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Articles

Comparative analysis of PM2.5 pollution risk in China using three-dimensional Archimedean copula method

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Pages 2368-2386 | Received 01 Aug 2019, Accepted 17 Oct 2019, Published online: 04 Dec 2019

References

  • Atkinson RW, Kang S, Anderson HR, Mills IC, Walton HA. 2014. Epidemiological time series studies of PM2.5 and daily mortality and hospital admissions: a systematic review and meta-analysis. Thorax. 69(7):660–665.
  • Carrao H, Naumann G, Barbosa P. 2016. Mapping global patterns of drought risk: An empirical framework based on sub-national estimates of hazard, exposure and vulnerability. Global Environ Change. 39:108–124.
  • Chen P, Bi X, Zhang J, Wu J, Feng Y. 2015. Assessment of heavy metal pollution characteristics and human health risk of exposure to ambient PM2.5 in Tianjin, China. Particuology. 20:104–109.
  • Chen Z, Chen D, Xie X, Cai J, Zhuang Y, Cheng N, He B, Gao B. 2019. Spatial self-aggregation effects and national division of city-level PM2.5 concentrations in China based on spatio-temporal clustering. J Clean Prod. 207:875–881.
  • Chen Z, Xie X, Cai J, Chen D, Gao B, He B, Cheng N, Xu B. 2018. Understanding meteorological influences on PM2.5 concentrations across China: a temporal and spatial perspective. Atmos Chem Phys. 18(8):5343–5358.
  • Cheng Z, Li L, Liu J. 2017. Identifying the spatial effects and driving factors of urban PM2.5 pollution in China. Ecol Indic. 82:61–75.
  • Environmental Information Network. 2012. A panorama of air pollution in China seen from space. [accessed 2019 March 5]. http://www.12369.com.cn/news/detail?id=1403.
  • Fu G, Butler D. 2014. Copula-based frequency analysis of overflow and flooding in urban drainage systems. J Hydrol. 510:49–58.
  • Gao M, Guttikunda SK, Carmichael GR, Wang Y, Liu Z, Stanier CO, Saide PE, Yu M. 2015. Health impacts and economic losses assessment of the 2013 severe haze event in Beijing area. Sci Total Environ. 511:553–561.
  • García-Santiago X, Gallego-Fernández N, Muniategui-Lorenzo S, Piñeiro-Iglesias M, López-Mahía P, Franco-Uría A. 2017. Integrative health risk assessment of air pollution in the northwest of Spain. Environ Sci Pollut Res. 24(4):3412–3422.
  • Ge Y, Zhang H, Dou W, Chen W, Liu N, Wang Y, Shi Y, Rao W. 2017. Mapping social vulnerability to air pollution: a case study of the Yangtze River Delta region, China. Sustainability. 9(1):109.
  • He J, Gong S, Yu Y, Yu L, Wu L, Mao H, Song C, Zhao S, Liu H, Li X, et al. 2017. Air pollution characteristics and their relation to meteorological conditions during 2014–2015 in major Chinese cities. Environ Pollut. 223:484–496.
  • Huang R, Zhang Y, Bozzetti C, Ho KF, Cao JJ, Han Y, Daellenbach KR, Slowik JG, Platt SM, Canonaco F, et al. 2014. High secondary aerosol contribution to particulate pollution during haze events in China. Nature. 514(7521):218.
  • Jiang P, Yang J, Huang C, Liu H. 2018. The contribution of socioeconomic factors to PM2.5 pollution in urban China. Environ Pollut. 233:977–985.
  • Joe H. 1997. Multivariate models and multivariate dependence concepts. New York: CRC Press.
  • Kao SC, Govindaraju RS. 2008. Trivariate statistical analysis of extreme rainfall events via the Plackett family of copulas. Water Resour Res. 44(2):1–19.
  • Karmakar S, Simonovic SP. 2009. Bivariate flood frequency analysis. Part 2: a copula‐based approach with mixed marginal distributions. J Flood Risk Manage. 2(1):32–44.
  • Koks EE, Jongman B, Husby TG, Botzen WJW. 2015. Combining hazard, exposure and social vulnerability to provide lessons for flood risk management. Environ Sci Policy. 47:42–52.
