scholarly journals Intercity transferability of land use regression models for estimating ambient concentrations of nitrogen dioxide

2008 ◽  
Vol 19 (1) ◽  
pp. 107-117 ◽  
Author(s):  
Karla Poplawski ◽  
Timothy Gould ◽  
Eleanor Setton ◽  
Ryan Allen ◽  
Jason Su ◽  
...  
Keyword(s):  
Land Use ◽  
Nitrogen Dioxide ◽  
Regression Models ◽  
Land Use Regression ◽  
Ambient Concentrations

scholarly journals Performance of Multi-City Land Use Regression Models for Nitrogen Dioxide and Fine Particles

2014 ◽  
Vol 122 (8) ◽  
pp. 843-849 ◽  
Author(s):  
Meng Wang ◽  
Rob Beelen ◽  
Tom Bellander ◽  
Matthias Birk ◽  
Giulia Cesaroni ◽  
...  
Keyword(s):  
Land Use ◽  
Nitrogen Dioxide ◽  
Regression Models ◽  
Fine Particles ◽  
Land Use Regression

scholarly journals Evaluation of Land Use Regression Models for Nitrogen Dioxide and Benzene in Four US Cities

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Shaibal Mukerjee ◽  
Luther Smith ◽  
Lucas Neas ◽  
Gary Norris
Keyword(s):  
Land Use ◽  
Nitrogen Dioxide ◽  
Regression Models ◽  
El Paso ◽  
Passive Samplers ◽  
Data Availability ◽  
Border Crossings ◽  
Monitoring Networks ◽  
Land Use Regression ◽  
Pollutant Concentrations

Spatial analysis studies have included the application of land use regression models (LURs) for health and air quality assessments. Recent LUR studies have collected nitrogen dioxide (NO2) and volatile organic compounds (VOCs) using passive samplers at urban air monitoring networks in El Paso and Dallas, TX, Detroit, MI, and Cleveland, OH to assess spatial variability and source influences. LURs were successfully developed to estimate pollutant concentrations throughout the study areas. Comparisons of development and predictive capabilities of LURs from these four cities are presented to address this issue of uniform application of LURs across study areas. Traffic and other urban variables were important predictors in the LURs although city-specific influences (such as border crossings) were also important. In addition, transferability of variables or LURs from one city to another may be problematic due to intercity differences and data availability or comparability. Thus, developing common predictors in future LURs may be difficult.

Long-term nitrogen dioxide exposure assessment using back-extrapolation of satellite-based land-use regression models for Australia

2018 ◽  
Vol 163 ◽  
pp. 16-25 ◽  
Author(s):  
Luke D. Knibbs ◽  
Craig.P. Coorey ◽  
Matthew J. Bechle ◽  
Julian D. Marshall ◽  
Michael G. Hewson ◽  
...  
Keyword(s):  
Land Use ◽  
Nitrogen Dioxide ◽  
Exposure Assessment ◽  
Regression Models ◽  
Land Use Regression

scholarly journals A Land Use Regression Model for Predicting Ambient Concentrations of Nitrogen Dioxide in Hamilton, Ontario, Canada

2006 ◽  
Vol 56 (8) ◽  
pp. 1059-1069 ◽  
Author(s):  
Talar Sahsuvaroglu ◽  
Altaf Arain ◽  
Pavlos Kanaroglou ◽  
Norm Finkelstein ◽  
Bruce Newbold ◽  
...  
Keyword(s):  
Land Use ◽  
Nitrogen Dioxide ◽  
Regression Model ◽  
Land Use Regression ◽  
Ambient Concentrations

Development of nitrogen dioxide and volatile organic compounds land use regression models to estimate air pollution exposure near an Italian airport

2016 ◽  
Vol 131 ◽  
pp. 254-262 ◽  
Author(s):  
Alessandra Gaeta ◽  
Giorgio Cattani ◽  
Alessandro Di Menno di Bucchianico ◽  
Antonella De Santis ◽  
Giulia Cesaroni ◽  
...  
Keyword(s):  
Land Use ◽  
Air Pollution ◽  
Volatile Organic Compounds ◽  
Nitrogen Dioxide ◽  
Organic Compounds ◽  
Regression Models ◽  
Land Use Regression ◽  
Volatile Organic ◽  
Air Pollution Exposure ◽  
Pollution Exposure

scholarly journals Nitrogen dioxide levels estimated from land use regression models several years apart and association with mortality in a large cohort study

2012 ◽  
Vol 11 (1) ◽  
Author(s):  
Giulia Cesaroni ◽  
Daniela Porta ◽  
Chiara Badaloni ◽  
Massimo Stafoggia ◽  
Marloes Eeftens ◽  
...  
Keyword(s):  
Land Use ◽  
Cohort Study ◽  
Nitrogen Dioxide ◽  
Regression Models ◽  
Large Cohort ◽  
Land Use Regression ◽  
Large Cohort Study

scholarly journals Seasonal effects in land use regression models for nitrogen dioxide, coarse particulate matter, and gaseous ammonia in Cleveland, Ohio

2012 ◽  
Vol 3 (3) ◽  
pp. 352-361 ◽  
Author(s):  
Shaibal Mukerjee ◽  
Robert D. Willis ◽  
John T. Walker ◽  
Davyda Hammond ◽  
Gary A. Norris ◽  
...  
Keyword(s):  
Land Use ◽  
Particulate Matter ◽  
Nitrogen Dioxide ◽  
Regression Models ◽  
Seasonal Effects ◽  
Gaseous Ammonia ◽  
Land Use Regression ◽  
Coarse Particulate Matter ◽  
Cleveland Ohio
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