目的 构建遵义市细颗粒物(particulate matter with an aerodynamic diameter≤2.5μm,PM2.5)土地利用回归(land use regression,LUR)模型.方法 收集整理遵义市常规空气质量监测站点2020年1月1日到2020年12月31日的逐小时PM2.5监测数据,以及土地利用、道路、人口密度、海拔等地理信息变量数据和气象因子数据,以PM2.5浓度为因变量,地理信息变量和气象因子为自变量,进行多元逐步线性回归,构建模型,并采用留一交叉验证(leave-one-out cross validation,LOOCV)对模型表现进行验证.结果 所建模型公式为Y=72.656-0.026×海拔-0.009× NDVI-0.62×平均气温-383.512×平均降水量,模型的R2=0.74,调整R2=0.72,交叉验证的R2=0.69,RMSE=3.51,空间分辨率高(250 m×250 m).结论 模型拟合情况较好,充分反映了遵义市PM2.5空间分布的影响因素,可以用于个体暴露水平的估计,为环境健康流行病学研究提供有力支持.
Establishment and analysis of LUR model for PM2.5,Zunyi
Objective To construct a land use regression(LUR)model for particulate matter with an aerodynamic diameter 2.5 μm(PM2.5)in Zunyi.Methods Collect and organize hourly PM2.5 monitoring data from routine air quality monitoring stations from January 1,2020 to December 31,2020,as well as geographic information data such as land use,roads,population density,altitude,and meteorological factors in Zunyi.Conduct multiple stepwise linear regression with PM2.5 concentration as the dependent variable and geographic information variables and meteorological factors as independent variables to construct a model.Use leave-one-out cross validation(LOOCV)to verify the performance of the model.Results The model formula is Y=72.656-0.026 × altitude-0.009 × NDVI-0.62 × average temperature-383.512 × average precipitation.The model had R2=0.74,adjusted R2=0.72,cross validation R2=0.69,RMSE=3.51,and a high spatial resolution(250 m × 250 m).Conclusion The model fits well and fully reflects the influencing factors of PM2.5 spatial distribution in Zunyi.It can be used to estimate individual exposure levels and provide strong support for environmental health epidemiological research.
万方数据
维普
