Modelled Global Ambient Air Pollution estimates
Estimation of global health risks from exposure to ambient air pollution requires a comprehensive set of air pollution exposure data covering all inhabited areas. The recently developed Data Integration Model for Air Quality (DIMAQ) has produced estimates based on data from ground measurements together with information from other sources including data from satellite retrievals of aerosol optical depth and chemical transport models. It provides estimates of annual exposures of PM2.5 levels at high spatial resolution (0.1° × 0.1°, which equates to approximately 11x11km at the equator) globally.
The sources of data include: Ground measurements from 6 003 monitoring locations around the world, satellite remote sensing; population estimates; topography; and information on local monitoring networks and measures of specific contributors of air pollution from chemical transport models. The DIMAQ model calibrates data from these sources with ground measurements. This model has provided produced estimates of air quality, expressed in terms of median concentrations of PM2.5, for all regions of the world, including areas in which PM2.5 monitoring is not available.
This model has been developed by an international group of experts, and led by the University of Bath and WHO.
Global ambient air pollution map
DIMAQ database, 2014 data
Detailed methods for DIMAQ
Meta-data file for DIMAQ
Wherever possible, estimates have been computed using standardized categories and methods in order to enhance cross-national comparability. This approach may result in some cases in differences between the estimates presented here and the official national statistics prepared and endorsed by individual WHO Member States. These differences between WHO and national statistics may be larger for countries with small cities and settlements which may not be fully represented by the resolution of the WHO model. This may be compounded for isolated regions where air pollution is primarily from local sources and is experienced at very local levels. It is important to stress that these estimates are also subject to considerable uncertainty, especially for countries with weak statistical information systems.
The boundaries and names shown and the designations used on this map do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted and dashed lines on maps represent approximate border lines for which there may not yet be full agreement. Data source: World Health Organization WHO 2016. All rights reserved.