Bridging the climate-corporate gap: utilizing GWP* with GWP100 for livestock companies’ greenhouse gas inventories

Abstract

Corporations must follow established standards when developing their emission accounting frameworks and reports. This standard necessitates that the various greenhouse gas (GHG) species are reported on a carbon dioxide (CO₂) equivalence (CO₂-e) basis using the global warming potential (GWP) metric on a 100-year timeframe (GWP100). However, GWP100 was developed to evaluate the warming contributions of a pulse or one-off emissions compared with an equivalent pulse emission of CO₂. Accordingly, the GWP100 metric does not account for scenarios of changing emission rates, which is an important factor for determining the warming effects of short-term climate pollutants. More recently, the GWP-star (GWP*) metric has been developed to address this issue by evaluating the short-term climate pollutants’ impact on global surface temperature change over time. With the emergence of GWP* there has been increasing interest in adopting this metric into corporate reporting. However, the 20-year baseline data required to calculate GWP* has limited companies’ ability to incorporate GWP* into their current GHG reporting inventories. To bridge the gap between GWP* and corporate accounting we developed a straightforward methodology to enable companies to dual report GWP* and GWP100 based on current GHG reporting inventories. Specifically, the methodology developed a “shadow company” technique that will allow GWP* to be calculated from a specified baseline reporting year and onwards. To realistically model a multi-national corporate GHG inventory, we developed a mock company, titled the Global Beef Company that operated in Brazil, Australia, and the United States. The GHG inventory was modeled and calculated using the same procedures currently employed by meat packers and retailers for estimating their scope 3 livestock GHG emissions. Emission reduction and growth scenarios were modeled over an 80-year time scale to demonstrate the long-term effects on warming. To evaluate the cumulative effect of warming over time, absolute GHG emissions were modeled using the cumulative sums of GWP* and GWP100 values. With many companies reporting GHG on an intensity basis, a new indicator was formulated entitled Cumulative Intensity where GWP* and GWP100 were both reported on intensity basis. Overall, the current analysis developed a step-by-step template for dual reporting GWP* and GWP100 on an absolute and intensity basis for GHG accounting at the corporate level.

Introduction

Greenhouse gases and aerosols differ significantly in radiative forcing, atmospheric lifetimes, and subsequent climate impacts (IPCC, 2023). To account for these differences, greenhouse gases (GHG) are often expressed on an equivalent basis using emission metrics. The most utilized metric is termed global warming potential (GWP) on a 100-year timeframe (GWP100). This metric evaluates the climate impact of a pulse emission of a GHG over a 100-year period and expresses the GHG relative to a carbon dioxide (CO₂) equivalent basis (CO₂e; IPCC, 2023). The usage of the GWP100 metric required by many corporate GHG reporting and goal-setting standards, including the Greenhouse Gas Protocol, Science Based Target, and CDP (previously known as the Carbon Disclosure Project; Cenci and Biffis, 2025; Greenhouse Gas Protocol (GHGP), 2024; Science Based Targets Initiative (SBTI), 2025). Furthermore, GWP100 is often the required metric for national and global GHG inventories (United Nations Climate Change (UNFCC), 2024). From both a corporate reporting and policy perspective, GWP100 provides several benefits. This globally adopted and simplified approach allows investors, corporations, and policy makers to compare multiple economic sectors with vastly different emission profiles, and it allows for transparency, and companies to identify their lowest and highest emitting regions and sources.

Despite the ubiquitous nature of GWP100, the metric, as with all GHG metrics, presents limitations and has received criticism, particularly when assessing warming impacts of temperature-related goals (O’Neill et al., 2000; Shine, 2009; Myhre et al., 2013). While the cumulative sum of GWP100 adequately relates long-lived climate pollutants (LLCP), e.g., nitrous oxide (N₂O) and CO₂, emissions to their warming impacts, the metric is inadequate for short-lived climate pollutants (SLCP), e.g., methane (CH₄), especially for changing emission rate scenarios. Methane has an atmospheric lifespan 11 ± 1.8 of years compared to 109 ± 10 years for N₂O and 100–1,000 years for CO₂ (IPCC, 2023). Therefore, fractions of these LLCP will persist in the atmosphere for centuries and continue to increase their atmospheric concentrations without long-term sustained interventions that drawdown that atmospheric pool (Lynch et al., 2020; Eby et al., 2009). These increases in GHG concentrations lead to a cumulative increase in temperature (Lynch et al., 2020). In contrast, when the atmospheric CH₄ oxidation rate is equal to the CH₄ emission rate, there will be no increase in atmospheric concentration of CH₄ (Cain et al., 2019). In the official IPCC AR5 report and reiterated in the AR6 report, GWP100 was determined to be not well-suited to estimating the warming effects of sustained SLCP emissions (IPCC, 2023; Forster et al., 2021; Allen et al., 2016; Cain et al., 2019; Collins et al., 2020). To more aptly represent the nuances of SLCP impacts temperature change, Allen et al. (2016) developed the GWP-star (GWP*) CO₂-warming equivalence (CO₂-we).

Although there has been controversy surrounding the use of GWP* (Meinshausen and Nicholls, 2022), in the IPCC 6th IPCC AR6 WGIII Second Order Draft Government and Expert Review Comments and Responses, commenters stated “GWP* may better represent the actual warming caused by methane emissions” and responses stated “GWP* provides a useful additional perspective about the effect of cumulative methane emissions” (IPCC, 2023). While both the GWP and GWP* metrics evaluate CH₄ effect on warming, they have different goals. On one hand, GWP describes the marginal effect of a pulse emission of CH₄ relative to an equivalent amount of CO₂ emissions. On the other hand, GWP* describes the equivalent CO₂ emissions that would give the same temperate change as an emission trajectory of CH₄, starting at a reference point. The IPCC AR6 report refrains from recommending one metric because the appropriateness of metric choice depends on the purposes for which gases or forcing agents are being compared. The same could be true for corporations, and why utilizing multiple metrics could aid organizations in having a more complete understanding of corporate contributions to warming. By dual reporting GWP100 and GWP*, corporations can adhere to the GHG reporting standards and can assess how changes in their annual emission rates impact their contributions to warming over time through GWP* (Allen et al., 2018; Collins et al., 2020). It should be noted, however, that GWP* is just one option to capture the behavior of SLCP, and other metrics could be chosen given that an appropriate framework was developed. Combined GWP (CGWP), combined global temperature change potential (CGTP; Collins et al., 2020) and Sum44 (Miller et al., 2025) are some examples. The current paper focuses on GWP* due to the increasing use and interest in the metric’s adoption from agricultural organizations and businesses (Mazzetto et al., 2023; Fonterra Co-Operative Group Limited (Fonterra), 2022; Deakin, 2025) eliciting the need to construct scientific “guardrails” for GWP* use in corporate accounting. While GWP* has previously been applied at a national inventory level (Hörtenhuber et al., 2022; Ridoutt, 2021), there has yet to be a defined methodology that would allow a corporation to dual-report metrics using their current GHG inventories. Such an approach would (1) allow readers of the report to make a more informed assessment of a company’s contribution to climate warming and (2) provide some companies with a means to report in a manner that aligns more closely with their stated climate goals (i.e. climate neutrality, net zero, etc.). By dual reporting GWP* and GWP100, the GHG report reader can make inferences based on a fuller complement of reporting metrics, thereby building transparency into the report.

