Periodic Reporting for period 1 - ResCool (Resilient cooling towards climate change adaptation of cities and buildings)
Okres sprawozdawczy: 2021-09-01 do 2023-08-31
The adaptation of urban contexts to mitigate the effects of global warming is one of the most critically overlooked issues of our time. Without additional efforts, climate change will gradually increase extreme heat events, which will occur more often and last longer. Moreover, the impact of rising temperatures will be felt acutely in urban environments affected by the urban heat island (UHI) phenomenon, raising extreme temperatures by more than 5ºC in comparison with rural surroundings. If left unchecked, UHI will increase the likelihood of severe, pervasive and irreversible impacts of extreme heat on people and ecosystems, exacerbating the energy demand for cooling even more.
In response to this challenge, this research project aims to: develop a holistic and reliable methodology to predict the impact of climate change globally (objective 1); generate a diagnosis protocol to identify climate-related hazards, heat vulnerabilities and risks of urban contexts where interventions should be prioritised (objective 2); identify the best available sustainable cooling solutions to strengthen the adaptive capacity of buildings and cities (objective 3); and highlight advanced adaptation pathways to promote climate resilience of the built environment globally (objective 4).
The four objectives are structured into five work packages (WPs). The definition of holistic methodologies to evaluate heat impacts and identify heat vulnerabilities at different scales is defined in WP1. Data collection and generation at different scales and contexts in Europe and globally are addressed in WP2. This data analysis supports the climate risk assessment of countries, cities, and buildings in WP3. Then, a parametric analysis of conventional and advanced resilient cooling strategies is evaluated in WP4 to identify the best available pathways under climate change scenarios. Finally, the results support the development of advanced adaptation pathways to promote climate adaptation and resilience of cities and buildings.
In response to this challenge, this research project aims to: develop a holistic and reliable methodology to predict the impact of climate change globally (objective 1); generate a diagnosis protocol to identify climate-related hazards, heat vulnerabilities and risks of urban contexts where interventions should be prioritised (objective 2); identify the best available sustainable cooling solutions to strengthen the adaptive capacity of buildings and cities (objective 3); and highlight advanced adaptation pathways to promote climate resilience of the built environment globally (objective 4).
The four objectives are structured into five work packages (WPs). The definition of holistic methodologies to evaluate heat impacts and identify heat vulnerabilities at different scales is defined in WP1. Data collection and generation at different scales and contexts in Europe and globally are addressed in WP2. This data analysis supports the climate risk assessment of countries, cities, and buildings in WP3. Then, a parametric analysis of conventional and advanced resilient cooling strategies is evaluated in WP4 to identify the best available pathways under climate change scenarios. Finally, the results support the development of advanced adaptation pathways to promote climate adaptation and resilience of cities and buildings.
As a result of the ResCool project, the following tasks and contributions have been developed. They are divided into two groups targeting climate risk assessment (WP1-3) and climate risk mitigation (W4-5):
CLIMATE RISK ASSESSMENT:
WP1. Holistic evaluation workflow. Three holistic evaluation workflows have been proposed and validated at different climate scales to tackle extreme heat and climate change impacts: at global, city, and building scales.
At a global scale, a novel climate change modelling through volunteered distributed computing generated the highest combined (temporal/geographical) resolution of temperatures for global 1.5° and 2.0 ° scenarios. The climate data has been processed and obtained using the climateprediction.net (CPDN) climate simulation environment to run the HadAM4 Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre.
At the city scale, a novel open-source diagnostic procedure has been developed and validated to measure atmospheric urban heat islands at the highest spatiotemporal resolution using citizen weather data. Cities around the world can use this method to identify urban hot spots where climate adaptation should be prioritised.
At the building scale, a novel physic-driven numerical model was used to simulate and quantify the impact of urban climate and specific microclimates, such as inner courtyards, on building performance.
WP2. Data collection/generation. Different datasets have been generated and made open access at different scales (Global, City and Building).
At a global scale, the highest combined (temporal/geographical) resolution of temperatures for global 1.5° and 2.0 ° scenarios has been generated and published. The data involves large ensembles of global temperature for three climate scenarios: historical (2006-16), 1.5°C and 2.0°C above pre-industrial levels. Each scenario has 700 members of 6-hourly mean temperatures at a resolution of 0.833° ´ 0.556° (longitude ´ latitude) over the land surface.
At a city scale, the highest spatial resolution of the urban heat island mapping of London has been provided. This data supports the identification of vulnerable urban hot spots.
Finally, at the building scale, three different case studies (building archetypes) in Seville (Spain) were monitored under extreme heat events. This data helps to understand common building responses to extreme heat events.
WP3. Climate impacts. The impact of heat at different scales (global, city and building) has been evaluated, identifying heat vulnerabilities and risks.
On a global scale, the countries are more affected if the global mean temperature rise increases from 1.5 °C to 2.0 °C has been identified, which should prioritise climate adaptation policies.
At the city scale, the validation of the urban diagnosis method in London resulted in the identification of urban hot spots of the city where climate interventions should be prioritised.
At building scale, a novel data-based diagnostic approach was proposed and tested to identify heat vulnerabilities in buildings. The method validation identified common heat vulnerabilities of buildings in southern Spain.
CLIMATE RISK MITIGATION (OR CLIMATE ADAPTATION).
WP4. Adaptation measures. Conventional and advanced passive, low-energy and renewable cooling techniques and technologies have been evaluated to identify the best available cooling alternative according to different criteria, requirements, and climates. The studies have quantified the benefits of cooling techniques and technologies under different climates and operating conditions to identify synergies and trade-offs in climate adaptation.
