Global Land Use Regression Model for Nitrogen Dioxide Air Pollution

全球土地利用回归模型与二氧化氮空气污染的关系

阅读:1

Abstract

Nitrogen dioxide is a common air pollutant with growing evidence of health impacts independent of other common pollutants such as ozone and particulate matter. However, the worldwide distribution of NO(2) exposure and associated impacts on health is still largely uncertain. To advance global exposure estimates we created a global nitrogen dioxide (NO(2)) land use regression model for 2011 using annual measurements from 5,220 air monitors in 58 countries. The model captured 54% of global NO(2) variation, with a mean absolute error of 3.7 ppb. Regional performance varied from R(2) = 0.42 (Africa) to 0.67 (South America). Repeated 10% cross-validation using bootstrap sampling (n = 10,000) demonstrated a robust performance with respect to air monitor sampling in North America, Europe, and Asia (adjusted R(2) within 2%) but not for Africa and Oceania (adjusted R(2) within 11%) where NO(2) monitoring data are sparse. The final model included 10 variables that captured both between and within-city spatial gradients in NO(2) concentrations. Variable contributions differed between continental regions, but major roads within 100 m and satellite-derived NO(2) were consistently the strongest predictors. The resulting model can be used for global risk assessments and health studies, particularly in countries without existing NO(2) monitoring data or models.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。