Assessment of PM2.5 concentrations and exposure throughout China using ground observations

Guo, Hong; Cheng, Tianhai; Gu, Xingfa; Wang, Ying; Chen, Hao; Bao, Fang; Shi, Shuaiyi; Xu, Binren; Wang, Wannan; Zuo, Xin; Zhang, Xiaochuan; Meng, Chunlei

doi:10.1016/j.scitotenv.2017.05.263

Cited by 107 publications

(58 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This study revealed that on the whole, PRE showed a negative relation to PM 2.5 pollution, while VE and SEC maintained a positive relation to PM 2.5 pollution-a finding that is generally consistent with that of related previous studies by Guo et al (2017) [57] and Wong et al (2019) [58]. Figure 7a shows that the value of the coefficient of PRE was reduced when the value of the coefficient of VE increased, which meant that in areas where VE was the critical factor leading to PM 2.5 pollution, the mitigation effect of PRE on PM 2.5 concentrations was weak.…”

Section: Discussionsupporting

confidence: 92%

Exploring the Spatial Variation Characteristics and Influencing Factors of PM2.5 Pollution in China: Evidence from 289 Chinese Cities

Zhao

2019

Sustainability

View full text Add to dashboard Cite

Haze pollution has become an urgent environmental problem due to its impact on the environment as well as human health. PM2.5 is one of the core pollutants which cause haze pollution in China. Existing studies have rarely taken a comprehensive view of natural environmental conditions and socio-economic factors to figure out the cause and diffusion mechanism of PM2.5 pollution. This paper selected both natural environmental conditions (precipitation (PRE), wind speed (WIN), and terrain relief (TR)) and socio-economic factors (human activity intensity of land surface (HAILS), the secondary industry's proportion (SEC), and the total particulate matter emissions of motor vehicles (VE)) to analyze the effects on the spatial variation of PM2.5 concentrations. Based on the spatial panel data of 289 cities in China in 2015, we used spatial statistical methods to visually describe the spatial distribution characteristics of PM2.5 pollution; secondly, the spatial agglomeration state of PM2.5 pollution was characterized by Moran’s I; finally, several regression models were used to quantitatively analyze the correlation between PM2.5 pollution and the selected explanatory variables. Results from this paper confirm that in 2015, most cities in China suffered from severe PM2.5 pollution, and only 17.6% of the sample cities were up to standard. The spatial agglomeration characteristics of PM2.5 pollution in China were particularly significant in the Beijing–Tianjin–Hebei region. Results from the global regression models suggest that WIN exerts the most significant effects on decreasing PM2.5 concentration (p < 0.01), while VE is the most critical driver of increasing PM2.5 concentration (p < 0.01). Results from the local regression model show reliable evidence that the relation between PM2.5 concentrations and the explanatory variables varied differently over space. VE is the most critical factor that influences PM2.5 concentrations, which means controlling motor vehicle pollutant emissions is an effective measure to reduce PM2.5 pollution in Chinese cities.

show abstract

Section: Discussionsupporting

confidence: 92%

Exploring the Spatial Variation Characteristics and Influencing Factors of PM2.5 Pollution in China: Evidence from 289 Chinese Cities

Zhao

2019

Sustainability

View full text Add to dashboard Cite

show abstract

“…[4][5][6][7][8] Many measures, policies, and future plans have been introduced by the Government of China to reduce air pollution and its adverse effects, 9 including restructuring of industry and energy infrastructure, formulation and implementation of the Air Pollution Prevention and Control Action Plan 10 (at both the national and local level), the 13th Five-Year Plan for Eco-Environmental Protection, 11 and the revision and implementation of the Ambient Air Quality Standards and the Environmental Protection Law. Following the release and implementation of the Air Pollution Prevention and Control Action Plan, the air quality of most regions in China has improved, and the national annual mean PM 2·5 concentrations decreased by 12·31% (from 79·21 μg/m³ to 69·51 μg/m³) between 2013 and 2015, 12 which might help to mitigate the disease burden from air pollution. However, as a result of the high baseline levels of pollution and rapid economic development occurring in China, air pollution and its subsequent health effects will persist.…”

Section: Introductionmentioning

confidence: 99%

Estimation of PM2·5-associated disease burden in China in 2020 and 2030 using population and air quality scenarios: a modelling study

Wang

Zhou

et al. 2019

The Lancet Planetary Health

View full text Add to dashboard Cite

Background Air pollution and its adverse effects on public health remain a considerable problem in China, where policies have been implemented to improve the situation. We aimed to estimate the disease burden associated with particulate matter (PM) 2·5 across China for 2020 and 2030 to identify the populations and regions most at risk, quantify the health benefits of air quality improvement targets, and determine the effect of population growth and ageing on this disease burden. Methods In this modelling study, we investigated premature deaths associated with PM 2·5 across China on the basis of air quality scenarios proposed by the expert group involved in the formulation of the 13th Five-Year Plan for Eco-Environmental Protection and population scenarios based on the Shared Socioeconomic Pathways of theIntergovernmental Panel on Climate Change. We used the integrated exposure-response model used for the Global Burden of Disease Study to estimate the number of PM 2·5 -related premature deaths under each scenario. Findings The projected health benefits of the air-quality-improving targets are substantial, and could reduce the number of PM 2.5 -related premature deaths in China by approximately 129 278 by 2020 and 217 988 by 2030, compared with 2010. However, since China's population is increasing and ageing, the number of PM 2.5 -related premature deaths was estimated to increase by 84 102 by 2020 and by 244 191 by 2030, indicating that the health benefits induced by air quality improvements could be offset by the effect of the population increasing in size and ageing.Interpretation To reduce the future disease burden in China, targets that are stricter than the interim target and stringent policies to improve air quality and protect public health are needed, especially for at-risk population groups, such as older individuals (aged >55 years) and patients with cardiovascular diseases, particularly in regions with a high disease burden.