WP5. Climate resilience actions. This work has focused on identifying the right steps in the right order to promote sustainable cooling and climate adaptation of the built environment globally.
This research has involved scientific publications, media dissemination (press releases, online webinars, videos, etc.), and policy impact (advisory meetings, inquiries, etc.).
CLIMATE RISK ASSESSMENT:
WP1. Holistic evaluation workflow. Three holistic evaluation workflows have been proposed and validated at different climate scales to tackle extreme heat and climate change impacts: at global, city, and building scales.
At a global scale, a novel climate change modelling through volunteered distributed computing generated the highest combined (temporal/geographical) resolution of temperatures for global 1.5° and 2.0 ° scenarios. The climate data has been processed and obtained using the climateprediction.net (CPDN) climate simulation environment to run the HadAM4 Atmosphere-only General Circulation Model (AGCM) from the UK Met Office Hadley Centre.
At the city scale, a novel open-source diagnostic procedure has been developed and validated to measure atmospheric urban heat islands at the highest spatiotemporal resolution using citizen weather data. Cities around the world can use this method to identify urban hot spots where climate adaptation should be prioritised.
At the building scale, a novel physic-driven numerical model was used to simulate and quantify the impact of urban climate and specific microclimates, such as inner courtyards, on building performance.
WP2. Data collection/generation. Different datasets have been generated and made open access at different scales (Global, City and Building).
At a global scale, the highest combined (temporal/geographical) resolution of temperatures for global 1.5° and 2.0 ° scenarios has been generated and published. The data involves large ensembles of global temperature for three climate scenarios: historical (2006-16), 1.5°C and 2.0°C above pre-industrial levels. Each scenario has 700 members of 6-hourly mean temperatures at a resolution of 0.833° ´ 0.556° (longitude ´ latitude) over the land surface.
At a city scale, the highest spatial resolution of the urban heat island mapping of London has been provided. This data supports the identification of vulnerable urban hot spots.
Finally, at the building scale, three different case studies (building archetypes) in Seville (Spain) were monitored under extreme heat events. This data helps to understand common building responses to extreme heat events.
WP3. Climate impacts. The impact of heat at different scales (global, city and building) has been evaluated, identifying heat vulnerabilities and risks.
On a global scale, the countries are more affected if the global mean temperature rise increases from 1.5 °C to 2.0 °C has been identified, which should prioritise climate adaptation policies.
At the city scale, the validation of the urban diagnosis method in London resulted in the identification of urban hot spots of the city where climate interventions should be prioritised.
At building scale, a novel data-based diagnostic approach was proposed and tested to identify heat vulnerabilities in buildings. The method validation identified common heat vulnerabilities of buildings in southern Spain.
CLIMATE RISK MITIGATION (OR CLIMATE ADAPTATION).
WP4. Adaptation measures. Conventional and advanced passive, low-energy and renewable cooling techniques and technologies have been evaluated to identify the best available cooling alternative according to different criteria, requirements, and climates. The studies have quantified the benefits of cooling techniques and technologies under different climates and operating conditions to identify synergies and trade-offs in climate adaptation.
WP5. Climate resilience actions. This work has focused on identifying the right steps in the right order to promote sustainable cooling and climate adaptation of the built environment globally.
This research has involved scientific publications, media dissemination (press releases, online webinars, videos, etc.), and policy impact (advisory meetings, inquiries, etc.).
The project has contributed to 11 open-access scientific articles, with one of them published in Nature Sustainability, 5 international conferences, 3 online webinars, 3 public datasets (CEDA, ORA, GitHub), 5 novel software and code in GitHub, 4 press releases (three of them in TheConversation) with coverage by more than 60 media journalists (Oxford Mail, Sky News, The Guardian, New Scientist, iNews, The Times, Daily Mail, etc.), 5 online videos (BBC Ideas, Network H+C, GCHU webinar, Podcast on Footprints Live, Build Up portal), many social media engagement (mainly in Twitter and Linkedin), dissemination activities in university (2 seminars) and schools (Science is Wanderful), and direct policy impact through written evidence, advisory meetings (UNEP, SSC, UK-GOV-DENZ, CIBSE, etc.), and policy briefs.
The three most important contributions are:
Miranda N, Lizana J, et al. (2023) Change in cooling degree days with global mean temperature rise increasing from 1.5º to 2.0ºC. Nature Sustainability. https://doi.org/10.1038/s41893-023-01155-z
Lizana J et al.(2023) Citizen data for global mapping of atmospheric urban heat islands. PRE-PRINT, 1–24. https://doi.org/10.21203/rs.3.rs-2924752/v1
Lizana J et al.(2022). Overcoming the incumbency and barriers to sustainable cooling. Buildings and Cities, 3(1), 1075–1097. https://doi.org/10.5334/bc.255
The three most important contributions are:
Miranda N, Lizana J, et al. (2023) Change in cooling degree days with global mean temperature rise increasing from 1.5º to 2.0ºC. Nature Sustainability. https://doi.org/10.1038/s41893-023-01155-z
Lizana J et al.(2023) Citizen data for global mapping of atmospheric urban heat islands. PRE-PRINT, 1–24. https://doi.org/10.21203/rs.3.rs-2924752/v1
Lizana J et al.(2022). Overcoming the incumbency and barriers to sustainable cooling. Buildings and Cities, 3(1), 1075–1097. https://doi.org/10.5334/bc.255