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A regression-based three-phase approach to assess outdoor thermal comfort in informal micro-entrepreneurial settings in tropical Mumbai
International Journal of Biometeorology ( IF 3.0 ) Pub Date : 2021-04-30 , DOI: 10.1007/s00484-021-02136-7
Shreya Banerjee 1 , Ariane Middel 2, 3 , Subrata Chattopadhyay 1
Affiliation  

Urban heat poses a public health risk to the residents of megacities in developing countries because the population spends a significant amount of time outdoors to work and socialize with limited cooling resources. Understanding the drivers of outdoor comfort and heat stress in informal work settings is important to design climate-sensitive outdoor spaces and reduce heat vulnerability. We present outdoor thermal comfort perceptions (OTCPs) of people engaged in outdoor micro entrepreneurial activities in Mumbai using seasonal surveys and biometeorological observations. We propose a three-phase approach to analyze the relative importance of climatic and non-climatic variables for OTCPs. The first phase evaluates the seasonal and intra-neighborhood variation of thermal sensation votes (TSV) with respect to physiological equivalent temperature (PET) and air temperature. Second, we include physiological parameters to evaluate the seasonal and intra-neighborhood variation of overall sensation votes (OSV). Third, we consider aggregated survey responses and include behavioral and perceptual variables to determine their relative significance. We employ three linear modeling techniques to assess model performance in explaining the variability of OTCP using OSV as dependent variable. Results reveal that microclimatic parameters alone are unable to explain the variability of OTCP. Our results yield a neutral PET value (PETneutral) of 23.75 °C for Mumbai in the winter. PETneutral was higher for activities at the clothing market compared to other micro entrepreneurial activities. Acclimatization significantly improved comfort in the summer, while evaporative cooling was beneficial in the winter. Further, an ANCOVA and ordinal logistic regressions demonstrate the importance of behavioral attributes (presence in the location, expectation, beverage intake) in explaining the variance in OTCP. Our study also reveals that wind speed and humidity play an important role in shaping overall comfort in the Mumbai neighborhoods.

更新日期:2021-04-30
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