# Barclays PLC Financed Emissions Methodology **Cover Page Content:** Barclays PLC Financed Emissions Methodology BARCLAYS --- # Contents | Section | Page | |---|---| | Barclays' climate strategy | 02 | | Barclays' financed emissions methodology | 04 | | Our approach to calculate an estimate of financed emissions | 08 | | Our approach by sector | 15 | | Upstream Energy | 15 | | Power | 21 | | Cement | 25 | | Steel | 28 | | Automotive | 31 | | UK Housing | 35 | | UK Commercial Real Estate | 40 | | Aviation | 44 | | UK Agriculture | 48 | | Known areas for future enhancement | 51 | | Appendix 1 | 53 | | Appendix 2 | 54 | --- # Barclays' climate strategy ## A strategy for a better financial future Our strategy is underpinned by the way we assess and manage our exposure to climate-related risk. Our climate strategy is driven by consideration of relevant risks and opportunities and in alignment with our Purpose: working together for a better financial future for our customers, clients and communities. Our ambition is to be a net zero bank by 2050, aligning our financing with the goals and timelines of the Paris Agreement, by achieving net zero operations, reducing our financed emissions and financing the transition. Barclays' climate strategy has three pillars: 1. **Achieving net zero operations:** Barclays is working to reduce its Scope 1, Scope 2 and Scope 3 operational emissions consistent with a 1.5°C-aligned pathway, and counterbalance any residual emissions. 2. **Reducing our financed emissions:** Barclays is committed to aligning its financing with the goals and timelines of the Paris Agreement, consistent with limiting the increase in global temperatures to 1.5°C. 3. **Financing the transition:** Barclays is helping to provide the green and sustainable finance required to transform the economies, customers and clients we serve. ### Achieving net zero operations We are committed to achieving net zero operations and have maintained and further progressed on our milestones and targets. We continued to source 100% renewable electricity for our global real estate portfolio ahead of our 2025 target and track ahead of our target of 90% reduction of our Scope 1 and 2 market-based emissions against a 2018 baseline - reducing these emissions by 95%. We also enhanced our visibility and understanding of our supply chain emissions data through increased supplier engagements, unlocking new opportunities to seek to decarbonise our supply chain. ### Reducing our financed emissions We are also committed to reducing our financed emissions, which are those deriving from in-scope activities of the clients that we finance. To support our efforts to do so we have set 2030 financed emissions targets which integrate 1.5°C-aligned scenarios for eight high-emitting sectors: Upstream Energy, Power, Cement, Steel, Automotive manufacturing, Aviation, UK Agriculture and UK Commercial Real Estate, as well as 2025 targets for Upstream Energy and Power and a convergence point for our UK Housing portfolio. Our Climate Change Statement outlines the policy that supports our effort to reduce our financed emissions in relation to certain sensitive sectors. The Statement was updated in 2024 to add certain restrictions on financing upstream oil and gas, including unconventional oil and gas and additional Enhanced Due Diligence requirements for biomass. In addition, our Client Transition Framework, through which we evaluate in-scope corporate clients' progress toward business models aligned with a transition to a low-carbon economy, helps to inform our approach to reducing financed emissions, and our client engagement and decision-making processes. ## Barclays' climate strategy (continued) ### Implementing our strategy against a shifting landscape While we have made progress in our ambition towards becoming a net zero bank, and continue to see a significant opportunity to demonstrate our commercial leadership and support for our clients in the transition, we recognise that the shift to a low-carbon economy is complex and subject to significant uncertainties. Our ability to implement our climate strategy depends heavily on our clients' ability to commercially decarbonise their business models, which is influenced by a wide range of external factors, including market developments, technological progress and its financial viability, a stable and supportive policy environment, regulatory alignment, changes to societal behaviour, geopolitical developments and regional variations. 2024 marked the first year in which the monthly global average temperature exceeded $1.5^{\circ} \text{C}^1$ and real economy emissions and government policies to reduce them remain misaligned with maintaining global warming at a 1.5°C average. Further divergence in the policy environment across the major global economies is likely to exacerbate that trend in 2025. Since we set our first emissions targets in 2020, we have evolved our approach significantly, developing new data sources, tools and products to support our clients. Our climate strategy will continue to evolve as we continue to pursue our ambition of being a net zero bank by 2050 against the shifting and rapidly developing landscape. Additionally, as scientific evidence relating to climate change and information on real world progress towards net zero emerges, we will incorporate this into our thinking and our approach. Further information on our Climate Strategy can be found in our Annual Report. The focus of this paper is on our methodology to measure our financed emissions. + More details about our Climate Strategy can be found in our Annual Report: barclays.com/annualreport --- **Notes:** * 2024 data subject to independent limited assurance under ISAE (UK)3000 and ISAE 3410. Current limited assurance scope and conclusion can be found within the ESG Resource Hub: home.barclays/sustainability/esg-resource-hub/reporting-and-disclos * 1. https://climate.copernicus.eu/copernicus-2024-first-year-exceed-15degc-above-pre-industrial-level\#:~\:text=The\%20monthly\%20global\%20average\%20temperature, 2024\%2C\%20at\%2017.16\%C2\%B0C. --- # Barclays' financed emissions methodology Our approach is underpinned by our methodologies to estimate our full in-scope balance sheet financed emissions and to track sector level emissions against the goals and timelines of the Paris Agreement. Our approach to tracking our financed emissions involves calculating an estimate of our full in-scope balance sheet financed emissions, using a methodology developed using the PCAF Standard, and by setting targets for specific activities using our Blue Track™ methodology. Most of our emissions result from the activities of the customers and clients we finance, and those generated in their respective value chains – falling within the general definition of Scope 3 emissions (see page 5). For those activities where we have set targets, our climate dashboards$^1$ show our financed emissions targets over time - and our progress towards them - by comparing our financed emissions against a benchmark emissions level. Since 2020, Barclays has been a member of PCAF. In 2024, we have calculated an estimate of our full in-scope balance sheet financed emissions as at December 2023 (see section 1A on page 8). This has enabled us to calculate the coverage of our financed emissions reduction targets across our portfolio (including integration of 1.5°C-aligned scenarios and ranges for certain sectors to reflect dependencies outside our control that will determine how quickly our financed emissions can be reduced in these sectors), and to assess the extent to which our business is aligned to a well-below 2°C pathway. In certain circumstances, we will also consider restating, recalculating and/or re-baselining our metrics in order to reflect significant changes – such as material portfolio changes or data and methodological developments - that may compromise the relevance and consistency of our existing targets. ## Our approach to track our financed emissions and set targets This process is illustrated as follows: ```mermaid graph TD subgraph I. For full in-scope balance sheet A1[1. Quantify customer and client emissions] --> A2[2. Link emissions to financing] end subgraph II. For activities where we have set targets$^2$ B1[3. Construct Paris-aligned portfolio benchmark] --> B2[4. Aggregate to a portfolio-level metric] --> B3[5. Portfolio alignment measurement] end A2 --> B1 subgraph Key design questions Q1("What scope of emissions is considered?") Q2("What data is used for these calculations?") Q3("What financial activities are in scope?") Q4("What metrics are used for which sectors?") Q5("What scenario is used for the benchmark?") Q6("How are metrics aggregated?") Q7("How is financing linked to emissions?") end A1 -.-> Q1 A1 -.-> Q2 A2 -.-> Q3 A2 -.-> Q7 B1 -.-> Q5 B2 -.-> Q6 B2 -.-> Q4 ``` *Note: This representation is for illustrative purposes only. The approach is described in detail on the next page.* --- **Notes:** 1. Can be found in our Annual Report: barclays.com/annualreport 2. Includes convergence point set for UK Housing. --- # Barclays' financed emissions methodology (continued) ## Calculating our financed emissions Our approach to calculating financed emissions under the Blue Track™ methodology was already based on the PCAF Standard, with some key exceptions. Starting 2023, we extended the scope for calculating the financed emissions metrics to cover our full in-scope activities as well. Our approach to measuring our financed emissions consists of two key steps: 1. **For our full in-scope balance sheet:** calculating financed emissions based on methodology developed using the PCAF Standard by (1) quantifying customer and client emissions; and (2) attributing emissions to our financing. This covers the activities for which we have already calculated emissions under the Blue Track™ methodology. 2. **For activities covered under a target incorporating 1.5°C scenarios:** we updated our baseline emission calculations (following Steps 1 and 2 as set above) for year-end 2024 and continue to use the Blue Track™ methodology, (3) constructing Paris aligned benchmarks; (4) calculating portfolio-level metrics; and (5) measuring progress against our targets. ### I. For our full in-scope balance sheet #### 1. Quantifying customer and client emissions The first step is to quantify emissions produced by the customers and clients to which we provide financing. **Emission boundaries** The GHG protocol$^1$ defines emissions in three categories, or 'Scopes': a. Scope 1 emissions are those directly from owned or controlled sources, including from fuel burned by a company in their office and/or plant b. Scope 2 emissions are indirect emissions from the generation of power or energy purchased by a company c. Scope 3 emissions are those indirectly occurring in a company's value chain, including those arising from the production of goods and services provided by the company. Our calculations are based on the Scope 1 and 2 emissions for all our clients and Scope 3 emissions for specific activities. The PCAF Standard recommends a phase-in approach which requires Scope 3 reporting for select sectors over time. We acknowledge that the availability and consistency of reported Scope 3 emissions from clients varies across sectors. For the purpose of our current estimation we have estimated Scope 3 emissions only for the following activities where we have set targets integrating 1.5°C scenarios: Upstream Energy, Automotive manufacturing (downstream only), Aviation (upstream only) and UK Agriculture (upstream only). The PCAF Standard recommends calculating financed emissions at client-level granularity. However, we have sought to calculate financed emissions at client activity level. Our clients often participate in multiple activities with different emission profiles across the value chain, meaning their company-reported emissions may not have the level of granularity and consistency we require. We measure Scope 2 emissions using a market-based approach where available. However, such data is often scarce – so these emissions are often measured using location-based methods. **Key data sources** For the calculation of our financed emissions, we rely on external sources for emissions data – for which the quality is currently evolving. At an activity level, we employ the full range of PCAF Data Quality options to estimate client emissions. Please refer to the section on Data Quality on page 6. For certain activities, such as Cement and Steel, we rely on client reported emissions. Where we require company-reported emissions we source this data from S&P Trucost. For specific activities - such as Upstream Energy (fossil fuel exploration and production), Power generation, Automotive manufacturing and air travel from Commercial Aviation - we source physical activity data from specialist providers Asset Impact and PACE (Platform for Analysing Carbon Emissions). For our UK Housing and UK Commercial Real Estate (CRE) sectors, our primary data source is the information held within Energy Performance Certificates (EPC). Where we require an estimation of emissions based on economic activities, we either calculate the implied emission factors based on our own portfolios, or externally source them from the PCAF web-based emission factor database. **Fall-back methodologies** Our methodology seeks to assess emissions with the most granular approach possible. For corporate sectors, this means we model emissions metrics at the level of the specific subsidiary that we provide financing to, rather than aggregated at the level of the parent company. In cases where we do not have the necessary data to compute an emissions metric for the entity we lend to, we assume the financing is provided directly to the parent entity of the group. For an immaterial part of our balance sheet (c. 1%), where the appropriate sector fall-backs could not be reliably obtained we have used the respective asset class average economic emissions intensity to estimate emissions. ### Overrides In certain cases the data, fall-back inputs or modelled outputs are overridden using expert judgement. To facilitate this, we run a series of filtering exercises identifying which data - including both emissions and financial data - may be stale to the portfolio metric. We review this by comparing it to other published sources, including news articles and company reports, and through dialogue with our data vendors. Where there is a significant divergence identified with a supporting rationale - for example where a company has divested a material asset not yet reflected in the underlying data - we apply an override to the data. We may also apply overlays to remediate other known model limitations. ### Treatment of emission offsets We do not allow company-purchased offsets such as carbon credits to reduce emissions, as we believe it is important to base a metric on operational activities under a company's control. We therefore do allow company-operated removals, such as on-site carbon capture at a plant. Given that company-operated removals are currently marginal in the context of emissions, they currently have no impact on our portfolio-financed emissions metrics. ### Data quality The PCAF Standard provides guidance to measure data quality through a Data Quality (DQ) hierarchy ranging from DQ1 (best) to DQ5 (worst), specific for each asset classes. Our estimation of data quality is based on the PCAF Standard's guidance. Our current data quality is dispersed across DQ1 and 2 (reported emissions) to DQ3 (deriving emissions from production data) and DQ4 and 5 (using revenue- and asset-based emission factors). For activities where we set targets, data quality is mostly concentrated across DQ1, 2 and DQ3. We disclose data quality scores across each of our sectors. Our data vendor does not provide a split for reported emissions between DQ1 and DQ2. Hence, where we have relied on reported emissions sourced from the data vendor, we have conservatively used DQ2 for calculating DQ scores. This indicates that we need to consider the current estimate of financed emissions for these activities as highly preliminary and indicative only, and which can change materially as we improve data quality. ### 2. Attributing emissions to our financing The second step is to attribute customer and client emissions to the financing provided to measure absolute emissions - which calculates Barclays' share of the company's emissions over time. This involves defining in-scope financing activities, determining how provided financing should be spread across the various business activities for diversified corporates, and appropriately linking each financing portion to the respective absolute emissions or emissions intensity metric. **Products in scope** We have aligned our scope of coverage not only to the PCAF Standard but also, notably, to include undrawn commitments, contingent liabilities, and capital markets financing. We include capital markets financing facilitated in the last 12 months prior to the reporting date as per the PCAF Standard on Facilitated Emissions published in December 2023. **Our measurement of financing** The majority of Barclays' lending to corporate sectors is in the form of Revolving Credit Facilities (RCF), which are typically undrawn - particularly in the Investment Bank. As a result we include both the drawn and undrawn portions of the facilities as of the reporting date. The use of limits is less applicable for lending in mortgages captured in the UK Housing sector, so we instead use the drawn balance in line with the PCAF Standard. For our corporate financing activities, we also considered using the drawn amount, exposure at default (EAD) or risk-weighted assets (RWAs). There are arguments for using drawn amounts - they better reflect spot exposure and would form part of the company's liabilities, for example - however, drawn amounts are typically much lower than the limit and using them would under-represent the financing Barclays has contractually committed to provide. It would also expose carbon metrics to volatility that cannot be controlled - for example, at times of an increase in drawn amounts - that would not be informative for the management of our activity, and that may be related to the near-term liquidity needs of a company rather than investment in carbon-generative activities. In addition to lending, our model considers debt and equity financing arranged in the capital markets sourced from Dealogic as in scope. This is a key element of our approach and ensures we are properly accounting for the breadth of support we provide our corporate clients through our capital markets franchise. We use the amount arranged over the past 12 months prior to the reporting date, which is pro-rated by the Dealogic league table credit if there are several banks in the syndicate. However, for deals where Barclays has been a co-manager, since Dealogic assigns zero credit to co-managers we pro-rate it by the Barclays fee share. Barclays is allocated 33% of the pro-rated financing amount which aligns with the PCAF Standard on Facilitated Emissions. **Emissions attribution** After determining a company's total emissions and the total amount of financing Barclays has provided to the company, we must determine how much of the company's total emissions to attribute to Barclays' financing. For example, if we provide £100 in financing to a fossil fuel company, we need to determine what percentage of their total financing that £100 represents. We take an activity-based view of calculating financed emissions. If a company straddles multiple activities - for example having one subsidiary that extracts fossil fuels and another that generates power - the former would be counted as part of the Upstream Energy portfolio, and the latter as part of the Power portfolio. We have also consistently used the book value of equity and debt to measure the attribution factor for all clients, while the PCAF Standard recommends using the Enterprise Value Including Cash (EVIC) for listed entities. In the case of UK Housing and UK CRE, property emissions are allocated on the basis of loan-to-valuation (LTV) - with the valuation assessed at the point of origination where available, and otherwise at the latest value (fixed). In the Power and Automotive sectors, loan facilities and capital market transactions are assumed to have a zero intensity if the proceeds are used for zero- or low-carbon activities - renewable power generation, for example - and are classified as 'green' dedicated purpose financing under Barclays' Sustainable Finance Framework (SFF)$^1$. --- **Note:** 1. The Greenhouse Gas Protocol, A Corporate Accounting and Reporting Standard, www.ghgprotocol.org/corporate-standard --- ### II. For activities with targets integrating 1.5°C scenarios #### 3. Constructing Paris-aligned portfolio benchmarks We use an external climate scenario to construct a Paris-aligned portfolio benchmark that defines how a given financing portfolio will need to reduce emissions over time. These scenarios have been selected because they have been developed by reputable external providers, are aligned with the Paris Agreement goals, and are sufficiently granular for our needs. When we released the first edition of this Whitepaper in 2020, the best available scenario to develop Paris-aligned benchmarks for our financing portfolios was the International Energy Agency's (IEA) Sustainable Development Scenario (SDS). At the time, SDS was aligned to a 1.7°C world and was a roadmap for realising net zero CO2 emissions in the Upstream Energy sector by 2070. The 2025 targets previously set for the Upstream Energy and Power sectors were informed by this SDS scenario. Later, we updated BlueTrack™ to include 2030 targets for Upstream Energy, Power, Cement, Steel and Automotive sectors based on the IEA's NZE2050 scenario. These targets remain unchanged. The NZE2050 scenario is aligned with a goal to limit global temperature rises to 1.5°C with a 50% probability. Our 2030 financed emissions targets for five sectors (Power, Cement, Steel, Automotive manufacturing, and Aviation) are expressed as ranges. The upper end of each range represents the reduction needed to align with the 1.5°C benchmark pathway at the time we set these targets. The lower end reflects our assessment of sector and client commitments at that time. For UK Housing and UK Agriculture, we have set a 2030 convergence point and target respectively, based on the UK Climate Change Committee (CCC)'s Balanced Net Zero (BNZ) pathway, which sets out a roadmap for decarbonising the UK economy by 2050. For UK CRE, we have set a 2030 target based on the Carbon Risk Real Estate Monitor (CRREM) pathways, which offer decarbonisation trajectories for different property types and are considered the most appropriate by industry standards. The CRREM scenario provides the relevant granularity as it understands that different properties will have different decarbonisation levers and trajectories. For the Aviation sector, we have set a 2030 target based on emissions from commercial air travel, in accordance with the Mission Possible Pathway's Prudent (MPP PRU) scenario published in 2022. It is a 1.5°C-aligned aviation decarbonisation strategy highlighting the efforts required to reach to net zero emissions in the sector. #### 4. Aggregating company-level measurements to a portfolio-level metric Next, we aggregate company-level emission measurements and financing information into portfolio-level metrics. In this step, in addition to the absolute financed emissions, we also calculate the physical intensity. This is the average intensity of our portfolio, weighted by our exposure to each company, typically adjusted for the proportion of revenue they generate from the in-scope activity. This defines how much $\text{CO}_2\text{e}$ (carbon dioxide equivalent) is released on average for a certain amount of economic activity or material produced for the activities where we have set targets - except for Upstream Energy and UK Agriculture. We use absolute emissions for the Upstream Energy and UK Agriculture sectors, whose decarbonisation pathways rely on a reduction in production volume as well as on a reduction in intensity. When we set a target based on an absolute emissions metric we measure the share of emissions of our financing relative to the company's value. As such, an absolute measurement is subject to significant volatility. For example, any event that changes the company valuation of a corporate client could increase or decrease the absolute emissions they contribute to our portfolio, despite no change in real-world emissions. #### 5. Portfolio alignment measurement We have set targets for eight sectors listed in this paper, articulated as percentage reductions compared to a baseline reporting year, and a convergence point for our UK Housing portfolio. Our financed emissions in our target year must therefore be calculated on a consistent basis to this baseline. However, as we continue to refine our methodology and as data standards improve over time, it will become increasingly difficult to recalculate our financed emissions for the baseline year. To manage the impact of these changes, we have adopted a principles-based approach to guide whether prior metrics and baselines should be restated or re-baselined. We will continue to review and evolve our approach as our processes mature and as accounting practices become clearer: * A restatement will involve updating the historical starting point for a period and, if the impact is greater than five percentage points, recalculating the historical performance. * A re-baseline will involve keeping the historical performance constant and re-calculating the current period baseline to ensure consistency when reviewing performance. The indicative historical baseline will also be disclosed. As a result, the reported baseline metrics may change from one reporting period to another. Where information is restated or re-baselined, this will be identified or explained. We calculate our annual progress against our target by calculating a theoretical baseline based on the recalibrated metric and the cumulative progress made up to the previous year. This ensures a fair representation of the cumulative progress we have made to date. Additional information, including a worked example for Upstream Energy, is provided in Appendix 2. --- # Our approach to calculate an estimate of financed emissions ## Deriving the scope of coverage of our activities relevant for measuring financed emissions We have prepared an estimate of our full in-scope balance sheet financed emissions. The scope of financing covered goes beyond the asset classes covered by the PCAF Standard, ensuring alignment for activities where we have already set targets incorporating 1.5°C scenarios. 1. **What is the approach to determining in-scope activities?** a. As a starting point to estimate the scope of activities for which we want to assess the financed emissions, we have considered the Group balance sheet as at FY2023. Hence, these numbers follow a lag of one year when compared to other disclosures based on December 2024 in this paper. The lag of one year is due to the lead time required to fully analyse our entire in-scope exposures. b. We have subsequently excluded two categories: i. Assets specifically excluded by the PCAF Standard (2.b) ii. Assets for which the associated emissions are already being measured and reported elsewhere. (2.c). c. We have then included additional activities for which PCAF has not yet established the methodology - but which we believe should be considered for calculating financed emissions (3.a). 2. **What has been excluded from the Group-level balance sheet to arrive at the in-scope activities?** a. The calculated financed emissions of counterparties constitutes Scope 3 Category 15 ('Investments'), following the PCAF Standard's use of Greenhouse Gas Protocol definition. b. We have excluded assets for which the methodology for measuring financed emissions is not covered under PCAF. Examples include retail lending (personal lending, retail cards), cash and bank balances, trading portfolio assets and reverse repos. An exhaustive list has been provided in the exhibits below. c. We have excluded the emissions associated with our Property, plant and equipment and retirement benefit assets. Similarly, we have excluded lending to internal Barclays counterparties. 3. **What has been additionally included to arrive at the in-scope activities?** a. We have included certain in-scope activities for specific sectors where we have already set targets not yet covered by the PCAF Standard. These include: i. Undrawn commitments for loans and advances ii. Contingent liabilities - for instance Trade Finance bonds, guarantees and/or indemnities and letters of credit. b. We have included capital markets financing activities for our calculations, noting that PCAF released its Standard for calculating facilitated emissions based on capital markets financing activities in December 2023. Aligned to the PCAF Standard, we consider 33% of Barclays' share of capital markets financing activities to calculate the financed emissions. 4. **How does our approach align with the PCAF asset class definitions?** a. We have identified the scope of coverage based on a methodology developed using the PCAF Standard. The tables below map our choice of in-scope financing to the preferences laid out by the PCAF Standard. ### Figure 1: Identification of in-scope exposure to calculate financed emissions | Category | Reasons | |---|---| | **Total Barclays balance sheet** | | | **Exclusions:** | | | Cash and bank balances, Cash collateral and settlement balances, Derivative financial instruments, Goodwill and intangible assets, Current tax assets, Deferred tax assets, Other assets, Trading portfolio assets, Reverse Repos, and Retail lending (personal lending, retail cards) | Exposures specifically excluded by the PCAF Standard | | Property, plant and equipment | Emissions covered under Barclays' Scope 1 and Scope 2 | | Retirement benefit assets | Emissions on Barclays Bank UK Retirement Fund reported separately as part of Task Force on Climate-Related Financial Disclosures Report 2023 | | **Total Barclays on-balance sheet exposure in scope for computing financed emissions** | | | **Inclusions:** | | | Total in-scope undrawn commitments and contingent liabilities | | | Capital markets financing (33% of Barclays' share) | | | **Total Barclays activities considered for financed emissions calculations** | | ### Figure 2: In-scope activities mapped to PCAF asset classes | Asset classes | What is covered | Comments | |---|---|---| | Listed Equities and Corporate Bonds (excluding sovereigns) | Equity and debt securities. Known purpose bonds will not be separated out and will be treated as general corporate purpose bonds | Sovereign counterparties are considered as a separate asset class | | Business Loans (including Contingent Liabilities) | Business loans. Contingent Liabilities (Letters of Credit, BGIs). Also includes undrawn commitments from sovereigns and project finance | Excludes drawn component for sovereigns which is considered as a separate asset class | | Unlisted Equities | N/A | Any financing will end up being treated as business loans. Exposure is not material for Barclays | | Mortgages | Secured mortgages | N/A | | Project Finance | All project finance | N/A | | Commercial Real Estate | For UK Commercial Real Estate loans where we have set targets | Financing to Commercial Real Estate where we have not set targets are considered as business loans | | Motor Vehicle Loans | N/A | Exposure is not material for Barclays | | Capital Markets Financing | Deals where Barclays' role was as underwriter or co-manager for DCM, ECM and Loans, including for sovereign entities | Excludes securitisation and advisory services. Excludes activities where clients did not receive proceeds (classified as No Proceeds to Issuer by Dealogic) | | Sovereign Loans and Debt | Sovereign loans and debt securities | N/A | ## Estimating the financed emissions for in-scope activities Financed emissions are calculated by applying an attribution factor to client emissions. Client emissions are calculated using a range of data quality options, ranging from reported emissions to sector-average emission factors. #### 1. What scope of emissions are included, and why? a. We have computed our overall financed emissions based on our clients' Scope 1 and Scope 2 emissions as of December 2023. b. For sovereigns, we have separately calculated Scope 1 emissions with and without the impact of land use, land-use change, and forestry (LULUCF). c. We note there are specific emissions required to be reported separately by the PCAF Standard. In our current estimate, we have not yet separately considered the following as it will entail additional modelling and/or data sourcing: i. Biogenic emissions ii. Avoided and removed emissions iii. Impact of carbon offsets iv. Lifetime emissions within project finance. d. The PCAF Standard recommends a phase-in approach requiring Scope 3 reporting for select sectors over time. We acknowledge that the availability and consistency of reported Scope 3 emissions from clients varies across sectors. For the purpose of our current estimation, we have included Scope 3 emissions only for activities where we have set targets incorporating a 1.5°C-aligned scenario. e. As the level of consistency and transparency of Scope 3 emissions reported and fall-back emission factors improve, we will also evaluate increasing the span of our financed emissions reporting to cover additional activities under our clients' Scope 3 emissions. #### 2. What data is used for these calculations? a. Based on the PCAF Standard, we use a range of data feeds to estimate client emissions: i. We source emissions data for our clients from S&P Trucost ii. For specific activities such as Upstream Energy, Power generation and Automotive manufacturing, we source physical activity data from Asset Impact, a specialist provider of asset-level data iii. For Aviation, we source physical activity data from PACE, an external data provider iv. For UK Housing and UK Commercial Real Estate (CRE) sectors, we source EPC data from the Department for Levelling Up, Housing and Communities (DLUHC) v. For UK Agriculture we use internally available activity data on customers' farming activities vi. Where we require estimation of emissions based on economic activities, we either calculate implied emissions factors based on our portfolios or externally source them from the PCAF web-based emission factor database (September 2024 version) and S&P sector averages (December 2024 version). b. We also source client financial data from S&P Capital IQ to calculate client emissions based on the emission factors. c. Barclays' on-balance-sheet, undrawn commitments and contingent liabilities data is sourced from internal databases. Barclays' capital markets financing activities data is sourced from Dealogic. ### Figure 3: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for calculation of full in-scope financed emissions | |---|---|---|---| | **Barclays' exposure** | Lending | Internal | December 2023 | | | Capital Markets | Dealogic | December 2023 | | | Revenue share | S&P Trucost | December 2023 | | **Client emissions** | Reported/estimated | S&P Trucost | December 2023 | | | Emissions factors | PCAF Database (Scope 1 and 2), S&P Trucost Sector Averages | PCAF emissions factor database, September 2024 release, S&P Trucost sector averages, December 2024 release | | **Client financials** | Total Debt | S&P CapIQ | December 2023 | | | Total Equity | S&P CapIQ | | | | Total Revenue | S&P CapIQ | | | | Total Assets | S&P CapIQ | | **Notes:** 1. NAICS - North American Industry Classification System. 2. BIC - Barclays Industry Classification, the system used for to classify clients and counterparties for internal Barclays purposes. #### 4. How do we calculate client emissions? a. Our underlying approach to estimating client emissions is to calculate these separately at an activity level. b. We use the business activity revenue share data from S&P Trucost as a starting point to identify the activity mix of a client. This is then multiplied by the appropriate revenue-based emissions factors to calculate 'emissions share' from each activity. c. Where the revenue share is not available from S&P Trucost, we assume the business activity is 100% aligned to the NAICS$^1$ code of the counterparty. Where the NAICS code of the counterparty cannot be determined with certainty, we assume the business activity is 100% aligned to the BIC$^2$ code. d. In cases where sufficient data is not available at the counterparty level, we source emissions data at the parent level. e. We employ a mix of DQ options to estimate client emissions from each activity. We have calculated and reported DQ score at an activity level for Scopes 1, 2 and Scope 3 separately. f. For Mortgages, we source EPC data to estimate emissions or use a fall-back to sub-portfolio economic intensity if EPC is unavailable. ### Figure 4: Approach for estimating emissions mapped to PCAF DQ scores | Activity | Data Quality option employed | PCAF DQ Mapping | |---|---|---| | Upstream Energy | Estimated based on production data | DQ 3 if production data and company value is available | | Power generation | Estimated based on average portfolio economic intensity if production data is not available | DQ 5 if production data or company value is not available | | Automotive manufacturing | Estimated based on production data | DQ 3 | | Aviation | Reported emissions | DQ 2 if reported emissions and company data is available | | Cement | Estimated based on production data | DQ 5 if production data or company value is not available | | Steel | Estimated based on average portfolio economic intensity if production data is not available | DQ 3 if production data and company value is available | | UK Agriculture | Estimated based on data available in EPC certificates | DQ 5 if production data or company value is not available | | Mortgages | Estimated based on average sub-portfolio economic intensity if EPC is not available | DQ 3 if EPC is available | | Other activities | Reported emissions if available | DQ 5 if EPC is not available | | | Fall-back to economic-activity-based emissions factors if reported emissions are not available | DQ 2 if reported emissions and company data is available. DQ 4,5 if reported emissions or company data is not available | ### Figure 5: Illustrative calculation of Scope 1 and 2 emissions shares | Trucost business activity ID | Revenue share % | Emission factor linked to the business activity | Emissions share (%) | Mapping to sectors where we have set targets | Covered under targets incorporating a 1.5°C scenario | Approach to calculating emissions | |---|---|---|---|---|---|---| | A | 40% | 3 | 57% | Oil and Gas exploration | Yes | Estimated based on production data | | B | 30% | 2 | 29% | Power generation | Yes | Estimated based on average portfolio economic intensity if production data is not available | | C | 30% | 1 | 14% | Power distribution | No | Reported emissions if available. Fall-back to economic-activity-based emissions factors if reported emissions are not available | | **Total** | 100% | | 100% | | | | #### 5. How is provided financing linked to company-level emissions metrics? When calculating our proportion of a client's emissions, we use financing provided as at December 2023 as a proportion of book value of total debt and equity - taken directly from the company balance sheet. Where equity is negative, only the total debt is used - and, where neither equity nor debt is known, total assets are used. The PCAF Standard recommends using EVIC for calculating company value where it is available. While there is some merit in using EVIC for listed companies, and while some of our peers prefer this approach, upon careful consideration it has been agreed to consistently use the book values - 'total equity + total debt' - where available, and 'total assets' as a fall-back approach permitted under the PCAF Standard. Given that PCAF-based emissions reporting is an annual activity, and where progress in financed emissions needs to be monitored across multiple years, it is prudent to opt for an approach that is standardised and scalable across the entire portfolio - and on which the effect of market volatility is limited across time periods. ### Figure 6: Indicative approach to calculate financed emissions ```mermaid graph TD subgraph Attribution Factor AF[Attribution factor = Exposure / Company value] E[Exposure] CV[Company value] end subgraph Client Emissions CE[Client emissions] AWD[Activity-wise emissions data] RE[Reported emissions] PABC[Physical activity-based calculations] EABC[Economic activity-based calculations] end subgraph Final Calculation FE[Financed emissions = Attribution factor x Client emissions] end E --> AF CV --> AF AF --> FE CE --> FE AWD --> CE RE --> AWD PABC --> AWD EABC --> AWD E --> E subgraph Exposure Components OLAS[On-balance-sheet lending and securities] UC[Undrawn commitments] CMF[Capital markets financing] end E --- OLAS E --- UC E --- CMF subgraph Client Emissions Calculation ES[Emissions share] MWE[Multiply by activity-wise Scope 1 and 2 emission factor] AEC[Assume 100% of emissions from counterparty's industry classification code] RSAV{Revenue share available?} end AWD --> ES RSAV -- Yes --> MWE RSAV -- No --> AEC MWE --> ES AEC --> ES subgraph Company Value Components DTES[Source Total Debt + Equity or Total Assets to measure company value] end ``` *Note: *Emissions share = Revenue share x Revenue-based emissions factor + Parent company's value is used with parent company's reported emissions.* --- # Our approach by sector – Upstream Energy The Upstream Energy sector covers the production, processing and distribution of hydrocarbon fuels and their derivatives. Hydrocarbons are mostly used as an energy source, but are also used in the petrochemical industry to produce plastics, solvents and other intermediate products. This sector generates emissions mainly through the combustion of fuels by end users – for example automotives and power generation - but also through production processes including flaring, venting and unexpected leaks across the supply chain. Efficiency upgrades, early detection of leaks and carbon capture may reduce emissions, but decarbonisation will largely rely on the expansion of renewable energy capacity to replace fossil fuels. ### 1.A. What metrics are used as benchmarks for the Upstream Energy sector and why? 1.A.1 Our model uses an absolute emissions metric to measure the performance of our Upstream Energy portfolio. 1.A.2 An absolute emissions metric is a measurement of the total quantity of GHGs emitted by an entity over time. For example, if a company emits 10 tonnes of $\text{CO}_2$ this year, its absolute emissions measurement would be 10 tonnes. 1.A.3 We have chosen this metric because the Upstream Energy sector cannot reduce its emissions intensity beyond a certain point - burning a barrel of oil will always produce a similar quantity of emissions, for example - and an emissions intensity metric will not capture the absolute reduction in production necessary for fossil fuel producers to be aligned with the Paris Agreement. 1.A.4 We recognise that many Upstream Energy companies are diversifying into alternative businesses, including renewable power generation. However, we capture the growth in renewable power through the Power metric to align as closely as possible with the scenario benchmark. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 When we released the first edition of this Whitepaper, the best available scenario to develop Paris-aligned benchmarks for our financing portfolios was the SDS. 1.B.2 As a result, Upstream Energy was benchmarked against the SDS Fossil Fuel Production projection for the OECD, with the absolute emissions projection taken from the SDS scenario using fossil fuel production forecasts. 1.B.3 Since then the IEA has released the NZE2050 scenario, which is more ambitious and realises net zero $\text{CO}_2$ emissions in the Upstream Energy sector by 2050. This scenario is aligned with a goal to limit global temperature rises by 1.5°C with a 50% probability. 1.B.4 As a result, we now benchmark Upstream Energy against the NZE2050 World scenario which requires a c.38% reduction in $\text{CO}_2$ from all energy-related sources by 2030. 1.B.5 Detailed production forecasts are not provided by the IEA, so we have used the total emissions from Upstream energy as a suitable proxy. The scenario is not available at an OECD level - however, in the SDS scenario, there was limited difference between the two benchmarks. 1.B.6 The IEA also separately publishes a methane tracker that suggests methane emissions can reasonably be reduced by c.75% by 2030. When combined with $\text{CO}_2$, this represents a c. 40% reduction in emissions on a $\text{CO}_2\text{e}$ basis. ### 2.A. What scope of emissions is included, and why? 2.A.1 For the Upstream Energy sector, we include all companies that extract fossil fuels. 2.A.2 Any emissions associated with fossil fuels extracted by another company are excluded, unless we have a financial relationship with them. As a result, a company solely involved in refining or transporting oil, for example, is excluded. 2.A.3 The emissions from production (Scope 1 and 2) are included in the metric, as well as refinery and combustion emissions from the produced fuel. Most of the emissions related to a given unit of fossil fuels are released into the atmosphere during combustion - for example by the end user as part of Scope 3. This decision was made to recognise that both producers and consumers of fossil fuels are responsible for reducing the resulting emissions. 2.A.4 We exclude any downstream emissions associated with non-energy purposes, such as petrochemical manufacturing. 2.A.5 We also include Natural Gas Liquids (NGLs) which form part of the natural gas production stream that becomes liquid in surface conditions. There are various types of NGLs and, chemically, they belong to the part of the spectrum between dry gas (simple methane) and crude oil, with combustion factors falling between them. 2.A.6 The IEA does not publish detailed information (volume or emissions) on NGLs, and Asset Impact does not provide data on production volumes of each NGL type (only at an aggregated country/technology level). As a result, we model the emissions associated with combustion using expected combustion rates and emissions factors, as detailed in Figure 7. ### Figure 7: Our approach to estimating intensity factors by fossil fuel | Oil | Gas | Natural Gas Liquids (NGLs) | Coal | |---|---|---|---| | Oil forms a significant part of our portfolio and extraction technologies are very diverse. We use the OPGEE$^1$ (Oil Production Greenhouse Gas Emissions Estimator) and the PRELIM$^2$ (Petroleum Refinery Lifecycle Inventory Model) lifecycle assessment models to calculate Scope 1 and 2 emissions, which provides increased granularity of energy intensity. For example, oil extracted from tar sands can be three times more intensive than the global midpoint on a $\text{CO}_2\text{e}$ basis. This is consistent with our sensitive sector policy requirements for oil sand producers. OPGEE is a peer-reviewed, independent academic study - and the model can provide estimates for $\text{CO}_2$ and methane both separately and on a combined ($\text{CO}_2\text{e}$) basis. Scope 3 $\text{CO}_2$ emissions factors are estimated using the annual emissions and production levels reported by the IEA. | Extraction technologies for gas are less diverse and detailed studies of production intensity are less common. We use the National Energy Technology Laboratory (NETL)$^3$ lifecycle assessment analysis to estimate $\text{CO}_2$ emissions factors, allowing us to differentiate by extraction technology (conventional, unconventional, deepwater, CBM). While NETL is a study of North American gas fields, we feel this methodology is suitable because the $\text{CO}_2$ component of gas extraction is reasonably consistent across geographies. We use the IEA Methane Tracker to estimate methane at a country and extraction technology level. There can be a significant divergence in methane intensity at a country level and those with stronger regulations in place often observe far lower intensities than average. The intensity of Norwegian gas, for example, is on average around one hundred times less intensive than the median - and around one thousand times less intensive than the most intensive country. Scope 3 $\text{CO}_2$ emissions factors are estimated using the annual emissions and production levels reported by the IEA. | Scope 1 and 2 emission factors are assumed to be the same as gas, given they are extracted as part of the same process. We source Scope 3 emissions intensity factors for oil and gas from the IEA. However, the IEA does not publish detailed information on NGLs, nor does Asset Impact provide data on production volumes of each NGL type. As a result we estimate emissions factors using a weighted average of all NGLs. This is calculated using NGL production volumes in the US (per 2021)$^5$ and combustion rates and emissions intensities from the Energy Information Administration (EIA)$^6$. The derived intensity factor is less than half that of gas, despite the emissions intensity being higher. This is because propane and ethane are the two most commonly produced NGLs (>50%) and the latter is rarely used for Energy purposes. | Detailed studies of coal Scope 1 and 2 intensity factors are also less common but generally form a much smaller part of the overall lifecycle emissions compared to oil and gas. There is, however, significant divergence in the energy and carbon content of different types of coal. As coal production from Asset Impact is measured in tonnes rather than mega joules (MJ), we first estimate the energy content - and this can vary significantly according to the type of coal being extracted, whether that is lignite, sub-bituminous, bituminous, or anthracite, for example. We estimate using the mid-point of a range provided by the US Environmental Protection Agency (EPA)$^7$. We then estimate emissions from the energy content. $\text{CO}_2$ emissions do not vary strongly with extraction technology, and are assumed to be 1% of lifecycle emissions as estimated by the EPA. Methane emissions, however, can vary depending on the extraction method - the average methane intensity of underground mines, for example, is around eight times more intensive than surface mines. We assess methane using the Global Energy Monitor$^8$, which follows the methodology developed by the Pacific Northwest National Laboratory and the EPA. Scope 3 $\text{CO}_2$ emission factors are estimated from the EPA. | --- **Notes:** 1. www.eao.stanford.edu/research-project/opgee-oil-production-greenhouse-gas-emissions-estimator 2. www.ucalgary.ca/energy-technology-assessment/open-source-models/prelim 3. www.netl.doe.gov/ 4. www.iea.org/data-and-statistics/data-tools/methane-tracker-data-explorer 5. www.eia.gov/dnav/pet/pet_sum_snd_d_nus_mbbl_a_cur-2.htm 6. www.eia-international.org/ 7. www.epa.gov/ 8. www.globalenergymonitor.org/ --- ### Figure 8: Key criteria for assessing the Global Warming Potential (GWP) of methane | No | Criteria | Description | Preferred measure | |---|---|---|---| | 1 | Comparability | The standard convention set out by the United Nations is to measure GHGs using a GWP100 basis. Typically, companies disclose emissions on a GWP100 basis, which also aligns to the approach adopted by our peers and aids comparability across the industry. Some clients have started to disclose methane on a standalone basis although coverage is currently low. | GWP100 | | 2 | Credibility | Methane is much more potent than $\text{CO}_2$ but is also shorter-lived, with an average life of 12 years. This makes it challenging to compare. The Intergovernmental Panel on Climate Change (IPCC) is currently debating the usefulness of a GWP20 measure, given a GWP100 may underestimate the short-term impact of methane (and other short-lived gases). | GWP20 | | 3 | Data quality | Data quality of methane is typically weaker than $\text{CO}_2$ given a significant proportion comes from fugitive sources. While a modelled estimate at a portfolio level will be reasonably accurate, it will be less so at a counterparty level where operating practices differ. A GWP 100 measure reduces the overall impact of methane in the portfolio, thus reducing reliance on poor data. | GWP100 | 2.B.6 We recognise this methodology is likely to show significant variances in respect of methane emissions at the underlying company level, given it does not reflect the underlying operations of each company but instead applies an industry-based estimate - which can lead to very different outcomes. 2.B.7 Using company disclosures instead of an estimate would pose a number of challenges around data sourcing and coverage, comparability and time consistency, that we are not in a position to address in the short term. As a result we intend to improve the quality of methane measurement. In this context, during 2024 we continued to work with RMI's Centre for Climate-Aligned Finance. 2.B.8 We acknowledge that $\text{CO}_2$ and methane have different warming characteristics and aggregating them requires the use of assumptions. However, given the data quality issues, we have decided to aggregate it into a $\text{CO}_2\text{e}$ measure using a standard GWP100 approach widely used in company reporting. Figure 8 describes the key criteria that have guided our selection. 2.B.9 Scope 3 $\text{CO}_2$ emissions factors are estimated using the annual emissions and production levels as reported by the IEA. Figure 9 shows the derivation from the IEA. ### 2.B. What data is used for these calculations? 2.B.1 We model company emissions by combining external fossil fuel production databases with assumptions about emissions factors. This is similar to the approach used in the PACTA$^1$ methodology. 2.B.2 Fossil fuel energy content for oil, gas and NGLs (MJ) and production for coal (tonnes) is obtained from specialist data provider Asset Impact and converted into emissions using a variety of techniques depending on the fuel - as shown in Figure 7. 2.B.3 Emissions relating to fossil fuel extraction can vary significantly depending on the extraction method, region of production and operational processes. 2.B.4 Methane emissions vary significantly across regions, depending on the source. We source methane emissions through extraction technology and country data from the IEA Methane Tracker. These emissions are aggregated using Asset Impact's production data. 2.B.5 We have specifically chosen not to use company-reported data given the ongoing, industry-wide challenges around methane measurement, and instead model it ourselves. This approach calculates a level of methane inherent in our portfolio, which is then attributed to each company according to their production, technology and location mix of underlying assets. ### Figure 9: Derived emissions factors from the IEA for fossil fuels$^1$ | Technology | Annual emissions (Mt$\text{CO}_2$) | Annual production (Mtoe) | Emission factor ($\text{gCO}_2$/MJ) | |---|---|---|---| | Coal | 15,667 | 4,190 | 89 | | Oil | 11,334 | 4,592 | 59 | | Natural Gas$^2$ | 7,520 | 3,464 | 52 | | NGLs$^2$ | n/a | n/a | 24 | 2.B.10 For companies with substantial footprints that do disclose emissions - generally at parent company level, with limited breakdown per activity or per subsidiary - available disclosures are used to check and, where appropriate, override the value calculated from production data. 2.B.11 Data coverage for companies classified as Upstream Oil and Gas and miners is greater than 90%. This is driven by better data coverage for the larger borrowers versus lower coverage in smaller borrowers. Over time we will look to improve data coverage through our vendors, improved company disclosures and client outreach. 2.B.12 To minimise potential understatement of our emissions, we estimate our financed emissions for Upstream companies for whom we lack production data. For these companies, we estimate absolute emissions based on the portfolio average of the sub-sector. ### 3.A. What financing activities are considered in scope, and why? 3.A.1 All financing activities shown on page 6 are in scope. 3.A.2 Green financing for activities in the Upstream Energy sector does not have a differentiated treatment for the purposes of financed emissions$^3$. ### 3.B. How is provided financing linked to company-level emissions metrics? 3.B.1 When calculating our proportion of a company's absolute emissions, we use financing provided as a proportion of book value of total debt and equity (taken directly from the company balance sheet). Where equity is negative, only the total debt is used - and, where neither equity nor debt is known, total assets are used. 3.B.2 We do not use the traditional measurement of enterprise value (EV) as it relies on market capitalisation, which can create volatility - Barclays' absolute emissions would increase if a company's stock price falls, for example, and vice versa. In addition, EV uses debt net of cash, which is why the PCAF Standard recommends using EVIC-which is increasingly becoming the norm. Using EV also would not be consistent with the definition of 'financing' and would lead to the equity and debt holders owning more than 100% of a company's emissions. Note that, while this approach reduces volatility, it will not eliminate it where there are material shifts in a company's book value of total debt and equity. 3.B.3 We are aware that an undrawn commitment does not form part of a company's balance sheet value. It is nonetheless included in exposure in our model as it is a better reflection of the balance sheet commitment we make. This leads to an over-allocation of emissions to Barclays versus other funders of a company when allocating an ownership share to Barclays, given most companies multi-bank and have a large book value of debt and equity. ### 4.A. How are client-level measurements aggregated for the Upstream Energy portfolio? 4.A.1 Total absolute emissions are calculated as a simple sum of Barclays' fair share of each company's absolute emissions. Figure 10 contains a full list of data sources used for each calculation component. ```mermaid graph TD subgraph Portfolio Metric Calculation A1(Σ Company) -- Barclays financing --> A2{Company emissions / Company value} A2 -- x --> A3[Company emissions] A2 -- x --> A4[Production] A4 -- Emission factor --> A5[Company emissions] A5 -- x --> A6[Production] end ``` --- **Notes:** 1. www.iea.org/reports/world-energy-outlook-2024 2. www.eia-international.org/ 3. In older versions of this paper, we have stated that certain sectors are 'not eligible for dedicated purpose green financing under Barclays SFF'. This has meant that activities in those sectors cannot be treated as 'green' for the purposes of financed emissions and assumed to have zero intensity, as is the case for activities which are classified as dedicated purpose green financing under the Barclays SFF in the Power and Automotive sectors. We have sought to clarify this further in this latest version of our Financed Emissions Methodology Whitepaper. --- ### Figure 10: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---|---|---|---|---| | **Barclays' financing** | Lending | Internal | December 2024 | **$\text{CO}_2$ emissions factors Scope 3** | Oil | IEA | 2024 estimate from 2024 WEO Report | | | Capital Markets | Dealogic | December 2024 | | Gas | IEA | 2024 estimate from 2024 WEO Report | | **Company value** | Total Debt | S&P CapIQ | December 2024 | | Coal | EPA | 2018 | | | Total Equity | S&P CapIQ | December 2024 | | NGLs | EIA | 2021 | | | Total Assets | S&P CapIQ | December 2024 | **Production** | Oil | Asset Impact | 2024 full-year forecast as at September 2024 | | **$\text{CO}_2$ emission factors Scope 1 and 2** | Oil | Estimates derived from OPGEE and PRELIM models | 2020 | | Gas | Asset Impact | 2024 full-year forecast as at September 2024 | | | Gas | Estimates derived from NETL lifecycle assessment analysis | 2014 | | Coal | Asset Impact | 2024 full-year forecast as at September 2024 | | | Coal | EPA | 2018 | | NGLs | Asset Impact | 2024 full-year forecast as at September 2024 | | | NGLs | Estimates derived from NETL lifecycle assessment analysis | 2014 | | | | | | **Methane emission factors Scope 1 and 2** | Oil | Estimates derived from OPGEE and PRELIM models | 2020 | | | | | | | Gas | IEA Methane Tracker | 2023 | | | | | | | Coal | Global Energy Monitor | 2021 | | | | | | | NGLs | IEA Methane Tracker | 2023 | | | | | --- ### Figure 11: Key choices to calculate the absolute metric | Key choice | Description | |---|---| | **Sector boundary** | Upstream Energy (producers of coal, oil, gas and NGLs) | | **Emissions scope** | Emissions generated from the extraction, refining and combustion of fossil fuels extracted by a producing company | | **GHGs measured** | Relate to $\text{CO}_2\text{e}$ Scope 1, 2 and 3 emissions for fossil fuel producers. $\text{CO}_2$ and methane | | **Scope 1 and 2 estimation** | Derived from OPGEE and PRELIM lifecycle assessment models for oil; NETL lifecycle assessment analysis and IEA Methane Tracker for gas and NGLS; EPA for energy content and $\text{CO}_2$ estimates; and Global Energy Monitor for methane as described in Figure 7. Checked against company disclosure, for material cases, if available | | **Scope 3 estimation** | Derived from asset-level fossil fuel extraction (tonnes of fuel), energy content of each fuel type (MJ per tonne) and global carbon emission factors for oil and gas ($\text{CO}_2$ per MJ). Derived as a weighted average of NGL mix using combustion and intensity factors from the EIA. Derived from EPA for coal as per Figure 7. Checked against company disclosure for material cases, if available. | | **Barclays' financing and attribution** | Financing provided or arranged. The share of financing as a percentage of a company's total debt and equity which is attributed to Barclays | | **Treatment of missing production data** | For the portion of the portfolio for which production data is not available, absolute emissions are estimated based on the average of our portfolio | | **Benchmark scenario** | IEA SDS (for 2025 target). IEA NZE2050 (for 2030 target) | | **Target baseline year** | 2020 | --- # Our approach by sector – Power The Power sector comprises the generation, distribution and sale of electric power to the general public and industry. This sector generates most of its emissions through the combustion of fossil fuels for power generation, though the construction of associated infrastructure also generates emissions in this sector. In order to decarbonise, the sector needs to phase out the use of fossil fuel power in favour of renewable energy sources, or fit fossil fuel plants with carbon capture technologies. ### 1.A. What metrics are used as benchmarks for the Power sector and why? 1.A.1 For power generation we consider emissions intensity to be the primary emissions metric, given that a reduction in the carbon intensity of electricity - via a switch to renewable or nuclear sources - is the key driver of decarbonisation pathways for the sector. 1.A.2 Emissions intensity metrics provide a view of the decarbonisation progress made by a company or sector over time. When transitioning, companies will need to invest in more sustainable activities, which would be captured using an intensity metric but not necessarily an absolute metric. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 When we released the first edition of this Whitepaper, the best available scenario to develop Paris-aligned benchmarks for our financing portfolios was the SDS. 1.B.2 As a result, power generation was benchmarked against the SDS electricity generation pathway for the OECD as the most appropriate benchmark, given that it is mostly a regionalised activity. 1.B.3 We also benchmark Power against the NZE2050 World scenario, which requires a c.69% reduction in $\text{CO}_2$ intensity at a World level by 2030 - representing the higher reduction in emissions in our target range. The IEA does not publish further geographic granularity in order to set a benchmark at an OECD level, however we would expect the OECD would require a faster rate of decarbonisation than the global average. 1.B.4 The intensity in both cases is derived by dividing electricity total emissions by electricity generation. ### 2.A. What scope of emissions are included, and why? 2.A.1 For the Power sector we attribute to each company the emissions resulting from the combustion of fossil fuels to produce electricity (Scope 1). In the case of renewable and nuclear power, as no combustion is required, the emissions are zero. 2.A.2 This methodology does not consider the Scope 2 emissions of the sector, given their marginality in the context of electricity generation. 2.A.3 Scope 3 emissions for the Power and Utilities sectors generally comprise the i) upstream emissions from fossil fuel extraction; ii) the purchase of power from upstream generation companies; and iii) the downstream combustion of natural gas transported to final consumers - for example for residential or commercial heating. Scope 3 emissions are excluded with the only exception being certain US government-owned utilities, where we include electricity purchased from government entitlements via Power Purchase Agreements. 2.A.4 We continue to measure only the emissions associated from combustion. However, there is one exception to this, where we assign zero emissions to biomass. 2.A.5 Biomass can take many forms, including waste products but also wood pellets. The burning of wood in particular is a carbon-intensive process which emits around one-and-a-half times the emissions for every unit of electricity generated, when compared to coal. However, the Greenhouse Gas (GHG) Protocol requires direct emissions from burning biomass to be excluded from their scope 1 reporting and reported separately. 2.A.6 For fossil fuel plants, the majority of lifetime emissions come from the use (combustion) phase. Our internal analysis suggests that $\text{CO}_2$ comprises more than 99% of GHG emissions from the combustion of oil, gas and coal. Other GHGs are more prevalent in the wider process of hydroelectricity and the use of biomass - but, as we describe below, these are currently not measured. 2.A.7 For renewable power, the majority of emissions arise from the construction of plants and the associated material production - notably concrete and steel. Emissions from solar photovoltaics mainly come from material extraction and the manufacturing process. At this stage, we do not have appropriate data or benchmark to capture manufacturing-related emissions. 2.A.8 As we only measure emissions from combustion processes, we ignore any biogenic emissions from hydroelectric facilities caused by the flooding of land during dam construction and the degradation of biomass in newly created reservoirs. There are various studies providing approximations that vary significantly depending on the geospatial features of the dam - however, the estimates are significantly lower than the intensity factors of fossil fuels. 2.A.9 Other upstream emissions, notably from the purchase of electricity by transmission and distribution companies, continue to be included as a Scope 1 emission where we lend directly to the power generator itself. 2.A.10 Downstream Scope 3 emissions from the supply of natural gas continue to be accounted for in the Scope 1 emissions of end users. ### 2.B. What data is used for these calculations? 2.B.1 We model emissions using emission factors and asset utilisation rates. 2.B.2 The electricity capacity data used is obtained from Asset Impact. 2.B.3 As electricity production capacity is typically not fully utilised, we estimate the actual production by applying a utilisation factor derived from IEA data for each fuel type and region. The estimated production is converted into Scope 1 emissions using IEA estimates of the carbon content of each fuel type. Figures 12 and 13 show the capacity and intensity factors derived from the 2023 IEA World Energy Outlook at a World and OECD level respectively, as of 2023. 2.B.4 We recognise this approach makes use of simplifying assumptions, and that both emission factors and utilisation rates will vary from the IEA averages used on a company-by-company basis. 2.B.5 For example, certain countries in which Barclays' clients operate have regulations in place to limit the use of coal-fired power generation where lower-carbon assets (renewable, gas) are installed. Renewable power asset utilisation is naturally limited by local weather - requirements for wind or sun, for example - which vary by geography. Emission factors may vary due to asset efficiency, as two different coal-fired power plants may generate different amounts of electricity per tonne of fuel combusted. 2.B.6 Furthermore, at each historic reporting date, these emissions factors and utilisation rates were only available with a one-year lag. For example, the rates used for the 2020 reporting period were taken from the 2019 IEA WEO report and those used for the latest reporting period reflect the most recent (2024) update. ### 3.A. What financing activities are considered in scope, and why? 3.A.1 All financing activities as explained on page 6 are in scope. 3.A.2 Loan facilities or capital market transactions are assumed to have a zero intensity if the proceeds are used for renewable power - such as electricity generation under SFF$^1$ - and are classified as 'green' dedicated purpose financing under the SFF. The 33% allocation for 'green' capital markets activity is equal to that of other capital markets activity. ### 3.A.3 All the relevant proceeds as per the terms of the arrangement are assumed to be for power generation. For example, if we provide £100 of dedicated financing for a company to generate renewable power, the entire £100 of financing would be assigned a zero intensity and included in the emissions intensity metric, regardless of how much revenue the company generates from power generation. 3.A.4 We acknowledge this approach could lead to some double-counting in the benefit from renewable production, as the company's overall emissions intensity may already account for the specific renewable generation financed via these green products. This may become more material over time. We also acknowledge that, at any point in time, the company may not have allocated all of the proceeds of the issuance. ### 3.B. How is provided financing linked to company-level emissions metrics? 3.B.1 If financing is provided to a Power company, we apportion financing across its businesses according to the division of that company's revenue (as per S&P Trucost, subject to fall-back provisions). This means that, if Barclays has arranged a £100m bond and provided a £50m RCF to a company that derives only 10% of its revenue from power generation, only £15m in financing will be included in the Power portfolio intensity calculations (before applying a 33% weighting). This is particularly important where we have exposure to large companies with relatively small Power businesses. 3.B.2 Where granular revenue data is not available, a standard matrix based on the sector classification of the producer (Barclays Industry Classification or 'BIC' code) will be used, as shown in Figure 14. ### 4.A. How are client-level measurements aggregated for the Power portfolio? 4.A.1 Emissions intensity is calculated as a function of each company's emissions and energy produced. The portfolio metric is then calculated as an average weighted value using the proportion of total portfolio financing. Figure 15 contains a full list of data sources used for each calculation component. ```mermaid graph TD subgraph Portfolio Metric Calculation A1(Σ Company) -- Company emissions --> A2{Company emissions / Production} A2 -- x --> A3(Barclays financing) A4(Σ Company) -- Barclays financing --> A5{Production} A5 -- x --> A6(Emission factor) A6 -- x --> A7(Capacity factor) end ``` ### Figure 12: Derived capacity factors from the IEA for power generation$^2$ | Technology | Annual electricity generation (TWh) | Generation capacity (GW) | Capacity factor | |---|---|---|---| | Coal | 10,648 | 2,243 | 54% | | Oil | 753 | 414 | 21% | | Natural Gas | 6,540 | 2,007 | 37% | | Nuclear | 2,765 | 416 | 76% | | Hydro | 4,249 | 1,411 | 34% | | Bioenergy | 714 | 188 | 43% | | Solar | 1,630 | 1,617 | 12% | | Wind | 2,336 | 1,015 | 26% | ### Figure 13: Derived emissions factors from the IEA for Power$^2$ | Technology | Annual emissions (Mt$\text{CO}_2$) | Annual electricity generation (TWh) | Emissions factor ($\text{kgCO}_2$/MWh) | |---|---|---|---| | Coal | 1,868 | 1,914 | 976 | | Oil | 125 | 157 | 798 | | Natural Gas | 1,380 | 3,363 | 410 | --- **Notes:** 1. Version 4.1 Sustainable Finance Framework. 2. www.iea.org/reports/world-energy-outlook-2024 --- ### Figure 14: Standard revenue adjustment matrix | Sector | Sub-sector | Production primary | Production other | Revenue share primary | Revenue share other | |---|---|---|---|---|---| | Power | Generation | Power | — | 100% | 0% | | | | Power | N types | 75% | 25%/N | | | | — | N types | 0% | 25%/N | | | Distribution | Power | — | 25% | 0% | | | | Power | N types | 25% | 25%/N | | | | — | N types | 0% | 25%/N | ### Figure 16: Key choices to calculate the intensity metric | Key choice | Description | |---|---| | **Sector boundary** | Power generators | | **Intensity type** | Physical intensity ($\text{CO}_2\text{e}$ emissions per unit of electricity generated), expressed in $\text{kgCO}_2\text{e}/\text{MWh}$ | | **Emissions scope** | Emissions generated from the combustion of fossil fuels for heat and electricity by a power generation and utility company | | **GHGs measured** | Relate to $\text{CO}_2\text{e}$ Scope 1 emissions for fossil fuel producers. $\text{CO}_2$ | | **Scope 1 emissions estimation** | Derived from asset-level capacity, capacity utilisation per fuel type and emission factors checked against company disclosure, for material cases, if available | | **Production estimation** | Total electricity generated derived from asset-level capacity and utilisation per fuel type | | **Barclays financing and attribution** | Financing provided or arranged. The share of a company's financing that relates to electricity generation is used (the rest is excluded). This is estimated using the share of revenue the client derives from those activities | | **Treatment of missing production data** | N/A | | **Benchmark scenario** | IEA SDS (for 2025 target). IEA NZE2050 (for 2030 target) | | **Target baseline year** | 2020 | ### Figure 15: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---| | **Barclays financing** | Lending | Internal | December 2024 | | | Capital Markets | Dealogic | December 2024 | | | Green Financing | Internal | December 2024 | | | Revenue Share | S&P Trucost | December 2024 | | **$\text{CO}_2$ emission factors Scope 1** | All generation | IEA | 2024 estimate from 2024 WEO Report | | **Capacity factors** | All generation | IEA | 2024 estimate from 2024 WEO Report | | **Production Capacity** | All generation | Asset Impact | 2024 full-year forecast as at September 2024 | --- # Our approach by sector – Cement Cement generates emissions primarily from both an unavoidable chemical reaction called calcination and from the burning of fossil fuels to generate the high heat required to make cement. The options proposed to abate its emissions include reducing the use of clinker, implementing carbon capture technology, using renewable forms of electricity, and fuel-switching to use biomass wastes or green hydrogen. ### 1.A. What metrics are used as benchmarks for the Cement sector and why? 1.A.1 Our model uses an emissions intensity metric to measure the performance of our Cement portfolio. 1.A.2 We have selected an emissions intensity metric because a reduction in the carbon intensity from manufacturing processes, through an increase in efficiency and investment in technology, is the key lever of decarbonisation for this sector, rather than a reduction in the products' use. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 The emissions benchmark for our Cement portfolio is taken from the IEA's NZE2050 World scenario, combined with forecasted production volumes. The higher end of the 2030 target range is also taken from the NZE2050 World scenario. Regional granularity is not available in this scenario. In addition, cement is an essential building block of economic and infrastructure development, and IEA pathways do not predict a rapid reduction in its use. 1.B.2 Cement is a hard-to-abate sector because most of the emissions generated are process emissions that cannot be avoided if cement production is to continue - direct emissions occur through a chemical process of calcination. The manufacturing process also generates emissions from the burning of fossil fuels to produce clinker, with production highly energy-intensive and tending to rely heavily on coal. 1.B.3 To achieve a net zero pathway by 2050, reduction levers can be split into two time periods: * From present day until 2030, there are near-term levers for reducing sector emissions from cement. However, these result in small reductions - for example, clinker substitution by reducing the clinker-to-cement ratio. * From 2030 to 2050, the levers are driven by investment and implementation of technology currently under development and likely to lead to substantial emissions reduction. For example, carbon capture, utilisation and storage (CCUS) technology will play an important role in reducing emissions from various industries, especially in the Cement sector - but scalability is currently a key challenge. 1.B.4 The IEA only produces granular forecasts for direct emissions associated with the manufacturing of cement - and does not provide forecasts for the electricity generated for this purpose, either on-site or through the grid. Previously, the NZE2050 scenario did not provide production forecasts and, as a result, we had to make some assumptions to infer an intensity metric that aligned to the reporting boundary$^1$. ### 2.A. What scope of emissions are included, and why? 2.A.1 For the Cement sector, a fixed boundary system for the manufacturing sector is used. We measure all emissions from an integrated cement plant - typically Scope 1 and 2 emissions - including thermal combustion for the production of clinker, electricity generation for the kiln, and the grinding and blending of materials. 2.A.2 We chose this boundary because a significant proportion of the emissions for these sectors are produced during the manufacturing process. 2.A.3 This methodology does not include emissions from the extraction and crushing of limestone and other raw materials used in the production or transportation of cement products, which are typically classed as Scope 3 due to low materiality and to align with the scenario benchmark. This includes the emissions associated with the production of clinker alternatives, such as fly ash. 2.A.4 We aim to measure all GHGs, however $\text{CO}_2$ is the most material gas by far for the sector. 2.A.5 For the avoidance of doubt, we measure the gross emissions of cement production. This includes emissions from the burning of waste products used as part of the calcination process. ### 2.B. What data is used for these calculations? 2.B.1 Given the small number of clients we have in the Cement sector, and that most of them disclose emissions and production data, we use company-reported data to calculate emissions intensity. 2.B.2 In certain situations, where company emissions data does not align to the reporting boundary, we may apply adjustments using expert judgement. No adjustments have been made on this basis to date. ### 3.A. What financing activities are considered in scope, and why? 3.A.1 All financing activities as explained on page 6 are in scope. 3.A.2 Green financing for activities in the Cement sector does not have a differentiated treatment for the purposes of financed emissions. ### 3.B. How is provided financing linked to company-level emissions metrics? 3.B.1 Once company-level emissions metrics are calculated they need to be linked to the financing we provide. We approach this in the same way as the Power metric, as described on page 23. 3.B.2 A fall-back table is used where revenue share data is not available, as shown in Figure 17. ### 4.A. How are client-level measurements aggregated for the Cement portfolio? 4.A.1 Emissions intensity is calculated as a function of each company's emissions and tonnes of cement produced. The portfolio metric is then calculated as an average weighted value using the proportion of total portfolio financing. Figure 18 contains a full list of data sources used for each calculation component. ```mermaid graph TD subgraph Portfolio Metric Calculation A1(Σ Company) -- Company emissions --> A2{Company emissions / Production} A2 -- x --> A3(Barclays financing) A4(Σ Company) -- Barclays financing --> A5{Company emissions} end ``` ### Figure 17: Standard revenue adjustment matrix | Sector | Sub-sector | Production primary | Production other | Revenue share primary | Revenue share other | |---|---|---|---|---|---| | Cement | Cement | Cement | — | 100% | 0% | | | | Cement | N types | 75% | 25%/N | | | | — | N types | 0% | 25%/N | ### Figure 18: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---| | **Barclays financing** | Lending | Internal | December 2024 | | | Capital Markets | Dealogic | December 2024 | | | Revenue Share | S&P Trucost | December 2024 | | **$\text{CO}_2$ emission factors Scope 1 and 2** | N/A | Company reports | Latest available | | **Production** | N/A | Company reports | Latest available | ### Figure 19: Key choices to calculate the intensity metric | Key choice | Description | |---|---| | **Sector boundary** | Cement manufacturers | | **Intensity type** | Physical intensity (gross $\text{CO}_2\text{e}$ emissions per tonne of cement produced), expressed in $\text{tCO}_2\text{e}/\text{t}$ cementitious material | | **Emissions scope** | Emissions generated from the thermal combustion required for the production of clinker, electricity generation for the kiln, and the grinding and blending of materials | | **GHGs measured** | Relate to the $\text{CO}_2\text{e}$ Scope 1 and Scope 2 emissions, calculated on a gross basis. All GHGs as sourced from company reports | | **Scope 1 and 2 emissions estimation** | Derived from client-reported data, but adjusted where necessary to align within a fixed boundary | | **Production estimation** | Total cement manufactured from client-reported data | | **Barclays financing and attribution** | Financing provided or arranged. The share of a company's financing that relates to in-scope activities. This is estimated by using the share of revenue the client derives from those activities | | **Treatment of missing production data** | N/A | | **Benchmark scenario** | IEA NZE2050 | | **Target baseline year** | 2021 | --- **Note:** 1. The latest IEA WEO publication (2024) does include production data. --- # Our approach by sector – Steel Steel is an engineering and construction material used in buildings, industrial infrastructure, vehicles, equipment and consumer goods. The process of manufacturing steel is carbon-intensive, requiring the mixing of iron and carbon at very high temperatures – typically fuelled by coal. To decarbonise, the sector requires greater use of carbon capture and storage, increased use of electric arc furnaces (EAF) and renewable electricity, and greater use of recycled scrap steel. ### 1.A. What metrics are used as benchmarks for the Steel sector and why? 1.A.1 Our model uses an emissions intensity metric to measure the performance of our Steel portfolio. 1.A.2 We have selected an emissions intensity metric because a reduction in the carbon intensity from manufacturing processes, through an increase in efficiency and investment in technology, is the key driver of decarbonisation for this pathway, rather than a material reduction in the products' use. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 The emissions benchmark for our Steel portfolio is taken from the IEA's NZE2050 World scenario, combined with forecast production volumes. The higher end of the 2030 target range is also taken from the NZE2050 World scenario. Regional granularity is not available in this scenario. Steel is an important construction and building material and, as the need for buildings and infrastructure continues to grow globally, reducing steel-related emissions is crucial for future sustainability. 1.B.2 Steel can be produced via two main processes: using an integrated blast furnace/basic oxygen furnace (BOF); or using an EAF. Integrated producers create steel from iron ore and need coal as a reductant, and EAF producers use steel scrap or direct reduced iron (DRI) as their main raw material. 1.B.3 To reduce emissions, the Steel industry requires greater use of EAF technologies alongside increased use of scrap and DRI - although this requires the availability of renewable electricity and high-quality steel scrap. 1.B.4 The IEA only produces granular forecasts for the direct emissions associated with the manufacturing of steel, and does not provide forecasts for the electricity generated for this purpose either on-site or through the grid. Previously, the NZE2050 scenario did not provide production forecasts and, as a result, we had to make some assumptions to infer an intensity metric that aligned to the reporting boundary$^1$. 1.B.5 Steel producers could use biomass as an alternative fuel to reduce $\text{CO}_2\text{e}$ emissions - however, a key limiting factor is that biomass (such as dried sugar) is not readily available globally at the level required to reduce carbon emissions on a significant scale. ### 2.A. What scope of emissions are included, and why? 2.A.1 Most of the emissions generated in the manufacturing of steel come from iron making (from iron ore), steelmaking, and in the preparation of materials. Steel production, for example, uses coke and involves high temperature combustion - resulting in a large amount of emissions. 2.A.2 Steel production can be broken down into primary and secondary production, where the latter is considerably less energy-intensive - although the availability of scrap may not be sufficient to meet demand. 2.A.3 We use a fixed-boundary system for the Steel sector where we measure all emissions from the midstream operations of a steel plant's manufacturing activities, which are typically Scope 1 and 2 emissions. We attribute all emissions from a steel plant, including coal coking, iron ore sintering, hot metal production and crude steel production. 2.A.4 We chose this boundary because a significant proportion of the emissions for these sectors are produced during the manufacturing process. 2.A.5 This methodology does not calculate emissions from the rolling and casting of steel, emissions from raw material extract (iron ore or coke), or the steel product's lifecycle use - which are typically Scope 3 in many cases due to low materiality and to align with the scenario benchmark. 2.A.6 We aim to measure all GHGs, however $\text{CO}_2$ is the most material gas by far for the sector. ### 2.B. What data is used for these calculations? 2.B.1 Given the small number of clients we have in the Steel sector, and that most of them disclose emissions and production data, we use company-reported data to calculate emissions intensity. 2.B.2 In certain situations where company emissions data does not align to the reporting boundary, we may apply adjustments using expert judgement. One company has been adjusted on this basis to date. ### 3.A. What financing activities are considered in scope, and why? 3.A.1 All financing activities as explained on page 6 are in scope. 3.A.2 Green financing for activities in the Steel sector does not have a differentiated treatment for the purposes of financed emissions. ### 3.B. How is provided financing linked to company-level emissions metrics? 3.B.1 Once company-level emissions metrics are calculated, they need to be linked to the financing we provide. We approach this in the same way as the Power metric, as described on page 23. 3.B.2 A fall-back table is used where revenue share data is not available, as shown in Figure 20. ### 4.A. How are client-level measurements aggregated for the Steel portfolio? 4.A.1 Emissions intensity is calculated as a function of each company's emissions per tonne of steel produced. The portfolio metric is then calculated as an average weighted value using the proportion of total portfolio financing. Figure 21 contains a full list of data sources used for each calculation component. ```mermaid graph TD subgraph Portfolio Metric Calculation A1(Σ Company) -- Company emissions --> A2{Company emissions / Production} A2 -- x --> A3(Barclays financing) A4(Σ Company) -- Barclays financing --> A5{Company emissions} end ``` ### Figure 20: Standard revenue adjustment matrix | Sector | Sub-sector | Production primary | Production other | Revenue share primary | Revenue share other | |---|---|---|---|---|---| | Steel | Steel | K types | — | 100%/K | 0% | | | | K types | N types | 75%/K | 25%/N | | | | — | N types | 0% | 25%/N | ### Figure 21: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---| | **Barclays financing** | Lending | Internal | December 2024 | | | Capital Markets | Dealogic | December 2024 | | | Revenue Share | S&P Trucost | December 2024 | | **$\text{CO}_2\text{e}$ emission factors Scope 1 and 2** | N/A | Company reports | Latest available | | **Production** | N/A | Company reports | Latest available | ### Figure 22: Key choices to calculate the intensity metric | Key choice | Description | |---|---| | **Sector boundary** | Steel manufacturers | | **Intensity type** | Physical intensity ($\text{CO}_2\text{e}$ emissions per tonne of steel produced), expressed in $\text{tCO}_2\text{e}/\text{t}$ crude steel | | **Emissions scope** | Emissions generated from midstream operations of a steel production, notably coal coking, iron ore sintering, hot metal production and crude steel production | | **GHGs measured** | Relate to the $\text{CO}_2\text{e}$ Scope 1 and Scope 2 emissions. All GHGs as sourced from company reports | | **Scope 1 and 2 estimation** | Derived from client-reported data, but adjusted where necessary to align within a fixed boundary | | **Production estimation** | Total steel manufactured from client-reported data | | **Barclays financing and attribution** | Financing provided or arranged. The share of a company's financing that relates to in-scope activities. This is estimated using the share of revenue the client derives from those activities | | **Treatment of missing production data** | N/A | | **Benchmark scenario** | IEA NZE2050 | | **Target baseline year** | 2021 | --- **Note:** 1. The latest IEA WEO publication (2024) does include production data. --- # Our approach by sector – Automotive The automotive sector comprises the development, manufacture and distribution of vehicles used to transport individuals and goods. The majority of emissions are generated from the combustion of oil to power internal combustion engine vehicles (ICEV) – often referred to as tailpipe emissions – but the production processes required to manufacture vehicles can also be intensive. Well-to-tank (WTT) emissions can also be material and result from oil production processes or electricity used to power electric vehicles (EVs). Decarbonisation will require a shift to EVs and more renewable forms of electricity, lower use of carbon-intensive raw materials, and the promotion of more efficient options to travel – including greater use of public transport. ### 1.A. What metrics are used as benchmarks for the Automotive sector and why? 1.A.1 Our model uses an emissions intensity metric to measure the performance of our Automotive portfolio. 1.A.2 Our chosen metric is $\text{CO}_2\text{e}/\text{vkm}$ (emissions per vehicle kilometres) for new vehicles sold in a given year, rather than those currently on the road (and sold in previous years). This best represents what our clients can control. 1.A.3 We have selected an emissions intensity metric because decarbonisation is mainly driven by a significant increase in the use of EVs (powered by renewable energy), rather than a reduction in the number of cars on the road or kilometres driven. 1.A.4 Ideally, we would prefer to use emissions per passenger kilometres to account for a vehicle's use. However, there are data limitations on load factors that would need be used to convert vehicle kilometres into passenger kilometres, and how they vary over time in the NZE2050 scenario (assuming vehicle sharing will increase). 1.A.5 We include light duty vehicles (LDVs) only, which incorporates cars, vans and light trucks with a Gross Vehicle Weight Rating (GVWR) below 3.85 tonnes (8,500 lb). 1.A.6 The GVWR is the maximum permissible weight that can be carried safely when used on the road. The IEA classifies vehicles with a GVWR below 3.5 tonnes as LDVs, in line with the definition used across Europe and Asia, while the US EPA classifies LDVs as vehicles below 3.85 tonnes. 1.A.7 The scope excludes all heavy duty vehicles (HDV), including buses and lorries, given their usage differs from LDVs and that they follow a different and slower transition pathway. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 The emissions intensity benchmark is based on the IEA's NZE2050 World scenario. 1.B.2 Our assessment indicates that the intensity of new vehicles needs to reduce by c.64% from 2022-30 in this scenario. 1.B.3 Regional granularity is less relevant for this sector as the majority of automotive manufacturers produce and sell vehicles globally. 1.B.4 Currently, the IEA only produces granular pathways for tailpipe emissions associated with the stock of vehicles on the road - so we have to make adjustments to convert this to new cars sold in a given year, including assessing the rate of retired LDVs and the growth in sales of EVs and hybrid vehicles. 1.B.5 The NZE2050 scenario relies on two key levers to reduce the tailpipe emissions intensity of new vehicles: the shift to the electrification of LDVs; and improvements in the fuel efficiency of all powertrains. 1.B.6 It should be noted that, while an increase of EVs will lead to reduced tailpipe emissions in transportation, there are other potential environmental and social costs from the extraction of minerals and battery production. Some of these minerals are already in short supply today, so it will be important to increase recycling rates in the future. ### 2.A. What scope of emissions are included, and why? 2.A.1 Our reporting boundary is defined as Scope 1, 2 and 3 emissions from LDV manufacturers. 2.A.2 For Scope 1 and 2 emissions, all GHGs are included in the metric. For Scope 3 emissions, which in this sector refers to tailpipe emissions, we only measure $\text{CO}_2$, as this is the most material gas emitted as part of the combustion process. 2.A.3 We only include tailpipe emissions and exclude WTT emissions as these include factors outside a manufacturer's control – such as the emissions intensity of electricity and oil production - and because data is not available at the required granularity. 2.A.4 Our methodology assigns all downstream tailpipe emissions to the manufacturer, because they play a major role in the type of vehicles sold and are in control of their manufacturing processes. 2.A.5 We also include Scope 1 and 2 emissions from our clients' manufacturing operations, although they form an immaterial component when compared to tailpipe emissions. 2.A.6 We intend to monitor upstream Scope 3 emissions inherent in a car's supply chain - mainly from battery production and raw material manufacturing - however these are not included in the target as there is no recognised pathway for how these emissions should decline over time. We will measure them using the GREET (Greenhouse Gases, Regulated Emissions, and Energy Use) model. ### 2.B. What data is used for these calculations? 2.B.1 We use data from Worldwide Harmonised Light Vehicle Test Procedures (WLTP) sourced from Asset Impact to measure Scope 3 emissions. 2.B.2 We also source production volumes from Asset Impact, which in turn sources this data from Auto Forecast Solutions. 2.B.3 A WLTP laboratory test is used to measure fuel consumption and $\text{CO}_2$ emissions from passenger cars, as well as their pollutant emissions. This introduces more realistic testing conditions to better reflect the on-road performance of a car. 2.B.4 Based on 2018 data there is a gap of c. 14% between WLTP and real-world $\text{CO}_2$ emissions. However, this is a better approximation than previous test cycles where the difference could be as high as 40% or higher for hybrid vehicles. 2.B.5 The NZE2050 scenario adjusts for the gap between test cycle data and real-world emissions - however, we do not apply any adjustments to WLTP data as there is no data on the factor used by IEA. Additionally, a hybrid vehicle's fuel economy and emissions can also vary significantly depending on user behaviour and for corporate fleets versus private vehicles. In particular, behaviours can be influenced by purchase subsidies and tax cuts as opposed to environmental concerns. The availability of easy and fast-charging options could influence this even further. 2.B.6 For Scope 1 and 2 emissions, we use S&P Trucost emissions data, which is typically sourced directly from company reports. If companies do not report their emissions, we estimate their emissions using the GREET model. 2.B.7 We assume an average vehicle is driven for 150,000km across its entire lifetime. We are aware that this range can vary significantly, particularly for electric vehicles, however there is limited data available on this. Our primary metric is not sensitive to average vehicle lifetime kilometres as the materiality of Scope 1 and 2 emissions reduces significantly once converted (to emissions per vehicle kilometres) and compared with tailpipe emissions. 2.B.8 We are aware that companies operate across different parts of the value chain. In particular, reported data may not distinguish between emissions from battery production and assembly - and would therefore result in higher Scope 1 and 2 emissions for those that manufacture their own batteries or produce both HDVs and LDVs. However, a sensitivity analysis on our 2022 portfolio suggests a negligible impact from this limitation. 2.B.9 Companies that supply manufacturers with parts are excluded as their emissions profiles will not be comparable. ### 3.A. What financing activities are considered in scope, and why? 3.A.1 All financing activities as explained on page 6 are in scope. 3.A.2 We exclude direct financing to captive financing arms, sellers and distributors, as they act as a marketplace connecting buyers and sellers and have limited control on the design of vehicles being sold in the market. However, we include financing such as lending to financing arms other than captive, where facilities can be used for vehicle manufacturing process. 3.A.3 Loan facilities or capital market transactions are assumed to have a zero tailpipe intensity if the proceeds are used for the manufacturing of electric vehicles (manufacture of new vehicles which are zero-direct emissions or the development and infrastructure for electric vehicles under Barclays SFF) and are classified as 'green' dedicated purpose financing under the Barclays SFF. Each deal is reviewed on a case-by-case basis to validate if the financing is expected for LDV manufacturing. The 33% allocation for 'green' capital markets activity is equal to that of other capital markets activity. 3.A.4 Deals flagged as green will continue to be assigned company-specific Scope 1 and 2 intensities. ### 3.B. How is provided financing linked to company-level emissions metrics? 3.B.1 Once company-level emissions metrics are calculated, they need to be attributed to the financing we provide. We attribute 100% of our financing to auto manufacturing emissions for counterparties that are LDV manufacturers. We also attribute 100% of our financing to captive arms of auto manufacturing companies where use of proceeds can be directed towards auto manufacturing processes. 3.B.2 For counterparties that manufacture both LDVs and HDVs, we do not weight our financing according to the portion of revenue each company generates from LDVs only, A sensitivity analysis of our 2022 portfolio suggests the impact on the intensity metric is immaterial. 3.B.3 We exclude any financing made directly and solely for the use of financing captive entities, as this is used for selling rather than manufacturing vehicles. ### Figure 23: Lifetime emissions analysis #### Fig 23A: 2020 world grid average Emissions intensity ($\text{gCO}_2\text{e}/\text{km}$) - EV versus ICEV ```mermaid xychart-beta title "2020 World Grid Average Emissions Intensity (gCO2e/km) - EV versus ICEV" x-axis "Vehicle Type" [Small car 1 EV, Small car 2 EV, Small car 1 ICE, Small car 2 ICE, SUV EV, SUV ICE, Medium car EV, Medium car ICE, Light truck EV, Light truck ICE] y-axis "Emissions Intensity (gCO2e/km)" 0 --> 350 bar [78, 71, 110, 95, 68, 109, 74, 124, 84, 89] bar [23, 23, 26, 26, 42, 45, 51, 63, 197, 211] legend ["WTT", "Tailpipe", "Production"] ``` *Note: WTT, Tailpipe, Production data points for each vehicle type are stacked for visualization.* #### Fig 23B: 2030 world grid average Emissions intensity ($\text{gCO}_2\text{e}/\text{km}$) - EV versus ICEV ```mermaid xychart-beta title "2030 World Grid Average Emissions Intensity (gCO2e/km) - EV versus ICEV" x-axis "Vehicle Type" [Small car 1 EV, Small car 2 EV, Small car 1 ICE, Small car 2 ICE, SUV EV, SUV ICE, Medium car EV, Medium car ICE, Light truck EV, Light truck ICE] y-axis "Emissions Intensity (gCO2e/km)" 0 --> 350 bar [33, 29, 110, 95, 68, 109, 74, 124, 84, 89] bar [21, 21, 26, 26, 42, 45, 51, 63, 197, 211] legend ["WTT", "Tailpipe", "Production"] ``` *Note: WTT, Tailpipe, Production data points for each vehicle type are stacked for visualization.* #### Fig 23C: 2020 Europe grid average Emissions intensity ($\text{gCO}_2\text{e}/\text{km}$) - EV versus ICEV ```mermaid xychart-beta title "2020 Europe Grid Average Emissions Intensity (gCO2e/km) - EV versus ICEV" x-axis "Vehicle Type" [Small car 1 EV, Small car 2 EV, Small car 1 ICE, Small car 2 ICE, SUV EV, SUV ICE, Medium car EV, Medium car ICE, Light truck EV, Light truck ICE] y-axis "Emissions Intensity (gCO2e/km)" 0 --> 350 bar [37, 33, 110, 95, 68, 109, 74, 124, 84, 89] bar [23, 23, 26, 26, 42, 45, 51, 63, 197, 211] legend ["WTT", "Tailpipe", "Production"] ``` *Note: WTT, Tailpipe, Production data points for each vehicle type are stacked for visualization.* #### Fig 23D: 2020 India grid average Emissions intensity ($\text{gCO}_2\text{e}/\text{km}$) - EV versus ICEV ```mermaid xychart-beta title "2020 India Grid Average Emissions Intensity (gCO2e/km) - EV versus ICEV" x-axis "Vehicle Type" [Small car 1 EV, Small car 2 EV, Small car 1 ICE, Small car 2 ICE, SUV EV, SUV ICE, Medium car EV, Medium car ICE, Light truck EV, Light truck ICE] y-axis "Emissions Intensity (gCO2e/km)" 0 --> 350 bar [51, 45, 110, 95, 68, 109, 74, 124, 84, 89] bar [33, 33, 26, 26, 42, 45, 51, 63, 197, 211] legend ["WTT", "Tailpipe", "Production"] ``` *Note: WTT, Tailpipe, Production data points for each vehicle type are stacked for visualization.* Our findings showed that: * EVs are typically less carbon-intensive than ICEVs, even after accounting for WTT emissions * The size of the vehicle is important, and a large EV can be more intensive than a small ICE driven in certain locations * Decarbonisation of electricity will be required to fulfill the potential of EVs. *Note: This is not a full projection as it only considers the impact of changes in the grid intensity on the WTT emissions of electric vehicles. We have not considered the impact on manufacturing emissions or the impact of improvement in ICEV efficiency.* ### 4.A. How are client-level measurements aggregated for the Automotive portfolio? 