Accordingly, to meet the scientific and corporate need to incorporate GWP* into GHG inventory reporting, the current study developed a straightforward methodology for dual reporting. Specifically, the study has developed a “shadow company” technique that will allow both GWP100 and GWP* to be calculated from their specified baseline year onwards. In addition, the present analysis created a mock company (termed Global Beef Company) emission reduction and growth scenarios over an 80-year timescale. By displaying how changes in emissions impact the GHG inventory on a decadal time series, changes in GHG emissions on warming can be evaluated holistically, both on a short-term and long-term basis. Finally, the current manuscript can provide guidance for companies on how to annually report their GWP* and GWP100 values on an absolute and intensity basis within their current GHG inventories. With this new methodology, companies can seamlessly transition to dual report GWP100 and GWP* using their current GHG inventories, enabling these companies to make more informed climate decisions.

Materials and methods

With an onslaught of new regulations for corporate GHG reporting, including the European Union Corporate Sustainability Reporting Directive and the California SB 253 Climate Risk Reporting, companies are under increasing scrutiny on how and what to report for their GHG emission inventories. To stay in compliance, most companies follow the GHGP corporate reporting standards (Swinkels and Markwat, 2024). This type of reporting divides companies’ emissions into three categories including: Scope 1-direct emissions, Scope 2-indirect energy emissions, and Scope 3- indirect upstream and downstream emissions. For companies that have livestock in their supply chains, most emissions are in Scope 3 (Greenhouse Gas Protocol (GHGP), 2025). With the regimented regulations corporations encounter, for any GHG corporate reporting methodology to be adaptable, the methodology must be reported on a GWP100 basis (Swinkels and Markwat, 2024). Therefore, the current methodology was designed to stay in GHGP compliance and recommends a dual reporting style, using GWP* and GWP100 for GHG disclosures and reporting.

Scope

To evaluate how to incorporate GWP* in to corporate GHG inventory reporting, we generated a mock company referred to herein as “Global Beef Company,” (GBC). The GWP* metric has been used to evaluate a variety of livestock CH₄ emissions, such as those of Beck et al. (2022), Beck et al. (2023) and Place et al. (2022), who used GWP* to assess enteric CH₄ emissions from the U. S. beef and dairy industries and the manure CH₄ emissions from the beef, dairy, pork, and poultry industries. While GWP* can be used for a variety of CH₄ emission sources, or simplicity, the present analysis only modeled and evaluated emissions from beef cattle. To explore multi-national use of GWP*, GBC was demonstrate how GWP* was built to operate in Australia, Brazil, and the United States. Each operational region, or division, of GBC harvested 1 million cattle per year for a total global harvest of 3 million head. The current scenario included cattle emissions from cradle to gate. Although this methodology can be utilized for all scopes that produce biogenic CH₄, most corporate livestock GHG emissions occur in Scope 3 (Thompson et al., 2025; Swinkels and Markwat, 2024), thus the current analysis is limited to Scope 3, Category 1a emissions. Category 1a is the purchase of goods and services. For this model, only cattle purchases were calculated in the inventory.

Baseline emissions

For companies to report annual updates on GHG emissions, they report against a baseline year (Greenhouse Gas Protocol (GHGP), 2005). For the present scenario, the GBC baseline year was 2020. A globally recognized emission database, the Food and Agriculture Organization’s life cycle assessment tool entitled Global Livestock Environmental Assessment Model (FAO GLEAM, 2023), was used to compute baseline beef cattle emissions. The GWP100 values in GLEAM were based on AR5, where CO₂ had a warming equivalent value of 1 (all other GHG being compared to CO₂), N₂O had a value of 265, and CH₄ had a value of 28. Although the GLEAM data set was based on 2015 data, the GLEAM dataset was the most up-to-date publicly available global livestock inventory. Furthermore, because the data were standardized across regions, GLEAM was one of the only publicly available tools for modeling on a global scale. The emission categories included in the GLEAM data were enteric CH₄, manure management, direct and indirect farm energy, feed, and transportation from the farm. This approach aligned with how packers, processors, and retailers have been calculating their beef cattle emissions. For most corporations operating in the food sector, there is limited traceability and visibility into their cattle supply chains (Scope 3 emissions). This lack of visibility relegates corporations to using country and global level emission factors, especially for those companies that harvest or purchase beef. Some corporations, such as those in Europe, may have the ability to use customized life cycle assessment; however, this type of methodology is not currently available for most corporations outside of Europe. Refining Scope 3 emissions factors is a goal and need for many corporations, but out of the scope of the current analysis.

The category of cattle selected within the GLEAM tool was “beef cattle.” Although dairy cattle are a significant source of beef, particularly in the United States, for simplicity, only beef cattle were evaluated in this analysis. Table 1 shows the GLEAM kg of CO₂e values per kg hot carcass weight (HCW) utilized for this analysis for the baseline year of, 2020.

The hot carcass weight values were adjusted to a per head basis by utilizing dressing percentages and average live weights based on government and trade association assessments (United States Department of Agriculture National Agriculture Statistical Services (USDA-NASS), 2020; Meat and Livestock Australia (MLA), 2021; Abiec Brazilian beef Exporters Association, 2023). The “per head emissions” were then converted to kg of CH₄ by dividing by 28 and multiplied by 1 million head for each country (Table 2). An example for US cattle:

Land use continues to be an important topic for climate, food security, and livestock production. This is particularly true in the Global South. At the time of this analysis, the Greenhouse Gas Protocol (GHGP) had yet to publish final guidelines on accounting for land sector emissions and removals (Greenhouse Gas Protocol (GHGP), 2022). Without the final guidance on land use change calculations, many livestock companies have yet to calculate and report on Scope 3 land use change emissions (including those that operate in the Global South). With uncertainties on land sector emissions reporting, land use change was excluded from the current analysis. If a company were to incorporate Land use change (LUC) into the proposed GWP* dual reporting structure, it would still be required to follow all GHGP guidelines. As stated under the GHGP guidance, land use change emissions would be reported and calculated separately from the main inventory.

