胡焕庸线两侧空气质量状况及影响因素分析

Analysis of air quality and its influential factors on both sides of Huhuanyong Dividing Line

基于2015—2018年胡焕庸线两侧44个主要城市的AQI监测数据,利用数理统计、空间插值和层次聚类法分析区域AQI的时空分布特征,并运用ESDA技术和空间回归模型探讨AQI的自然、社会经济影响因素。结果表明,时间变化上,两侧AQI季均变化规律为夏季最好,冬季最差,东侧季节变化幅度大于西侧;月均变化整体呈U形分布,1月份浓度均较高;工作日内污染物累增,AQI在一周后半段达到最大值。空间分布上,AQI呈现东侧中部高西侧低的特点,分布区域特征明显;2015—2018年西侧空气质量优占41.93%,东侧为31.31%,AQI与PM_(2.5)、PM_(10)、O3相关性显著,首要污染物来自于PM_(10)和PM_(2.5)。AQI与影响因素在空间上呈现显著集聚效应,GWR模型在模拟影响程度和空间差异方面优于OLS模型,林草覆盖率对AQI最大,其他依次为相对湿度、日照时数、人口密度、气压、第二产业比重。

The present paper intends to introduce our comparative analysis of the spatiotemporal evolution of the air quality on both sides of the Huhuanyong Dividing Line(short for Hu Line)and its relationship with the influential factors.To achieve the purpose,we have collected the AQI monitoring data of 44 major cities from 2015 to 2018 and analyzed the time series characteristic features of the air quality on the both sides of the line via a mathematical statistics.And,then,we have managed to analyze the spatial distribution pattern of the regional AQI by establishing a Kriging index model to generate AQI raster data.And,finally,a multi-factor comprehensive analysis model of AQI so as to analyze the natural and socioeconomic factors so as to clarify the factors that are influencing the AQI through an analysis of the spatial correlation of AQI and the other influential factors in combination with ESDA method and spatial regression model.The results show that:(1)In terms of time prolonging,the AQI seasonal distribution on the both sides of the Hu Line may be getting to be more and more similar,the best change used to be taking place in summer,whereas the least change used to occur in winter.The seasonal variation on its eastern side should be greater than on its western side,whereas the monthly mean change tends to take place being U-shaped.For example,the higher changing contrast concentration rate may take place in January,while the lowest value of AQI can be reached in August and September.And,whatever the weekly mean change,the similar changes ought to take place in every 4 seasons of a year.Besides,with the increase of the air pollution during the working days,the AQI may reach the maximalist in the second half of the week;(2)In terms of the spatial distribution,it would be possible to use Hu’s Line as an important dividing sign of the air quality distribution in the country.For example,the both sides of AQI can be characterized by the high east and the low west due to its remarkable gap-distribution area.Say,the ratio of the excellent air quality during the years of 2015-2018 has been estimated as41.93%in its western side but 31.31%in its eastern side,with its AQI being significantly correlated in PM_(2.5),PM_(10) and O3,with the primary pollutants being from PM_(10) and PM_(2.5);(3)Both AQI and natural and socioeconomic factors turn out to be noticeably spatial-autocorrelated.And,the GWR model has been found spatially hetero-genetical in influential factors over the OLS model.Besides,the regression coefficient of the GWR model also suggest that the grass coverage and population density has the biggest impact on the AQI,with the rest influential factors,such as the relative humidity,the sunshine hours,the population density,the pressure and proportion of the secondary industry,among which forestry thickness and grass coverage should also be the significant factors that inhibit the AQI.