Issue
Climatologie
Volume 20, 2023
Changement climatique : les territoires acteurs des trajectoires d’adaptation et de transition écologique
Article Number 6
Number of page(s) 17
DOI https://doi.org/10.1051/climat/202320006
Published online 24 October 2023
  • Abbasabadi, N., Ashayeri, J., 2019. Urban energy use modeling methods and tools: A review and an outlook, Building and environment, 161, 17, 106270. doi: 10.106/j.buildenv.2019.106270. [CrossRef] [Google Scholar]
  • ADEME, 2011. Diagnostic de vulnérabilité d’un territoire au changement climatique - Éléments méthodologiques tirés de l’expérience internationale. ADEME, Angers, p. 53 pages. [Google Scholar]
  • ADEME, 2017. Diagnostic de la surchauffe urbaine - Méthodes et Applications Territoriales. ADEME, Angers, 67 p. [Google Scholar]
  • Aghamolaei, R., Fallahpour, M., Mirzaei, P., 2021. Tempo- spatial thermal comfort analysis of urban heat island with coupling of CFD and building energy simulation. Energy and Buildings, 251, 111317, doi: 10.1016/j.enbuild.2021.111317. [CrossRef] [Google Scholar]
  • Akbari, H., Cartalis, C., Kolokotsa, D., Muscio, A., Pisello, A., Rossi, F., et al., 2016. Local climate change and urban heat island mitigation techniques - the state of the art. Journal of Civil Engineering and Management 22, 1, 1–16. doi: 10.3846/13923730.2015.1111934. [CrossRef] [Google Scholar]
  • Akbari, H., Kolokotsa, D., 2016. Three decades of urban heat islands and mitigation technologies research. Energy and Buildings, 133, 834–842, 10.1016/j.enbuild.2016.09.067. [CrossRef] [Google Scholar]
  • Aleksandrowicz, O., Vuckovic,M., Kiesel, K., Mahdavi, A., 2017. Current trends in urban heat island mitigation research: Observations based on a comprehensive research repository. Urban Climate, 21, 1–26. doi: 10.1016/j.uclim.2017.04.002. [CrossRef] [Google Scholar]
  • Allegrini, J., Carmeliet, J., 2017. Coupled CFD and building energy simulations for studying the impacts of building height topology and buoyancy on local urban microclimates. Urban Climate 21, 278–305, doi: 10.1016/j.uclim.2017.07.005. [CrossRef] [Google Scholar]
  • Allegrini, J., Carmeliet, J., 2018. Simulations of local heat islands in Zürich with coupled CFD and building energy models. Urban Climate, 24, 340–359, doi: 10.1016/j.uclim.2017.02.003. [CrossRef] [Google Scholar]
  • Alonso, L., Renard, F., 2020. A Comparative Study of the Physiological and Socio-Economic Vulnerabilities to Heat Waves of the Population of the Metropolis of Lyon (France) in a Climate Change Context. International Journal of Environmental Research and Public Health, 17, 3, 1004. Doi: 10.3390/ijerph17031004. [CrossRef] [Google Scholar]
  • Al-Yahyai, S., Charabi, Y., Gastli, A., 2010. Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment. Renewable and Sustainable Energy Reviews, 14, 9, 3192–3198. Doi: 10.1016/j.rser.2010.07.001. [CrossRef] [Google Scholar]
  • Ameer, B., Krarti, M., 2022. Review of Urban Heat Island and Building Energy Modeling Approaches. ASME Journal of Engineering for Sustainable Buildings and Cities, 3, 1. doi: 10.1115/1.4053677. [CrossRef] [Google Scholar]
  • Arnfield, A. (2003) Two decades of urban climate research: A review of turbulence, exchanges of energy and water and the urban heat island. International Journal of Climatology, 23, 26 pages. [CrossRef] [Google Scholar]
  • Bahi, H., Mastouri, H., Radoine, H., 2020. Review of methods for retrieving urban heat islands. Materials Today: Proceedings, 27, 3004–3009. Doi: 10.1016/j.matpr.2020.03.272. [CrossRef] [Google Scholar]
