Global, high-resolution, reduced-complexity air quality modeling for PM2.5 using InMAP (Intervention Model for Air Pollution).

ABSTRACT: Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce these deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many scenarios at high spatial resolution. However, air quality modeling typically has substantial requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain

SUBMITTER: Thakrar SK 

PROVIDER: S-EPMC9132322 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature