Datasets:
metadata
license: cc-by-4.0
task_categories:
- tabular-classification
- feature-extraction
tags:
- environment
- rivers
- pollution
- geospatial
- europe
size_categories:
- 100K<n<1M
EEA Industrial Emissions - River Proximity Dataset
This dataset links 160,576 industrial facilities from the European Environment Agency (EEA) to nearby rivers, with upstream/downstream flow analysis based on HydroRIVERS network data.
Why This Dataset?
Industrial facilities that discharge pollutants into water bodies affect downstream ecosystems and communities. This dataset enables:
- Impact assessment: Which communities/ecosystems are downstream of polluting facilities?
- Source tracing: Where does a facility's water supply come from?
- Regulatory analysis: Mapping industrial emissions to affected river networks
- Environmental research: Studying relationships between industry and water quality
How It Works
┌─────────────┐
│ UPSTREAM │ ← Source water (green)
│ (5 parts) │ flowing TOWARD facility
└──────┬──────┘
│
───────●─────── ← Split point (closest to facility)
│
┌──────┴──────┐
│ FACILITY │ ← Industrial facility (orange)
│ (211m) │ within 1km of river
└─────────────┘
│
┌──────┴──────┐
│ DOWNSTREAM │ → Affected water (red)
│ (4 parts) │ flowing AWAY from facility
└─────────────┘
For each facility:
- Find the closest river segment within 1km
- Split the river at the closest point
- Trace upstream 10km (source water)
- Trace downstream 10km (potentially affected)
- Clip water surface polygons to match
Dataset Files
river_data_facilities.geoparquet (2.6 GB)
Main dataset with 160,576 facilities matched to rivers.
| Column | Type | Description |
|---|---|---|
facilityName |
string | Name of industrial facility |
city |
string | City location |
countryName |
string | Country |
EPRTR_SectorCode |
int | Industry sector code (1-9) |
EPRTR_SectorName |
string | Industry sector name |
Pollutant |
string | Pollutant released to water |
Releases |
float | Amount released |
closest_river_id |
int | HydroRIVERS segment ID |
distance_to_river_m |
float | Distance to river (meters) |
river_strahler |
int | Strahler stream order (1-9) |
river_discharge |
float | Average discharge (m³/s) |
upstream_segment_ids |
list[int] | Upstream HydroRIVERS IDs |
downstream_segment_ids |
list[int] | Downstream HydroRIVERS IDs |
n_upstream |
int | Number of upstream parts |
n_downstream |
int | Number of downstream parts |
upstream_line_wkb |
bytes | Upstream river geometry (WKB) |
downstream_line_wkb |
bytes | Downstream river geometry (WKB) |
upstream_poly_wkb |
bytes | Upstream water surface (WKB) |
downstream_poly_wkb |
bytes | Downstream water surface (WKB) |
geometry |
Point | Facility location (WGS84) |
closest_river_overlap_fraction |
float | Fraction (0–1) of the closest HydroRIVERS segment's length that falls inside an EU-Hydro River_Net_p polygon (± 30 m buffer) |
closest_river_is_sentinel_visible |
bool | True if closest_river_overlap_fraction ≥ 0.30 — the closest river segment is wide enough to be detectable in Sentinel-2 |
n_upstream_sentinel_visible |
int | Number of upstream segments that meet the Sentinel-visibility threshold |
n_downstream_sentinel_visible |
int | Number of downstream segments that meet the Sentinel-visibility threshold |
has_sentinel_visible_river |
bool | Summary flag — True if any of the closest, upstream, or downstream segments is Sentinel-visible; use this column to filter facilities to those where Sentinel-2 water-quality retrieval is feasible |
river_data_segments.geoparquet (1.7 MB)
River segments with direction labels (28,434 entries).
