Substantial changes in air pollution across China during 2015–2017

Silver, Ben; Reddington, Carly L.; Arnold, S. R.; Spracklen, Dominick V.

doi:10.1088/1748-9326/aae718

Cited by 187 publications

(149 citation statements)

References 60 publications

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“…Nonetheless, some other areas have experienced a slight worsening of their mortality burden in the last few years. The most notable examples are the urban area of Xi'An and the westernmost cities of China, coherently with the findings (in terms of air quality) reported in Silver et al (2018). The spatial distribution of the difference in terms of total mortality values can be found in the Supplementary Information (figure S6).…”

Section: Premature Mortality Estimatessupporting

confidence: 85%

“…These actions will contribute to mitigate not only pollution impacts on air quality (Yang and Zhang 2018), but also those on climate change . The recent decreasing trend in pollution concentrations (during 2015-2017) has been linked to the effective implementation of emissions reduction strategies by purely observation-based studies (Silver et al 2018) as well as by model simulations (Ding et al 2019).…”

Section: Introductionmentioning

confidence: 99%

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Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Giani

Anav

Marco

et al. 2020

Environ. Res. Lett.

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Atmospheric pollution from fine particulate matter (PM 2.5 ) is one of the major concerns in China because of its widespread and harmful impacts on human health. In recent years, multiple studies have sought to estimate the premature mortality burden from exposure to PM 2.5 to inform policy decisions. However, different modeling choices have led to a wide array of results, with significant discrepancies both in the total mortality burden and in the confidence intervals. Here, we present a new comprehensive assessment of PM 2.5 -related mortality for China, which includes quantification of the main sources of variability, as well as of age and province-specific premature mortality trends during 2015-2018. Our approach integrates PM 2.5 observations from more than 1600 monitoring stations with the output of a high-resolution (8 km) regional simulation, to accurately estimate PM 2.5 fields along with their uncertainty, which is generally neglected. We discuss the sensitivity of mortality estimates to the choice of the exposure-response functions (ERFs), by comparing the widely used integrated exposure response functions (IERs) to the recently developed Global Exposure Mortality Models (GEMMs). By propagating the uncertainty in baseline mortalities, PM 2.5 and ERFs under a Monte Carlo framework, we show that the 95% confidence intervals of mortality estimates are considerably wider than previously reported. We thus highlight the need for more epidemiological studies to constrain ERFs and we argue that uncertainty related to PM 2.5 estimate should be also incorporated in health impact assessment studies. Although the overall mortality burden remains vast in China (~1.6 million premature deaths, according to GEMMs), our results suggest that 200 000 premature deaths were avoided and 195 billion US dollars were saved in 2018 compared to 2015, bolstering the mounting evidence about the effectiveness of China's air quality policies.

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Section: Premature Mortality Estimatessupporting

confidence: 85%

Section: Introductionmentioning

confidence: 99%

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Giani

Anav

Marco

et al. 2020

Environ. Res. Lett.

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“…A rapid increasing trend in summertime surface ozone over China after 2012 was observed in recent studies (Lu et al, 2018;Silver et al, 2018;Shen et al, 2019;. We examine the regional mean trend over eastern China in daily, daytime (7:00-18:00), and nighttime (19:00-6:00) means ( Figure 4).…”

Section: Seasonal and Interannual Variations Of Surface Ozone In Eastmentioning

confidence: 95%

Local and synoptic meteorological influences on daily variability of summertime surface ozone in eastern China

Han¹,

Liu²,

Shu³

et al. 2019

Preprint

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Abstract. Ozone pollution in China is influenced by meteorological processes on multiple scales. Using multiple linear regression and weather classification, we statistically assess the impacts of local and synoptic meteorology on daily variability of surface ozone in eastern China in summer during 2013–2018. In this period, summertime surface ozone in eastern China (110–130° E, 20–42° N) is among the highest in the world with regional means of 73.1 and 114.7 µg m−3, respectively, in daily mean and daily maximum 8-hour average. By developing a multiple linear regression (MLR) model driven by local and synoptic weather factors, we establish a quantitative linkage between the daily ozone concentrations and meteorology in the study region. The meteorology described by the MLR model can explain ~ 46 % of the daily variability in summertime surface ozone across eastern China. The model shows that synoptic factors contribute to ~ 37 % of the overall meteorological effects on daily variability of surface ozone in eastern China. Among local meteorological factors, relative humidity is the most influential variable in the center and south of eastern China including the Yangtze River Delta and the Pearl River Delta regions, while temperature is the most influential variable in the north covering the Beijing-Tianjin-Hebei region. To further examine the synoptic influence of weather conditions explicitly, six predominant synoptic weather patterns (SWPs) over eastern China in summer are objectively identified using the self-organizing map clustering technique. The six SWPs are formed under the integral influence of the East Asian summer monsoon, the western Pacific subtropical high, the Meiyu front, and the typhoon activities. The results show that the impacts of each of the SWPs on the daily variability of surface ozone vary largely inside the study area. The maximum impact can reach &pm;8 µg m−3 or &pm;16 % of the daily mean over some subregions in eastern China. A combination of the regression and the clustering approaches suggests a strong performance of the MLR model in predicting the sensitivity of surface ozone in eastern China to the variation of synoptic weather. Our assessment highlights the important role of meteorology in modulating ozone pollution over China.

