US Carbon Transition Risk: The Highwire Act of Municipal Credit Impairment and Climate Justice

  • Carbon is a massive financial liability for the U.S.: Using the Biden administration’s Social Cost of Carbon (SCC) of $51 per metric ton of CO2 applied to Scope 1 emissions in the contiguous US, there is ~$294B in annual carbon transition risk liability. In the electricity production sector alone, that liability still stands at ~$116B.
  • Areas with some of the worst physical climate risk contribute the most emissions: Texas and Florida, two states with outsized physical climate change risk, have the highest electricity production Scope 1 CO2 liabilities, with the former totaling $13.5B on its own, or 12% of the US total. Locally, Harris County, TX and Jefferson County, AL lead the way among counties. The former saw significant destructive climate events in recent years, while the latter is legendary in the municipal bond community for its debt-defaulting financial challenges.
  • Municipal debt issuing communities’ carbon transition risk swamps their pension liabilities: Across 334 debt-issuing counties across 5 states, 92% of counties with available pension data have larger total Scope 1 emission liabilities aggregated over all greenhouse gas sectors than pension liabilities — an issue that itself has led the list of municipal market concerns for years.
  • Communities vulnerable to carbon transition risk also have outsized employment risk and education gaps: A socioeconomic vulnerability analysis using all US census tracts shows that communities with the highest per capita electricity emissions are those with the highest levels of risk from an employment sector perspective, have significantly lower educational attainment levels and more health risks.
  • Black populations near power plants suffer from disproportionate health risks: Although the direct relationship between racial settlement patterns and carbon intensive electricity production is complex, education gaps and health risks (themselves being directly correlated to carbon intensity of electricity production) are significantly higher for communities of color.
  • Carbon transition and flood risks present a double-edged sword: For communities with non-zero electricity production, flood risk — which is demonstrably linked to negative outcomes for property value, mortgage delinquency and population loss — is positively correlated with per capita emissions. Communities with high flood risk and significant transition risk are particularly vulnerable to the double-edged climate sword.
  • Municipal debt stakeholders have a crucial role in catalyzing a just transition away from fossil fuels: The combination of federal, state, and local jurisdictions and fixed income investors can and should explicitly incorporate views and data on carbon emissions into risk management and ESG-related decisions. Communities that are currently heavily dependent on fossil fuel — and especially those that are vulnerable from employment, educational, racial, and municipal credit perspectives — can and should be proactively targeted by appropriate public and impact investing capabilities.

Carbon Transition Risk: A Local Problem for Local Economies

Electricity Emissions as a Liability: Data and Approach

Texas and Florida: Carbon Transition Risk to go with their Physical Climate Risk

Figure 1: State-level population and emissions figures for all contiguous US states plus the District of Columbia, with focal states highlighted.
Figure 2: Rankings (top) and values of absolute tCO2 liability $ figures (bottom) for selected counties across the 5-state group, as well as tCO2 liabilities denominated in terms of each county’s assets, revenues, and assessed values, according to each county’s most recent year of reported data.
Figure 3: Population-weighted dot plot of counties in the 5-state group (+ Jefferson County AL); EP tCO2 liability is provided on the y-axis, and total county assets on the x-axis. Counties in the top left represent those that are most vulnerable.

Socioeconomic Vulnerability & Electricity Production

Figure 4: Using all census tracts (N=9,380) with non-zero electricity production emissions, per capita emissions are log-transformed and then grouped into 5 bins with a simple univariate k-means clustering algorithm. Distributions of risQ’s Health Obstacle Score are shown for each emissions bin. Each point is a census tract, colored by percentage of population that is white alone and sized by population density.
Figure 5: The same is shown as Figure 4 but for the At-Risk Employment Score.
Figure 6: The same is shown as Figure 4 but for the Low Educational Attainment Score.
Figure 7: The same is shown as Figure 4 but for the Flood risQ Score.

Insights for US Fixed Income Participants


The Social Cost of Carbon

County-Level Case Studies

New York: Nassau County

Ohio: Gallia County

Texas: Titus County

Mississippi: Attala County




We quantify climate risk, carbon transition risk and social impact for US Fixed Income, covering the full municipal bond and MBS universes

Love podcasts or audiobooks? Learn on the go with our new app.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
risQ, Inc.

risQ, Inc.

We quantify climate risk, carbon transition risk and social impact for US Fixed Income, covering the full municipal bond and MBS universes

More from Medium

Is reading too much negative news harmful for youth activists?

Panasonic’s Green Impact: More than a Commitment, a Dedication to the Future

The Secret Weapon for Net-Zero Cities:

COP26: A Reewild Perspective.