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San Francisco's 2030 District: Performance and Implications for Urban Energy Efficiency

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Final Report for Nicholas School
5.4 Mb
Workbook for Baseline Calculator, redacted
49.8 Kb
Date
2017-04-26
Author
Johnstone, Eleanor
Advisor
Johnson, Timothy
Repository Usage Stats
458
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1,043
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Abstract
Buildings are responsible for 40% of the United States’ total energy consumption and a proportionate amount of greenhouse gas emissions. Transportation activities are responsible for another 30%, of which a significant amount is linked to workers’ daily commutes by car. Individual investments in home energy retrofits are helpful in the fight against climate change, but the greatest opportunities in the built environment lie with commercial properties in urban cores. As one of 15 cities subscribed to the 2030 Challenge, San Francisco has organized 40+ downtown properties to reduce their aggregate energy consumption and commuter-based emissions by 50-100% by 2030. This master’s project analyzes energy consumption by District properties against a city-established baseline and reduction target. It also calculates a commuter emissions baseline for the San Francisco 2030 District (SF2030D), and compares it to the District’s current performance as measured by a custom survey. The results show that SF2030D has outperformed its peers and reached its 2030 energy target within its first reportable year (2016). These findings have significant implications for the 2030 Challenge’s design, and may position SF2030D as a leader in the pursuit of energy efficiency innovations at the district scale.
Type
Master's project
Department
Nicholas School of the Environment and Earth Sciences
Subject
urban sustainability
2030 District
San Francisco
building energy efficiency
transportation emissions
2030 Challenge
Permalink
https://hdl.handle.net/10161/14122
Citation
Johnstone, Eleanor (2017). San Francisco's 2030 District: Performance and Implications for Urban Energy Efficiency. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/14122.
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

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