Most polluted cities, 2024
1,686 cities ranked by their average PM2.5 over the 366 days. A city needs measurements on 70% of the days to be ranked.
| # | City | µg/m³ | |
|---|---|---|---|
| 1 | Lahore low-cost sensors Punjab, Pakistan | 142.6 | |
| 2 | Delhi Delhi, India | 102.2 | |
| 3 | Dhaka low-cost sensors Dhaka Division, Bangladesh | 98.1 | |
| 4 | Peshawar low-cost sensors Khyber Pakhtunkhwa, Pakistan | 97.8 | |
| 5 | N'Djamena N’Djaména, Chad | 97.1 | |
| 6 | Kolkata West Bengal, India | 71.9 | |
| 7 | Islamabad low-cost sensors Islamabad, Pakistan | 61.1 | |
| 8 | Kampala low-cost sensors Central Region, Uganda | 58.9 | |
| 9 | Kathmandu low-cost sensors Bagmati Province, Nepal | 57.1 | |
| 10 | Baghdad Baghdad, Iraq | 53.4 | |
| 11 | Santa Anita - Los Ficus Lima region, Peru | 47.8 | |
| 12 | Ulan Bator Ulaanbaatar, Mongolia | 47.7 | |
| 13 | Cairo Cairo, Egypt | 47.5 | |
| 13 | Dushanbe Dushanbe, Tajikistan | 47.5 | |
| 15 | Mumbai Maharashtra, India | 46.7 | |
| 16 | Hanoi Hanoi, Vietnam | 43.5 | |
| 17 | Karachi low-cost sensors Sindh, Pakistan | 43.4 | |
| 18 | Beijing Beijing, China | 43.3 | |
| 19 | Hyderabad Telangana, India | 40.7 | |
| 20 | Abuja low-cost sensors FCT, Nigeria | 40.0 | |
| 21 | Jakarta Jakarta, Indonesia | 38.6 | |
| 22 | Sarajevo Federation of B&H, Bosnia and Herzegovina | 37.1 | |
| 23 | Novi Pazar Central Serbia, Serbia | 36.7 | |
| 24 | Banja Luka Srpska, Bosnia and Herzegovina | 36.4 | |
| 25 | Şabāḩ as Sālim Mubārak al Kabīr, Kuwait | 35.1 | |
| 26 | Chiang Mai low-cost sensors Chiang Mai, Thailand | 34.9 | |
| 27 | Salor Tashkent Region, Uzbekistan | 34.8 | |
| 28 | Chennai Tamil Nadu, India | 32.0 | |
| 29 | Antananarivo Analamanga, Madagascar | 29.1 | |
| 30 | Lima Lima Province, Peru | 28.4 | |
| 31 | Užice Central Serbia, Serbia | 27.4 | |
| 32 | Lazarevac Central Serbia, Serbia | 26.9 | |
| 33 | Ashgabat Ashgabat, Turkmenistan | 26.8 | |
| 34 | Addis Ababa Addis Ababa, Ethiopia | 26.6 | |
| 34 | Niš Central Serbia, Serbia | 26.6 | |
| 36 | Bangkok low-cost sensors Bangkok, Thailand | 26.1 | |
| 37 | Shanghai Shanghai, China | 25.9 | |
| 38 | Tha Bo Nong Khai, Thailand | 25.0 | |
| 39 | Guangzhou Guangdong, China | 24.8 | |
| 40 | Zemun Central Serbia, Serbia | 24.3 | |
| 41 | Almaty low-cost sensors Almaty, Kazakhstan | 24.2 | |
| 42 | Yangon Yangon, Myanmar | 24.1 | |
| 42 | Celaya Guanajuato, Mexico | 24.1 | |
| 44 | Wan Chai Wan Chai, Hong Kong | 24.0 | |
| 45 | Baku Baki, Azerbaijan | 23.9 | |
| 46 | Smederevo Central Serbia, Serbia | 23.7 | |
| 47 | San Francisco De Borja Lima region, Peru | 23.3 | |