Development and rules for shadow company

In 2019, the GWP* model was adjusted to allow for the direct comparison of values from GWP100 and GWP* (Cain et al., 2019). and further modified by Smith et al. (2021). The latest version of the GWP* metric for CH₄ is as follows:

Where E^* are the CO₂-we emissions of CH₄ at year t, and E_CH4 is the CH₄ emissions in tons of CO₂-e (using AR5 GWP100 values) at years t or t minus 20. Given the equivalence in warming contributions of CO₂-we with a pulse of CO₂, cumulative CO₂-we emissions can be combined with CO₂-e from long-lived climate pollutants, leading to a cumulative CO₂e value that corresponds to the climate response.

A twenty-year time horizon of emission data has been needed to use GWP* to accurately link SLCP emissions to temperature impacts (Smith et al., 2021). However, many companies that have been publicly disclosing their GHG emission inventories have only done so in the past 5 years, with many not disaggregating their inventories by gas, which would be required to integrate GWP* into GHG disclosures (Cenci and Biffis, 2025). To overcome the lack of data, specifically 20 years of historical CH₄ data, we proposed a shadow company approach to construct past time series of emissions data.

The shadow company was constructed to represent a hypothetical company’s emissions from the 20 years prior to the baseline reporting year (2020 in our current example). For the case of this analysis, the shadow company was built to represent the historic emissions of GBC. Global and regional livestock herd dynamics and emission inventories have fluctuated greatly over the last 30 years (Beck et al., 2023). Some countries’ cattle herd sizes and emissions have decreased considerably (AHDB, 2025; Meat and Livestock Australia (MLA), 2021), while other countries have experienced dramatic increases in herd growth and emissions (Abiec Brazilian beef Exporters Association, 2023; Ministerio da Ciencia, Tecnologie e Inovacao for the Brazil Government (MCTI Brazil), 2024). To reflect the changes in emissions at scale, the shadow company was based on country-level CH₄ emission changes (i.e., government-level sourced data). This methodology would allow GWP* to be used by companies starting in their baseline year. Companies would no longer need to wait 20 years post baseline reporting year to utilize GWP* in their inventories. In addition, the shadow company methodology could avoid potential conflicts, including corporate mergers, divestments, or growth, thereby creating fairness across GHG reporting companies. Furthermore, the shadow company approach will limit the ability of a company to greenwash, or misrepresent their baseline emissions, as GWP* is sensitive to changes in SLCP relative to their baseline. The shadow company was designed to evaluate historic CH₄ levels for GWP* usage only. No other GHG were evaluated for the shadow company. To utilize GWP*, corporations would need to separate biogenic CH₄ from their current GHG inventory. Although some emission factors may only be available on a CO₂e basis, such as certain Scope 3 downstream categories, the largest sources of CH₄, such as manure and enteric CH₄ can be separated from the inventory analysis using tools like GLEAM.

For this study, the country databases used to create the shadow companies were the Ministerio da Ciencia, Tecnologie e Inovacao used for Brazil (Ministerio da Ciencia, Tecnologie e Inovacao for the Brazil Government (MCTI Brazil), 2024), the DCCEEW Australia, (2025), and the Environmental Protection Agency for the United States (U.S. Environmental Protection Agency (EPA) 2024, 2022). As the current analysis was refined to evaluate beef cattle CH₄ emissions, only historic CH₄ emissions from beef cattle (enteric and manure) were included in the shadow company. For companies that have different agricultural commodities with CH₄ emissions (i.e., rice, hogs, or chickens), these historic emissions would need to be computed for the shadow company. The current analysis was limited to biogenic CH₄ only. At this time, non-biogenic CH₄ should not be included in the shadow company or in GWP*. We advise calculating non-biogenic CH₄ separately from biogenic CH₄Table 3 was constructed to provide a step-by-step guide for shadow company development. To avoid confusion between metrics, the analysis refers to any GWP* use as CO₂-we and GWP100 use as CO₂-e.

Cumulative emissions

After the baseline year, CH₄ emissions have been computed, and the shadow company has been formed; the non-biogenic CH₄ emissions can be computed and entered in the accounting platform (see Supplementary material). These include N₂O, Hydrofluorocarbons, CO₂, and non-biogenic CH₄. Since N₂O and CO₂ are LLCP and persist in the atmosphere for well over 100 years (IPCC, 2023), GWP100 was considered the most accurate warming equivalence metric for these GHG. For the purposes of determining the long-term impacts and additive effects on warming potential, the cumulative CO₂-e and CO₂-we were calculated over time. The cumulative CO₂-e and CO₂-we have been used previously and can demonstrate how the utilization of different metrics impacts a GHG emission’s implied contribution to climate warming over time (Place et al., 2022; Del Prado et al., 2023; Beck et al., 2022; Beck et al., 2023; Thompson et al., 2025).

To utilize GWP* and GWP100 on an intensity level, the cumulative total GHG emissions of CO₂-we or CO₂-e were divided by the cumulative product. For this analysis, the product was defined as kg of hot carcass weight. Expressing GWP* and GWP100 on an intensity basis can allow a company to assess changes in production efficiency on a carbon footprint (or warming footprint). The cumulative intensity metrics included cumulative CO₂, CH₄, and N₂O emissions in the numerator with CH₄ expressed either as CO₂-e or CO₂-we, and cumulative kg of hot carcass weight in the denominator.

Projected change in emissions

Five scenarios were simulated to determine how changes in emissions from the baseline year to year 2050 affected inventory reporting (Table 4). These scenarios included a 50% increase in emissions, a 25% increase in emissions, no change in emissions, a 25% decrease, and finally a 50% decrease in emissions. These increases or decreases in emissions were applied to all GHG in the inventory (i.e., CO₂, CH₄, and N₂O). The scenarios determined how a variety of corporate emission changes impacted long-term warming potential as implied by the GWP* and GWP100 metrics.

