The impact of different cooling strategies on urban air temperatures: the cases of Campinas, Brazil and Mendoza, Argentina

Abstract

This paper describes different ways of reducing urban air temperature and their results in two cities: Campinas, Brazil—a warm temperate climate with a dry winter and hot summer (Cwa), and Mendoza, Argentina—a desert climate with cold steppe (BWk). A high-resolution microclimate modeling system—ENVI-met 3.1—was used to evaluate the thermal performance of an urban canyon in each city. A total of 18 scenarios were simulated including changes in the surface albedo, vegetation percentage, and the H/W aspect ratio of the urban canyons. These results revealed the same trend in behavior for each of the combinations of strategies evaluated in both cities. Nevertheless, these strategies produce a greater temperature reduction in the warm temperate climate (Cwa). Increasing the vegetation percentage reduces air temperatures and mean radiant temperatures in all scenarios. In addition, there is a greater decrease of urban temperature with the vegetation increase when the H/W aspect ratio is lower. Also, applying low albedo on vertical surfaces and high albedo on horizontal surfaces is successful in reducing air temperatures without raising the mean radiant temperature. The best combination of strategies—60 % of vegetation, low albedos on walls and high albedos on pavements and roofs, and 1.5 H/W—could reduce air temperatures up to 6.4 °C in Campinas and 3.5 °C in Mendoza.

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Acknowledgments

This work was sponsored by the Research Support Foundation of the State of São Paulo (FAPESP), the National Council of Scientific and Technical Researches (CONICET), and the National Agency for Scientific and Technological Promotion (ANPCYT).

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Correspondence to Noelia Liliana Alchapar.

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Alchapar, N.L., Pezzuto, C.C., Correa, E.N. et al. The impact of different cooling strategies on urban air temperatures: the cases of Campinas, Brazil and Mendoza, Argentina. Theor Appl Climatol 130, 35–50 (2017). https://doi.org/10.1007/s00704-016-1851-5

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Keywords

  • Root Mean Square Error
  • Radiant Temperature
  • Green Roof
  • Urban Surface
  • Mean Bias Error