Simulating how carbon markets work in the wild

For about a year, I’ve been building a Python-based simulation model that mirrors how large-emitter trading systems behave in the wild. These industrial carbon pricing systems look somewhat uniform on paper but operate very differently once you dig into the design details. Each province runs its own version, with distinct compliance obligations, offset rules, and limits on what counts toward compliance.

At first glance, the $170 carbon price looks like the great equalizer. But once you layer in offset availability, credit banking, use-limit rules that dictate how much must be paid at the ceiling price, and the effects of past oversupply, the market dynamics and outcomes start to diverge sharply.

That’s where the model comes in. The Large Emitter Market Simulator (LEMS) is built to toggle these design features on and off, including tightening rates, offset use limits, banking rules, price floors and ceilings, investment credits, and fund payment options so each provincial system can be represented as it actually works. Each year, the model calculates facility-level obligations, credit supply and demand, and market balance, adjusting prices depending on whether the system is in surplus, shortage, or equilibrium.

What emerges is a more realistic picture of how Canada’s large-emitter markets function. The model reveals when oversupply keeps prices soft, when tightening drives scarcity, and how new policy changes ripple through the market. I’ve been refining the framework and over the coming months, I’ll be rolling out insights that show how these simulated markets respond as governments reform their systems – and what modernized systems could look like as the federal government updates both their backstop and the benchmark.

To start, the most recent application focuses on the 2025 reforms to Alberta’s TIER system: TEIRy-eyed and off balance: Alberta’s TIER reforms. Read it here.