Analysis of High‐Resolution Utility Data for Understanding Energy Use in Urban Systems: The Case of Los Angeles, California. (18th June 2015)

• Record Type: Journal Article
• Authors: Pincetl, Stephanie; Graham, Robert; Murphy, Sinnott; Sivaraman, Deepak
• Is Part Of: Journal of industrial ecology. Volume 20:Number 1(2016:Feb.)
• Page Start: 166
• Page End: 178
• Publication Date: 2015-06-18
• Subjects: building energy -- electricity -- energy conservation -- resource efficiency -- sustainable city -- urban metabolism; Industrial ecology -- Periodicals; Product life cycle -- Environmental aspects -- Periodicals; Industrial management -- Environmental aspects -- Periodicals; Écologie industrielle -- Périodiques; 658.56
• DOI: 10.1111/jiec.12299
• Languages: English
• ISSNs: 1088-1980

Abstract

Summary: Urban metabolism provides a framework to understand resource flows into cities and waste flows out. Its potential has been hampered by the lack of good disaggregated data. This article presents energy‐use findings for the residential sector for the city of Los Angeles based on census‐block–level aggregation of address‐level electricity use obtained from the Los Angeles Department of Water and Power. City or county billing data by customer class over time can enable empirical tracking of energy conservation and efficiency programs by different customer classes, and matched to census information and county tax assessor data about building vintage, size, and type can provide information important for rate setting, for example, or energy conservation and efficiency program investments. We report on median electricity demand and corresponding greenhouse gas emissions and expenditures at three geographical aggregations: city council district (15 in total); neighborhood (114 in total); and census block group (2, 538 in total). We find that the ratio of median annual demand between highest‐ and lowest‐tier users is 26 at the census‐block group level, but only 2.2 at the city council district level, demonstrating that spatial aggregation significantly masks the degree of variation that may be observed. We also show how such data can enable the description of energy to develop energy disclosure thresholds that reflect a city's morphology. In contrast to New York City's 50, 000‐square‐foot reporting threshold, to capture half of Los Angeles' electricity consumption, the threshold for reporting would have to be 5, 000 square feet.