Estimating traffic contribution to particulate matter concentration in urban areas using a multilevel Bayesian meta-regression approach.

ABSTRACT: Quantifying traffic contribution to air pollution in urban settings is required to inform traffic management strategies and environmental policies that aim at improving air quality. Assessments and comparative analyses across multiple urban areas are challenged by the lack of datasets and methods available for global applications. In this study, we quantify the traffic contribution to particulate matter concentration in multiple cities worldwide by synthesising 155 previous studies reported in the World Health Organization (WHO)'s air pollution source apportionment data for PM₁₀ and PM_2.5. We employed a Bayesian multilevel meta-regression that accounts for uncertainties and captures both within- and between-study variations (in estimation methods, study protocols, etc

SUBMITTER: Heydari S 

PROVIDER: S-EPMC7273192 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature