Examination of the Correlation between Beijing's Population and Air Quality Index through the Lens of Spatial Interpolation
As urbanization accelerates globally,air pollution has emerged as a prominent public health concern,particularly in highly urbanized areas such as Beijing.Given the significant disparities in population density and socio-economic factors in Beijing,conventional Air Quality Indexes(AQI)struggle to accurately reflect the actual impact of air pollution on its residents.This study delves into an in-depth spatial interpolation analysis of Beijing's population and AQI,examining three methods:Ordinary Kriging,Simple Kriging,and Inverse Distance Weighted(IDW)interpolation.The results reveal that Ordinary Kriging interpolation exhibits notable advantages in key statistical indicators,such as mean error and root mean square error.However,in assessing the correlation of spatial data,Simple Kriging interpolation demonstrates the strongest positive relationship between Beijing's population and AQI data.A comprehensive analysis indicates that while Ordinary Kriging interpolation excels in data accuracy and stability,Simple Kriging interpolation surpasses in the assessment of rank correlation.This nuanced examination contributes a refined understanding to the methodologies employed in air quality assessment,underscoring the complexity and variability inherent in urban environmental studies.
geostatisticsspatial interpolationatmospheric quality indexpopulation density
国家科技期刊平台
NSTL
万方数据
