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Study finds that suburban sprawl cancels carbon-footprint savings of dense urban cores in US

7 January 2014

Kammen
East Coast metropolitan statistical areas (J), with a larger map of New York metropolitan area (K, outer line) and New York City (K, inner line) highlight the consistent pattern of relatively low GHG urban core cities and high GHG suburbs. Credit: ACS, Jones and Kammen. Click to enlarge.

Although population-dense cities contribute less greenhouse-gas emissions per person than other areas of the country, these cities’ extensive suburbs essentially wipe out the climate benefits, according to a new study by Christopher Jones and Daniel Kammen at UC Berkeley. The average carbon footprint of households living in the center of large, population-dense urban cities is about 50% below average, while households in distant suburbs are up to twice the average.

The study, published in the ACS journal Environmental Science & Technology (ES&T), used local census, weather and other data—37 variables in total—to approximate greenhouse gas emissions resulting from the energy, transportation, food, goods and services consumed by US households. A key finding is that suburbs account for half of all household greenhouse gas emissions, even though they account for less than half the US population.

Previous research using a diverse set of methods focused largely on large metropolitan regions or cities has shown that household carbon footprints (HCFs) vary considerably, with energy, transportation, or consumption comprising a larger share of the total and with households in some locations contributing far more emissions than others. For example, motor vehicles in California account for 30% of HCF, compared to 6% for household electricity, while electricity is frequently the largest single source of emissions in locations with predominantly coal-fired electricity. Income, household size, and social factors have been shown to affect total HCF, while a large number of factors have been shown to contribute to household energy and transportation-related emissions.

A number of studies suggest that geographic differences in emissions are in part explained by population density. Population-dense municipalities tend to be urban centers with employment, housing, and services closely colocated, reducing travel distances, increasing demand for public transit, and with less space for larger homes. … These earlier studies have been limited to analyzing a small set of case studies, and the resulting conclusions are difficult to generalize beyond those included in the studies themselves. A large, nationwide data set of all locations at fine geographic resolution holds potential to reassess the urban form hypothesis to more accurately describe the relationship between population, policy, urban form, and emissions. Our primary research questions are (1) how much variability exists in the size and composition of household carbon footprints across all U.S. locations and (2) how much of this variability can be explained by population density, income, home size, and other factors contributing to carbon footprints in urban, suburban, and rural areas?

—Jones and Kammen

Using the nationwide data set, they found a “more nuanced relationship” between population density and household carbon footprints than determined by previous research using much smaller data sets. Those studies suggested a negative correlation between population density and emissions—i.e., as population density increases, emissions decrease.

In contrast, Jones and Kammen found that the mean, standard deviation and range of emissions increase until a population density of about 3,000 persons per square mile is reached, after which mean HCF declines logarithmically, leveling out at a lower limit of about 30 tCO2 per household (35% below average) at densities over 50,000 persons per square mile.

The net effect of this “inverted-U” relationship is that there is no overall correlation between population density and HCF when considering all US zip codes and cities. However, there is a strong negative log−linear correlation between population density and HCF if only considering the most populous cities—findings consistent with previous studies. However, when considering entire metropolitan statistical areas, the inverted-U relationship disappears and the correlation appears to be slightly positive.

  • More populous metropolitan areas tend to have somewhat higher net HCF due to the influence of more extensive suburbs, which are on average 25% higher than urban cores.

  • The two largest metropolitan areas, New York and Los Angeles, are exceptions with somewhat lower net carbon footprints, suggesting the inverted-U relationship may hold when including extremely population-dense metropolitan areas, or megacities.

Metropolitan areas look like carbon footprint hurricanes, with dark green, low-carbon urban cores surrounded by red, high-carbon suburbs. Unfortunately, while the most populous metropolitan areas tend to have the lowest carbon footprint centers, they also tend to have the most extensive high-carbon footprint suburbs.

—Christopher Jones

The UC Berkeley researchers found that the primary drivers of carbon footprints are household income, vehicle ownership and home size, all of which are considerably higher in suburbs. Other important factors include population density, the carbon intensity of electricity production, energy prices and weather.

As a policy measure to reduce GHG emissions, increasing population density appears to have severe limitations and unexpected trade-offs. In suburbs, we find more population-dense suburbs actually have noticeably higher HCF, largely because of income effects. Population density does correlate with lower HCF when controlling for income and household size; however, in practice population density measures may have little control over income of residents. Increasing rents would also likely further contribute to pressures to suburbanize the suburbs, leading to a possible net increase in emissions. As a policy measure for urban cores, any such strategy should consider the larger impact on surrounding areas, not just the residents of population dense communities themselves. The relationship is also log−linear, with a 10-fold increase in population density yielding only a 25% decrease in HCF. Generally, we find no evidence for net GHG benefits of population density in urban cores or suburbs when considering effects on entire metropolitan areas.

