What you should know about this indicator

How is this data described by its producer?

Population-weighted exposure to ambient PM2.5 pollution is defined as the average level of exposure of a nation's population to concentrations of suspended particles measuring less than 2.5 microns in aerodynamic diameter, which are capable of penetrating deep into the respiratory tract and causing severe health damage. Exposure is calculated by weighting mean annual concentrations of PM2.5 by population in both urban and rural areas.

Aggregation method:

Weighted average

Statistical concept and methodology:

Methodology: Population exposure to ambient PM2.5 air pollution is estimated using an integrated modeling approach developed for the Global Burden of Disease (GBD) study by the Institute for Health Metrics and Evaluation (IHME). Annual mean concentrations of fine particulate matter (PM2.5) are derived by combining satellite-based aerosol optical depth measurements, chemical transport models, and available ground-level air quality monitoring data. These data sources are fused using geophysical–statistical models to generate globally consistent, high-resolution gridded estimates of PM2.5 concentrations, including areas without direct monitoring.

Population exposure is calculated by weighting annual mean PM2.5 concentrations by the spatial distribution of population in both urban and rural areas. National estimates represent the population-weighted average annual concentration of PM2.5 to which a country’s population is exposed. Estimates are produced annually using a consistent methodology to allow comparison across countries and over time. Values represent modeled exposure levels and are intended for comparative risk assessment rather than regulatory compliance monitoring. Statistical concept(s): Fine particulate matter (PM2.5) refers to airborne particles with an aerodynamic diameter of 2.5 micrometers or less, which are small enough to penetrate deeply into the human respiratory system. Exposure to PM2.5 is associated with adverse health outcomes, including cardiovascular and respiratory diseases and premature mortality.

Development relevance:

Air pollution places a major burden on world health. In many places, including cities but also in rural areas, exposure to air pollution is the main environmental threat to health, responsible for 6.5 million deaths per year, about one every 5 seconds. Around 40 percent of the world’s people rely on household burning of wood, charcoal, dung, crop waste, or coal to meet basic energy needs. Cooking and heating with solid fuels create harmful smoke and particles that fill homes and the surrounding environment. Household air pollution from cooking and heating with solid fuels is responsible for 2.9 million deaths a year. Long-term exposure to high levels of fine particles in the air contributes to a range of health effects, including respiratory diseases, lung cancer, and heart disease, resulting in 4.2 million deaths annually. Not only does exposure to air pollution affect the health of the world’s people, it also carries huge economic costs and represents a drag on development, particularly for low and middle income countries and vulnerable segments of the population such as children and the elderly.

Limitations and exceptions:

Pollutant concentrations are sensitive to local conditions, and even monitoring sites in the same city may register different levels. Direct monitoring of PM2.5 is still rare in most parts of the world, and measurement protocols and standards are not the same for all countries. These data should be considered only a general indication of air quality, intended to inform cross-country comparisons of the health risks due to particulate matter pollution. The guideline set by the World Health Organization (WHO) for PM2.5 is that annual mean concentrations should not exceed 10 micrograms per cubic meter, representing the lower range over which adverse health effects have been observed. The WHO has also recommended guideline values for emissions of PM2.5 from burning fuels in households.

Source
Global Burden of Disease Study 2023, Institute for Health Metrics and Evaluation (IHME), via World Bank (2026)processed by Our World in Data
Last updated
July 14, 2026
Next expected update
January 2027
Date range
1990–2023
Unit
micrograms per cubic meter

Sources and processing

Global Burden of Disease Study 2023, Institute for Health Metrics and Evaluation (IHME), via World Bank – World Development Indicators

The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades. WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability. The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization. WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally. Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.

Retrieved on
July 14, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Global Burden of Disease Study 2023 (GBD 2023) Air Pollution Exposure Estimates and Risk Curves 1990-2023, GBD Collaborator Network, uri: https://ghdx.healthdata.org/record/ihme-data/gbd-2023-air-pollution-exposure-estimates-1990-2023, note: Need to create account to retrieve data., publisher: Institute for Health Metrics and Evaluation (IHME), date accessed: 2026-04-03, date published: 2026-01-23. Indicator EN.ATM.PM25.MC.M3 (https://data.worldbank.org/indicator/EN.ATM.PM25.MC.M3). World Development Indicators - World Bank (2026). Accessed on 2026-07-14.

The World Development Indicators (WDI) database, published by the World Bank, is a comprehensive collection of global development data, providing key economic, social, and environmental statistics. It includes over 1,500 indicators covering more than 200 countries and territories, with data spanning several decades. WDI serves as a vital resource for policymakers, researchers, businesses, and analysts seeking to understand global trends and make data-driven decisions. The database covers a wide range of topics, including economic growth, education, health, poverty, trade, energy, infrastructure, governance, and environmental sustainability. The indicators are sourced from reputable national and international agencies, ensuring high-quality, consistent, and comparable data. Users can access the database through interactive online tools, API services, and downloadable datasets, facilitating detailed analysis and visualization. WDI is also used for tracking progress on the Sustainable Development Goals (SDGs) and other global development initiatives. By providing accessible and reliable statistics, it helps to inform policy discussions and strategies globally. Whether for academic research, policy planning, or economic analysis, the World Development Indicators database is an essential tool for understanding and addressing global development challenges.

Retrieved on
July 14, 2026
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Global Burden of Disease Study 2023 (GBD 2023) Air Pollution Exposure Estimates and Risk Curves 1990-2023, GBD Collaborator Network, uri: https://ghdx.healthdata.org/record/ihme-data/gbd-2023-air-pollution-exposure-estimates-1990-2023, note: Need to create account to retrieve data., publisher: Institute for Health Metrics and Evaluation (IHME), date accessed: 2026-04-03, date published: 2026-01-23. Indicator EN.ATM.PM25.MC.M3 (https://data.worldbank.org/indicator/EN.ATM.PM25.MC.M3). World Development Indicators - World Bank (2026). Accessed on 2026-07-14.

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

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To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Average annual exposure to PM2.5 air pollution”. Our World in Data (2026). Data adapted from Global Burden of Disease Study 2023, Institute for Health Metrics and Evaluation (IHME), via World Bank. Retrieved from https://archive.ourworldindata.org/20260717-115345/grapher/average-exposure-pm25-pollution.html [online resource] (archived on July 17, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Global Burden of Disease Study 2023, Institute for Health Metrics and Evaluation (IHME), via World Bank (2026) – processed by Our World in Data

Full citation

Global Burden of Disease Study 2023, Institute for Health Metrics and Evaluation (IHME), via World Bank (2026) – processed by Our World in Data. “Average annual exposure to PM2.5 air pollution” [dataset]. Global Burden of Disease Study 2023, Institute for Health Metrics and Evaluation (IHME), via World Bank, “World Development Indicators 129” [original data]. Retrieved July 18, 2026 from https://archive.ourworldindata.org/20260717-115345/grapher/average-exposure-pm25-pollution.html (archived on July 17, 2026).

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Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/average-exposure-pm25-pollution.csv?v=1&csvType=full&useColumnShortNames=false")
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import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/average-exposure-pm25-pollution.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/average-exposure-pm25-pollution.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/average-exposure-pm25-pollution.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/average-exposure-pm25-pollution.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/average-exposure-pm25-pollution.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear