Large cities are less green.

Area of Science:

• Urban studies
• Environmental science
• Complexity science

Background:

• Understanding the relationship between urban growth and environmental impact is crucial for sustainable development.
• Previous studies on urban scaling often rely on administrative boundaries, which may not accurately reflect functional urban areas.

Purpose of the Study:

• To investigate the scaling relationship between urban population and carbon dioxide (CO2) emissions using a novel, data-driven approach.
• To compare findings with traditional methods based on administrative city definitions.

Main Methods:

• Utilized a bottom-up approach with microscopic population and CO2 emission data for the continental US.
• Employed the City Clustering Algorithm (CCA) to define cities based on proximity, transcending administrative boundaries.
• Calculated total city emissions using fine-scale CO2 data.

Main Results:

• Discovered a superlinear scaling relationship (power-law) between city population and CO2 emissions, with an average allometric exponent (β) of 1.46.
• Observed isometric scaling for cities defined by administrative boundaries (Metropolitan Statistical Areas - MSAs).
• Attributed the discrepancy to the overestimation of MSA areas, suggesting potential endogeneity bias in prior research.

Conclusions:

• Urban agglomerations exhibit disproportionately higher CO2 emissions as they grow larger.
• The definition of a 'city' significantly impacts the observed urban scaling laws.
• Findings challenge the reliability of administrative boundaries in urban scaling research and emphasize the need for spatially accurate city definitions.