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9 September 2019 Air Quality Evaluation of Bo Hai Coastal Region Based on Entropy Weight Method
Weiyang Yu, Songjia Zhang, Huitao Shen, Shaodong Yu, Teng Chen
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Abstract

Yu, W.; Zhang, S.; Shen, H.; Yu, S., and Chen, T., 2019. Air quality evaluation of Bo Hai coastal region based on entropy weight method. In: Gong, D.; Zhu, H., and Liu, R. (eds.), Selected Topics in Coastal Research: Engineering, Industry, Economy, and Sustainable Development. Journal of Coastal Research, Special Issue No. 94, pp. 83–86. Coconut Creek (Florida), ISSN 0749-0208.

Air quality is an important issue for Bo Hai Coastal Region, and the government have invest much resource to control the air pollution. However, before invest any resource to improve the air quality, an effective and accurate air quality assessment method should be proposed. In viewing the limitation of the existing air quality assessment method, this paper proposed a much more comprehensive and objective method to assess the air quality by employing the entropy weight method to determine the weight of the evaluation index. Combining the fuzzy evaluation method with the gray cluster analysis method, according to the characteristics of pollutants, the membership functions of different pollutants belonging to different pollution levels are proposed. Based on it, the membership degree of each pollutant to different levels and the weighted membership degree were calculated, and the regional air quality comprehensive evaluation results are determined. Finally, the validity of the proposed method was justified by the numerical analysis.

©Coastal Education and Research Foundation, Inc. 2019
Weiyang Yu, Songjia Zhang, Huitao Shen, Shaodong Yu, and Teng Chen "Air Quality Evaluation of Bo Hai Coastal Region Based on Entropy Weight Method," Journal of Coastal Research 94(sp1), 83-86, (9 September 2019). https://doi.org/10.2112/SI94-015.1
Received: 20 January 2019; Accepted: 30 March 2019; Published: 9 September 2019
KEYWORDS
air quality
comprehensive evaluation
entropy weight method
fuzzy evaluation
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