统计与数据科学学院知识库

中原城市群正处于加速崛起的关键时期，在其发展的进程中注入生态文明理念，对于中原城市群的绿色、高质量发展具有十分重要的意义。但是近年来，中原城市群部分城市空气污染问题日益突出，严重阻碍了中原城市群的可持续发展。因此，探究中原城市群空气质量时空分布特征，并对其影响因素进行研究，有助于推动中原城市群更好地实现可持续发展。
结合研究目的，本文首先对大气污染的时空分布特征、大气污染影响因素的指标选择以及大气污染影响因素的研究方法的相关文献进行整理与归纳。发现，现有以中原城市群为研究范围，探索其空气质量指数(AQI)的空间分布特征的文献较少，并且采用地理加权回归模型对该区域空气质量影响因素进行异质性分析的文献更是缺乏。因此，本文选用中原城市群 2015～2018 年空气质量指数（AQI）
数据对该区域大气污染的时空分布特征及影响因素进行分析。
其次，研究中原城市群大气污染时空分布特征时，采用核密度估计、空间自相关法、空间描述性统计分析和数据可视化等方法对 29 个城市 2015～2018 年AQI 数值进行梳理。研究表明，考察期内中原城市群大气污染范围显著缩小，空气质量逐年向好；从季节特征来看，春、秋季节 AQI 数值大小居中，夏季 AQI数值较低，冬季 AQI 数值较高，且春、冬季 AQI 数值呈逐年下降的趋势；从月度特征来看，AQI 月均值呈现出“U”型分布的特征，且 6、7、8 月 AQI 数值最小；从日度特征来看，空气质量优良日总数逐年增加，空气污染聚集特征明显，空气质量优良区位于中原城市群东南部，而空气质量相对劣质区域则始终出现于中北部地区。然后，结合环境污染影响因素的理论框架 STIRPAT 模型和 EKC 假设，选取经济发展、人口聚集、产业结构、对外开放、科技进步、尾气排放、环境规制等7 个方面的因素，对影响大气污染的社会经济因素进行了研究。且从空间异质性的视角出发，运用地理加权回归模型对各因素进行逐年分析。研究结果表明：人均 GDP、城市人口密度和汽车尾气排放的增加是促进中原城市群城市空气质量
恶化的重要因素，城市绿化水平、对外开放水平和科技水平的提高对中原城市群
空气质量改善具有显著的推动作用。此外，各因素对大气污染的影响具有明显的
空间异质性。对人均 GDP 弹性系数敏感的城市主要分布在中原城市群的南部；
对外开放水平弹性系数大的城市已经从 2015 年的西南地区转变为 2018 年的北
部地区；城市绿化水平的提高对空气质量改善较大的城市位于中原城市群的东南
部，且其改善程度逐年增大；科技水平的提高对空气质量的改善作用也在逐年增
强；对于汽车尾气排放弹性系数敏感的城市主要分布在东部及东南部地区，影响
程度由东向西逐渐递减，对空气污染的恶化程度越来越强烈。
最后，将中原城市群 AQI 的时空分布特征及影响因素分析所得到的结果进行归纳，得出其主要结论，并给出相应的建议及展望。

The Central Plains urban agglomeration is in a critical period ofaccelerating its rise. Injecting the concept of ecological civilization into its development process is of great significance to the green and high-quality development of the Central Plains urban agglomeration. However, in recent years, the problem of air pollution in some cities of the Central
Plains urban agglomeration has become increasingly serious, which has
seriously hindered the sustainable development of the Central Plains urban agglomeration. Therefore, exploring the temporal and spatial distribution characteristics of air quality in the Central Plains urban agglomeration and researching its influencing factors will help promote the better sustainable development of the Central Plains urban agglomeration. Combining the research purposes, this article first sorts out and summarizes the relevant literature on the temporal and spatial distribution characteristics of air pollution, the index selection of air pollution influencing factors, and the research methods of air pollution influencing factors. It is found that there are fewer documents exploring the spatial distribution characteristics of the air quality index (AQI) with the Central Plains urban agglomeration as the research scope, and there are more documents using geographically weighted regression models to analyze the heterogeneity of the regional air quality influencing factors. It is lacking.
Therefore, this paper selects the air quality index (AQI) data of the Central 
Plains urban agglomeration from 2015 to 2018 to analyze the spatial and
temporal distribution characteristics and influencing factors of air pollution in the region.
Second, when studying the spatial and temporal distribution characteristics of air pollution in the Central Plains urban agglomeration,
methods such as nuclear density estimation, spatial autocorrelation, spatial descriptive statistical analysis, and data visualization were used to sort out the AQI values of 29 cities from 2015 to 2018. Studies have shown that during the inspection period, the air pollution range of the Central Plains urban agglomeration has been significantly reduced, and the air quality has been improving year by year; from the perspective of seasonal characteristics, the AQI value in spring and autumn is in the middle, the summer AQI value is lower, the winter AQI value is higher, and the spring , The winter AQI value shows a downward trend year by year; from the monthly characteristics, the monthly average AQI presents a "U"-shaped distribution, and the AQI value in June, July, and August is the smallest; from the daily characteristics, the air quality is good The total number of days has increased year by year, and air pollution has obvious
characteristics. Areas with good air quality are located in the southeast of
the Central Plains urban agglomeration, while areas with relatively poor air
quality always appear in the central and northern regions. Then, combined with the STIRPAT model and EKC hypothesis, the  theoretical framework of environmental pollution influencing factors, seven factors including economic development, population agglomeration, industrial structure, opening to the outside world, technological progress, exhaust emissions, and environmental regulations are selected to affect the society that affects air pollution. Economic factors were studied. And from
the perspective of spatial heterogeneity, the geographically weighted
regression model is used to analyze each factor year by year. The results of the study show that the increase in per capita GDP, urban population
density and automobile exhaust emissions are important factors that
promote the deterioration of urban air quality in the Central Plains urban
agglomeration. The improvement of urban greening, opening to the outside world and technological level have significant improvements in the air quality of the Central Plains urban agglomeration. The driving role of the.
In addition, the influence of various factors on air pollution has obvious
spatial heterogeneity. Cities sensitive to the elastic coefficient of per capita
GDP are mainly distributed in the southern part of the Central Plains urban agglomeration; the cities with a large elastic coefficient of opening to the outside world have changed from the southwest region in 2015 to the northern region in 2018; the improvement of urban greening has improved air quality Larger cities are located in the southeast of the Central Plains urban agglomeration, and the degree of improvement is increasing year by year; the improvement of technology level is increasing year by year; the cities sensitive to the elastic coefficient of automobile exhaust emission are mainly distributed in the east and southeast. In the region, the degree of influence gradually decreases from east to west, and the degree of deterioration of air pollution is getting stronger and stronger.

Finally, the results obtained from the analysis of the temporal and spatial distribution characteristics and influencing factors of the Central Plains urban agglomeration are summarized, and the main conclusions are drawn, and corresponding suggestions and prospects are given.