The Air Quality KPI provides metrics on the concentration of atmospheric pollutants in the study area, based on the variable selected by the user. The indicator enables monitoring of exposure to primary and secondary pollutants, comparison with international regulatory standards (WHO Air Quality Guidelines, 2021; EEA Air Quality in Europe, 2023), and analysis of daily trends and average values for the selected period.
Air pollution is recognised as one of the primary risk factors for human health and biodiversity: the WHO estimates that 99% of the world's population lives in areas with air quality below recommended limits. Ecologically, high levels of NOx, O3, and SO2 cause soil acidification, eutrophication, and direct damage to vegetation.
The KPI covers seven pollutant variables — carbon monoxide (CO), formaldehyde (HCHO), methane (CH4), nitrogen dioxide (NO2), ozone (O3), sulphur dioxide (SO2), and UV aerosol index — and includes both European AQI and US AQI for regulatory comparison. Separate satellite-derived map layers provide high-resolution spatial distribution for each pollutant, plus a static PM2.5 concentration layer.
ESRS alignment: E1.
For each selected pollutant variable, the system computes:
Data are sourced from the Open-Meteo Air Quality API, which integrates outputs from the CAMS (Copernicus Atmosphere Monitoring Service) atmospheric model at approximately 11 km spatial resolution, with temporal coverage from 2013 to the present and hourly updates.
The satellite map layers for individual pollutants (NO2, O3, SO2, CO, HCHO, CH4, UV aerosol index) are produced separately from Sentinel-5P imagery via Google Earth Engine at native resolution of approximately 1,113 m. The PM2.5 map layer uses a separate static dataset from Resource Watch (2018).
Line Chart. A horizontally scrollable time series chart displaying daily pollutant concentration values for the selected variable over the chosen period.
Purpose: To answer the question "How does the concentration of this pollutant change day by day at my site?" and to identify temporal trends, seasonal peaks, and anomalies.
Description: The section is titled "Air quality" with the sub-topic badge "E1". A wind icon appears next to the title. The user selects a pollutant variable from a dropdown (carbon monoxide, formaldehyde, methane, nitrogen dioxide, ozone, sulphur dioxide, UV aerosol index, European AQI, or US AQI). A summary line below the dropdown shows the minimum, average, and maximum values for the selected period. The chart area displays the daily concentration as a continuous line, with the x-axis showing dates and the y-axis showing the pollutant concentration in its respective unit. The chart is horizontally scrollable when the time period is long, with left/right navigation arrows.
How it's calculated: Each point on the chart represents the daily mean concentration for the selected pollutant at the site coordinates, sourced from the Open-Meteo Air Quality API (CAMS model). The summary statistics (min, avg, max) are computed across all daily values in the period. When European AQI or US AQI is selected, the chart shows the composite index value rather than a single pollutant concentration.
Note: For most pollutants (CO, HCHO, CH4, NO2, SO2, UV aerosol index), this indicator is inverted — lower concentrations indicate better air quality. Ozone is the exception: lower ozone values do not necessarily indicate better conditions, as the reading represents total column ozone including the protective stratospheric layer.
Interpretation example:
If nitrogen dioxide is selected and the chart shows values consistently below 0.00003 mol/m2 (grade A), the site has very low NO2 exposure — typical of rural areas far from traffic and industrial sources. If values regularly spike above 0.0001 mol/m2 (grade D), the site is subject to significant urban or industrial NO2 pollution.
Line Chart. A chart showing the number of days on which PM2.5 and PM10 concentrations exceeded the EU regulatory limits, based on PollyX IoT sensor data when available.
Purpose: To answer the question "How often does particulate matter at my site exceed the legal limits set by EU Directive 2008/50/EC?"
Description: The chart displays PM threshold exceedance counts. The PM2.5 threshold is 25 ug/m3 and the PM10 threshold is 40 ug/m3, as defined by EU Directive 2008/50/EC. A horizontal line marks each threshold. The chart is horizontally scrollable and includes navigation arrows.
How it's calculated: The system counts days where the daily mean concentration of PM2.5 or PM10 exceeded the regulatory threshold. PM data come from the PollyX IoT sensor when installed at the site; if no sensor is present, this element is not displayed.
Interpretation example:
If the chart shows 45 exceedance days for PM10 in a year, the site has exceeded the EU daily limit on roughly 12% of days — indicating a moderate particulate pollution problem that may warrant mitigation measures such as increased green buffer zones.
Assessment Sidebar Row. A grade row in the Assessment sidebar navigation showing the overall Air Quality score as a letter grade (A through E).
Purpose: To provide a quick, at-a-glance quality rating for air quality within the Risks category of the assessment sidebar.
Description: The sidebar row displays "Air quality" with the sub-topic code "E1" and a letter grade badge (A–E) coloured according to the quality level. Clicking the row scrolls to the Air quality section in the main content area.
How it's calculated: The letter grade is derived from the quality level thresholds applied to the primary pollutant variable. The grade aggregates across the monitored pollutants using the A–E scale defined by the platform's quality ranges.
Legend:
| Level | Color | Meaning |
|---|---|---|
| A | ■ #00A67A | Excellent air quality — pollutant concentrations well below concern thresholds |
| B | ■ #00DF80 | Good air quality — low pollutant levels |
| C | ■ #FFD21E | Moderate air quality — some pollutant levels approaching concern thresholds |
| D | ■ #FF8B16 | Poor air quality — elevated pollutant concentrations |
| E | ■ #FF367F | Critical air quality — pollutant concentrations significantly above concern thresholds |
Interpretation example:
If the sidebar shows grade B (light green), the site has generally good air quality with pollutant concentrations in the low range. A grade D (orange) would signal elevated pollution levels requiring attention.
Map Layer. An interactive map overlay showing the spatial distribution of tropospheric nitrogen dioxide (NO2) concentration derived from Sentinel-5P satellite data.
Purpose: To provide a spatially resolved view of NO2 pollution across the site and surrounding area, identifying emission hotspots from traffic and industrial sources.
Description: When the "Nitrogen Dioxide" layer chip is selected in the map panel, the Sentinel-5P NO2 raster composite is displayed over the base map. The legend panel shows the pollutant name and a continuous colour gradient bar. The colour scale adjusts dynamically to the data range of each image.
How it's calculated: The raster is derived from the Sentinel-5P L3 NO2 product (tropospheric column number density in mol/m2), processed through bilinear resampling at 100 m scale and temporal compositing over the selected period.
Note: This indicator is inverted — lower values indicate better conditions.
Legend: The map uses a continuous nipy_spectral colormap. The scale auto-adjusts to the image data range (no fixed bounds).
Interpretation example:
If the map shows intense warm colours over a motorway corridor and cool colours over an adjacent forest, the spatial contrast reveals the localised impact of traffic emissions on NO2 levels.
Map Layer. An interactive map overlay showing the total column ozone (O3) concentration derived from Sentinel-5P satellite data.
Purpose: To visualise the spatial distribution of atmospheric ozone across the site and surrounding area.
Description: When the "Ozone" layer chip is selected in the map panel, the Sentinel-5P O3 raster composite is displayed over the base map. The legend panel shows the pollutant name and a continuous colour gradient bar.
How it's calculated: The raster is derived from the Sentinel-5P L3 O3 product (total column number density in mol/m2), processed through bilinear resampling at 100 m scale and temporal compositing over the selected period.
Legend: The map uses a continuous nipy_spectral colormap. The scale auto-adjusts to the image data range.
Interpretation example:
If the map shows relatively uniform ozone values across the site (around 0.13 mol/m2), this indicates normal stratospheric ozone coverage. Significant spatial variation may indicate local tropospheric ozone formation from photochemical reactions involving NOx and VOCs.
Map Layer. An interactive map overlay showing the spatial distribution of sulphur dioxide (SO2) concentration derived from Sentinel-5P satellite data.
Purpose: To identify sources of SO2 emissions such as industrial facilities and volcanic activity in and around the site.
Description: When the "Sulphur Dioxide" layer chip is selected in the map panel, the Sentinel-5P SO2 raster composite is displayed over the base map. The legend panel shows the pollutant name and a continuous colour gradient bar.
