Dataset used in the study "Nationwide heat-related workability loss and adaptation measures: development of a geospatial tool to support work management in heat conditions"

This directory includes codes, input and output data of the study entitled “Nationwide heat-related workability loss and adaptation measures: development of a geospatial tool to support work management in heat conditions”.

The attached code allows to calculate the workability loss occurred in Italy for workers performing different metabolic rate tasks (moderate and high) in summer (from June to August) during the period 2007-2019.

According to the methodology implemented by Bröde et al. (2018), the workability loss was calculated in shade and sun conditions using hourly Wet Bulb Globe Temperature (WBGT) data obtained from downscaled procedure developed for Italy at 2.5 km spatial resolution (Capecchi et al., 2023).

The average workability loss was obtained within each Italian plain municipality areas filtered by elevation data (under 300 m a.s.l.), combining several information about geographical areas (northern, central, southern and island municipalities) and the distance from the coastline.

The input data are polygonal features (shapefile) of the Italian municipalities from the National Institute of Statistics (ISTAT, source: https://www.istat.it/en/).

The output data are the municipality datasets, including the geographical classification and the workability loss information averaged on a ten-day basis (decade) for various 8-hour working time slots (5am-1pm; 6am-2pm; 7am-3pm; 8am-4pm; 9am-5pm):  

For further information about the output data structure, please read the “description_output_data.pdf” file in the output data folder.

This work was funded by INAIL Research Plan 2022–2024 (ID 05), under Project WORKLIMATE 2.0 (Prot. N. 115715, April 18, 2023).

Contacts

Scientific coordinator, PhD Marco Morabito, e-mail: [e-mail]

References

Bröde, P., Fiala, D., Lemke, B., Kjellstrom, T. Estimated work ability in warm outdoor environments depends on the chosen heat stress assessment metric. Int J Biometeorol. 62(3):331-345 (2018). https://doi.org/10.1007/s00484-017-1346-9

Capecchi, V., Pasi, F., Gozzini, B., Brandini, C. A convection-permitting and limited area model hindcast driven by ERA5 data: precipitation performances in Italy. Climate Dynamics 61, 1411-1437 (2023). https://doi.org/10.1007/s00382-022-06633-2