Pearsonsâ correlation coefficients for daily mean pollutant concentrations among monitoring stations in Fukuoka, 2014. Table S2. Pearsonâs correlation coefficients between pollutant concentrations measured at the Yoshizuka monitoring station and those at the nearest monitoring stations to the respective residential postal code regions. (XLSX 20 kb
Figure S1. Scatterplots showing the relationships between air pollution at the front door location (...
Further details of equations (5–7) used to express “pseudo” model data in terms of spatial and tempo...
Table S3. Geometric mean PM2.5 substituting limit of detection concentrations at selected times and ...
Scoring for severity of asthma modified by Eisnerâs method. Table S2: Pearson correlation coeffici...
Table S2. Associations between monitor location and PM2.5 and CO concentrations during 24âh of mon...
Figure S1. Air pollution trends for non-PM10 pollutants, Santiago, Chile, 1997-2017. Table S1. Corre...
Table S1. Association between cumulative air pollution concentrations and risk of preterm birth. (DO...
Table S2. Excess risks (ERs) and 95% confidence intervals of preterm birth per IQR increment in air ...
Table S1. Associations between monitor location and PM2.5 and CO concentrations during biomass cooki...
Additional file 1: Table S1. Summary of Model Fit with Different Numbers of Knots and Degrees. Table...
Table S1. Spearman’s correlation coefficients among aeroallergens, Brussels-Capital Region, 2008–201...
Table S1. Land-use regression models with model performance (leave-one-out cross-validation R2, R2LO...
Figure S1. Mass concentrations of fine (a) and coarse (b) particles in the outdoor air of Kyoto, Jap...
Figure S1. Spatial distribution of the BECO (rural) and AFU (urban) measurement locations in the can...
Table S3. Difference of estimates and 95% confidence intervals (95% CIs) of air pollutants on risk o...
Figure S1. Scatterplots showing the relationships between air pollution at the front door location (...
Further details of equations (5–7) used to express “pseudo” model data in terms of spatial and tempo...
Table S3. Geometric mean PM2.5 substituting limit of detection concentrations at selected times and ...
Scoring for severity of asthma modified by Eisnerâs method. Table S2: Pearson correlation coeffici...
Table S2. Associations between monitor location and PM2.5 and CO concentrations during 24âh of mon...
Figure S1. Air pollution trends for non-PM10 pollutants, Santiago, Chile, 1997-2017. Table S1. Corre...
Table S1. Association between cumulative air pollution concentrations and risk of preterm birth. (DO...
Table S2. Excess risks (ERs) and 95% confidence intervals of preterm birth per IQR increment in air ...
Table S1. Associations between monitor location and PM2.5 and CO concentrations during biomass cooki...
Additional file 1: Table S1. Summary of Model Fit with Different Numbers of Knots and Degrees. Table...
Table S1. Spearman’s correlation coefficients among aeroallergens, Brussels-Capital Region, 2008–201...
Table S1. Land-use regression models with model performance (leave-one-out cross-validation R2, R2LO...
Figure S1. Mass concentrations of fine (a) and coarse (b) particles in the outdoor air of Kyoto, Jap...
Figure S1. Spatial distribution of the BECO (rural) and AFU (urban) measurement locations in the can...
Table S3. Difference of estimates and 95% confidence intervals (95% CIs) of air pollutants on risk o...
Figure S1. Scatterplots showing the relationships between air pollution at the front door location (...
Further details of equations (5–7) used to express “pseudo” model data in terms of spatial and tempo...
Table S3. Geometric mean PM2.5 substituting limit of detection concentrations at selected times and ...