School of Computer and Information Science, Southwest University, Chongqing, 400715, China.
Environ Sci Pollut Res Int. 2015 Apr;22(8):6372-80. doi: 10.1007/s11356-015-4229-9. Epub 2015 Mar 3.
Weather system is a relative complex dynamic system, the factors of the system are mutually influenced PM2.5 concentration. In this paper, a new method is proposed to quantify the influence on PM2.5 by other factors in the weather system and identify the most important factors for PM2.5 with limited resources. The relation map (RM) is used to figure out the direct relation matrix of 14 factors in PM2.5. The decision making trial and evaluation laboratory(DEMATEL) is applied to calculate the causal relationship and extent to a mutual influence of 14 factors in PM2.5. According to the ranking results of our proposed method, the most important key factors is sulfur dioxide (SO2) and nitrogen oxides (NO(X)). In addition, the other factors, the ambient maximum temperature (T(max)), concentration of PM10, and wind direction (W(dir)), are important factors for PM2.5. The proposed method can also be applied to other environment management systems to identify key factors.
天气系统是一个相对复杂的动力系统，系统中的因素相互影响 PM2.5 浓度。本文提出了一种新的方法，用于量化天气系统中其他因素对 PM2.5 的影响，并在有限的资源下确定对 PM2.5 影响最重要的因素。关系图（RM）用于构建 PM2.5 中 14 个因素的直接关系矩阵。决策试验和评价实验室（DEMATEL）用于计算 PM2.5 中 14 个因素相互影响的因果关系和程度。根据我们提出的方法的排名结果，最重要的关键因素是二氧化硫（SO2）和氮氧化物（NO(X)）。此外，其他因素，如环境最高温度（T(max)）、PM10 浓度和风向（W(dir)），也是 PM2.5 的重要因素。该方法还可应用于其他环境管理系统，以识别关键因素。
