GovTwin / Institution

Narsingdi District

Local Gov

A textile and handloom district northeast of Dhaka on the Meghna and Shitalakshya river system, Narsingdi pairs a dense weaving and dyeing industry with intensive vegetable and fruit agriculture. It is a relatively prosperous district whose factory cluster has pushed its air toward the worst NO2 tier nationally even as its economic-activity growth has stalled.

Wealth rank 58/64 (1 = poorest district) Warming +0.7°C (1980s–2020s) Air NO₂ #5/64 (1 = most polluted) Night-lights +58% (2014–23 activity) Built-up 30 km² Forest loss 49 ha (2001–23) Rainfall 2,028 mm/yr

Indicators: Meta RWI (HDX); ERA5-Land; MODIS; Sentinel-5P; VIIRS night-lights; GHSL; Hansen v1.11; CHIRPS v2.0. Exposure: GloFAS v2.1, FABDEM, MODIS LST, ACAG PM2.5, WorldPop 2020.

Problems and issues

  1. air quality Narsingdi has the 5th-highest tropospheric NO2 of 64 districts at 77.3 umol/m2, reflecting its concentration of dyeing, weaving and textile-processing units. So what: High NO2 over a manufacturing district imposes a hidden health tax on the same workers the local economy depends on. Source: Sentinel-5P tropospheric NO2 via Google Earth Engine
  2. economy Nightlights growth of 58 percent ranks 60th of 64, among the slowest in the country, indicating economic-activity expansion has largely stalled relative to peer districts. So what: Near-stagnant activity growth in a traditional textile hub signals an industry losing competitiveness and in need of upgrading. Source: VIIRS nighttime lights (annual radiance) via Google Earth Engine
  3. environment Dyeing and washing effluent from the textile cluster discharges into the Meghna-Shitalakshya system, degrading surface water that supports the district's 40.2 km2 of permanent water and downstream irrigation. So what: Contaminated rivers undermine both the vegetable agriculture and the fisheries that diversify the local economy. Source: Department of Environment
  4. urbanization Built-up surface has grown about 44 percent since 2000 to 30.3 km2, spreading along the Dhaka corridor and converting farmland and floodplain into unplanned settlement. So what: Rapid built-up growth without planning erodes the productive vegetable belt and raises future flood and drainage costs. Source: GHSL built-up surface (JRC) via Google Earth Engine
  5. climate disaster Air temperature has warmed 0.7 C with daytime surface heat trending up 0.38 C to a recent 27.2 C, adding heat stress to dye houses and field labour alike. So what: Rising heat raises cooling and irrigation costs and threatens worker productivity across both factories and farms. Source: ERA5-Land reanalysis (Copernicus/ECMWF) via Google Earth Engine, district mean

Probable solutions

Upazilas (6)

Belabo Monohardi Narsingdi Sadar Palash Raipura, Narsingdi Shibpur