Rebaselining scenario

Over time, companies may need to recalculate and re-establish GHG emissions for the base line year to reflect “significant” changes in a company’s structure or inventory, such as mergers, acquisitions, or divestitures. While GHG protocol does not mandate rebaselining nor has a definition for what constitutes a “significant” organizational change been given, they have recommended rebaselining as a practice to maintain accuracy and transparency in GHG reporting (Greenhouse Gas Protocol (GHGP), 2005). A scenario was built to demonstrate the utilization of GWP* during a rebaselining process. For the scenario, GBC either acquired an outside Brazilian beef business with an inventory of 100,000 cattle or they divested from their current GBC Brazil operations at the amount of 100,000 cattle. The rebaseline methodology was based on GHG protocols “Rebaseline All Year Approach” (GHGP, 2005). This approach stipulates that regardless of when a business was acquired or divested, emissions were to be adjusted starting from the baseline reporting year. Therefore, for both the divestment and acquisition scenarios, GBC emissions were rebaselined for the year, 2020. To utilize GWP* during rebaselining, a new Brazilian shadow company was created for the acquisition of assets. The baseline mass emissions would be based on 100,000 cattle using GLEAM data for Brazil, where the GBC Brazil division increases from 1,000,000 head of cattle to 1,100,000. The shadow company data was based on historic Brazilian emissions provided by the Ministerio da Ciencia, Tecnologie e Inovacao. During the rebaselining process, the two shadow companies’ historic data (GBC and the acquired Brazilian beef company) were combined to create the new rebaselined inventory. For the divestment scenario, the baseline year mass GHG numbers for the GBC Brazil division were adjusted from 1,000,000 head of cattle to 900,000. The shadow company’s emissions were then based on 900,000 vs. 1,000,000, and the new baseline inventory was formed.

Emerging technology scenario

Currently, there are limited large-scale technologies available for the immediate reduction of CH₄ from global beef production. Although these technologies may not be available today, future advancements in emerging CH₄ mitigating technologies may be available in the future. To model how a large-scale CH₄ mitigating technology would impact long-term company emission reporting, we designed a hypothetical scenario where a CH₄ technology was implemented by GBC at scale. In Scenario GBC began adopting a CH₄ mitigation technology in 2030 and had 100% adoption by the year 2032. In total, CH₄ mitigation from each country was reduced by 30% by the year 2032. In the emerging technology scenario, there were no increases or decreases in emissions outside of the years 2030–2032 (Table 5).

Sensitivity analysis

To evaluate how changes in GHG inventories impacted GWP* and GWP100 over time, a sensitivity analysis was constructed. The sensitivity analysis evaluated how steady increases or decreases in total GHG emissions (CH4, CO2, and N2O) affected cumulative GHG emissions over time (Figure 1). The emission increase scenarios that were evaluated included either a 70% increase, a 50% increase, a 30% increase, or a 15% increase in emissions. Decreasing-emission scenarios included either a 70% decrease, a 50% decrease, a 30% decrease, or a 15% decrease in emissions. In addition, a no-change in GHG emissions scenario was evaluated. Both the modeled increases and decreases in emissions were linear from, 2020 to 2050. No changes post 2050 occurred for this sensitivity analysis.

Figure 1

Annual reporting

Annual GHG reporting has become an integral component of a company’s Environmental, Social, and Governance (ESG) scores, as well as corporate compliance. For companies to utilize GWP* as part of their annual emission reports, two reporting style options were formulated. The Option 1 reporting style reported two values. The first metric combined SLCP and LLCPs into total GWP CO₂-we, and the second metric combined SLCP and LLCPs into total GWP100 basis (Table 6). Since companies most often report combined inventory numbers, this methodology allows for a total emission inventory number to be reported using GWP*. In addition to an annual total reporting number, Option 1 included the mass (on the desired scale) of CH₄ in its reporting output. Reporting the mass of CH₄ in addition to the combined metrics may increase transparency and prevent any misinterpretation of corporate emissions. For Option 2 reporting style, each gas species was reported on an individual (Table 7) and a combined basis. Combined emissions reporting style was identical as Option 1 where SLCP and LLCPs were combined into GWP100 CO2-e and a GWP CO₂-we. Both reporting options were based on GBC emissions. Since GHG reporting requires that emissions be reported on an annual basis, GWP cumulative was not used as a metric. For both reporting options, the example year used for the report was the baseline year of 2020.

Results

Annual emission growth and reduction scenarios

When evaluating GWP cumulative in both reduction scenarios (50 and 25% reduction by 2050) for GBC, CH₄, and CO₂, the cumulative value become negative (Figure 1). The negative value was due to the rate of CH₄ atmospheric oxidation being greater than the rate of CH₄ production, resulting in a decreased warming potential. The negative value does not suggest that a company no longer contributes to warming. Rapidly declining CH₄ emissions have a negative CO₂-we value because there is a declining temperature impact, relative to the warming caused by past SLCP emissions at a previous point in time (IPCC, 2023). This timescale is critical for interpretation, and companies should not interpret negative cumulative values as no warming impact, particularly during the early deployment of GWP* when limited historical years are built into the framework. Although emissions were negative for these scenarios, GWP* was built utilizing a ΔT of 20 years; the CO₂-we value of CH₄ would not continue to decrease in perpetuity. Twenty years after the reductions stopped, in 2070, the CO₂-we value for CH₄ in the modeled scenarios increased. In contrast, CH₄ CO₂-e maintained positive and sustained emissions in all emission reduction scenarios. Both GWP metrics reflected how taking immediate action to reduce CH₄ would have ramifications on warming potential, particularly when utilizing GWP*. When the reductions of CH₄ were high, both CO₂ and N₂O exhibited greater impacts on warming potential compared to CH₄ CO₂-we. For corporations within the beef cattle industry, the utilization of GWP* may shift corporate focus from CH₄-centric to be more robust and prioritize LLCP reductions as well.

For GBC, the 50% increase in emissions by year 2050 scenario (Figure 1), CH₄ CO₂-we cumulative produced a higher value than CH₄ CO₂-e, reflecting how large, sustained increases in CH₄ production can greatly increase warming potential. For the 25% increase in emissions by the 2050 scenario, cumulative CH₄ CO₂-we and CH₄ CO₂-e maintained similar impacts on warming potential over time. In both emission increase scenarios after the emission increases ceased in the year 2050, CH₄ CO₂-we cumulative values gradually decreased. In the no change in emissions scenario (Figure 1), CH₄ CO₂-e cumulative on average resulted in a 60% higher value than CH₄ CO₂-we cumulative. Although CH₄ CO₂-we cumulative was lower than CH₄ CO₂-e cumulative, the model showed that any continued production of CH₄ resulted in a positive impact on warming over time. Therefore, if no action were taken to reduce CH₄, there would be an increasing positive impact on temperature over time, regardless of the GWP metric. For specific baseline year reporting values, including mass, CH₄, CO₂-we, and CH₄ CO₂-e, can be viewed in Tables 6, 7.