  • 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 PM2.5 pollution. Aerosol Air Qual Res. 13(3):943–956.
  • Lavell A, Oppenheimer M, Diop C, Hess J, Lempert R, Li J, Cardona OD. 2012. Climate change: new dimensions in disaster risk, exposure, vulnerability, and resilience In: Field C B, Barros V, Stocker T F, Qin D, Dokken D J, Ebi K L, Mastrandrea M D, Mach K J, Plattner G-K, Allen S K, Tignor M, and Midgley P M, editors. Managing the risks of extreme events and disasters to advance climate change adaptation: special report of the intergovernmental panel on climate change. Cambridge and New York: Cambridge University Press. p: 25–64.
  • Li N, Liu X, Xie W, Wu J, Zhang P. 2013. The return period analysis of natural disasters with statistical modeling of bivariate joint probability distribution. Risk Anal. 33(1):134–145.
  • Lin G, Fu J, Jiang D, Hu W, Dong D, Huang Y, Zhao M. 2013. Spatio-temporal variation of PM2.5 concentrations and their relationship with geographic and socioeconomic factors in China. Int J Environ Res Public Health. 11(1):173–186.
  • Liu X, Li N, Yuan S, Xu N, Shi W, Chen W. 2015. The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors. Sci Total Environ. 538:724–732.
  • Lu F, Xu D, Cheng Y, Dong S, Guo C, Jiang X, Zheng X. 2015. Systematic review and meta-analysis of the adverse health effects of ambient PM2.5 and PM10 pollution in the Chinese population. Environ Res. 136:196–204.
  • Ma LM, Zhang X. 2014. The spatial effect of haze pollution in China and the impact from economic change and energy structure. China Ind Econ. 4:19–31.
  • Mach K, Mastrandrea M. 2014. Climate change 2014: impacts, adaptation, and vulnerability. Vol. 1. Field CB, Barros VR, editors. The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) — Climate Change 2013/2014. Cambridge: Cambridge University Press.p:1371–1438.
  • Milla dos Santos AP, Passuello A, Schuhmacher M, Nadal M, Domingo JL, Martinez CA, Segura-Munoz SI, Takayanagui AMM. 2014. A support tool for air pollution health risk management in emerging countries: a case in Brazil. Hum Ecol Risk Assess: Int J. 20(5):1406–1424.
  • Ming X, Xu W, Li Y, Du J, Liu B, Shi P. 2015. Quantitative multi-hazard risk assessment with vulnerability surface and hazard joint return period. Stochastic Environ Res Risk Assess. 29(1):35–44.
  • Nelsen RB. 2007. An introduction to copulas. Portland, USA: Springer Science & Business Media.
  • Pui DYH, Chen SC, Zuo Z. 2014. PM2.5 in China: measurements, sources, visibility and health effects, and mitigation. Particuology. 13:1–26.
  • Pun VC, Kazemiparkouhi F, Manjourides J, Suh HH. 2017. Long-term PM2.5 exposure and respiratory, cancer, and cardiovascular mortality in older US adults. Am J Epidemiol. 186(8):961–969.
  • Rodriguez JC. 2007. Measuring financial contagion: a copula approach. J Empirical Finance. 14(3):401–423.
  • Tao J, Gao J, Zhang L, Zhang R, Che H, Zhang Z, Lin Z, Jing J, Cao J, Hsu SC. 2014. PM2.5 pollution in a megacity of southwest China: source apportionment and implication. Atmos Chem Phys. 14(16):8679–8699.
  • Wang B, Chen Z. 2010. A GIS-based fuzzy aggregation modeling approach for air pollution risk assessment. In 2010 Seventh International Conference on Fuzzy Systems and Knowledge Discovery. Yantai, China. Vol. 2: IEEE. p. 957–961.
  • Wang G, Gu S, Chen J, Wu X, Yu J. 2016. Assessment of health and economic effects by PM2.5 pollution in Beijing: a combined exposure-response and computable general equilibrium analysis. Environ Technol. 37(24):3131–3138.
