摘要
采用区间型空间自回归面板模型,分析长三角地区27个城市PM_(2.5)的空间相关性,以及PM_(10)、SO_(2)、CO、NO_(2)、O_(3)对PM_(2.5)的影响.通过对比空间自回归中点模型、空间自回归最小最大模型、空间自回归中点半径模型和空间自回归参数化模型,获得空间相关系数和影响系数,并评估了4个模型的拟合精度.结果显示:空间自回归中点半径模型的拟合效果最好;长三角城市群的PM_(2.5)存在正向的空间溢出效应;PM_(10)、CO正向影响PM_(2.5)质量浓度,O_(3)的作用相反,SO_(2)和NO_(2)的影响则不显著.基于空间自回归中点半径模型,进一步预测了杭州、合肥、南京和上海4个城市的PM_(2.5)质量浓度.结果表明,预测值与真实值有较高的拟合度.
This study employed an interval spatial autoregressive panel model to analyze the spatial correlation of PM_(2.5)across 27 cities in the Yangtze River Delta,as well as the impacts of PM_(10),SO_(2),CO,NO_(2),and O_(3)on PM_(2.5).By comparing four models—spatial autoregression models based on the centre and range method,spatial autoregression models based on the min-max method,spatial autoregression models based on the centre method,and spatial autoregression models based on the parametrized method,we obtained spatial correlation coefficients and impact coefficients while evaluating the fitting accuracy of the models.Results indicated that the spatial autoregression models based on the centre and range method exhibited the best fitting performance.PM_(2.5)in the Yangtze River Delta urban agglomeration demonstrated a positive spatial spillover effect.PM_(10)and CO positively influenced PM_(2.5)concentrations,whereas O_(3)exerted a negative impact,and the effects of SO_(2)and NO_(2)were statistically insignificant.Using the spatial autoregression models based on the centre and range method,this study further forecasted the mass concentration of PM_(2.5)in Hangzhou,Hefei,Nanjing,and Shanghai.The results showed a high degree of fit between the predicted values and the actual values.
作者
张雨琪
田瑞琴
夏淼杰
ZHANG Yuqi;TIAN Ruiqin;XIA Miaojie(School of Mathematics,Hangzhou Normal University,Hangzhou 311121,China)
出处
《杭州师范大学学报(自然科学版)》
2025年第4期337-346,共10页
Journal of Hangzhou Normal University(Natural Science Edition)