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“…The SO 2 decrease is quantitatively consistent with the decrease in SO 2 emissions estimated by MEIC . This drastic cut of China SO 2 emissions is due to installation of scrubbers at coal-fired power plants (Siwen et al, 2015;Karplus et al, 2018;Silver et al, 2018), elimination of small coal boilers, improvement of coal quality , and switch from residential coal to cleaner fuels . We also see a significant decrease in CO of 18 %-43 % for the five regions from 2013 to 2018, again consistent with the MEIC and suggesting a reduction in organic PM 2.5 emissions.…”

Section: Application To 2013-2018 Pm 25 Trendsmentioning

confidence: 99%

Fine particulate matter (PM<sub>2.5</sub>) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology

et al. 2019

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Abstract. Fine particulate matter (PM2.5) is a severe air pollution problem in China. Observations of PM2.5 have been available since 2013 from a large network operated by the China National Environmental Monitoring Center (CNEMC). The data show a general 30 %–50 % decrease in annual mean PM2.5 across China over the 2013–2018 period, averaging at −5.2 µg m−3 a−1. Trends in the five megacity cluster regions targeted by the government for air quality control are -9.3±1.8 µg m−3 a−1 (±95 % confidence interval) for Beijing–Tianjin–Hebei, -6.1±1.1 µg m−3 a−1 for the Yangtze River Delta, -2.7±0.8 µg m−3 a−1 for the Pearl River Delta, -6.7±1.3 µg m−3 a−1 for the Sichuan Basin, and -6.5±2.5 µg m−3 a−1 for the Fenwei Plain (Xi'an). Concurrent 2013–2018 observations of sulfur dioxide (SO2) and carbon monoxide (CO) show that the declines in PM2.5 are qualitatively consistent with drastic controls of emissions from coal combustion. However, there is also a large meteorologically driven interannual variability in PM2.5 that complicates trend attribution. We used a stepwise multiple linear regression (MLR) model to quantify this meteorological contribution to the PM2.5 trends across China. The MLR model correlates the 10 d PM2.5 anomalies to wind speed, precipitation, relative humidity, temperature, and 850 hPa meridional wind velocity (V850). The meteorology-corrected PM2.5 trends after removal of the MLR meteorological contribution can be viewed as being driven by trends in anthropogenic emissions. The mean PM2.5 decrease across China is −4.6 µg m−3 a−1 in the meteorology-corrected data, 12 % weaker than in the original data, meaning that 12 % of the PM2.5 decrease in the original data is attributable to meteorology. The trends in the meteorology-corrected data for the five megacity clusters are -8.0±1.1 µg m−3 a−1 for Beijing–Tianjin–Hebei (14 % weaker than in the original data), -6.3±0.9 µg m−3 a−1 for the Yangtze River Delta (3 % stronger), -2.2±0.5 µg m−3 a−1 for the Pearl River Delta (19 % weaker), -4.9±0.9 µg m−3 a−1 for the Sichuan Basin (27 % weaker), and -5.0±1.9 µg m−3 a−1 for the Fenwei Plain (Xi'an; 23 % weaker); 2015–2017 observations of flattening PM2.5 in the Pearl River Delta and increases in the Fenwei Plain can be attributed to meteorology rather than to relaxation of emission controls.

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Substantial changes in air pollution across China during 2015–2017

Cited by 187 publications

References 60 publications

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Local and synoptic meteorological influences on daily variability of summertime surface ozone in eastern China

Fine particulate matter (PM<sub>2.5</sub>) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology

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Substantial changes in air pollution across China during 2015–2017

Cited by 187 publications

References 60 publications

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Exploring sources of uncertainty in premature mortality estimates from fine particulate matter: the case of China

Local and synoptic meteorological influences on daily variability of summertime surface ozone in eastern China

Fine particulate matter (PM&lt;sub&gt;2.5&lt;/sub&gt;) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology

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Fine particulate matter (PM<sub>2.5</sub>) trends in China, 2013–2018: separating contributions from anthropogenic emissions and meteorology