摘要
基于空间变系数模型,采用局部线性BGWR拟合方法,分别从经济、人口和环境的角度,选取9个指标,对2016年中国各地区PM2.5浓度的空间差异性及其影响因素进行探究.结果表明:降水、天气、森林覆盖率、对外开放水平、污染治理和地区生产总值与PM2.5浓度显著负相关;单位GDP能耗、产业结构和城镇化率与PM2.5浓度显著正相关.其中,天气因素和城镇化率的影响程度较其他因素更为显著.最后,提出人口空间合理布局、产业结构优化升级等建议,旨在成功实现PM2.5污染控制和减排.
Based on the spatial variable coefficient model,the local linear BGWR fitting method is used to estimate the model parameters.From the perspectives of economy,population and environment,nine indicators are selected to explore the spatial differences and influencing factors of PM2.5 in China’s 31 regions in 2016.The results show that precipitation,weather,forest coverage,opening level,pollution control and household consumption level are significantly negatively correlated with PM2.5 concentration,and unit GDP energy consumption,industrial structure,urbanization rate have significant positive correlations with PM2.5 concentration.The degree of influence of weather factors and urbanization rate is more significant than that of other factors.Finally,the paper proposes the rational layout of population space and the optimization and upgrading of industrial structure,aiming at successfully achieving PM2.5 pollution control and emission reduction.
作者
张晨晨
张辉国
胡锡健
ZHANG Chen-chen;ZHANG Hui-guo;HU Xi-jian(College of Mathematics and System Sciences,Xinjiang University,Urumqi 830046,China)
出处
《数学的实践与认识》
北大核心
2020年第3期187-193,共7页
Mathematics in Practice and Theory
基金
新疆高校科研项目(XJEDU2017M001).
