National Spatiotemporal Exposure Surface for NO2: Monthly Scaling of a Satellite-Derived Land-Use Regression, 2000鈥?010

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• 作者：Matthew J. Bechle ; Dylan B. Millet ; Julian D. Marshall
• 刊名：Environmental Science & Technology
• 出版年：2015
• 出版时间：October 20, 2015
• 年：2015
• 卷：49
• 期：20
• 页码：12297-12305
• 全文大小：365K
• ISSN：1520-5851

文摘

Land-use regression (LUR) is widely used for estimating within-urban variability in air pollution. While LUR has recently been extended to national and continental scales, these models are typically for long-term averages. Here we present NO₂ surfaces for the continental United States with excellent spatial resolution (鈭?00 m) and monthly average concentrations for one decade. We investigate multiple potential data sources (e.g., satellite column and surface estimates, high- and standard-resolution satellite data, and a mechanistic model [WRF-Chem]), approaches to model building (e.g., one model for the whole country versus having separate models for urban and rural areas, monthly LURs versus temporal scaling of a spatial LUR), and spatial interpolation methods for temporal scaling factors (e.g., kriging versus inverse distance weighted). Our core approach uses NO₂ measurements from U.S. EPA monitors (2000鈥?010) to build a spatial LUR and to calculate spatially varying temporal scaling factors. The model captures 82% of the spatial and 76% of the temporal variability (population-weighted average) of monthly mean NO₂ concentrations from U.S. EPA monitors with low average bias (21%) and error (2.4 ppb). Model performance in absolute terms is similar near versus far from monitors, and in urban, suburban, and rural locations (mean absolute error 2鈥? ppb); since low-density locations generally experience lower concentrations, model performance in relative terms is better near monitors than far from monitors (mean bias 3% versus 40%) and is better for urban and suburban locations (1鈥?%) than for rural locations (78%, reflecting the relatively clean conditions in many rural areas). During 2000鈥?010, population-weighted mean NO₂ exposure decreased 42% (1.0 ppb [鈭?.2%] per year), from 23.2 ppb (year 2000) to 13.5 ppb (year 2010). We apply our approach to all U.S. Census blocks in the contiguous United States to provide 132 months of publicly available, high-resolution NO₂ concentration estimates.