SmogRank / History / week of October 30, 2023
Most polluted cities, week of October 30, 2023
1,841 cities ranked by their average PM2.5 over the 7 days. A city needs measurements on 70% of the days to be ranked.
| # | City | µg/m³ | |
|---|---|---|---|
| 1 | Lahore low-cost sensors Punjab, Pakistan | 272.9 | |
| 2 | Delhi Delhi, India | 258.9 | |
| 3 | Peshawar low-cost sensors Khyber Pakhtunkhwa, Pakistan | 168.0 | |
| 4 | Calexico California, United States | 146.4 | |
| 5 | N'Djamena N’Djaména, Chad | 117.1 | |
| 6 | Dhaka low-cost sensors Dhaka Division, Bangladesh | 99.4 | |
| 7 | Kolkata West Bengal, India | 96.0 | |
| 8 | Beijing Beijing, China | 78.4 | |
| 9 | Karachi low-cost sensors Sindh, Pakistan | 74.5 | |
| 10 | Ashgabat Ashgabat, Turkmenistan | 72.7 | |
| 11 | Mumbai Maharashtra, India | 72.2 | |
| 12 | Tlaquepaque Jalisco, Mexico | 72.0 | |
| 13 | Islamabad low-cost sensors Islamabad, Pakistan | 69.0 | |
| 14 | Hyderabad Telangana, India | 64.6 | |
| 15 | Cairo Cairo, Egypt | 52.7 | |
| 16 | Shenyang Liaoning, China | 52.1 | |
| 17 | Şabāḩ as Sālim Mubārak al Kabīr, Kuwait | 51.5 | |
| 18 | Jakarta Jakarta, Indonesia | 49.4 | |
| 19 | Hanoi Hanoi, Vietnam | 46.9 | |
| 20 | Salor Tashkent Region, Uzbekistan | 45.3 | |
| 21 | Tha Bo Nong Khai, Thailand | 41.9 | |
| 22 | Abuja low-cost sensors FCT, Nigeria | 36.1 | |
| 23 | Bangkok low-cost sensors Bangkok, Thailand | 32.9 | |
| 24 | Guangzhou Guangdong, China | 32.4 | |
| 25 | Pristina Pristina, Kosovo | 32.2 | |
| 26 | Antananarivo Analamanga, Madagascar | 32.1 | |
| 27 | Guadalajara Jalisco, Mexico | 31.8 | |
| 28 | Mexicali Baja California, Mexico | 31.5 | |
| 29 | Victoria de Durango Durango, Mexico | 29.7 | |
| 30 | Toluca México, Mexico | 27.1 | |
| 31 | Kathmandu low-cost sensors Bagmati Province, Nepal | 26.8 | |
| 32 | Jeddah Mecca Region, Saudi Arabia | 26.4 | |
| 33 | Hanford California, United States | 26.3 | |
| 34 | Kurashiki Okayama, Japan | 26.2 | |
| 35 | Almaty low-cost sensors Almaty, Kazakhstan | 25.3 | |
| 36 | San Francisco Tlalcilalcalpan México, Mexico | 24.7 | |
| 37 | Ciudad Benito Juárez Nuevo León, Mexico | 24.6 | |
| 38 | Cholula Puebla, Mexico | 24.5 | |
| 38 | San Salvador Tizatlalli México, Mexico | 24.5 | |
| 40 | Ang Mo Kio New Town Singapore | 24.1 | |
| 41 | Chikusei Ibaraki, Japan | 24.0 | |
| 41 | Yatomi Aichi, Japan | 24.0 | |
| 43 | Coeur d'Alene Idaho, United States | 23.5 | |
| 44 | Kigali Kigali, Rwanda | 23.4 | |
| 44 | Ulu Bedok Singapore | 23.4 | |
| 46 | Kazo Saitama, Japan | 23.3 | |
| 47 | Wan Chai Wan Chai, Hong Kong | 23.2 | |
| 47 | Tijuana Baja California, Mexico | 23.2 | |
| 49 | Fresno California, United States | 23.0 | |
| 50 | Kasaoka Okayama, Japan | 22.8 | |
| 50 | Handa Aichi, Japan | 22.8 | |
| 52 | Baku Baki, Azerbaijan | 22.3 | |
| 52 | Youkaichi Shiga, Japan | 22.3 | |
| 52 | Corcoran California, United States | 22.3 | |
| 52 | Cranbrook British Columbia, Canada | 22.3 | |
| 56 | Bakersfield California, United States | 22.0 | |
| 57 | Kan’onjichō Kagawa, Japan | 21.9 | |
| 57 | Gyōda Saitama, Japan | 21.9 | |
| 59 | Ourense Galicia, Spain | 21.7 | |
| 59 | Regina Saskatchewan, Canada | 21.7 | |
| 61 | Tokoname Aichi, Japan | 21.6 | |
| 61 | Hanyū Saitama, Japan | 21.6 | |
| 63 | Tahara Aichi, Japan | 21.3 | |
| 64 | Tetovo Tetovo, North Macedonia | 21.1 | |
| 64 | Sōja Okayama, Japan | 21.1 | |
| 64 | Kōnosu Saitama, Japan | 21.1 | |
| 64 | Sarajevo Federation of B&H, Bosnia and Herzegovina | 21.1 | |
| 68 | Igusa Saitama, Japan | 21.0 | |
| 69 | Addis Ababa Addis Ababa, Ethiopia | 20.8 | |
| 69 | Nagoya Aichi, Japan | 20.8 | |
| 69 | Visalia California, United States | 20.8 | |
| 69 | Chikugo Fukuoka, Japan | 20.8 | |
| 73 | Asaka Saitama, Japan | 20.7 | |
| 73 | Yakima Washington, United States | 20.7 | |
| 75 | Ciudad Apodaca Nuevo León, Mexico | 20.6 | |
| 76 | Nara-shi Nara, Japan | 20.5 | |
| 76 | Menuma Saitama, Japan | 20.5 | |
| 76 | Ageo Saitama, Japan | 20.5 | |
| 76 | Kaminoma Aichi, Japan | 20.5 | |
| 80 | Kampala low-cost sensors Central Region, Uganda | 20.4 | |
| 80 | Kasukabe Saitama, Japan | 20.4 | |
| 82 | Koshigaya Saitama, Japan | 20.2 | |
| 82 | Higashi-Matsuyama Saitama, Japan | 20.2 | |
| 82 | Asakuchi Okayama, Japan | 20.2 | |
| 85 | Yokkaichi Mie, Japan | 20.0 | |
| 85 | Misato, Saitama Saitama, Japan | 20.0 | |
| 85 | Tōkai Aichi, Japan | 20.0 | |
| 88 | Yawata Kyoto, Japan | 19.9 | |
| 88 | Jōsō Ibaraki, Japan | 19.9 | |
| 90 | Kameyama Mie, Japan | 19.8 | |
| 91 | Kumagaya Saitama, Japan | 19.7 | |
| 91 | Chiryū Aichi, Japan | 19.7 | |
| 93 | Kukichūō Saitama, Japan | 19.6 | |
| 93 | Matsusaka Mie, Japan | 19.6 | |
| 95 | Suzuka Mie, Japan | 19.5 | |
| 95 | Morohongō Saitama, Japan | 19.5 | |
| 95 | Kodamachō-kodamaminami Saitama, Japan | 19.5 | |
| 95 | Kakogawachō-honmachi Hyōgo, Japan | 19.5 | |
| 99 | Nampa Idaho, United States | 19.4 | |
| 99 | Altamont Oregon, United States | 19.4 | |
| 101 | Sakai-nakajima Gunma, Japan | 19.2 | |
| 101 | Kashihara-shi Nara, Japan | 19.2 | |
| 101 | Sunnyside Washington, United States | 19.2 | |
| 104 | Tanushimarumachi-toyoki Fukuoka, Japan | 19.1 | |
| 104 | Birmingham Alabama, United States | 19.1 | |
| 106 | Sano Tochigi, Japan | 19.0 | |
| 107 | Chigasaki Kanagawa, Japan | 18.9 | |
| 107 | Niiza Saitama, Japan | 18.9 | |
| 107 | Bizen Okayama, Japan | 18.9 | |
| 110 | Tamano Okayama, Japan | 18.8 | |
| 110 | Shimo-tsuma Ibaraki, Japan | 18.8 | |
| 112 | Colombo Western Province, Sri Lanka | 18.7 | |
| 112 | Sōka Saitama, Japan | 18.7 | |
| 112 | Noda Chiba, Japan | 18.7 | |
| 115 | Toyohashi Aichi, Japan | 18.6 | |
| 115 | Okayama Okayama, Japan | 18.6 | |
| 115 | Santa Catarina Nuevo León, Mexico | 18.6 | |
| 118 | Tuen Mun Tuen Mun, Hong Kong | 18.5 | |
| 118 | Nabari Mie, Japan | 18.5 | |
| 118 | Ashikaga Tochigi, Japan | 18.5 | |
| 118 | Anjō Aichi, Japan | 18.5 | |
| 118 | Edmonton Alberta, Canada | 18.5 | |
| 123 | Zentsujichó Kagawa, Japan | 18.4 | |
| 123 | Tsu Mie, Japan | 18.4 | |
| 123 | Okazaki Aichi, Japan | 18.4 | |
| 123 | Kashiwara Nara, Japan | 18.4 | |
| 123 | Columbus Georgia, United States | 18.4 | |
| 123 | Turlock California, United States | 18.4 | |
| 123 | Yachiyo Chiba, Japan | 18.4 | |
| 123 | Ama Aichi, Japan | 18.4 | |
| 131 | Tsuyama Okayama, Japan | 18.3 | |
| 131 | Kawaguchi Saitama, Japan | 18.3 | |
| 131 | Kariya Aichi, Japan | 18.3 | |
| 131 | Nagai Yamagata, Japan | 18.3 | |
| 131 | Bandō Ibaraki, Japan | 18.3 | |
| 131 | Arao Kumamoto, Japan | 18.3 | |
| 131 | Iga Mie, Japan | 18.3 | |
| 138 | Skopje Grad Skopje, North Macedonia | 18.2 | |
| 138 | Inuyama Aichi, Japan | 18.2 | |
| 138 | Alessandria Piedmont, Italy | 18.2 | |
| 141 | Yorii Saitama, Japan | 18.1 | |
| 141 | Saitama Saitama, Japan | 18.1 | |
| 141 | Higashigō Saga, Japan | 18.1 | |
| 141 | Kuwana Mie, Japan | 18.1 | |
| 145 | Higashinozoe Hyōgo, Japan | 18.0 | |
| 145 | Naka Ibaraki, Japan | 18.0 | |
| 145 | Modesto California, United States | 18.0 | |
| 145 | Iruma Saitama, Japan | 18.0 | |
| 145 | Sugai Kyoto, Japan | 18.0 | |
| 150 | Tin Shui Wai Yuen Long, Hong Kong | 17.9 | |
| 150 | Gifu Gifu, Japan | 17.9 | |
| 152 | Niihama Ehime, Japan | 17.8 | |
| 152 | Miyakonojō Miyazaki, Japan | 17.8 | |
| 154 | Tamana Kumamoto, Japan | 17.7 | |
| 154 | Sakado Saitama, Japan | 17.7 | |
| 154 | Kakamigahara Gifu, Japan | 17.7 | |
| 154 | Saltillo Coahuila, Mexico | 17.7 | |
| 158 | Ono Hyōgo, Japan | 17.6 | |
| 158 | Ōmuta Fukuoka, Japan | 17.6 | |
| 158 | Ichinomiya Aichi, Japan | 17.6 | |
| 158 | Amagasaki Hyōgo, Japan | 17.6 | |
| 158 | Salem Oregon, United States | 17.6 | |
| 158 | Spokane Washington, United States | 17.6 | |
| 158 | Owariasahi Aichi, Japan | 17.6 | |
| 165 | Sekimachi Gifu, Japan | 17.5 | |
| 165 | Salamanca Guanajuato, Mexico | 17.5 | |
| 165 | Grande Prairie Alberta, Canada | 17.5 | |
| 165 | Nisshin Aichi, Japan | 17.5 | |
| 165 | Nantan Kyoto, Japan | 17.5 | |
| 170 | Uji Kyoto, Japan | 17.4 | |
| 170 | Tenri Nara, Japan | 17.4 | |
| 170 | Seto Aichi, Japan | 17.4 | |
| 170 | Oyama Tochigi, Japan | 17.4 | |
| 170 | Nishio Aichi, Japan | 17.4 | |
| 170 | Kusatsu Shiga, Japan | 17.4 | |
| 170 | Kawagoe Saitama, Japan | 17.4 | |
| 170 | Ciudad Juárez Chihuahua, Mexico | 17.4 | |
| 170 | Stockton California, United States | 17.4 | |
| 170 | Tsuchiura Ibaraki, Japan | 17.4 | |
| 180 | Kanzakimachi-kanzaki Saga, Japan | 17.3 | |
| 180 | Hannō Saitama, Japan | 17.3 | |
| 180 | Hermiston Oregon, United States | 17.3 | |
| 180 | Spokane Valley Washington, United States | 17.3 | |
| 184 | Mong Kok Yau Tsim Mong District, Hong Kong | 17.2 | |
| 184 | Iyo Ehime, Japan | 17.2 | |
| 186 | Uto Kumamoto, Japan | 17.1 | |
| 186 | Honjō Saitama, Japan | 17.1 | |
| 186 | Hekinan Aichi, Japan | 17.1 | |
| 186 | Parkland Washington, United States | 17.1 | |
| 190 | Kurume Fukuoka, Japan | 17.0 | |
| 190 | Inabe Mie, Japan | 17.0 | |
| 190 | Hashima Gifu, Japan | 17.0 | |
| 193 | Saijō Ehime, Japan | 16.9 | |
| 194 | Niš Central Serbia, Serbia | 16.8 | |
| 194 | Sandachō Hyōgo, Japan | 16.8 | |
| 194 | Saikū Mie, Japan | 16.8 | |
| 194 | Boise Idaho, United States | 16.8 | |
| 194 | Mizuho Gifu, Japan | 16.8 | |
| 199 | Takahashi Okayama, Japan | 16.7 | |
| 199 | Kyoto Kyoto, Japan | 16.7 |
Top 200 of 1,841 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