Query historical climate and air quality data for a geographic region.

Returns Copernicus CAMS reanalysis (NO₂, PM2.5, PM10, O₃) and/or ECMWF ERA5 meteorological data (temperature, precipitation, wind, boundary layer height) for any location on Earth.

Args: lat_min: Southern boundary latitude (decimal degrees, e.g. 48.8) lat_max: Northern boundary latitude (decimal degrees, e.g. 49.0) lon_min: Western boundary longitude (decimal degrees, e.g. 2.2) lon_max: Eastern boundary longitude (decimal degrees, e.g. 2.5) time_start: Start of the period, e.g. "2022-01-01" or "2022-01" time_end: End of the period, e.g. "2023-12-31" or "2023-12" variables: Comma-separated list of variables to query. Air quality: no2, pm2p5, pm10, o3. Meteorology: era5_t2m (2m temperature), era5_tp (precipitation), era5_blh (boundary layer height), era5_u10, era5_v10 (wind). Default: "no2" aggregate: Time aggregation — "hourly", "daily", "monthly", "seasonal", or "trend" (OLS slope per year). Default: "monthly" format: Output format — "csv" (rows of data) or "stats" (summary: min/max/mean). Default: "csv"

Returns: CSV data or stats summary depending on the format argument. Credits used are shown in the response metadata.

Examples: - Air quality in Paris 2022: lat_min=48.8, lat_max=49.0, lon_min=2.2, lon_max=2.5, time_start="2022-01", time_end="2022-12", variables="no2,pm2p5" - 5-year NO₂ trend for London: aggregate="trend", time_start="2020-01", time_end="2024-12"

Query climate data for a single point location (snaps to nearest grid cell).

Convenience wrapper around query_climate for point queries. Use this when you have a specific address or coordinate rather than a bounding box region. The coordinate is snapped to the nearest CAMS 0.1° grid cell centre.

Args: lat: Latitude in decimal degrees (e.g. 48.8566 for Paris) lon: Longitude in decimal degrees (e.g. 2.3522 for Paris) time_start: Start date, e.g. "2022-01" or "2022-01-01" time_end: End date, e.g. "2024-12" or "2024-12-31" variables: Comma-separated variable names. Default: "no2,pm2p5,pm10" aggregate: "hourly", "daily", "monthly", "seasonal", or "trend"

Returns: CSV with time series data at the nearest grid cell.

Estimate the credit cost of a climate query before running it.

Use this before large queries (multi-year, large bounding box) to check the cost. Returns the number of credits that would be consumed and an estimated row count, without actually running the query.

Args: lat_min: Southern boundary latitude lat_max: Northern boundary latitude lon_min: Western boundary longitude lon_max: Eastern boundary longitude time_start: Start date, e.g. "2020-01" time_end: End date, e.g. "2024-12" variables: Comma-separated variable names

Returns: Estimated credit cost and row count.

Convert a street address to coordinates (forward geocoding).

Resolves any address worldwide to a latitude/longitude pair using the Jiskta geocoding index (113M housenumbers, global coverage).

Args: address: Free-form address string, e.g. "10 Downing Street, London" or "Eiffel Tower, Paris" or "Potsdamer Platz 1, Berlin, 10785, DE"

Returns: JSON with lat, lon, confidence score (0–1), and matched address components (street, city, postcode, country). confidence=1.0 means exact housenumber match; confidence=0.7 means street centroid; confidence=0.5 means postcode centroid.

Convert coordinates to a street address (reverse geocoding).

Args: lat: Latitude in decimal degrees lon: Longitude in decimal degrees

Returns: JSON with nearest address: street, housenumber, city, postcode, country.

Get administrative region and water risk context for a coordinate.

Returns the NUTS3 administrative region (for EU locations), WRI Aqueduct 4.0 water risk scores, and the nearest E-PRTR industrial facility within 5 km (if any). Useful for site screening and CSRD/ESRS preliminary assessment.

Args: lat: Latitude in decimal degrees lon: Longitude in decimal degrees

Returns: JSON with: - nuts3_id, nuts3_name, country (EU only) - water_stress: bws (baseline water stress), bwd (water depletion), rfr (riverine flood risk), drr (drought risk) — scored 1–5 where 1=Low, 5=Extremely High - nearest_facility: closest industrial facility within 5 km (if any)

Get WRI Aqueduct 4.0 water risk scores for a geographic region.

Returns water stress, depletion, flood risk, and drought risk for every 0.1° grid cell in the bounding box. Useful for CSRD ESRS E3-1 §27 (water stress) and E3-3 §38 (flood/drought risk) portfolio screening.

Scores: 1=Low, 2=Low-Medium, 3=Medium-High, 4=High, 5=Extremely High. Source: WRI Aqueduct 4.0 (2023). No credits consumed.

Args: lat_min: Southern boundary latitude lat_max: Northern boundary latitude lon_min: Western boundary longitude lon_max: Eastern boundary longitude Max bounding box: 50°×50°

Returns: JSON array of grid cells with bws, bwd, rfr, drr scores and labels.

Find E-PRTR industrial facilities near a location.

Searches the European Pollutant Release and Transfer Register (E-PRTR) database of ~97,000 verified industrial facilities in the EU. Returns facilities sorted by distance with their sector, annual NOₓ, PM10, PM2.5, and CO₂ emissions.

Useful for CSRD ESRS E2-9 §55 industrial proximity assessment.

Args: lat: Latitude of the site location lon: Longitude of the site location radius_km: Search radius in kilometres (default 10, max 500) max_results: Maximum number of facilities to return (default 20)

Returns: JSON array of facilities with name, sector, distance, and available emission data.

Check which months of climate data are available.

Returns the full data availability index — which months have been downloaded and what quality tier they are (validated reanalysis, interim reanalysis, or NRT). Use this to understand what date ranges are available before running a query.

No API key required, no credits consumed.

Returns: JSON with coverage by pollutant and month, including data type and download timestamp.

Aggregate raster climate data to administrative regions (NUTS3 or country).

Performs a spatial join — takes one or more raster datasets and computes the mean value for each NUTS3 region or country that overlaps the bounding box. Returns a table of regions with mean values per dataset.

Useful for regional comparison, portfolio screening, or joining climate data with official statistics by administrative area.

Args: lat_min: Southern boundary latitude lat_max: Northern boundary latitude lon_min: Western boundary longitude lon_max: Eastern boundary longitude time_start: Start date, e.g. "2022-01-01" time_end: End date, e.g. "2022-12-31" datasets: List of dataset source names to aggregate. Options: "cams_no2", "cams_pm2p5", "cams_pm10", "cams_o3", "era5_t2m", "era5_tp", "era5_blh", "era5_u10", "era5_v10", "viirs_radiance", "odiac_co2", "ghsl_pop", "ghsl_built", "aqueduct_bws", "aqueduct_bwd", "aqueduct_rfr", "aqueduct_drr" resolution: "nuts3" (EU administrative regions) or "country" (global)

Returns: JSON with a list of regions, each containing the mean value of each requested dataset. Also includes region name, country, and cell count.