Country-level emissions

When the various emission scenarios were compared on the country level, the effect of computing shadow companies at the country level on long-term emissions emerged. Figure 2 compares GBC CH₄ CO₂-e, and CH₄ CO₂-we cumulative emissions by country divisions, including Brazil, Australia, and the United States. Using national country-level emission data to build a shadow company, the GBC Australia division resulted in a baseline year CH₄ emission value of 0.21 million metric tons (MMT) of CH₄ (Figure 2), 5.9 MMT kg CO₂e, and −1.6 MMT CO₂we. Over the last 20 years, Australia has experienced a decrease in herd size, principally due to drought, which resulted in a 13% decrease in beef cattle CH₄ emissions (United States Department of Agriculture Foreign Agricultural Service (USDA-GAIN), 2019; Meat and Livestock Australia (MLA), 2021; DCCEEW Australia, 2025). This long-term reduction in emissions resulted in a negative GWP* value for the GBC Australia division for the baseline reporting year. This contrasts with the Brazilian and the American GBC divisions that resulted in positive baseline year CH₄ CO₂-we. In Brazil, where the cow herd has grown by over 17% in the last 20 years (Abiec Brazilian beef Exporters Association, 2023), CH₄ emissions from the beef cattle sector have increased by 26% (from 2000 to, 2020; Ministerio da Ciencia, Tecnologie e Inovacao for the Brazil Government (MCTI Brazil), 2024). For the GBC Brazil sector, CH₄ baseline year values were as follows: 0.29 MMT (Figure 2), 8.1 MMT CO₂we, and 11.4 MMT CO₂e. For the GBC United States division, the mass of CH₄ in, 2020 was 0.12 MT, GWP100 was valued at 4.79 MMT CO₂-e, and GWP* was valued at 1.31 MT CO₂-we (Figure 1). In the United States, both herd size and emissions between the years 2000 to, 2020 were relatively constant (United States Department of Agriculture National Agriculture Statistical Services (USDA-NASS), 2025; U.S. Environmental Protection Agency (EPA) 2024, 2022). This resulted in CH₄ CO₂-we to be neither negative nor greater than CH₄ CO₂-e. However, recently the United States has experienced record-setting droughts, resulting in a substantial cull to the cow herd, and thus a decrease in herd CH₄ emissions has occurred. Additionally, there has been a long-term trend for a decreasing beef cow herd that aids in this response. Thus, if a more recent baseline year was used for reporting, this decrease in emissions would be reflected in the shadow company and future GWP* value. These results indicate that the choice of baseline year may have long-term impacts on GWP* usage.

Figure 2

Emission intervention scenario

Currently, there are limited technologies available to substantially reduce enteric CH₄ emissions from beef cattle. Although feed additives such as 3-nitroxyproponal have the potential to reduce CH₄ emissions in concentrated finishing operations by 22% or greater (Kebreab et al., 2025), these technologies are not currently adaptable for the cow-calf sector (Hegarty et al., 2021). This creates a large obstacle for CH₄ mitigation, for the majority of CH₄ emissions occur during the cow-calf phase (Klopatek et al., 2022; Rotz et al., 2019). However, with technological advancements, such as a potential bolus (a small pill-like structure that can be administered into the rumen to slowly release chemical contents), feed additive technologies may be available to all sectors of the cattle industry in the future. To model a large-scale emissions intervention, we designed a scenario in which GBC implemented a CH₄-reducing technology to their global cattle supply chain over a 3-year period starting in 2030 (Figure 3, Table 5). In total, CH₄ emissions were reduced by 30%. The GWP* metric was sensitive to the rapid, large-scale reduction in CH₄, with CH₄ CO₂-we cumulative becoming negative by year 2035. However, with the emissions decreasing for only a 3-year period, CH₄ CO₂-we values began increasing 20 years after the reduction occurred. In contrast, CH₄ CO₂-e exhibited a slight decrease in slope, but with GWP100 treating CH₄ emissions as a stock gas, emissions continued to accumulate at a steady rate over time.

Figure 3

Rebaselining scenario

With corporations often rebaselining their emissions at times of mergers, acquisitions, and divestments, a scenario was designed to determine the outcomes of GBC emissions for both company divestment and acquisition. For these scenarios, GBC either acquired a Brazilian beef company with an inventory of 100,000 cattle or divested from its current GBC in Brazil by 100,000 head of cattle. Although GWP* is sensitive to large and rapid decreases in CH₄, as shown in the intervention scenario (Figure 4), rebaselining adjusts the past time series of emissions; these types of large shifts in inventories will not be observed for rebaselining scenarios. Therefore, if a company rebaselines their emissions, consistent with GHG Protocol recommendations, this would prevent a company from having a negative CH₄ CO₂-we simply with divestment. In addition, rebaselining would prevent a large spike in CH₄ CO₂-we from expansion. Ultimately, rebaselining will be necessary following a sudden growth or shrinkage of a company following acquisition or divestment, respectively. Without rebaselining, companies would be incentivized to divest themselves and disincentivized from growing.

Figure 4

This is demonstrated using our rebaselining scenarios and is displayed in Figure 4. For the acquisition scenario, the CH₄ CO₂-we at year 2100 was observed to be 11.5% higher in the year 2100 when no rebaselining occurred, whereas the divestment reduced their warming impact by 17.5% without rebaselining. This demonstrated that the appropriate use of rebaselining a company’s emissions within the context of national inventories minimizes perverse incentives that could be obtained by divesting and disincentivizing company growth. Not rebaselining following an acquisition or divestment would result in an inaccurate representation of a company’s true warming impact, as those emissions do not simply cease to exist when they move on or off of financial ledgers.

Cumulative intensity factor

The cumulative intensity factor, dividing GWP cumulative by production value cumulative, has the ability to incorporate the changes in GHG inventory over time with the changes in production efficiency. Using a cumulative intensity factor GWP* has the ability to be directly compared to GWP100 on an intensity level and thereby has the potential to be utilized in future life cycle assessment work. In the current production scenario (Figure 5), GBC total GHG emissions were steady from the baseline reporting year till year 2100. To model an increase in GBC production over time, scenarios included 0, 1, and 2% increases in production on an annual basis while emissions stayed constant from the baseline year onwards. The production scenario did not alter GHG to clearly evaluate how changes in production impacted the two intensity metrics. In the current scenario, production was based on kg of hot carcass weight. However, production value can be determined at the corporation’s discretion, such as kg of total product (e.g., human edible and inedible or kg of human edible product). Increased meat production without large increases in GHG absolute values has taken place in a variety of protein sectors across the globe, including hog and poultry (Ottosen et al., 2021; Thoma and Putman, 2020). For the beef sector, this pattern often coincides with changes in the breeding herd inventory and an increase in total meat yield per animal (United States Department of Agriculture National Agriculture Statistical Services (USDA-NASS), 2025; U.S. Environmental Protection Agency (EPA) 2024, 2022). In all scenarios, GWP* intensity maintained a lower value than GWP100 when directly comparing the increase in production scenarios. This was expected with GWP* maintaining a lower absolute value compared to GWP100. However, GWP100 was more sensitive to production changes than GWP*. By the year 2100, the GWP100 demonstrated an 84% difference in intensity value between 0% annual change in production and a 2% change in production, compared to GWP* that only experienced a 40% difference between the 0 and 2% change in production scenarios. Similar patterns were observed in the decreasing production scenarios (1 and 2% annual decrease in production). Decreasing production scenarios can occur when efficiency within the system begins to degrade. For the livestock sector, this may occur when technologies are removed from the supply chain or there are regulatory changes to animal production management.

