A novel grey spatial extension relational model and its application to identify the drivers for ambient air quality in Shandong Province, China

被引:19
|
作者
Wu, Honghua [1 ,2 ]
Liu, Sifeng [1 ]
Du, Junliang [1 ]
Fang, Zhigeng [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Econ & Management, Nanjing 211106, Peoples R China
[2] Univ Jinan, Sch Math Sci, Jinan 250022, Peoples R China
基金
中国国家自然科学基金;
关键词
Grey relational analysis; Spatial extension; Ambient air quality; Grey system theory; POLLUTION; OPTIMIZATION; MORTALITY; HEALTH; COHORT;
D O I
10.1016/j.scitotenv.2022.157208
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The ambient air quality is a complex dynamical system that is shocked by a number of subsystems, such as government policies, industry regulation adjustment and internationalization. To identify the drivers for ambient air quality, a grey spatial extension relational analysis model is proposed. Firstly, a spatial extension method for one-dimensional time series of complex systems is introduced, and the two key parameters are obtained based on the grey similarity and proximity relational analysis models. Secondly, grey relational coefficient is calculated by the difference of the three-dimensional vector, and a grey spatial extension relational analysis model is presented. Furthermore, the properties of the proposed model were investigated. Finally, the model is used to identify the drivers of the ambient air quality in eastern coastal Shandong Province, China. Results suggest that the drivers of the ambient air quality vary among cities, but with some common ones. Therefore, this paper provides an important reference for the improvement of ambient air quality.
引用
收藏
页数:11
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