PM2.5 air pollution, population exposed to levels exceeding WHO guideline value (% of total) - Country Ranking
Definition: Percent of population exposed to ambient concentrations of PM2.5 that exceed the WHO guideline value is defined as the portion of a country’s population living in places where mean annual concentrations of PM2.5 are greater than 10 micrograms per cubic meter, the guideline value recommended by the World Health Organization 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
| Rank | Country | Value | Year |
|---|---|---|---|
| 1 | Afghanistan | 100.00 | 2017 |
| 1 | United Arab Emirates | 100.00 | 2017 |
| 1 | Armenia | 100.00 | 2017 |
| 1 | Azerbaijan | 100.00 | 2017 |
| 1 | Benin | 100.00 | 2017 |
| 1 | Bangladesh | 100.00 | 2017 |
| 1 | Belize | 100.00 | 2017 |
| 1 | Dem. Rep. Congo | 100.00 | 2017 |
| 1 | Comoros | 100.00 | 2017 |
| 1 | Cyprus | 100.00 | 2017 |
| 1 | Algeria | 100.00 | 2017 |
| 1 | Egypt | 100.00 | 2017 |
| 1 | Eritrea | 100.00 | 2017 |
| 1 | Ethiopia | 100.00 | 2017 |
| 1 | Gabon | 100.00 | 2017 |
| 1 | Guinea | 100.00 | 2017 |
| 1 | The Gambia | 100.00 | 2017 |
| 1 | Guinea-Bissau | 100.00 | 2017 |
| 1 | Equatorial Guinea | 100.00 | 2017 |
| 1 | Greece | 100.00 | 2017 |
| 1 | Grenada | 100.00 | 2017 |
| 1 | Haiti | 100.00 | 2017 |
| 1 | India | 100.00 | 2017 |
| 1 | Iraq | 100.00 | 2017 |
| 1 | Jamaica | 100.00 | 2017 |
| 1 | Kenya | 100.00 | 2017 |
| 1 | Kiribati | 100.00 | 2017 |
| 1 | Korea | 100.00 | 2017 |
| 1 | Kuwait | 100.00 | 2017 |
| 1 | Libya | 100.00 | 2017 |
| 1 | Guatemala | 100.00 | 2017 |
| 1 | Mali | 100.00 | 2017 |
| 1 | Malta | 100.00 | 2017 |
| 1 | Mauritius | 100.00 | 2017 |
| 1 | Malawi | 100.00 | 2017 |
| 1 | Namibia | 100.00 | 2017 |
| 1 | Nepal | 100.00 | 2017 |
| 1 | Oman | 100.00 | 2017 |
| 1 | Pakistan | 100.00 | 2017 |
| 1 | Qatar | 100.00 | 2017 |
| 1 | Rwanda | 100.00 | 2017 |
| 1 | Singapore | 100.00 | 2017 |
| 1 | Eswatini | 100.00 | 2017 |
| 1 | Seychelles | 100.00 | 2017 |
| 1 | Syrian Arab Republic | 100.00 | 2017 |
| 1 | Chad | 100.00 | 2017 |
| 1 | Togo | 100.00 | 2017 |
| 1 | Tajikistan | 100.00 | 2017 |
| 1 | Timor-Leste | 100.00 | 2017 |
| 1 | Trinidad and Tobago | 100.00 | 2017 |
| 1 | Tunisia | 100.00 | 2017 |
| 1 | Uganda | 100.00 | 2017 |
| 1 | Ukraine | 100.00 | 2017 |
| 1 | Sierra Leone | 100.00 | 2017 |
| 1 | Somalia | 100.00 | 2017 |
| 1 | São Tomé and Principe | 100.00 | 2017 |
| 1 | Slovak Republic | 100.00 | 2017 |
| 1 | St. Vincent and the Grenadines | 100.00 | 2017 |
| 1 | Vietnam | 100.00 | 2017 |
| 1 | Vanuatu | 100.00 | 2017 |
| 1 | Zimbabwe | 100.00 | 2017 |
| 1 | Angola | 100.00 | 2017 |
| 1 | Albania | 100.00 | 2017 |
| 1 | Antigua and Barbuda | 100.00 | 2017 |
| 1 | Burundi | 100.00 | 2017 |
| 1 | Burkina Faso | 100.00 | 2017 |
| 1 | Bahrain | 100.00 | 2017 |
| 1 | The Bahamas | 100.00 | 2017 |
| 1 | Barbados | 100.00 | 2017 |
| 1 | Bhutan | 100.00 | 2017 |
| 1 | Botswana | 100.00 | 2017 |
| 1 | Central African Republic | 100.00 | 2017 |
| 1 | Côte d'Ivoire | 100.00 | 2017 |
| 1 | Cameroon | 100.00 | 2017 |
| 1 | Congo | 100.00 | 2017 |
| 1 | Cabo Verde | 100.00 | 2017 |
| 1 | Cuba | 100.00 | 2017 |
| 1 | Djibouti | 100.00 | 2017 |
| 1 | Dominica | 100.00 | 2017 |
| 1 | Georgia | 100.00 | 2017 |
| 1 | Ghana | 100.00 | 2017 |
| 1 | Hungary | 100.00 | 2017 |
| 1 | Iran | 100.00 | 2017 |
| 1 | Israel | 100.00 | 2017 |
| 1 | Jordan | 100.00 | 2017 |
| 1 | Cambodia | 100.00 | 2017 |
