What this planner does
Buying carbon removal is not the same as receiving verified tons by the date your organization plans to claim them. Projects can slip, MRV (measurement, reporting, and verification) can take longer than expected, and supplier performance can vary across pathways such as direct air capture, biochar, mineralization, or enhanced weathering. This Delivery Assurance Portfolio Planner helps you translate those uncertainties into a small set of practical portfolio metrics: how much to contract, what you can reasonably expect to receive on time, and what the financial exposure may look like if the portfolio misses its target.
The model is intentionally lightweight. It is meant for early-stage planning, internal discussions, budget conversations, and scenario testing rather than contract administration or audited valuation. That makes it especially useful when a procurement team needs to compare strategies that feel quite different in practice: a smaller purchase with higher confidence, a larger buffered purchase with lower confidence, or a more diversified mix that may cost more to manage but improves delivery assurance. Throughout this page, tons are treated as portfolio-level tons of carbon removal, percentages are entered as percent values rather than decimals, and the results should be read as expected values rather than promises.
In plain language, the calculator asks a simple question: if your target is a certain number of delivered tons by a deadline, how much extra do you need to contract so that ordinary delivery risk does not leave you short? The answer depends on your assumptions about reliability, price, diversification, and the cost of missing. By forcing those assumptions into one place, the planner gives procurement, climate strategy, finance, and leadership teams a common way to discuss tradeoffs that are often described only qualitatively.
How to use the calculator
A good workflow is to start with the operational requirement and only then move to economics. First enter the volume you actually need on time for a reporting year, compliance date, or public milestone. Then enter a weighted average contract price across the portfolio you expect to sign. After that, estimate the weighted on-time delivery probability for the same portfolio. If you are uncertain, begin with a conservative assumption and test higher and lower cases rather than pretending you already know the answer precisely.
- Set your target tons. This is the delivered volume you need to count by the deadline.
- Enter your average price. A weighted average is usually better than a simple average because large contracts should influence the estimate more than tiny ones.
- Estimate on-time delivery probability. Use a portfolio-level probability that contracted tons arrive by the target date.
- Choose a buffer. Buffer means over-contracting above the target so late or underperforming projects are less likely to create a gap.
- Set a penalty per shortfall ton. This can stand in for make-good purchases, contractual damages, internal compliance consequences, or reputational cost.
- Add a diversification bonus. If you believe a spread of suppliers or pathways reduces concentration risk, enter the percentage here.
- Set discount rate and delivery delay. These inputs add a basic time-value-of-money adjustment to the shortfall penalty.
- Click Plan Portfolio. Review the result, then change one assumption at a time to see what matters most.
That last step is more important than it sounds. The real value of the planner usually comes from comparing scenarios, not from freezing on a single output. Try one case with a lower reliability estimate, another with a larger buffer, and a third with a higher shortfall penalty. When you do that, the conversation shifts from vague optimism or caution to a clearer question: which assumption is really driving the decision?
Core concepts and formulas
The calculator summarizes a portfolio using a small set of inputs. A target tells you what must arrive on time. A buffer tells you how much extra volume you are willing to contract above that need. Reliability converts that nominal purchase into an expected delivered amount. Diversification is a simplified adjustment that nudges reliability upward when you believe a spread of suppliers or pathways reduces concentration risk. Penalties turn any remaining expected shortfall into a cost signal that is easier to compare with procurement spending.
- Target delivered carbon removal: the tons you need to receive on time.
- Buffer purchase: extra contracted tons above the target, expressed as a percentage.
- On-time delivery probability (p): the portfolio-level probability of on-time delivery.
- Diversification bonus: a simplified adjustment that increases reliability to reflect risk reduction from spreading purchases across suppliers or pathways.
- Penalty per shortfall ton: the cost applied to any expected shortfall, modeled linearly.
Expected contracted tons.
Contracted tons are calculated from the target and buffer:
ContractedTons = TargetTons × (1 + BufferPercent/100)
This is the first practical planning question many teams need to answer. If the target is 50,000 tons and the buffer is 35%, the discussion is no longer really about 50,000 tons. It becomes a discussion about whether the team is comfortable contracting 67,500 tons to improve confidence in on-time delivery.
Adjusted reliability with diversification.
The calculator applies diversification as a multiplier on the on-time probability and caps the result at 100%:
AdjustedReliability = min(1, (p/100) × (1 + DiversificationBonus/100))
This step is intentionally simple. In real procurement, diversification may reduce exposure to one developer, one feedstock source, one geography, one permitting regime, or one MRV bottleneck. It can also disappoint if those risks are more correlated than expected. For that reason, the diversification bonus is best treated as a scenario lever rather than a scientific law.
Expected delivered tons and shortfall.
Expected delivered tons are contracted tons multiplied by adjusted reliability:
Expected shortfall exposure is the remaining gap to the target, floored at zero:
Shortfall = max(0, TargetTons − ExpectedDelivered)
This output matters because it separates a portfolio that is expensive from a portfolio that is risky. Two strategies can have similar spend but very different shortfall exposure. When shortfall is zero in this calculator, it means the portfolio clears the target on an expected-value basis. It does not mean every delivery path is safe, only that the average expected result is above the line.
Costs, penalties, and discounting.
Procurement cost and expected penalty value are:
ProcurementCost = ContractedTons × AvgPrice
PenaltyValue = Shortfall × PenaltyPerTon
To account for delivery delay and discount rate, the calculator uses:
The NPV shown by the calculator follows the page JavaScript logic:
NPV = ExpectedDelivered × AvgPrice − ProcurementCost − PenaltyValue / DF
Important: this NPV is a simplified planning metric. It effectively values expected delivered tons at the assumed average price, subtracts procurement cost, and discounts the penalty over the delay period. Real contracts may have staged payments, milestone-based pricing, escrow terms, revenue implications, insurance, or accounting rules that make a fuller valuation necessary. The NPV line is therefore most useful as a directional comparison tool across scenarios that use the same logic.
Worked example
Assume a team needs 50,000 tons delivered on time. They estimate a 72% on-time probability, plan a 35% buffer, and assume a 12% diversification bonus. Average price is $425 per ton.
- Contracted tons: 50,000 × (1 + 0.35) = 67,500
- Adjusted reliability: 0.72 × (1 + 0.12) = 0.8064, or 80.64%
- Expected delivered: 67,500 × 0.8064 ≈ 54,432
- Shortfall: max(0, 50,000 − 54,432) = 0
- Procurement cost: 67,500 × $425 = $28,687,500
That example shows what the buffer is really accomplishing. Without the buffer, 50,000 contracted tons at 80.64% adjusted reliability would only produce about 40,320 expected delivered tons. In other words, the portfolio does not become safer simply because the mix feels diversified. It becomes safer when diversification is combined with enough contracted volume to absorb the remaining risk of delay or under-delivery.
It is also a reminder that expected-value success and downside resilience are not the same thing. In this example, the expected delivered number exceeds the target, so the shortfall line is zero. A cautious buyer might still test a weaker reliability assumption to see how quickly that comfortable-looking margin disappears. If the answer changes sharply, the strategy may still be fragile even though the base case looks good.
Scenario comparison
This table gives quick intuition for how buffer and diversification can change expected delivery. It is illustrative only. The exact values you use should come from your own project diligence, pathway mix, contract structure, and internal definition of what counts as on-time delivery.
| Scenario | Buffer (%) | Diversification bonus (%) | Approx. contracted tons | Approx. E[delivered] (tons) | Approx. shortfall (tons) | Qualitative risk |
|---|---|---|---|---|---|---|
| Low buffer, no diversification | 10% | 0% | 55,000 | 39,600 | 10,400 | High |
| Moderate buffer, moderate diversification | 35% | 12% | 67,500 | 54,432 | 0 | Low |
| High buffer, strong diversification | 60% | 25% | 80,000 | 72,000 | 0 | Low |
Notice what stays constant and what changes. The target is the same in every row, but the portfolio design is not. A low buffer can leave a visible expected gap even if the team feels comfortable with the supplier mix. A higher buffer can eliminate expected shortfall, but it also raises spend and may create more procurement complexity. Diversification helps in the model, yet it cannot rescue a portfolio that is under-contracted by too much. That is why it is useful to think of reliability, diversification, and buffer as interacting levers rather than isolated settings.
Assumptions and next steps
This planner is intentionally simplified, so the best use of it is disciplined comparison rather than false precision. It works with one weighted on-time probability instead of modeling each supplier, contract, milestone, and verification schedule separately. It treats diversification as a single bonus capped at 100% reliability. It applies shortfall penalties linearly to expected shortfall and discounts only that penalty over the delay period. It does not model correlation matrices, staged deliveries, changing market prices for make-good purchases, or non-linear reputational consequences.
- Portfolio-level aggregation. A single probability stands in for many contracts and delivery paths.
- Diversification is simplified. The bonus is a scalar multiplier, not an explicit correlation model.
- Shortfall penalties are linear. Real impacts may escalate sharply around public milestones or compliance deadlines.
- Discounting is basic. Payment schedules, financing structures, and milestone disbursements are not represented.
- Definitions vary. On-time delivery could mean verified credits, issued removals, physical completion, or another internal milestone depending on your program.
The practical next step is to stress-test the assumptions that matter most. Lower the reliability estimate, increase the penalty, or extend the delay to see how much buffer you need to preserve confidence. For committee review, it is often helpful to document where the probability estimate came from, which suppliers dominate the weighted average price, and why the diversification bonus is or is not justified. That short narrative often matters as much as the final number because it reveals how dependent the strategy is on a few uncertain beliefs.
Practical interpretation and input tips
Carbon removal portfolios often combine multiple suppliers and pathways, each with different construction timelines, MRV processes, feedstock dependencies, and operational risks. This planner gives teams a consistent way to discuss delivery assurance using a compact set of assumptions. It is especially helpful when you need to explain buffer logic to finance, compare two procurement strategies, or quantify the cost of being wrong about delivery timing.
What the results mean.
Total tons to contract shows how much volume you would need to sign for once buffer is included. Expected delivered tons after risk applies adjusted reliability to that contracted total. Residual shortfall exposure is the expected gap to your target, floored at zero. Total procurement cost multiplies contracted tons by average price, while Expected shortfall penalty value multiplies shortfall by the penalty per ton. Finally, Net present value of program rolls those pieces into the simplified economic formula implemented on this page.
MathML formula for NPV as implemented.
The discounted net value of the program can be expressed as:
Here, r is the annual discount rate and Delay is the delivery delay in months. This mirrors the calculator implementation exactly and is intended for planning comparisons rather than accounting-grade valuation.
How to interpret a result responsibly.
If expected delivered tons are above the target, the portfolio looks adequate on an average basis. That is useful, but it is not the same as saying the plan is guaranteed. Expected-value tools compress many possible delivery paths into one number. A concentrated portfolio with one dominant supplier can display the same expected delivered total as a more balanced portfolio even though it may feel much more fragile in practice. That is why it helps to run multiple scenarios instead of stopping at the first acceptable output.
When comparing cases, change one assumption at a time. Start with reliability, because it usually has the largest effect on expected delivered tons. Then test buffer, because buffer directly raises contracted volume and cost. Finally test penalties and delay to understand the financial consequence of missing. This makes the analysis easier to explain to non-specialists: you can show whether the plan depends more on confidence in suppliers, willingness to over-contract, or tolerance for shortfall risk.
Related planning tools.
Teams evaluating other carbon removal pathways can also reference the enhanced rock weathering CO2 removal calculator and the direct air capture cost calculator to benchmark technology pathways.
Tips for better inputs.
If you are unsure what to enter for on-time probability, start with a conservative estimate and run sensitivity tests. For example, compare 60%, 70%, and 80% reliability while holding price constant. If the penalty per ton is hard to quantify, try a range that reflects both the premium you might pay for last-minute make-good purchases and the internal cost of missing a public commitment. The goal is not to pretend there is one perfect number. The goal is to learn which assumptions dominate the decision and how much risk the organization is actually willing to carry.
Delivery Assurance Summary
Total tons to contract: 0 tCO₂e
Expected delivered tons after risk: 0 tCO₂e
Residual shortfall exposure: 0 tCO₂e
Total procurement cost: $0
Expected shortfall penalty value: $0
Net present value of program: $0
How to read your summary
The most useful way to read the result is to move from operational meaning to financial meaning. Start with Total tons to contract. That tells you how much purchasing activity the strategy really implies once the buffer is included. Then check Expected delivered tons after risk. This is the heart of the model, because it applies reliability and diversification to the contracted total. If that expected delivered number sits comfortably above the target, the portfolio may be adequate on an average basis. If it sits below the target, the portfolio is carrying expected shortfall even before you consider worse outcomes.
Next, compare Residual shortfall exposure with Expected shortfall penalty value. Those two outputs translate operational under-delivery into a cost signal. In some portfolios, the cheapest way to reduce risk is not to accept shortfall and pay for it later, but to contract extra tons up front. In other portfolios, the market price of extra buffer may be so high that accepting some shortfall exposure is economically rational. The calculator does not make that decision for you, but it frames the trade clearly and consistently.
The NPV line is best used as a directional comparison metric. It helps when one strategy has lower expected shortfall but requires much larger procurement spending, or when two strategies deliver similar expected tons but one comes with a longer delay. If you are presenting results to colleagues, it is often helpful to show two or three scenarios side by side and explain which single input change caused the biggest shift. That habit keeps the conversation grounded in assumptions rather than false precision.
Mini-game: Delivery Assurance Dispatch
This optional arcade-style mini-game turns the calculator logic into a fast portfolio-routing challenge. Incoming carbon removal contracts appear one by one, and three supplier lanes show live reliability that rises and falls over time. Your job is to assign each contract to the lane with the best current chance of on-time delivery. If you spread routes across pathways, you build a diversification bonus. If you stay clean through a streak, you earn buffer reserves that can rescue part of a missed contract later.
The game does not change the calculator math above. Instead, it gives an intuition for why the planner asks for reliability, buffer, and diversification. A concentrated portfolio can look fine until one lane gets hit by a correlation shock. A healthy buffer can absorb some mistakes, but not every mistake. In that sense the game is a short teaching aid: it makes expected delivery feel less abstract while keeping the main calculator result fully separate and intact.
Why it matters: The main calculator estimates expected delivered tons from contracted tons, reliability, diversification, buffer, and shortfall costs. This mini-game lets you feel those tradeoffs in motion without changing the calculator result.