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Health Risk and Resilience Assessment with Respect to the Main Air Pollutants in Sichuan

Author

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  • Junnan Xiong

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China
    State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China)

  • Chongchong Ye

    (School of Civil Engineering and Architecture, Southwest Petroleum University, Chengdu 610500, China)

  • Tiancai Zhou

    (Synthesis Research Centre of Chinese Ecosystem Research Network, Key Laboratory of Ecosystem Network Observation and Modelling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Weiming Cheng

    (State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Rapid urbanization and industrialization in developing countries have caused an increase in air pollutant concentrations, and this has attracted public concern due to the resulting harmful effects to health. Here we present, through the spatial-temporal characteristics of six criteria air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , CO, and O 3 ) in Sichuan, a human health risk assessment framework conducted to evaluate the health risk of different age groups caused by ambient air pollutants. Public health resilience was evaluated with respect to the risk resulting from ambient air pollutants, and a spatial inequality analysis between the risk caused by ambient air pollutants and hospital density in Sichuan was performed based on the Lorenz curve and Gini coefficient. The results indicated that high concentrations of PM 2.5 (47.7 μg m −3 ) and PM 10 (75.9 μg m −3 ) were observed in the Sichuan Basin; these two air pollutants posed a high risk to infants. The high risk caused by PM 2.5 was mainly distributed in Sichuan Basin (1.14) and that caused by PM 10 was principally distributed in Zigong (1.01). Additionally, the infants in Aba and Ganzi had high health resilience to the risk caused by PM 2.5 (3.89 and 4.79, respectively) and PM 10 (3.28 and 2.77, respectively), which was explained by the low risk in these two regions. These regions and Sichuan had severe spatial inequality between the infant hazard quotient caused by PM 2.5 ( G = 0.518, G = 0.493, and G = 0.456, respectively) and hospital density. This spatial inequality was also caused by PM 10 ( G = 0.525, G = 0.526, and G = 0.466, respectively), which is mainly attributed to the imbalance between hospital distribution and risk caused by PM 2.5 (PM 10 ) in these two areas. Such research could provide a basis for the formulation of medical construction and future air pollution control measures in Sichuan.

Suggested Citation

  • Junnan Xiong & Chongchong Ye & Tiancai Zhou & Weiming Cheng, 2019. "Health Risk and Resilience Assessment with Respect to the Main Air Pollutants in Sichuan," IJERPH, MDPI, vol. 16(15), pages 1-19, August.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:15:p:2796-:d:255035
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    References listed on IDEAS

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    1. Fazley K. Siddiq & Halyna Klymentieva & Taylor J. C. Lee, 2023. "Applying the Lorenz Curve and Gini Coefficient to Measure the Population Distribution," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 29(3), pages 177-192, August.
    2. Yinpeng Mo & Guangming Shi & Xia Jiang & Tianzhi Luo & Shuhua Zhou & Fumo Yang, 2023. "Transport Channels of Air Pollutants Affecting the Southern Sichuan Basin Based on Gridded Dispersion Simulation," IJERPH, MDPI, vol. 20(7), pages 1-16, April.
    3. Liang Xiao & Yong Zhou & He Huang & Yu-Jie Liu & Ke Li & Meng-Yao Li & Yang Tian & Fei Wu, 2020. "Application of Geostatistical Analysis and Random Forest for Source Analysis and Human Health Risk Assessment of Potentially Toxic Elements (PTEs) in Arable Land Soil," IJERPH, MDPI, vol. 17(24), pages 1-19, December.

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