SmogRank / History / week of November 20, 2023

Most polluted cities, week of November 20, 2023

1,879 cities ranked by their average PM2.5 over the 7 days; the worst was Lahore, Pakistan, at 282.6 µg/m³. A city needs measurements on 70% of the days to be ranked.

  1. 1Lahorelow-cost sensorsPunjab, Pakistan
    282.6
  2. 2DelhiDelhi, India
    239.0
  3. 3Dhakalow-cost sensorsDhaka Division, Bangladesh
    153.8
  4. 4KolkataWest Bengal, India
    152.9
  5. 5VeracruzVeracruz, Mexico
    135.7
  6. 6Karachilow-cost sensorsSindh, Pakistan
    114.4
  7. 7MexicaliBaja California, Mexico
    105.0
  8. 8Islamabadlow-cost sensorsIslamabad, Pakistan
    97.0
  9. 9SarajevoFederation of B&H, Bosnia and Herzegovina
    77.8
  10. 10CairoCairo, Egypt
    76.3
  11. 11MumbaiMaharashtra, India
    68.6
  12. 12Ulan BatorUlaanbaatar, Mongolia
    60.9
  13. 13BeijingBeijing, China
    55.7
  14. 14TlaquepaqueJalisco, Mexico
    53.0
  15. 15HyderabadTelangana, India
    52.6
  16. 16TetovoTetovo, North Macedonia
    52.3
  17. 17Abujalow-cost sensorsFCT, Nigeria
    49.2
  18. 18GuangzhouGuangdong, China
    46.8
  19. 19JakartaJakarta, Indonesia
    45.1
  20. 20AntananarivoAnalamanga, Madagascar
    39.5
  21. 21Banja LukaSrpska, Bosnia and Herzegovina
    38.4
  22. 22NišCentral Serbia, Serbia
    37.1
  23. 23PristinaPristina, Kosovo
    36.2
  24. 24KavadarciKavadarci, North Macedonia
    35.7
  25. 25SkopjeGrad Skopje, North Macedonia
    35.5
  26. 26Bangkoklow-cost sensorsBangkok, Thailand
    35.3
  27. 27Şabāḩ as SālimMubārak al Kabīr, Kuwait
    34.6
  28. 28Chiang Mailow-cost sensorsChiang Mai, Thailand
    34.3
  29. 29BitolaBitola, North Macedonia
    33.7
  30. 30CapannoriTuscany, Italy
    32.4
  31. 31JeddahMecca Region, Saudi Arabia
    30.5
  32. 32ShenyangLiaoning, China
    30.0
  33. 33Tuen MunTuen Mun, Hong Kong
    29.8
  34. 33BadgerAlaska, United States
    29.8
  35. 35DushanbeDushanbe, Tajikistan
    29.4
  36. 36GuadalajaraJalisco, Mexico
    29.1
  37. 37VelesVeles, North Macedonia
    28.8
  38. 37ZapopanJalisco, Mexico
    28.8
  39. 39Tha BoNong Khai, Thailand
    28.4
  40. 40OurenseGalicia, Spain
    28.2
  41. 40AlessandriaPiedmont, Italy
    28.2
  42. 42BelgradeCentral Serbia, Serbia
    28.0
  43. 42Wan ChaiWan Chai, Hong Kong
    28.0
  44. 44YangonYangon, Myanmar
    27.7
  45. 45CholulaPuebla, Mexico
    26.9
  46. 46IlindenIlinden, North Macedonia
    26.8
  47. 47ParedesPorto, Portugal
    26.4
  48. 48Ciudad Benito JuárezNuevo León, Mexico
    25.4
  49. 49ManlleuCatalonia, Spain
    25.1
  50. 50Ban Khlong Prawetlow-cost sensorsBangkok, Thailand
    25.0
  51. 51Almatylow-cost sensorsAlmaty, Kazakhstan
    24.9
  52. 52Tin Shui WaiYuen Long, Hong Kong
    24.6
  53. 53KigaliKigali, Rwanda
    24.5
  54. 54TolucaMéxico, Mexico
    24.4
  55. 55San Tung Chung HangIslands, Hong Kong
    24.3
  56. 56San Francisco TlalcilalcalpanMéxico, Mexico
    24.2
  57. 57Novi SadVojvodina, Serbia
    23.7
  58. 58FanlingNorth District, Hong Kong
    22.8
  59. 59CelayaGuanajuato, Mexico
    22.5
  60. 60ThessaloníkiCentral Macedonia, Greece
    22.4
  61. 61VisaliaCalifornia, United States
    22.1
  62. 62Tai PoTai Po, Hong Kong
    22.0
  63. 62FresnoCalifornia, United States
    22.0
  64. 64Mong KokYau Tsim Mong District, Hong Kong
    21.8