Given these limitations of urban planning our data suggest that an entirely new approach of highly tailored, community-scale carbon management is urgently needed. Regions with high energy-related emissions, such as the Midwest, the South, and parts of the Northeast, should focus more on reducing household energy consumption than regions with relatively clean sources of energy, such as California. However, if household energy were the sole focus of residential GHG mitigation programs, then between two-thirds and 85% of household carbon footprints would be left unaddressed in most locations; the full carbon footprint of households should be considered in community GHG inventories and management plans. Suburbs, which account for 50% of total U.S. HCF, tend to have high motor vehicle emissions, large homes, and high incomes. These locations are ideal candidates for a combination of energy efficient technologies, including whole home energy upgrades and solar photovoltaic systems combined with electric vehicles. Food tends to be a much larger share of emissions in urban cores, where transportation and energy emissions tend to be lower, and in rural areas, where household size tends to be higher and consumption relatively low.

—Jones and Kammen

The project website includes a tool that calculates carbon footprints for essentially every populated US zipcode, city, county and U.S. state (31,531 zipcodes, 10,093 cities and towns, 3,124 counties, 276 metropolitan regions and 50 states) as well as an interactive online map allowing users to zoom in and out of different locations. Households and cities can calculate their own carbon footprints to see how they compare to their neighbors and create customized climate action plan from over 40 mitigation options.

The research was funded by the National Science Foundation and the California Air Resources Board.

Resources

  • Christopher Jones and Daniel M. Kammen (2014) “Spatial Distribution of U.S. Household Carbon Footprints Reveals Suburbanization Undermines Greenhouse Gas Benefits of Urban Population Density,” Environmental Science & Technology doi: 10.1021/es4034364

January 7, 2014 in Emissions, Land use, Policy, Urban mobility | Permalink | Comments (8) | TrackBack (0)

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Comments

Maybe "negates" or "wastes" would be a better word than "cancels"

That's what happens went suburb people go to work, shopping, school etc mostly in large heavy 4 x 4 gas guzzlers.

All this will change when they start using smaller more efficient electrified vehicles equipped with solar energy capture windows, hood, roof and booths?

It'll change when the criminal class is forcibly removed from cities, making them habitable by decent people once more and eliminating the need for long commutes just to have safety in one's home.

USA is more likely to see many more Detroit like cities with armed workless drug dealers and robbers than decent people moving back in. The jungle is expanding?

It may be easier to move jobs to suburbs and let city cores go bankrupt?

However, expanded suburb dwellers would still need cleaner transportation. Three-wheeled electric Elio units, at under $10K, could do it?

Suburb dwellers will have to find ways to protect themselves from hungry city dwellers?

Suburban living is more comfortable and relaxing than high-density inner city. Carbon footprint will no longer be an issue once all energy consumption will come from zero-CO2 sources.

So, the solution is not higher population density. The solution is building more and more Renewable Energy and Nuclear Energy capacity to phase out fossil-fuel energy.

No so sure RP.

After many years, I got tired of cleaning the pool, cutting grass, blowing the snow, fixing the roof, the HVAC, etc etc.

Our current high rise condo has two huge pools, very large air conditioned exercise room with 25+ units, 144 internal heated garages, library, 6 car washing facilities, card room, billard room, ping pong room, large work shop, 4 high speed elevators, 32 cameras, sprinklers every 7-ft, two mail rooms, two reception rooms with fully equipped kitchens, very large South side balcony (38 x 9.5 ft), huge lobby, 60 outside parkings, etc.

The place is always spotless, located on a small Island, very quiet and extremely comfortable. On clear days, we can see the Lake Placid NY mountains some 94 Km South of us.

The wife and I like it better than the 3000+ sq. ft. house we had.

Forgot, the inside heated pool is equipped with a large over heated whirlpool, 2 saunas, 6 showers, 20 lockers, 4 toilets, 4 hand wash sinks etc. All spotless.

The all electric house used 70 kWh/day (average for 15 years) and the Condo uses 22 kWh/day (average last 4 years) but it may go up a bit this year because we are having a very COLD windy winter.

An ($220,000) computerized energy management system + LED lights + timers + auto ON-OFF etc were installed for all common areas and facilities in the building two years ago. Energy cost was reduced by more than 50% or by more than $58,000/year with no real reduction in comfort level.

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