Spatio-temporal electrical grid emission factors effects on calculated GHG emissions of buildings in mixed-grid environments

St-Jacques, Max; Bucking, Scott; O’Brien, William; Macdonald, Iain

doi:10.1080/23744731.2023.2276012

Science and Technology for the Built Environment

2023

DOI: 10.1080/23744731.2023.2276012

|View full text |Cite

Spatio-temporal electrical grid emission factors effects on calculated GHG emissions of buildings in mixed-grid environments

Max St-Jacques,

Scott Bucking,

William O’Brien

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article3

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

The role of the electricity grid in operation-induced greenhouse gas emissions by a residential building: A multi-year retrospective simulation study

Rouws,

Loonen,

Hensen

2024

Energy and Buildings

View full text Add to dashboard Cite

The role of the electricity grid in operation-induced greenhouse gas emissions by a residential building: A multi-year retrospective simulation study

Rouws,

Loonen,

Hensen

2024

Energy and Buildings

View full text Add to dashboard Cite

Do peak energy loads and peak GHG emissions correlate in buildings? Insights from emission duration curves and emission event duration curves analysis

St-Jacques,

Bucking,

O'Brien

2024

Journal of Cleaner Production

View full text Add to dashboard Cite

Exploration of multiple regression analysis and prediction methods for power grid carbon emission factors

Ye,

Xiao,

Xie

et al. 2024

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

Carbon emissions from the power sector account for about one-third of China’s total carbon emissions, and carbon emission reduction in the power sector is crucial to the realization of the “double carbon” goal. This paper proposes a prediction model for grid carbon emission factor based on the combination of multiple linear regression models and the GM(1,1) model. The grid carbon measurement model is built using the theory of carbon emission flow, and the grid carbon emission accounting model is built using the consumption side. The average grid carbon emission factor is calculated by dividing the grid carbon emission factor into three different dimensions. The multiple linear regression model is used to study the correlation between the independent variables and the dependent variables, and the specific values of each regression factor are predicted by combining with the GM(1,1) model, and it is judged whether the prediction model is reasonable or not. Among the contributions of the increase in carbon emissions from the power grid, the contribution of electricity consumption increased from 2010 to 2014 and reached a peak of 2.9824 million tons in 2014, and the carbon emission factor value of the power grid gradually decreased from 0.719kg CO2/(kW·h) in 2010 to 0.593kg CO2/(kW·h) in 2022. The MR-GM(1,1) model is applied to the prediction of carbon emissions from power grids, and the absolute error of the results is within 15,000 tons, and the maximum relative error is only 2.42%. The calculation and prediction of carbon emission factors of the power grid can help power grid enterprises to clarify the trend of carbon emission, which is conducive to the realization of the low-carbon goal of “carbon neutral” and “carbon peak”.

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Spatio-temporal electrical grid emission factors effects on calculated GHG emissions of buildings in mixed-grid environments

Cited by 3 publications

References 45 publications

The role of the electricity grid in operation-induced greenhouse gas emissions by a residential building: A multi-year retrospective simulation study

The role of the electricity grid in operation-induced greenhouse gas emissions by a residential building: A multi-year retrospective simulation study

Do peak energy loads and peak GHG emissions correlate in buildings? Insights from emission duration curves and emission event duration curves analysis

Exploration of multiple regression analysis and prediction methods for power grid carbon emission factors

Contact Info

Product

Resources

About