Land use regression models revealing spatiotemporal co-variation in NO2, NO, and O3 in the Netherlands

[1]  D. Karssenberg,et al.  Activity-based air pollution exposure assessment: Differences between homemakers and cycling commuters. , 2019, Health & place.

[2]  Luc Int Panis,et al.  Annual, seasonal, and morning rush hour Land Use Regression models for black carbon in a school catchment area of Milan, Italy. , 2019, Environmental research.

[3]  B. Brunekreef,et al.  High resolution annual average air pollution concentration maps for the Netherlands , 2019, Scientific data.

[4]  Pamela Ohman-Strickland,et al.  Land use regression models to assess air pollution exposure in Mexico City using finer spatial and temporal input parameters. , 2018, The Science of the total environment.

[5]  Lidia Morawska,et al.  Development of a land use regression model for daily NO2 and NOx concentrations in the Brisbane metropolitan area, Australia , 2017, Environ. Model. Softw..

[6]  L. Modig,et al.  The spatial variation of O3, NO, NO2 and NOx and the relation between them in two Swedish cities , 2017, Environmental Monitoring and Assessment.

[7]  Stefania Bertazzon,et al.  Accounting for spatial effects in land use regression for urban air pollution modeling. , 2015, Spatial and spatio-temporal epidemiology.

[8]  R. Beelen,et al.  Air Pollution and Mortality in Seven Million Adults: The Dutch Environmental Longitudinal Study (DUELS) , 2015, Environmental health perspectives.

[9]  David C. Wheeler,et al.  Selecting Spatial Scale of Covariates in Regression Models of Environmental Exposures , 2015, Cancer informatics.

[10]  Jaakko Kukkonen,et al.  Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies. , 2014, Environment international.

[11]  M. Brauer,et al.  Use of Satellite Observations for Long-Term Exposure Assessment of Global Concentrations of Fine Particulate Matter , 2014, Environmental health perspectives.

[12]  A. Pinjari,et al.  Impacts of travel activity and urbanicity on exposures to ambient oxides of nitrogen and on exposure disparities , 2014, Air Quality, Atmosphere & Health.

[13]  J. Burke,et al.  Air pollution dispersion models for human exposure predictions in London , 2013, Journal of Exposure Science and Environmental Epidemiology.

[14]  Geert Wets,et al.  Modeling temporal and spatial variability of traffic-related air pollution: Hourly land use regression models for black carbon , 2013 .

[15]  Bert Brunekreef,et al.  Development of NO2 and NOx land use regression models for estimating air pollution exposure in 36 study areas in Europe - The ESCAPE project , 2013 .

[16]  A. Peters,et al.  Long-term air pollution exposure and cardio- respiratory mortality: a review , 2013, Environmental Health.

[17]  Bert Brunekreef,et al.  Development of Land Use Regression models for PM(2.5), PM(2.5) absorbance, PM(10) and PM(coarse) in 20 European study areas; results of the ESCAPE project. , 2012, Environmental science & technology.

[18]  S. Klot.  Equivalence of using nested buffers and concentric adjacent rings as predictors in land use regression models , 2011 .

[19]  Yinchang Feng,et al.  Analysis of the Relationship between O3, NO and NO2 in Tianjin, China , 2011 .

[20]  Bert Brunekreef,et al.  Stability of measured and modelled spatial contrasts in NO2 over time , 2011, Occupational and Environmental Medicine.

[21]  Peter Salamon,et al.  A software framework for construction of process-based stochastic spatio-temporal models and data assimilation , 2010, Environ. Model. Softw..

[22]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[23]  Lianne Sheppard,et al.  Approach to estimating participant pollutant exposures in the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air). , 2009, Environmental science & technology.

[24]  J. Gulliver,et al.  A review of land-use regression models to assess spatial variation of outdoor air pollution , 2008 .

[25]  Bert Brunekreef,et al.  Long-Term Effects of Traffic-Related Air Pollution on Mortality in a Dutch Cohort (NLCS-AIR Study) , 2007, Environmental health perspectives.

[26]  Ulrike Groemping,et al.  Relative Importance for Linear Regression in R: The Package relaimpo , 2006 .

[27]  H. Zou,et al.  Regularization and variable selection via the elastic net , 2005 .

[28]  P. Elliott,et al.  A regression-based method for mapping traffic-related air pollution: application and testing in four contrasting urban environments. , 2000, The Science of the total environment.

[29]  M. Kwan,et al.  Individual exposure estimates may be erroneous when spatiotemporal variability of air pollution and human mobility are ignored , 2017, Health & place.

[30]  A. Ranzi,et al.  Combining land use regression models and fixed site monitoring to reconstruct spatiotemporal variability of NO2 concentrations over a wide geographical area. , 2017, The Science of the total environment.

[31]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .