2019
DOI: 10.1016/j.envint.2019.105137
|View full text |Cite
|
Sign up to set email alerts
|

Scale, distribution and variations of global greenhouse gas emissions driven by U.S. households

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

2
31
0

Year Published

2020
2020
2024
2024

Publication Types

Select...
6
1
1
1

Relationship

2
7

Authors

Journals

citations
Cited by 60 publications
(33 citation statements)
references
References 33 publications
2
31
0
Order By: Relevance
“…2 A ). In energy models, consumption side accounting has found similar links using energy expenditure data ( 19 ) and using income as an explanatory variable ( 18 ). The building-level data enabled the capture of housing attributes afforded by affluence—greater floor space, access to older, established neighborhoods—while keeping income endogenous to our model.…”
Section: Resultsmentioning
confidence: 96%
See 1 more Smart Citation
“…2 A ). In energy models, consumption side accounting has found similar links using energy expenditure data ( 19 ) and using income as an explanatory variable ( 18 ). The building-level data enabled the capture of housing attributes afforded by affluence—greater floor space, access to older, established neighborhoods—while keeping income endogenous to our model.…”
Section: Resultsmentioning
confidence: 96%
“…How household energy emissions vary across income groups is not well understood but important given the rapidly changing demographics of US cities and suburbs ( 14 ). Research has traditionally focused on geographically limited cases ( 15 17 ) or lumped building energy emission with other end uses in carbon accounting ( 18 , 19 ). Finally, the influence of built form—the spatial relationships between buildings—and emissions have only been explored for a few US cities ( 20 , 21 ).…”
mentioning
confidence: 99%
“…Some studies also investigated household carbon footprints in spatial detail, from metropolitan areas (Markolf et al, 2017), counties (Tamayao et al, 2014), cities (Ramaswami and Chavez, 2013;Wheeler et al, 2018), to the zipcode level (Jones and Kammen, 2014). Analyzing temporal change, Song et al (2019), using global MRIO, found that the average US household CF decreased from approximately 70 tCO 2 eq per household (tCO 2 eq/hh) in 2000 to below 50 tCO 2 eq/hh in 2014, with an increasing share of household CF from overseas. In terms of major contributors and potential mitigation, Jones and Kammen (2011) concluded that changes in diet and telecommuting were among the most effective approaches to reduce GHG emissions for households.…”
Section: Introductionmentioning
confidence: 99%
“…This assumption is grounded in the findings of numerous studies relating income, consumption, energy use and/or emissions, which draw upon a variety of methodologies (see for example Wiedenhofer et al 2013;Ummel 2014;Hubacek et al 2017;Wiedenhofer et al 2017;Dorband et al 2019;Song et al 2019;Li et al 2020;Oswald et al 2020;Ivanova and Wood 2020). Some studies are based on consumption surveys of a set of households that span a range of incomes, coupled with national input-output matrices and emissions coefficients, or sometimes coupled with estimates from lifecycle analysis.…”
Section: The Relationship Between Income and Emissionsmentioning
confidence: 99%