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Does size matter? Scaling of CO2 emissions and US urban areas.

Fragkias M, Lobo J, Strumsky D, Seto KC - PLoS ONE (2013)

Bottom Line: Here we examine the relationship between city size and CO2 emissions for U.S. metropolitan areas using a production accounting allocation of emissions.We find that for the time period of 1999-2008, CO2 emissions scale proportionally with urban population size.Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.

View Article: PubMed Central - PubMed

Affiliation: Department of Economics, Boise State University, Boise, Idaho, USA. michailfragkias@boisestate.edu

ABSTRACT
Urban areas consume more than 66% of the world's energy and generate more than 70% of global greenhouse gas emissions. With the world's population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO2) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO2 emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999-2008, CO2 emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.

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Cross-sectional log-log regressions for years (A) 1999 and (B) 2008.
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pone-0064727-g001: Cross-sectional log-log regressions for years (A) 1999 and (B) 2008.

Mentions: The 95% confidence interval for the ln(population) coefficient in Eq. 4 is [.9164905,.9499573]. The coefficient is thus statistically different than 1. The scaling coefficient can be interpreted as elasticity, where a 1% increase in population size is associated with a nearly proportional increase in CO2 emissions of 0.93%. The value in parentheses is the heteroskedasticity-corrected standard error. Note that the same model and specification, run only for the subsample of MSAs for the 10 years (leading to a total of 3630 observations) yields a ln(population) coefficient of 0.90 and the same level of R2. We also conduct cross-sectional OLS estimations for each of the ten years for which data is available, done with a correction for heteroskedasticity; these regressions yield scaling coefficients in the order of 0.93–0.95 (a remarkable stability across time) and R2 values ranging from 0.67–0.76. Using only the subsample of MSAs, the OLS estimations for each of the ten years, correcting for heteroskedasticity, yield scaling coefficients in the order of 0.91–0.92 and R2 values ranging from 0.67–0.68. Figure 1 plots the cross-sectional regression results for the full sample and the two endpoint years in our dataset.


Does size matter? Scaling of CO2 emissions and US urban areas.

Fragkias M, Lobo J, Strumsky D, Seto KC - PLoS ONE (2013)

Cross-sectional log-log regressions for years (A) 1999 and (B) 2008.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3672169&req=5

pone-0064727-g001: Cross-sectional log-log regressions for years (A) 1999 and (B) 2008.
Mentions: The 95% confidence interval for the ln(population) coefficient in Eq. 4 is [.9164905,.9499573]. The coefficient is thus statistically different than 1. The scaling coefficient can be interpreted as elasticity, where a 1% increase in population size is associated with a nearly proportional increase in CO2 emissions of 0.93%. The value in parentheses is the heteroskedasticity-corrected standard error. Note that the same model and specification, run only for the subsample of MSAs for the 10 years (leading to a total of 3630 observations) yields a ln(population) coefficient of 0.90 and the same level of R2. We also conduct cross-sectional OLS estimations for each of the ten years for which data is available, done with a correction for heteroskedasticity; these regressions yield scaling coefficients in the order of 0.93–0.95 (a remarkable stability across time) and R2 values ranging from 0.67–0.76. Using only the subsample of MSAs, the OLS estimations for each of the ten years, correcting for heteroskedasticity, yield scaling coefficients in the order of 0.91–0.92 and R2 values ranging from 0.67–0.68. Figure 1 plots the cross-sectional regression results for the full sample and the two endpoint years in our dataset.

Bottom Line: Here we examine the relationship between city size and CO2 emissions for U.S. metropolitan areas using a production accounting allocation of emissions.We find that for the time period of 1999-2008, CO2 emissions scale proportionally with urban population size.Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.

View Article: PubMed Central - PubMed

Affiliation: Department of Economics, Boise State University, Boise, Idaho, USA. michailfragkias@boisestate.edu

ABSTRACT
Urban areas consume more than 66% of the world's energy and generate more than 70% of global greenhouse gas emissions. With the world's population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO2) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO2 emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999-2008, CO2 emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.

Show MeSH
Related in: MedlinePlus