摘要
【目的】客观评价城市环境空气质量并分析其影响因素,对了解空气质量现状,控制污染源具有重要意义。【方法】依据污染因子浓度监测值构建基于模糊数学综合评价法的环境空气质量评价方法用于长治市的环境空气质量评价,并对首要污染因子与其他污染因子进行斯皮尔曼相关性分析。【结果】采用阶梯型隶属度函数的模糊综合评价法相较AQI(Ambient Air Quality Index)和内梅罗指数法能够综合所有污染因子的作用更加全面评价环境空气质量,且长治市2017—2022共6年间环境空气质量状况在逐渐好转。长治市的首要污染因子为PM_(10),且与PM_(2.5)、SO_(2)、NO_(2)、CO均具有相关性,相关性依次递减,而与O_(3)不具相关性。通过污染因子时间分布特征分析发现,每年一、四季度PM_(2.5)、PM_(10)、CO、NO_(2)、SO_(2)的浓度会上升,二、三季度5种污染因子的浓度呈现下降趋势,并且一、四季度5项污染因子的浓度值高于二、三季度。新冠肺炎疫情暴发期间,所有污染因子均呈现下降趋势,且CO浓度的下降趋势最为明显。
【Purposes】Objective evaluations of urban ambient air quality and analyses of its influencing factors are of great significance for understanding of current air quality situation and controlling of pollutants.【Methods】In this paper,an ambient air quality evaluation method based on fuzzy mathematics comprehensive evaluation method was constructed on the basis of the monitoring values of pollution factor concentration for the ambient air quality assessment of Changzhi City,and Spearman correlation analyses were carried out between the primary pollution factor and other pollution factors.【Results】The results show that compared with AQI(Ambient Air Quality Index)and Nemerow index method,the fuzzy comprehensive evaluation method using the stepped membership function can evaluate ambient air quality more comprehensively.The ambient air quality of Changzhi City was gradually improving from 2017 to 2022.The primary pollution factor in Changzhi City is PM_(10),and it is correlated with PM_(2.5),SO_(2),NO_(2),and CO,and the correlations decrease in turn,but not with O_(3).Through the analyses of the time distribution characteristics of pollution factors,it can be found that the concentrations of PM_(2.5),PM_(10),CO,NO_(2),and SO_(2) increase in the fourth quarter of each year,while the concentrations of 5 pollution factors decrease in the second and third quarters of each year,and the concentrations of 5 pollution factors in the fourth quarter are higher than those in the second and third quarters of each year.During the outbreak of COVID-19,all pollution factors show decreasing trends,and the decreasing trend of CO concentration is the most obvious.
作者
徐双
秦慧敏
邱兰
董云云
李灯熬
赵菊敏
XU Shuang;QIN Huimin;QIU Lan;DONG Yunyun;LI Deng’ao;ZHAO Jumin(College of Artificial Intelligence,Taiyuan University of Technology,Taiyuan,Shanxi,China;Key Laboratory of Data Governance and Intelligent Decision Making of Shanxi Province,Taiyuan University of Technology,Taiyuan,Shanxi,China;College of Software,Taiyuan University of Technology,Taiyuan,Shanxi,China;School of Mathematical Sciences,Shanxi University,Taiyuan,Shanxi,China;Xinjiang Shiwen Technology Development Co.,LTD,Urumqi,Xinjiang,China)
出处
《太原理工大学学报》
北大核心
2025年第3期543-558,共16页
Journal of Taiyuan University of Technology
基金
国家自然科学基金资助项目(62102280,62306206)
国家自然科学基金面上项目(61972273)
山西省基础研究计划资助项目(20210302124167)
山西省重点研发计划项目(202102020101001)
山西省关键核心技术和共性技术研发攻关专项项目(2020XXX007)。
关键词
长治市
环境空气质量
模糊数学综合评价法
影响因素
斯皮尔曼相关系数法
Changzhi city
ambient air quality
fuzzy mathematics comprehensive evaluation method
influencing factors
Spearman correlation coefficient method
作者简介
第一作者:徐双(1990−),博士,讲师,主要研究领域为空天网络、边缘计算、大数据技术等,(E-mail)xushuang@tyut.edu.cn;通信作者:李灯熬(1971−),博士,教授,博士生导师,研究方向为大数据、物联网关键技术及应用等,(E-mail)lidengao@tyut.edu.cn.
