Decarbonisation Technology - November 2024 Issue

goal and scope phase. Key categories include global warming potential (GWP), resource depletion, and water use. Different impact categories are identified and quantified, from climate change to acidification and land use.  Interpretation: In this phase, the results are interpreted against the study’s original goals and scope. This includes identifying significant issues, drawing conclusions, and making recommendations for reducing environmental impacts. It is essential to fully describe assumptions, describe sources of data, and test sensitivity to different variables used to calculate CI scores. Highlighting uncertainty and variability without explaining its context in the study provides no inherent value and can expose companies to reputational and regulatory risks. Challenges in carbon accounting: Data, methodologies, and regulatory evolution While the benefits of carbon accounting are clear, its implementation across diverse industries and regions presents several challenges. One of the most significant challenges is data identification, selection, availability, and quality. Carbon accounting involves the meticulous management of information and relying on precise and comprehensive data, which can be difficult to acquire, particularly for first-of-a-kind, new processes and industries with complex global supply chains. Although the data might be available, decisions on the formatting, collection, and sharing of the data are a challenge. For example, the agriculture sector, which provides feedstocks for biofuels like RD and SAF, involves multiple stakeholders across different regions, each with its unique data collection practices. Inconsistent or incomplete data can lead to a high range of uncertainty in the calculated CI scores, jeopardising a company’s compliance with regulatory programmes and its ability to participate in carbon markets. Another challenge is the variability between carbon accounting models and methodologies. Models are the software tools used to calculate GHG emissions, while methodologies refer to the underlying frameworks that define how, when, where, and why data is assessed. Different industries and regions use various models, each with unique default values, units, and data requirements. For example, the Argonne GREET

100

90.8

82.3

35.7

Credits for soil carbon management

-20

-40

CORSIA (ICAO)

RFS (EPA)

GREET 2022

No til l age Manure management Cover cropping

Net GHG emissions

Direct supply chain emissions ILUC emissions

(Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies) model is commonly used in the US to calculate CI scores for transportation fuels, whereas regions like Canada may use models such as GHGenius or openLCA. The differences in methodologies make comparing CI scores across projects and geographies challenging. Moreover, the regulatory landscape for carbon accounting is constantly evolving. Governments worldwide are updating and expanding their climate policies to meet local and global emission reduction targets. These updates often dictate the models and methodologies required for calculating compliance or participation within a regulated environment. Regulations set the rules for how carbon accounting must be conducted and can affect reporting requirements, which may complicate companies’ efforts to align with these rules. Therefore, companies must proactively monitor regulatory changes and adjust their practices to maintain compliance. Government incentives in renewable fuels Today, the production of renewable fuels like RD and/or SAF needs substantial governmental incentives to be financially feasible, and many countries are incorporating them into their low- Figure 3 Different LCA models include different iLUC default values and yield different results. This chart shows life-cycle emissions estimates for corn ethanol-to-jet. Source: The International Council on Clean Transportation (ICCT, 2023)