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Correlation Analysis of PM 10 and the Incidence of Lung Cancer in Nanchang, China

Author

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  • Yi Zhou

    (College of Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Lianshui Li

    (College of Economics and Management, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Lei Hu

    (Agrometeorological Experiment Station of Jiangxi Province, Nanchang 330200, China)

Abstract

Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM 10 ) is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO 2 , NO 2 , PM 10 , annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI). Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures.

Suggested Citation

  • Yi Zhou & Lianshui Li & Lei Hu, 2017. "Correlation Analysis of PM 10 and the Incidence of Lung Cancer in Nanchang, China," IJERPH, MDPI, vol. 14(10), pages 1-19, October.
  • Handle: RePEc:gam:jijerp:v:14:y:2017:i:10:p:1253-:d:115700
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    References listed on IDEAS

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    1. Sueyoshi, Toshiyuki & Yuan, Yan, 2015. "China's regional sustainability and diversified resource allocation: DEA environmental assessment on economic development and air pollution," Energy Economics, Elsevier, vol. 49(C), pages 239-256.
    2. Sueyoshi, Toshiyuki & Yuan, Yan, 2017. "Social sustainability measured by intermediate approach for DEA environmental assessment: Chinese regional planning for economic development and pollution prevention," Energy Economics, Elsevier, vol. 66(C), pages 154-166.
    3. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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    Cited by:

    1. Ning Zhang & Zaiwu Gong & Kedong Yin & Yuhong Wang, 2018. "Special Issue “Decision Models in Green Growth and Sustainable Development”," IJERPH, MDPI, vol. 15(6), pages 1-8, May.

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