PM2.5 pollution, population exposed to levels exceeding WHO Interim Target-1 value (% of total) - Country Ranking

Definition: Percent of population exposed to ambient concentrations of PM2.5 that exceed the World Health Organization (WHO) Interim Target 1 (IT-1) is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 35 micrograms per cubic meter. The Air Quality Guideline (AQG) of 10 micrograms per cubic meter is recommended by the WHO as the lower end of the range of concentrations over which adverse health effects due to PM2.5 exposure have been observed.

Source: Brauer, M. et al. 2017, for the Global Burden of Disease Study 2017.

See also: Thematic map, Time series comparison

Find indicator:
Rank Country Value Year
1 Bahrain 100.00 2017
1 Burundi 100.00 2017
1 Cameroon 100.00 2017
1 Congo 100.00 2017
1 Djibouti 100.00 2017
1 Central African Republic 100.00 2017
1 Eritrea 100.00 2017
1 Equatorial Guinea 100.00 2017
1 Iraq 100.00 2017
1 Libya 100.00 2017
1 Mauritania 100.00 2017
1 Niger 100.00 2017
1 Saudi Arabia 100.00 2017
1 Sudan 100.00 2017
1 Yemen 100.00 2017
1 Rwanda 100.00 2017
1 Qatar 100.00 2017
1 Chad 100.00 2017
1 Uganda 100.00 2017
20 Egypt 100.00 2017
21 Gabon 99.99 2017
22 Nepal 99.96 2017
23 Bangladesh 99.95 2017
24 Kuwait 99.90 2017
25 Afghanistan 99.66 2017
26 Pakistan 99.61 2017
27 Oman 98.94 2017
28 United Arab Emirates 98.31 2017
29 Burkina Faso 94.42 2017
30 Turkey 91.58 2017
31 Dem. Rep. Congo 89.59 2017
32 Nigeria 85.51 2017
33 India 84.76 2017
34 Algeria 84.41 2017
35 Senegal 83.83 2017
36 China 81.24 2017
37 Tajikistan 79.97 2017
38 Ethiopia 77.01 2017
39 Tunisia 76.96 2017
40 Syrian Arab Republic 69.77 2017
41 Mali 64.15 2017
42 Mongolia 63.30 2017
43 Bhutan 54.86 2017
44 Togo 51.85 2017
45 Iran 49.63 2017
46 Benin 45.22 2017
47 Ghana 45.06 2017
48 Myanmar 42.89 2017
49 Vietnam 34.48 2017
50 Armenia 34.26 2017
51 Cabo Verde 30.00 2017
52 Angola 23.94 2017
53 Morocco 21.87 2017
54 North Macedonia 21.22 2017
55 Kenya 20.83 2017
56 Jordan 19.81 2017
57 Somalia 19.69 2017
58 Dem. People's Rep. Korea 19.31 2017
59 Tanzania 19.29 2017
60 Uzbekistan 17.98 2017
61 The Gambia 17.23 2017
62 Bosnia and Herzegovina 13.40 2017
63 Kyrgyz Republic 12.61 2017
64 Peru 11.72 2017
65 South Africa 6.24 2017
66 Israel 6.07 2017
67 Lao PDR 4.10 2017
68 Thailand 3.15 2017
69 Côte d'Ivoire 2.77 2017
70 Brazil 2.02 2017
71 Belarus 1.85 2017
72 Mexico 1.59 2017
73 São Tomé and Principe 1.25 2017
74 Turkmenistan 0.81 2017
75 Russia 0.79 2017
76 Indonesia 0.59 2017
77 Azerbaijan 0.56 2017
78 Poland 0.39 2017
79 Chile 0.29 2017
80 Montenegro 0.26 2017
81 Serbia 0.24 2017
82 Georgia 0.17 2017
83 Lesotho 0.14 2017
84 Greece 0.12 2017
85 Bulgaria 0.11 2017
86 Argentina 0.06 2017
87 United States 0.02 2017
88 Zambia 0.01 2017
89 Lebanon 0.00 2017
90 Liberia 0.00 2017
90 St. Lucia 0.00 2017
90 Japan 0.00 2017
90 Kazakhstan 0.00 2017
90 Cambodia 0.00 2017
90 Lithuania 0.00 2017
90 Luxembourg 0.00 2017
90 Latvia 0.00 2017
90 Mozambique 0.00 2017
90 Moldova 0.00 2017
90 Madagascar 0.00 2017
90 Belgium 0.00 2017
90 Brunei 0.00 2017
90 Canada 0.00 2017
90 Switzerland 0.00 2017
90 Colombia 0.00 2017
90 Comoros 0.00 2017
90 Costa Rica 0.00 2017
90 Cyprus 0.00 2017
90 Germany 0.00 2017
90 Denmark 0.00 2017
90 Dominica 0.00 2017
90 Dominican Republic 0.00 2017
90 Spain 0.00 2017
90 Fiji 0.00 2017
90 France 0.00 2017
90 Ireland 0.00 2017
90 Honduras 0.00 2017
90 Hungary 0.00 2017
90 Italy 0.00 2017
90 Iceland 0.00 2017
90 Albania 0.00 2017
90 Andorra 0.00 2017
90 Antigua and Barbuda 0.00 2017
90 Australia 0.00 2017
90 Austria 0.00 2017
90 The Bahamas 0.00 2017
90 Bolivia 0.00 2017
90 Barbados 0.00 2017
90 Cuba 0.00 2017
90 Czech Republic 0.00 2017
90 Botswana 0.00 2017
90 Tonga 0.00 2017
90 Mauritius 0.00 2017
90 Malawi 0.00 2017
90 Namibia 0.00 2017
90 Nicaragua 0.00 2017
90 Netherlands 0.00 2017
90 Norway 0.00 2017
90 Suriname 0.00 2017
90 Sweden 0.00 2017
90 Paraguay 0.00 2017
90 Romania 0.00 2017
90 Venezuela 0.00 2017
90 Samoa 0.00 2017
90 Puerto Rico 0.00 2017
90 Papua New Guinea 0.00 2017
90 El Salvador 0.00 2017
90 Malta 0.00 2017
90 Malaysia 0.00 2017
90 New Zealand 0.00 2017
90 Panama 0.00 2017
90 Grenada 0.00 2017
90 Greenland 0.00 2017
90 Guatemala 0.00 2017
90 Guyana 0.00 2017
90 Croatia 0.00 2017
90 Haiti 0.00 2017
90 Belize 0.00 2017
90 Ecuador 0.00 2017
90 Estonia 0.00 2017
90 Kiribati 0.00 2017
90 Korea 0.00 2017
90 Sri Lanka 0.00 2017
90 Guinea-Bissau 0.00 2017
90 Jamaica 0.00 2017
90 Finland 0.00 2017
90 United Kingdom 0.00 2017
90 Guinea 0.00 2017
90 St. Vincent and the Grenadines 0.00 2017
90 Ukraine 0.00 2017
90 Uruguay 0.00 2017
90 Timor-Leste 0.00 2017
90 Trinidad and Tobago 0.00 2017
90 Vanuatu 0.00 2017
90 Zimbabwe 0.00 2017
90 Slovak Republic 0.00 2017
90 Slovenia 0.00 2017
90 Eswatini 0.00 2017
90 Seychelles 0.00 2017
90 Philippines 0.00 2017
90 Portugal 0.00 2017
90 Singapore 0.00 2017
90 Solomon Islands 0.00 2017
90 Sierra Leone 0.00 2017