4.A.1 Emission intensity is calculated as a function of each company's emissions per vehicle km travelled by LDVs produced. The portfolio metric is then calculated as an average weighted value using the proportion of total portfolio financing. Figure 24 contains a full list of data sources used for each calculation component. ```mermaid graph TD subgraph Portfolio Metric Calculation A1(Σ Company) -- Company emissions --> A2{Company emissions / Production} A2 -- x --> A3(Barclays financing) A4(Σ Company) -- Barclays financing --> A5{Company emissions} end ``` ### Figure 24: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---| | **Barclays financing** | Lending | Internal | December 2024 | | | Capital Markets | Dealogic | December 2024 | | | Green Financing | Internal | December 2024 | | | Revenue Share | S&P Trucost | December 2024 | | **$\text{CO}_2\text{e}$ emission factors Scope 1 and 2** | N/A | Derived from company-reported emissions, sourced from S&P Trucost | December 2024 | | **$\text{CO}_2\text{e}$ emission factors Scope 3** | N/A | Asset Impact | 2024 full-year forecast as at September 2024 | | **Production** | N/A | Asset Impact | 2024 full-year forecast as at September 2024 | ### Figure 25: Key choices to calculate the intensity metric | Key choice | Description | |---|---| | **Sector boundary** | LDV manufacturers | | **Intensity type** | Physical intensity ($\text{CO}_2\text{e}$ emissions per vehicle kilometre travelled by LDV produced), expressed in $\text{gCO}_2\text{e}/\text{vkm}$ | | **Emissions scope** | Emissions generated from the manufacturing and lifetime tailpipe emissions of new vehicles | | **Greenhouse gases measured** | Relate to the $\text{CO}_2\text{e}$ Scope 1, 2 and 3 emissions for automotive manufacturers. All GHGs for Scope 1 and 2, $\text{CO}_2$ for Scope 3 | | **Scope 1 and 2 estimation** | Derived from client-reported data | | **Scope 3 estimation** | Downstream emissions are derived from WLTP test cycle data and sourced from Asset Impact | | **Production weighting** | Total LDVs manufactured, sourced from Asset Impact | | **Barclays financing and attribution** | Financing provided or arranged | | **Treatment of missing production data** | N/A | | **Benchmark scenario** | IEA NZE2050 | | **Target baseline year** | 2022 | --- # Our approach by sector – UK Housing The UK Housing sector comprises the use and construction of properties for residential purposes. The emissions attributed to this sector are the embodied emissions from the materials used in the construction phase, and operational emissions from the use and maintenance of the properties – primarily from water and space heating and power usage. Reducing emissions for this sector will require the use of less-carbon-intensive materials, retrofitting existing properties to increase their energy efficiency, facilitating the installation of non-fossil-fuel heating systems such as heat pumps, greening of the electricity grid, and changes made by individual homeowners to reduce energy consumption. ### 1.A. What metrics are used as benchmarks for the UK Housing sector and why? 1.A.1 Our model uses an emissions intensity metric to measure the performance of our UK Housing portfolio, following the methodology outlined in the PCAF Standard. The physical intensity is a measurement of financed emissions per square metre of floor area. 1.A.2 Given demand for new housing in the UK is expected to grow in the coming decades, and additional financing to help houses become more energy efficient will be required, we believe setting an absolute emissions target would not be appropriate. 1.A.3 An alternative option could be to use financed emissions per occupancy rate, however there is limited data to support this calculation and it would be overly complex. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 We have used the BNZ scenario published by the CCC in 2020 and modified it to consider both Scope 1 and Scope 2 emissions for residential properties. This 'synthetic' pathway is used to benchmark our UK Housing portfolio. 1.B.2 The CCC is an independent UK Government body and sets out a roadmap for decarbonising the UK economy by 2050. This scenario is more relevant for our UK collateral base than the regional and global pathways from the IEA, and relies on government policies - including electricity grid decarbonisation, the roll-out of heat pumps, and regulations enforcing minimum Energy Performance Certificate (EPC) ratings. 1.B.3 The BNZ scenario includes pathways for water and space heating emissions, and emissions relating to the supply of electricity. 1.B.4 We have combined these pathways to arrive at an overall benchmark while also using the latest grid emission factors published by the Department for Energy Security and Net Zero (DESNZ)$^1$ for 2024 (based on 2022 actuals). The floor area of new builds is assumed to remain constant out to 2050, given there has been limited variance in yearly averages observed over the past decade. 1.B.5 Using these assumptions we estimate that the physical intensity of UK Housing will need to reduce to $19.3 \text{kg } \text{CO}_2\text{e}/\text{m}^2$ by 2030, down from $31.8 \text{kg } \text{CO}_2\text{e}/\text{m}^2$ as of December 2024. ### 2.A. What scope of emissions are included, and why? 2.A.1 We measure operational emissions from water and space heating, and indirect emissions from the use of electricity. This translates to the Scope 1 and 2 emissions for a homeowner, although the Greenhouse Gas Protocol only applies to companies and not individual homeowners. 2.A.2 Operational carbon emissions are generated by fuel consumption for heating and cooling, and the supply of fresh water, ventilation and power over a building's lifetime. 2.A.3 We recognise that a large proportion of lifecycle emissions from UK Housing come via the construction phase (embodied carbon). Our initial analysis of embodied carbon suggested it was responsible for more than 50% of lifecycle emissions of a property - however, as available data and published reporting standards currently only cover estimations of operational emissions, we have not included embodied carbon, although we may do in the future. 2.A.4 Furthermore, it is estimated that c.80% of residential buildings present in 2050 already exist - and hence reducing the operational emissions of existing stock will be key. 2.A.5 We also acknowledge that we could instead focus on decarbonising the suppliers of gas, rather than targeting homeowners, as they also have an important role in the decarbonisation of heating. 2.A.6 Our preliminary analysis suggested that our absolute emissions related to our financing of the UK's key gas suppliers are broadly similar to our absolute emissions for UK Housing. 2.A.7 Bio methane can be used as an alternative to traditional gas but currently supplies less than 1% of the UK market - and suppliers publish very limited information on its supply. Furthermore, while low-carbon hydrogen may become a more readily available source for heating homes in the future, it is not a viable source of energy today and there are some public reports that have questioned its use. We will continue to monitor developments here. 2.A.8 The GHGs included in our estimate mainly comprise $\text{CO}_2$ but also include methane and nitrous oxide from fossil fuel combustion - either directly in boilers or indirectly in power plants. Fluorinated gases are currently not captured, due to both lack of information and the need for consistency with the scope of the selected benchmark. ### 2.B. What data is used for these calculations? 2.B.1 We use data from the latest EPC certificates for properties where they are available$^1$ including energy efficiency rating, fuel source and floor area. This is sourced via Hometrack and our internal team that specializes in address matching - who source EPCs from government registries$^2$. 2.B.2 We are aware of the limitations of using EPCs as a source of data for emissions measurements, including: i) incomplete coverage; ii) outdated certificates; iii) mapping issues; and iv) that they do not reflect actual energy consumption. As a result we use average metered consumption as our primary source and supplement it with EPC band (and floor area). We then make further adjustments based on location and heating type (from EPC). 2.B.3 EPC certificates are used as a common basis for assessing expected energy costs across Europe, but do not give a precise picture of emissions intensity. For example, they assume electricity is sourced from the UK's grid as of 2012, at which time coal and gas was far more prevalent in the energy mix. They also exclude the energy used to power appliances and do not take into account the behaviour of the occupants. 2.B.4 In our studies we observed a significant difference between estimated and observed energy consumption across all EPC bands, particularly those at either end of the spectrum. 2.B.5 Furthermore, according to the UK GHG Emissions Report from DESNZ$^3$, emissions from the residential sector decreased by 16% between 2021 and 2022, which according to the DESNZ report were likely related to higher domestic energy prices and warmer weather, leading to lower energy consumed for heating purposes. Our methodology does not yet take into account these behavioural aspects. We aim to monitor developments in this area and will make enhancements as relevant. 2.B.6 Figure 26 shows a stylised illustration of how we convert emissions estimates from EPC certificates for use in our methodology. 2.B.7 Where a property does not have an EPC certificate (c.30% of our portfolio), we estimate emissions using a derived intensity fall-back table based on the construction age of the property, the building type and the region. This estimate is based on actual meter consumption data and sector-level statistics from DESNZ (formerly BEIS). Where we have no information on the property location or building type, we use a UK average intensity based on EPC, National Energy Efficiency Data-Framework (NEED) and Energy Consumption in the UK (ECUK) databases as shown in Figure 27. 2.B.7 We report a DQ score in line with the PCAF Standard. Where we estimate emissions using an EPC certificate, we assign a DQ score of 3. Where we utilise the fall-back approach, we typically assign a DQ score of 5. A higher score will likely require access to individual household energy consumption data not yet available. ### Figure 26: Visual representation showing a reconciliation between EPC emissions and BlueTrack™ emissions ```mermaid graph LR A[Raw emissions estimate from EPC certificates] --> B[Incorporate electricity grid decarbonisation] B --> C[Inclusion of appliances] C --> D[Normalisation to mean actual consumption] D --> E[Barclays emissions metric] ``` ### Figure 27: Methodology to estimate building emissions ```mermaid graph TD subgraph Portfolio P1[Floor area EPC (m²)] P2[EPC available] P3[EPC not available] end subgraph EPC available path P2 --> P2A[Energy Intensity Lookup EPC] P2A --> P2A1[EER | Fuel | Building type | Region] P2A1 --> P2B[Energy consumption (kWh/m² fuel)] P2A1 --> P2C[Building emissions (kgCO2e)] P2B --> P2C P2C --> PM[Portfolio metrics] end subgraph EPC not available path P3 --> P3A[Energy Intensity Lookup - Fall-back] P3A --> P3A1[Building type | Region | Age band] P3A --> P3A2[Floor area fall-back (m²)] P3A2 --> P3B[Energy consumption (kWh/m² fuel)] P3A1 --> P3C[UK Government emission factors (kgCO2e/kWh/fuel)] P3C --> P2C P3B --> P2C end subgraph Common data/output P1 -.-> P2A P1 -.-> P3A2 P2A --> P2C P3A --> P2C P2C --> PM subgraph Intensity Calculation IC1[Physical intensity (kgCO2e/m²)] IC2[Economic intensity (kgCO2e/£)] end P2C --> IC1 P2C --> IC2 IC1 --> PM IC2 --> PM subgraph Financing Link FA[Financing amount] end FA --> IC2 end ``` *Note: While EPCs contain an estimate of emissions, we do not use these directly within the methodology. Instead, we use the energy consumption estimate as our starting point. The variance between the raw emissions estimate from the EPC certificate and the BlueTrack™ metric can be stylised as per the graph on the left. It incorporates three adjustments: i. Changes in the intensity of the grid and removal of upstream Scope 3 emissions (notably from the production of gas); ii. The inclusion of emissions from the use of appliances; and iii. a normalisation to actual consumption levels.* ### 3.A. What financing activities are considered in scope, and why? 3.A.1 In 2023, our methodology covered owner-occupied and buy-to-let lending in our UK Mortgages and Private Banking businesses. 3.A.2 We expanded the scope to include lending to our UK Social Housing and Business Banking businesses in 2024 which is now referred as the UK Housing sector. 3.A.3 In 2025, we now include our financing as part of Kensington mortgage portfolio which comprises of approximately £4bn in mortgages across both owner occupied and buy-to-let book. 3.A.4 Social Housing properties are completely residential in nature. Property lending in Business Banking is largely collateralised by residential assets, with a small proportion for commercial purposes. 3.A.5 Financing of properties outside of the UK is excluded - notably our Italy Mortgages portfolio, which is in run-off, and certain assets in our Private Banking portfolio in Continental Europe. We also exclude buy-to-let warehousing lines of credit to mortgage originators or Mortgage Backed Securities. 3.A.6 A loan is included as in scope from the time the exposure is on our book to the complete repayment of the loan, including in cases of refinancing with an alternative lender. 3.A.7 Green financing for activities in the UK Housing sector does not have a differentiated treatment for the purposes of financed emissions. ### 3.B. How is provided financing linked to loan-level emissions metrics? 3.B.1 When calculating the attribution factor of a loan's absolute emissions, we use the loan outstanding as a proportion of property value at origination, in line with the PCAF Standard. Where the property value at origination is not available, we use the latest property value and keep it constant from the latest period. In cases where there are some additional unsecured lending, such as BGIs$^4$ and overdrafts in Social Housing, the attribution factor is adjusted to add these to existing secured lending. ### 4.A. How are customer-level measurements aggregated for the UK Housing portfolio? 4.A.1 Emissions intensity is calculated as a function of each property's emissions and the floor area of the property. The portfolio metric is then calculated as an average weighted value using the proportion of total portfolio financing. Figure 28 contains a full list of data sources used for each calculation component. ```mermaid graph TD subgraph Intensity Calculation 1 (Emissions-based) A1(Σ Building) -- Outstanding amount --> A2{Property value at origination} A2 -- x --> A3[Building emissions] end subgraph Intensity Calculation 2 (Area-based) B1(Σ Building) -- Outstanding amount --> B2{Property value at origination} B2 -- x --> B3[Floor area] end ``` ### Figure 28: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---| | **Outstanding amount** | N/A | Internal | December 2024 | | **Property value at origination** | N/A | Internal | December 2022 | | | N/A | Internal - KMC | December 2024 | | **Building energy efficiency ratings and heating types** | N/A | EPC certificates DLUHC$^1$ sourced through Home Track and DCM | September 2024 | | **Floor area** | N/A | Internal, EPC certificates DLUHC sourced through Home Track and DCM | September 2024 | | **Emission Factors** | N/A | DESNZ | July 2024 | --- **Notes:** 1. Department for Levelling Up, Housing and Communities (DLUHC). 2. We use expired EPCs where available since they provide important information on property characteristics, even after they have expired. 3. www.gov.uk/government/publications/greenhouse-gas-reporting-conversion-factors-2024 4. Bonds, Guarantees and Indemnities. --- ### Figure 29: Key choices to calculate the intensity metric | Key choice | Description | |---|---| | **Sector boundary** | Buy-to-let and owner-occupied mortgages in the UK. These mortgages reside in Personal Banking within Barclays UK and our Private Banking division in Barclays International. Social Housing across Barclays UK and Barclays International. Business Banking exposures in Barclays UK | | **Intensity type** | Physical intensity ($\text{CO}_2\text{e}$ emissions per floor area), expressed in $\text{kgCO}_2\text{e}/\text{m}^2$ | | **Emissions scope** | Operational emissions that relate to the use of the property. Can be considered Scope 1 and 2 emissions from a homeowner's perspective | | **GHGs measured** | $\text{CO}_2$, methane and nitrous oxide | | **Emissions estimation** | Derived from EPC certificates and NEED average consumption information (estimate of energy consumption used where not available) and supplemented with appliance energy consumption | | **Production weighting** | Floor area as derived from EPC certificates or estimated using property attributes | | **Barclays financing and attribution** | All mortgage financing activities under Barclays UK (including Kensington mortgages), Wealth and Private Business. The portion of the mortgage for which Barclays finances is used, defined as the outstanding balance divided by the property value at origination (LTV). For Social Housing, all secured loans, unsecured loans and capital markets financing is included. In Business Banking lending to commercial landlords is considered but excludes lending to property companies set up in an opco/propco | | **Treatment of missing production data** | Where EPC certificates are not available, we use the intensity information developed at property type, property age and region level, and apply the UK Government emission factor. Where no information on the property location or building type is available, we apply the UK average intensity | | **Benchmark scenario** | BNZ scenario outlined by the CCC | | **Baseline year** | 2023 | --- # Our approach by sector – UK Commercial Real Estate The UK Commercial Real Estate (CRE) sector incorporates loans for the purpose of purchase and refinance of commercial real estate. These assets could be used for income-generating commercial and residential purposes – for example retail, office space, student accommodation, build-to-rent, and so on. Emissions come from the materials used in the construction phase (embodied) and from the use and maintenance of the properties (operational), primarily from water and space heating and power usage. Reducing emissions for this sector will require the use of less-carbon-intensive construction materials, retrofitting existing properties to increase their energy efficiency, facilitating the installation of non-fossil-fuel heating systems, more efficient heating, ventilation and cooling (HVAC) systems, greening the electricity grid, and lower energy consumption by occupants. ### 1.A. What metrics are used as benchmarks for the UK CRE sector and why? 1.A.1 Our model uses a physical intensity metric to measure the performance of our UK CRE portfolio, following the methodology outlined in the PCAF Standard. The physical intensity is a measurement of financed emissions per square metre of floor area. 1.A.2 We have chosen to align to the PCAF Standard as it has become the emerging standard for estimating real estate financed emissions. 1.A.3 We set a physical intensity target in line with the UK Housing sector. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 We have used the CRREM (V2.02) pathway to benchmark our UK CRE portfolio, which is the most widely accepted and recognised pathway for commercial properties. 1.B.2 CRREM$^1$ is the leading global standard and initiative for operational decarbonisation of real estate assets. We use the second version of CRREM, published in February 2023, which includes decarbonisation pathways for real estate, down-scaled to the country and property type level from the global IEA NZE 2050 scenario. 1.B.3 The down-scaling methodology follows the Sectoral Decarbonization Approach (SDA) by SBTi. 1.B.4 The UK CRE sector comprises an array of different property types and uses. Properties will have varying emissions profiles based on their use and type - an average residential property, for example, will have a lower emissions output than an average high street retail unit. 1.B.5 Due to this varying emissions profile, any change in the use of a property has wider implications. Substituting the property is often complex and involves planning and regulatory considerations. Repositioning of assets through either conversion or redevelopment leads to a change in the property mix of our portfolio - and the consequent emissions profile. To monitor our progress, the benchmark needs to be updated and reflective of the property mix of our portfolio. We intend to monitor the make-up of our portfolio over time and, should there be any large shifts, we may update our benchmark accordingly. ### 2.A. What scope of emissions are included, and why? 2.A.1 We measure operational emissions (Scope 1 and 2) from water and space heating, and indirect emissions from the use of electricity. 2.A.2 Operational carbon emissions are generated by fuel consumption for heating and cooling, and the supply of fresh water, ventilation and power over a building's lifetime. 2.A.3 We recognise that a large proportion of lifecycle emissions from UK CRE come via the construction phase (embodied carbon). However, as available data and published reporting standards only cover estimations of operational emissions, at this stage we have not included embodied carbon. 2.A.4 The GHGs included in our estimate are $\text{CO}_2$, methane and nitrous oxide from fossil fuel combustion, either directly in boilers or indirectly in power plants. Due to the lack of available data we have not considered fluorinated gases at this stage. ### 2.B. What data is used for these calculations? 2.B.1 Sourcing property-level information for this portfolio has a number of challenges due to incomplete data or matching issues. We found that: i) addresses captured in our system are not consistent with those in the EPC registry; ii) the address line misses some key information, such as building unit number; and iii) different property types were listed within the same postcode. 