  • Benzerzour M., Masson V., Groleau D., Lemonsu A., 2011. Simulation of the urban climate variations in connection with the transformations of the city of Nantes since the 17th century. Building and Environment, 46, 8, 1545–1557. doi: https://doi.org./10.1016/j.buildenv.2011.01.014. [CrossRef] [Google Scholar]
  • Bernard J., Musy M., Marie H., 2020. Rafraîchissement des villes : Solutions existantes et pistes de recherche. ADEME, Éditions Paranthèses, 16 pages. [Google Scholar]
  • Bherwani H., Singh A., Kumar R., 2020. Assessment methods of urban microclimate and its parameters: A critical review to take the research from lab to land. Urban Climate, 34, 100690. doi: 10.1016/j.uclim.2020.100690. [CrossRef] [Google Scholar]
  • Bouyer J., Inard C., Musy M., 2011. Microclimatic coupling as a solution to improve building energy simulation in an urban context. Energy and buildings, 43, 1549–1559. doi: 10.1016/j.enbuild.2011.02.010. [CrossRef] [Google Scholar]
  • Brode P., Blazejczyk K., Fiala D., Havenith G., Holmér I., Jendritzky G. et al., 2013. The Universal Thermal Climate Index UTCI compared to ergonomics standards for assessing the thermal environment. Industrial Health, 51, 1, 16–24. doi: 10.2486/indhealth.2012-0098. [Google Scholar]
  • Brozovsky J., Radivojevic J., Simonsen A., 2022. Assessing the impact of urban microclimate on building energy demand by coupling CFD and building performance simulation. Journal of Building Engineering, 55, doi: 10.1016/j.jobe.2022.104681. [CrossRef] [Google Scholar]
  • Buchin O., Hoelscher M., Meier F., Nehls T., Ziegler F., 2016. Evaluation of the health-risk reduction potential of countermeasures to urban heat islands. Energy and Buildings, 114, 27–37. doi: 10.1016/j.enbuild.2015.06.038. [CrossRef] [Google Scholar]
  • Bueno B., Norford L., Pigeon G., Britter R., 2011. Combining a detailed building energy model with a physically-based Urban Canopy Model. Boundary-Layer Meteorology, 140, 3, 471–489. doi: 10.1007/s10546-011-9620-6. [CrossRef] [Google Scholar]
  • Bueno B., Norford L., Hidalgo J., Pigeon G., 2013. The urban weather generator. Journal of Building Performance Simulation, 6, 4, 269–281. doi: 10.1080/19401493.2012.718797. [CrossRef] [Google Scholar]
  • Chen F., Kusaka H., Tewari M., Bao J., Hirakuchi H., 2004. Utilizing the coupled WRF/LSM/URBAN modeling system with detailed urban classification to simulate the urban heat island phenomena over the greater Houston area. Fifth Symposium on the Urban Environment, American Meteorological Society, Vancouver B.C. Canada, 23–26 août 2004, 25, 9–11. [Google Scholar]
  • De Ridder K., Maiheu B., Lauwaet D., Daglis I., Keramitsoglou I., Kourtidis K. et al., 2017. Urban Heat Island intensification during hot spells—The case of Paris during the Summer of 2003. Urban Science, 1, 1, 3. doi: 10.3390/urbansci1010003. [Google Scholar]
  • De Groot-Reichwein M., Van Lammeren R., Goosen H., Koekoek A., Bregt A., Vellinga P., 2015. Urban heat indicator map for climate adaptation planning. Mitigation and Adaptation Strategies for Global Change, 23, 2, 169–185. doi: 10.1007/s11027-015-9669-5. [Google Scholar]
  • Delage Y., Taylor P., 1970. Numerical studies of heat island circulations. Boundary-Layer Meteorology, 1, 2, 201–226. doi: https://doi.org/10.1007/BF00185740. [CrossRef] [Google Scholar]
  • Diallo-Dudek J., Lacaze B., Comby J., 2015. Land surface temperature in the urban area of Lyon metropolis: A comparative study of remote sensing data and MesoNH model simulation. Joint Urban Remote Sensing Event (JURSE), 2015, 1–4. doi: 10.1109/JURSE.2015.7120528. [Google Scholar]
  • Douay N., 2013. La planification urbaine française : théories, normes juridiques et défis pour la pratique. L’Information géographique, 77, 3, 45–70. doi: 10.3917/lig.773.0045. [Google Scholar]
