Methodology

What the Carbon Quotient Ratio measures

The Carbon Quotient Ratio is a normalized measure of transition risk — the imputed cost of a company’s future carbon emissions, expressed relative to the value of the long-lived tangible assets (property, plant & equipment, or “PPE”) that produce those emissions. A company with high current emissions and a long remaining PPE Life carries more of that future cost than one with the same emissions today but assets that turn over quickly. Whether that future cost is already reflected in market prices today is a separate question — see our research.

The core formula

The Carbon Quotient Ratio is built from three figures, all drawn from a company’s own financial filings and emissions disclosures, and one assumed variable (the cost to permanently remove carbon emissions from the atmosphere):

PPE Life

= PPE ÷ DD&A Expense

Carbon Expense

= Realized Emissions × Carbon Price

Unrealized Carbon Expense

= Carbon Expense × PPE Life

Carbon Quotient Ratio

= Unrealized Carbon Expense ÷ PPE

Realized Emissions are a company’s direct (Scope 1) emissions in tCO2e for the current period. Carbon Price is a fixed $100/tCO2e assumption, not a market price — see Carbon Price in the glossary.

Decomposed: Carbon Intensity

The same result can be read as two independent drivers of risk — how emissions-intensive a company’s assets are, and how long those assets will keep producing emissions:

Carbon Quotient Ratio = Carbon Intensity × PPE Life, where Carbon Intensity = Carbon Expense ÷ PPE

Pro forma financial impact

Carbon Expense and Unrealized Carbon Expense are also used to show what a company’s financial statements would look like if that future carbon cost were already recognized:

• Adjusted Net Income = Net Income − Carbon Expense, and Adjusted EPS = Adjusted Net Income ÷ diluted shares
• Adjusted Total Assets and Adjusted Stockholder’s Equity each subtract Unrealized Carbon Expense from the reported balance-sheet figure

Full definitions for every term above are in the glossary.

Data sources

Financial figures (PPE, depreciation, revenue, net income, shares outstanding, and related fields) are pulled directly from each company’s SEC EDGAR XBRL filings. Scope 1 emissions figures are sourced from each company’s own sustainability or ESG disclosures, with the source document archived and the specific figure verified against the archived source. Every published company page links to its financial and emissions source documents.

Data quality & edge cases

A small number of companies are missing one or more inputs the Carbon Quotient Ratio needs in a given year — most often Scope 1 emissions data isn’t publicly disclosed. Rather than estimate a missing figure, that company’s Carbon Quotient Ratio is left unpublished for that period.

PPE Life normally uses a company’s reported Depreciation expense. When a company hasn’t reported Depreciation for the current period — for example, because its filings report only the combined Depreciation, Depletion & Amortization figure — PPE Life falls back to that combined figure instead. That fallback applies to 151 of the 451 companies in the 2024 CQ500 Index (33%); the other 300 (67%) disclose Depreciation separately.

For the 167 companies on the fallback when we ran this investigation (before the October 2026 data corrections moved 15 of them onto a separately reported Depreciation figure and excluded one), we investigated whether a company-specific Depreciation figure could instead be reconstructed from the year-over-year change in the company’s disclosed Accumulated Depreciation balance — matched to the same 10-K’s own comparative prior-year figure by accession number, to rule out picking up a stale, pre-restatement value. That reconstruction was technically possible for 106 of the 167; for the other 61, either no current-year Accumulated Depreciation balance exists under any tag we check (60 companies), or no matching prior-year comparative could be found in the same filing (1 company). Among the 106, the reconstructed figure differed from the company’s own reported DD&A by more than 20% in 86% of cases, undershot it by roughly half at the median, and came out negative — impossible for a real expense — in 14 cases. Accumulated Depreciation also falls when assets are disposed of, impaired, or swept into a business combination, none of which reflects the period’s actual depreciation expense, so a balance-sheet reconstruction is a noisier estimate than the company’s own reported figure, not a more precise one. We use the reported DD&A figure directly rather than a derived approximation.

The fallback isn’t spread evenly across the index. By GICS sector, Energy (67%), Real Estate (57%) and Utilities (48%) rely on the combined DD&A figure far more often than Health Care (12%), Communication Services (14%) or Information Technology (15%); at the sub-industry level, Retail REITs, Health Care REITs and Passenger Airlines are 100% DD&A, and Oil & Gas Exploration & Production is near 90%. Because Depreciation, Depletion and Amortization is a company-level fallback rather than a random one, we tested whether that concentration skews sector- and sub-sector-level comparisons, not just individual company figures. Scaling every fallback company’s Carbon Quotient Ratio by 1.46 — the median ratio between DD&A and Depreciation observed across the 258 companies that disclose both, used here as an index-wide proxy for what each fallback company’s own ratio would look like under a Depreciation figure it doesn’t report — leaves every sector’s rank by mean Carbon Quotient Ratio unchanged, and holds within-sector company rank stable at a Spearman correlation of 0.95 or higher in every one of the 11 sectors, including the two largest (Industrials, 74 companies, and Information Technology, 66). The concentration itself is real; its effect on sector-level and within-sector comparisons, under this proxy correction, is not material. This is a sensitivity check on the direction and rough size of the bias — an index-wide ratio applied uniformly, not a per-company reconstruction, since the balance-sheet approach above already ruled out a more precise substitute — not a corrected dataset.

Companies also switch, over time, which literal XBRL tag they use to disclose the same figure — a utility moving from a generic Property, Plant & Equipment tag to a utility-specific one, for example. Our EDGAR collection checks a set of known alternate tags per field and prefers whichever one carries a value for the fiscal year being indexed, rather than reporting the field as missing or silently returning a stale prior- year figure.

Anyone — including a member company — can flag a suspected data error through the correction submission form. An approved correction takes effect immediately on the published index, and is automatically re-applied to that same fiscal year’s figures if the index is later refreshed from source data — for example after an ingestion fix like the tag-selection handling described above — for as long as the fresh source data still disagrees with the correction. Once a company’s own disclosed data resolves the discrepancy, the correction stops being applied on its own, with no separate cleanup step required.