Evaluation of Urban Air Quality Based on Entropy Weight Method
DOI:
https://doi.org/10.54097/2cjwyx56Keywords:
Entropy Weight Method, Multi-index Evaluation, Air Pollution and Control, Air Quality Index (AQI).Abstract
With the rapid development of China's economy and the continuous growth of population, environmental problems have become an important challenge to be solved urgently.In this study, entropy weight method is used to process the data in order to solve the common problem of multi-index evaluation of environmental problems. By calculating the information entropy between the indicators to determine the weights, avoid subjective errors, fully consider the relative importance of each indicator, and establish a mathematical model between the Air Quality index (AQI) and different pollutant concentrations.This paper describes in detail the selection of SO2, PM10, NO2, NO, O3, PM2.5 six indicators to evaluate the air quality status, and explains the source and characteristics of each indicator. Through data standardization and weight determination, the entropy weight method obtained the comprehensive score of the air quality of each city from 2013 to 2021, showing the air quality of different cities.Finally, the paper puts forward suggestions to improve air quality, including measures to reduce fossil fuel use, promote clean energy, and strengthen emission management and limits.
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A P I K, Wiharja, A S, et al. The air quality index based on measurements of mobile air quality monitoring station at the waste-to-energy incineration plant PLTSa Bantargebang [J]. IOP Conference Series: Earth and Environmental Science, 2021, 926(1):
Ghosh M, Chatterjee N P, Pradhan K M, et al. ASSESSMENT OF AMBIENT AIR QUALITY IN INDUSTRIALCLUSTER AT PARADIP (INDIA) BASED ON AIR QUALITY INDEX(AQI) [J]. Ecology, Environment and Conservation Paper, 2022, 28 (August S):
Adiang C M, Cedric Y N, Arti C, et al. Measurement of fine particle concentrations and estimation of air quality index (AQI) over northeast Douala, Cameroon. [J]. Environmental monitoring and assessment, 2023, 195(8): 965-965.
Zexi J, Yunchuan G, Huaxing C, et al. Characteristics of ambient air quality and its air quality index (AQI) model in Shanghai, China. [J]. Journal of The Science of the total environment, 2023896652, 84-165284.
Wang Visiting, Zhao Wencheng, and Jiang Shan. Based on multiscale dynamic characteristics analysis of air quality index [J]. Journal of environmental science and technology, 2021, 44 (07): 49-59.
Wang Fu-ming, Li Ming-Yan, Zhang Mei-Hang, et al. Change characteristics of air quality in 31 key cities in China from 2014 to 2018 [J]. China's public health management, 2020, 4 (4) :441-445.
A S H, K P D. The Air Quality Index (AQI) in historical and analytical perspective a tutorial Review. [J]. Journal of Talanta, 60-125260-2023267252.
R H, M R, A H. Assessment of air quality index (AQI) in Riyadh, Saudi Arabia[J]. IOP Conference Series: Earth and Environmental Science,2022,1026(1):
Sanjoy M, Sirajuddin A, Santu G, et al.Evaluation of air quality index for air quality data interpretation in Delhi, India[J].CURRENT SCIENCE, 2019,119(6):1019-1026.
Qinghua S, Huanhuan Z, Wanying S, et al.Development of the National Air Quality Health Index - China, 2013-2018. [J].China CDC weekly,2021,3(4):61-64.
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