How it's calculated: The raster is derived from the Sentinel-5P L3 SO2 product (column number density in mol/m2), processed through bilinear resampling at 500 m scale and temporal compositing over the selected period.
Note: This indicator is inverted — lower values indicate better conditions.
Legend: The map uses a continuous nipy_spectral colormap. The scale auto-adjusts to the image data range.
Interpretation example:
If the map shows elevated SO2 values concentrated around an industrial zone and negligible values over surrounding agricultural land, the spatial pattern confirms localised industrial emissions as the primary SO2 source.
Map Layer. An interactive map overlay showing the spatial distribution of carbon monoxide (CO) concentration derived from Sentinel-5P satellite data.
Purpose: To visualise CO pollution patterns across the site and surrounding area, identifying combustion-related emission sources.
Description: When the "Carbon Monoxide" layer chip is selected in the map panel, the Sentinel-5P CO raster composite is displayed over the base map. The legend panel shows the pollutant name and a continuous colour gradient bar.
How it's calculated: The raster is derived from the Sentinel-5P L3 CO product (column number density in mol/m2), processed through bilinear resampling at 100 m scale and temporal compositing over the selected period.
Note: This indicator is inverted — lower values indicate better conditions.
Legend: The map uses a continuous nipy_spectral colormap. The scale auto-adjusts to the image data range.
Interpretation example:
If the map shows higher CO values along urban corridors and lower values over vegetated areas, the pattern reflects incomplete combustion emissions from traffic and heating systems concentrated in built-up zones.
Map Layer. An interactive map overlay showing the spatial distribution of tropospheric formaldehyde (HCHO) concentration derived from Sentinel-5P satellite data.
Purpose: To visualise HCHO distribution across the site, which serves as an indicator of volatile organic compound (VOC) emissions from vegetation, fires, and industrial activity.
Description: When the "Formaldehyde" layer chip is selected in the map panel, the Sentinel-5P HCHO raster composite is displayed over the base map. The legend panel shows the pollutant name and a continuous colour gradient bar.
How it's calculated: The raster is derived from the Sentinel-5P L3 HCHO product (tropospheric column number density in mol/m2), processed through bilinear resampling at 100 m scale and temporal compositing over the selected period.
Note: This indicator is inverted — lower values indicate better conditions.
Legend: The map uses a continuous nipy_spectral colormap. The scale auto-adjusts to the image data range.
Interpretation example:
If the map shows elevated HCHO values over a densely forested area during summer, the pattern likely reflects biogenic VOC emissions from vegetation rather than anthropogenic pollution — a natural process that increases during warm months.
Map Layer. An interactive map overlay showing the spatial distribution of methane (CH4) concentration derived from Sentinel-5P satellite data.
Purpose: To identify methane emission sources such as agriculture, landfills, and fossil fuel extraction around the site.
Description: When the "Methane" layer chip is selected in the map panel, the Sentinel-5P CH4 raster composite is displayed over the base map. The legend panel shows the pollutant name and a continuous colour gradient bar.
How it's calculated: The raster is derived from the Sentinel-5P L3 CH4 product (column-averaged dry-air mixing ratio in ppb), processed through bilinear resampling at 100 m scale and temporal compositing over the selected period.
Note: This indicator is inverted — lower values indicate better conditions.
Legend: The map uses a continuous nipy_spectral colormap. The scale auto-adjusts to the image data range.
Interpretation example:
If the map shows a methane hotspot of 1,950 ppb over a landfill site while surrounding areas show 1,850 ppb, the 100 ppb differential confirms the landfill as a significant local methane source.
Map Layer. An interactive map overlay showing the spatial distribution of the UV aerosol index derived from Sentinel-5P satellite data.
Purpose: To detect and monitor absorbing aerosol events such as desert dust transport, wildfire smoke, and volcanic ash plumes across the site and surrounding area.
Description: When the "UV Aerosol Index" layer chip is selected in the map panel, the Sentinel-5P UV aerosol index raster composite is displayed over the base map. The legend panel shows the index name and a continuous colour gradient bar.
