HEALTHY DEVELOPMENT MEASUREMENT TOOL

Indicator ES.1.b Electricity use

Descriptive Title: Residential electricity use per capita

Geographic Unit of Analysis: Zip code

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Why Is This An Indicator Of Health and Sustainability?

Since 99% of the electricity produced for San Francisco is generated from fossil fuels, reducing electricity use in buildings results in the reduced combustion of fossil fuels. Electricity generated from fossil fuels produces air pollution in the form of particulate matter, nitrogen dioxides, volatile organic compounds, and toxic air contaminants. Energy efficient buildings reduce emissions from the products of combustion, which include less particulates and pollutants that can improve health and outdoor air quality. Air pollution from the combustion of fossil fuels contributes to respiratory disease and deaths from cardio-vascular diseases.^a The combustion of fossil fuels also contributes to greenhouse gas emissions which are altering the earth’s atmospheric chemistry and climate. On a carbon-equivalent basis, energy-related carbon dioxide emissions accounted for81%  of U.S. anthropogenic greenhouse gas emissions in 2010.^b

Climate change threatens health through the potential of more extreme weather events, increased air pollution, limitations on food production, increased water-borne and food-borne illnesses, and increased infectious disease vectors. For the major fossil fuels, the amounts of carbon dioxide produced for each billion Btu (British thermal units) of heat energy extracted are: 208,000 pounds for coal, 164,000 pounds for petroleum products, and 117,000 pounds for natural gas.

The benefits of energy efficiency go beyond environmental sustainability. Energy efficiency can have economic benefits for both residents and property managers by lowering utility bills. Furthermore, energy efficient design and construction techniques can contribute to the long term affordability of housing through lowered energy costs. 

Interpretation and Geographic Equity Analysis

The above map illustrates disaggregated residential (single family and multi-family) electricity use zip code for 2010. Table 1 details the residential per capita electricity usage for 2010 by zip code. The highest residential per capita electricity use in San Francisco is in the 94105 zip code, which contains the Financial and South of Market neighborhoods. Residential per capita electricity use is also high in some of the northern and central zip codes. The lowest residential per capita electricity usage is in the south-eastern section of the city, which includes the following neighborhoods:

• Bayview
• Bernal Heights
• Crocker Amazon
• Excelsior
• Mission
• Ocean View
• Outer Mission
• Visitacion Valley
• West of Twin Peaks

Table 2 illustrates average electricity usage per single family  and multi-family home , the total usage and the residential carbon dioxide emissions from electricity production in San Francisco from 2005-2010 . Table 3 shows the average electricity use by sector (residential versus non-residential). In 2010, 29% of electricity is used for residential purposes while non-residential use accounts for 71%.

There is substantial variation amongst the San Francisco zip codes with regard to energy usage. Many factors influence energy usage, such as climate, age of housing, housing density, perceived safety, building design, appliances, and equipment, and conservation practices. The South East sector of San Francisco, due to its distance from the ocean fog and breeze, receives more natural sunlight, potentially decreasing its use of heaters and in-turn decreasing its energy usage. In recent years, there has been more development in the South East sector of San Francisco, which has resulted in new dense residential housing. Dense multifamily units, require less energy than single family detached housing. Additionally, the age of housing has been directly associated with energy efficiency--the older the home the more inefficient the use of energy.

Perceived safety may also influence how often residents open windows and doors to regulate the indoor temperature. If an area is perceived as unsafe, one may not leave windows and doors open, relying more on indoor appliances to regulate temperature, increasing their energy usage.

Methods

Electricity use by zip code was provided by Pacific Gas & Electric Tableau worksheets. “Total multi-family use” and “total single family use” were aggregated to get “Total Use.” ”Total use” was the divided by the estimated population within each zip code to get the “Total Use per Capita.” The “Total Use per Capita” data was then mapped by zip code using ArcGIS software.

Average residential electricity usage is calculated by dividing the number of normalized customer months in the year. Customer months are the number of months in a year that a customer has an active account. Normalized means full month and partial month billing periods were taking into consideration. By using this methodology the average value represents a more accurate monthly usage average for the group as a whole. Please note, this methodology is different from calculating residential per capita electricity use and the figures are not comparable.

Limitations

To protect confidentiality, data is not reported where one single family or multi-family dwelling accounts for more than 85% of the demand in that zip code. Therefore, if one single or multi-family account represents 85% of the load in a zip code, zip code location is not given and natural gas use is not accounted for in this map.

For this analysis, using the a larger geographic reference, such as zip code, compared to neighborhood or census tract makes a more detailed analysis of electricity use in San Francisco difficult. 

Data Source

All electricity data was provided by Pacific Gas & Electric Company (PG&E)

Map and tables prepared by City and County of San Francisco, Department of Public Health, Environmental Health Section using ArcGIS software.

Map and table data is presented by zip code. Detailed information regarding census data, geographic units of analysis, their definitions, and their boundaries can be found in the HDMT at the following links:

http://www.thehdmt.org/etc/Geographic_Units_of_Analysis.pdf

http://www.thehdmt.org/data_map_methods.php