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Abstract Despite the proven benefits of natural ventilation (NV) as an effective low-carbon solution to meet growing cooling demand, its effectiveness can be constrained by poor outdoor air quality. Here, we propose a modeling approach that integrates highly granular air pollution data with a coupled EnergyPlus and differential equation airflow model to evaluate how NV potential for space cooling changes when accounting for air pollution exposure (PM2.5). Given the high vulnerability of low-income populations to air pollution and the dearth of energy and thermal comfort research on informal settlements, we applied our model to a typical informal settlement residence in two large Indian cities: New Delhi and Bangalore. Our results indicate that outdoor PM2.5 levels have a significant impact on NV potential especially in highly polluted cities like New Delhi. However, we found that low-cost filtration (MERV 14) increased the NV potential by 25% and protected occupants from harmful exposure to PM2.5 with a minor energy penalty of 6%. We further find that adoption of low-cost filtration is a viable low-carbon solution pathway as it provides both thermal comfort and exposure protection at 65% less energy intensity—energy intensity reduced to 60 kWh m−2from 173.5 kWh m−2in case of adoption of potentially unaffordable full mechanical air conditioning. Our work highlights ample opportunities for reducing both air pollution and energy consumption in informal settlements across major Indian cities. Finally, our work can guide building designers and policymakers to reform building codes for adopting low-cost air filtration coupled with NV and subsequently reduce energy demand and associated environmental emissions.
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The Goldilocks Zone in Cooling Demand: What Can We Do Better?
Abstract The higher frequency and intensity of sustained heat events have increased the demand for cooling energy across the globe. Current estimates of summer‐time energy demand are primarily based on Cooling Degree Days (CDD), representing the number of degrees a day's average temperature exceeds a predetermined comfort zone temperature. Through a comprehensive analysis of the historical energy demand data across the USA, we show that the commonly used CDD estimates fall significantly short (±25%) of capturing regional thermal comfort levels. Moreover, given the increasingly compelling evidence that air temperature alone is not sufficient for characterizing human thermal comfort, we extend the widely used CDD calculation to heat index, which accounts for both air temperature and humidity. Our results indicate significant mis‐estimation of regional thermal comfort when humidity is ignored. Our findings have significant implications for the security, sustainability, and resilience of the grid under climate change.
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- Award ID(s):
- 1826161
- PAR ID:
- 10448380
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Earth's Future
- Volume:
- 10
- Issue:
- 1
- ISSN:
- 2328-4277
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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