| 48 | Obrenovac Central Serbia, Serbia | 22.7 | |
| 49 | Pančevo Vojvodina, Serbia | 22.3 | |
| 50 | Racibórz Silesia, Poland | 21.5 | |
| 51 | Tuen Mun Tuen Mun, Hong Kong | 21.0 | |
| 52 | Jastrzębie Zdrój Silesia, Poland | 20.8 | |
| 53 | Belgrade Central Serbia, Serbia | 20.7 | |
| 54 | Działdowo Warmia-Masuria, Poland | 20.5 | |
| 55 | Miskolc Borsod-Abaúj-Zemplén, Hungary | 20.4 | |
| 56 | Zgierz Łódź Voivodeship, Poland | 20.2 | |
| 57 | Skarżysko-Kamienna Świętokrzyskie, Poland | 20.1 | |
| 57 | Callao Callao, Peru | 20.1 | |
| 59 | Accra low-cost sensors Greater Accra, Ghana | 19.8 | |
| 59 | Katowice Silesia, Poland | 19.8 | |
| 61 | Bielsko-Biala Silesia, Poland | 19.7 | |
| 62 | Włocławek Kujawsko-Pomorskie, Poland | 19.4 | |
| 63 | Sremčica Central Serbia, Serbia | 19.1 | |
| 63 | Astana Astana, Kazakhstan | 19.1 | |
| 63 | Villa Poeta José Gálvez Barrenechea Lima region, Peru | 19.1 | |
| 66 | Maputo Maputo City, Mozambique | 18.9 | |
| 67 | Kazincbarcika Borsod-Abaúj-Zemplén, Hungary | 18.7 | |
| 68 | Kalisz Greater Poland, Poland | 18.6 | |
| 68 | Asunción low-cost sensors Asuncion, Paraguay | 18.6 | |
| 70 | Otwock Mazovia, Poland | 18.5 | |
| 70 | Opole Opole Voivodeship, Poland | 18.5 | |
| 72 | Radomsko Łódź Voivodeship, Poland | 18.3 | |
| 72 | Łask Łódź Voivodeship, Poland | 18.3 | |
| 74 | Fengshan Takao, Taiwan | 18.2 | |
| 74 | Algiers Algiers, Algeria | 18.2 | |
| 74 | Żywiec Silesia, Poland | 18.2 | |
| 74 | Rabinal Baja Verapaz, Guatemala | 18.2 | |
| 78 | Kutno Łódź Voivodeship, Poland | 18.1 | |
| 79 | Prešov Prešov Region, Slovakia | 18.0 | |
| 79 | Kielce Świętokrzyskie, Poland | 18.0 | |
| 81 | Kędzierzyn-Koźle Opole Voivodeship, Poland | 17.9 | |
| 81 | Czechowice-Dziedzice Silesia, Poland | 17.9 | |
| 83 | Mielec Subcarpathia, Poland | 17.8 | |
| 83 | Kraków Lesser Poland, Poland | 17.8 | |
| 85 | Lublin Lublin, Poland | 17.7 | |
| 85 | Mong Kok Yau Tsim Mong District, Hong Kong | 17.7 | |
| 87 | Colombo Western Province, Sri Lanka | 17.5 | |
| 87 | Quezon City low-cost sensors National Capital Region, Philippines | 17.5 | |
| 89 | Cluj-Napoca Cluj County, Romania | 17.4 | |
| 90 | Kłodzko Lower Silesia, Poland | 17.3 | |
| 91 | Dębica Subcarpathia, Poland | 17.2 | |
| 91 | Tin Shui Wai Yuen Long, Hong Kong | 17.2 | |
| 93 | Przemyśl Subcarpathia, Poland | 17.1 | |
| 93 | Łuków Lublin, Poland | 17.1 | |
| 95 | Humenné Prešov Region, Slovakia | 17.0 | |
| 95 | Radom Mazovia, Poland | 17.0 | |
| 95 | Pruszków Mazovia, Poland | 17.0 | |
| 95 | Nisko Subcarpathia, Poland | 17.0 | |
