India · West Bengal · 35 cities
Air quality in West Bengal today The AQI right now, city by city
Right now, Bangaon has the cleanest air of the 35 cities we track in West Bengal (AQI 50, Good), and Puruliya the worst (AQI 219, Very unhealthy). Dārjiling has the most tree cover, at 88.2% — #1 of 470 cities measured in India.
Every city is measured the same way, over the same 2 km around its center: the air quality right now, from ground stations where there are any, and its tree cover.
AQI 103
Average right now
Unhealthy for sensitive groups
- cities tracked
- 35
- average tree cover
- 53.0%
- India: 27.3%
- worst air now: Puruliya
- 219
- cleanest air now: Bangaon
- 50
Lower is better on the US EPA index: 0–50 is Good, above 300 is Hazardous, and it reads differently from India's AQI (CPCB). Measured by Airleaf, refreshed hourly.
West Bengal · average AQI 103
Air quality today across West Bengal, city by city
| Kolkata | 87Moderate | 28.7% | 4.1K | #156 of 470 |
|---|---|---|---|---|
| Durgapur | 108Unhealthy for sensitive groups | 52.1% | — | #39 of 470 |
| Siliguri | 62Moderate | 39.3% | — | #81 of 470 |
| Āsansol | 158Unhealthy | 41.9% | — | #63 of 470 |
| Bhātpāra | 83Moderate | 51.6% | — | #40 of 470 |
| Maheshtala | 90Moderate | 72.1% | — | #11 of 470 |
| Rajpur Sonarpur | 87Moderate | 67.9% | — | #14 of 470 |
| Pānihāti | 108Unhealthy for sensitive groups | 39.7% | — | #76 of 470 |
| Kulti | 158Unhealthy | 45.2% | — | #51 of 470 |
| Barddhamān | 81Moderate | 44.7% | — | #55 of 470 |
| Bārāsat | 89Moderate | 52.9% | — | #37 of 470 |
| Uluberiya | 87Moderate | 76.6% | — | #7 of 470 |
| Kharagpur | 85Moderate | 64.4% | — | #19 of 470 |
| Baharampur | 109Unhealthy for sensitive groups | 52.2% | — | #38 of 470 |
| Haldia | 64Moderate | 38.8% | — | #84 of 470 |
| Rāiganj | 114Unhealthy for sensitive groups | 60.4% | — | #24 of 470 |
| Malda | 90Moderate | 45.3% | — | #48 of 470 |
| Jāmuria | 159Unhealthy | 28.7% | 35.4K | #154 of 470 |
| Jaigaon | 78Moderate | 34.3% | — | #108 of 470 |
| Medinīpur | 75Moderate | 55.4% | — | #31 of 470 |
| Bālurghāt | 163Unhealthy | 49.8% | — | #43 of 470 |
| Shāntipur | 91Moderate | 76.5% | — | #8 of 470 |
| Bārākpur | 83Moderate | 57.7% | — | #26 of 470 |
| Krishnanagar | 91Moderate | 55.8% | — | #28 of 470 |
| Basirhat City | 81Moderate | 71.6% | — | #12 of 470 |
| Hābra | 81Moderate | 80.1% | — | #5 of 470 |
| Kānchrāpāra | 83Moderate | 60.6% | — | #23 of 470 |
| Bānkura | 161Unhealthy | 41.2% | — | #64 of 470 |
| Rānīganj | 198Unhealthy | 25.5% | 45.1K | #203 of 470 |
| Dārjiling | 52Moderate | 88.2% | — | #1 of 470 |
| Dam Dam | 111Unhealthy for sensitive groups | 37.9% | — | #92 of 470 |
| Puruliya | 219Very unhealthy | 40.7% | 13.3K | #73 of 470 |
| Bangaon | 50Good | 73.8% | — | #10 of 470 |
| Navadwīp | 75Moderate | 64.7% | — | #18 of 470 |
| Jalpāiguri | 105Unhealthy for sensitive groups | 39.6% | — | #77 of 470 |
Air quality is the US AQI from ground monitoring stations via OpenAQ where available, otherwise the Open-Meteo / CAMS model, refreshed hourly. Tree cover is measured within 2 km of each city center from Sentinel-2 imagery; the rank compares every city measured in India.