Figure 5

Sensitivity analysis

For the sensitivity analysis (Figure 6), when changes in CH₄ emissions over an 80-year period were compared, GWP* and GWP100 cumulative emissions values and patterns were markedly different from one another. For these scenarios, emission reduction or increase scenarios occurred by 2050, with emissions being steady post 2050. For high reduction scenarios 50% and above, CH₄ CO₂-we exhibited a higher warming potential than CH₄ CO₂-e. However, over time, when emissions began to stabilize (post 2050) CH₄ CO₂-we warming impacts began to decrease. For GBC, CH₄ emissions would need to increase over 1% per year for GWP* metric to result in a greater warming value than GWP100 metric. For the lower emission increase scenarios, 30% and below, CH₄ CO₂-we maintained a lower warming potential than did CH₄ CO₂-e. For a CH₄ CO₂-we cumulative negative value to be observed, GBC would need to sustain substantial reductions in CH₄ (greater than 0.5% a year). Although these reductions may be possible for some divisions of the business (i.e., Brazil), in the other divisions, including Australia or the United States, reducing emissions from these cattle herds will be difficult without an onslaught of new technologies (Caro et al., 2014; FAO, 2023). For both modest reduction and modest growth in CH₄, the GWP* cumulative metric maintained a lower warming potential than the GWP100 cumulative metric.

Figure 6

Reporting

In order to utilize GWP* for corporate annual reporting, two reporting options were considered (Table 6; Table 7). Option 1 (Table 6) enabled GBC to combine all the emissions together, allowing for the direct comparison of Total CO₂-e (CH₄ CO₂-e, CO₂ CO₂-e, and N₂O CO₂-e combined) and Total CO₂-we (CH₄ CO₂-we, CO₂ CO₂-e, and N₂O CO₂-we combined). However, to avoid any appearance of greenwashing, we recommend reporting the mass of CH₄ in addition to the combined metrics. This can allow outside stakeholders to observe the changes in corporate GHG inventory reports while limiting confusion that may occur while reporting on GWP*. Option 2 (Table 7), a “split-gas” approach separated CH₄, CO₂, and N₂O from one another. This type of reporting has advantages for companies that would like to set targets for individual GHG reduction, such as suggested by the IPCC SLP Net Zero models (IPCC, 2025).

Discussion

Since the inception of the GWP* metric, rigorous debates have unfolded regarding the reliability, accuracy, and usability of GWP* compared to other global warming potential metrics (Meinshausen and Nicholls, 2022; Cusworth et al., 2023; Ferreira and McCabe, 2024). With continuing concerns over climate change, the discourse on animal agriculture, and ideological differences between various stakeholder groups, the debate over warming equivalent metrics will certainly persist. However, the purpose of this study was not to wade into the dispute about which metric is “better.” The purpose, rather, was to provide companies with the ability to expand the scope of their reporting to include GWP* along with their current GWP100 inventories. Utilizing multiple metrics can enable companies to inclusively evaluate long-term and short-term impacts of their respective GHG emissions on climate, and, ideally, allow them to better assess their progress towards stated climate goals, such as commitments related to climate neutrality. The knowledge acquired during this evaluation process may better inform organizations on how and where to focus their financial resources for reducing emissions. Although there are a variety of metrics that could have been evaluated alongside GWP100, GWP* was selected both for its ability to evaluate SLCP impact on warming over time and because of the increasing public use of the metric. Public use of a metric does not justify the use of one metric over another. However, with the GWP* metric receiving more attention, there are increasing risks that GWP* will be incorrectly adopted into accounting schemes and misinterpreted, leading to greenwashing. As such, we aimed to develop a methodology for corporate accounting to ensure the proper use of the metric and to enact “scientific guardrails” for GWP* in corporate accounting.

Usability and simplicity

An argument against the utilization of GWP* has been the lack of simplicity and usability for multiple stakeholders. Meinshausen and Nicholls (2022) stated that for a metric to be usable, it needed to be both simple and transparent, thereby allowing adaptation of the metric by a wide variety of stakeholders. Previously, corporations were limited in their ability to adapt GWP* for corporate accounting, primarily due to a temporal aspect of the GWP* metric. With the methodology developed here, of a shadow company along with step-by-step instructions for the future shadow company development, the temporal aspect of GWP* will no longer be a limiting factor of GWP* use in corporate accounting. However, utilizing this tool should not replace other accounting practices, but rather be used in conjunction with them to give a more nuanced and clear assessment of warming impact. In tandem with the shadow company development and synchronous reporting style, GWP* with GWP100 now can meet the usability and simplicity criteria of the GWP metric. A caveat should be noted when discussing the different climate metrics. As stated previously, although both metrics have been formulated to evaluate GHG impacts on warming, these two metrics have different focuses and tell different stories. Global warming potentials evaluate the relative effect of pulse emissions, or the amount of energy trapped in the atmosphere due to a given emission compared to an equivalent emission of CO₂ with the absence of that emission (IPCC, 2023). However, GWP is not well-suited to estimate the warming effect at specific time points from sustained SLCP emissions because warming caused by an individual SLCP emission pulse diminishes over time (IPCC, 2023). By contrast, GWP* closely approximates the additional effect on warming from a time series of SLCP and can be used to compare the warming effect to the impact on temperature from the rate of CO₂-we emission production or removal (IPCC, 2023).

Using GWP* in corporate inventories may allow for corporate reporting growth and may enable companies to evaluate their climate impacts more effectively. For example, in Beck et al. (2023), when GWP* was used to evaluate US dairy emissions sources, the dairy cattle manure CH₄ implied warming impact was ~2-fold higher using GWP* than GWP100. Furthermore, when using GWP*, dairy manure CH₄ emissions became the largest source of CO₂-we compared to all other livestock emission sources. Although the current analysis did not segregate manure and enteric emissions, Beck et al. (2022) demonstrated how using multiple metrics can tell different climate impact stories. Dual reporting of metrics could bring these different climate stories to the center stage and thereby may aid companies in effectively executing climate change mitigation strategies.

