3.2.2Active indicatorHousehold Air Pollution
3.1Energy use, energy generation, and health
3.2Air quality and health co-benefits
3.3Food, agriculture, and health co-benefits
3.5Health-care Sector Emissions
Indicator 3.2.2 · Mitigation
Household Air Pollution
The use of dirty fuels and inefficient technologies for household energy exposes people to high concentrations of PM₂.₅ air pollution, including highly toxic black carbon, increasing the risk of disease and premature death. Gendered roles in household energy-related activities mean women and girls are often disproportionately exposed, and bear a greater share of the associated health burden. This indicator tracks exposure to household air pollution from dirty fuels and inefficient technologies and estimates the premature deaths attributable to it.
Headline finding
Between 2016 and 2023, deaths attributable to household air pollution from solid fuel use declined from 2.4 million to 2.0 million globally, largely driven by reductions in High and Medium HDI countries. In contrast, Low HDI countries were the only group to experience an increase, with deaths rising by 6% over the same period.
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Figure 1
Household Air Pollution
Household PM2.5 exposure (µg/m³) and total deaths due to indoor air pollution from the use of solid fuels, including biomass and coal burning, in urban and rural areas from 2016 to 2023, by selected countries, Human Development Index (HDI) groups, and World Health Organization (WHO) regions.
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About this indicator
Description
This indicator uses a Bayesian hierarchical model to estimate exposure to household air pollution by source of emission in 65 of the countries most dependent on dirty fuels and inefficient technologies for cooking and heating. The model accounts for socio-demographic and epidemiological characteristics and estimates attributable mortality through a comparative risk assessment.
Data downloads
Caveats
The indicator captures variations in household PM2.5 exposure by fuel, stove type, and location, linking them to climate and health impacts. 1. Incomplete housing information: Important housing characteristics—such as ventilation rates, kitchen location, kitchen windows, and roofing materials—are not consistently captured in monitored datasets. 2. Limited country-level data: Household air pollution monitoring studies are scarce in several regions, including parts of Europe, restricting the analysis to 65 countries. 3. Small sample sizes: Many studies include only a limited number of households, reducing the representativeness and reliability of country-level estimates. 4. Differences between studies: Studies use different monitoring technologies, measurement periods, data-processing procedures, and analytical methods, creating substantial heterogeneity. 5. Potential double counting of mortality: Overlap between ambient and household PM₂.₅ exposure may lead to double counting when estimating attributable deaths. 6. Uncertain contribution of outdoor pollution: Methods are still needed to accurately estimate how much ambient air pollution contributes to indoor PM₂.₅ concentrations.
Data sources
- Final energy use for each fuel types from IIASA GAINS model
- Fuel Type: IIASA GAINS model via IEA
- Stove Type: IIASA GAINS model via IEA
- Country-based faction of the unsustainably harvested biomass, that is, non-renewable biomass
- Urban – rural population at country level: Global Human Settlement Layer (GHSL)
- % of fuel use -year 2016 – 2023: WHO data.
- % of stove technology – year 2016-2023; IIASA GAINS model.
- Baseline mortality rates: GBD national estimates for males and females.
- Exposure-response functions for attributable premature mortality: MR-BRTs, cause, and age specific, for 6 diseases.