Powered by Poverty: Energy Access and Income in the United States

Powered by Poverty

The clean-energy transition is real. The geography is not fair.

30% U.S. capacity from renewables in 2024

10 / 11 highest-poverty states are majority-fossil

84% known coal capacity predates 1990

The Time Window

The story starts with time because a single map can make the grid look fixed. It is not fixed; the U.S. capacity mix has been changing for decades.

Capacity and emissions run from 1990 to 2024 using EIA data. Income and poverty come from Census SAIPE 2024, the most recent year where both sources overlap.

Renewables grew from 12% to 30% of U.S. installed capacity over that span.

Fossil capacity fell from 72% to 58%. That is progress, but not replacement.

Closeread lets the argument narrow one step at a time: first the national shift, then the 2024 geography, then the socioeconomic question hidden inside that geography.

The U.S. grid has been changing for three decades. The question is whether that change reached everyone equally.

The Argument In One Sentence

National clean-energy progress hides a state-level split: the places with more poverty are often still more fossil-heavy, and coal/oil infrastructure is old enough that “legacy system” is measurable rather than rhetorical.

The 2024 Map

Freeze the timeline at 2024. The national transition becomes a state-by-state map.

The renewable leaders are VT, WA, ID, OR. The question is no longer whether clean energy exists; it is where it has accumulated, and where it has not.

The East Coast appears less renewable in this capacity view partly because dense, high-demand states have older gas, nuclear, and imported-power systems, while large utility-scale wind and solar buildouts need space, policy support, and transmission access.

The 2024 map shows who is ahead. The next maps show why some states are still behind.

Carbon Burden

This map shows total CO2 from electricity generation, not an emissions rate. Large, high-demand states will naturally produce more total carbon even if their mix is not the dirtiest.

Texas leads in total tons partly because it generates a lot of electricity for a large population, major industry, and a large power market. That is different from saying every megawatt-hour there is dirtier than elsewhere.

What the map shows is where carbon burden is concentrated, a useful equity question even without an intensity rate.

Scale Before Blame

Some high-emission states are also major industrial electricity states. EIA reports Texas as the top state for direct-use electricity in 2024 and Louisiana as the second-highest, which helps explain why their power systems are so large before we make any equity claim.

This is why the project separates system scale from equity exposure. Texas is the scale case: #1 in direct-use electricity and #1 in power-sector CO2. Louisiana is both an industrial scale case and a poverty case: #2 in direct-use electricity, 42 million metric tons of power-sector CO2, and one of the highest state poverty rates in the dataset.

New load growth adds another layer. DOE identifies data centers, AI, domestic manufacturing, and electrification as major drivers of rising U.S. electricity demand. That makes the equity question more urgent: the grid is not only cleaning up old demand, it is also being asked to power a more electricity-intensive economy.

Income Is Not The Whole Answer

The obvious explanation: wealthier states have cleaner grids.

The correlation between state median household income and renewable capacity share is only 0.08, essentially flat. Wealth alone does not explain where clean energy has been built.

Policy, geography, legacy infrastructure, and utility markets all shape the grid in ways income cannot predict.

The map changes when you switch lenses.

Poverty Is The Equity Lens

Switch from income to poverty, and the geography sharpens.

The highest-poverty states include LA (84% fossil), MS (80% fossil), WV (91% fossil), NM (40% fossil), KY (91% fossil); most of them still majority-fossil.

National clean-energy averages hide real disparities.

The transition should be evaluated state by state, especially for communities with the fewest resources to absorb aging infrastructure, rising costs, or investment that arrives late.

State averages are where the story begins. The real divide runs county by county.

State Averages Hide Local Reality

A state average flattens everything inside it. Within the same state, counties can sit on opposite ends of the income distribution.

State outlines stay visible so local patterns are easier to read against the geographic context.

The Poverty Belt

County poverty is not randomly scattered. The rural South, Appalachia, and parts of the Southwest come up again and again, even when state borders are visible.

These are the communities with the fewest resources to absorb rising energy costs, aging infrastructure, or investment that arrives late.

Coal and Appalachia

Coal plants are not confined to one place, but the Appalachian cluster is visible. That matters because the region also contains many counties with high poverty, making it a clear example of overlapping economic vulnerability and legacy fossil infrastructure.

Dominance of Gas

Gas plants are numerous throughout the US, with more than 1,800 spread across the coasts and eastern states.

Here the point layer complicates the story instead of confirming a simple claim. Gas plant locations appear less tied to poverty itself and more tied to infrastructure geography, including proximity to water for cooling and dense regional demand.

Midwest and Coastal Oil

Oil plants cluster in the East Coast and Midwest, where county poverty is often more moderate than in the South and Appalachia.

Poverty, fuel type, demand, geography, and history do not move together in one simple pattern. The geography of fossil infrastructure is shaped by more than poverty alone.

Compare Fossil Plant Geography

The fuel-specific scrolls isolate coal, gas, and oil. This combined view lets the reader compare those patterns directly: hover a fuel type to dim the others and see where each fossil system is concentrated.

When the plants were built

84% of known U.S. coal capacity was commissioned before 1990. Median commissioning year: 1980. Oil is similar at 80%.

Where the Burdens Collide

Four variables in one frame: poverty rate on x, fossil capacity share on y, power-sector CO2 as point size, and renewable share as color.

The upper-right quadrant is where all four burdens land at once.

10 of the 11 highest-poverty states are majority-fossil.

These are not the same case. Some are industrial-scale emissions stories. Some are poverty stories. Some are both, and those are the sharpest equity questions.

The patterns are measurable. The relationship is not strict. But it is consistent enough to ask who is still waiting.

Poverty and Renewable Capacity

The slope is modest but it points in the expected direction: states with higher poverty rates tend to have less renewable capacity.

Poverty and fossil capacity correlate at 0.33. Poverty and renewable capacity correlate at -0.29.

The Double Burden

Higher poverty also tracks with higher total power-sector CO2, though total emissions reflect state size and electricity demand as well as fuel mix.

The two burdens tend to land in the same places.

For an equitable transition, the question is not only how fast the United States cuts emissions.

It is who gets cleaner infrastructure first, and who is still waiting.

A cleaner grid is not automatically an equitable grid.

This project combines EIA electricity data with Census SAIPE income and poverty data to make one point visible: energy transition maps and poverty maps should be read together.

The evidence is not causal, and it is not the final word. But it is strong enough to shape the next question.

When public and private clean-energy investment expands, which communities are first in line?