Understand the local and regional contributions on air pollution from the view of human health impacts

Highlights

• PM_2.5-related deaths were estimated to be 227 thousand in BTH & surrounding regions.

• Local emissions contribute more to PM_2.5-related deaths than PM_2.5 concentration.

• Local controls are underestimated if only considering its impacts on concentrations.

• Rural residents suffer larger impacts of regional transport than urban residents.

• Reducing regional transport benefits in mitigating environmental inequality.

Abstract

The source-receptor matrix of PM_2.5 concentration from local and regional sources in the Beijing-Tianjin-Hebei (BTH) and surrounding provinces has been created in previous studies. However, because the spatial distribution of concentration does not necessarily match with that of the population, such concentration-based source-receptor matrix may not fully reflect the importance of pollutant control effectiveness in reducing the PM_2.5-related health impacts. To demonstrate that, we study the source-receptor matrix of the PM_2.5-related deaths instead, with inclusion of the spatial correlations between the concentrations and the population. The advanced source apportionment numerical model combined with the integrated exposure–response functions is used for BTH and surrounding regions in 2017. We observed that the relative contribution to PM_2.5-related deaths of local emissions was 0.75% to 20.77% larger than that of PM_2.5 concentrations. Such results address the importance of local emissions control for reducing health impacts of PM_2.5 particularly for local residents. Contribution of regional transport to PM_2.5-related deaths in rural area was 22% larger than that in urban area due to the spatial pattern of regional transport which was more related to the rural population. This resulted in an environmental inequality in the sense that people staying in rural area with access to less educational resources are subjected to higher impacts from regional transport as compared with their more resourceful and knowledgeable urban compatriots. An unexpected benefit from the multi-regional joint controls is suggested for its effectiveness in reducing the regional transport of PM_2.5 pollution thus mitigating the associated environmental inequality.

Graphical abstract

Keywords

PM_2.5 / Regional transport / Local emissions / Health impact / Environmental inequality

References

[1] Bell M L, Ebisu K (2012). Environmental inequality in exposures to airborne particulate matter components in the United States. Environmental Health Perspectives, 120(12): 1699–1704

[2] Burnett R T, Pope C A 3rd, Ezzati M, Olives C, Lim S S, Mehta S, Shin H H, Singh G, Hubbell B, Brauer M, Anderson H R, Smith K R, Balmes J R, Bruce N G, Kan H, Laden F, Pruss-Ustun A, Turner M C, Gapstur S M, Diver W R, Cohen A (2014). An integrated risk function for estimating the global burden of disease attributable to ambient fine particulate matter exposure. Environmental Health Perspectives, 122(4): 397–403

[3] Chang X, Wang S, Zhao B, Cai S, Hao J (2018). Assessment of inter-city transport of particulate matter in the Beijing-Tianjin-Hebei region. Atmospheric Chemistry and Physics, 18: 4843–4858

[4] Chang X, Wang S X, Zhao B, Xing J, Liu X X, Wei L, Song Y, Wu W J, Cai S Y, Zheng H T, Ding D, Zheng M (2019). Contributions of inter-city and regional transport to PM_2.5 concentrations in the Beijing-Tianjin-Hebei region and its implications on regional joint air pollution control. Science of the Total Environment, 660: 1191–1200

[5] Chen D, Liu X, Lang J, Zhou Y, Wei L, Wang X, Guo X (2017). Estimating the contribution of regional transport to PM_2.5 air pollution in a rural area on the North China Plain. Science of the Total Environment, 583: 280–291

[6] Cheng Z, Li L, Liu J (2020). The impact of foreign direct investment on urban PM_2.5 pollution in China. Journal of Environmental Management, 265: 110532

[7] Ding D, Xing J, Wang S, Liu K, Hao J (2019). Estimated contributions of emissions controls, meteorological factors, population growth, and changes in baseline mortality to reductions in ambient PM_2.5 and PM_2.5-related mortality in China, 2013–2017. Environmental Health Perspectives, 127(6): 067009

[8] Ding D A, Zhu Y, Jang C, Lin C J, Wang S X, Fu J, Gao J, Deng S, Xie J P, Qiu X Z (2016). Evaluation of health benefit using BenMAP-CE with an integrated scheme of model and monitor data during Guangzhou Asian Games. Journal of Environmental Sciences-China, 42: 9–18