  • Dubreuil V., 2022. Le changement climatique en France illustré par la classification de Koppen. La Météorologie, 116, 037. doi: 10.37053/lameteorologie-2022-0012. [Google Scholar]
  • Dudhia J., 2014. A history of mesoscale model development. Asia-Pacific Journal of Atmospheric Sciences, 50, 1, 121–131. doi: https://doi.org/10.1007/s13143-014-0031-8. [CrossRef] [Google Scholar]
  • Fallmann J., Emeis S., Suppan P., 2014. Mitigation of urban heat stress - A modelling case study for the area of Stuttgart. Journal of the Geographical Society of Berlin, 144, 202–216. [Google Scholar]
  • Gao Z., Bresson R., Qu Y., Milliez M., de Munck C., Carissimo B., 2018. High resolution unsteady RANS simulation of wind, thermal effects and pollution dispersion for studying urban renewal scenarios in a neighborhood of Toulouse. Urban Climate, 23, 114–130. doi: 10.1016/j.uclim.2016.11.002. [CrossRef] [Google Scholar]
  • Gardes T., Schoetter R., Hidalgo J., Long N., Marqués E., Masson V., 2020. Statistical prediction of the nocturnal urban heat island intensity based on urban morphology and geographical factors - An investigation based on numerical model results for a large ensemble of French cities. Science of The Total Environment, 737, 139253. doi: 10.1016/j.scitotenv.2020.139253. [CrossRef] [Google Scholar]
  • Gobakis K., Kolokotsa D., Synnefa A., Saliari M., Giannopoulou K., Santamouris M., 2011. Development of a model for urban heat island prediction using neural network techniques. Sustainable Cities and Society, 1, 2, 104–115. doi: 10.1016/j.scs.2011.05.001. [CrossRef] [Google Scholar]
  • Grafakos S., Viero G., Reckien D., Trigg K., Viguie V., Sudmant A., et al., 2020. Integration of mitigation and adaptation in urban climate change action plans in Europe: A systematic assessment. Renewable and Sustainable Energy Reviews, 121, 109623. doi: 10.1016/j.rser.2019.109623. [CrossRef] [Google Scholar]
  • Gros A., Bozonnet E., Inard C., 2014. Cool materials impact at district scale - Coupling building energy and microclimate models. Sustainable Cities and Society, 13, 254–266. doi: 10.1016/j.scs.2014.02.002. [CrossRef] [Google Scholar]
  • Hamman P., 2011. Les échelles spatiales et temporelles de la « ville durable». Espaces et sociétés, 144–145, 1–2, 213–227, doi: 10.3917/esp.144.0213. [CrossRef] [Google Scholar]
  • Hidalgo J., 2014. L’intégration des enjeux climatiques dans la planification et l’aménagement urbains, un nouveau chantier de recherche interdisciplinaire, 5ème Congrés National Santé Environnement, Rennes, novembre 2014 [Google Scholar]
  • Hoppe P., 1999. The physiological equivalent temperature - a universal index for the biometeorological assessment of the thermal environment. International Journal of Biometeorology, 43, 2, 71–75. doi:10.1007/s004840050118. [CrossRef] [PubMed] [Google Scholar]
  • Hu Z., Yu B., Chen Z., Li T., Liu M., 2012. Numerical investigation on the urban heat island in an entire city with an urban porous media model. Atmospheric Environment, 47, 509–518. 10.1016/j.atmosenv.2011.09.064. [CrossRef] [Google Scholar]
  • Hulley M., 2012. The urban heat island effect: Causes and potential solutions. In Metropolitan Sustainability, Editions F. Zeman, Woodhead Publishing, 79-98, doi:10.1533/9780857096463.1.79. [CrossRef] [Google Scholar]
  • Hurlimann A., Moosavi S., Browne G., 2020. Urban planning policy must do more to integrate climate change adaptation and mitigation actions. Land Use Policy, 105188, doi: 10.1016/j.landusepol.2020.105188. [Google Scholar]
  • Imran H., Shammas M., Rahman A., Jacobs S., Ng A., Muthukumaran S., 2021. Causes, modeling and mitigation of Urban Heat Island : A review. Earth Sciences, 6, 10, 244–264. doi: 10.11648/j.earth.20211006.11. [CrossRef] [Google Scholar]