Is this the same as India's AQI (CPCB)?
No. Airleaf shows the US EPA Air Quality Index (AQI), the scale used by IQAir and most air-quality apps. India's Central Pollution Control Board (CPCB) publishes the National Air Quality Index on its own scale: 0–50 good, 51–100 satisfactory, 101–200 moderate, 201–300 poor, 301–400 very poor and 401–500 severe. The two scales don't line up. At moderate fine-particle levels the US scale reads higher: 55 µg/m³ of PM2.5 is 149 on the US AQI but about 92, "satisfactory", on India's. In heavy smog India's reads higher: 100 µg/m³ is 182 on the US AQI and about 232, "poor", on India's. CPCB also averages particles over 24 hours, so its figure moves more slowly than an hourly reading.
India's AQI (CPCB) and the AQI, explainedDeforestation · 2001–2025
How much forest has West Bengal lost?
Since 2001, West Bengal has lost about 16,000 hectares of forest (about 22,000 football pitches): 4% of the forest it had in 2000. Most of it (63%) was deforestation, forest cleared for good, mainly for farms, pasture and plantations.
- Forest lost since 2001
- 16,000 haabout 22,000 football pitches
- Share of its forest
- 4%of what there was in 2000
- Cleared for good
- 10,000 hadeforestation: turned into farms, mines or towns
Hectares of forest lost each year
Show the figures as a table
| Year | Cleared for good | Can grow back | Total |
|---|---|---|---|
| 2001 | 224 ha | 156 ha | 380 ha |
| 2002 | 174 ha | 181 ha | 355 ha |
| 2003 | 130 ha | 60 ha | 190 ha |
| 2004 | 294 ha | 263 ha | 557 ha |
| 2005 | 264 ha | 182 ha | 446 ha |
| 2006 | 453 ha | 311 ha | 764 ha |
| 2007 | 760 ha | 735 ha | 1,500 ha |
| 2008 | 880 ha | 639 ha | 1,520 ha |
| 2009 | 545 ha | 320 ha | 865 ha |
| 2010 | 1,390 ha | 574 ha | 1,970 ha |
| 2011 | 669 ha | 253 ha | 922 ha |
| 2012 | 784 ha | 425 ha | 1,210 ha |
| 2013 | 191 ha | 130 ha | 321 ha |
| 2014 | 360 ha | 267 ha | 627 ha |
| 2015 | 80 ha | 70 ha | 150 ha |
| 2016 | 118 ha | 125 ha | 243 ha |
| 2017 | 296 ha | 179 ha | 475 ha |
| 2018 | 197 ha | 87 ha | 284 ha |
| 2019 | 243 ha | 105 ha | 348 ha |
| 2020 | 219 ha | 70 ha | 289 ha |
| 2021 | 342 ha | 90 ha | 432 ha |
| 2022 | 352 ha | 155 ha | 507 ha |
| 2023 | 461 ha | 94 ha | 555 ha |
| 2024 | 301 ha | 109 ha | 410 ha |
| 2025 | 287 ha | 431 ha | 718 ha |
Forest loss is speeding up: about 524 hectares a year in 2021–2025, up from 328 hectares a year in 2016–2020. The worst year was 2010, when about 1,970 hectares of forest were lost.
What is causing deforestation in West Bengal?
- Farms, pasture and plantationscleared for good58% · 9,290 ha
- Loggingcan grow back21% · 3,300 ha
- Storms, floods and other natural causescan grow back11% · 1,690 ha
Also: towns and roads, shifting farming, mining and energy, wildfires, unknown causes.
Causes for 2025 are estimates, based on what caused forest loss in the same places up to 2024.
Source: Hansen/UMD/Google/USGS/NASA, Global Forest Change (GFC-2025-v1.13); causes: WRI/Google DeepMind drivers of forest loss; both CC BY 4.0, summed by Airleaf for each area. How it's measured
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