[9] Dong Z, Wang S, Xing J, Chang X, Ding D, Zheng H (2020). Regional transport in Beijing-Tianjin-Hebei region and its changes during 2014–2017: The impacts of meteorology and emission reduction. Science of the Total Environment, 737: 139792

[10] Emery C, Tai E, Yarwood G (2001). Enhanced Meteorological Modeling and Performance Evaluation for Two Texas Episodes. Novato, CA: ENVIRON International Corp

[11] Fann N, Fulcher C M, Baker K (2013). The recent and future health burden of air pollution apportioned across U.S. sectors. Environmental Science & Technology, 47(8): 3580–3589

[12] Guenther A, Karl T, Harley P, Wiedinmyer C, Palmer P I, Geron C (2006). Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature). Atmospheric Chemistry and Physics, 6: 3181–3210

[13] Guo H, Kota S H, Sahu S K, Zhang H (2019). Contributions of local and regional sources to PM_2.5 and its health effects in north India. Atmospheric Environment, 214: 116867

[14] Kwok R H F, Napelenok S L, Baker K R (2013). Implementation and evaluation of PM_2.5 source contribution analysis in a photochemical model. Atmospheric Environment, 80: 398–407

[15] Lang J, Cheng S, Li J, Chen D, Zhou Y, Wei X, Han L, Wang H (2013). A monitoring and modeling study to investigate regional transport and characteristics of PM_2.5 pollution. Aerosol and Air Quality Research, 13(3): 943–956

[16] Li M, Zhang Q, Kurokawa J I, Woo J H, He K, Lu Z, Ohara T, Song Y, Streets D G, Carmichael G R, Cheng Y, Hong C, Huo H, Jiang X, Kang S, Liu F, Su H, Zheng B (2017). MIX: A mosaic Asian anthropogenic emission inventory under the international collaboration framework of the MICS-Asia and HTAP. Atmospheric Chemistry and Physics, 17(2): 935–963

[17] Li X, Zhang Q, Zhang Y, Zheng B, Wang K, Chen Y, Wallington T J, Han W J, Shen W, Zhang X Y, He K B (2015). Source contributions of urban PM_2.5 in the Beijing-Tianjin-Hebei region: Changes between 2006 and 2013 and relative impacts of emissions and meteorology. Atmospheric Environment, 123: 229–239

[18] Liu S, Xing J, Wang S, Ding D, Chen L, Hao J (2020a). Revealing the impacts of transboundary pollution on PM_2.5-related deaths in China. Environment International, 134: 105323

[19] Liu X, Bai X, Tian H, Wang K, Hua S, Liu H, Liu S, Wu B, Wu Y, Liu W, Luo L, Wang Y, Hao J, Lin S, Zhao S, Zhang K (2020b). Fine particulate matter pollution in North China: Seasonal-spatial variations, source apportionment, sector and regional transport contributions. Environmental Research, 184: 109368

[20] Ministry of Ecology and Environment of the People’s Republic of China (2012). Ambient air quality standards. Beijing: China Environment Science Press (in Chinese)

[21] Ministry of Ecology and Environment of the People’s Republic of China (2018). Bulletin of China Ecological Environment 2017. Beijing: Ministry of Ecology and Environment of the People’s Republic of China (in Chinese)

[22] Sacks J D, Lloyd J M, Zhu Y, Anderton J, Jang C J, Hubbell B, Fann N (2018). The environmental benefits mapping and analysis program- community edition (BenMAP-CE): A tool to estimate the health and economic benefits of reducing air pollution. Environmental Modelling & Software, 104: 118–129

[23] Tai A P K, Mickley L J, Jacob D J, Leibensperger E M, Zhang L, Fisher J A, Pye H O T (2012). Meteorological modes of variability for fine particulate matter (PM_2.5) air quality in the United States: implications for PM_2.5 sensitivity to climate change. Atmospheric Chemistry and Physics, 12(6): 3131–3145

[24] The State Council of the People’s Republic of China (2013). Air Pollution Prevention and Control Action Plan. Beijing: The State Council of the People’s Republic of China (in Chinese)