  • IPCC, 2022. Climate Change 2022: Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Pörtner, H., Roberts, D., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A. et al. (eds.).Cambridge University Press. Cambridge University Press, Cambridge, RU et New York, USA, 3056 pages. doi: 10.1017/9781009325844. [Google Scholar]
  • Janicke B., Milosevic D., Manavvi S., 2021. Review of user- friendly models to improve the urban micro-climate. Atmosphere, 12, 1291. doi: 10.3390/atmos12101294. [CrossRef] [Google Scholar]
  • Jin M., 2012. Developing an index to measure Urban Heat Island effect using satellite land skin temperature and land cover observations. Journal of Climate, 25, 18, 6193–6201. doi:10.1175/JCLI-D-11-00509.1. [CrossRef] [Google Scholar]
  • Kardinal J., Ignatius M., Hien W., Akbari H., 2019. Editorial: Urban heat island (UHI) and its mitigation through urban planning, design, and landscaping. Architectural science review, 1, 62, 2. doi: 10.1080/00038628.2019.1548095. [Google Scholar]
  • Kastendeuch P., Najjar G., Lacarrere P., Colin J., 2010. Modélisation de l’îlot de chaleur urbain à Strasbourg. Climatologie, 7, 21–37. doi:10.4267/climatologie.361. [CrossRef] [Google Scholar]
  • Kastendeuch P., Najjar G., 2015. Une simulation des interactions ville-atmosphère à différentes échelles : Application sur Strasbourg. Climatologie, 12, 44–64. doi: 10.4267/climatologie.1118. [CrossRef] [Google Scholar]
  • Kohler M., Tannier C., Blond N., Aguejdad R., Clappier A., 2017. Impacts of several urban-sprawl countermeasures on building (space heating) energy demands and urban heat island intensities. A case study. Urban climate, 19, 92–121. doi: 10.1016/j.uclim.2016.12.006. [CrossRef] [Google Scholar]
  • Kwak Y., Park C., Deal B., 2020. Discerning the success of sustainable planning: A comparative analysis of urban heat island dynamics in Korean new towns. Sustainable Cities and Society, 61, 102341, doi:10.1016/j.scs.2020.102341. [CrossRef] [Google Scholar]
  • Kwok Y., Ng E., 2021. Trends, topics, and lessons learnt from real case studies using mesoscale atmospheric models for urban climate applications in 2000–2019. Urban climate, 36, 100785, doi: 10.1016/j.uclim.2021.100785. [CrossRef] [Google Scholar]
  • Lambert M., Demazeux C., Gallafrio M., 2016. Climat urbain, énergie et droit de l’urbanisme - PLU(i). Rapport de présentation etPADD. Hal-01354282. [Google Scholar]
  • Lambert M., Hidalgo J., Masson V., 2019. Urbanisme & (micro-)climat : Outils et recommandation générales pour les documents de planification urbaine issus du projetMApUCE. Guide méthodologique, ANR France , 48 pages. [Google Scholar]
  • Le Mentec S., 2022. Impact de la végétalisation sur l’îlot de chaleur urbain et la pollution d’ozone: Quantification par une approche de modélisation à l’échelle d’un quartier. Thèse de l’Université Paris-Saclay, AgroParisTech, tel-03807318. [Google Scholar]
  • Lee D., Pietrzyk P., Donkers S., Liem V., Van Oostveen J., Montazeri S. et al., 2013. Modeling and observation of heat losses from buildings: The impact of geometric detail on 3D heat flux modeling, Towards Horizon 2020: Earth Observation and Social Perspectives, 33rd AERSel Symposium, Matera Italie, 3–6 juin 2013, 20. [Google Scholar]
  • Lee Y., Kim J., Yun G., 2016. The neural network predictive model for heat island intensity in Seoul. Energy and Buildings, 110, 353–361. doi: 10.1016/j.enbuild.2015.11.013. [CrossRef] [Google Scholar]
  • Lemonsu A., Viguié V., Daniel M., Masson V., 2015. Vulnerability to heat waves: Impact of urban expansion scenarios on urban heat island and heat stress in Paris (France). Urban Climate, 14, 586–605. doi:10.1016/j.uclim.2015.10.007. [CrossRef] [Google Scholar]
  • Lin P., Sin Yu Lau S., Qin H., Gou Z., 2017. Effects of urban planning indicators on urban heat island: A case study of pocket parks in high-rise high-density environment. Landscape and urban planning, 168, 48–60. doi:10.1016/j.landurbplan.2017.09.024. [CrossRef] [Google Scholar]
  • Marando F., Heris M.P., Zulian G., Udias A., Mentaschi L., Chrysoulakis N. et al., 2022. Urban heat island mitigation by green infrastructure in European Functional Urban Areas. Sustainable Cities and Society, 77, 103564. doi:10.1016/j.scs.2021.103564. [CrossRef] [Google Scholar]
  • Martins T., Adolphe L., Bonhomme M., Bonneaud F., Faraut S., Ginestet S., et al., 2016. Impact of Urban Cool Island measures on outdoor climate and pedestrian comfort: Simulations for a new district of Toulouse, France. Sustainable Cities and Society, 26, 9–26. doi: 10.1016/j.scs.2016.05.003. [CrossRef] [Google Scholar]
  • Masson V., 2000. A physically-based scheme for the urban energy budget in atmospheric models. Boundary-Layer Meteorology, 94, 3, 357–397. doi: 10.1023/A:1002463829265. [Google Scholar]
  • Masson V., Gomes L., Pigeon G., Liousse C., Pont V., Lagouarde J. et al., 2008. The Canopy and Aerosol Particles Interactions in Toulouse Urban Layer (CAPITOUL) experiment. Meteorology and Atmospheric Physics, 102, 3, 135. doi: 10.1007/s00703-008-0289-4. [CrossRef] [Google Scholar]
  • Masson V., Marchadier C., Adolphe L., Aguejdad R., Avner P., Bonhomme M. et al., 2014. Adapting cities to climate change: A systemic modelling approach. Urban climate, 10, 407–409. doi: 10.1016/j.uclim.2014.03.004. [CrossRef] [Google Scholar]
  • Mauree D., Naboni E., Coccolo S., Perera A., Nik V., Scartezzini J., 2019. A review of assessment methods for the urban environment and its energy sustainability to guarantee climate adaptation of future cities. Renewable and Sustainable Energy Reviews, 112, 733–746. doi: 10.1016/j.rser.2019.06.005. [CrossRef] [Google Scholar]
  • Memon R., Leung D., Liu C., 2009. An investigation of urban heat island intensity (UHII) as an indicator of urban heating. Atmospheric Research, 94, 3, 491–500. doi: 10.1016/j.atmosres.2009.07.006. [CrossRef] [Google Scholar]
  • Ming T., Lian S., Wu Y., Shi T., Peng C., Fang Y. et al., 2021. Numerical investigation on the Urban Heat Island effect by using a porous media model. Energies, 14, 15, 4681. doi: 10.3390/en14154681. [CrossRef] [Google Scholar]
  • Ministère de la cohésion des territoires, 2017. PLUI- Un outil pour l’avenir des territoires. Guide, Ministère de la cohésion des territoires, 4 pages. [Google Scholar]
  • Mirzaei P., Haghighat F., 2010. Approaches to study Urban Heat Island - Abilities and limitations. Building and Environment, 45, 10, 2192–2201. doi: 10.1016/j.buildenv.2010.04.001. [CrossRef] [Google Scholar]
  • Mirzaei P., 2015. Recent challenges in modeling of urban heat island. Substainable Cities and Society, 19, 200–206. doi: 10.1016/j.scs.2015.04.001. [CrossRef] [Google Scholar]
  • Morille B., Musy M., Malys L., 2016. Preliminary study of the impact of urban greenery types on energy consumption of building at a district scale: Academic study on a canyon street in Nantes (France) weather conditions. Energy and Buildings, 114, 275–282. doi: 10.1016/j.enbuild.2015.06.030. [CrossRef] [Google Scholar]
  • Morille B., Musy M., 2017. Comparison of the impact of three climate adaptation strategies on summer thermal comfort - Cases study in Lyon, France. Procedia Environmental Sciences, 38, 619–626. doi: 10.1016/j.proenv.2017.03.141. [CrossRef] [Google Scholar]