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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. Three interim targets were defined for PM2.5 and have been shown to be achievable with successive and sustained abatement measures. Countries may find these interim targets particularly helpful in gauging progress over time in the difficult process of steadily reducing population exporsure to PM. IT-1 level corresponds to the highest mean concentrations reported in studies of long-term effects, and may also reflect higher but unknown historical concentrations that may have been contributed to observed health effects. IT-1 level has been shown to be associated with significant mortality in the developed world.

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.

Statistical Concept and Methodology: A. van Donkelaar, R.V. Martin, M. Brauer, N.C. Hsu, R.A. Kahn, R.C. Levy, A. Lyapustin, A.M. Sayer, D.M. Winker, "Global Estimates of Fine Particulate Matter using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors," Environ. Sci. Technol 50, no. 7 (2016): 3762–3772;GBD 2017 Risk Factors Collaborators, "Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 194 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017," Lancet 392 (2018): 1923-1994; Shaddick G, Thomas M, Amini H, Broday DM, Cohen A, Frostad J, Green A, Gumy S, Liu Y, Martin RV, Prüss-Üstün A, Simpson D, van Donkelaar A, Brauer M. Data integration for the assessment of population exposure to ambient air pollution for global burden of disease assessment. Environ Sci Technol. 2018 Jun 29. Data provided by Institute for Health Metrics and Evaluation, University of Washington, Seattle. Data on exposure to ambient air pollution are derived from estimates of annual concentrations of very fine particulates produced by the Global Burden of Disease study, an international scientific effort led by the Institute for Health Metrics and Evaluation at the University of Washington. Estimates of annual concentrations are generated by combining data from atmospheric chemistry transport models, satellite observations of aerosols in the atmosphere, and ground-level monitoring of particulates. Overlaying PM2.5 estimates with gridded population data, the percent of a nation's people that lives in areas where PM2.5 concentrations exceed recommended levels is calculated by summing the population for grid cells where PM2.5 concentrations are beyond a threshold value, in this case 10 micrograms per cubic meter, and then dividing by total population.

Aggregation method: Weighted average

Periodicity: Annual