  65. 65DejCluj County, Romania
    21.7
  66. 66GrazStyria, Austria
    20.8
  67. 66Victoria de DurangoDurango, Mexico
    20.8
  68. 68Santa CatarinaNuevo León, Mexico
    20.7
  69. 69KochaniKochani, North Macedonia
    20.6
  70. 70KazincbarcikaBorsod-Abaúj-Zemplén, Hungary
    20.5
  71. 70San Salvador TizatlalliMéxico, Mexico
    20.5
  72. 72Ciudad ApodacaNuevo León, Mexico
    20.2
  73. 73Tsuen WanTsuen Wan, Hong Kong
    20.1
  74. 74ValdemoroMadrid, Spain
    19.9
  75. 75VigoGalicia, Spain
    19.6
  76. 76Kwai ChungKwai Tsing District, Hong Kong
    19.5
  77. 76TurinPiedmont, Italy
    19.5
  78. 78IaşiIași County, Romania
    19.2
  79. 79Sha TinSha Tin, Hong Kong
    19.1
  80. 79Sham Shui PoSham Shui Po District, Hong Kong
    19.1
  81. 79PratoTuscany, Italy
    19.1
  82. 82Sau Mau PingKwun Tong District, Hong Kong
    18.8
  83. 82SallanchesAuvergne-Rhône-Alpes, France
    18.8
  84. 84VictoriaCentral and Western, Hong Kong
    18.7
  85. 85Botevgradlow-cost sensorsSofia, Bulgaria
    18.5
  86. 85IrapuatoGuanajuato, Mexico
    18.5
  87. 87BakersfieldCalifornia, United States
    18.4
  88. 88JesiThe Marches, Italy
    18.2
  89. 89MonterreyNuevo León, Mexico
    18.0
  90. 90Cluj-NapocaCluj County, Romania
    17.9
  91. 91MiskolcBorsod-Abaúj-Zemplén, Hungary
    17.8
  92. 92Sevlievolow-cost sensorsGabrovo, Bulgaria
    17.7
  93. 92BailénAndalusia, Spain
    17.7
  94. 92MoreliaMichoacán, Mexico
    17.7
  95. 95Arden-ArcadeCalifornia, United States
    17.6
  96. 96Ciudad General EscobedoNuevo León, Mexico
    17.5
  97. 97AthensAttica, Greece
    17.4
  98. 97ArezzoTuscany, Italy
    17.4
  99. 97PueblaPuebla, Mexico
    17.4
  100. 100Addis AbabaAddis Ababa, Ethiopia
    17.1
  101. 100Mollet del VallèsCatalonia, Spain
    17.1
  102. 100ChikuseiIbaraki, Japan
    17.1
  103. 103Shakaskraallow-cost sensorsKwaZulu-Natal, South Africa
    17.0
  104. 103Quezon Citylow-cost sensorsNational Capital Region, Philippines
    17.0
  105. 103Falconara MarittimaThe Marches, Italy
    17.0
  106. 103Ciudad JuárezChihuahua, Mexico
    17.0
  107. 107ParklandWashington, United States
    16.9
  108. 108MiyakonojōMiyazaki, Japan
    16.8
  109. 108HanfordCalifornia, United States
    16.8
  110. 110Shimo-tsumaIbaraki, Japan
    16.7
  111. 111Collado-VillalbaMadrid, Spain
    16.4
  112. 111FlorenceTuscany, Italy
    16.4
  113. 111StocktonCalifornia, United States
    16.4
  114. 114HonmachiKumamoto, Japan
    16.3
  115. 114NagaiYamagata, Japan
    16.3
  116. 114SaltilloCoahuila, Mexico
    16.3
  117. 117Silao de la VictoriaGuanajuato, Mexico
    16.2
  118. 117ChikugoFukuoka, Japan
    16.2
  119. 119KasaokaOkayama, Japan
    16.1
  120. 120Uekimachi-mōnoKumamoto, Japan
    15.9
  121. 120ViareggioTuscany, Italy
    15.9
  122. 122BakuBaki, Azerbaijan
    15.8
  123. 122AberdeenSouthern District, Hong Kong
    15.8
  124. 124ŌmutaFukuoka, Japan
    15.7
  125. 124PrievidzaTrenčín Region, Slovakia
    15.7
  126. 124ClovisCalifornia, United States
    15.7
  127. 127Tanushimarumachi-toyokiFukuoka, Japan
    15.6
  128. 127PisaTuscany, Italy
    15.6
  129. 129CosladaMadrid, Spain
    15.5
  130. 129HattiesburgMississippi, United States
    15.5
  131. 129CorcoranCalifornia, United States
    15.5
  132. 132CalexicoCalifornia, United States
    15.4
  133. 133Haskovolow-cost sensorsHaskovo, Bulgaria
    15.2
  134. 133SevillaAndalusia, Spain
    15.2
  135. 135KurashikiOkayama, Japan
    15.1
  136. 135KumamotoKumamoto, Japan
    15.1
  137. 137MurciaMurcia, Spain
    15.0
  138. 137Sainte-Geneviève-des-BoisÎle-de-France, France
    15.0
  139. 137MonacoMunicipality of Monaco, Monaco
    15.0
  140. 137BogotáBogota D.C., Colombia
    15.0
  141. 141CórdobaAndalusia, Spain
    14.9
  142. 141KirishimaKagoshima, Japan
    14.9
  143. 143SōjaOkayama, Japan
    14.7
  144. 143AltamontOregon, United States
    14.7
  145. 145LleidaCatalonia, Spain
    14.6
  146. 145MercedCalifornia, United States
    14.6
  147. 145JōsōIbaraki, Japan
    14.6
  148. 148Hondomachi-hondoKumamoto, Japan
    14.5
  149. 148San Luis de la PazGuanajuato, Mexico
    14.5
  150. 150AmoraSetúbal, Portugal
    14.3
  151. 150TehuacánPuebla, Mexico
    14.3
  152. 152NyíregyházaSzabolcs-Szatmár-Bereg, Hungary
    14.2
  153. 152MinamataKumamoto, Japan
    14.2
  154. 152AlgiersAlgiers, Algeria
    14.2
  155. 152TsuchiuraIbaraki, Japan
    14.2
  156. 152YatomiAichi, Japan
    14.2
  157. 157UtoKumamoto, Japan
    14.1
  158. 157EsztergomKomárom-Esztergom, Hungary
    14.1
  159. 157León de los AldamaGuanajuato, Mexico
    14.1
  160. 157DublinOhio, United States
    14.1
  161. 157MaderaCalifornia, United States
    14.1
  162. 157KogaFukuoka, Japan
    14.1
  163. 163Maebaru-chūōFukuoka, Japan
    14.0
  164. 163FukuyamaHiroshima, Japan
    14.0
  165. 163GardanneProvence-Alpes-Côte d'Azur, France
    14.0
  166. 163Grants PassOregon, United States
    14.0
  167. 167AsprópyrgosAttica, Greece
    13.9
  168. 167Gabrovolow-cost sensorsGabrovo, Bulgaria
    13.9
  169. 167SendaiKagoshima, Japan
    13.9
  170. 167Santiago de QuerétaroQuerétaro, Mexico
    13.9
  171. 167Misato, SaitamaSaitama, Japan
    13.9
  172. 172RuseRuse, Bulgaria
    13.8
  173. 172TogitsuNagasaki, Japan
    13.8
  174. 172NantesPays de la Loire, France
    13.8
  175. 172TurlockCalifornia, United States
    13.8
  176. 176NagasakiNagasaki, Japan
    13.7
  177. 176Kanzakimachi-kanzakiSaga, Japan
    13.7
  178. 176Klagenfurt am WörtherseeCarinthia, Austria
    13.7
  179. 176Asunciónlow-cost sensorsAsuncion, Paraguay
    13.7
  180. 176BirminghamAlabama, United States
    13.7
  181. 176ComptonCalifornia, United States
    13.7
  182. 182KošiceKošice Region, Slovakia
    13.6
  183. 182SaseboNagasaki, Japan
    13.6
  184. 182ŌzuKumamoto, Japan
    13.6
  185. 182NodaChiba, Japan
    13.6
  186. 182KagoshimaKagoshima, Japan
    13.6
  187. 182Alcalá de HenaresMadrid, Spain
    13.6
  188. 188Kan’onjichōKagawa, Japan
    13.5
  189. 188AraoKumamoto, Japan
    13.5
  190. 190PartizánskeTrenčín Region, Slovakia
    13.4
  191. 190MedfordOregon, United States
    13.4
  192. 192YanagawaFukuoka, Japan
    13.3
  193. 192LormontNew Aquitaine, France
    13.3
  194. 192HernandoMississippi, United States
    13.3
  195. 192ChicoCalifornia, United States
    13.3
  196. 192KotōKumamoto, Japan
    13.3
  197. 197TagawaFukuoka, Japan
    13.2
  198. 197KobayashiMiyazaki, Japan
    13.2
  199. 197IzumiKagoshima, Japan
    13.2
  200. 197Valašské MeziříčíZlín, Czechia
    13.2

Top 200 of 1,879 shown.

Good0–9.0
Moderate9.1–35.4
Sensitive groups35.5–55.4
Unhealthy55.5–125.4
Very unhealthy125.5–225.4
Hazardous225.5+