Development and Back-Extrapolation of NO2 Land Use Regression Models for Historic Exposure Assessment in Great Britain

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• 作者：John Gulliver ; Kees de Hoogh ; Anna Hansell ; Danielle Vienneau
• 刊名：Environmental Science & Technology (ES&T)
• 出版年：2013
• 出版时间：July 16, 2013
• 年：2013
• 卷：47
• 期：14
• 页码：7804-7811
• 全文大小：275K
• 年卷期：v.47,no.14(July 16, 2013)
• ISSN：1520-5851

文摘

Modeling historic air pollution exposures is often restricted by availability of monitored concentration data. We evaluated back-extrapolation of land use regression (LUR) models for annual mean NO₂ concentrations in Great Britain for up to 18 years earlier. LUR variables were created in a geographic information system (GIS) using land cover and road network data summarized within buffers, site coordinates, and altitude. Four models were developed for 2009 and 2001 using 75% of monitoring sites (in different groupings) and evaluated on the remaining 25%. Variables selected were generally stable between models. Within year, hold-out validation yielded mean-squared-error-based R² (MSE-R²) (i.e., fit around the 1:1 line) values of 0.25鈥?.63 and 0.51鈥?.65 for 2001 and 2009, respectively. Back-extrapolation was conducted for 2009 and 2001 models to 1991 and for 2009 models to 2001, adjusting to the year using two background NO₂ monitoring sites. Evaluation of back-extrapolated predictions used 100% of sites from an historic national NO₂ diffusion tube network (n = 451) for 1991 and 70 independent sites from automatic monitoring in 2001. Values of MSE-R² for back-extrapolation to 1991 were 0.42鈥?.45 and 0.52鈥?.55 for 2001 and 2009 models, respectively, but model performance varied by region. Back-extrapolation of LUR models appears valid for exposure assessment for NO₂ back to 1991 for Great Britain.