| Column | Type | Description |
|---|---|---|
HYRIV_ID |
int | HydroRIVERS segment ID |
direction |
string | "upstream" or "downstream" |
ORD_STRA |
int | Strahler stream order |
DIS_AV_CMS |
float | Average discharge (m³/s) |
LENGTH_KM |
float | Segment length (km) |
geometry |
LineString | River segment geometry |
Usage
Load the dataset
import geopandas as gpd
from shapely import wkb
# Load facilities
facilities = gpd.read_parquet("river_data_facilities.geoparquet")
print(f"Loaded {len(facilities):,} facilities")
# Example: Find facilities in Germany
german = facilities[facilities['countryName'] == 'Germany']
print(f"Germany has {len(german):,} facilities near rivers")
Extract river geometries
# Get a specific facility
facility = facilities[facilities['facilityName'].str.contains('PRECHEZA')].iloc[0]
# Parse WKB geometries
upstream_line = wkb.loads(facility['upstream_line_wkb'])
downstream_line = wkb.loads(facility['downstream_line_wkb'])
upstream_poly = wkb.loads(facility['upstream_poly_wkb'])
downstream_poly = wkb.loads(facility['downstream_poly_wkb'])
print(f"Upstream: {facility['n_upstream']} segments")
print(f"Downstream: {facility['n_downstream']} segments")
Visualize a facility
python visualize_single_facility.py "PRECHEZA"
# Opens facility_map.html in browser
Visualize multiple facilities
python visualize_facilities_rivers.py
# Opens facilities_rivers_map.html with 200 sampled facilities
Scripts
river_proximity.py
Main pipeline that:
- Loads EEA facilities, HydroRIVERS segments, and EU-Hydro polygons
- Builds river network graph from NEXT_DOWN field
- For each facility, finds closest river and splits at nearest point
- Traces upstream (BFS) and downstream (linear) within distance limits
- Clips water surface polygons to match river geometries
- Outputs geoparquet files
visualize_single_facility.py
Creates an interactive Folium map for a single facility showing:
- Green: upstream river and water surface
- Red: downstream river and water surface
- Orange marker: facility location
visualize_facilities_rivers.py
Creates an overview map with sampled facilities and their river associations.
Source Data
| Dataset | Source | Usage |
|---|---|---|
| Industrial Facilities | EEA E-PRTR | Facility locations & emissions |
| River Network | HydroRIVERS v1.0 | River segments & flow direction |
| Water Polygons | EU-Hydro | Water surface geometry |
Parameters
| Parameter | Value | Description |
|---|---|---|
max_distance_m |
1,000 | Max distance from facility to river |
upstream_distance_km |
10 | How far to trace upstream |
downstream_distance_km |
10 | How far to trace downstream |
polygon_buffer_m |
600 | Buffer for polygon clipping |
Statistics
- Total facilities processed: 254,027
- Facilities near rivers: 160,576 (63%)
- Unique upstream segments: 18,498
- Unique downstream segments: 9,936
- Average upstream parts: 7.1
- Average downstream parts: 3.7
Sentinel visibility (EU-Hydro River_Net_p overlap ≥ 30 %)
| Strahler order | Facilities | % Sentinel-visible |
|---|---|---|
| 1 | 43,699 | 22.5 % |
| 2 | 28,113 | 20.5 % |
| 3 | 31,616 | 23.9 % |
| 4 | 24,961 | 42.5 % |
| 5 | 15,709 | 67.8 % |
| 6 | 8,128 | 86.5 % |
| 7 | 8,131 | 97.5 % |
| 8 | 219 | 100.0 % |
- Facilities with
has_sentinel_visible_river = True: 59,568 / 160,576 (37.1 %) - Facilities where the closest reach is visible: 23,507 / 160,576 (14.6 %)
Lower-order rates (~20–25 %) are driven by upstream/downstream propagation: a headwater facility may drain into a wider river within the 10 km trace window.
License
CC-BY-4.0. See source datasets for their respective licenses.
Citation
If you use this dataset, please cite the source datasets:
- Lehner, B., Grill G. (2013): Global river hydrography and network routing: baseline data and new approaches to study the world's large river systems. Hydrological Processes, 27(15): 2171–2186.
- European Environment Agency (EEA) Industrial Emissions Database
- Copernicus EU-Hydro River Network Database