show abstract

“…As one of the largest emission sources of aerosols and their precursors, China has been suffering from serious air pollution for years (Lei et al, 2011;Li et al, 2011), with severe haze events frequently occurring in winter, especially over large urban agglomerations, such as the North China Plain (NCP) (Han et al, 2014;Gao et al, 2015), the Yangtze River Delta area (YRD) (Ding et al, 2016;Wang et al, 2016a), the Pearl River Delta area (PRD) (Fan et al, 2015;Liu et al, 2018b), and the Sichuan Basin (SCB) (Zhao et al, 2018;Zhang et al, 2019). During severe haze events, the observed maximum hourly surface-layer PM 2.5 (fine particulate matter with aerodynamic diameter of 2.5 µm or less) concentration exceeded 1000 µg m -3 (Wang et al, 2013b;Sun et al, 2016;Li et al, 2017a), which could significantly influence visibility (Li et al, 2014), radiation budget (Steiner et al, 2013), atmospheric circulation (Jiang et al, 2017), cloud properties (Unger et al, 2009), and even human health (Guo et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Assessing the formation and evolution mechanisms of severe haze pollution in Beijing−Tianjin−Hebei region by using process analysis

Chen¹,

Zhu²,

Liu³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. Fine&#8211;particle pollution associated with haze threatens human health, especially in the North China Plain, where extremely high PM2.5 concentrations were frequently observed during winter. In this study, the WRF&#8211;Chem model coupled with an improved integrated process analysis scheme was used to investigate the formation and evolution mechanisms of a haze event happened over Beijing&#8211;Tianjin&#8211;Hebei (BTH) in December 2015, including examining the contributions of local emission and outside transport to the absolute PM2.5 concentration in BTH, and the contributions of each detailed physical or chemical process to the variations in the PM2.5 concentration. The influence mechanisms of aerosol radiative forcing (including aerosol direct and indirect effects) were also examined by using the process analysis. During the aerosol accumulation stage (December 20&#8211;22, Stage_1), the average near&#8211;surface PM2.5 concentration in BTH was 250.0&#8201;&#181;g&#8201;m&#8722;3, which was contributed by local emission of 42.3&#8201;% and outside transport of 36.6&#8201;%. During the aerosol dispersion stage (December 23&#8211;27, Stage_2), the average concentration of PM2.5 was 107.9&#8201;&#181;g&#8201;m&#8722;3. The contribution of local emission increased to 50.9&#8201;%, while the contribution of outside transport decreased to 24.3&#8201;%. The 24&#8211;h change (23:00LST minus 00:00LST) in the near&#8211;surface PM2.5 concentration was +50.4&#8201;&#181;g&#8201;m&#8722;3 during Stage_1 and &#8722;41.5&#8201;&#181;g&#8201;m&#8722;3 during Stage_2. Contributions of aerosol chemistry process and vertical mixing process to the 24&#8211;h change were +43.8 (+17.9) &#181;g&#8201;m&#8722;3 and &#8722;161.6 (&#8722;221.6) &#181;g&#8201;m&#8722;3 for Stage_1 (Stage_2), respectively. Small differences in contributions from other processes were found between Stage_1 and Stage_2, such as advection process, cloud chemistry process, and so on. Therefore, the PM2.5 increase over BTH during haze formation stage (Stage_1) was mainly attributed to strong production by aerosol chemistry process and weak removal by vertical mixing process. When aerosol radiative feedback was considered, the 24&#8211;h PM2.5 increase was enhanced by 9.6 &#181;g&#8201;m&#8722;3 during Stage_1, which could be mainly attributed to the contributions of vertical mixing process (+39.8&#8201;&#181;g&#8201;m&#8722;3), advection process (&#8722;38.6&#8201;&#181;g&#8201;m&#8722;3) and aerosol chemistry process (+5.1&#8201;&#181;g&#8201;m&#8722;3). The restrained vertical mixing could be the primary reason for the enhancement in near&#8211;surface PM2.5 increase when aerosol radiative forcing was considered.

show abstract

Assessment of PM2.5 concentrations and exposure throughout China using ground observations

Cited by 107 publications

References 37 publications

Exploring the Spatial Variation Characteristics and Influencing Factors of PM2.5 Pollution in China: Evidence from 289 Chinese Cities

Exploring the Spatial Variation Characteristics and Influencing Factors of PM2.5 Pollution in China: Evidence from 289 Chinese Cities

Estimation of PM2·5-associated disease burden in China in 2020 and 2030 using population and air quality scenarios: a modelling study

Assessing the formation and evolution mechanisms of severe haze pollution in Beijing−Tianjin−Hebei region by using process analysis

Contact Info

Product

Resources

About