Country stringclasses 174
values | City stringlengths 2 30 | AQI Value int64 7 500 | AQI Category stringclasses 6
values | CO AQI Value int64 0 133 | CO AQI Category stringclasses 3
values | Ozone AQI Value int64 0 222 | Ozone AQI Category stringclasses 5
values | NO2 AQI Value int64 0 91 | NO2 AQI Category stringclasses 2
values | PM2.5 AQI Value int64 0 500 | PM2.5 AQI Category stringclasses 6
values | lat float64 -54.8 70.8 | lng float64 -171.75 178 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Italy | Gela | 53 | Moderate | 1 | Good | 38 | Good | 2 | Good | 53 | Moderate | 37.0667 | 14.25 |
Netherlands | Gennep | 30 | Good | 0 | Good | 25 | Good | 3 | Good | 30 | Good | 51.7 | 5.9667 |
Germany | Genthin | 31 | Good | 0 | Good | 30 | Good | 1 | Good | 31 | Good | 52.4 | 12.1667 |
Guyana | Georgetown | 27 | Good | 0 | Good | 19 | Good | 0 | Good | 27 | Good | 6.8058 | -58.1508 |
Guyana | Georgetown | 27 | Good | 0 | Good | 19 | Good | 0 | Good | 27 | Good | -7.9286 | -14.4119 |
Guyana | Georgetown | 27 | Good | 0 | Good | 19 | Good | 0 | Good | 27 | Good | 30.666 | -97.6966 |
Guyana | Georgetown | 27 | Good | 0 | Good | 19 | Good | 0 | Good | 27 | Good | 38.2247 | -84.5487 |
Guyana | Georgetown | 27 | Good | 0 | Good | 19 | Good | 0 | Good | 27 | Good | 31.9849 | -81.226 |
Guyana | Georgetown | 27 | Good | 0 | Good | 19 | Good | 0 | Good | 27 | Good | -18.3 | 143.55 |
Germany | Gera | 30 | Good | 0 | Good | 28 | Good | 2 | Good | 30 | Good | 50.8806 | 12.0833 |
United States of America | Lake Jackson | 25 | Good | 0 | Good | 24 | Good | 2 | Good | 25 | Good | 29.0516 | -95.4521 |
United States of America | Lakeside | 57 | Moderate | 2 | Good | 22 | Good | 14 | Good | 57 | Moderate | 30.1356 | -81.7674 |
United States of America | Lakeside | 57 | Moderate | 2 | Good | 22 | Good | 14 | Good | 57 | Moderate | 32.856 | -116.904 |
United States of America | Lakeside | 57 | Moderate | 2 | Good | 22 | Good | 14 | Good | 57 | Moderate | 37.6132 | -77.4768 |
Thailand | Lam Luk Ka | 66 | Moderate | 1 | Good | 28 | Good | 1 | Good | 66 | Moderate | 13.9297 | 100.7375 |
Netherlands | Leusden | 33 | Good | 0 | Good | 33 | Good | 1 | Good | 26 | Good | 52.1333 | 5.4333 |
United Kingdom of Great Britain and Northern Ireland | Lewes | 37 | Good | 1 | Good | 12 | Good | 13 | Good | 37 | Good | 50.8747 | 0.0117 |
Philippines | Lianga | 50 | Good | 1 | Good | 20 | Good | 0 | Good | 50 | Good | 8.633 | 126.0932 |
France | Libourne | 46 | Good | 1 | Good | 26 | Good | 2 | Good | 46 | Good | 44.92 | -0.24 |
Czechia | Litovel | 49 | Good | 1 | Good | 24 | Good | 2 | Good | 49 | Good | 49.7012 | 17.0762 |
Belgium | Lokeren | 31 | Good | 0 | Good | 31 | Good | 2 | Good | 31 | Good | 51.1 | 3.9833 |
Belgium | Londerzeel | 34 | Good | 0 | Good | 29 | Good | 3 | Good | 34 | Good | 51 | 4.3 |
