Cities, data, and greenhouse gas emissions

Stephanie Pincetl & Erik Porse
University of California, Los Angeles, USA

With a growing proportion of Earth’s human population living in cities, the role of urban systems in global environmental change is an increasingly important question (Kennedy et al., 2009; Pincetl et al., 2014; Newman et al., 1999). Buildings, in particular, are a sizeable contributor to urban energy use and greenhouse gas emissions. In U.S. cities alone, buildings produce 40% of urban greenhouse gases (GHGs). Yet, despite this easy target for reducing carbon footprints in industrialized societies, little information exists for localities to target energy efficiency and renewable generation investments across buildings.

In the United States, the 20th century was the era of utilities. In an effort to promote equal access to electricity and water services across a majority rural population, governments granted state-sanctioned monopolies to utilities to ensure equal access to these growing necessities. The relationship was simple. Your address determined your utility, which will bill you monthly for electricity, oil, water, or other services. In return for guaranteed service, utilities received a stable rate of return on their investments. The nuances of system operations, including who used resources where, were obtuse and only known by a handful of technical and policy experts charged with ensuring reliable services.

Today, however, infrastructure systems are changing. In the energy sector, rooftop solar, energy storage, and microgrids are all disrupting the established utility model. A critical component to this revolution is data. While utilities bill customers for electricity and natural gas use, the data is rarely disclosed publicly.  A few cities such as Gainesville, Florida and Madison, Wisconsin have fought to open access to such data, but the vast majority of localities have limited access to energy consumption data. Utilities typically do not publicly reveal high detail energy consumption, citing privacy concerns. Available data lies at the heart of an energy system revolution that may leave 20th century public utilities behind.

This tight control of data inhibits effective local planning for greenhouse gas reductions in many ways. Billing data is not matched with important available data sets that can provide building age, type, use, and size.  This presents an enormous handicap in understanding building energy use in cities, the drivers of that use, and the parsimonious targeting of high energy users in the built environment.  In U.S. cities alone, buildings produce 40% of urban greenhouse gases (GHGs), equal to the emissions produced by the transportation sector.  Despite the importance of the building sector for mitigating climate change, electricity and natural gas use in buildings is rarely reported in a consistent manner. Instead, projections based on models, small samples, and self-reported data support energy efficiency planning.

At UCLA’s Institute of the Environment and Sustainability, The California Center for Sustainable Communities uses gas and electricity billing data from the region’s private utilities, provided through an agreement with the state Public Utilities Commission and major public utilities, to assess trends in electricity consumption, natural gas consumption, and GHG emissions in Los Angeles County, additionally matched to socio-demographic trends and county assessor data for buildings.  The data is compiled into an interactive web atlas (, which reports aggregated results to protect customer privacy, but still shows important energy consumption patterns across the metropolitan region.

With this data, researchers are able to discern differences in energy use across many socio-demographic and building factors at a much more detailed resolution. For instance, the database allows for analyzing energy use by income group, home ownership building age, building size, and other factors. This research approach has immediate real-world impacts for public policy and equity. For instance, California spends over $1 billion per year on improving energy efficiency in buildings with limited systematic verification of predicted savings. After more than a decade of investments in energy conservation and efficiency, the actual impacts of energy conservation programs in California are not well understood, either for whole buildings or individual efficiency incentives such as home ceiling insulation, appliance rebates, and others.

The UCLA Energy Atlas shows that much of the region’s building stock that dates from the post-World War II period, an era of rapid suburban development throughout the U.S uses the most energy per square foot.  Analyzing the data helps identify intricate relationships:

  • Older buildings are much less energy efficient especially those built before 1990 (but they tend to be smaller, so overall use less energy.)
  • Residential buildings, which comprise over 26% of buildings in the region, consume 30% of total building energy.
  • Per capita residential energy consumption in 2010 varied across Los Angeles County according to income. Census block groups that consumed the most energy were in high-income areas, even though fewer people lived in these areas. Census blocks with a median income of over $86,622 consumed nearly three times more total energy than census blocks with a median income less than $36,474 (33 million BTU and 12 million BTU, respectively).
  • Cities with the highest per capita consumption tended to be wealthier coastal cities that hosted newer buildings, along with several more affluent inland areas.
  • Cities with lower rates of total residential energy consumption tended to be less affluent, with average household incomes around $50,000.
  • The lowest residential per capita cities in 2010 were primarily concentrated inland in the southern part of the county and around the older working class cities of Bell, Lynwood and Huntington Park. These areas are in majority renter-occupied, and have a higher proportion of multifamily residences than areas with high per capita energy use.
  • Many low-income areas, when measured per square foot, rank just as high or higher than affluent areas. For instance, Compton another working class city and landlocked, had the highest median consumption per square foot in 2010, but was in the bottom half when ranking cities for median parcel consumption or per capita. This trend across the metropolitan regions results from the predominance of older buildings. In Compton, for instance, the largest percentage of buildings was built between 1950-1978 (Pincetl, 2015).

