This page explores carbon dioxide (CO₂) emissions in the United States from 1973 to 2025, broken down by energy source and economic sector. The stacked bar charts show how each sector relies on different fuels, while the line chart reveals national trends over time. Coal and petroleum emissions have declined sharply since the mid-2000s, while natural gas remains steady and renewables are gradually increasing. These patterns reflect shifts in energy policy, market dynamics, and environmental priorities.
Interpretation of Bar Charts: Electric power and industrial sectors show the largest declines in coal use, while transportation remains petroleum-heavy.
Interpretation of Line Chart:
National emissions from coal dropped by over 50% since 2008, while natural gas and biomass held steady.
These charts track U.S. renewable energy production and consumption over time, letting you compare how each source has grown and shifted in importance.
Summary table shows a steady increase in both production and consumption of renewable energy from 2000-2020
| Time Period | Total Consumption (Trillion Btu) | Total Production (Trillion Btu) |
|---|---|---|
| 2000–2005 | 19395.11 | 19385.38 |
| 2005–2010 | 23668.29 | 23625.63 |
| 2010–2015 | 31737.25 | 31927.04 |
| 2015–2020 | 36419.14 | 36994.01 |
Information on the data shown on this page
| Top 5 States (High → Low) | Solar consumption | Bottom 5 States (Low → High) | Solar consumption |
|---|---|---|---|
| California | 19775 | North Dakota | 0 |
| Texas | 15006 | West Virginia | 0 |
| Florida | 7802 | New Hampshire | 2 |
| North Carolina | 6598 | Alaska | 8 |
| Georgia | 4123 | Kansas | 40 |
The Summary table shows consumption trends of the top 5 fastest and slowest solar energy adopters. The Choropleth map of the United States shows which states consume the largest amount of solar energy. The lighter colors indicate higher solar consumption while darker colors represent lower amounts of consumption.
Highest Solar Consuming States Include: California, Texas, Florida, North Carolina, and Georgia
Lowest Solar Consuming States Include: North Dakota, West Virginia, New Hampshire, and Kansas
These charts compare solar electricity net generation across major categories in the United States using the most recent data from EIA Table 10.6. The goal is to show which parts of the energy system are producing the most solar power right now.
Solar electricity generation is concentrated in a few key categories. The tallest bars on the chart show where most solar power is being produced right now, while the shorter bars point to areas that still have room to grow.
This dashboard explores key energy trends in the United States from 1973 to 2025, focusing on emissions, renewable energy growth, solar generation, and U.S. solar energy generation comparisons.
Together, these findings demonstrate that U.S. energy policy has reduced coal reliance and expanded renewables, but strategic investment and regional incentives will be critical for closing adoption gaps and achieving leadership in solar generation.
Key Recommendations:Limitations: Current analysis is U.S.‑focused; future work could expand globally to compare trends across countries.
| 🔥 Emissions | 🌱 Renewables | ☀️ Solar Adoption | ☀️ Solar Generation Comparison | ⚖️ Energy Mix |
|---|---|---|---|---|
| Coal & petroleum largest emitters; coal decline since 2008 | Hydro led historically; solar & wind drive growth post‑2010 | Fast adopters: CA, NV, AZ, TX, FL; slow adopters: AK, WY, ND | Utility-scale dominates; small-scale sectors show slower growth | Fossil decline aligns with renewable rise |
| Year | Milestone |
|---|---|
| 1973 | Fossil fuels dominate U.S. energy mix |
| 2000 | Renewables begin steady growth |
| 2008 | Coal decline accelerates (>50% drop since peak) |
| 2010 | Solar & wind surge reshape renewable growth |
| 2025 | Renewables reshape U.S. energy mix |
For more information: - EIA Total Energy Data - The Pros and Cons of Solar Energy
This dashboard was created using Quarto in RStudio, and the R Language and Environment.
The dataset used to create this dashboard was downloaded from EIA Total Energy Data and World Bank Renewable Energy Statistics
Allaire J, Dervieux C (2024). quarto: R Interface to ‘Quarto’ Markdown Publishing System. R package version 1.4.4, https://CRAN.R-project.org/package=quarto.
Arnold J (2024). ggthemes: Extra Themes, Scales and Geoms for ‘ggplot2’. R package version 5.1.0, https://github.com/jrnold/ggthemes, https://jrnold.github.io/ggthemes/.
Bache S, Wickham H (2025). magrittr: A Forward-Pipe Operator for R. doi:10.32614/CRAN.package.magrittr https://doi.org/10.32614/CRAN.package.magrittr, R package version 2.0.4, https://CRAN.R-project.org/package=magrittr.
Dancho M, Vaughan D (2025). tidyquant: Tidy Quantitative Financial Analysis. doi:10.32614/CRAN.package.tidyquant https://doi.org/10.32614/CRAN.package.tidyquant, R package version 1.0.11, https://CRAN.R-project.org/package=tidyquant.
Kunst J (2022). highcharter: A Wrapper for the ‘Highcharts’ Library. R package version 0.9.4, https://CRAN.R-project.org/package=highcharter.
Neuwirth E (2022). RColorBrewer: ColorBrewer Palettes. R package version 1.1-3, https://CRAN.R-project.org/package=RColorBrewer.
Posit team (2025). RStudio: Integrated Development Environment for R. Posit Software, PBC, Boston, MA. URL http://www.posit.co/.
R Core Team (2025). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.https://www.R-project.org/.
Rinker, T. W. & Kurkiewicz, D. (2017). pacman: Package Management for R. version 0.5.0. Buffalo, New York. http://github.com/trinker/pacman
Wickham H, Averick M, Bryan J, Chang W, McGowan LD, François R, Grolemund G, Hayes A, Henry L, Hester J, Kuhn M, Pedersen TL, Miller E, Bache SM, Müller K, Ooms J, Robinson D, Seidel DP, Spinu V, Takahashi K, Vaughan D, Wilke C, Woo K, Yutani H (2019). “Welcome to the tidyverse.” Journal of Open Source Software, 4(43), 1686. doi:10.21105/joss.01686 https://doi.org/10.21105/joss.01686.
Xie Y (2025). knitr: A General-Purpose Package for Dynamic Report Generation in R. R package version 1.50, https://yihui.org/knitr/.
Yihui Xie (2015) Dynamic Documents with R and knitr. 2nd edition. Chapman and Hall/CRC. ISBN 978-1498716963
Yihui Xie (2014) knitr: A Comprehensive Tool for Reproducible Research in R. In Victoria Stodden, Friedrich Leisch and Roger D. Peng, editors, Implementing Reproducible Computational Research. Chapman and Hall/CRC. ISBN 978-1466561595
Zhu H (2024). kableExtra: Construct Complex Table with ‘kable’ and Pipe Syntax. R package version 1.4.0, https://github.com/haozhu233/kableExtra, http://haozhu233.github.io/kableExtra/.