Impacts of the shadow company on reporting

The shadow company revealed large variations in CH₄ emissions for the three countries operating within GBC (Figure 2). Despite Brazil, Australia, and the United States maintaining identical herd inventories (1,000,000 head annually), there were substantial differences in their CH₄ inventories. Using GWP100, Brazil had the highest CH₄ emissions at 8.0 MMT, followed by Australia at 5.9 MMT, and finally the United States at 4.7 MMT. These differences were primarily due to efficiency, genetics, environment, and management of cattle within the designated regions. In Brazil, for example, cattle are harvested at a later age, and only a small percentage of the Brazilian herd is finished in confinement compared to cattle operations in the United States (United States Department of Agriculture National Agriculture Statistical Services (USDA-NASS), 2025). The United States resulted in the lowest emissions of the three operating business divisions due to the high utilization of confinement feeding operations, feed additive technologies (i.e., beta-agonists and ionophores), management, and genetics (Herrero and Thornton, 2013). As stated previously, unlike GWP100, GWP* evaluates the rate of CH₄ emissions over time. Therefore, any changes in the rate of CH₄ outputs are integrated into the GWP* value. With the shadow companies’ historic fluctuations based upon changes from national GHG emission inventories, herd size was the dominant factor affecting the Δ/T of the shadow company. For GBC, the impact of the Δ/T from the shadow company was reflected in the CH₄ CO₂-we values from the baseline reporting year to year 2040. In the present GBC model for the baseline year 2020 at the country level, Brazil produced 11 MMT CO₂-we, Australia produced 1.5 MMT CO₂-we for Australia, and the United States produced 1.3 MMT CO₂-we. In the early 2000’s, Australia suffered massive droughts that resulted in large reductions in its ruminant populations. This large decrease in herd size ultimately led to a decrease in emissions, with beef cattle CH₄ emissions decreasing 30% over a 20-year period (DCCEEW Australia, 2025). This contrasted with the country of Brazil, where there was a substantial increase in cattle numbers over the last several decades, resulting in a 30% growth in absolute emissions (Ministerio da Ciencia, Tecnologie e Inovacao for the Brazil Government (MCTI Brazil), 2024). For corporations that have set emissions reduction goals, using GWP* may have a greater impact on product sourcing strategy and their related emissions compared to using GWP100. In essence, if a company chooses to change sourcing region to a country with a growing herd size, their GWP* values will most likely be higher than regions with shrinking cow herds. However, the shadow company emissions will only be relevant for the first 20 years post baseline year reporting.

The implementation of a shadow company and the reliance on national inventory data may place a greater emphasis on baseline reporting year impact and selection process. If the baseline reporting year selected coincides with a rise in the cattle cycle, herd emissions will be higher than when the cattle cycle is moving downward. With that said, these fluctuations in herd size and their subsequent CH₄ rates can be assessed by GWP*. Incorporating these dynamics into corporate accounting may provide more value for company emission reporting. However, baseline reporting years have been found to have an impact on corporate GHG inventories and future reduction goals (Changing Markets, 2025), and there may be concerns that baseline reporting years may be altered based on the shadow company Δ/T. Despite these concerns, corporate reporting baseline years are often selected by corporations based on data availability and the implementation of financial resources to collect said data. Therefore, no conclusion or inferences can be made regarding corporate baseline year selection in relation to cattle cycles and their subsequent outcome on shadow company Δ/T.

While there has been criticism that GWP* leads to inequalities, particularly in the global south (Meinshausen and Nicholls, 2022), the shadow company was developed to create fairness across all countries and regions. By building the shadow company with national emission inventory data, the methodology helps create fairness across operations and prevents companies from manipulating or distorting data at the inception of reporting. What has often been overlooked in the discussion regarding fairness in the use of GWP* has been how cow-herds in developing regions may have a greater opportunity to reduce emissions compared to cow-herds in developed regions. In developed nations, such as the United States, the cattle sector has made tremendous strides in nutrition, genetics, and management (Caro et al., 2014; Klopatek and Oltjen, 2022). However, because these advancements have already occurred, future per-head emission reductions may be challenging (Caro et al., 2014; FAO, 2023). In contrast, counties and regions where these production advancements have not been widely adopted, particularly in developing nations, the cattle sectors may have greater opportunities to reduce their emissions (FAO, 2023). For example, feedlots and feedlot rations have had a profound effect on lowering beef cattle GHG emissions, with around 95% of beef animals being finished in confinement (Capper, 2012; Klopatek et al., 2022). In Brazil, only 9–10% of cattle are finished in feedlots in 2020 (Abiec Brazilian beef Exporters Association, 2023). However, with the age restrictions placed on cattle harvest from China, there has been a continued boon in feedlot development across Brazil (United States Department of Agriculture Foreign Agricultural Service (USDA-FAS), 2025). Combined with efforts of pasture restoration, Brazil’s cattle herds have the opportunity to make substantial reduction in intensity emissions and in absolute emissions. These absolute reductions in emissions and their effects on warming potential may be more accurately depicted using GWP* compared to GWP100.

Emission change scenarios

The uniqueness of the GWP* metric has been its ability to compare pulses of long-lived climate pollutants with the rates of emissions of short-lived climate pollutants (Allen et al., 2018). Although the present model showed variability in the shadow companies and emission change scenarios, aggressive year-to-year emission changes were not observed. For GBC, emission reductions were modeled from −1.67% annually to +1.67% annually (Figure 1). For greater and more abrupt shifts in emissions to occur, a company would need to experience dynamic fluctuations in product type such as changes in other protein sources, sourcing region, or large-scale CH₄ mitigation technology implementation. These types of shifts would not only affect GWP* but would also impact GWP100. Although concerns over the volatility of GWP* in corporate accounting may exist, many of these concerns can be ameliorated with the act of rebaselining. To remove noise or confusion from reporting, when businesses undergo acquisitions or divestments, the company will often rebaseline its inventories. This process stipulates that the company needs to adjust its emissions from the baseline reporting year onward (Greenhouse Gas Protocol (GHGP), 2005). For GBC, rebaselining would occur at the baseline reporting year of, 2020 (Figure 4). In this scenario for GBC the percentage change in emissions between GWP* cumulative and GWP100 cumulative were similar when acquiring an additional beef business.

