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Europe-wide air pollution modeling from 2000 to 2019 using geographically weighted regression

Shen, Y. and de Hoogh, K. and Schmitz, O. and Clinton, N. and Tuxen-Bettman, K. and Brandt, J. and Christensen, J. H. and Frohn, L. M. and Geels, C. and Karssenberg, D. and Vermeulen, R. and Hoek, G.. (2022) Europe-wide air pollution modeling from 2000 to 2019 using geographically weighted regression. Environment international, 168. p. 107485.

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Abstract

Previous European land-use regression (LUR) models assumed fixed linear relationships between air pollution concentrations and predictors such as traffic and land use. We evaluated whether including spatially-varying relationships could improve European LUR models by using geographically weighted regression (GWR) and random forest (RF). We built separate LUR models for each year from 2000 to 2019 for NO2, O3, PM2.5 and PM10 using annual average monitoring observations across Europe. Potential predictors included satellite retrievals, chemical transport model estimates and land-use variables. Supervised linear regression (SLR) was used to select predictors, and then GWR estimated the potentially spatially-varying coefficients. We developed multi-year models using geographically and temporally weighted regression (GTWR). Five-fold cross-validation per year showed that GWR and GTWR explained similar spatial variations in annual average concentrations (average R(2) = NO2: 0.66; O3: 0.58; PM10: 0.62; PM2.5: 0.77), which are better than SLR (average R(2) = NO2: 0.61; O3: 0.46; PM10: 0.51; PM2.5: 0.75) and RF (average R(2) = NO2: 0.64; O3: 0.53; PM10: 0.56; PM2.5: 0.67). The GTWR predictions and a previously-used method of back-extrapolating 2010 model predictions using CTM were overall highly correlated (R(2) > 0.8) for all pollutants. Including spatially-varying relationships using GWR modestly improved European air pollution annual LUR models, allowing time-varying exposure-health risk models.
Faculties and Departments:09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH)
09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Department of Epidemiology and Public Health (EPH) > Environmental Exposures and Health Systems Research > Physical Hazards and Health (Röösli)
UniBasel Contributors:de Hoogh, Kees
Item Type:Article, refereed
Article Subtype:Research Article
ISSN:0160-4120
Note:Publication type according to Uni Basel Research Database: Journal article
Language:English
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Last Modified:27 Dec 2022 21:55
Deposited On:27 Dec 2022 21:55

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