Mixing data modelling method for response of water environment quality to economic development

3rd International Conference on Energy Engineering and Environmental Protection

能源学;生态环境科学

Wang, Jiefang^1 ; Feng, Shuqi^1 ; Pang, Dongyang^1 ; Zhou, Yun^1 ; Liu, Muyuan^2

Management and Economic Department, North China University of Water Resource and Electric Power, Zhengzhou, China^1

Business School, Nanjing University, Nanjing, China^2

关键词: Economic development;    Environmental index;    Environmental Kuznets curves;    Environmental quality;    Low frequency measurements;    Macroeconomic indicators;    Polynomial equation;    Water environments;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/227/5/052024/pdf
DOI  :  10.1088/1755-1315/227/5/052024

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Environmental Kuznets Curve (EKC) is one of the main tools to analyze the response relationship between water environmental quality and economic development. In classical EKC curve modeling process, the environmental index time series and economic index time series must be the same frequency. Because basin water-quality in China has been gradually monitored and released with high frequency, and most macroeconomic indicators are on annual basis, therefore, by the construction of three classes mix data polynomial equation of EKC curve, the mixing data modeling method of the response relationship between water quality and economic development is proposed to adapt to the situation. The mix data model not only avoids destroying original information due to simple low-frequency measurement of high frequency water quality data using classical model, but also through direct mining of high frequency water quality data, the lag time of water environment quality response to economic development can be obtained. To verify the validity of the model, according to the monitoring and statistical data of 2009-2017, a prefecture level city in Henan province of Haihe River Basin is taken as the research object, and EKC three classes mix data polynomial equation of chemical oxygen demand (COD) concentration and ammonia nitrogen concentration is established.