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Cool roofs can mitigate cooling energy demand for informal settlement dwellers

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  • Nutkiewicz, Alex
  • Mastrucci, Alessio
  • Rao, Narasimha D.
  • Jain, Rishee K.

Abstract

Cities are critical to meeting our sustainable energy goals. Informal settlement redevelopment programs represent an opportunity to improve living conditions and curb increasing demand for active cooling. We introduce an energy modeling framework for informal settlements to investigate how building design decisions influence the onset of heat stress and energy-intensive cooling demand. We show that occupants of tropically-located informal settlements are most vulnerable to prolonged heat stress year-round. Up to 98% of annual heat stress exposure can be mitigated by improving the building envelope. We find a universal solution (cool roofs) that reduces up to 91% of annual heat stress exposure. Finally, we show how proposed redevelopment building schemes could worsen thermal conditions of dwellers and further increase urban energy demand. Our results underscore how building design affects human well-being and highlight potential near-term and long-term pathways for reducing energy-intensive cooling demand for 800+ million informal settlement dwellers worldwide.

Suggested Citation

  • Nutkiewicz, Alex & Mastrucci, Alessio & Rao, Narasimha D. & Jain, Rishee K., 2022. "Cool roofs can mitigate cooling energy demand for informal settlement dwellers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
  • Handle: RePEc:eee:rensus:v:159:y:2022:i:c:s1364032122001083
    DOI: 10.1016/j.rser.2022.112183
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    1. Ma, Nan & Aviv, Dorit & Guo, Hongshan & Braham, William W., 2021. "Measuring the right factors: A review of variables and models for thermal comfort and indoor air quality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    2. Chou, S.K. & Lee, Y.K., 1988. "A simplified overall thermal transfer value equation for building envelopes," Energy, Elsevier, vol. 13(8), pages 657-670.
    3. Aklin, Michaël & Bayer, Patrick & Harish, S.P. & Urpelainen, Johannes, 2015. "Quantifying slum electrification in India and explaining local variation," Energy, Elsevier, vol. 80(C), pages 203-212.
    4. Henson, Rosie Mae & Ortigoza, Ana & Martinez-Folgar, Kevin & Baeza, Fernando & Caiaffa, Waleska & Vives Vergara, Alejandra & Diez Roux, Ana V. & Lovasi, Gina, 2020. "Evaluating the health effects of place-based slum upgrading physical environment interventions: A systematic review (2012–2018)," Social Science & Medicine, Elsevier, vol. 261(C).
    5. Harkouss, Fatima & Fardoun, Farouk & Biwole, Pascal Henry, 2018. "Passive design optimization of low energy buildings in different climates," Energy, Elsevier, vol. 165(PA), pages 591-613.
    6. Yao, Runming & Liu, Jing & Li, Baizhan, 2010. "Occupants' adaptive responses and perception of thermal environment in naturally conditioned university classrooms," Applied Energy, Elsevier, vol. 87(3), pages 1015-1022, March.
    7. Bhattacharyya, Subhes C., 2015. "Influence of India’s transformation on residential energy demand," Applied Energy, Elsevier, vol. 143(C), pages 228-237.
    8. Chen, Xi & Yang, Hongxing & Wang, Yuanhao, 2017. "Parametric study of passive design strategies for high-rise residential buildings in hot and humid climates: miscellaneous impact factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 442-460.
    9. Nutkiewicz, Alex & Yang, Zheng & Jain, Rishee K., 2018. "Data-driven Urban Energy Simulation (DUE-S): A framework for integrating engineering simulation and machine learning methods in a multi-scale urban energy modeling workflow," Applied Energy, Elsevier, vol. 225(C), pages 1176-1189.
    10. Tian Han & Qiong Huang & Anxiao Zhang & Qi Zhang, 2018. "Simulation-Based Decision Support Tools in the Early Design Stages of a Green Building—A Review," Sustainability, MDPI, vol. 10(10), pages 1-23, October.
    11. Narasimha D. Rao & Jihoon Min & Alessio Mastrucci, 2019. "Energy requirements for decent living in India, Brazil and South Africa," Nature Energy, Nature, vol. 4(12), pages 1025-1032, December.
    12. Indraganti, Madhavi, 2010. "Thermal comfort in naturally ventilated apartments in summer: Findings from a field study in Hyderabad, India," Applied Energy, Elsevier, vol. 87(3), pages 866-883, March.
    13. Nutkiewicz, Alex & Jain, Rishee K. & Bardhan, Ronita, 2018. "Energy modeling of urban informal settlement redevelopment: Exploring design parameters for optimal thermal comfort in Dharavi, Mumbai, India," Applied Energy, Elsevier, vol. 231(C), pages 433-445.
    14. Yıldız, Yusuf & Arsan, Zeynep Durmuş, 2011. "Identification of the building parameters that influence heating and cooling energy loads for apartment buildings in hot-humid climates," Energy, Elsevier, vol. 36(7), pages 4287-4296.
    15. Yang, Liu & Yan, Haiyan & Lam, Joseph C., 2014. "Thermal comfort and building energy consumption implications – A review," Applied Energy, Elsevier, vol. 115(C), pages 164-173.
    16. Chandel, S.S. & Sharma, Vandna & Marwah, Bhanu M., 2016. "Review of energy efficient features in vernacular architecture for improving indoor thermal comfort conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 459-477.
    17. Chen, Yixing & Hong, Tianzhen & Piette, Mary Ann, 2017. "Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis," Applied Energy, Elsevier, vol. 205(C), pages 323-335.
    18. Ali, Usman & Shamsi, Mohammad Haris & Bohacek, Mark & Purcell, Karl & Hoare, Cathal & Mangina, Eleni & O’Donnell, James, 2020. "A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making," Applied Energy, Elsevier, vol. 279(C).
    19. Fonseca, Jimeno A. & Schlueter, Arno, 2015. "Integrated model for characterization of spatiotemporal building energy consumption patterns in neighborhoods and city districts," Applied Energy, Elsevier, vol. 142(C), pages 247-265.
    20. von Grabe, Jörn, 2016. "Potential of artificial neural networks to predict thermal sensation votes," Applied Energy, Elsevier, vol. 161(C), pages 412-424.
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