Brick Kiln Dataset for Pakistan's IGP Region Using AI
Authors/Creators
- 1. School of Electrical Engineering and Computer Science, National University of Sciences and Technology, Islamabad, 46000, Pakistan
- 2. Department of Geoinformatics – Z GIS, University of Salzburg, 5020, Austria
- 3. Smith School of Enterprise and Environment, University of Oxford, South Parks Rd, Oxford OX1 3QY
Description
This dataset represents the first geospatial mapping of brick kiln sites in the IGP region of Pakistan, providing an invaluable resource for understanding the spatial distribution of these sites. Each data point captures a brick kiln's precise location, including coordinates, state, and other important information, standardized in Coordinate Reference System (CRS) EPSG:4326 (WGS 84). This dataset, to the best of our knowledge, is the first of its kind to consolidate and geolocate brick kiln operations across this region, where air pollution impacts from kiln emissions are a significant environmental and public health concern.
In addition to the primary geolocation data, the dataset also includes an initial, secondary estimation of emissions (PM10, PM2.5, NOx, and SOx) from these sites. This supplementary information supports preliminary risk assessments, emphasizing proximity-based exposure for populations and sensitive areas (e.g., schools, hospitals) within a 1 km radius of each kiln site.
The dataset is made available in multiple formats to facilitate wide usage across spatial analysis platforms:
- Geojson (.geojson)
- Shapefile (.shp)
- Comma-Separated Values (.csv)
Metadata:
- Geographic Coverage: IGP - Pakistan
- CRS: EPSG:4326 (WGS 84)
Data Structure:
"Main" files have Basic ID & Location information, while the "Emission" files have Basic ID & Location + Production & Emission information.
Basic ID & Location
id: Unique identifier for the kiln.lat: Latitude of the kiln location.lon: Longitude of the kiln location.state: State where the kiln is located.type: Type of kiln (e.g., FCBK).
Production Data
avg_bricks: Average number of bricks produced daily. Refer to the GitHub repository for detailed methodology.seasonprod(bricks): Seasonal production of bricks in kilograms (excluding monsoon and smog days, considering 215 operational days).
Daily Emissions
pm2.5d(kg): Daily PM2.5 emissions in kilograms.pm10d(kg): Daily PM10 emissions in kilograms.noxd(kg): Daily NOx emissions in kilograms.soxd(kg): Daily SOx emissions in kilograms.
Seasonal Emissions
pm2.5s(kg): Seasonal PM2.5 emissions in kilograms.pm10s(kg): Seasonal PM10 emissions in kilograms.noxs(kg): Seasonal NOx emissions in kilograms.soxs(kg): Seasonal SOx emissions in kilograms.
Emission Factors
emf_coal(pm2.5): Emission factor for PM2.5 using coal as fuel (kg).emf_coal(pm10): Emission factor for PM10 using coal as fuel (kg).emf_coal(nox): Emission factor for NOx using coal as fuel (kg).emf_coal(so2): Emission factor for SOx using coal as fuel (kg).emf_coal(pm2.5): Emission factor for PM2.5 using biomass as fuel (kg).emf_coal(pm10): Emission factor for PM10 using biomass as fuel (kg).emf_coal(nox): Emission factor for NOx using biomass as fuel (kg).emf_coal(so2): Emission factor for SOx using biomass as fuel (kg).
Seasonal Emissions by Fuel Type
pm2.5s_c(kg): Seasonal PM2.5 emissions in kilograms using coal as a fuel.pm10s_c(kg): Seasonal PM10 emissions in kilograms using coal as a fuel.noxs_c(kg): Seasonal NOx emissions in kilograms using coal as a fuel.so2s_c(kg): Seasonal SO2 emissions in kilograms using coal as a fuel.pm2.5s_b(kg): Seasonal PM2.5 emissions in kilograms using biomass as a fuel.pm10s_b(kg): Seasonal PM10 emissions in kilograms using biomass as a fuel.noxs_b(kg): Seasonal NOx emissions in kilograms using biomass as a fuel.so2s_b(kg): Seasonal SO2 emissions in kilograms using biomass as a fuel.
Funding Sources: This research and data collection were funded by Amazon Web Services (AWS) and Smith School of Enterprise and The Environment (University of Oxford).
Files
Brick_Kilns_IGP_Emissions_PK.csv
Files
(50.7 MB)
| Name | Size | Download all |
|---|---|---|
|
md5:ae3b3df9970b49b6523e608759bc957d
|
5 Bytes | Download |
|
md5:2fc67fea8875965b3804b82dc2f33409
|
2.8 MB | Preview Download |
|
md5:8057a9c18f69157f529c7368301691c1
|
18.9 MB | Download |
|
md5:1139a6f70206a7311c29f35a599050b8
|
10.0 MB | Preview Download |
|
md5:c742bee3d4edfc2948a2ad08de1790a5
|
145 Bytes | Download |
|
md5:750c623ef1bc4cf0652ec49c5f9fdd13
|
701 Bytes | Download |
|
md5:df59cc80e5991a56ee707378dc119716
|
315.7 kB | Download |
|
md5:20cd8c746db845d0c8c2a327bf9dfde9
|
90.3 kB | Download |
|
md5:5428465c8a65420279c3363c70c89cce
|
3.6 MB | Download |
|
md5:ae3b3df9970b49b6523e608759bc957d
|
5 Bytes | Download |
|
md5:e96975b1749e1f453d8a4f898ebe88bc
|
578.9 kB | Preview Download |
|
md5:759f54685cc945d38b1aca759a625020
|
9.5 MB | Download |
|
md5:3b3b2d31e247da22d60552ce090731da
|
2.8 MB | Preview Download |
|
md5:c742bee3d4edfc2948a2ad08de1790a5
|
145 Bytes | Download |
|
md5:3c2d80d55c400e5af15210bb772b9282
|
1.6 kB | Download |
|
md5:df59cc80e5991a56ee707378dc119716
|
315.7 kB | Download |
|
md5:20cd8c746db845d0c8c2a327bf9dfde9
|
90.3 kB | Download |
|
md5:fe0b670b80e26e72170f462b2a865cf9
|
1.7 MB | Download |
Additional details
Related works
- Is part of
- Journal article: 10.1038/s41597-025-05148-9 (DOI)
Dates
- Available
-
2024-11-04
Software
- Repository URL
- https://drive.google.com/drive/folders/1ghDuKUz0-pTaDuCyKypyD0AR_ohL98gW?usp=sharing
- Programming language
- Python