Potential Urban Heat Island Countermeasures and Building Energy Efficiency Improvements in Los Angeles County

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Los Angeles County has been experiencing increasing numbers of very hot days and heatwaves later into the summer. Scientists predict a significant increase in days with temperatures over 95 °F [35 °C] over the next 15-20 years. As the climate warms, deploying energy efficiency technologies at scale can be an effective method to address the associated increase in urban temperatures, particularly during periodic heatwaves.

Utilizing existing information and data, the research project provided the Los Angeles County Internal Services Department with supplementary datasets and tools that support the identification and prioritization of neighborhoods/districts, building clusters, and specific buildings for retrofits, according to criteria identified and developed during the analysis process. There was a focus on the County’s multi-family residential building stock, to enable low-cost energy retrofits that also support improvement of thermal resilience and occupant health and comfort.

Urban fabric analysis indicated that there are substantial opportunities to reduce unwanted solar heating of buildings and pavements and cool the urban environment with reflective roofs, walls, and pavements. On average, albedo (solar reflectance) values for roofs (0.19) and pavements (0.15) are currently quite low. The potential increases to roof and pavement albedos are 0.33, and 0.25 respectively, indicating substantial opportunities for brightening.

Building stock analysis determined that there are over 43,000 multi-family residential buildings, holding over 150,000 housing units in Los Angeles County, that represent priority opportunities for large-scale energy efficiency policies and activities to ameliorate the impacts of the urban heat island effect.

Building energy simulations were conducted for 13 multifamily residential buildings, to evaluate a low-cost energy efficiency retrofit package. Implementation of these measures in the baseline housing units are expected to reduce annual electricity use by 17%, lower peak electricity demand by 19%, and provide net annual energy cost savings of $183 per housing unit. Importantly, annual hours of heat stress for building occupants are expected to be dramatically reduced by implementation of the energy efficiency retrofit—and for buildings with existing air-conditioning, eliminated entirely.

Unmanned Aerial Vehicle (UAV) flights were conducted as a remote-sensing proof-of-concept for building energy performance evaluation. This approach represents an opportunity for inspection and analysis of existing building stocks, where energy performance can be documented using infrared imaging and 3D photogrammetry. Machine-learning algorithms developed by Berkeley Lab researchers were employed to detect thermal anomalies on building facades, and to indicate issues potentially related to moisture, infiltration, and/or exfiltration. The potential benefits can be seen via implementation of this method at the building test site, which highlighted areas around windows and facade surface corners as locations for further inspection.



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