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Title: City-Scale Building Anthropogenic Heating during Heat Waves

Abstract

More frequent and longer duration heat waves have been observed worldwide and are recognized as a serious threat to human health and the stability of electrical grids. Past studies have identified a positive feedback between heat waves and urban heat island effects. Anthropogenic heat emissions from buildings have a crucial impact on the urban environment, and hence it is critical to understand the interactive effects of urban microclimate and building heat emissions in terms of the urban energy balance. Here we developed a coupled-simulation approach to quantify these effects, mapping urban environmental data generated by the mesoscale Weather Research and Forecasting (WRF) coupled to Urban Canopy Model (UCM) to urban building energy models (UBEM). We conducted a case study in the city of Los Angeles, California, during a five-day heat wave event in September 2009. We analyzed the surge in city-scale building heat emission and energy use during the extreme heat event. We first simulated the urban microclimate at a high resolution (500 m by 500 m) using WRF-UCM. We then generated grid-level building heat emission profiles and aggregated them using prototype building energy models informed by spatially disaggregated urban land use and urban building density data. The spatial patternsmore » of anthropogenic heat discharge from the building sector were analyzed, and the quantitative relationship with weather conditions and urban land-use dynamics were assessed at the grid level. The simulation results indicate that the dispersion of anthropogenic heat from urban buildings to the urban environment increases by up to 20% on average and varies significantly, both in time and space, during the heat wave event. The heat dispersion from the air-conditioning heat rejection contributes most (86.5%) of the total waste heat from the buildings to the urban environment. We also found that the waste heat discharge in inland, dense urban districts is more sensitive to extreme events than it is in coastal or suburban areas. The generated anthropogenic heat profiles can be used in urban microclimate models to provide a more accurate estimation of urban air temperature rises during heat waves.« less

Authors:
ORCiD logo [1];  [1]; ORCiD logo [1];  [1]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1764544
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Atmosphere (Basel)
Additional Journal Information:
Journal Name: Atmosphere (Basel); Journal Volume: 11; Journal Issue: 11; Journal ID: ISSN 2073-4433
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; anthropogenic heat; building heat emissions; WRF-UCM; urban building energy model; heat wave; urban microclimate

Citation Formats

Luo, Xuan, Vahmani, Pouya, Hong, Tianzhen, and Jones, Andrew. City-Scale Building Anthropogenic Heating during Heat Waves. United States: N. p., 2020. Web. doi:10.3390/atmos11111206.
Luo, Xuan, Vahmani, Pouya, Hong, Tianzhen, & Jones, Andrew. City-Scale Building Anthropogenic Heating during Heat Waves. United States. https://doi.org/10.3390/atmos11111206
Luo, Xuan, Vahmani, Pouya, Hong, Tianzhen, and Jones, Andrew. Sat . "City-Scale Building Anthropogenic Heating during Heat Waves". United States. https://doi.org/10.3390/atmos11111206. https://www.osti.gov/servlets/purl/1764544.
@article{osti_1764544,
title = {City-Scale Building Anthropogenic Heating during Heat Waves},
author = {Luo, Xuan and Vahmani, Pouya and Hong, Tianzhen and Jones, Andrew},
abstractNote = {More frequent and longer duration heat waves have been observed worldwide and are recognized as a serious threat to human health and the stability of electrical grids. Past studies have identified a positive feedback between heat waves and urban heat island effects. Anthropogenic heat emissions from buildings have a crucial impact on the urban environment, and hence it is critical to understand the interactive effects of urban microclimate and building heat emissions in terms of the urban energy balance. Here we developed a coupled-simulation approach to quantify these effects, mapping urban environmental data generated by the mesoscale Weather Research and Forecasting (WRF) coupled to Urban Canopy Model (UCM) to urban building energy models (UBEM). We conducted a case study in the city of Los Angeles, California, during a five-day heat wave event in September 2009. We analyzed the surge in city-scale building heat emission and energy use during the extreme heat event. We first simulated the urban microclimate at a high resolution (500 m by 500 m) using WRF-UCM. We then generated grid-level building heat emission profiles and aggregated them using prototype building energy models informed by spatially disaggregated urban land use and urban building density data. The spatial patterns of anthropogenic heat discharge from the building sector were analyzed, and the quantitative relationship with weather conditions and urban land-use dynamics were assessed at the grid level. The simulation results indicate that the dispersion of anthropogenic heat from urban buildings to the urban environment increases by up to 20% on average and varies significantly, both in time and space, during the heat wave event. The heat dispersion from the air-conditioning heat rejection contributes most (86.5%) of the total waste heat from the buildings to the urban environment. We also found that the waste heat discharge in inland, dense urban districts is more sensitive to extreme events than it is in coastal or suburban areas. The generated anthropogenic heat profiles can be used in urban microclimate models to provide a more accurate estimation of urban air temperature rises during heat waves.},
doi = {10.3390/atmos11111206},
journal = {Atmosphere (Basel)},
number = 11,
volume = 11,
place = {United States},
year = {Sat Nov 07 00:00:00 EST 2020},
month = {Sat Nov 07 00:00:00 EST 2020}
}

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