  • Musy M., Azam M., Guernouti S., Morille B., Rodler A., 2021. The SOLENE-Microclimat Model: Potentiality for comfort and energy studies. Urban Microclimate Modelling for Comfort and Energy Studies. Edition Palme & A. Salvati, Springer International Publishing, 265–291, doi: 10.1007/978-3-030-65421-4_13. [CrossRef] [Google Scholar]
  • Neij L., Heiskanen E., 2021. Municipal climate mitigation policy and policy learning - A review. Journal of Cleaner Production, 317, 128348. doi:10.1016/j.jclepro.2021.128348. [CrossRef] [Google Scholar]
  • Ng E., Ren C., 2015. The Urban Climatic Map. Routldege, Taylor & Francis Group, p. 543 pages, doi: 10.4324/9781315717616. [Google Scholar]
  • Nieuwenhuijsen M., 2021. New urban models for more sustainable, liveable and healthier cities post covid19; reducing air pollution, noise and heat island effects and increasing green space and physical activity. Environment International, 157, 106850, doi: 10.1016/j.envint.2021.106850. [CrossRef] [Google Scholar]
  • Nogueira M., Hurduc A., Ermida S., Lima D., Soares P., Johannsen F., et al., 2022. Assessment of the Paris urban heat island in ERA5 and offline SURFEX-TEB (v8.1) simulations using the METEOSAT land surface temperature product. Geoscientific Model Development, 15, 14, 5949–5965. doi: 10.5194/gmd-15-5949-2022. [CrossRef] [Google Scholar]
  • Oke T., 1976. The distinction between canopy and boundary- layer urban heat islands. Atmosphere, 14, 4, 268–277. doi: 10.1080/00046973.1976.9648422. [CrossRef] [Google Scholar]
  • Oke T., 1982. The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108, 455, 1–24. doi: 10.1002/qj.49710845502. [Google Scholar]
  • Page M., McKenzie J., Bossuyt P., Boutron I., Hoffmann T., Mulrow C. et al., 2021. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, 71. doi:10.1136/bmj.n71. [CrossRef] [Google Scholar]
  • Parsaee M., Joybari M., Mirzaei P., Haghighat F., 2019. Urban heat island, urban climate maps and urban development policies and actions plans. Environemental Technology & Innovation, 14, 16. doi: 10.1016/j.eti.2019.100341. [Google Scholar]
  • Ramora S., Broomberg K., Molinier J., 2013. Le schéma de cohérence territoriale SCOT : un projet stratégique partagé pour l’aménagement durable d’un territoire. Guide pratique, Ministère de l’égalité des territoires et du logement, 152 pages. [Google Scholar]
  • Reder A., Rianna G., Mercogliano P., Castellari S., 2018. Parametric investigation of Urban Heat Island dynamics through TEB 1D model for a case study: Assessment of adaptation measures. Sustainable Cities and Society, 39, 662–673. doi: 10.1016/j.scs.2018.03.023. [CrossRef] [Google Scholar]
  • Ren C., Lau K., Yiu K., Ng E., 2013. The application of urban climatic mapping to the urban planning of high-density cities: The case of Kaohsiung, Taiwan. Cities, 31, 1–16. doi:10.1016/j.cities.2012.12.005. [CrossRef] [Google Scholar]
  • Revi A., Sattertwhaite D., Aragon-Durand F., Corfee-Morlot J., Kiunsi R., Pelling M. et al., 2014. Urban areas. In Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Field, C., Barros, V., Dokken, D., Mach, K., Mastrandrea, M., Bilir, T. et al. (eds.),Cambridge University Press, Cambridge, RU et New-York, US, 535–612. [Google Scholar]
  • Salamanca F., Krpo A., Martilli A., Clappier A., 2009. A new building energy model coupled with an urban canopy parameterization for urban climate simulations - Part I. formulation, verification, and sensitivity analysis of the model. Theoretical and Applied Climatology, 99, 3, 331. doi: 10.1007/s00704-009-0142-9. [Google Scholar]
  • Santamouris M., 2016. Innovating to zero the building sector in Europe : Minimising the energy consumption, eradication of the energy poverty and mitigating the local climate change. Solar Energy, 128, 61–94. doi:10.1016/j.solener.2016.01.021. [CrossRef] [Google Scholar]
