ZHAO Xiaoliang1, QI Qingjie1, ZHAO Dongyang1, ZHAO Guozhi2, ZHENG Jiao3
(1. College of Source and Environment Engineering,Liaoning Technical University,FuXin 123000,China;
2.College of Environmental and ResourceSciences,Zhejiang University,HangZhou 310029,China;
3. Institute of Chemical Engineering, Nanjing University of Science & Technology, Nanjing 210094, China)
Abstract: with the unceasing change of Fuxin City, China,former air monitoring can not fully reflect the status of air environmental quality, so the optimization of air monitoring sites is imperative. Based on the classification of distance coefficient of data, optimization model for air monitoring sites was established.Clustering analysis of the optimization model was also discussed. Results show that the SO2 concentration in the correlation coefficient is 0.984, PM10 correlation coefficient is 0.968, and NO2 correlation coefficient is 0.973. CALPUFF model correlation coefficient between simulation value and the actual monitoring is higher than 0.75, indicating that the optimized Fuxin city air monitoring points is objective representative.
Key words: Fuxin City; Atmospheric monitoring site; optimization; Clustering analysis; CALPUFF air quality model
EARTH AND ENVIRONMENT Vol. 43, No.3, Tot No.305, 2015, Page 350-355