Compton building stock age and consumption per square foot1

Residential Energy Consumption in Los Angeles County 20102

Commercial buildings tend to use the most electricity per square foot, followed by institutional and single family.  For natural gas (measured in therms per square foot), single and multi-family homes consume the most, often twice as much as industrial and institutional buildings.  Energy consumption trends in institutional buildings, schools and government buildings for instance, are most difficult to ascertain as many organizations who own and operate buildings do not pay taxes.  County tax assessors have less motivation to maintain key data such as square footage.

Over time, energy consumption has increased in California though per capita consumption has remained stable through energy efficiency improvements. With the addition of more people to the state, energy use will continue to slowly increase.  Thus, conservation, measured as a reduction in consumption per capita, is not occurring.  Should this trend continue, GHG emissions from buildings will rise, despite more efficiency.  Addressing conservation, and not just efficiency, will require new initiatives, supported by new data availability. These include the de-carbonization of sources of building energy, which the state of California is pursuing, including the California Energy Commission’s standards requiring zero net energy residential standards starting in 2020 and for commercial buildings in 2025.  These address the building sector, and are complimented by GHG emissions reductions required by the Governor: 40 percent below 1990 levels by 2030.  Increased heat from climate change, however, will likely create an additional challenge for cities in L.A. County to reduce impacts of, for example, increasing use of air conditioners. While energy efficiency building codes target new buildings, Los Angeles has a vast older building stock.  And many questions remain about how to integrate new renewable generation, especially distributed sources such as rooftop solar, into the existing grid.  Utilities in California are struggling to implement a shift in energy resources from centralized fossil fuels to a more hybridized system of distributed renewable generation, supported by backup capacity.  Issues of scale – large scale solar thermal energy plants or distributed photovoltaic rooftop panels – and their associated grid and storage issues, are currently being played out at Public Utilities Commissions across the county. Utilities consider distributed solar generation a disruptive technology (Kind, 2013).

Next steps and ways forward

Currently the Center is now updating the Atlas with 2010-2014 electricity and natural gas data.  Researchers are expanding the geography of the Atlas to include the full service area of the local investor owned utilities, expanding to include most of southern California and Sand Diego County as well.  In addition researchers have received energy efficiency and conservation program data that will be analyzed and added to the Atlas.  This latter data will be examined for its geographical distribution and distribution by type of program.  Additionally, researchers will attempt to evaluate their success using billing data.  This is an enormously complex task as there are many unknown contingencies that may affect success.  Yet, the Atlas remains an important new initiative to explore energy use by building over time and space.  It shows that real time data – in contrast to modeled or sampled data – provides additional insights that are not derivable from previous approaches.  It can greatly inform equity understanding of building energy use in the urban fabric.

Still, cities are complex systems and deciphering precise causes of energy use in a given parcel require consideration of available technologies, building stock and economic resources (Porse et al., 2016).  Address level billing data, matched to buildings and sociodemographic characteristics, makes it possible to significantly improve analysis of energy use in major metropolitan areas and the associated GHG emissions.  Finally, the Atlas contributes to methods that help decipher the relationship of cities to global environmental change through revealing the use of greenhouse gas and pollution emitting fossil fuels in buildings.  It can also help develop policies and programs to reduce energy use in buildings through conservation measures, as well as serve as a resource to develop alternative energy production (such as solar) in cities themselves.  In fact, the Altas shows solar generation potential relative to energy use by neighborhood providing a practical planning tool.

Stephanie Pincetl

Dr. Stephanie Pincetl is Professor-in-Residence at the UCLA Institute of the Environment and Sustainability, and Director of the California Center for Sustainable Communities at UCLA.

Erik Porse

Dr. Erik Porse is a Post Doctoral Researcher at the UCLA Institute of the Environment and Sustainability.

Header Image: LOS ANGELES, CALIFORNIA – MARCH 1, 2016: Traffic and pedestrians on Hollywood Boulevard at dusk.  Credit: Sean Pavone /


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