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Edited by M. Granger Morgan, Carnegie Mellon University, Pittsburgh, PA, and approved June 4, 2020 (received for review December 18, 2019)
Article Figures & SI
Figures
- Fig. 1.
Energy and GHG intensity of homes in 2015 by US state. (A) Household energy intensity represented by kilowatt-hours per square meter (kWh/m2) by state (Upper). (Lower) Scatterplots show energy intensity correlations with annual sum of daily average deviation from ∼18 °C (65 °F), degree days (Left) (n = 49, P value = 4.4 e-16, r = 0.87), and average year built (Right) (n = 49, P < 5.6 e-10, r = −0.75). (B) Household GHG intensity represented by kilograms CO2-equivalents per square meter (kg CO2-e/m2) by state (Upper). Scatterplots showing its correlations with household energy intensity (Left) (n = 49, P = 0.002, r = 0.43) and carbon intensity of the electrical grid (Right) (n = 49, P = 5.2 e-12, r = 0.80).
- Fig. 2.
Influence of income on living area and household energy emissions. (A) Boxplots of per capita emissions of households classified as high income (n = 7,141) or low income (n = 1,717) according to the US Department of Housing and Urban Development’s 2015 poverty thresholds. Outliers not shown but included in calculation of averages (red lines). (95% C.I.: 0.52–0.62, P < 2.2 e-16, t test) (B) Scatterplot of per capita income against per capita living area. Income is plotted on natural logarithmic axes (n = 8,858, P < 2.2 e-16, r = 0.57). (C) Scatterplots of per capita income against per capita emissions for Illinois (Upper Left) (n = 101, P = 3.05 e-10, r = 0.58), Ohio (Upper Right) (n = 364, P < 2.2 e-16, r = 0.58), Arizona (Lower Left) (n = 178, P < 2.2 e-16, r = 0.72), and Texas (n = 574, P < 2.2 e-16, r = 0.55).
- Fig. 3.
Carbon footprints from household energy use in Los Angeles and Boston. (A) Map of per capita emissions across Los Angeles. Scatterplots show relationships between per capita emissions and income (Upper) (n = 6,800, P < 2.2 e-16, r = 0.55), density (Middle) (n = 6,800, P < 2.2 e-16, r = −0.15) and distance from downtown (Lower) (n = 6,800, P < 2.2 e-16, r = −0.16). (B) Map of per capita emissions across Boston. Scatterplots show relationships between per capita emissions and income (Upper) (n = 3,079, P < 2.2 e-16, r = 0.54), density (Middle) (n = 3,079, P < 2.2 e-16, r = −0.49) and distance from downtown (Lower) (n = 3,079, P < 2.2 e-16, r = 0.20). Income and density are plotted on natural logarithmic axes. Diameter of circle graph is proportional to total emissions.
- Fig. 4.
Pathways to the Paris Agreement targets in 2025 and 2050 for residential energy use. Scenarios 1–4 for decarbonization of the electrical grid, home energy retrofits, and addressing in-home fuel use. Scenario 1: reference scenario of projected grid decarbonization and home retrofit rates according to the US Energy Information Administration. Scenario 2: aggressive energy retrofits of households. Scenario 3: aggressive home energy retrofits and grid decarbonization. Scenario 4: grid decarbonization, aggressive home energy retrofits, and distributed low-carbon energy. Results are for 8,588 ZIP codes in the United States (A), 3,079 block groups in Boston (B), and 6,800 block groups in Los Angeles (C).
- Fig. 5.
Built form and the Paris Agreement 2050 target. Attributes of neighborhoods meeting the Paris Agreement target in scenario 4 relative to the 2015 average in each state and two case cities for FAC (A), population density (persons/km2) (B), and percentage of single-family homes (C). Nonvalues indicate no difference between communities meeting the 2050 Paris target in scenario 4 and 2015 average. North Dakota not shown, since it lacked communities that met 2050 Paris target. Results for all scenarios in SI Appendix, Tables SI-30–32.
Tables
- Table 1.
Four decarbonization scenarios: The scenarios model pathways for GHG emissions reductions for existing US households to 2050
Scenario Electrical grid Energy retrofit rate (annual %) Efficiencies of appliances, home electronics, heating and cooling equipment Distributed low-carbon energy 1. Baseline Energy Information Administration (EIA) projection to 2050 (current trends) 1.1 Average Minor contributions to grid 2. Aggressive Energy Retrofits EIA projection to 2050 (current trends) 1.7 High Minor contributions to grid 3. Grid Decarbonization with Aggressive Energy Retrofits EIA projection to 2050 (current trends) 1.7 High Minor contributions to grid 4. Distributed Low-Carbon Energy 80% decarbonization relative to 2005 1.7 High + additional heat pumps Household solar water and photovoltaics; local combined heat and power
Data supplements
Supporting Information
The carbon footprint of household energy use in the United States
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