The heat stress risk measures the physiological discomfort from heat on the human body, beyond mere air temperature. It is estimated with the Universal Thermal Climate Index (UTCI), the "perceived temperature", counting each year the days that exceed the heat-stress thresholds: the more days with strong, very strong or extreme stress, the higher the risk.
Indicator. Universal Thermal Climate Index (UTCI), in °C: a human biometeorology index that integrates air temperature, humidity, wind and radiation into a single "perceived temperature".
Data. UTCI from the Copernicus Climate Data Store (CDS); daily series (the classification uses fixed UTCI thresholds, without a historical baseline). Scenarios: SSP1-2.6 / SSP2-4.5 / SSP3-7.0 / SSP5-8.5.
Calculation. For each scenario and year the days are counted by stress band: extreme stress = UTCI ≥ 46 °C; very strong = 38 ≤ UTCI < 46 °C; strong = 32 ≤ UTCI < 38 °C. The combination of the three counts determines the level.
Thresholds → level A–F.
• F: extreme-days > 5 or very-strong > 20
• E: extreme > 0 or very-strong > 10
• D: very-strong > 0 or strong > 30
• C: strong > 10
• B: strong > 0
• A: otherwise.
The day counts that separate the classes (extreme above 5 and above 0; very strong above 20, above 10 and above 0; strong above 30, above 10 and above 0) are a xNatura choice without a published source; the UTCI bands at 32, 38 and 46 °C are those of the UTCI heat stress scale.
From physical to impact. The physical level (A–F) is combined with the production process's sensitivity through the risk matrix (6 physical levels by 5 sensitivity bands) → impact level. The euro amount of this risk is the one described in the "Production damage" paragraph (Version 2026): the damage factor per class of Version 2025 is no longer used for this risk.
Production damage. Heat does not damage the building but slows down the people who work: the working hours lost and their value are estimated, in euro per employee per year (multiplied by the site's employees). It is the gross yearly cost of heat: it also counts the hours lost in today's climate, not only the extra hours due to climate change.
• Hours lost: for every working hour (8-12 and 13-17, Monday to Friday) of the years 2015-2024 the indoor or shade WBGT is computed from hourly ERA5 temperature and humidity (Bernard formula recommended by Lemke and Kjellstrom 2012, Stull 2011 wet bulb), and the share of the hour lost with the Kjellstrom et al. 2018 functions and the ILO 2019 cut-offs (losses below 1% of an hour are not counted, at most 90% of the hour is lost; curve parameters from Parsons et al. 2021 and Scientific Reports 2025), by the ILO 2019 work intensity: agriculture and construction 400 W, industry 300 W, services 200 W, from the sector of the site's production processes (without processes, half industry and half services). Basis of the hours: published source.
• Future: the warming of the CMIP6 scenario (mean of the models over the 20 years around the year) that ERA5 does not show yet is added to the hourly temperatures; never less than today's climate.
• Euro: share of hours lost × yearly value added per employed person of the country and sector (Eurostat in Europe, for each country the latest year with the sector detail, real estate excluded, sectors with fewer than 1,000 workers use the whole economy; outside Europe World Bank value added divided by ILO employment, whole economy, or GDP in the 8 countries where the World Bank publishes no value added). Basis: "published source", because ILO 2019 turns the hours lost into money the same way (equivalent full-time jobs lost × GDP per worker); the one difference, stated, is the sector's value added per employed person in place of GDP per worker.
The production damage of heat is counted only once, here: extreme heat and heat waves measure the same hours and carry no euro.
Simplifications: no air conditioning, no heat from the processes, fixed working hours.
Sources.
• [Copernicus Climate Data Store (CDS)](Copernicus Climate Data Store (CDS))
• [UTCI: Why another thermal index?](UTCI: Why another thermal index?)
• [Deriving the operational procedure for the Universal Thermal Climate Index (UTCI)](Deriving the operational procedure for the Universal Thermal Climate Index (UTCI))
• UTCI
• [The Universal Thermal Climate Index as an Operational Forecasting Tool of Human Biometeorological Conditions in Europe](The Universal Thermal Climate Index as an Operational Forecasting Tool of Human Biometeorological Conditions in Europe)
• [Hersbach et al. 2020, The ERA5 global reanalysis](Hersbach et al. 2020, The ERA5 global reanalysis)
• [Lemke and Kjellstrom 2012, Calculating workplace WBGT from meteorological data](Lemke and Kjellstrom 2012, Calculating workplace WBGT from meteorological data)
• [Stull 2011, Wet-bulb temperature from relative humidity and air temperature](Stull 2011, Wet-bulb temperature from relative humidity and air temperature)
• [Kjellstrom et al. 2018, Estimating population heat exposure and impacts on working people](Kjellstrom et al. 2018, Estimating population heat exposure and impacts on working people)
• [Parsons et al. 2021, Increased labor losses and decreased adaptation potential in a warmer world](Parsons et al. 2021, Increased labor losses and decreased adaptation potential in a warmer world)
• [Heat stress productivity loss constants by work intensity (Scientific Reports 2025)](Heat stress productivity loss constants by work intensity (Scientific Reports 2025))
• [ILO 2019, Working on a warmer planet](ILO 2019, Working on a warmer planet)
• [Eurostat, national accounts by industry (nama_10_a64)](Eurostat, national accounts by industry (nama_10_a64))
• [World Bank, gross value added at basic prices](World Bank, gross value added at basic prices)
• [ILOSTAT, employment (ILO modelled estimates)](ILOSTAT, employment (ILO modelled estimates)).
