Last decades have seen increasing consensus towards the issue of climate change and rising awareness of the implied responsibility of human activity. With growing global warming, extreme climate events like heat waves have increased in duration, frequency and intensity leading to higher heat-related morbidity and mortality rates. In this context, heat vulnerability assessments play an important role supporting decision-makers in implementing targeted mitigation and prevention actions. With this motivation, this work develops a heat vulnerability index by means of the Composite Indicator techniques to depict heat vulnerability in the Friuli Venezia Giulia region at the census tract level. The results show that heat vulnerability follows a spatial pattern, where most vulnerable census tracts are located in urbanised and densely populated areas, lower risk is observed in rural areas and lowest danger in mountainous areas. The Performance Interval approach confirms that these results do not depend on the aggregation method used to construct the index.
The Construction of a Heat Vulnerability Index by Means of the Composite Indicator Approach: A Case Study for Friuli Venezia Giulia Region, Italy
Pagani L.
;Habus A.
2024-01-01
Abstract
Last decades have seen increasing consensus towards the issue of climate change and rising awareness of the implied responsibility of human activity. With growing global warming, extreme climate events like heat waves have increased in duration, frequency and intensity leading to higher heat-related morbidity and mortality rates. In this context, heat vulnerability assessments play an important role supporting decision-makers in implementing targeted mitigation and prevention actions. With this motivation, this work develops a heat vulnerability index by means of the Composite Indicator techniques to depict heat vulnerability in the Friuli Venezia Giulia region at the census tract level. The results show that heat vulnerability follows a spatial pattern, where most vulnerable census tracts are located in urbanised and densely populated areas, lower risk is observed in rural areas and lowest danger in mountainous areas. The Performance Interval approach confirms that these results do not depend on the aggregation method used to construct the index.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.