Empirical models aim to predict spatial variability in concentrations of outdoor air pollution. For year-2010 concentrations of PM~2.5~ in the US, we intercompared six national-scale empirical models, each generated by a different research group. Despite differences in methods and independent variables for the models, we find a relatively high degree of agreement among model predictions (e.g., correlations of 0.84 to 0.92, RMSD (root-mean-square-difference; units: μg/m^3^) of 0.8 to 1.4, or on average \~12% of the average concentration; many best-fit lines are near the 1:1 line)
Although fine particulate matter with a diameter of <2.5 μm (PM2.5) has a greater negative impact...
Urbanization and industrialization have spurred air pollution, making it a global problem. An unders...
The short-term and acute health effects of fine particulate matter less than 2.5 μm (PM<sub>2.5</sub...
National-scale empirical models for air pollution can include hundreds of geographic variables. The ...
Epidemiologic studies have found associations between fine particulate matter (PM2.5) exposure and a...
Although PM2.5 (particulate matter with aerodynamic diameters less than 2.5 μm) in the air originate...
BACKGROUND: National- or regional-scale prediction models that estimate individual-level air polluti...
There is concern regarding the heterogeneity of exposure to airborne particulate matter (PM) across ...
National-scale empirical models of air pollution (e.g., Land Use Regression) rely on predictor varia...
Ten state-of-the-science regional air quality (AQ) modeling systems have been applied to continental...
Abstract Traditional statistical methods (TSM) and machine learning (ML) methods have been widely us...
BACKGROUND: Epidemiologic studies of air pollution have demonstrated a link between long-term air po...
PDFTech ReportDOT TSC-OST-76-58Air pollutionAlternatives analysisAnalysisCluster analysisMathematica...
We present a simple approach to estimating ground-level fine particulate matter (PM2.5, particles sm...
A statistical modelling of PM10 concentration (2006–2015) is applied to understand the behaviour, t...
Although fine particulate matter with a diameter of <2.5 μm (PM2.5) has a greater negative impact...
Urbanization and industrialization have spurred air pollution, making it a global problem. An unders...
The short-term and acute health effects of fine particulate matter less than 2.5 μm (PM<sub>2.5</sub...
National-scale empirical models for air pollution can include hundreds of geographic variables. The ...
Epidemiologic studies have found associations between fine particulate matter (PM2.5) exposure and a...
Although PM2.5 (particulate matter with aerodynamic diameters less than 2.5 μm) in the air originate...
BACKGROUND: National- or regional-scale prediction models that estimate individual-level air polluti...
There is concern regarding the heterogeneity of exposure to airborne particulate matter (PM) across ...
National-scale empirical models of air pollution (e.g., Land Use Regression) rely on predictor varia...
Ten state-of-the-science regional air quality (AQ) modeling systems have been applied to continental...
Abstract Traditional statistical methods (TSM) and machine learning (ML) methods have been widely us...
BACKGROUND: Epidemiologic studies of air pollution have demonstrated a link between long-term air po...
PDFTech ReportDOT TSC-OST-76-58Air pollutionAlternatives analysisAnalysisCluster analysisMathematica...
We present a simple approach to estimating ground-level fine particulate matter (PM2.5, particles sm...
A statistical modelling of PM10 concentration (2006–2015) is applied to understand the behaviour, t...
Although fine particulate matter with a diameter of <2.5 μm (PM2.5) has a greater negative impact...
Urbanization and industrialization have spurred air pollution, making it a global problem. An unders...
The short-term and acute health effects of fine particulate matter less than 2.5 μm (PM<sub>2.5</sub...