Indicator. Universal Thermal Climate Index (UTCI), in °C: a human biometeorology index that integrates air temperature, humidity, wind and radiation into a single "perceived temperature".
Data. UTCI from the Copernicus Climate Data Store (CDS); daily series (the classification uses fixed UTCI thresholds, without a historical baseline). Scenarios: SSP1-2.6 / SSP2-4.5 / SSP3-7.0 / SSP5-8.5.
Calculation. For each scenario and year the days are counted by stress band: extreme stress = UTCI ≥ 46 °C; very strong = 38 ≤ UTCI < 46 °C; strong = 32 ≤ UTCI < 38 °C. The combination of the three counts determines the level.
Thresholds → level A–F.
• F: extreme-days > 5 or very-strong > 20
• E: extreme > 0 or very-strong > 10
• D: very-strong > 0 or strong > 30
• C: strong > 10
• B: strong > 0
• A: otherwise.
The day counts that separate the classes (extreme above 5 and above 0; very strong above 20, above 10 and above 0; strong above 30, above 10 and above 0) are a xNatura choice without a published source; the UTCI bands at 32, 38 and 46 °C are those of the UTCI heat stress scale.
From physical to impact. The physical level (A–F) is combined with the production process's sensitivity through the risk matrix (6 physical levels by 5 sensitivity bands) → impact level. The euro amount of this risk is the one described in the "Production damage" paragraph (Version 2026): the damage factor per class of Version 2025 is no longer used for this risk.
Production damage. Heat does not damage the building but slows down the people who work: the working hours lost and their value are estimated, in euro per employee per year (multiplied by the site's employees). It is the gross yearly cost of heat: it also counts the hours lost in today's climate, not only the extra hours due to climate change.
• Hours lost: for every working hour (8-12 and 13-17, Monday to Friday) of the years 2015-2024 the indoor or shade WBGT is computed from hourly ERA5 temperature and humidity (Bernard formula recommended by Lemke and Kjellstrom 2012, Stull 2011 wet bulb), and the share of the hour lost with the Kjellstrom et al. 2018 functions and the ILO 2019 cut-offs (losses below 1% of an hour are not counted, at most 90% of the hour is lost; curve parameters from Parsons et al. 2021 and Scientific Reports 2025), by the ILO 2019 work intensity: agriculture and construction 400 W, industry 300 W, services 200 W, from the sector of the site's production processes (without processes, half industry and half services). Basis of the hours: published source.
• Future: the warming of the CMIP6 scenario (mean of the models over the 20 years around the year) that ERA5 does not show yet is added to the hourly temperatures; never less than today's climate.
• Euro: share of hours lost × yearly value added per employed person of the country and sector (Eurostat in Europe, for each country the latest year with the sector detail, real estate excluded, sectors with fewer than 1,000 workers use the whole economy; outside Europe World Bank value added divided by ILO employment, whole economy, or GDP in the 8 countries where the World Bank publishes no value added). Basis: "published source", because ILO 2019 turns the hours lost into money the same way (equivalent full-time jobs lost × GDP per worker); the one difference, stated, is the sector's value added per employed person in place of GDP per worker.
The production damage of heat is counted only once, here: extreme heat and heat waves measure the same hours and carry no euro.
Simplifications: no air conditioning, no heat from the processes, fixed working hours.
Sources.
• [Copernicus Climate Data Store (CDS)](Copernicus Climate Data Store (CDS))
• [UTCI: Why another thermal index?](UTCI: Why another thermal index?)
• [Deriving the operational procedure for the Universal Thermal Climate Index (UTCI)](Deriving the operational procedure for the Universal Thermal Climate Index (UTCI))
• UTCI
• [The Universal Thermal Climate Index as an Operational Forecasting Tool of Human Biometeorological Conditions in Europe](The Universal Thermal Climate Index as an Operational Forecasting Tool of Human Biometeorological Conditions in Europe)
• [Hersbach et al. 2020, The ERA5 global reanalysis](Hersbach et al. 2020, The ERA5 global reanalysis)
• [Lemke and Kjellstrom 2012, Calculating workplace WBGT from meteorological data](Lemke and Kjellstrom 2012, Calculating workplace WBGT from meteorological data)
• [Stull 2011, Wet-bulb temperature from relative humidity and air temperature](Stull 2011, Wet-bulb temperature from relative humidity and air temperature)
• [Kjellstrom et al. 2018, Estimating population heat exposure and impacts on working people](Kjellstrom et al. 2018, Estimating population heat exposure and impacts on working people)
• [Parsons et al. 2021, Increased labor losses and decreased adaptation potential in a warmer world](Parsons et al. 2021, Increased labor losses and decreased adaptation potential in a warmer world)
• [Heat stress productivity loss constants by work intensity (Scientific Reports 2025)](Heat stress productivity loss constants by work intensity (Scientific Reports 2025))
• [ILO 2019, Working on a warmer planet](ILO 2019, Working on a warmer planet)
• [Eurostat, national accounts by industry (nama_10_a64)](Eurostat, national accounts by industry (nama_10_a64))
• [World Bank, gross value added at basic prices](World Bank, gross value added at basic prices)
• [ILOSTAT, employment (ILO modelled estimates)](ILOSTAT, employment (ILO modelled estimates)).