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

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 NO2 and Particulate Matter in 20 European Study Areas: The ESCAPE Project

2013 ◽  
Vol 47 (9) ◽  
pp. 4357-4364 ◽  
Author(s):  
Meng Wang ◽  
Rob Beelen ◽  
Xavier Basagana ◽  
Thomas Becker ◽  
Giulia Cesaroni ◽  
...  
Keyword(s):  
Land Use ◽  
Particulate Matter ◽  
Regression Models ◽  
European Study ◽  
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.

Land use regression models to estimate the annual and seasonal spatial variability of sulfur dioxide and particulate matter in Tehran, Iran

2014 ◽  
Vol 488-489 ◽  
pp. 343-353 ◽  
Author(s):  
Hassan Amini ◽  
Seyed Mahmood Taghavi-Shahri ◽  
Sarah B. Henderson ◽  
Kazem Naddafi ◽  
Ramin Nabizadeh ◽  
...  
Keyword(s):  
Land Use ◽  
Particulate Matter ◽  
Sulfur Dioxide ◽  
Spatial Variability ◽  
Regression Models ◽  
Land Use Regression

Land-Use Regression Models of Particulate Matter in Temuco, Chile Due to Residential Wood Burning

2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Daniel Cortez ◽  
Carola A Blazquez ◽  
Maria Elisa Quinteros ◽  
Siyao Lu ◽  
Francisco Rubilar ◽  
...  
Keyword(s):  
Land Use ◽  
Particulate Matter ◽  
Regression Models ◽  
Land Use Regression ◽  
Wood Burning

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
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