How it's calculated: The raster is derived from the Sentinel-5P L3 absorbing aerosol index product, processed through bilinear resampling at 100 m scale and temporal compositing over the selected period. The index is dimensionless and indicates the presence of UV-absorbing aerosols at altitude.
Note: This indicator is inverted — lower values indicate better conditions (fewer absorbing aerosols).
Legend: The map uses a continuous nipy_spectral colormap. The scale auto-adjusts to the image data range.
Interpretation example:
If the map shows UV aerosol index values above 2.0 across the entire site, this may indicate a Saharan dust intrusion event or nearby wildfire smoke — conditions that reduce air quality and can affect solar radiation reaching the ground.
Map Layer. An interactive map overlay showing the annual mean concentration of fine particulate matter (PM2.5) at ground level, derived from a static 2018 dataset.
Purpose: To provide a spatial overview of long-term PM2.5 exposure levels across the site and surrounding area, for comparison against WHO guidelines.
Description: When the "PM2.5 Air Quality" layer chip is selected in the map panel, the PM2.5 concentration raster is displayed over the base map. The legend panel shows the title and a colour gradient bar from green (clean) to dark red (polluted).
How it's calculated: The raster uses the Resource Watch global PM2.5 concentration dataset (2018, static). Values are expressed in ug/m3. The WHO guideline for annual mean PM2.5 is 5 ug/m3.
Legend: A discrete colour scale from green (low) to dark red (high), with a fixed range of 0 to 50 ug/m3.
| PM2.5 (ug/m3) | Color | Meaning |
|---|---|---|
| 0 — 5 | ■ #1a9850 | Very clean air; meets WHO guideline |
| 5 — 10 | ■ #91cf60 | Clean air; below most regulatory limits |
| 10 — 25 | ■ #fee08b | Moderate; exceeds WHO guideline |
| 25 — 35 | ■ #fc8d59 | Unhealthy for sensitive groups |
| 35 — 45 | ■ #d73027 | Unhealthy; exceeds EU limits |
| 45 — 50 | ■ #a50026 | Very unhealthy; severe pollution |
Interpretation example:
If the map shows yellow-orange colours (15–30 ug/m3) over the site, the annual PM2.5 concentration exceeds the WHO guideline of 5 ug/m3 by a factor of 3–6, indicating moderate-to-poor long-term air quality that may affect human health and sensitive ecosystems.
| Source | Provider | Coverage | Resolution | Period |
|---|---|---|---|---|
| Open-Meteo Air Quality API (CAMS) | Open-Meteo / Copernicus | Global | ~11 km | 2013 — present |
| Sentinel-5P L3 NO2 | ESA / Copernicus | Global | ~1,113 m | 2018-06-28 — present |
| Sentinel-5P L3 O3 | ESA / Copernicus | Global | ~1,113 m | 2018-09-08 — present |
| Sentinel-5P L3 SO2 | ESA / Copernicus | Global | ~1,113 m | 2018-12-05 — present |
| Sentinel-5P L3 CO | ESA / Copernicus | Global | ~1,113 m | 2018-06-28 — present |
| Sentinel-5P L3 HCHO | ESA / Copernicus | Global | ~1,113 m | 2018-12-05 — present |
| Sentinel-5P L3 CH4 | ESA / Copernicus | Global | ~1,113 m | 2019-02-08 — present |
| Sentinel-5P L3 UV Aerosol Index | ESA / Copernicus | Global | ~1,113 m | 2018-07-04 — present |
| Resource Watch PM2.5 Concentration | Resource Watch | Global | ~10 km | 2018 (static) |
The time series data are sourced from the Open-Meteo Air Quality API, which integrates the CAMS atmospheric model. For each pollutant variable, the API returns hourly concentration values at the site coordinates. The system aggregates these to daily means and computes period statistics (minimum, average, maximum). The European AQI and US AQI are composite indices derived from multiple pollutant concentrations following their respective regulatory formulas.
The satellite map layers for individual pollutants are produced from Sentinel-5P Level 3 data via Google Earth Engine. The processing pipeline for each pollutant map layer follows these steps:
The PM2.5 map layer uses a separate static dataset from Resource Watch (2018), not the Open-Meteo API. Values are expressed in ug/m3 on a fixed 0–50 scale.