Senegal | Louga | 176 | Unhealthy | 2 | Good | 21 | Good | 3 | Good | 176 | Unhealthy | 15.6167 | -16.2167 |
Poland | Lubin | 35 | Good | 1 | Good | 20 | Good | 3 | Good | 35 | Good | 51.4 | 16.2 |
Poland | Lublin | 32 | Good | 1 | Good | 32 | Good | 1 | Good | 28 | Good | 51.25 | 22.5667 |
Philippines | Lucena | 32 | Good | 1 | Good | 29 | Good | 0 | Good | 32 | Good | 13.9333 | 121.6167 |
Philippines | Lucena | 32 | Good | 1 | Good | 29 | Good | 0 | Good | 32 | Good | 37.4 | -4.4833 |
Philippines | Lucena | 32 | Good | 1 | Good | 29 | Good | 0 | Good | 32 | Good | 10.8833 | 122.6 |
Philippines | Lucena | 32 | Good | 1 | Good | 29 | Good | 0 | Good | 32 | Good | -6.9 | -34.8689 |
Lesotho | Mafeteng | 117 | Unhealthy for Sensitive Groups | 4 | Good | 14 | Good | 7 | Good | 117 | Unhealthy for Sensitive Groups | -29.8167 | 27.25 |
United States of America | Magnolia | 56 | Moderate | 1 | Good | 25 | Good | 2 | Good | 56 | Moderate | 33.2775 | -93.2261 |
India | Maihar | 171 | Unhealthy | 1 | Good | 36 | Good | 0 | Good | 171 | Unhealthy | 24.262 | 80.761 |
United States of America | Maitland | 53 | Moderate | 1 | Good | 18 | Good | 14 | Good | 53 | Moderate | 28.6295 | -81.3718 |
United States of America | Maitland | 53 | Moderate | 1 | Good | 18 | Good | 14 | Good | 53 | Moderate | -32.7167 | 151.55 |
France | Malakoff | 40 | Good | 1 | Good | 26 | Good | 3 | Good | 40 | Good | 48.8169 | 2.2944 |
Benin | Malanville | 34 | Good | 1 | Good | 18 | Good | 1 | Good | 34 | Good | 11.8667 | 3.3833 |
Italy | Malnate | 69 | Moderate | 1 | Good | 22 | Good | 6 | Good | 69 | Moderate | 45.8 | 8.8833 |
Democratic Republic of the Congo | Manono | 74 | Moderate | 2 | Good | 23 | Good | 1 | Good | 74 | Moderate | -7.2947 | 27.4545 |
Venezuela (Bolivarian Republic of) | Maracaibo | 118 | Unhealthy for Sensitive Groups | 1 | Good | 17 | Good | 4 | Good | 118 | Unhealthy for Sensitive Groups | 10.6333 | -71.6333 |
Germany | Hagen | 30 | Good | 0 | Good | 30 | Good | 1 | Good | 25 | Good | 51.3667 | 7.4833 |
France | Halluin | 35 | Good | 0 | Good | 28 | Good | 2 | Good | 35 | Good | 50.7836 | 3.1256 |
Germany | Hamburg | 34 | Good | 0 | Good | 28 | Good | 2 | Good | 34 | Good | 53.55 | 10 |
Germany | Hamburg | 34 | Good | 0 | Good | 28 | Good | 2 | Good | 34 | Good | 42.7394 | -78.8581 |
United States of America | Hanahan | 73 | Moderate | 2 | Good | 35 | Good | 8 | Good | 73 | Moderate | 32.9302 | -80.0027 |
Bulgaria | Harmanli | 40 | Good | 1 | Good | 40 | Good | 1 | Good | 24 | Good | 41.9333 | 25.9 |
Pakistan | Harunabad | 500 | Hazardous | 1 | Good | 43 | Good | 0 | Good | 443 | Hazardous | 29.613 | 73.1409 |
Germany | Hattingen | 28 | Good | 0 | Good | 27 | Good | 2 | Good | 28 | Good | 51.3992 | 7.1858 |
United States of America | Hauppauge | 52 | Moderate | 1 | Good | 27 | Good | 12 | Good | 52 | Moderate | 40.8211 | -73.2109 |