2.B.2 Some of these challenges were overcome by the use of a Unique Property Reference Number (UPRN) fuzzy matching techniques and specialised software to match domestic and non-domestic EPC certificates to the properties held in our book. Certificates are sourced directly from the UK Government website and matched in our data warehouse. 2.B.3 We use the data from the latest EPC certificates for properties where they are available$^2$. We are aware of the limitations of using EPCs as the primary source of data for emissions measurements, including: i) incomplete coverage; ii) outdated certificates; and iii) mapping issues across both domestic and non-domestic EPCs. Properties used for residential purposes (c.25% our portfolio) use the emissions methodology outlined in the UK Housing sector. 2.B.4 In the case of non-domestic EPCs (c.75% of our portfolio), the EPC rating is directly proportional to the building's emissions as calculated by the UK Government's EPC methodology. This is a more straightforward approach than for domestic EPCs, where the EPC rating is derived from the cost of energies for the building and therefore the link to emissions is more complicated. For each property type, baseline emissions intensity from CRREM is adjusted using the published 'Asset Rating' given in the certificate, further updated for the latest grid emission factor, to arrive at a consistent EPC-informed emission. 2.B.5 Where a property does not have a matched EPC certificate (c.69% of our portfolio), we estimate the emissions. For domestic properties, this is done using the same intensity look-up created for the UK Housing sector. A four-step approach is followed for non-domestic properties: i) we start with baseline emissions intensity from CRREM; ii) electricity emissions fraction (by property type) is determined from BEES data; so that iii) emissions from electricity can be updated using the latest grid emission factor; iv) the product of the average floor area and average intensity gives the overall $\text{CO}_2\text{e}$ for the property. 2.B.6 We are aware that EPC certificates do not consider all buildings emissions. Hence, we assess this using UK BEES$^1$ data for property type mentioned in step 'ii' above. Emissions due to activity - considered to come from electricity - and changes in the latest emission factors give us the most accurate emissions estimate. 2.B.7 Figure 30 shows a stylised illustration of our overall methodology, laying out how we estimate the portfolio metrics using internal property-level data, information from EPC certificates, CRREM and other relevant sources. 2.B.8 We also report a DQ score in line with the PCAF Standard. Where we estimate emissions using an EPC certificate, we assign a DQ score of 3. In cases where an EPC certificate is not available, but where the actual floor area is available (captured in our internal collateral data), a DQ score of 4 is assigned. Where we use the fall-back approach, we typically assign a DQ score of 5. A better score would require access to individual buildings' energy consumption data. ### 3.A. What financing activities are considered in scope, and why? 3.A.1 This sector includes all secured financing activities within our UK Corporate Bank real estate portfolio. 3.A.2 We provide financing to companies that typically use the proceeds for the purchase and refinancing of commercially let investment properties. For the completeness of this portfolio, we also considered any unsecured lending to these existing clients - typically in the form of revolving credit facilities. 3.A.3 We exclude commercial mortgages where we finance a company for its own operations. 3.A.4 We have not assessed our financed emissions for Real Estate Investment Trusts (REITs), where we typically lend on an unsecured basis, due to insufficient availability of asset-level data critical for this sector. We will continue to explore sources for this data, including assessing specialised vendors. 3.A.5 Due to the lack of a unified metric of emissions measurement like the EPC in the UK, and less regulatory focus impacting coverage, the information available was limited for some portfolios. These are also lower materiality compared to our UK book. Hence, we exclude structured lending finance in the US, exposures in non-UK geographies, and our Wealth and Private Banking portfolio. 3.A.6 A loan is included from the time the exposure is on our book until it is fully repaid. 3.A.7 Green financing for activities in the UK CRE sector does not have a differentiated treatment for the purposes of financed emissions. ### 3.B. How is provided financing linked to loan-level emissions metrics? 3.B.1 We use the attribution factor defined by the PCAF Standard. In the simplest case, this is the ratio of the financing - we use the limit, rather than the balance of the loan - to the latest property value, kept constant throughout the assessment period (as prescribed by PCAF). 3.B.2 There are often complex cases where 'many-to-many' relationships exist between loans, customers and properties. Here, the approach is generalised to properly attribute the financed emissions from the collateral. 3.B.3 These cases include: loans secured by several properties (exposure is distributed among the properties); properties securing several loans (attribution at an overarching level of loans); unknown valuation of properties securing a loan (using average attribution from customers' properties of known valuation); and unsecured exposures in the social housing and BB CRE where no collateral is posted (emissions estimate based on the entire portfolio of properties owned by a given counterparty). ### 4.A. How are customer-level measurements aggregated for the UK CRE portfolio? 4.A.1 Emissions intensity is calculated as a function of each property's emissions and the floor area of the property. The portfolio metric is then calculated as an average weighted value using the proportion of total portfolio financing. For this year, the majority of the property assessment utilises the latest property value (fixed for the duration of the benchmark) - however, as internal data improves, the origination valuation may be considered. Figure 31 contains a full list of data sources used for each calculation component. ```mermaid graph TD subgraph Intensity Calculation 1 (Emissions-based) A1(Σ Building) -- Outstanding amount --> A2{Property value at origination} A2 -- x --> A3[Building emissions] end subgraph Intensity Calculation 2 (Area-based) B1(Σ Building) -- Outstanding amount --> B2{Property value at origination} B2 -- x --> B3[Floor area] end ``` ### Figure 30: Methodology ```mermaid graph TD subgraph Portfolio P1[EPC available] P2[EPC not available] end subgraph EPC available path P1 --> P1A[Domestic EPC] P1 --> P1B[Non-domestic EPC] end subgraph EPC not available path P2 --> P2A[Property attributes available: property type, floor area] P2 --> P2B[Property attributes not available] end P1A --> P1A1[CRREM Baseline Emissions Intensity. BEES data and EPC data: Asset Rating | Fuel | Building type] P1B --> P1B1[CRREM Baseline Emissions Intensity. BEES data] P1A1 --> P1C[Emissions from electricity and other fuels] P1B1 --> P1C P1C --> P1C1[UK Govt. Emission Factors (kgCO2e/kWh/fuel)] P1A1 --> P1D[Physical intensity (kgCO2e/m²)] P1B1 --> P1D P2A --> P2C[CRREM Baseline Emissions Intensity. BEES data] P2A --> P2D[Property attributes available: property type, floor area] P2B --> P2E[Average 'known' portfolio emissions per £] P2E --> P2F[Economic intensity (kgCO2e/£)] P2C --> P2D P2D --> P2F subgraph Intensity Combination IC1[Physical intensity (kgCO2e/m²)] IC2[Economic intensity (kgCO2e/£)] end P1D --> IC1 P2F --> IC2 subgraph Financing Link FA[Financing amount] end IC2 -- x --> FA subgraph Portfolio Metrics PM[Portfolio metrics] end IC1 --> PM FA --> PM subgraph Housing Approach Reference HA[Housing approach] HA --> P1A1 end ``` *Note: Emissions calculations for UK CRE sector are modelled using information from CRREM, domestic and non-domestic EPCs, and UK BEES data for each property. Since different commercial properties decarbonise at different rates, the assessment considers property type as a key factor. Where properties are residential, the model refers to the UK Housing methodology described in the previous section. For non-domestic properties, baseline emissions from CRREM are used as a starting value. Overall building emissions consist of two parts: emissions covered by EPC; and those not covered by EPC. The former – from heating, cooling and lighting requirements – are proportional to the Asset Rating value of the EPC, while the latter – emissions from activities within the building – are determined using UK BEES data and are assumed to be entirely due to electricity use. Overall emissions are adjusted following changes in grid emission factors for electricity. For properties where there are no certificates, CRREM's baseline emissions are supplemented to account for to-date electricity grid emission factor changes. For segments of our portfolio where no property data is available, we estimate absolute emissions – but these are currently excluded from the physical intensity metric.* ### Figure 31: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---| | **Outstanding amount** | N/A | Internal | December 2024 | | **Latest value (fixed)** | N/A | Internal | September 2023 | | **Building emissions** | N/A | EPC certificates from DLUHC, sourced through DCM | November 2024 | | **Floor area** | N/A | Internal and EPC certificates from DLUHC, sourced through DCM | November 2024 | ### Figure 32: Key choices to calculate the intensity metric | Key choice | Description | |---|---| | **Sector boundary** | Direct CRE lending to specific commercial landlords in UK only | | **Intensity type** | Physical intensity ($\text{CO}_2\text{e}$ emissions per floor area), expressed in $\text{kgCO}_2\text{e}/\text{m}^2$ | | **Emissions scope** | Operational emissions that relate to the use of the property. Can be considered Scope 1 and 2 emissions from the landlord's perspective | | **GHGs measured** | $\text{CO}_2$, methane and nitrous oxide | | **Emissions estimation** | Derived from EPC certificates (estimate of baseline energy intensity used where not available) and supplemented with updated grid emission factor | | **Production weighting** | Floor area as derived from EPC certificates or estimated using property attributes | | **Barclays financing and attribution** | All secured financing activities under Barclays International – CB CRE. The portion of the property for which Barclays financing is used, which is defined as the outstanding balance divided by the property value at origination (LTV) | | **Treatment of missing production data** | Where EPC certificates are not available, we use the intensity information developed at property type and region level and apply the UK Government emission factor | | **Benchmark scenario** | CRREM version two scenario based on the IEA NZE2050 scenario | | **Target baseline year** | 2023 | --- **Notes:** 1. www.crrem.org 2. We use expired EPCs where available since they provide important information on property characteristics, even after they are expired. --- # Our approach by sector – Aviation The Aviation sector comprises the manufacture of aircraft, airport construction and ground operations, and air travel transporting passengers and goods. The majority of this sector's emissions come from the production (often referred to as well-to-tank) and combustion (tank-to-wake) of jet fuel for aircraft operations in commercial aviation. In the short term, decarbonisation may be achieved by shifting to sustainable aviation fuel and through fuel efficiency improvements. In the long run, battery and hydrogen aircrafts may also play a significant role. Shifting short-distance air travel to high-speed rail can also reduce demand, leading to lower emissions from the sector. ### 1.A What metrics are used as benchmarks for the Aviation sector and why? 1.A.1 Our model uses an emissions intensity metric ($\text{gCO}_2\text{e}/\text{revenue tonne kilometres}$) to measure the performance of our Aviation portfolio. 1.A.2 We have selected an intensity metric because emissions reduction is driven by lower intensity (emissions per unit of traffic) while there is an increase in air traffic (passenger and cargo) in the benchmark scenarios. 1.A.3 Commonly used metrics to express air traffic (the denominator) include revenue tonne kilometres (RTK), revenue passenger kilometres (RPK), available tonne kilometres (ATK) and available seat kilometers (ASK). 1.A.4 RPK and RTK measure one paying passenger or tonne of cargo, transported 1km aboard an aircraft. ATK and ASK measure the total payload capacity of an aircraft. 1.A.5 RTK is our chosen metric because it measures the revenue-generating portion of available capacity actually used by operators. It also better captures airlines' efforts to improve operational efficiency (by increasing occupancy rates), resulting in lower emissions intensity. RPK to RTK$^1$ conversion allows emissions from passenger and cargo traffic to be combined and measured with a single intensity metric. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 The benchmark for our Aviation portfolio is based on the MPP PRU scenario for aviation. Released by MPP in its 2022 aviation strategy report, it is based on a bottom-up technical model of the Aviation sector and details a 1.5°C-compatible roadmap for Aviation to achieve net zero emissions by 2050. 1.B.2 Aviation is a hard-to-abate sector as there are limited feasible and cost-effective renewable alternatives. As per the MPP pathway$^2$ there are two levers that may play a crucial role in the overall decarbonisation of the sector in the short term: a. Increased use of Sustainable Aviation Fuel (SAF) as a substitution for jet fuel, produced from sustainable biomass and renewable electricity. b. Increased fuel efficiency, which can reduce final energy demand and emissions - for example through improvements in turbine efficiency, aircraft aerodynamics, air traffic management, flight and ground operations efficiency. 1.B.3 In the longer term, the introduction of hydrogen, battery and hybrid electric aircrafts may be a viable decarbonisation lever. However, these aircraft are not expected to enter the market at scale until the late 2030-40s, and are expected to be limited in their range of travel to only short- and medium-haul flights. Therefore, the use of SAF will likely continue to be important to decarbonise long-haul flights. 1.B.4 A mode shift from short-haul flights to high-speed rail can lead to a reduction in demand for regional flights. MPP estimates this could yield a reduction potential of up to 2% of all commercial aviation emissions, but this shift is dependent on the expansion of high-speed rail networks. 1.B.5 The MPP PRU scenario provides granular information on the decarbonisation of the Aviation sector and the increase in the demand of air travel. 1.B.6 It projects a compound annual growth rate (CAGR) of 2.5% per year (2019-50) in global air travel demand but achieves a 95% reduction in GHG emissions over the same period. Residual emissions are counterbalanced by $\text{CO}_2$ removal solutions to reach net zero. 1.B.7 The scenario also provides a breakdown of the contribution of each decarbonisation measure and the corresponding investments necessary for achieving the required targets. 1.B.8 The MPP PRU was also the chosen benchmark pathway for the Pegasus Guidelines published in March 2024$^3$. 1.B.9 We also assessed IEA's NZE scenario. While we have selected this benchmark for other sectors, we identified some challenges in using it for Aviation-notably, the lack of granularity necessary to construct a pathway based on well-to-wake intensity for commercial aviation, given the scope of the IEA scenario includes military and civil aviation, and includes tank-to-wake emissions only. 1.B.10 While the MPP PRU and IEA NZE pathways are not directly comparable due to differences in scope (well-to-wake versus tank-to-wake), we observe broad consistency in 2019 emissions from the sector (post adjustment) and an increase in air travel demand forecasts across both pathways. ### 2.A. What scope of emissions are included, and why? 2.A.1 The aviation value chain broadly consists of aircraft manufacturers, building and ground operators, aircraft operators (commercial, military, and so on) and suppliers (including fuel suppliers). 2.A.2 As per SBTi's aviation guidance 2021, jet fuel is the primary source of pollution - representing more than 90% of most airlines' value-chain emissions. 2.A.3 We include emissions related to the direct combustion of jet fuel by aircrafts (tank-to-wake) and upstream production and refining (well-to-tank). The emissions scope can differ based on the actual operator of the aircraft, as the owner may not necessarily be the operator. 2.A.4 Our methodology focuses on commercial passengers (including belly$^3$ cargo) and dedicated cargo operators. Military aviation, corporate jets, general civil aviation, tour operators and multi-modal logistics companies are out of scope due to low materiality (share of sector emissions) and data availability challenges. 2.A.5 Measuring well-to-wake emissions is appropriate for the sector as SAF is one of the key decarbonisation levers in the short term. SAF still generates emissions during the combustion phase, like jet fuel, but the emissions are offset by those sequestered during the growth of the feedstock. 2.A.6 Moreover, depending on the type of feedstock used, the lifecycle emissions (both direct and indirect) of different SAF types will vary, impacting the actual amount of decarbonisation. 2.A.7 Our approach to include well-to-tank emissions for the Aviation sector differs from our approach to Automotive, the other transportation sector we assessed. 2.A.8 While the use of electricity is the key source of energy to power alternate technologies (EVs) in the Automotive sector, manufacturers do not have control of the fuel used for electricity generation - which impacts WTT emissions for EVs - in their sales locations. Conversely, airline operators have more control of the fuel source (SAF) used in their aircraft. 2.A.9 We include all GHGs in our upstream well-to-tank emissions estimates, but only consider $\text{CO}_2$ emissions for in-flight operations (tank-to-wake). This is based on the International Civil Aviation Organisation's$^1$ (ICAO) methodology, which provides standardised lifecycle emissions coefficients for different fuels, including conventional jet fuel. 2.A.10 Upstream GHG emissions and in-flight $\text{CO}_2$ emissions from the combustion of jet fuel are responsible for about one-third of the total climate impact of aviation. The other two-thirds could stem from short-lived, non-$\text{CO}_2$ effects such as contrails, in-flight $\text{NO}_\text{x}$, soot and so on. 2.A.11 While there is a growing consensus that climate may be impacted by non-$\text{CO}_2$ effects, there is still a large uncertainty over the actual warming magnitude$^2$. Due to the complex and variable nature of chemical reactions, these can have different impacts on the atmosphere depending on various factors - such as altitude, dispersion area, a region's atmospheric condition, time of day, the season of year and so on. 2.A.12 As a result, it is challenging to monitor non-$\text{CO}_2$ emissions comprehensively - and so they are out of scope of our methodology. This exclusion is in line with SBTi methodology and the Pegasus Principles. ### 2.B. What data is used for these calculations? 2.B.1 The Aviation sector has good data availability on the number and type of aircraft operated by airlines, total flight distance, source and destination between which aircrafts operate, and total fuel burnt. 2.B.2 To calculate emissions from our Aviation portfolio, we source data from PACE (Platform for Analysing Carbon Emissions). 2.B.3 PACE tracks commercial aviation flights operating between airports worldwide. It models emissions for each flight by calculating the amount of fuel burnt between airports by respective aircraft type and variant. PACE's fuel burn methodology aligns with the ICAO's methodology. 2.B.4 PACE also models traffic metrics for passenger, belly and cargo payloads carried by aircraft, presented in RTK for airline fleets. We use emissions and traffic data to calculate our portfolio intensity metric. 2.B.5 While there is good data availability to enable emissions (numerator) modelling, there are data challenges in the availability of actual flight utilisation rate (occupancy) - and even more so for belly cargo - which impact the calculation of air traffic (denominator). 2.B.6 We have considered company-reported emissions and intensities as a potential source of data. However, there are challenges associated with the consistency of reporting at this stage. 