| 95 | San Tung Chung Hang Islands, Hong Kong | 17.0 | |
| 100 | Zhushan Taiwan, Taiwan | 16.9 | |
| 100 | Poznań Greater Poland, Poland | 16.9 | |
| 100 | Futog Vojvodina, Serbia | 16.9 | |
| 103 | Košice Košice Region, Slovakia | 16.8 | |
| 103 | Starachowice Świętokrzyskie, Poland | 16.8 | |
| 103 | Augustów Podlasie, Poland | 16.8 | |
| 106 | Shakaskraal low-cost sensors KwaZulu-Natal, South Africa | 16.7 | |
| 106 | Novi Sad Vojvodina, Serbia | 16.7 | |
| 106 | Guatemala City Guatemala, Guatemala | 16.7 | |
| 109 | Kościan Greater Poland, Poland | 16.6 | |
| 110 | Zamość Lublin, Poland | 16.5 | |
| 111 | Yongkang Taiwan, Taiwan | 16.4 | |
| 112 | Kaohsiung Takao, Taiwan | 16.3 | |
| 112 | Erlun Taiwan, Taiwan | 16.3 | |
| 114 | Douliu Taiwan, Taiwan | 16.0 | |
| 115 | Legionowo Mazovia, Poland | 15.9 | |
| 116 | Nyíregyháza Szabolcs-Szatmár-Bereg, Hungary | 15.8 | |
| 116 | Chaozhou Taiwan, Taiwan | 15.8 | |
| 116 | Tai Po Tai Po, Hong Kong | 15.8 | |
| 119 | Vranov nad Topľou Prešov Region, Slovakia | 15.7 | |
| 119 | Jarosław Subcarpathia, Poland | 15.7 | |
| 119 | Tainan Taiwan, Taiwan | 15.7 | |
| 119 | Beigang Taiwan, Taiwan | 15.7 | |
| 123 | Tsuen Wan Tsuen Wan, Hong Kong | 15.6 | |
| 124 | Grajewo Podlasie, Poland | 15.5 | |
| 124 | Richards Bay low-cost sensors KwaZulu-Natal, South Africa | 15.5 | |
| 124 | Jincheng Fukien, Taiwan | 15.5 | |
| 127 | Puli Taiwan, Taiwan | 15.4 | |
| 128 | Żyrardów Mazovia, Poland | 15.3 | |
| 128 | Kwai Chung Kwai Tsing District, Hong Kong | 15.3 | |
| 130 | Konstancin-Jeziorna Mazovia, Poland | 15.2 | |
| 130 | Yuanlin Taiwan, Taiwan | 15.2 | |
| 130 | Xinying Taiwan, Taiwan | 15.2 | |
| 130 | Chiayi City Taiwan, Taiwan | 15.2 | |
| 134 | Wrocław Lower Silesia, Poland | 15.1 | |
| 134 | Toruń Kujawsko-Pomorskie, Poland | 15.1 | |
| 136 | Iaşi Iași County, Romania | 15.0 | |
| 136 | Sham Shui Po Sham Shui Po District, Hong Kong | 15.0 | |
| 138 | Náchod Hradec Králové Region, Czechia | 14.8 | |
| 138 | Bydgoszcz Kujawsko-Pomorskie, Poland | 14.8 | |
| 140 | Botevgrad low-cost sensors Sofia, Bulgaria | 14.6 | |
| 140 | Rzeszów Subcarpathia, Poland | 14.6 | |
| 140 | Erlin Taiwan, Taiwan | 14.6 | |
| 140 | Pécs Baranya, Hungary | 14.6 | |
| 140 | Jelenia Góra Lower Silesia, Poland | 14.6 | |
| 140 | Mission Texas, United States | 14.6 | |
| 146 | Szczecin West Pomerania, Poland | 14.5 | |
| 147 | Nitra Nitra Region, Slovakia | 14.4 | |
| 148 | Bucharest Bucharest, Romania | 14.3 | |
| 148 | Aberdeen Southern District, Hong Kong | 14.3 | |
| 148 | Łódź Łódź Voivodeship, Poland | 14.3 | |
