Dataset Information

Drivers of improved PM_2.5 air quality in China from 2013 to 2017.

ABSTRACT: From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM_2.5) concentrations occurred nationwide. Here we estimate the drivers of the improved PM_2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functions. The estimated national population-weighted annual mean PM_2.5 concentrations decreased from 61.8 (95%CI: 53.3-70.0) to 42.0 µg/m³ (95% CI: 35.7-48.6) in 5 y, with dominant contributions from anthropogenic emission abatements. Although interannual meteorological variations could significantly alter PM_2.5 concentrations, the corresponding effects on the 5-y trends were relatively small. The measure-by-measure evaluation indicated that strengthening industrial emission standards (power plants and emission-intensive industrial sectors), upgrades on industrial boilers, phasing out outdated industrial capacities, and promoting clean fuels in the residential sector were major effective measures in reducing PM_2.5 pollution and health burdens. These measures were estimated to contribute to 6.6- (95% CI: 5.9-7.1), 4.4- (95% CI: 3.8-4.9), 2.8- (95% CI: 2.5-3.0), and 2.2- (95% CI: 2.0-2.5) µg/m³ declines in the national PM_2.5 concentration in 2017, respectively, and further reduced PM_2.5-attributable excess deaths by 0.37 million (95% CI: 0.35-0.39), or 92% of the total avoided deaths. Our study confirms the effectiveness of China's recent clean air actions, and the measure-by-measure evaluation provides insights into future clean air policy making in China and in other developing and polluting countries.

SUBMITTER: Zhang Q

PROVIDER: S-EPMC6900509 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Drivers of improved PM2.5 air quality in China from 2013 to 2017.

Zhang Qiang Q Zheng Yixuan Y Tong Dan D Shao Min M Wang Shuxiao S Zhang Yuanhang Y Xu Xiangde X Wang Jinnan J He Hong H Liu Wenqing W Ding Yihui Y Lei Yu Y Li Junhua J Wang Zifa Z Zhang Xiaoye X Wang Yuesi Y Cheng Jing J Liu Yang Y Shi Qinren Q Yan Liu L Geng Guannan G Hong Chaopeng C Li Meng M Liu Fei F Zheng Bo B Cao Junji J Ding Aijun A Gao Jian J Fu Qingyan Q Huo Juntao J Liu Baoxian B Liu Zirui Z Yang Fumo F He Kebin K Hao Jiming J

Proceedings of the National Academy of Sciences of the United States of America 20191118 49

From 2013 to 2017, with the implementation of the toughest-ever clean air policy in China, significant declines in fine particle (PM2.5) concentrations occurred nationwide. Here we estimate the drivers of the improved PM2.5 air quality and the associated health benefits in China from 2013 to 2017 based on a measure-specific integrated evaluation approach, which combines a bottom-up emission inventory, a chemical transport model, and epidemiological exposure-response functio ...[more]

PMID: 31740599

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Project description:High concentrations of particulate matter (PM2.5) and frequent air pollution episodes in Beijing have attracted widespread attention. This paper utilizes data from the new air pollution network in China to examine the current spatial and temporal variability of PM2.5 at 12 monitoring sites in Beijing over a recent 2-year period (April 2013) to March 2015). The long term (2-year) average concentration was 83 µg·m-3, well above Chinese and international standards. Across the region, annual average concentrations varied by 20 µg·m-3 (25% of the average level), with lower levels in suburban areas compared to periurban and urban areas, which had similar concentrations. The spatial variation in PM2.5 concentrations was associated with several land use and economic variables, including the fraction of vegetated land and building construction activity, which together explained 71% of the spatial variation. Daily air quality was characterized as "polluted" (above 75 µg·m-3) on 36 to 47% of days, depending on site. There were 77 pollution episodes during the study period (defined as two or more consecutive days with Beijing-wide 24-hour average concentrations over 75 µg·m-3), and 2 to 5 episodes occurred each month, including summer months. The longest episode lasted 9 days and daily concentrations exceeded 450 µg·m-3. Daily PM2.5 levels were autocorrelated (rlag1 = 0.516) and associated with many meteorological variables, including barometric pressure, relative humidity, hours of sunshine, surface and ambient temperature, precipitation and scavenging coefficient, and wind direction. Parsimonious models with meteorological and autoregressive terms explained over 60% of the variation in daily PM2.5 levels. The first autoregressive term and hours of sunshine were the most important variables in these models, however, the latter variable is PM2.5-dependent and thus not an explanatory variable. The present study can serve as a baseline to compare the improved air quality in Beijing expected in future years.

Dataset Information

Drivers of improved PM_2.5 air quality in China from 2013 to 2017.

Publications

Drivers of improved PM<sub>2.5</sub> air quality in China from 2013 to 2017.

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