典型文献
Influence of urban spatial and socioeconomic parameters on PM2.5 at subdistrict level:A land use regression study in Shenzhen,China
文献摘要：
The intraurban distribution of PM2.5 concentration is influenced by various spatial,socioe-conomic,and meteorological parameters.This study investigated the influence of 37 pa-rameters on monthly average PM2.5 concentration at the subdistrict level with Pearson cor-relation analysis and land-use regression(LUR)using data from a subdistrict-level air pollu-tion monitoring network in Shenzhen,China.Performance of LUR models is evaluated with leave-one-out-cross-validation(LOOCV)and holdout cross-validation(holdout CV).Pearson correlation analysis revealed that Normalized Difference Built-up Index,artificial land frac-tion,land surface temperature,and point-of-interest(POI)numbers of factories and indus-trial parks are significantly positively correlated with monthly average PM2.5 concentrations,while Normalized Difference Vegetation Index and Green View Factor show significant neg-ative correlations.For the sparse national stations,robust LUR modelling may rely on a priori assumptions in direction of influence during the predictor selection process.The month-by-month spatial regression shows that RF models for both national stations and all stations show significantly inflated mean values of R2 compared with cross-validation results.For MLR models,inflation of both R2 and R2cv was detected when using only national stations and may indicate the restricted ability to predict spatial distribution of PM2.5 levels.Inflated within-sample R2 also exist in the spatiotemporal LUR models developed with only national stations,although not as significant as spatial LUR models.Our results suggest that a denser subdistrict level air pollutant monitoring network may improve the accuracy and robustness in intraurban spatial/spatiotemporal prediction of PM2.5 concentrations.
文献关键词：
中图分类号：
作者姓名：
Liyue Zeng;Jian Hang;Xuemei Wang;Min Shao
作者机构：
School of Atmospheric Sciences,Sun Yat-sen University,and Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai),Zhuhai 519082,China;Key Laboratory of Tropical Atmosphere-Ocean System(Sun Yat-sen University),Ministry of Education,Zhuhai 519000,China;Guangdong Provincial Field Observation and Research Station for Climate Environment and Air Quality Change in the Pearl River Estuary,Guangzhou 510275,China;Institute for Environmental and Climate Research,Jinan University,Guangzhou 510632,China
文献出处：
引用格式：
[1]Liyue Zeng;Jian Hang;Xuemei Wang;Min Shao-.Influence of urban spatial and socioeconomic parameters on PM2.5 at subdistrict level:A land use regression study in Shenzhen,China)[J].环境科学学报（英文版）,2022(04):485-502
A类：
subdistrict,intraurban,socioe,conomic,holdout,Inflated
B类：
Influence,spatial,socioeconomic,parameters,PM2,land,use,regression,study,Shenzhen,China,distribution,influenced,by,various,meteorological,This,investigated,monthly,average,analysis,LUR,using,data,from,air,monitoring,network,Performance,models,evaluated,leave,one,cross,validation,LOOCV,revealed,that,Normalized,Difference,Built,up,Index,artificial,frac,surface,temperature,point,interest,POI,numbers,factories,indus,trial,parks,significantly,positively,correlated,concentrations,while,Vegetation,Green,View,Factor,neg,ative,correlations,For,sparse,national,stations,modelling,may,rely,priori,assumptions,direction,during,predictor,selection,process,shows,RF,both,all,inflated,mean,values,compared,results,MLR,inflation,R2cv,was,detected,when,only,indicate,restricted,ability,levels,within,sample,also,exist,spatiotemporal,developed,although,not,Our,suggest,denser,pollutant,improve,accuracy,robustness,prediction
AB值：
0.467062
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