Regional Difference of US Residential Building Energy Usage and Carbon Footprint: State-Level Analysis
Jianli Chen （ Department of Civil and Environmental Engineering, The University of Utah, Salt Lake City, UT 84112, USA ）
Biao Kuang （ Department of Civil and Environmental Engineering, The University of Utah, Salt Lake City, UT 84112, USA ）
Abstract
United States (US) residential buildings demonstrate great decarbonization and energy-saving potential. However, research on the carbon footprint of residential buildings at the state level, especially consumption-based emissions, is limited. Therefore, this paper aims to quantify and compare the state-level carbon emissions and energy consumption of residential buildings in the US. Specifically, state carbon emission factors of electricity are estimated using area and population-based interpolations of eGRID regional carbon factors. Total carbon emissions and carbon intensity (e.g., carbon emission per household/ capita) of each state are then calculated based on the 2020 Residential Energy Consumption Survey dataset. Results of state carbon footprints demonstrate regional differences and spatial patterns: Texas and California stand out as the top energy consumers and contribute to the largest amount of carbon emissions, while Missouri has the highest carbon intensity on a household/ capita/ housing area basis. Also, west and east coastal states (e.g., California) exhibit lower carbon intensities than central states. Sensitivity analysis concludes that highly electrified states (e.g., Florida and Hawaii) are more sensitive to the carbon emission factor of electricity generation, with sensitivity degrees over 0.97. Furthermore, correlation analysis indicates that total carbon emission and its sensitivity to electricity carbon emission factor, as well as emission intensity positively correlate with state energy profile (e.g., gas ratio). Therefore, to achieve residential building decarbonization, besides energy-conservative measures, high gas-penetration states (e.g. Illinois) need to reduce direct fossil fuel use in residential energy services; states with high carbon emission factors and electrifications, e.g., Hawaii and Missouri, need to decarbonize electricity generation by adopting renewable energy as sources. The research findings contribute to understanding the regional variations in carbon footprints and energy usage of residential buildings, facilitating the development of tailored decarbonization and energy-saving measures for targeting states in the US.
Keywords
Carbon footprint; Energy usage; Residential building; Regional difference; Consumption-based emissionsFull Text
PDFReferences
[2] United Nations. Emissions Gap Report 2022: The Closing Window. 2022. https://www.unep.org/resources/emissions-gap-report-2022 (accessed on November 16, 2023).
[3] Wu Z, Huang X, Chen R, et al. The United States and China on the paths and policies to carbon neutrality. Journal of Environmental Management, 2022; 320:115785. https://doi.org/10.1016/j.jenvman.2022.115785.
[4] US EIA. Monthly Energy Review – November 2022 2022: DOE/EIA‐0035(2022/11). http://large.stanford.edu/courses/2022/ph240/tidd2/docs/mer-nov22.pdf
[5] US EIA. U.S. Energy-Related carbon dioxide emissions, 2021. 2022. https://www.eia.gov/environment/emissions/carbon/pdf/2021_co2analysis.pdf (accessed on October 29, 2023).
[6] Kuang B, Schelly C, Ou G, et al. Data-driven analysis of influential factors on residential energy end-use in the US. Journal of Building Engineering, 2023:106947. https://doi.org/10.1016/j.jobe.2023.106947.
[7] Dehdar F, Fuinhas JA, Karimi Alavijeh N, et al. Investigating the determinants of carbon emissions in the USA: a state-level analysis. Environ Sci Pollut Res, 2023; 30:23023–34. https://doi.org/10.1007/s11356-022-23831-x.
[8] Goldstein B, Gounaridis D and Newell JP. The carbon footprint of household energy use in the United States. Proceedings of the National Academy of Sciences, 2020; 117:19122–30. https://doi.org/10.1073/pnas.1922205117.
[9] Keerthana KB, Wu S-W, Wu M-E, et al. The United States energy consumption and Carbon dioxide emissions: a comprehensive forecast using a regression model. Sustainability, 2023; 15:7932. https://doi.org/10.3390/su15107932.
[10] US EIA. Energy-Related Carbon Dioxide Emissions by State, 2005–2016. 2019. https://www.eia.gov/environment/emissions/state/analysis/pdf/stateanalysis.pdf (accessed on October 27, 2023).
[11] Jorgenson A, Schor J and Huang X. Income inequality and carbon emissions in the United States: a state-level analysis, 1997–2012. Ecological Economics, 2017; 134:40–8. https://doi.org/10.1016/j.ecolecon.2016.12.016.
[12] Chen Y. Does a regional greenhouse gas policy make sense? A case study of carbon leakage and emissions spillover. Energy Economics, 2009; 31:667–75. https://doi.org/10.1016/j.eneco.2009.02.003.
[13] Zhang Q, Fang K. Comment on “Consumption-based versus production-based accounting of CO2 emissions: Is there evidence for carbon leakage?”. Environmental Science & Policy, 2019; 101:94–6. https://doi.org/10.1016/j.envsci.2019.08.002.
[14] Chen L, Wemhoff AP. Predicting embodied carbon emissions from purchased electricity for United States counties. Applied Energy, 2021; 292:116898. https://doi.org/10.1016/j.apenergy.2021.116898.
[15] Ji C, Hong T and Kim H. Statistical analysis of greenhouse gas emissions of South Korean residential buildings. Renewable and Sustainable Energy Reviews, 2022; 156:111981. https://doi.org/10.1016/j.rser.2021.111981.
[16] Hong J, Shen GQ, Feng Y, et al. Greenhouse gas emissions during the construction phase of a building: a case study in China. Journal of Cleaner Production, 2015; 103:249–59. https://doi.org/10.1016/j.jclepro.2014.11.023.
[17] US EPA. eGrid Data 2022. https://www.epa.gov/egrid/download-data (accessed on November 08, 2023).
[18] Berrill P, Gillingham KT and Hertwich EG. Drivers of change in US residential energy consumption and greenhouse gas emissions, 1990–2015. Environ Res Lett, 2021; 16:034045. https://doi.org/10.1088/1748-9326/abe325.
[19] eGRID. eGRID2021 Technical Guide. 2021. https://www.epa.gov/system/files/documents/2023-01/eGRID2021_technical_guide.pdf (accessed on November 07, 2023).
[20] EIA. Comparing the 2020 RECS with Previous RECS and Other Studies. 2023. https://www.eia.gov/consumption/residential/data/2020/pdf/Comparing_2020_with_previous_RECS.pdf (accessed on November 16, 2023).
[21] EIA. 2020 RECS Technical Documentation. 2023. https://www.eia.gov/consumption/residential/data/2020/pdf/2020%20RECS_Methodology%20Report.pdf (accessed on November 16, 2023).
[22] US EPA O. Greenhouse Gases Equivalencies Calculator - Calculations and References 2023. https://www.epa.gov/energy/greenhouse-gases-equivalencies-calculator-calculations-and-references (accessed on October 23, 2023).
[23] Esri. USA Counties Generalized Boundaries - Overview 2022. https://www.arcgis.com/home/item.html?id=3c164274a80748dda926a046525da610 (accessed on November 17, 2023).
[24] Timmons D, Zirogiannis N and Lutz M. Location matters: Population density and carbon emissions from residential building energy use in the United States. Energy Research & Social Science, 2016; 22:137–46. https://doi.org/10.1016/j.erss.2016.08.011.
[25] Kuang B, Liu Z, Shi Y, et al. Characteristics and Influencing Factors of HVAC Energy Consumption in the US Residential Buildings. In Construction Research Congress, 2024. https://doi.org/10.1061/9780784485279.012
[26] Berrill P, Wilson EJH, Reyna JL, et al. Decarbonization pathways for the residential sector in the United States. Nature Climate Change, 2022; 12. https://doi.org/10.1038/s41558-022-01429-y.
[27] US EIA. State Energy Data System 2023. https://www.eia.gov/state/seds/ (accessed on November 08, 2023).
Copyright © 2024 Jianli Chen, Biao Kuang
Publishing time:2024-01-17
This work is licensed under a Creative Commons Attribution 4.0 International License
Email
Location