Abstract
Assessment of and controlling air pollution are urgent global issues where international cooperation is deemed necessary. Although a very relevant data source can be obtained through continuous monitoring of air quality, measuring air pollutant concentrations is quite difficult when compared to other environmental indicators. We mainly have three different aims for the current study: (1) we propose the computation of the interval weights of decision makers (DMs) based on a group multiple criteria decision making (GMCDM) model; (2) we aim to rank the overall preferences of DMs by the possibility concepts; (3) we aim to evaluate the air quality in China using the most recent data based on our proposed method. We consider three monitoring stations, namely Luhu Park, Wanqingsha, and Tianhu, and the data for SO2, NO2, and PM10 are collected for November 2017, 2018, and 2019. The results from our innovative model show that November 2019 had the best air quality. Finally, robustness analyses are also performed to confirm the discriminatory power of the proposed approach.
Highlights
The industrial revolution was the trigger for the discharge of harmful substances into the air at a growing rate, which has been non-stop since 1850
We mainly have three different aims for the current study: (1) we propose the computation of the interval weights of decision makers (DMs) based on a group multiple criteria decision making (GMCDM) model; (2) we aim to rank the overall preferences of DMs by the possibility concepts; (3) we aim to evaluate the air quality in China using the most recent data based on our proposed method
The issue related to the assessment of air pollution/air quality has been widely engaged by empirical researchers for different geographical locations, and various approaches have been used to investigate this topic including land use regression modeling and mobile monitoring [29,30,31], statistical analysis [32], multivariate analysis [33,34], the proposed use of the air quality index [35], and the atmosphere evaluation and research integrated model [36]
Summary
The industrial revolution was the trigger for the discharge of harmful substances into the air at a growing rate, which has been non-stop since 1850. Given that the determination of the exact criterion weights can become a cumbersome task, the use of weight intervals constitutes a flexible approach to overcome this issue [27] Putting these methodologies into perspective, the use of MCDM models for measuring and monitoring air quality is a growing research field with a handful of recently published papers [28]. Distinct from previous research, possibility fuzzy concepts are employed to rank the overall preferences of DMs. To further clarify, we mainly have three different aims for the current study: (1) we propose the computation of the interval weights of DMs based on a GMCDM model; (2) we aim to rank the overall preferences of DMs by the possibility concepts; (3) we aim to evaluate the air quality in China using the most recent data based on our proposed method.
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