| 148 | São Paulo São Paulo, Brazil | 14.3 | |
| 148 | Jurupa Valley California, United States | 14.3 | |
| 153 | Olsztyn Warmia-Masuria, Poland | 14.2 | |
| 153 | Victoria Central and Western, Hong Kong | 14.2 | |
| 153 | Tijuana Baja California, Mexico | 14.2 | |
| 156 | Nantou Taiwan, Taiwan | 14.1 | |
| 156 | Esztergom Komárom-Esztergom, Hungary | 14.1 | |
| 158 | Warsaw Mazovia, Poland | 14.0 | |
| 158 | Sau Mau Ping Kwun Tong District, Hong Kong | 14.0 | |
| 158 | Fontana California, United States | 14.0 | |
| 161 | Prievidza Trenčín Region, Slovakia | 13.9 | |
| 161 | Gorzów Wielkopolski Lubusz, Poland | 13.9 | |
| 163 | Gdynia Pomerania, Poland | 13.8 | |
| 163 | Elbląg Warmia-Masuria, Poland | 13.8 | |
| 163 | Fort McMurray Alberta, Canada | 13.8 | |
| 166 | Wawer Mazovia, Poland | 13.7 | |
| 166 | Ang Mo Kio New Town Singapore | 13.7 | |
| 168 | Pułtusk Mazovia, Poland | 13.6 | |
| 168 | Taibao Taiwan, Taiwan | 13.6 | |
| 168 | Płock Mazovia, Poland | 13.6 | |
| 171 | Dunaújváros Fejér, Hungary | 13.5 | |
| 171 | Los Angeles California, United States | 13.5 | |
| 173 | Zielona Góra Lubusz, Poland | 13.4 | |
| 173 | Kościerzyna Pomerania, Poland | 13.4 | |
| 175 | Białystok Podlasie, Poland | 13.3 | |
| 175 | Jurong West Singapore | 13.3 | |
| 175 | Birmingham Alabama, United States | 13.3 | |
| 178 | Taichung Taiwan, Taiwan | 13.1 | |
| 179 | Zhubei Taiwan, Taiwan | 13.0 | |
| 180 | Sha Tin Sha Tin, Hong Kong | 12.9 | |
| 180 | Badger Alaska, United States | 12.9 | |
| 182 | Teltow Brandenburg, Germany | 12.8 | |
| 182 | Bratislava Bratislava Region, Slovakia | 12.8 | |
| 184 | Craiova Dolj, Romania | 12.7 | |
| 184 | Tarnów Lesser Poland, Poland | 12.7 | |
| 184 | Kasaoka Okayama, Japan | 12.7 | |
| 184 | Riverside California, United States | 12.7 | |
| 184 | Edmonton Alberta, Canada | 12.7 | |
| 189 | Buzi Taiwan, Taiwan | 12.6 | |
| 189 | Gdańsk Pomerania, Poland | 12.6 | |
| 189 | Visalia California, United States | 12.6 | |
| 192 | Sevlievo low-cost sensors Gabrovo, Bulgaria | 12.5 | |
| 192 | Houston Texas, United States | 12.5 | |
| 194 | Pristina Pristina, Kosovo | 12.4 | |
| 194 | Ulu Bedok Singapore | 12.4 | |
| 194 | Świecie Kujawsko-Pomorskie, Poland | 12.4 | |
| 197 | Haskovo low-cost sensors Haskovo, Bulgaria | 12.3 | |
| 197 | Bishkek low-cost sensors Bishkek, Kyrgyzstan | 12.3 | |
| 197 | Toufen Taiwan, Taiwan | 12.3 | |
| 197 | Saijō Ehime, Japan | 12.3 |
Top 200 of 1,686 shown.
Good 0–9.0Moderate 9.1+Unhealthy for sensitive groups 35.5+Unhealthy 55.5+Very unhealthy 125.5+Hazardous 225.5+No data