Maryland has committed to cutting greenhouse gas emissions 60% by 2031 and reaching net zero by 2045 — among the most ambitious climate targets of any U.S. state. But setting a target is the easy part. The hard part is designing a carbon pricing system that actually works: one that cuts emissions, generates revenue for the clean energy transition, and protects the communities that can least afford higher energy costs.
That is what this toolkit is built to do.
What it does
The Maryland Carbon Pricing Toolkit is a set of four Python scripts that take you from raw federal data to a complete policy analysis in minutes. It pulls real emissions data from two public APIs — the Federal Reserve Economic Data (FRED) service for state-level CO2 trends and the EPA Greenhouse Gas Reporting Program for facility-level emissions.
This is a partial equilibrium model. Unlike complex "black box" Computable General Equilibrium (CGE) models often used by large consulting firms, this toolkit focuses purely on the direct relationship between price signals and emission reductions. This makes the logic transparent and the code accessible to anyone with a laptop, allowing for rapid iteration of policy scenarios.
The scripts generate exploratory charts, model revenue under four pricing scenarios, and produce an implementation roadmap from 2026 through 2030.
Why Maryland, why now
Maryland already participates in the Regional Greenhouse Gas Initiative (RGGI), which prices carbon from the power sector. But electricity is only about 21% of the state's emissions. Transportation — cars, trucks, planes — accounts for 53%. An economy-wide carbon price would cover the sectors that RGGI cannot reach.
The toolkit focuses on Prince George's County as a case study because the stakes there are especially high. It is Maryland's second-most-populous county, home to nearly a million residents, 47% Black and 20% Hispanic. Any credible carbon pricing policy has to grapple with who pays and who benefits. The analysis models progressive household rebates funded by carbon revenue, ensuring that lower-income families come out ahead.
The "Open Economy" Reality Check
State-level carbon pricing is notoriously difficult to model because states, unlike nations, have open borders. Businesses can move trucking depots to Virginia; consumers can drive to Delaware for gas. This phenomenon, known as "leakage," is difficult to capture without a full CGE model that accounts for trade flows and macroeconomic feedback loops.
Because this toolkit does not model that cross-border friction, the results below should be viewed as optimistic upper bounds. A full legislative fiscal note would likely show slightly lower revenues due to this leakage. However, for the purpose of a policy brief or proof-of-concept, this model establishes the necessary baseline of what is possible before the friction of the real world applies.
Key findings
Under the recommended hybrid scenario — a $20 per ton starting price, increasing $3 per year, covering 82% of emissions — the model projects significant revenue potential.
That revenue can fund $400 to $600 in annual household rebates, expand public transit, retrofit buildings, and establish a just-transition fund for workers and communities affected by the shift away from fossil fuels.
Open source, open data
The entire toolkit is open source. The data comes from public federal APIs — no proprietary datasets, no paywalls. Anyone can fork the repository, swap in a different state's FIPS code, adjust the price elasticity, or add new scenarios. It is designed so that a policy staffer, graduate student, or community advocate can run the full analysis on a laptop in under five minutes.
The data is public. The tools are free. The climate targets are set. What remains is the political will to price carbon and the analytical rigor to design it well. This toolkit is a contribution to both.
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