  • Wang S, Zhou C, Wang Z, Feng K, Hubacek K. 2017. The characteristics and drivers of fine particulate matter (PM2.5) distribution in China. J Clean Prod. 142:1800–1809.
  • Wang Y, Gao C, Wang A, Wang Y, Zhang F, Zhai J, Li X, Su B. 2014. Temporal and spatial variation of exposure and vulnerability of flood disaster in China. Adv Clim Change Res. 10:391–398.
  • Wang Y, Ying Q, Hu J, Zhang H. 2014. Spatial and temporal variations of six criteria air pollutants in 31 provincial capital cities in China during 2013–2014. Environ Int. 73:413–422.
  • Wu J, Zheng H, Zhe F, Xie W, Song J. 2018. Study on the relationship between urbanization and fine particulate matter (PM2.5) concentration and its implication in China. J Clean Prod. 182:872–882.
  • Wu X, Chen Y, Guo J, Wang G, Gong Y. 2017. Spatial concentration, impact factors and prevention-control measures of PM2.5 pollution in China. Nat Hazards. 86(1):393–410.
  • Xie Y, Chen J, Li W. 2014. An assessment of PM2.5 related health risk and impaired values of Beijing residents in a consecutive high-level exposure during heavy haze days. Environ Sci. 35(1):1–8.
  • Yang D, Ye C, Wang X, Lu D, Xu J, Yang H. 2018. Global distribution and evolvement of urbanization and PM2.5 (1998–2015). Atmos Environ. 182:171–178.
  • Yang K, Yang Y, Zhu Y, Li C, Meng C. 2016. Social and economic drivers of PM2.5 and their spatial relationship in China. Geog Res. 35:1051–1060.
  • Ye Q, Fu JF, Mao JH, Shang SQ. 2016. Haze is a risk factor contributing to the rapid spread of respiratory syncytial virus in children. Environ Sci Pollut Res Int. 23(20):20178–20185.
  • Zhang L, Singh VP. 2007a. Bivariate rainfall frequency distributions using Archimedean copulas. J Hydrol. 332(1–2):93–109.
  • Zhang L, Singh VP. 2007b. Gumbel–Hougaard copula for trivariate rainfall frequency analysis. J Hydrol Eng. 12(4):409–419.
  • Zhang Q, Crooks R. 2012. Toward an environmentally sustainable future: country environmental analysis of the People's Republic of China. Mandaluyong City, Philippines: Asian Development Bank.
  • Zhang Y, Cao F. 2015. Fine particulate matter (PM2.5) in china at a city level. Sci Rep. 5(1):14884.
  • Zhang Y, Wang K, Liu X, Zhang S, Zhou J, Wang C. 2017. The three-dimensional joint distributions of rainstorm factors based on copula function: a case in Kuandian county, Liaoning province. Sci Geog Sin. 37:603–610.
  • Zhang YL, Cao F. 2015. Fine particulate matter (PM 2.5) in China at a city level. Sci Rep. 5:14884.
  • Zheng X, Xu X, Yekeen TA, Zhang Y, Chen A, Kim SS, Dietrich KN, Ho S-M, Lee S-A, Reponen T, et al. 2016. Ambient air heavy metals in PM2.5 and potential human health risk assessment in an informal electronic-waste recycling site of China. Aerosol Air Qual Res. 16(2):388–397.
  • Zhou L, Wu X, Ji Z, Gao G. 2017. Characteristic analysis of rainstorm-induced catastrophe and the countermeasures of flood hazard mitigation about Shenzhen city. Geomat Nat Hazards Risk. 8(2):1886–1897.
  • Zhou T, Ru X. 2012. Research on the cause and treatment of haze in Beijing. J North China Electr Power Univ (Social Sciences). 2:12–16.
  • Zhu L, Gong X, Shen J, Liu L, Liu JF, Liu JL, Xu Z. 2019. Application of computational aerodynamics on the risk prediction of PM2.5 in congenital tracheal stenosis. In: Lhotska L, Sukupova L, Lacković I, Ibbott G, editors. World congress on medical physics and biomedical engineering 2018. IFMBE Proceedings. Singapore: Springer. p: 807–811.