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Public Library of Science, PLoS ONE, 2(8), p. e55642, 2013

DOI: 10.1371/journal.pone.0055642

Urban Development for the 21st Century, p. 35-64

DOI: 10.1201/b18765-4

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Greenhouse Gas Emissions Accounting of Urban Residential Consumption: A Household Survey Based Approach

Journal article published in 2013 by Tao Lin, Yunjun Yu, Xuemei Bai ORCID, Ling Feng, Jin Wang
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Devising policies for a low carbon city requires a careful understanding of the characteristics of urban residential lifestyle and consumption. The production-based accounting approach based on top-down statistical data has a limited ability to reflect the total greenhouse gas (GHG) emissions from residential consumption. In this paper, we present a survey-based GHG emissions accounting methodology for urban residential consumption, and apply it in Xiamen City, a rapidly urbanizing coastal city in southeast China. Based on this, the main influencing factors determining residential GHG emissions at the household and community scale are identified, and the typical profiles of low, medium and high GHG emission households and communities are identified. Up to 70% of household GHG emissions are from regional and national activities that support household consumption including the supply of energy and building materials, while 17% are from urban level basic services and supplies such as sewage treatment and solid waste management, and only 13% are direct emissions from household consumption. Housing area and household size are the two main factors determining GHG emissions from residential consumption at the household scale, while average housing area and building height were the main factors at the community scale. Our results show a large disparity in GHG emissions profiles among different households, with high GHG emissions households emitting about five times more than low GHG emissions households. Emissions from high GHG emissions communities are about twice as high as from low GHG emissions communities. Our findings can contribute to better tailored and targeted policies aimed at reducing household GHG emissions, and developing low GHG emissions residential communities in China.