Energy Use in Cities: A New Model Simulating Growth and Land Use Policies

Originally published on October 30, 2015

Does a city of 2 million consume less energy than two cities of 1 million? What is the general relation between city size and per capita energy use? What drives a city to increase energy consumption?

In their paper “The Energy Implications of City Size and Density,” forthcoming in the Journal of Urban Economics, IIEP affiliate Anthony Yezer and William Larson of the Federal Housing Finance Agency establish a new urban simulation model capable of showing the relationship between energy consumption and city size. This mathematical model recognizes variables such as growth caused by wages and amenities, and cities with and without housing and land use regulation.

Los Angeles, California
The type of energy consumed in Los Angeles is unique because of the high temperatures and traffic rates.

Naturally, actual cities are far too complex and differentiated to answer questions about the effects of doubling or quadrupling size, holding all else constant. When analyzing cities, it is therefore necessary to rely on a model due to differences in population and industrial structures. If one analyzes Tokyo, it does not give an accurate answer for energy consumption in a smaller U.S. city. The current form, housing, transportation, and technology in cities have come out of years of history, whereas some developed when transportation and energy-saving building engineering techniques were far less evolved than they are today. A city’s climate and topography also have a major impact on its energy use: a city like Winnipeg, for instance, will consume different types of energy than a warmer city like Los Angeles. Political affairs and land use regulations will also have different implications in different areas. All of these variables are constantly changing with location and time, and so the use of a simulation model is imperative.

Thus, a numerical simulation model allows one to “build” a city while holding output mix, technology, regulation, and even preferences of the population in the city constant. The model can then change one feature at a time and determine the partial effect of that change. In this particular application, Yezer pinpoints his research specifically on wage increase and amenity value of the city. As a city grows and the population rises, the city changes in a multitude of ways, such as in the density of housing units, commute times, and the household expenditure shares on various goods and services. Each of these changes alters the energy consumed by households. For instance, if the average household is in a denser unit, less energy is consumed because less energy is required to heat and cool the home. If a household commutes a longer distance, they consume more gasoline.

In this particular use of the model, the population of a city increases. This occurs either because of a growth in amenity (the benefits of living in a city) or in wages and employment. When the city grows because of amenity, the per capita change in energy actually falls by 3.7%. However, city growth due to wages (which is much more common in real life applications) does not create any change in energy use. In this case, several variables offset each other – housing units must be smaller to make efficient use of space, which reduces energy consumption. Although commute times and growing gasoline use do increase energy consumption, they are not increased beyond the savings from denser housing, and thus approximate equilibrium is achieved. This final accounting indicates that these three changes are, perhaps surprisingly, offsetting, and that energy use per capita does not fall with city size.

greenbelt
Greenbelts are areas of open land near or around a city that can lower energy use per capita.

The effects of regulations on energy use can also be evaluated by imposing those regulations on the model, and observing how consumption changes as city size changes. Height limits on buildings, for example, cause significant increase in energy use per capita if cities grow outward rather than upward. On the other hand, greenbelts (areas of open land near or around a city) can lower energy use per capita.

Looking forward to 2050, many scientists estimate that countries like the United States, China, Nigeria, India, Brazil, and Ethiopia will see their populations double. Energy, water, and transportation will be under immense strain. Yezer’s model can be used to analyze proposed solutions to the challenges of rapid urbanization and sustainability. Most recently, African designer, urbanist, and founder of NLE Architects Kunle Adeyemi proposed a vision to create cities with a “multi-modal transportation system”, which no longer relies primarily on fossil fuels.

Lagos, Nigeria
The Makoko floating school in Lagos, Nigeria is one example of the maximization of habitable space.

Adeyemi believes that “localized solutions will be key to maximizing habitable space” – like in the Nigerian city of Lagos, where floating schools and houses in lagoons could take advantage of the region’s largest natural resources. According to Yezer, Adeyemi’s proposed sustainable living option would cause an increase in the size of the city due to the attraction of better amenities, but a slight decrease in the energy use per capita. According to the findings of Yezer’s research, if cities prepare for the forthcoming population boom by moving toward energy saving, sustainable infrastructure, then they can counteract the assumed energy spike that would logically follow suit.

Urban simulations, while necessary, have never been effective in analyzing differences in city size. The mathematical formula of Larson and Yezer is not only more effective, but more realistic, as it features an endogenous population, supply and demand in housing, and reasonable highway behaviors like commute times and congestion. The simulation is valuable in studying a variety of issues related to cities – and evaluating ideas to reduce energy costs and defray the economic and social costs of a booming population.

In general, this is just one application of what is an important and useful framework for evaluating different theories of urban economics, energy economics, and city planning. This simulation “laboratory” is ripe for further exploration of these and other topics – and can help us examine how evolving urban areas can impact energy use, pollution, and climate change under a large number of criteria.

For more on Professor Yezer’s work, visit his website. Some of his recent work has studied amenity, diversity, and obesity in cities.