No change in emissions

When the emissions for the GBC were stable over time, GWP* cumulative values were 60% lower in warming potential value compared to GWP100 cumulative. Previous assessments have speculated how constant CH₄ emissions utilizing the GWP* metric would display no impact on warming potential (Changing Markets, 2025). In contrust to this speculation, in the present assessment the GWP* cumulative metric produced positive warming values from 2020–2100. Furthermore, in the no change emissions scenario the GWP* cumulative warning potential outputs increased over time. Therefore, companies that do not implement interventions to reduce CH₄ emissions will continue to have positive effects on warming.

Negative CO₂-we

In the high GHG reduction scenarios of 50% and greater (Figure 1 and Figure 2) as well as in the emerging technology scenario (Figure 3), GWP* cumulative produced a negative warming potential. Unlike GWP100, GWP* can result in a negative value due to the temporal component, or the ΔT, of the GWP* metric. When the atmospheric destruction rate of CH₄ was greater than the rate of CH₄ production, CO₂-we outputs become negative. This negative value has evoked concerns not only among the environmental communities (Changing Markets, 2025), but also regulatory concern on its usability as a metric outside of academic institutions (IPCC, 2023).

A negative CO₂-we may cause confusion and invoke greenwashing claims. To avoid these confusions or accusations corporate dual reporting of metrics may mitigate these concerns from various stakeholder groups (Table 6, Table 7). Presenting CH₄ in mass, CH₄ on a CO₂-we and CO₂-e basis can demonstrate how and what changes corporations have made to their inventories and allow stakeholders to holistically evaluate corporate GHG inventories. Presenting a negative GWP* value should not be articulated as having no warming effect on climate, a negative CO₂-we value demonstrates how dramatic reductions in emissions result in profound effects on temperature. Furthermore, although there may be concerns regarding the possibility of negative CO₂-we, in the current assessment a negative CO₂-we was only observed when substantial CH₄ reductions occurred. With limited traceability, limited financial resources, and a lack of technological advancements, the possibility of a substantial global reduction in CH₄ for a multinational livestock company will remain a challenge.

Limitation of National Inventories

The current methodology relied on updated national GHG inventory data being available. This data has generally been provided by government entities, either using a Tier 1 or Tier 2 data collection format. Other sources of data may be available such as those provided by FAO, but generally, national level inventories are more accurate and up to date (Beck et al., 2022). Although national inventories are the preferred data sources for GWP* shadow company modeling, there is no guarantee that governments will continue to calculate and publish national GHG inventories. For example, as of, 2025, the United States has ceased reporting on national GHG inventories. Without this data continuing to be available, utilizing GWP* for future corporate accounting will become increasingly challenging and will become reliant on international data inventories such as those provided by the FAO.

Reporting and next steps

Many have found single static GHG metrics to be insufficient in expressing the dynamic and complex nature of agriculture’s systemic effect on climate (Del Prado et al., 2023). Using a variety of GWP metrics, including both GWP100 and GWP*, may better represent agriculture’s, particularly ruminant livestock, impact on warming potential. The current methodology recommends dual reporting, where both GWP* and GWP100 are reported. This new type of GHG reporting can enable decision makers to evaluate the long-term and short-term impacts of reduction strategies and evaluate potential trade-offs in their GHG mitigation strategies. The dual reporting style may have impacts for climate financing, corporate reporting, and supply chain GHG intervention.

The current methodology provides two options for GWP* corporate inventory reporting. The first reporting style combined the GHG into an equivalent value GWP* total and GWP100 total, presented as Total CO₂-we and Total CO₂-e, respectively in Table 6. To avoid confusion, the mass of the individual GHG were also reported. This can allow reviewers of the inventory report to undertake their own climate impact examination and avoid the appearance of greenwashing. The second reporting option, the split gas approach, as first suggested by Lynch et al., reports each GHG independently (Table 7). Both reporting strategies require companies to disaggregate CH₄, N₂O, and CO₂ from equivalent warming emission factors, which will require more resources and time for corporate GHG accounting teams. Although decoupling GHG within corporate inventories will require more effort, there are multiple benefits for this undertaking. Not only will corporations be able to utilize multi-metric reporting, but companies will also be able to set GHG-reducing targets by species, as suggested by the IPCC (2025). In terms of livestock-specific emissions, utilizing publicly available datasets that report GHG by species, such as the United Nations Food and Agriculture GLEAM, tool may make the transition to a split gas reporting transition manageable.

Reporting absolute emissions in corporate sustainability reports has been useful when demonstrating total changes in corporate emissions, but often, absolute emissions cannot express advances in supply chain system efficiency. One such example has been the change in dressing percentage (yield of carcass per animal). If average carcass dressing percentage increases from 59 to 62% while emissions remain unchanged, total product yield increases, absolute emissions remain stagnant, but GHG emission intensity (GHG/ product produced) decreases. Therefore, sustainability reports would be improved if both absolute and intensity metrics were incorporated into their reports. Previously, researchers have expressed the need for utilizing GWP* in intensity figures such as life cycle assessments (McAuliffe et al., 2023; Deakin, 2025). Despite the scientific interest, because GWP* had not been adaptable for corporate GHG accounting, there has yet to be an available GWP* intensity metric for companies prior to this analysis. By combining GWP*_Total Cumulative emissions with product (kg of hot carcass weight) cumulative, for the first time, GWP* intensity can be reported by companies on an annual basis. This revolutionary reporting can allow corporations to methodically evaluate how changes in production over time affect GHG intensity by using multiple metrics. While using their current inventories and adopting the methodologies of the current analysis, corporations will now be able to address the short-term and long-term impacts of GHG mitigation strategies on climate and food security.

Conclusion

The increased pressure and demand for food companies to accurately report emissions while continuing to improve supply chain resilience and food security has fueled the need for more holistic and nuanced reporting. For the first time, a methodology has been developed to allow companies to dual report both GWP100 and GWP* in their inventories. The creation of a shadow company eliminated the 20-year time obstacle from incorporating GWP* into inventories. Furthermore, reflecting the changes in biogenic CH₄ production for the shadow company at the national level decreased the chances of misappropriating emissions and claims of greenwashing. With many corporations setting GHG targets based on production volume, for GWP* to be useful for a variety of goal-setting strategies, GWP* was also formulated on an intensity basis. To ensure the longevity of this methodology, any future updates to GWP* should be included in annual reporting to maintain accurate use of the metric. Overall, the dual reporting of corporate GHG emissions equips companies with more information on the effects of their GHG emissions on climate. With more information, companies can make more strategic decisions on how and where they want to invest their resources to reduce emissions. However, even with a holistic approach to GHG reporting, reducing emissions from the beef supply chain will continue to be financially, logistically, and scientifically challenging.

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