United States of America | Hayward | 70 | Moderate | 2 | Good | 20 | Good | 20 | Good | 70 | Moderate | 37.6328 | -122.0766 |
Finland | Heinola | 33 | Good | 0 | Good | 33 | Good | 0 | Good | 5 | Good | 61.2 | 26.0333 |
Japan | Hekinan | 59 | Moderate | 1 | Good | 59 | Moderate | 1 | Good | 23 | Good | 34.8847 | 136.9934 |
Germany | Hemsbach | 30 | Good | 0 | Good | 30 | Good | 1 | Good | 24 | Good | 49.5903 | 8.6564 |
China | Hengyang | 169 | Unhealthy | 4 | Good | 169 | Unhealthy | 3 | Good | 150 | Unhealthy | 26.8968 | 112.5857 |
United States of America | Hoboken | 61 | Moderate | 1 | Good | 27 | Good | 11 | Good | 61 | Moderate | 40.7452 | -74.0281 |
United States of America | Hoboken | 61 | Moderate | 1 | Good | 27 | Good | 11 | Good | 61 | Moderate | 51.1667 | 4.3667 |
Somalia | Hobyo | 58 | Moderate | 0 | Good | 21 | Good | 0 | Good | 58 | Moderate | 5.3514 | 48.5256 |
Solomon Islands | Honiara | 18 | Good | 0 | Good | 18 | Good | 0 | Good | 6 | Good | -9.4319 | 159.9556 |
Paraguay | Horqueta | 20 | Good | 0 | Good | 20 | Good | 0 | Good | 20 | Good | -23.3442 | -57.0436 |
Armenia | Hrazdan | 31 | Good | 0 | Good | 31 | Good | 0 | Good | 30 | Good | 40.5 | 44.7667 |
China | Hsinchu | 138 | Unhealthy for Sensitive Groups | 3 | Good | 138 | Unhealthy for Sensitive Groups | 2 | Good | 112 | Unhealthy for Sensitive Groups | 24.8167 | 120.9833 |
Peru | Huaura | 39 | Good | 1 | Good | 19 | Good | 1 | Good | 39 | Good | -11.1 | -77.6 |
Zimbabwe | Hwange | 44 | Good | 0 | Good | 17 | Good | 0 | Good | 44 | Good | -18.3647 | 26.5 |
Japan | Ichihara | 74 | Moderate | 1 | Good | 74 | Moderate | 1 | Good | 35 | Good | 35.4981 | 140.1154 |
India | Khed | 95 | Moderate | 0 | Good | 22 | Good | 0 | Good | 95 | Moderate | 17.7189 | 73.3969 |
Russian Federation | Khimki | 40 | Good | 1 | Good | 30 | Good | 8 | Good | 40 | Good | 55.8892 | 37.445 |
Ukraine | Khotyn | 75 | Moderate | 1 | Good | 37 | Good | 1 | Good | 75 | Moderate | 48.5078 | 26.486 |
Turkey | Kilis | 64 | Moderate | 1 | Good | 41 | Good | 0 | Good | 64 | Moderate | 36.7167 | 37.1167 |
United States of America | Killeen | 40 | Good | 0 | Good | 21 | Good | 1 | Good | 40 | Good | 31.0753 | -97.7297 |
Austria | Klosterneuburg | 59 | Moderate | 1 | Good | 30 | Good | 3 | Good | 59 | Moderate | 48.3042 | 16.3167 |
Croatia | Knin | 48 | Good | 1 | Good | 48 | Good | 0 | Good | 35 | Good | 44.0414 | 16.1986 |
Papua New Guinea | Kokopo | 104 | Unhealthy for Sensitive Groups | 0 | Good | 22 | Good | 0 | Good | 104 | Unhealthy for Sensitive Groups | -4.35 | 152.2736 |
Russian Federation | Kola | 30 | Good | 1 | Good | 30 | Good | 0 | Good | 10 | Good | 22.43 | 87.87 |
Russian Federation | Kola | 30 | Good | 1 | Good | 30 | Good | 0 | Good | 10 | Good | 68.8833 | 33.0833 |
Russian Federation | Kotelnikovo | 39 | Good | 1 | Good | 39 | Good | 0 | Good | 20 | Good | 47.6333 | 43.15 |
