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Data Accuracy – Target Setting and Limited Assurance

Our Carbon Accounting Specialist, Emma, looks at the importance of accurate company-specific emissions data for climate disclosure.

data documents

Executive Summary 

– Although they are widely used by carbon accounting companies, and frameworks don’t explicitly state that they should be avoided, spend-based sectoral averages for estimating emissions are discouraged by Carbon Responsible.  

– An emissions analysis based only on sectoral averages and financial data lacks specificity and accuracy and does not allow effective tracking of a company’s progress towards emissions reduction targets.  

– It is also not sufficient for limited assurance, which is increasingly being integrated into disclosure frameworks.

– Bespoke activity data better identifies emissions hotspots which enable the company to prioritise emissions reduction efforts.


Priorities in data collection  

The primary objective for the first years of emissions disclosure should be to achieve a high level of data accuracy in core areas of emission disclosure such as fuel, electricity, and refrigerant consumption, followed by high impact areas such as business travel, employee commuting and supply chain. This enables the establishment of ambitious yet attainable emissions reduction targets.

At Carbon Responsible, we encourage our clients to collect company-specific activity-based data, such as distances travelled and kWh energy consumed, and avoid relying on sectoral cost-based averages. We do this because a comprehensive understanding of a company’s carbon impact is crucial when it comes to setting and complying with emissions reduction targets.

Moreover, accurate company-specific emissions data is necessary for limited assurance, which is expected to be required by most climate disclosure frameworks in the next few years.

Limitations of Cost-Based Emissions Analysis 

Relying on cost alone for emissions data falls short in accuracy, hindering the ability to set reduction targets or ensure data assurance by external parties. The impact of inflation and geographic differences in costs are two examples of why estimates are unlikely to have a high degree of accuracy. 

Data accuracy is crucial when reviewing a company’s emissions reduction targets by assessing year-on-year emissions changes. When you set an emissions reduction target, you then need to verify whether you are on track to achieving it. Should you not align with your targets, you will be likely to lose investor and client confidence, and you might also need to pay some fees for non-compliance. If you use expense-based factors and the cost of your purchases increases without corresponding updates to the conversion factors, your reported emissions for the same purchase will increase compared to the previous year, despite the actual emissions remaining unchanged. This may result in your company failing to meet its emissions reduction targets.

Also, collecting accurate company-specific emissions data can help identify your company’s emissions hotspots, which in turns would allow you to better prioritise your emissions reduction efforts and allocate your resources more effectively.

Additionally, the limited or reasonable assurance requirements have been or will be soon introduced in many climate disclosure frameworks such as the European Commission’s Corporate Sustainability Reporting Directive (CSRD). These require your emissions data to be verified by a third-party company to confirm or contest (assure) the accuracy and reliability of your emissions analysis. Your emissions data needs to be accurate to the third-party verified; otherwise, it will fail the assurance process.  

Case Study – Air Travel Emissions 

EPA’s Supply Chain Greenhouse Gas Emission Factors v1.2 by NAICS-6 (last updated in April 2023) suggests that, on average, “Scheduled Passenger Air Transportation” (i.e., passenger flights on a commercial plane) emits 0.976 kgCO2e per US dollar spent (based on 2021 purchaser prices). Flight costs are, however, influenced by various factors unrelated to emissions, such as route, booking date, travel time, and airline choice, which can vary greatly.  

Moreover, these factors require a long time to be compiled, so that the 2023 air travel factor is, as mentioned before, based on 2021 prices. Finally, these factors are only available for a few countries (for instance, the mentioned EPA factors are based on US costs), and costs (including flight costs) change significantly depending on the country of purchase. 

Image Description: Figure 1. Cost of flights for the same route can vary greatly over time. Source: (visited 01.12.2023)

Here we compare estimated emissions for the same route (LAX to JFK, single journey, flying economy) using the different types of conversion factors. To calculate the spend-based emissions, we used the EPA factor and the lowest and highest prices available on the Skyscanner website for March 2024 (website visited on 1st December 2023). To calculate the activity-based emissions, we used some data on the air distance between LAX and JFK airport and we applied the DEFRA/BEIS conversion factor (excluding radiative forcing).

graph of emissions
Image Description: Figure 2. Differences in estimated emissions (tCO2e) flying from LAX to JFK in March 2024 vary widely depending on emission factor used.

Our simple comparative analysis showed that the potential for over or under reporting emissions using spend can be vast. In this specific case, spend-based factors could estimate emissions being up to 58% less and 48% more than the distance-based emissions. It is worth noting that for this exercise we only selected direct flights, and in the case of multi-leg flights, the cost-based approach may lead to even more significant underestimations of emissions. Moreover, we have not considered the cost of last-minute flights, which might be much higher. 


Data accuracy and bespoke activity data collection are fundamental pillars for calculating a company’s emissions. Accurate and bespoke data informs decision-making, facilitates realistic target setting, and enables progress tracking. As limited assurance obligations become more prevalent, companies that invest in data accuracy and assurance processes will be better positioned to navigate regulatory landscapes, gain stakeholders’ trust, and remain competitive.  These practices are no longer just beneficial; they are essential.  

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