基于多元线性回归模型的东莞市空气质量指数研究  

Study on air quality index in Dongguan based on multiple linear regression model

作　　者：许紫潼 方嘉声 陈玉兰 Xu Zitong;Fang Jiasheng;Chen Yulan(School of Environment and Civil Engineering,Dongguan University of Technology,Dongguan 523808)

机构地区：[1]东莞理工学院生态环境与建筑工程学院,广东东莞523808

出　　处：《环保科技》2024年第2期40-44,共5页Environmental Protection and Technology

摘　　要：东莞市空气污染一直是市政府高度重视的问题,实证分析该城市空气质量的主要影响因素,对提高该城市空气质量有指导意义。本文依据中国环境监测总站发布的东莞市2013年12月-2019年12月的空气质量实时监测数据,运用计量经济学知识,对东莞市空气质量的影响因素(包括PM_(2.5)、PM_(10)、SO_(2)、CO、NO_(2)、O_(3)等污染物浓度)进行实证研究。运用Stata软件进行多元线性回归实证分析,结果显示东莞市首要大气污染物为PM_(2.5)、O_(3)、NO_(2),同时提出了改善东莞市空气质量和生态环境的建议。The Dongguan municipal government has always attached great importance to air pollution.The empirical analysis of the main factors of the city's air quality is of guiding significance for improving the city's air quality.Based on the real-time air quality monitoring data of Dongguan City from December 2013 to December 2019 released by China General Station of Environmental Monitoring,this paper conducted an empirical study on the influencing factors of Dongguan City's air quality(including the concentration of pollutants such as PM_(2.5),PM_(10),SO_(2),CO,NO_(2) and O_(3))by using the knowledge of econometric economy.The Stata software was used to conduct multiple linear regression empirical analysis,and the results showed that the main air pollutants in Dongguan city were PM_(2.5),O_(3) and NO_(2).Relevant suggestions were put forward to improve the air quality and ecological environment of Dongguan city.

关 键 词：空气质量指数 计量经济 多元回归线性分析 STATA软件 

分 类 号：X322[环境科学与工程—环境工程]