Chad | Koumra | 59 | Moderate | 2 | Good | 6 | Good | 0 | Good | 59 | Moderate | 8.91 | 17.55 |
Russian Federation | Krasnovishersk | 29 | Good | 1 | Good | 28 | Good | 0 | Good | 29 | Good | 60.4167 | 57.1 |
Russian Federation | Krasnyy Yar | 34 | Good | 1 | Good | 34 | Good | 1 | Good | 24 | Good | 46.5331 | 48.3456 |
Russian Federation | Krasnyy Yar | 34 | Good | 1 | Good | 34 | Good | 1 | Good | 24 | Good | 53.3239 | 69.2525 |
Germany | Kronach | 36 | Good | 1 | Good | 26 | Good | 2 | Good | 36 | Good | 50.2411 | 11.3281 |
Germany | Kronberg | 30 | Good | 0 | Good | 30 | Good | 1 | Good | 27 | Good | 50.1833 | 8.5 |
Russian Federation | Kulebaki | 48 | Good | 1 | Good | 33 | Good | 1 | Good | 48 | Good | 55.4167 | 42.5333 |
Japan | Kushiro | 33 | Good | 1 | Good | 33 | Good | 0 | Good | 9 | Good | 42.9833 | 144.3833 |
Japan | Kushiro | 33 | Good | 1 | Good | 33 | Good | 0 | Good | 9 | Good | 42.9961 | 144.4661 |
Mexico | La Barca | 37 | Good | 1 | Good | 8 | Good | 3 | Good | 37 | Good | 20.2833 | -102.5667 |
France | La Crau | 60 | Moderate | 1 | Good | 30 | Good | 6 | Good | 60 | Moderate | 43.1497 | 6.0742 |
Honduras | La Entrada | 55 | Moderate | 2 | Good | 5 | Good | 4 | Good | 55 | Moderate | 15.05 | -88.7333 |
United States of America | La Presa | 58 | Moderate | 2 | Good | 14 | Good | 19 | Good | 58 | Moderate | 32.711 | -117.0027 |
Germany | Ilsede | 41 | Good | 0 | Good | 28 | Good | 2 | Good | 41 | Good | 52.2667 | 10.1833 |
Brazil | Imbituba | 31 | Good | 1 | Good | 15 | Good | 1 | Good | 31 | Good | -28.24 | -48.67 |
Brazil | Imbituva | 24 | Good | 1 | Good | 8 | Good | 0 | Good | 24 | Good | -25.23 | -50.6044 |
Japan | Inagi | 78 | Moderate | 1 | Good | 78 | Moderate | 3 | Good | 51 | Moderate | 35.6379 | 139.5046 |
Spain | Inca | 43 | Good | 1 | Good | 43 | Good | 0 | Good | 30 | Good | 39.7167 | 2.9167 |
India | Indore | 150 | Unhealthy | 1 | Good | 30 | Good | 0 | Good | 150 | Unhealthy | 22.7167 | 75.8472 |
United Kingdom of Great Britain and Northern Ireland | Inverurie | 31 | Good | 1 | Good | 31 | Good | 2 | Good | 25 | Good | 57.28 | -2.38 |
Japan | Ishigaki | 116 | Unhealthy for Sensitive Groups | 2 | Good | 116 | Unhealthy for Sensitive Groups | 0 | Good | 64 | Moderate | 24.3406 | 124.1556 |
Spain | Jaen | 36 | Good | 1 | Good | 17 | Good | 3 | Good | 36 | Good | 15.3392 | 120.9069 |
Mexico | Jilotepec | 95 | Moderate | 2 | Good | 9 | Good | 9 | Good | 95 | Moderate | 19.9519 | -99.5328 |
Mexico | Jilotepec | 95 | Moderate | 2 | Good | 9 | Good | 9 | Good | 95 | Moderate | 19.6113 | -96.9224 |
United Republic of Tanzania | Kabanga | 171 | Unhealthy | 6 | Good | 10 | Good | 3 | Good | 171 | Unhealthy | -2.9022 | 30.4986 |
Finland | Kajaani | 32 | Good | 1 | Good | 32 | Good | 0 | Good | 24 | Good | 64.2311 | 27.7194 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.