Spatial Distribution Of Major Pollutants In The Yellow River Basin Predicted Based On LUR/BME

Air pollution is a significant concern in terms of environmental and public health,especially when considering the impact of air pollution on human well-being.Understanding the distribution of pollution concentrations at a highly localized level is crucial for studying the effects of air pollution on human health.In China,the Yellow River Basin is an important region in terms of population activity and economic development,but it is also facing significant air pollution challenges.Nitrogen Dioxide（NO₂）and Fine Particulate Matter(PM_2.5)with a diameter of 2.5μm or less are the primary pollutants in the Yellow River Basin,and their emissions remain high,posing a considerable health risk to the local population.Therefore,it is essential to gain insights into the distribution of pollutants,their environmental and health impacts,and their sources in this region.In this study,we constructed a Land Use Regression（LUR）model based on ground monitoring stations,remote sensing satellites and land use data,and combined it with a Bayesian Maximum Entropy（BME）model to predict the spatial distribution of major pollutants(NO₂,PM_2.5)in the Yellow River Basin.Additionally,we used spatial autocorrelation to identify clusters and correlations among neighboring image elements.Integrating the spatial distribution of population density data,we mapped the relative risk of population exposure in the Yellow River Basin.Furthermore,we analyzed the transport pathways and potential sources of major pollutants in cities with a high relative risk of population exposure.The key findings of our study are as follows:（1）Analyzing the changes in NO₂ and PM_2.5 concentrations,we observed similar trends at ground monitoring stations,characterized by a“U”shape.In the Yellow River Basin as a whole,NO₂ pollution was relatively light,while PM_2.5 pollution was more severe.The annual average concentrations were 38.7μg/m³ for NO₂ and 53.1μg/m³ for PM_2.5 Regarding pollutant correlations,the highest coefficients were observed between NO₂ and PM_2.5,as well as between NO₂ and PM₁₀,indicating a significant linear relationship.Regarding meteorological factors,NO₂ showed a positive correlation with the annual mean air pressure and annual mean temperature,while it exhibited a negative correlation with the V-wind component（horizontal velocity of air moving north）.On the other hand,PM_2.5 demonstrated positive correlations with the annual mean air pressure,annual mean temperature,and annual mean precipitation.Additionally,it displayed a linear correlation with the U-wind component（horizontal velocity of air moving east）.The linear correlations between PM_2.5 and the annual mean pressure,annual mean temperature,and annual mean precipitation were positive,while the correlation with the U-wind component was negative.（2）Spatial distribution analysis of NO₂ and PM_2.5 concentrations shows that the LUR/BME model has better prediction accuracy and is more precise compared to the LUR model.The ten-fold cross-validation R-squared(R_cv²)and Root Mean Square Error（RMSE）values for NO₂ and PM_2.5 are 0.84 and 12.94μg/m³,and 0.88 and 8.39μg/m³,respectively.From an overall perspective of the Yellow River Basin,NO₂ and PM_2.5concentrations are higher in the eastern region than in the western region,and pollution is more severe in the downstream region than in the middle and upstream regions,with PM_2.5 being the most severe pollutant.From the perspective of each urban agglomeration,the most severely polluted area is the Jinan urban agglomeration,followed by the Zhengzhou urban agglomeration.NO₂ and PM_2.5 spatial clustering mainly occur in urban areas,and the spatial clustering range of NO₂ is wider than that of PM_2.5 in rural areas.（3）Evaluation of the relative risk of NO₂ and PM_2.5 population exposure.From the perspective of the Yellow River basin as a whole,the relative risk of NO₂ population exposure is low,while the relative risk of PM_2.5 population exposure is high;from the perspective of urban agglomerations,as the Yellow River moves from west to east,the proportion of population exposure in higher risk areas increases,and the population is concentrated in the spatial characteristics of higher PM_2.5 concentrations,with the highest risk of PM_2.5 population exposure in the Zhengzhou metropolitan area.（4）Taking Luoyang as a representative of a heavily polluted city,the city has relatively light NO₂ pollution and serious PM_2.5 pollution,so the PM_2.5 transmission paths and potential source areas are analysed.The distribution of the contribution values of the potential source areas of PM_2.5 pollutants has obvious seasonal characteristics,and its potential source areas can be divided into Luoyang city itself,cities around Luoyang city in the province,and cities outside the province such as Yan’an city in Shaanxi province and Jining city in Shandong province as important source areas.