Apr 09, 2026

Modelling a Bovaer Strategy

This post breaks from the sector-by-sector analysis of the National Greenhouse Gas Inventory to do a bit of modelling: what would happen if Canada's beef and dairy farmers gradually transitioned to administering the feed additive Bovaer, which reduces methane emissions? A PlanZero model finds that it could eventually remove 10Mt of annual emissions, and cost about $222 per tonne removed.

Table of Contents:

Introduction

Several recent posts, indeed almost all of them, have been about replicating per-IPCC-sector emissions from the 2025 National Inventory Report. But the reason PlanZero is named as it is, is that it's supposed to include some models (potential plans) of the future. This post breaks from the series replicating emissions histories in order to test that the research on emissions histories is laying a useful foundation for modelling future scenarios. Specifically, it follows up on the recent post on Enteric Fermentation and looks at the potential impact if beef and dairy farmers were to gradually transition to administering Bovaer.

Bovaer is a brand name for a feed additive for cattle and sheep, also known as 3-Nitrooxypropanol, also known as 3-NOP. It is a synthetic organic compound (organic as in carbon-containing-molecules, not organic as in pesticide-free) that, when added to ruminant livestock feed in the correct manner, has the effect of inhibiting methane production in their first stomach. Bovaer is approved for use in Canada. The modelling presented in this post codifies assumptions about what Bovaer does, how much it costs, which kinds of cattle would consume it, that most farmers would adopt it at a certain price, how long it would take them to do so, how much it might cost to verify that farmers are administering it correctly, and what fraction of purchased Bovaer actually make it into cattle as intended vs. e.g. accidental waste. The results of the modelling are now included as part of a "Scaling" simulation on a revised simulations page, and specifically associated with the "Scale Bovaer" strategy.

This post does not establish a position on the question of whether Canada should fund Bovaer. There are a number of reasons not to leap to conclusions, foremost being that Bovaer is the only strategy implemented in the PlanZero model at this time so there's no comparison to alternatives. What the post does do, is calculate that under a set of modelling assumptions, Bovaer usage represents a strategy that can remove up to 10 Mt CO2e annually at a cost of about $222/tCO2e.

The post is organized as follows:

  • Review of Emissions Calculation for Enteric Fermentation: what factors drive enteric fermentation emissions, and how does the strategy aim to help?
  • A Model of Bovaer Adoption: through what time-varying variables does the adoption of Bovaer influence the annual emissions calculation?
  • Simulation Results: PlanZero models can be extrapolated into the future to produce hypothetical scenarios based on modelling assumptions. What does a future with Bovaer adoption look like?
  • Conclusion: what can we conclude from the simulation, results, and what's next for PlanZero?

Review of Emissions Calculation for Enteric Fermentation

Recall from this earlier post analyzing the enteric fermentation emissions, that the NIR-2025 enteric fermentation emissions were accurately approximated by a sum over (a) provinces and territories and (b) cattle types (dairy cows, beef heifers, calves, etc.), of an emissions contribution. Each emissions contribution was the product of

  • headcount: how many heads of each type of cattle there were (per-type, and per-region), and
  • emission factor: how much methane each type of cattle emitted on an annual basis, per head
This approximation was somewhat inaccurate by ignoring other livestock types such as sheep, swine, and poultry, but the emissions from cattle make up over 95% of the sector total, so the simplified estimator is about 95% accurate.

The headcounts (per-type, per-region) and emission factors (per-type, per-region) are the key time-varying quantities that support the calculation of enteric fermentation emissions. The next section explains a hypothetical Bovaer adoption process that affects these time-varying quantities and lowers emissions in future years beyond 2026.

A Model of Bovaer Adoption

This post imagines how Bovaer adoption might occur in Canada. Bovaer is approved for use in Canada, but there is not yet widespread adoption. Bovaer costs money after all, and it can presumably be harmful if administered improperly (e.g. too much at once) and it confers no economic benefit to farmers. This post supposes that some unspecified balance of federal and provincial governments decide to drive Bovaer adoption with subsidies.

The PlanZero model of this adoption process works by defining some of the key time-varying quantities supporting the enteric fermentation emissions calculation so that they take different values in future years depending on the level of Bovaer adoption. With regards to headcounts, the model in this post assumes that Bovaer adoption has no impact on headcounts. Bovaer is considered safe and the subsidy is not expected to be so large that it drives farmers into or out of the farming business. With regards to emission factors, the model in this post is that methane emissions from cattle will drop if Bovaer is administered; in particular, that it will drop according to published methane reduction rates from the manufacturer ( up to i.e. 30% for dairy cows, and 45% for beef cows, link). Whether the emission factors drop by 0% or 30% for dairy cows in a particular region depends on what fraction are consuming Bovaer. If no cattle are consuming Bovaer, then the drop in average methane emission per head will be 0% and if all of them are consuming Bovaer, then the drop will be 30%.

