Clean Power Delayed: Effects of Infrastructure Delays on Health, Environment, and US Households

Electricity transmission and generation investments are necessary for maintaining a reliable power grid and achieving air pollution and climate goals. However, in the United States in recent years, the typical development time for additions to the electricity transmission system has been 10 years (Solomon 2023). For new generation facilities, the typical development time from interconnection request to commercial operation is 5 years, up from 2 years in 2008 (Rand et al. 2024). There has been much recent discussion of factors that contribute to these lengthy timelines and of potential reforms to reduce them. In this paper, we estimate the extent to which lengthy development timelines, or delays, affect the power system and consequently emissions, public health, and people’s pocketbooks. We also estimate how these costs and benefits accrue to different demographic groups.To estimate the impacts of such delays, we simulate the power system in the year 2032 three times: with no delays, with transmission delays, and with generation delays. We then compare the results. The comparison indicates that the lengthening of transmission and generation capacity development times in recent years increases emissions enough to cause hundreds of premature deaths for each year that the long development times persist. Low-income households, Black-headed households, and Hispanic-headed households are disproportionately harmed by the delays. Rural households are disproportionately low-income.We use a detailed model of the US and Canadian power sector, the Engineering, Economic, and Environmental Electricity Simulation Tool (E4ST). The model incorporates a natural gas market model and projects generator construction, retirement, and hourly operation, as well as other outcomes, in each scenario. We then use a detailed air pollution model to estimate the effects on fine airborne particulate matter (PM₂.₅) concentrations and on the deaths caused by those PM₂.₅ changes. Finally, we use the RFF Incidence Model to estimate the value of the economic and mortality impacts for different demographic groups.To represent the transmission and generation delays, we shift a set of transmission system additions and a set of generation capacity additions from being completed by 2032 to being completed after 2032. We shift a set of real, anticipated new transmission lines in the transmission delay scenario. In the generation delay scenario, we shift 20 percent of four generator types’ new generation capacity that our model predicts would otherwise be built between 2028 and 2032. The 20 percent reduction applies to each major type: wind, solar, gas, and energy storage. The delayed transmission system additions have an annualized cost of approximately $5 billion, creating an annual investment cost savings benefit from each year of delay that will be compared with other costs and benefits of the delay. With our central set of background assumptions—that is, in our central case—the delayed generation capacity additions also have an annualized cost of $5 billion. The set of delayed additions that we model represents only a fraction of total transmission or generation infrastructure projects currently in various stages of development in the United States and Canada.Our central set of background assumptions includes the US Inflation Reduction Act tax credits for new nonemitting generators and existing nuclear generators. It omits the 2024 EPA greenhouse gas rules and the 2023 Good Neighbor Plan for NOx emissions, both of which are expected to be revised under the current administration. In three alternative sets of background assumptions (sensitivity cases), we employ different policy assumptions or technology costs.Both the transmission and generation delays result in a net increase of emitting generation, which causes negative health and other environmental outcomes. In our central case, the transmission delays have the following estimated effects (compared with the scenario without the delays):These delays increase power sector emissions of greenhouse gases in 2032 by 9 percent, NOₓ by 10 percent, SO₂ by 8 percent, and PM₂.₅ by 9 percent. For comparison, the average annual rate of greenhouse gas emissions reduction in the US power sector from 2005 through 2023 was 3 percent.The increased 2032 emissions cause an estimated increase in premature deaths from PM₂.₅ and ground-level ozone by 350 and 370, respectively.The increased 2032 emissions increase estimated net environmental damage by $31 billion, of which $9 billion is due to health damage from particulate matter and ground-level ozone and $22 billion is due to climate damage.Across the central and sensitivity cases, the effects of the transmission and generation delays are similar to each other. In our central case, the generation delays have the following estimated effects:These delays increase power sector emissions of greenhouse gases by 7 percent, NOₓ by 7 percent, SO₂ by 6 percent, and PM₂.₅ by 7 percent.The increased 2032 emissions cause an estimated increase in premature deaths from PM₂.₅ and ground-level ozone by 290 and 250, respectively.The increased 2032 emissions increase estimated net environmental damage by $24 billion, of which $7 billion is due to health damage from particulate matter and ground-level ozone and $17 billion is due to climate damage.Our companion paper presents the economic costs and benefits. When we consider the economic and environmental costs and benefits of our central case together, we find that the total net cost of the transmission delays in 2032 is $24 billion, and the total net cost of the generation delays is $23 billion, after subtracting the $5 billion capital cost savings from each. The transmission delays we model increase environmental damage more than the generation delays we model, but they increase energy bills less. In addition, the effects of the delays on electric supply reliability are likely to be substantial and create additional costs, as discussed in our first paper.We find that the net costs of the delays are not uniformly distributed. Rather, the delays disproportionately harm low-income, Black, and Hispanic individuals. In our central case, the delays are not just regressive; they are hyper-regressive: Not only do the households in the highest income quintile bear a smaller cost; on average, they benefit from the delays at the expense of the households in the other quintiles, which are harmed by the delays. The delays increase energy producer profits and reduce taxes. Those effects disproportionately benefit the top income quintile and are larger than the health and utility bill costs for that quintile. Once reliability and climate change are taken into account, the delays might be net harmful for the highest income quintile as well, but we do not produce monetary estimates of those costs broken out by demographic groups.Black- and Hispanic-headed households are disproportionately harmed mainly because their health is more sensitive to a given increase in airborne particulate matter and because they benefit relatively little from increased energy producer profits and reduced taxes. Black individuals also tend to live in locations where the delays increase airborne particulate matter more than the average. On average, a Black individual is more than four times as likely to die prematurely because of increased particulate matter caused by transmission or generation delays as a White individual. Black and Hispanic-headed households, which constitute just 31 percent of the population and have lower average incomes, bear more total estimated net costs from delays than White-headed households, which constitute approximately 60 percent of the population.The results of the sensitivity cases are similar to the central case results. While the transmission and generation development delays produce some benefits in terms of higher energy producer profits and lower taxes, the costs via higher prices, shorter lives, and environmental harms are considerably larger. Black, Hispanic, and low-income people are, on average, the most harmed.