  • Santamouris M., 2020. Recent progress on urban overheating and heat island research. Integrated assessment of the energy, environmental, vulnerability and health impact. Synergies with the global climate change. Energy and Buildings, 207, 109482, doi:10.1016/j.enbuild.2019.109482. [CrossRef] [Google Scholar]
  • Schoetter R., Hidalgo J., Jougla R., Masson V., Rega M., Pergaud J., 2020. A statistical-dynamical downscaling for the urban heat island and building energy consumption - Analysis of Its uncertainties. Journal of Applied Meteorology and Climatology, 59, 5, 859. doi:10.1175/JAMC-D-19-0182.1. [CrossRef] [Google Scholar]
  • Schwarz N., Lautenbach S., Seppelt R., 2011. Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures. Remote Sensing of Environment, 115, 12, 3175–3186. doi: 10.1016/j.rse.2011.07.003. [CrossRef] [Google Scholar]
  • Steensen B., Marelle L., Hodnebrog Ø., Myhre G., 2022. Future urban heat island influence on precipitation. Climate Dynamics, 58, 3393. doi:10.1007/s00382-021-06105-z. [CrossRef] [Google Scholar]
  • Stewart I., 2011. A systematic review and scientific critique of methodology in modern urban heat island literature. International Journal of Climatology, 31, 2, 200–217. doi:10.1002/joc.2141. [CrossRef] [Google Scholar]
  • Struillou J., 2012. L’intégration des préoccupations environnementales dans les documents de planification urbaine. L’apport de la loi Grenelle II. Revue française de droit administratif, 5, 872, Hal-02243241. [Google Scholar]
  • Tian L., Li Y., Lu J., Wang J., 2021. Review on Urban Heat Island in China: Methods, its Impact on buildings energy demand and mitigation strategies. Sustainability, 13, 2, 762. doi:10.3390/su13020762. [CrossRef] [Google Scholar]
  • Toparlar Y., Blocken B., Vos P., Van Heijst G., Janssen W., Van Hooff T. et al., 2015. CFD simulation and validation of urban microclimate: A case study for Bergpolder Zuid, Rotterdam. Building and Environment, 83, 79–90. doi: 10.1016/j.buildenv.2014.08.004. [CrossRef] [Google Scholar]
  • Toparlar Y., Blocken B., Maiheu B., Van Heijst G., 2017. A review of the CFD analysis of urban microclimate. Renewable and substainable energy reviews, 80, 1613–1640. doi:10.1016/j.rser.2017.05.248. [CrossRef] [Google Scholar]
  • Tsoka S., Tsikaloudaki K., Theodosiou T., Bikas D., 2020. Urban warming and cities’ microclimates: Investigation methods and mitigation strategies - A review. Energies, 13, 25, 1414. doi:10.3390/en13061414. [CrossRef] [Google Scholar]
  • Tzavali A., Paravantis J., Mihalakakou G., Fotiadi A., Stigka E., 2015. Urban heat island: A literature review. Fresenius Environmental Bulletin, 24, 12b, 21. [Google Scholar]
  • Wang H., Peng C., Li W., Ding C., Ming T., Zhou N., 2021. Porous media : A faster numerical simulation method applicable to real urban communities. Urban Climate, 38, 100865, 10.1016/j.uclim.2021.100865. [CrossRef] [Google Scholar]
  • Wang X., Li Y., 2016. Predicting urban heat island circulation using CFD. Building and Environment, 99, 82–97. doi:10.1016/j.buildenv.2016.01.020. [CrossRef] [Google Scholar]
  • Wouters H., De Ridder K., Demuzere M., Lauwaet D., Van Lipzig N., 2013. The diurnal evolution of the urban heat island of Paris: A model-based case study during Summer 2006. Atmospheric Chemistry and Physics, 13, 17, 8525–8541. doi:10.5194/acp-13-8525-2013. [CrossRef] [Google Scholar]
  • 2ei Véolia, 2022. Ilots de chaleur : quand l’eau rafraîchit la ville. Planet Veolia https://www.planet.veolia.com/fr/ilots-de-chaleur-quand-l-eau-rafraichit-la-ville. [Google Scholar]

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