Explore
Institutions
Bank Watch: scheduled banks tracked on stability metrics.
Parliament Watch: members and their activity.
Government Watch: the executive, tracked over time.
University Watch: the higher-education system, tracked.
NGO Watch: civil society and development NGOs, tracked.
Development Partner Watch: the donors, tracked.
Industry Association Watch: the apex chambers, tracked.
Early warning
The LDC 2029 graduation monitor.
The national early-warning board across hazards.
Early warning for the haor flood basin.
The multi-hazard exposure atlas, by district.
Where hazards compound across the same places.
A priority index ranking places by combined risk.
Cropland exposed to flood, heat, and salinity.
The bank distress watch: stress signals across banks.
The disaster ledger: events and losses over time.
বায়ুদূষণজনিত মৃত্যু
Environment
State
warning
Score
79.9
As of
2026-07-21
"Indicative" means no validated crisis-prediction skill: the labelled-episode record is too thin to score a crisis probability, so the page shows the benchmark-anchored state and (where available) the forecast trajectory only, never a crisis probability.
| Indicator | Value | z-score | Weight | As of |
|---|---|---|---|---|
| wb air pollution mortality p5 | 143.90 | - | 1.00 | 2019-12-31 |
Districts ranked by population-weighted PM2.5, population-weighted with WorldPop 2020. See the exposure atlas.
| District | Division | population-weighted PM2.5 |
|---|---|---|
| Noakhali | Chittagong | 85.3 ug/m3 |
| Lakshmipur | Chittagong | 84.6 ug/m3 |
| Chittagong | Chittagong | 84.4 ug/m3 |
| Munshiganj | Dhaka | 82.8 ug/m3 |
| Feni | Chittagong | 82.3 ug/m3 |
| Narayanganj | Dhaka | 82.1 ug/m3 |
| Chandpur | Chittagong | 81.7 ug/m3 |
| Bhola | Barisal | 81.7 ug/m3 |
air_pollution_mortality: Air-pollution mortality (per 100k, age-std.) 144 per 100k (as of 2019-12-31); level-anchored thresholds. WHO SDG 3.9.1 (household + ambient air-pollution mortality): 2019 global average ~60 per 100,000; bands set from the WHO income-group distribution (lower-middle-income ~80-100, worst-affected countries >150). Bangladesh ~144 per 100,000 (2019) is in the severe-to-critical band. Forward forecast omitted (series too short to validate).