Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe – The ESCAPE project

Beelen, Rob; Hoek, Gerard; Vienneau, Danielle; Eeftens, Marloes; Dimakopoulou, Konstantina; Pedeli, Xanthi; Tsai, Ming-Yi; Künzli, Nino; Schikowski, Tamara; Marcon, Alessandro; Eriksen, Kirsten Thorup; Raaschou-Nielsen, Ole; Stephanou, Euripides G.; Patelarou, Evridiki; Lanki, Timo; Yli‐Tuomi, Tarja; Declercq, Christophe; Falq, Grégoire; Stempfelet, Morgane; Birk, Matthias; Cyrys, Josef; Klot, Stephanie von; Nádor, Gizella; Varró, Mihály János; Dėdelė, Audrius; Gražulevičienė, Regina; Mölter, Anna; Lindley, Sarah; Madsen, Christian; Cesaroni, Giulia; Ranzi, Andrea; Badaloní, Chiara; Hoffmann, Barbara; Nonnemacher, Michael; Krämer, Ursula; Kuhlbusch, Thomas A. J.; Cirach, Marta; Nazelle, Audrey de; Nieuwenhuijsen, Mark; Bellander, Tom; Korek, Michal; Olsson, David; Strömgren, Magnus; Dons, Evi; Jerrett, Michael; Fischer, Paul; Wang, Meng; Brunekreef, Bert; Hoogh, Kees de

doi:10.1016/j.atmosenv.2013.02.037

Cited by 812 publications

(711 citation statements)

References 34 publications

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“…37,38 Furthermore, in the EU methodological consistency of monitoring is greater for NO 2 (chemiluminescence) than PM 10 (multiple methods). Recent spatiotemporal LURs for the USA reported an R 2 of 0.78 for NO 2 17 and 0.63 for PM 2.5 .…”

Section: Discussionmentioning

confidence: 99%

Western European Land Use Regression Incorporating Satellite- and Ground-Based Measurements of NO₂ and PM₁₀

Vienneau

Hoogh

Bechle

et al. 2013

Environ. Sci. Technol.

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Land use regression (LUR) models typically investigate within-urban variability in air pollution. Recent improvements in data quality and availability, including satellite-derived pollutant measurements, support fine-scale LUR modeling for larger areas. Here, we describe NO 2 and PM 10 LUR models for Western Europe (years: 2005−2007) based on >1500 EuroAirnet monitoring sites covering background, industrial, and traffic environments. Predictor variables include land use characteristics, population density, and length of major and minor roads in zones from 0.1 km to 10 km, altitude, and distance to sea. We explore models with and without satellite-based NO 2 and PM 2.5 as predictor variables, and we compare two available land cover data sets (global; European). Model performance (adjusted R 2 ) is 0.48−0.58 for NO 2 and 0.22−0.50 for PM 10 . Inclusion of satellite data improved model performance (adjusted R 2 ) by, on average, 0.05 for NO 2 and 0.11 for PM 10 . Models were applied on a 100 m grid across Western Europe; to support future research, these data sets are publicly available.

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Section: Discussionmentioning

confidence: 99%

Western European Land Use Regression Incorporating Satellite- and Ground-Based Measurements of NO₂ and PM₁₀

Vienneau

Hoogh

Bechle

et al. 2013

Environ. Sci. Technol.

Self Cite

175

144

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“…To avoid the exaggerated influence of a high NO2 point in the models validation process, the predictor variables were truncated. All the details of the development of the models are described in a previous publication (Beelen et al 2013) and more general information on LUR can be found in Hoek et al 2008. Cyrys et al, Atmospheric Environment, 2012(Cyrys et al 2012 …”

Section: No2 Exposure Assessmentmentioning

confidence: 99%

Socioeconomic position and outdoor nitrogen dioxide (NO2) exposure in Western Europe: A multi-city analysis

Temam

Burte

Adam

et al. 2017

Environment International

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“…Based on the Mauritanian road network classification system, two main road types were determined: local paved roads and local feeder roads. Road variables by type were calculated as total road length within 50, 100, 150 and 200 m buffers; the Euclidian distance between measurement sites and roads by type were also computed (Briggs et al, 2000;Beelen et al, 2013;Abernethy et al, 2013).…”

Section: Geographic Information System Analysismentioning

confidence: 99%

“…LUR modelling has thus far been employed in a variety of European and North American cities (Hoek et al, 2008;Ross et al, 2005;Beelen et al, 2013). To our knowledge, with the exception of a few studies in some Asian LMICs Allen et al, 2013;Saraswat et al, 2013), this approach has not been applied in an African region.…”

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confidence: 99%

Spatial air pollution modelling for a West-African town

Gebreab¹,

Vienneau²,

Feigenwinter³

et al. 2015

Geospat Health

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Land use regression (LUR) modelling is a common approach used in European and Northern American epidemiological studies to assess urban and traffic related air pollution exposures. Studies applying LUR in Africa are lacking. A need exists to understand if this approach holds for an African setting, where urban features, pollutant exposures and data availability differ considerably from other continents. We developed a parsimonious regression model based on 48-hour nitrogen dioxide (NO2) concentrations measured at 40 sites in Kaédi, a medium sized West-African town, and variables generated in a geographic information system (GIS). Road variables and settlement land use characteristics were found to be important predictors of 48-hour NO2 concentration in the model. About 68% of concentration variability in the town was explained by the model. The model was internally validated by leave-one-out cross-validation and it was found to perform moderately well. Furthermore, its parameters were robust to sampling variation. We applied the model at 100 m pixels to create a map describing the broad spatial pattern of NO2 across Kaédi. In this research, we demonstrated the potential for LUR as a valid, cost-effective approach for air pollution modelling and mapping in an African town. If the methodology were to be adopted by environmental and public health authorities in these regions, it could provide a quick assessment of the local air pollution burden and potentially support air pollution policies and guidelines.

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Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe – The ESCAPE project

Abstract: h i g h l i g h t s < LUR models were developed in 36 study areas in Europe using a standardized approach. < NO 2 models explained a large fraction of concentration variability (median R 2 82%). < Local traffic intensity data were important predictors for LUR model development.

Cited by 812 publications

References 34 publications

Western European Land Use Regression Incorporating Satellite- and Ground-Based Measurements of NO₂ and PM₁₀

Western European Land Use Regression Incorporating Satellite- and Ground-Based Measurements of NO₂ and PM₁₀

Socioeconomic position and outdoor nitrogen dioxide (NO2) exposure in Western Europe: A multi-city analysis

Spatial air pollution modelling for a West-African town

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Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe – The ESCAPE project

Abstract: h i g h l i g h t s < LUR models were developed in 36 study areas in Europe using a standardized approach. < NO 2 models explained a large fraction of concentration variability (median R 2 82%). < Local traffic intensity data were important predictors for LUR model development.

Cited by 812 publications

References 34 publications

Western European Land Use Regression Incorporating Satellite- and Ground-Based Measurements of NO2 and PM10

Western European Land Use Regression Incorporating Satellite- and Ground-Based Measurements of NO2 and PM10

Socioeconomic position and outdoor nitrogen dioxide (NO2) exposure in Western Europe: A multi-city analysis

Spatial air pollution modelling for a West-African town

Contact Info

Product

Resources

About

Western European Land Use Regression Incorporating Satellite- and Ground-Based Measurements of NO₂ and PM₁₀

Western European Land Use Regression Incorporating Satellite- and Ground-Based Measurements of NO₂ and PM₁₀