5 emitted from in-use diesel vehicles. Atmos. Environ. 2010, 44, 15−22. (44) Li, S. J. Development of technology and stoves for coke production in Shanxi. Shanxi Energy Conserv. 2000, 4, 23−26. (45) He, Q. S.; Fan, X. Z.; Wang, X. M.; Sheng, G. Y.; Fu, J. M. Emissions of TSP and Sulfur Dioxide from coal coking process. Earth Environ. 2007, 35, 283. (46) State Power Corporation of China. China Electricity Yearbook 2007; China Electricity Press: Beijing, 2008. (47) Global Rural-Urban Mapping Project (GRUMP). Global urban/ rural population datasets; http://beta.sedac.ciesin.columbia.edu/gpw/ (accessed June 1, 2011). (48) European Commission, Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency (PBL). Emission Database for Global Atmospheric Research (EDGAR), release version 4.2. http://edgar.jrc.ec.europa.eu, 2011. (49) Oak Ridge National Laboratory (ORNL). LandScan Global Population 2007 Database; ORNL, 2008; http://www.ornl.gov/sci/ landscan/ (accessed Oct 1, 2010). (50) Friedl, M. A.; Mclver, D. K.; Hodges, J. C. F.; Zhang, X. Y.; Muchoney, D.; Strahler, A. H.; Woodcock, C. E.; Gopal, S.; Schneider, A.; Cooper, A.; Baccini, A.; Gao, F.; Schaaf, C. Global 10 land cover mapping from MODIS: algorithms and early results. Remote. Sens. Environ. 2002, 83, 287−302. (51) vander Werf, G. R.; et al. Global fire emissions and the contribution of deforestation, savanna, forest, agriculture, and peat fires. Atmos. Chem. Phys. 2010, 10, 16153−16230. (52) The World Bank World Development Indicators (The World Bank, 2010); available at http://databank.worldbank.org/ddp/home. do. (53) Lanzhou Morning Post. Future of small brick kilns. 2011, July; available at http://lzcb.gansudaily.com.cn/system/2011/07/20/ 012084557_01.shtml. (54) U.S. Environmental Protection Agency. Nonroad Diesel Equipment: Regulations and Standards. 2012, January; available at http://www.epa.gov/nonroad-diesel/regulations.htm. (55) Streets, D. G.; Bond, T. C.; Lee, T.; Jang, C. On the future of carbonaceous aerosol emissions. J. Geophys. Res. Atmos. 2004, 109, D24212. (56) Shaanxi Statistics Bureau. Shaanxi Statistical Yearbook 2008; China Statistics Press: Beijing, 2008. (57) Stohl, A. Characteristics of atmospheric transport into the Arctic troposphere. J. Geophys. Res. Atmos. 2006, 111, D11. (58) Wang, R.; Tao, S.; Wang, B.; Yang, Y.; Lang, C.; Zhang, Y. X.; Hu, J.; Ma, J. M.; Hung, H. Sources and pathways of polycyclic aromatic hydrocarbons transported to Alert, the Canadian High Arctic. Environ. Sci. Technol. 2010, 44, 1017−1022. (59) Ministry of Environmental Protection of the People’s Republic of China. China Environment Yearbook 2008; China Environment Yearbook, Inc.: Beijing, 2008. (60) Zeng, X. Y.; Ma, Y. T.; Ma, L. R. Utilization of straw in biomass energy in China. Renew. Sustain. Energy Rev. 2007, 11, 976−987. (61) Westerdahl, D.; Wang, X.; Pan, X. C.; Zhang, K. M. Characterization of on-road vehicle emission factors and microenvironmental air quality in Beijing, China. Atmos. Environ. 2009, 43, 697−705. (62) Twigg, M. V. Progress and future challenges in controlling automotive exhaust gas emissions. Appl. Catal. B: Environ. 2007, 70, 2−15. 7602
dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
Environmental Science & Technology
Article
(63) Wang, X. P.; Mauzerall, D. L.; Hu, Y. T.; Russell, A. G.; Larson, E. D.; Woo, J. H.; Streets, D. G.; Guenther, A. A high-resolution emission inventory for eastern China in 2000 and three scenarios for 2020. Atmos. Environ. 2005, 39, 5917−5933. (64) Zhang, Y. L. The current situation and development countermeasures of rural biogas in China. Renew. Energy 2004, 4, 5−8. (65) Wang, M. X. Sources of methane in China. J. Environ. Sci. 1993, 5, 383−399. (66) Lin, D. The development and prospective of bioenergy technology in China. Biomass Bioenergy 1998, 15, 181−186. (67) Chen, L. J.; Xing, L.; Han, L. J. Renewable energy from agroresidues in China: Solid biofuels and biomass briquetting technology. Renew. Sustain. Energy Rev. 2009, 13, 2689−2695.
7603
dx.doi.org/10.1021/es3003684 | Environ. Sci. Technol. 2012, 46, 7595−7603
