More from Less? Environmental Rebound Effects of City Size

Joao Meirelles, Fabiano L. Ribeiro, Gabriel Cury, Claudia R. Binder and Vinicius M. Netto
Additional contact information
Joao Meirelles: Laboratory for Human-Environmental Relations in Urban Systems, Institute for Environmental Engineering, Swiss Federal Institute of Technology Lausanne (HERUS/EPFL), 1015 Lausanne, Switzerland
Fabiano L. Ribeiro: Department of Physics (DFI), Federal University of Lavras (UFLA), Lavras, MG 37200-900, Brazil
Gabriel Cury: Independent Researcher, Universidade Federal Fluminense (UFF), Niterói, RJ 24220-900, Brazil
Claudia R. Binder: Laboratory for Human-Environmental Relations in Urban Systems, Institute for Environmental Engineering, Swiss Federal Institute of Technology Lausanne (HERUS/EPFL), 1015 Lausanne, Switzerland
Vinicius M. Netto: Department of Urbanism, Universidade Federal Fluminense (UFF), Niterói, RJ 24220-900, Brazil

Sustainability, 2021, vol. 13, issue 7, 1-20

Abstract: Global sustainability relies on our capacity of understanding and guiding urban systems and their metabolism adequately. It has been proposed that bigger and denser cities are more resource-efficient than smaller ones because they tend to demand less infrastructure, consume less fuel for transportation and less energy for cooling/heating in per capita terms. This hypothesis is also called Brand’s Law. However, as cities get bigger, denser and more resource-efficient, they also get richer, and richer inhabitants consume more, potentially increasing resource demand and associated environmental impacts. In this paper, we propose a method based on scaling theory to assess Brand’s Law taking into account greenhouse gas (GHG) emissions from both direct (energy and fuels locally consumed) and indirect (embedded in goods and services) sources, measured as carbon footprint (CF). We aim at understanding whether Brand’s Law can be confirmed once we adopt a consumption-based approach to urban emissions. By analyzing the balance between direct and indirect emissions in a theoretical urban system, we develop a scaling theory relating carbon footprint and city size. Facing the lack of empirical data on consumption-based emissions for cities, we developed a model to derive emission estimations using well-established urban metrics (city size, density, infrastructure, wealth). Our results show that, once consumption-based CF is considered, Brand’s Law falls apart, as bigger cities have greater purchase power, leading to greater consumption of goods and higher associated GHG. Findings also suggest that a shift in consumption patterns is of utmost importance, given that, according to the model, each new monetary unit added to the gross domestic product (GDP) or to other income variables results in a more than proportional increase in GHG emissions. This work contributes to a broader assessment of the causes of emissions and the paradigm shift regarding the assumption of efficiency in the relationship of city size and emissions, adding consumption behavior as a critical variable, beyond Brand’s Law.

Keywords: Brand’s Law; urban scaling; city size; consumption behavior; greenhouse gas emissions (GHG); carbon footprint; complex systems (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/2071-1050/13/7/4028/pdf (application/pdf)
https://www.mdpi.com/2071-1050/13/7/4028/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:7:p:4028-:d:530338

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().