PM2.5 pollution, population exposed to levels exceeding WHO Interim Target-2 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 2 (IT-2) is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 25 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 Equatorial Guinea 100.00 2017
1 Dem. Rep. Congo 100.00 2017
1 Mali 100.00 2017
1 Qatar 100.00 2017
1 Rwanda 100.00 2017
1 The Gambia 100.00 2017
1 Chad 100.00 2017
1 Yemen 100.00 2017
1 Burundi 100.00 2017
1 Cameroon 100.00 2017
1 Congo 100.00 2017
1 Niger 100.00 2017
1 Senegal 100.00 2017
1 Ethiopia 100.00 2017
1 Nepal 100.00 2017
1 Uganda 100.00 2017
1 Bahrain 100.00 2017
1 Ghana 100.00 2017
1 Afghanistan 100.00 2017
1 Benin 100.00 2017
1 United Arab Emirates 100.00 2017
1 Bangladesh 100.00 2017
1 Algeria 100.00 2017
1 Guinea-Bissau 100.00 2017
1 Iraq 100.00 2017
1 São Tomé and Principe 100.00 2017
1 Tunisia 100.00 2017
1 Eritrea 100.00 2017
1 Kuwait 100.00 2017
1 Gabon 100.00 2017
1 Somalia 100.00 2017
1 Togo 100.00 2017
1 Libya 100.00 2017
1 Central African Republic 100.00 2017
1 Djibouti 100.00 2017
1 Oman 100.00 2017
1 Mauritania 100.00 2017
1 Saudi Arabia 100.00 2017
1 Sudan 100.00 2017
1 Angola 100.00 2017
1 Burkina Faso 100.00 2017
1 Cabo Verde 100.00 2017
43 Egypt 100.00 2017
44 Turkey 99.96 2017
45 Syrian Arab Republic 99.95 2017
46 Pakistan 99.90 2017
47 Dem. People's Rep. Korea 99.88 2017
48 Nigeria 99.87 2017
49 Tajikistan 99.86 2017
50 Lebanon 99.55 2017
51 Lesotho 99.31 2017
52 Morocco 98.82 2017
53 Iran 98.53 2017
54 Zambia 98.03 2017
55 China 97.16 2017
56 Myanmar 96.15 2017
57 India 93.73 2017
58 Bhutan 93.35 2017
59 Jordan 91.61 2017
60 Mongolia 80.56 2017
61 Armenia 77.97 2017
62 Vietnam 76.72 2017
63 Uzbekistan 72.24 2017
64 Côte d'Ivoire 68.57 2017
65 Thailand 67.14 2017
66 North Macedonia 67.01 2017
67 Namibia 63.61 2017
68 Bosnia and Herzegovina 63.17 2017
69 Kenya 61.98 2017
70 Cambodia 55.79 2017
71 Suriname 55.62 2017
72 Tanzania 55.29 2017
73 Lao PDR 54.69 2017
74 Korea 52.96 2017
75 Guinea 52.07 2017
76 Serbia 48.22 2017
77 South Africa 42.48 2017
78 Kyrgyz Republic 42.44 2017
79 Peru 39.23 2017
80 El Salvador 34.81 2017
81 Botswana 34.43 2017
82 Georgia 32.43 2017
83 Chile 31.24 2017
84 Bolivia 24.51 2017
85 Guatemala 24.02 2017
86 Guyana 23.71 2017
87 Turkmenistan 22.99 2017
88 Cuba 20.74 2017
89 Trinidad and Tobago 20.24 2017
90 Montenegro 19.22 2017
91 Poland 19.13 2017
92 Mexico 18.62 2017
93 Malawi 11.78 2017
94 Madagascar 11.55 2017
95 Honduras 8.86 2017
96 Ukraine 8.48 2017
97 Israel 8.25 2017
98 Zimbabwe 8.07 2017
99 Bulgaria 7.08 2017
100 Italy 6.73 2017
101 Indonesia 6.54 2017
102 Philippines 6.19 2017
103 Croatia 5.90 2017
104 Azerbaijan 5.70 2017
105 Czech Republic 4.88 2017
106 Brazil 4.70 2017
107 Mozambique 4.50 2017
108 Belarus 4.42 2017
109 Russia 3.95 2017
110 Greece 3.66 2017
111 Argentina 3.58 2017
112 Albania 3.10 2017
113 Belize 2.69 2017
114 Nicaragua 2.12 2017
115 Venezuela 2.04 2017
116 Sierra Leone 1.92 2017
117 Kazakhstan 1.36 2017
118 Colombia 1.34 2017
119 United States 0.05 2017
120 Spain 0.04 2017
121 Japan 0.00 2017
121 Liberia 0.00 2017
121 St. Vincent and the Grenadines 0.00 2017
121 Australia 0.00 2017
121 The Bahamas 0.00 2017
121 Barbados 0.00 2017
121 Belgium 0.00 2017
121 Greenland 0.00 2017
121 Kiribati 0.00 2017
121 Netherlands 0.00 2017
121 Norway 0.00 2017
121 Brunei 0.00 2017
121 Costa Rica 0.00 2017
121 Germany 0.00 2017
121 Haiti 0.00 2017
121 Timor-Leste 0.00 2017
121 Solomon Islands 0.00 2017
121 Estonia 0.00 2017
121 Denmark 0.00 2017
121 Slovak Republic 0.00 2017
121 Vanuatu 0.00 2017
121 Jamaica 0.00 2017
121 Mauritius 0.00 2017
121 Seychelles 0.00 2017
121 Grenada 0.00 2017
121 Finland 0.00 2017
121 United Kingdom 0.00 2017
121 Canada 0.00 2017
121 Cyprus 0.00 2017
121 Comoros 0.00 2017
121 Switzerland 0.00 2017
121 Singapore 0.00 2017
121 Eswatini 0.00 2017
121 Slovenia 0.00 2017
121 Uruguay 0.00 2017
121 Andorra 0.00 2017
121 Paraguay 0.00 2017
121 Sri Lanka 0.00 2017
121 Hungary 0.00 2017
121 Moldova 0.00 2017
121 Luxembourg 0.00 2017
121 Malaysia 0.00 2017
121 Ecuador 0.00 2017
121 Malta 0.00 2017
121 Austria 0.00 2017
121 Puerto Rico 0.00 2017
121 Lithuania 0.00 2017
121 Fiji 0.00 2017
121 Samoa 0.00 2017
121 Portugal 0.00 2017
121 Romania 0.00 2017
121 St. Lucia 0.00 2017
121 New Zealand 0.00 2017
121 Panama 0.00 2017
121 Ireland 0.00 2017
121 Iceland 0.00 2017
121 Latvia 0.00 2017
121 Dominica 0.00 2017
121 Dominican Republic 0.00 2017
121 France 0.00 2017
121 Tonga 0.00 2017
121 Antigua and Barbuda 0.00 2017
121 Papua New Guinea 0.00 2017
121 Sweden 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-2 level is greater than the mean concentration at which effects have been observed in studies of long-term exposure and mortality and is likely to be associated with significant health impacts from both long-term and daily exposures to PM2.5. Attainment of IT-2 value would reduce the health risks of long-term exposure by about 6% relative to the IT-1 value.

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