The fraction of cattle consuming Bovaer is a new time-varying quantity that is introduced by this model. The fraction of cattle on Bovaer starts at zero, and is modelled as either remaining constant, or increasing by 5% of farmers per year. I chose this number as providing a rate of change on a similar time scale to equipment turnover, as a general rate of change in farming operations. I imagined I was modelling the effect of a hypothetical farm subsidy program that paid farmers to administer Bovaer. It allows for a transition to nearly 100% Bovaer usage between 2030 and 2050. As the fraction of cattle on Bovaer starts at zero, and rises nearly to 100% over time, it drives several effects:

  • methane emissions from dairy cows drop by 30%, as per manufacturer claim
  • methane emissions from beef cows drop by 45%, as per manufacturer claim
  • methane emissions from other cattle drop by 40% (I guestimated this number, as being between 30% and 45%)
  • carbon emissions rise by 45 kg CO2e/head/year to account for the production of Bovaer (I guessed this number based on an AI recommendation)
  • subsidy payments to farmers rise to an average of $5000/farm/year (I estimated this number for a hypothetical subsidy program, so that it would be larger than the monitoring costs)
  • on-site monitoring costs rise to an average of $3000/farm/year (I estimated this number to budget for a a few multi-hour professional service calls using specialized equipment)
  • offsite-site monitoring costs rise to an average of $1000/farm/year (I estimated this number to be a relatively small fraction of the subsidy program)
  • Bovaer purchase costs rise to an average of $182/head/year for adult cattle, $127/head/year for steers and heifers, and $73/head/year for calves (based on estimates from this article on producer.com)
The fraction of cattle on Bovaer only rises to 99% instead of 100% to account for the fraction of farms that produce organic milk and dairy. I estimated that fraction to be about 1% (based on 3% of Canadian farms being organic in 2021 and most organic farms focusing on fruits and vegetables), and organic certification does not permit Bovaer usage. The model assumes a constant 160 cattle / farm on average, based on the actual number hovering around 160 in recent years. The production capacity of Bovaer is not modelled; it is assumed that sufficient production could be ramped up over this period of time to meet demand at the prices in the model. The model also doesn't model any change to farmers' insurance needs, although there may be some cost there as well that would add cost to the program. The model in this post implicitly assumes that it is a complete model, and that nothing else changes in the National Greenhouse Gas Inventory after 2026 except the gradual adoption of Bovaer.

The subsidy program assumed in this model is hypothetical, there is no current subsidy program at the federal level or in any province or territory that aims to work in this way.

Simulation Results

The PlanZero software can roll out the year-by-year consequences of the modelling assumptions above to create a hypothetical scenario covering future years. With the assumptions listed above, the following figure is what the inventory would look like out to 2050 and beyond.

For most sectors, the figure shows historical actuals until 2023, followed by constant projections. I want to make a habit of including this style of figure in strategy-analysis posts because I believe it is important to keep the big picture in mind. That said, the impact of Bovaer adoption is small, and does not stand out visually on the scale of national emissions in recent years (it reduces the total by about 1.3%). Ablative analysis (looking at simulation results with and without the strategy) can visualize the effects of a single strategy more clearly. The following two strategy-specific figures plot the impact on emissions, and required subsidies.

With regards to the emissions impact of Bovaer we see no reduction in emissions until 2030, when the modelled subsidy programs are in place. After 2030 we see a large decline in enteric fermentation emissions, and a small increase in "Other Product Manufacture and Use" to account for the production of Bovaer. For the "Enteric Fermentation" sector, we see a steady reduction in emissions from 2030 to 2050 as our simulated farmers adopt Bovaer at 5% per year. Enteric emissions are ultimately reduced by a little over 10 MtCO2e. At the same time, we see a steady (although smaller) rise in emissions in the "Other Product Manufacture and Use" sector, which ultimately rise to about 510 ktCO2e. After all eligible farms have adopted Bovaer, net annual emissions are reduced by 9.5 Mt CO2e.

In this second strategy-specific figure, the difference between the scenarios with and without Bovaer adoption is shown in terms of subsidy amounts. Here, we see the relative quantities of the four types of subsidy modelled as being required: purchasing Bovaer, offsite and onsite monitoring activities, and compensating farmers for the work and risk of administering Bovaer. The cost is modelled as rising to about $2.1 billion per year, without factoring in any currency inflation. Since Bovaer usage and cost is proportional and synchronous, the cost of emissions reduction from using Bovaer can be computed directly by dividing these two numbers: 2.1 billion dollars / 9.5 Mt CO2e equates to $222.94 / tCO2e.

Conclusion

With this post, PlanZero now includes a strategy for emission reduction (Scale Bovaer), and a model of the impact of that strategy. In this model, the strategy of paying farmers an average of $5000 / year to administer Bovaer is estimated to deliver up to 9.5Mt CO2e/year of emissions reductions by 2050 at a cost of about $222/tCO2e.

The strategy assumes government subsidy programs that do not exist at either the federal level or provincial level. I believe there will not likely be such a strategy any time soon, because Bovaer adoption is considered by industry experts to be too expensive. This PlanZero estimate of $222/tCO2e would be consistent with that assessment, in the sense that the benchmark price defined by e.g. Canada's Output-Based Carbon Pricing system has historically been less than $100/tCO2e, and has recently been re-negotiated to rise only to $140/tCO2e by 2040, instead of $170/tCO2e by 2030. A Bovaer strategy would have to be viable at e.g. $130/tCO2e in order for large emitters to pay into a Bovaer subsidy fund rather than simply pay the benchmark penalty rate into the more general OBPS fund.

Writing this first strategy-analysis post was difficult, and presented several behind-the-scenes challenges for me. I'd like to mention some of the biggest ones, so that I can link to GitHub Issues meant to serve as reminders that they need attention in the form of future work.

  • Ideally PlanZero would implement a dynamic bibliography, which would allow the implementation software to summarize the active set of assumptions when viewing standard analysis and summary pages for strategies and models (e.g. annotated links to data source, papers, website, books, other software, other models, etc.; gh issue re: Dynamic Bibliography)
  • The first version of this post was too long and scattered. I really like the linearity and typical scope of the posts so far; how can I work my way through big chunks of communication work when required? (Edit: this has been addressed to some degree through introducion of "Draft Status" as described in subsequent post "About this project..." April 12, 2026, although I still might prefer a system for hosting posts from un-merged branches.)
  • If this post is any indication, the modelling of multiple strategies across multiple sectors will be complicated. How should PlanZero organize and manage this complexity in terms of both communication and technical implementation? I've introduced terminology such as strategy, model, simulation, and scenario in this post, but I relied on their conventional English definitions. Unbeknownst to the reader, I was trying to use these terms according to precise meanings within a conceptual framework of PlanZero's modelling system, but the explanation of the conceptual framework was lengthy and distracted from the strategy-analysis narrative. How might I introduce this conceptual framework? (Edit: this conceptual framework has been introduced instead via a design documentation post "New: The PlanZero Glossary", April 19, 2026 and the glossary page on the PlanZero site; also, this page has been updated with links to the glossary.)
  • Probability and uncertainty is critical to this sort of modelling, and is completely absent from all PlanZero posts to date, including this one. Some of the assumptions made in this model are relatively coarse guestimates (will farmers be motivated at $5000?), some of the assumptions may be more precise (I expect the 30% methane reduction for dairy cattle depends on some factors, but has been studied and measured precisely), and some of the uncertainties will vary in time (the size of Canada's cattle herd can be estimated with relatively high certainty for 2026, and with ever-lower certainty ever-further into the future). I believe one of the greatest challenges to planning around climate change is that it's difficult to characterize and bear in mind all of the uncertainties involved. I would like for PlanZero's models, simulations, scenarios, analysis and visualizations to all work together to wrangle these various kinds of uncertainties into comprehensible results, but the multi-faceted effort required has hardly begun. I've created a few starting points such as Estimate some uncertainties around the Bovaer Strategy as a direct follow-up to this post, and Support uncertainty in timeseries values for some more foundational work, but I expect this to be more of a long-running theme than a discrete issue that can be defined and resolved.
  • PlanZero assumes decision-making entities will decide things in certain ways, such as farmers adopting Bovaer at $5000/year, and voters supporting governments that budget for subsidy programs. How might this decision-making be modelled rather than assumed? A similar phenomenon seems to come up with regards to the adoption of EVs and heat pumps at different rates in response to various subsidy amounts. I expect there are general models or patterns the sorts of behaviour change / technology adoption scenarios that PlanZero aims to model, but I don't know what they are, or when or how to use them.

On a more straightforward note, I think PlanZero is better off now with its first strategy analysis than it was before, and PlanZero should include more strategies. There are several large scale, large impact, low-cost strategies that are at various stages of planning and implementation on the national stage, which PlanZero should model in order to make informed predictions of future emissions:

All that said, I like to close with next steps, and the three highest priorities to address with follow-up work are, I think:

  1. Procedural: working with posts in a Draft Status [Edit: Addressed in "About this project..." April 12, 2026.]
  2. Documentation: thinking through and articulating the conceptual framework of PlanZero models [Edit: Addressed in "New: The PlanZero Glossary", April 19, 2026.]
  3. Handling and Communicating Uncertainty: what kinds of uncertainty are there, and how can they be reflected in PlanZero visualizations and analysis?
Draft-Status efforts for the first two are live on this site already, as I remove the Draft status from this post. Work has begun on the third area of priority, which will re-examine the simulation and analysis of this post with uncertainty estimates for both the baseline and Bovaer-usage scenarios.

Signing off until the next post,

- James Bergstra