The Environmental Impact of Sharing: Household and Urban Economies in CO2 Emissions

Fremstad, Anders; Underwood, Anthony; Zahran, Sammy

doi:10.1016/j.ecolecon.2017.08.024

Cited by 86 publications

(48 citation statements)

References 41 publications

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“…In Finland, several studies have found inner urban residents to have the highest CBCF (Heinonen et al 2011, Ottelin et al 2015, 2018a, Ala-Mantila et al 2016. Fremstad et al (2018) and Heinonen (2016) presented similar findings to those from the US. In contrast, for the US Jones and Kammen (2014) reported the average CBCF to be higher in suburban cities and towns compared to urban core cities.…”

Section: Absolute Cbcf Comparisonsmentioning

confidence: 65%

“…Of course, the magnitude of the reported urbanization relationships differs. The highest reported difference between the most urban and most rural area type, other factors controlled for, is around 20% (Fremstad et al 2018). Quantitatively smaller differences are also found, for example, in Finland Ala-Mantila et al (2014) reported the difference between urban and rural areas to be approximately 15%, and in Sweden Nässén et al (2015) found that longer geographical distances increased emissions by about 9% relative to average emissions.…”

Section: Statistical Analyzes Explaining Cbcfmentioning

confidence: 96%

“…Sustainable urban planning covers other aspects aside from urban density and transport planning. Several recent papers highlight the potential of cities to facilitate the sharing economy (Underwood and Zahran 2015, Ala-Mantila et al 2016, Fremstad et al 2018, Jones et al 2018. Decreasing household size in cities is a global trend.…”

Section: City Policiesmentioning

confidence: 99%

“…When comparing the averages of the absolute CBCF without controlling for any background variables, the more urban areas tend to have higher footprints , Seriño 2017, Fremstad et al 2018 in the SI). The majority of the reviewed papers for this section (19 papers) conclude that, generally, the higher the level of urbanization, the higher the consumption-based emissions.…”

Section: Absolute Cbcf Comparisonsmentioning

confidence: 99%

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What can we learn from consumption-based carbon footprints at different spatial scales? Review of policy implications

Ottelin

Ala-Mantila

Heinonen

et al. 2019

Environ. Res. Lett.

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Background: Current climate change mitigation policies, including the Paris Agreement, are based on territorial greenhouse gas (GHG) accounting. This neglects the understanding of GHG emissions embodied in trade. As a solution, consumption-based accounting (CBA) that reveals the lifecycle emissions, including transboundary flows, is gaining support as a complementary information tool. CBA is particularly relevant in cities that tend to outsource a large part of their production-based emissions to their hinterlands. While CBA has so far been used relatively little in practical policymaking, it has been used widely by scientists. Methods and design: The purpose of this systematic review, which covers more than 100 studies, is to reflect the policy implications of consumption-based carbon footprint (CBCF) studies at different spatial scales. The review was conducted by reading through the discussion sections of the reviewed studies and systematically collecting the given policy suggestions for different spatial scales. We used both numerical and qualitative methods to organize and interpret the findings of the review. Review results and discussion: The motivation for the review was to investigate whether the unique consumption perspective of CBA leads to similarly unique policy features. We found that various carbon pricing policies are the most widely supported policy instrument in the relevant literature. However, overall, there is a shortage of discussion on policy instruments, since the policy discussions focus on policy outcomes, such as behavioral change or technological solutions. In addition, some policy recommendations are conflicting. Particularly, urban density and compact city policies are supported by some studies and questioned by others. To clarify the issue, we examined how the results regarding the relationship between urban development and the CBCF vary. The review provides a concise starting point for policymakers and future research by summarizing the timely policy implications.

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Section: Absolute Cbcf Comparisonsmentioning

confidence: 65%

Section: Statistical Analyzes Explaining Cbcfmentioning

confidence: 96%

Section: City Policiesmentioning

confidence: 99%

Section: Absolute Cbcf Comparisonsmentioning

confidence: 99%

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What can we learn from consumption-based carbon footprints at different spatial scales? Review of policy implications

Ottelin

Ala-Mantila

Heinonen

et al. 2019

Environ. Res. Lett.

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“…In order to find out the impacts of socio-economic factors on household CO 2 emissions, many variables, such as population, affluence, energy intensity, the urbanization level, employment rate, and the share of the tertiary industry, are considered. A large amount of research has shown that household energy requirements, carbon emissions and carbon footprint are closely related to income [42], level of education [43], age [36], gender [38], occupation [14], household size [44], urbanization [45], car ownership [43], urban density [46,47], consumption patterns [48,49], and imports [50]. Different methods, such as index decomposition analysis (IDA) [51], logarithmic mean Divisia index (LMDI) [52], and Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT)model [53,54] were adopted.…”

Section: Introductionmentioning

confidence: 99%

Comparing Urban and Rural Household CO2 Emissions—Case from China’s Four Megacities: Beijing, Tianjin, Shanghai, and Chongqing

2018

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CO 2 emissions caused by household consumption have become one of the main sources of greenhouse gas emissions. Studying household CO 2 emissions (HCEs) is of great significance to energy conservation and emissions reduction. In this study, we quantitatively analyzed the direct and indirect CO 2 emissions by urban and rural households in Beijing, Tianjin, Shanghai, and Chongqing. The results show that urban total HCEs are larger than rural total HCEs for the four megacities. Urban total per capita household CO 2 emissions (PHCEs) are larger than rural total PHCEs in Beijing, Tianjin, and Chongqing, while rural total PHCEs in Shanghai are larger than urban total PHCEs. Electricity and hot water production and supply was the largest contributor of indirect HCEs for both rural and urban households. Beijing, Tianjin, Shanghai, and Chongqing outsourced a large amount of indirect CO 2 emissions to their neighboring provinces.

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Population and Energy Consumption/Carbon Emissions: What We Know, What We Should Focus on Next

Liddle

Casey

2022

International Handbooks of Population

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The Environmental Impact of Sharing: Household and Urban Economies in CO2 Emissions

Cited by 86 publications

References 41 publications

What can we learn from consumption-based carbon footprints at different spatial scales? Review of policy implications

What can we learn from consumption-based carbon footprints at different spatial scales? Review of policy implications

Comparing Urban and Rural Household CO2 Emissions—Case from China’s Four Megacities: Beijing, Tianjin, Shanghai, and Chongqing

Population and Energy Consumption/Carbon Emissions: What We Know, What We Should Focus on Next

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