Micro-scale UHI risk assessment on the heat-health nexus within cities by looking at socio-economic factors and built environment characteristics: The Turin case study (Italy)

Ellena, Marta; Melis, Giulia; Zengarini, Nicolás; Gangi, Eduardo Di; Ricciardi, Giuseppe Kenneth; Mercogliano, Paola; Costa, Giuseppe

doi:10.1016/j.uclim.2023.101514

Cited by 25 publications

(4 citation statements)

References 43 publications

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“…Figure 2 shows the methodological approach used in the study and the key steps are summarized below. In order to achieve the final risk, we used the following procedure, which has been widely used in several studies [19,[26][27][28]: Concerning the climate analysis of the future, the variation in extreme precipitation indicators was performed using the high-resolution simulation (about 12 km) of different regional climate models (RCM) included in the EURO-CORDEX initiative [17,18]. The simulation considered was obtained according to the RCP 2.6, RCP 4.5, RCP 8.5 IPCC scenarios (i.e., multi-scenarios approach).…”

Section: Conceptual Approach For Quantifying Climate Risk For the Sel...mentioning

confidence: 99%

Climate-Risk Assessment Framework for Airports under Extreme Precipitation Events: Application to Selected Italian Case Studies

et al. 2023

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Extreme weather phenomena are increasing due to climate change and having a severe impact on critical infrastructure, including airports. In this context, conducting climate risk assessments is an essential step to implement appropriate adaptation strategies. In the present study, a climate-risk assessment framework is applied to evaluate the risk of extreme precipitation events for specific Italian airports: Malpensa, Bergamo, Linate, Fiumicino, Ciampino, Napoli, Catania, Palermo, and Cagliari. This analysis is based on the definition of risk as reported by Sixth Assessment Report of IPCC. The assessment of the climate hazard over the recent-past period (1981–2010) is evaluated through indicators developed from re-analysis data, using the Uncertainties in Ensemble of Regional Re-Analyses dataset are provided by Copernicus Climate Change Service. The expected climate variations are evaluated using an ensemble of high-resolution climate projections from the EURO-CORDEX initiative for the short- (2021–2050), medium- (2041–2070), and long-term future period (2071–2100), under RCP 2.6, RCP 4.5, and RCP 8.5 climate scenarios. The information related to exposure and vulnerability indicators are collected from official documents and website of selected airports, and are freely available. The final risk index provides elements allowing stakeholders to implement adaptation measures to increase their resilience.

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Section: Conceptual Approach For Quantifying Climate Risk For the Sel...mentioning

confidence: 99%

Climate-Risk Assessment Framework for Airports under Extreme Precipitation Events: Application to Selected Italian Case Studies

et al. 2023

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“…• building footprint extraction from point clouds (Wu et al, 2018;Buyukdemircioglu et al, 2022); • 3D building/city model generation (Lafarge and Mallet., 2012;Biljecki et al, 2015;Özdemir and Remondino, 2018); • photovoltaic potential estimation of building roof or other suitable areas (Nex et al, 2013;Giannelli et al, 2022); • urban heat island analysis and forecasting (Voelkel and Shandas, 2017;Bosch et al, 2021;Ellena et al, 2023); • urban tree mapping using hyperspectral and LiDAR data fusion (Dalponte et al, 2013;Ballanti et al, 2020); • derivation of urban ecological indexes (Darvishzadeh et al, 2009;Heiden et al, 2012;Sun et al, 2021).…”

Section: The Usage Dataset and Related Workmentioning

confidence: 99%

Multi-Modal Geospatial and Thematic Data to Foster Green Deal Applications

Beber,

Perda,

Takhtkeshha

et al. 2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The Urban Data Space for Green Deal - USAGE - project is founded by the European Union (EU) to support the green transition of cities. Within USAGE, a series of geospatial, thematic and other datasets have been newly acquired or created to test and evaluate solutions (i) to better understand issues and trends on how our planet and its climate are changing and (ii) to address the role that humans play in these changes, e.g., with behaviour adaptation and mitigation actions. The paper aims to provide some relevant datasets collected in two urban areas, reporting processing methodologies and applications of analysis-ready and decision-ready geospatial data. The shared data are unique urban datasets due to their resolutions and sensors type and could boost progresses of geospatial procedures to create and use data useful for climate change adaptation, renewable energy monitoring and management, etc.

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“…As the main habitat of human beings, cities are susceptible to more heat risks under the combined influence of rapid world urbanization and global climate changes [1][2][3]. Among these negative impacts caused by land cover and land use changes, the urban heat island (UHI) phenomenon, suggesting that urban areas have higher temperatures than the rural areas, has proven to produce a wide range of impacts on social-ecological issues, such as threatening public health, resulting in more energy costs from air conditioners, and causing severe urban air pollution [4][5][6][7]. It is projected that over two-thirds of the world's population will soon live in urban areas, indicating more people will be influenced by climate-related risks [8].…”

Section: Introductionmentioning

confidence: 99%

Comparing Characteristics of the Urban Thermal Environment Based on the Local Climate Zone in Three Chinese Metropolises

Su,

Yang,

et al. 2024

IJGI

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Urban landscape has important effects on urban climate, and the local climate zone (LCZ) framework has been widely applied in related studies. However, few studies have compared the relative contributions of LCZ on the urban thermal environment across different cities. Therefore, Beijing, Shanghai, and Shenzhen in China were selected to conduct a comparative study to explore the relationship between LCZ and land surface temperature (LST). The results showed that (1) both the composition and spatial configuration of LCZ had obvious differences among the three cities. Beijing had a higher area proportion of compact mid-rise and low-rise LCZ types. The spatial pattern of LCZ in Shenzhen was especially quite different from those of Beijing and Shanghai. (2) Shenzhen had the strongest summer surface urban heat island (UHI) intensity and the largest UHI region area. However, the proportion of urban cooling island areas was still the highest in Shenzhen. (3) Different LCZs showed significant LST differences. The largest LST difference between the LCZs reached 5.57 °C, 4.50 °C, and 12.08 °C in Beijing, Shanghai, and Shenzhen, respectively. Built-up LCZs had higher LSTs than other LCZ types. (4) The dominant driving LCZs on LST were different among these cities. The LST in Beijing was easily influenced by built-up LCZ types, while the cooling effects generated by LCZ G(water) were much stronger than built-up LCZs’ warming effects in Shanghai. These results indicated that the effect of the LCZ on LST had significant differences among LCZ types and across cities, and the dominant LCZs should be given more priority in future urban planning.

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Micro-scale UHI risk assessment on the heat-health nexus within cities by looking at socio-economic factors and built environment characteristics: The Turin case study (Italy)

Cited by 25 publications

References 43 publications

Climate-Risk Assessment Framework for Airports under Extreme Precipitation Events: Application to Selected Italian Case Studies

Climate-Risk Assessment Framework for Airports under Extreme Precipitation Events: Application to Selected Italian Case Studies

Multi-Modal Geospatial and Thematic Data to Foster Green Deal Applications

Comparing Characteristics of the Urban Thermal Environment Based on the Local Climate Zone in Three Chinese Metropolises

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