Spatial decomposition analysis of NO2 and PM2.5 air pollution in the United States. (15th November 2020)

• Record Type: Journal Article
• Authors: Wang, Yuzhou; Bechle, Matthew J.; Kim, Sun-Young; Adams, Peter J.; Pandis, Spyros N.; Pope, C. Arden; Robinson, Allen L.; Sheppard, Lianne; Szpiro, Adam A.; Marshall, Julian D.
• Is Part Of: Atmospheric environment. Volume 241(2020)
• Publication Date: 2020-11-15
• Subjects: Spatial decomposition -- Spatial increment -- NO2 -- PM2.5; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2020.117470
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: Length scales for spatial variability of air pollution concentrations depend on the pollutant and the location. In this paper, we develop a readily scalable algorithm based on "spatial-increment", to decompose the air pollution concentration into four spatial components: long-range, mid-range, neighborhood, and near-source. We apply the algorithm to annual-average concentrations of outdoor nitrogen dioxide (NO2 ) and fine particulate matter (PM2.5 ) for all census blocks in the contiguous US. For NO2, "neighborhood" and "mid-range" components dominate both within-city and between-city concentration differences (both components are ~5-fold larger in large urbanized areas than rural areas). For PM2.5, the "long-range" component dominates; this component varies by region (e.g., is three times greater in the Midwest [7 μg/m 3 ] than in the West [2.3 μg/m 3 ]), whereas variation by urban area size is relatively minor. Our study provides the first nation-level fine-scale decomposed pollution surfaces to date; this dataset is publicly available. Results can be used to estimate, at least to a zeroth order, the contribution of sources at different distances from the receptor to the annual average pollution in a location of interest. Graphical abstract: Image 1