[25] U.S. Environmental Protection Agency (2007). Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze. Research Triangle Park, North Carolina: U.S. Environment Protection Agency, Office of Air Quality Planning and Standards

[26] Wang G Z, Gu S J, Chen J B, Wu X H, Yu J (2016). Assessment of health and economic effects by PM_2.5 pollution in Beijing: a combined exposure-response and computable general equilibrium analysis. Environmental Technology, 37(24): 3131–3138

[27] Wang J, Xing J, Mathur R, Pleim J E, Wang S, Hogrefe C, Gan C M, Wong D C, Hao J (2017). Historical trends in PM_2.5-related premature mortality during 1990–2010 across the northern hemisphere. Environmental Health Perspectives, 125(3): 400–408

[28] Yang S, Fang D, Chen B (2019). Human health impact and economic effect for PM_2.5 exposure in typical cities. Applied Energy, 249: 316–325

[29] Zhang H, Cheng S, Yao S, Wang X, Zhang J (2019a). Multiple perspectives for modeling regional PM_2.5 transport across cities in the Beijing–Tianjin–Hebei region during haze episodes. Atmospheric Environment, 212: 22–35

[30] Zhang Q, Jiang X, Tong D, Davis S J, Zhao H, Geng G, Feng T, Zheng B, Lu Z, Streets D G, Ni R, Brauer M, Van Donkelaar A, Martin R V, Huo H, Liu Z, Pan D, Kan H, Yan Y, Lin J, He K, Guan D (2017a). Transboundary health impacts of transported global air pollution and international trade. Nature, 543(7647): 705–709

[31] Zhang S, Xing J, Sarwar G, Ge Y, He H, Duan F, Zhao Y, He K, Zhu L, Chu B (2019b). Parameterization of heterogeneous reaction of SO₂ to sulfate on dust with coexistence of NH₃ and NO₂ under different humidity conditions. Atmospheric Environment, 208: 133–140

[32] Zhang Y L, Zhu B, Gao J H, Kang H Q, Yang P, Wang L L, Zhang J K (2017b). The source apportionment of primary PM_2.5 in an aerosol pollution event over Beijing-Tianjin-Hebei region using WRF-Chem, China. Aerosol and Air Quality Research, 17(12): 2966–2980

[33] Zhao B, Wu W, Wang S, Xing J, Chang X, Liou K N, Jiang J H, Gu Y, Jang C, Fu J S, Zhu Y, Wang J, Lin Y, Hao J (2017). A modeling study of the nonlinear response of fine particles to air pollutant emissions in the Beijing–Tianjin–Hebei region. Atmospheric Chemistry and Physics, 17(19): 12031–12050

[34] Zheng B, Tong D, Li M, Liu F, Hong C, Geng G, Li H, Li X, Peng L, Qi J, Yan L, Zhang Y, Zhao H, Zheng Y, He K, Zhang Q (2018). Trends in China’s anthropogenic emissions since 2010 as the consequence of clean air actions. Atmospheric Chemistry and Physics, 18(19): 14095–14111

[35] Zheng H, Zhao B, Wang S, Wang T, Ding D, Chang X, Liu K, Xing J, Dong Z, Aunan K, Liu T, Wu X, Zhang S, Wu Y (2019). Transition in source contributions of PM_2.5 exposure and associated premature mortality in China during 2005–2015. Environment International, 132: 105111

[36] Zheng S, Pozzer A, Cao C X, Lelieveld J (2015). Long-term (2001–2012) concentrations of fine particulate matter (PM_2.5) and the impact on human health in Beijing, China. Atmospheric Chemistry and Physics, 15(10): 5715–5725

Acknowledgements

This work was supported by National Natural Science Foundation of China (Grant Nos. 41907190 & 21625701), Beijing Municipal Commission of Science and Technology (Z191100009119001 & Z191100009119004) and Tsinghua-Toyota Research Center. This work was completed on the “Explorer 100” cluster system of Tsinghua National Laboratory for Information Science and Technology.

Electronic Supplementary Material

Supplementary material is available in the online version of this article at https://doi.org/10.1007/s11783-020-1382-2 and is accessible for authorized users.

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