Modelled estimates of particulate matter air pollution

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 Data Integration Model for Air Quality (DIMAQ) – developed by the University of Exeter – has produced estimates based on data from ground measurements (see the Database on air quality)  together with information from other sources including data from satellite retrievals of aerosol optical depth and chemical transport models. It provides estimates of annual concentrations to PM_2.5 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 9690 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. Within DIMAQ, data from these sources are calibrated with ground measurements. The model provides estimates of air quality, expressed in terms of median concentrations of PM_2.5, for all regions of the world, including areas in which PM_2.5 monitoring is not available

Detailed methods for Data Integration Model for Air Quality: A Hierarchical Approach to the Global Estimation of Exposures to Ambient Air Pollution

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.

• DIMAQ database, 2014 data xlxs, 51.33Mb

Contains the following rows: longitude, latitude, country code, PM_2.5 (annual average PM_2.5 in μg/m₃, for 2014)

• Meta-data file for DIMAQ 2014 xlsx, 156kb

Data Integration Model for Air Quality: A Hierarchical Approach to the Global Estimation of Exposures to Ambient Air Pollution