| 1 | Lao PDR | 100.00 | 2017 |
| 1 | Lebanon | 100.00 | 2017 |
| 1 | Liberia | 100.00 | 2017 |
| 1 | St. Lucia | 100.00 | 2017 |
| 1 | Lesotho | 100.00 | 2017 |
| 1 | Morocco | 100.00 | 2017 |
| 1 | Moldova | 100.00 | 2017 |
| 1 | Madagascar | 100.00 | 2017 |
| 1 | North Macedonia | 100.00 | 2017 |
| 1 | Myanmar | 100.00 | 2017 |
| 1 | Montenegro | 100.00 | 2017 |
| 1 | Mozambique | 100.00 | 2017 |
| 1 | Mauritania | 100.00 | 2017 |
| 1 | Niger | 100.00 | 2017 |
| 1 | Nigeria | 100.00 | 2017 |
| 1 | Saudi Arabia | 100.00 | 2017 |
| 1 | Sudan | 100.00 | 2017 |
| 1 | Senegal | 100.00 | 2017 |
| 1 | El Salvador | 100.00 | 2017 |
| 1 | Serbia | 100.00 | 2017 |
| 1 | Suriname | 100.00 | 2017 |
| 1 | Dem. People's Rep. Korea | 100.00 | 2017 |
| 1 | Thailand | 100.00 | 2017 |
| 1 | Turkmenistan | 100.00 | 2017 |
| 1 | Turkey | 100.00 | 2017 |
| 1 | Tanzania | 100.00 | 2017 |
| 1 | Uzbekistan | 100.00 | 2017 |
| 1 | Samoa | 100.00 | 2017 |
| 1 | Yemen | 100.00 | 2017 |
| 1 | South Africa | 100.00 | 2017 |
| 1 | Zambia | 100.00 | 2017 |
| 118 | Bolivia | 100.00 | 2017 |
| 119 | China | 100.00 | 2017 |
| 120 | Papua New Guinea | 100.00 | 2017 |
| 121 | Guyana | 99.99 | 2017 |
| 122 | Honduras | 99.98 | 2017 |
| 123 | Poland | 99.97 | 2017 |
| 124 | Peru | 99.96 | 2017 |
| 125 | Bosnia and Herzegovina | 99.96 | 2017 |
| 126 | Venezuela | 99.93 | 2017 |
| 127 | Belarus | 99.93 | 2017 |
| 128 | Solomon Islands | 99.92 | 2017 |
| 129 | Dominican Republic | 99.91 | 2017 |
| 130 | Nicaragua | 99.90 | 2017 |
| 131 | Bulgaria | 99.89 | 2017 |
| 132 | Tonga | 99.81 | 2017 |
| 133 | Croatia | 99.78 | 2017 |
| 134 | Costa Rica | 99.69 | 2017 |
| 135 | Czech Republic | 99.68 | 2017 |
| 136 | Mexico | 99.66 | 2017 |
| 137 | Netherlands | 99.60 | 2017 |
| 138 | Slovenia | 99.49 | 2017 |
| 139 | Paraguay | 99.06 | 2017 |
| 140 | Ecuador | 98.32 | 2017 |
| 141 | Romania | 98.02 | 2017 |
| 142 | Chile | 97.66 | 2017 |
| 143 | Kyrgyz Republic | 97.43 | 2017 |
| 144 | Mongolia | 97.01 | 2017 |
| 145 | Philippines | 96.37 | 2017 |
| 146 | Lithuania | 96.00 | 2017 |
| 147 | Indonesia | 95.57 | 2017 |
| 148 | Italy | 94.78 | 2017 |
| 149 | Argentina | 93.85 | 2017 |
| 150 | Colombia | 92.10 | 2017 |
| 151 | Belgium | 91.95 | 2017 |
| 152 | Russia | 91.61 | 2017 |
| 153 | Malaysia | 90.54 | 2017 |
| 154 | Germany | 89.17 | 2017 |
| 155 | Latvia | 89.01 | 2017 |
| 156 | Kazakhstan | 87.41 | 2017 |
| 157 | Austria | 85.05 | 2017 |
| 158 | Fiji | 82.80 | 2017 |
| 159 | Greenland | 80.02 | 2017 |
| 160 | France | 78.21 | 2017 |
| 161 | Japan | 76.76 | 2017 |
| 162 | Panama | 71.64 | 2017 |
| 163 | Luxembourg | 68.78 | 2017 |
| 164 | Brazil | 68.14 | 2017 |
| 165 | United Kingdom | 66.53 | 2017 |
| 166 | Denmark | 56.91 | 2017 |
| 167 | Switzerland | 49.30 | 2017 |
| 168 | Sri Lanka | 45.54 | 2017 |
| 169 | Spain | 41.12 | 2017 |
| 170 | Australia | 24.89 | 2017 |
| 171 | Uruguay | 22.39 | 2017 |
| 172 | Andorra | 17.82 | 2017 |
| 173 | Portugal | 16.01 | 2017 |
| 174 | Iceland | 10.29 | 2017 |
| 175 | Puerto Rico | 3.67 | 2017 |
| 176 | Sweden | 3.64 | 2017 |
| 177 | United States | 3.34 | 2017 |
| 178 | Norway | 2.04 | 2017 |
| 179 | Ireland | 0.27 | 2017 |
| 180 | New Zealand | 0.00 | 2017 |
| 180 | Brunei | 0.00 | 2017 |
| 180 | Canada | 0.00 | 2017 |
| 180 | Estonia | 0.00 | 2017 |
| 180 | Finland | 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.
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
