A review of land-use regression models for characterizing intraurban air pollution exposure.
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The primary conclusion of this study is that LUR models are an important tool for integrating traffic and geographic information to characterize variability in exposures.Abstract:
Epidemiologic studies of air pollution require accurate exposure assessments at unmonitored locations in order to minimize exposure misclassification. One approach gaining considerable interest is the land-use regression (LUR) model. Generally, the LUR model has been utilized to characterize air pollution exposure and health effects for individuals residing within urban areas. The objective of this article is to briefly summarize the history and application of LUR models to date outlining similarities and differences of the variables included in the model, model development, and model validation. There were 6 studies available for a total of 12 LUR models. Our findings indicated that among these studies, the four primary classes of variables used were road type, traffic count, elevation, and land cover. Of these four, traffic count was generally the most important. The model R2 explaining the variability in the exposure estimates for these LUR models ranged from .54 to .81. The number of air sampling sites generating the exposure estimates, however, was not correlated with the model R2 suggesting that the locations of the sampling sites may be of greater importance than the total number of sites. The primary conclusion of this study is that LUR models are an important tool for integrating traffic and geographic information to characterize variability in exposures.read more
Citations
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Journal ArticleDOI
A review of land-use regression models to assess spatial variation of outdoor air pollution
Gerard Hoek,Rob Beelen,Kees de Hoogh,Danielle Vienneau,John S. Gulliver,Paul Fischer,David J. Briggs +6 more
TL;DR: Land-use regression (LUR) models have been increasingly used in the past few years to assess the health effects of long-term average exposure to outdoor air pollution as mentioned in this paper.
Journal ArticleDOI
Development of Land Use Regression Models for PM2.5, PM2.5 Absorbance, PM10 and PMcoarse in 20 European Study Areas; Results of the ESCAPE Project
Marloes Eeftens,Rob Beelen,Kees de Hoogh,Tom Bellander,Giulia Cesaroni,Marta Cirach,Christophe Declercq,Audrius Dėdelė,Evi Dons,Evi Dons,Audrey de Nazelle,Konstantina Dimakopoulou,Kirsten Thorup Eriksen,Grégoire Falq,Paul Fischer,C Galassi,Regina Gražulevičienė,Joachim Heinrich,Barbara Hoffmann,Michael Jerrett,Dirk Keidel,Dirk Keidel,Michal Korek,Timo Lanki,Sarah Lindley,Christian Madsen,Anna Mölter,Gizella Nádor,Mark J. Nieuwenhuijsen,Michael R. Nonnemacher,Xanthi Pedeli,Ole Raaschou-Nielsen,Evridiki Patelarou,Ulrich Quass,Andrea Ranzi,Christian Schindler,Christian Schindler,Morgane Stempfelet,Euripides G. Stephanou,Dorothea Sugiri,Ming-Yi Tsai,Ming-Yi Tsai,Ming-Yi Tsai,Tarja Yli-Tuomi,Mihály J. Varró,Danielle Vienneau,Stephanie von Klot,Kathrin Wolf,Bert Brunekreef,Gerard Hoek +49 more
TL;DR: Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models, which are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.
Journal ArticleDOI
Exposure assessment models for elemental components of particulate matter in an urban environment: A comparison of regression and random forest approaches.
Cole Brokamp,Roman Jandarov,Marepalli B. Rao,Grace K. LeMasters,Grace K. LeMasters,Patrick H. Ryan,Patrick H. Ryan +6 more
TL;DR: A novel land use random forest (LURF) model is developed and its accuracy and precision is compared to a LUR model for elemental components of PM in the urban city of Cincinnati, Ohio to provide more accurate exposure assessment.
Journal ArticleDOI
Land Use Regression Models of On-Road Particulate Air Pollution (Particle Number, Black Carbon, PM2.5, Particle Size) Using Mobile Monitoring.
Steve Hankey,Julian D. Marshall +1 more
TL;DR: The findings suggest that LUR modeling from mobile measurements is possible, but that more work could usefully inform best practices.
Journal ArticleDOI
Effect of the number of measurement sites on land use regression models in estimating local air pollution
Xavier Basagaña,Marcela Rivera,Inmaculada Aguilera,David Agis,Laura Bouso,Roberto Elosua,Maria Foraster,Audrey de Nazelle,Mark J. Nieuwenhuijsen,Joan Vila,Nino Künzli,Nino Künzli,Nino Künzli +12 more
TL;DR: In this paper, the effect of the number of potential predictors and the variable selection algorithm used, and the consequences of the use of LUR predictions in regression models for a health outcome were investigated.
References
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Journal ArticleDOI
A review and evaluation of intraurban air pollution exposure models
Michael Jerrett,Altaf Arain,Pavlos S. Kanaroglou,Bernardo Beckerman,Dimitri Potoglou,Talar Sahsuvaroglu,Jason Morrison,Chris Giovis +7 more
TL;DR: In this article, a review of models for assessing intraurban exposure under six classes, including proximity-based assessments, statistical interpolation, land use regression models, line dispersion models, integrated emission-meteorological models, and hybrid models combining personal or household exposure monitoring with one of the preceding methods is presented.
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Concentration and Size Distribution of Ultrafine Particles Near a Major Highway
TL;DR: Data showed that both atmospheric dispersion and coagulation contributed to the rapid decrease in particle number concentration and change in particle size distribution with increasing distance from the freeway.
Journal ArticleDOI
Mapping urban air pollution using GIS: a regression-based approach
David J. Briggs,Susan Collins,Paul Elliott,Paul Fischer,Simon Kingham,Erik Lebret,Karel Pryl,Hans Van Reeuwijk,Kirsty Smallbone,Andre Van Der Veen +9 more
TL;DR: A regression-based methodology for mapping traffic-related air pollution was developed within a GIS environment and carried out for NO2 in Amsterda...
Journal ArticleDOI
Estimating long-term average particulate air pollution concentrations: application of traffic indicators and geographic information systems.
Michael Brauer,Gerard Hoek,Patricia van Vliet,Kees Meliefste,Paul Fischer,Ulrike Gehring,Joachim Heinrich,Josef Cyrys,Tom Bellander,Marie Lewné,Bert Brunekreef +10 more
TL;DR: This approach can be used to estimate individual exposures to traffic-related particulate air pollution in communities throughout the Netherlands; in Munich, Germany; and in Stockholm County, Sweden and offers advantages over alternative techniques relying on surrogate variables or traditional approaches that utilize ambient monitoring data alone.
Journal ArticleDOI
A regression-based method for mapping traffic-related air pollution: application and testing in four contrasting urban environments
David J. Briggs,Cornelis de Hoogh,John S. Gulliver,John Wills,Paul Elliott,Simon Kingham,Kirsty Smallbone +6 more
TL;DR: It is concluded that the model might be used as a means of mapping long-term air pollution concentrations either in support of local authority air-quality management strategies, or in epidemiological studies, and offers substantially reduced costs and processing times compared to formal dispersion modelling.
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