2.B.7 Currently, there is no reliable data source providing accurate granular information on the use of SAF (and type) by airline operators, although the share of SAF in overall fuel usage is marginal. 2.B.8 Given the role of SAF in decarbonising the sector, we expect to continue engaging with data providers and counterparties to source relevant data in the future. ### 3.A.3 What financing activities are considered in-scope, and why? 3.A.1 All financing activities (products) as explained on page 6 are in scope, including financing to commercial airlines. 3.A.2 We include exposures through asset-backed securities (ABS) in this sector, which represents financing to aircraft lessors. ABS are typically used to finance the purchase of an individual or pool of aircrafts, which are then leased out to airlines for passenger and cargo operations. 3.A.3 We also include exposures from our payments-acquiring business where we provide products that facilitate clients in accepting card payments. Barclays acquires the transaction, processes it, and settles the value to the client. In the event of default, potential credit losses could occur due to charge-backs. Acquiring is a contingent risk driven by processing transactions for the airline's clients for goods and services (flights) that have not yet been delivered. Payments made through our Barclaycard business, where they are structured as loans, are also included in scope. ### 3.A.4 Green financing for activities in the Aviation sector does not have a differentiated treatment for the purposes of financed emissions. ### 3.A. How is provided financing linked to company-level emissions metrics? 3.B.1 Once company-level emissions metrics are calculated, they need to be linked to the financing we provide. If financing is provided to an airline company or aircraft lessors, our model assigns 100% of financing to its aircraft-operating business. ### 4.A How are client-level measurements aggregated for the Aviation portfolio? 4.A.1 Emissions intensity is calculated as a function of each company's emissions and total air (passenger + belly and cargo) traffic. The portfolio metric is tabulated as an average weighted value using proportion of total portfolio financing. ```mermaid graph TD subgraph Portfolio Metric Calculation A1(Σ Company) -- Company emissions --> A2{Company emissions / Total Company Air Traffic} A2 -- x --> A3(Barclays financing) A4(Σ Company) -- Barclays financing --> A5{Total Company Air Traffic} end ``` ### Figure 33: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---| | **Barclays' financing** | Lending | Internal | December 2024 | | | Capital Markets | Dealogic | December 2024 | | | Asset Backed Securities | Internal | December 2024 | | | Payments | Internal | December 2024 | | | Barclaycard | Internal | December 2024 | | **$\text{CO}_2$ emission factors (Scope 1 and 3)** | N/A | PACE | December 2023 | | **Activity** | N/A | PACE | December 2023 | ### Figure 34: Key choices to calculate the intensity metric | Key choice | Description | |---|---| | **Sector boundary** | Commercial passenger, belly cargo and dedicated cargo operators | | **Intensity type** | Physical intensity ($\text{CO}_2\text{e}$ emissions per revenue tonne kilometres), expressed in $\text{gCO}_2\text{e}/\text{RTK}$ | | **Emissions scope** | Direct in-flight emissions from fuel burnt through aircraft operations (tank-to-wake) and upstream emissions from production and refining of fuel (well-to-tank) | | **GHGs measured** | $\text{CO}_2$ for Scope 1, All GHGs for Scope 3 | | **Scope 1 and 3 emissions estimation** | Well-to-wake emissions calculated from PACE based on fuel burnt by aircrafts that are operated for commercial purposes | | **Activity weighting** | RTK sourced from PACE | | **Barclays financing** | Financing provided or arranged | | **Treatment of missing data** | N/A | | **Benchmark scenario** | MPP PRU | | **Target baseline year** | 2023 | --- **Notes:** 1. Conversion of RPK to RTK includes passenger weight and weight of luggage carried by passenger. 2. www.missionpossiblepartnership.org/wp-content/uploads/2023/01/Making-Net-Zero-Aviation-possible.pdf 3. https://ndcpartnership.org/knowledge-portal/climate-toolbox/pegasus-guidelines-aviation-sector 4. Belly Cargo: Cargo transported in the lower deck (hold or belly) of a passenger aircraft. Belly cargo does not include passenger luggage. 5. Dedicated Cargo: Cargo transported on aircraft specifically flown for the purpose of transporting goods (without passengers). --- # Our approach by sector – UK Agriculture UK Agriculture is a broad sector with a value chain spanning farm commodity production, manufacturing inputs such as tractors and fertiliser, and the distribution and sale of food and other agricultural products. The majority of Agriculture emissions occur during production on the farm. The sector requires changes in the production mix to respond to shifts in societal diets – in particular changes in the quantity and locality of meat and dairy production, improvements in the carbon intensity of production, and changes in how land is used to sequester carbon, including the critical importance of addressing deforestation in delivering on global climate and biodiversity goals. ### 1.A. What metrics are used as benchmarks for the UK Agriculture sector and why? 1.A.1 Our model uses an absolute emissions metric to measure the performance of our UK Livestock and Dairy farming portfolio. We have selected an absolute emissions metric because the majority of emissions reduction is driven by a shift away from the production of meat and dairy towards alternative protein sources, as farmers respond to changing diets. While improvements in carbon intensity of the remaining production also contribute to emissions reductions, these are a small proportion of the total. 1.A.2 In addition, as farming covers a wide range of commodities, setting a single intensity metric presents a challenge. An intensity metric such as emissions per tonne may be inappropriate, as it is less intuitive to aggregate activities such as the production of milk with the production of beef, using tonne of production. 1.A.3 We have also explored alternative metrics such as emissions per calories, but they present challenges and may lead to unintuitive second-order effects. ### 1.B. What scenarios are used for benchmark construction, and why? 1.B.1 The emissions benchmark for our UK Livestock and Dairy portfolio is taken from the CCC BNZ pathway. It provides the geographical granularity needed to inform a UK-focused approach to Agriculture, which is particularly important given the emissions profile of UK Agriculture differs from other countries where issues such as deforestation may be more prevalent. 1.B.2 The pathway to net zero for UK farming will involve a number of decarbonisation activities. The most significant levers in the BNZ pathway, representing over 75% of decarbonisation, occur because of changes in consumer diets- including a reduction in meat and dairy consumption. Additional levers include steps to reduce the intensity of food production, such as feed additives to reduce enteric fermentation emissions. ### 2.A. What scope of emissions are included, and why? 2.A.1 For the UK Agriculture sector, we measure emissions from UK Livestock and Dairy farmers. This reflects that Barclays' exposure to farming production, where the majority of emissions occur, is predominantly within the UK - and recognises the materiality of the Livestock and Dairy sub-sector to overall UK farming emissions. 2.A.2 Our farming clients are assigned a BIC code when at least 50% of their revenue is driven by the operating activity (see Appendix 1) as defined by the BIC code. 2.A.3 Methane and nitrous oxide dominate emissions within this sector, with smaller amounts of $\text{CO}_2$. Methane largely arises from enteric fermentation and manure management related to livestock, and nitrous oxide from the application of fertilisers to agricultural soils. Our approach considers all three of these GHGs. 2.A.4 $\text{CO}_2$, methane and nitrous oxide have different warming effects. We use the GWP100 conversion system, which is the same aggregation approach used in the Upstream Energy sector - more detail can be found on page 17. 2.A.5 We use a fixed boundary system for the Livestock and Dairy sub-sector, where we estimate emissions within the farm-gate. While the majority of emissions occur within this boundary, we have also included emissions associated with activities upstream of the farm - notably feedstock production for livestock. ### 2.B. What data is used for these calculations? 2.B.1 The UK farming industry is characterised by a large number of small farm holdings, which makes collating and processing data challenging. In addition, unlike other sectors where there are databases available of activities and emissions, this is not currently available in the farming industry. 2.B.2 We have enhanced our methodology in 2024 to use internally available data on customers' farming activity, where the data is available (~35% as of December 2024). This corresponds to a move from a PCAF DQ score of 5 to DQ score of 3. 2.B.3 Specifically, we now use livestock headcount and crop area data combined with emission factors from the UK National Atmospheric Emissions Inventory (NAEI)$^1$ to estimate emissions. Our approach follows the IPCC guidelines for national greenhouse gas inventories. 2.B.4 For clients where we have data unavailability, we employ asset-based emission intensities which correspond to PCAF DQ score 5. We use the most recent data available, which in some cases is more than one year old. The consequence is that the calculated attribution factors for these clients may be higher than in practice should be due to the inflation of asset values over time. 2.B.5 Due to the methodology change, our disclosed financed emissions in this sector are greatly reduced compared to last year. This difference is driven mainly by the overestimation of PCAF emissions factors used in the previous methodology. This overestimation is evident from a consideration of disclosed financed emissions in UK Agriculture from the major UK banks who use PCAF emissions factor based models. If these financed agricultural emissions are summed, then the result is greater than the UK's disclosed annual agricultural emissions. We note that the reduction in disclosed emissions does not count towards our target progress since it is due to a methodology change. 2.B.6 We are also aware that there is a high level of uncertainty in the estimation of farm-level emissions using the carbon calculator tools available in the agriculture industry. A study from Defra$^2$ has highlighted large deviations in emissions calculations when using these tools, noting inconsistencies in the use of emission factors, for example. Barclays will seek to incorporate Defra's guidance within future enhancements of emissions calculations for farming customers. ### 3.A. What financing activities are considered in scope, and why? 3.A.1 All financing activities as explained on page 6 are in scope. 3.A.2 Green financing for activities in the UK Agriculture sector does not have a differentiated treatment for the purposes of financed emissions. ### 3.B. How is provided financing linked to client-level emissions metrics? 3.B.1 Once client-level emissions metrics are calculated, they need to be linked to the financing we provide. We approach this by using customer total assets as the measure of the value of that business. 3.B.2 Within the UK Livestock and Dairy portfolio, a large proportion of customers are not registered companies - and, as such, the concepts used in other Blue Track$^{\text{TM}}$ sectors, such as book value of total debt and equity, are not appropriate measures. ### 4.A. How are client-level emissions aggregated for the UK Agriculture portfolio? 4.A.1 Total absolute emissions are calculated as a sum of Barclays' fair share of each client's absolute emissions. Each client's absolute emissions is estimated using internal customer farming activity data and emissions factors from the UK Emission Factor Database. ```mermaid graph TD subgraph Absolute Emissions Calculation A1(Σ Client) -- Barclays financing --> A2{Client emissions / Client value} A2 -- x --> A3[Client emissions] A4(Company emissions) -- Emission factor --> A5[Activity quantity] A5 -- x --> A3 A3 -- x --> A6[Barclays financing] end ``` ### Figure 35: Summary of key data sources for each calculation component | Calculation component | Sub-component | Source | Date of source used for 2024 report | |---|---|---|---| | **Barclays' financing** | Lending | Internal | December 2024 | | **Client financials** | Company value | Internal | December 2024 | | **Emission factors** | N/A | UK NAEI | December 2022 | | **Client activity data** | Farm activity | Internal | Latest available | ### Figure 36: Key choices to calculate the absolute metric | Key choice | Description | |---|---| | **Sector boundary** | Livestock and dairy farmers | | **Emissions scope** | Emissions generated by all farming activities of livestock and dairy farmers | | **GHGs measured** | Relate to the $\text{CO}_2\text{e}$ Scope 1, Scope 2 and Scope 3 upstream emissions. $\text{CO}_2$, methane and nitrous oxide | | **Emissions scope estimation** | Derived from internal client farming data and livestock emission factors, including enteric fermentation and managed manure | | **Activity data** | Total livestock headcount and crop area | | **Barclays' financing and attribution** | Financing provided, including all UK Agriculture mortgage facilities within Barclays UK | | **Treatment of missing data** | Emissions per asset is calculated from available internal data, and applied to those clients where internal data is unavailable on farming activity | | **Benchmark scenario** | BNZ scenario outlined by the CCC | | **Target baseline year** | 2023 | --- **Notes:** 1. https://naei.energysecurity.gov.uk/ 2. Defra (2023), Harmonisation of Carbon Accounting Tools for Agriculture. --- # Known areas for future enhancement Barclays recognises that, while this is the fifth iteration of our methodology, this remains an emerging area with no consistent industry-wide approach to measuring emissions – and that approaches continue to evolve. We believe industry co-operation, particularly in setting common standards and transparent reporting, is important for our stakeholders. We continue to engage with peers, industry experts and academics to assess the transition to a low-carbon economy and consider emerging methodologies and taxonomies – including in respect of carbon accounting and portfolio alignment. ### 5.A. Calculation granularity 5.A.1 Corporate and asset-level information can be inconsistent, lack granularity and be difficult to source. As company disclosures begin to improve, not least as a result of the regulatory reporting requirements, we are hopeful this source of data will play a greater role in the calculation of financed emissions metrics over time. This would allow us to account more easily for regional capacity factors, global carbon intensity factors and other GHGs. 5.A.2 In particular, we recognise that our approach to estimating methane within the Upstream Energy sector is not sufficient to be tracked at a counterparty level, given the difficulties the industry currently faces in measuring emissions. ### 5.B. Data quality, including precision, coverage, matching and recalculations 5.B.1 Climate data, models and methodologies are evolving and are not yet at the same standard as more traditional financial metrics - nor are they yet subject to the same or equivalent disclosure standards, historical reference points, benchmarks or globally accepted accounting principles. Most of our data is collected from external sources, and the quality and methodologies relating to the underlying data can be hard to assess. External sources then require mapping to Barclays' internal data. While we have set a framework that facilitates a robust matching process, it is likely residual issues will remain for reasons such as mergers and acquisitions within corporate sectors or land sales in the UK Agriculture sector. 5.B.2 Asset Impact is our key data source for our most carbon-intensive sectors of Power, Upstream Energy and Automotive. While it has strong coverage across our key markets (the US and Europe), it is not complete in more developing parts of the world and does not include all sectors. There will also be cases - such as oil production owned by sovereign states - not captured within the Upstream Energy financed emissions metric, given the difficulties in assigning Barclays' fair share of the associated emissions. 5.B.3 Data coverage issues are of primary importance when calculating absolute emissions but less important for the other metrics, which are weighted averages. This is partially mitigated as larger clients also tend to have better-quality data. We seek to make these issues and limitations transparent in relation to all the targets we set. 5.B.4 There are also issues with time lags as most of our data is not available as at the reporting date. This is particularly important where we estimate the utilisation of power plants that can be impacted by many events, such as rapid changes in fuel prices, geopolitical events and weather patterns. This may be particularly relevant in years where energy price shocks and market capacity is constrained, for example, as a result of the Russo-Ukrainian conflict, or for other reasons. 5.B.5 For sectors where we rely on company-disclosed emissions, such as Cement and Steel, there are challenges around granularity, consistency and transparency across data - which may lead to inconsistencies in our metrics. Where we source data from company disclosures, our approach is to use the most recent reliable inputs. 5.B.6 In UK Housing, there are limitations of using domestic EPC certificates for measuring emissions of properties. This challenge continues and can only reliably be solved by obtaining actual energy consumption data at a more granular level than is currently available. Furthermore, we have challenges in matching EPC certificates to properties in the UK CRE sector given the differences in our internal addresses to the UK registry. Internal data enhancements are required to improve current matching rates. 5.B.7 Data for the UK Agriculture sector is particularly challenging as, unlike other sectors, databases of production activities and emissions are not currently available in the farming industry. We have enhanced our methodology in 2024 to use internally available data on customers' farming activity. This data is manually obtained through collaboration between the clients and Barclays' Relationship team. We are also working on sourcing customer-specific activity data, in partnership with Oxford University and through engagement with our clients. 5.B.8 We will continue working to enhance and refine our financed emissions metric over time, including as climate data quality improves, methodologies change and company disclosures become more granular. We may re-perform estimates with the improved data that subsequently becomes available - which may lead to a re-baselining of our financed emissions metrics in future years. ### 5.C. Company-level forecasting/ commitments Through public company commitments and our corporate client relationships we are often aware of climate-related commitments clients have made, and we would like to reflect these in our approach over time. ### 5.D. Metrics We calculate a physical intensity and absolute emissions for each sector. However, we make a choice to set a target against either of these metrics - with the exception of UK Agriculture, where data does not currently allow us to measure physical intensity. We do not calculate an aggregated metric across sectors, given the significant double-count of emissions across sectors, nor a temperature alignment metric. ### 5.E. Scenario benchmarks 5.E.1 We use a number of different scenarios to construct Paris-aligned portfolio benchmarks, including the IEA NZE, MPP PRU, CRREM and the BNZ published by the CCC. 5.E.2 While these scenarios have been selected carefully to reflect the appropriate decarbonisation pathway for our portfolios, there are a number of challenges - including consistency and coherency across sectors, and the granularity and emissions coverage of the scenarios. We often have to apply assumptions to the scenario data such that it aligns to our emissions boundary. 5.E.3 Furthermore, we are also aware that new scenario vintages are being published to reflect the latest data on emissions in the sector and the residual emissions budget, to remain Paris-aligned. We intend to review our portfolio benchmarks over time. --- # Appendix 1: Blue Track™ Barclays Industry Classification codes ### Figure 37: Full list of BIC codes used to identify in-scope companies | BIC Code | BIC Name | Sector | Sub-Sector | BIC Code | BIC Name | Sector | Sub-Sector | |---|---|---|---|---|---|---|---| | 2321 | Oil&Gas: Oil & Petroleum Refining & Marketing | Upstream Energy | Downstream | 2750 | Mfg. Metal Castings; Foundries | Metals | Manufacture | | 2322 | Oil&Gas: Other Treatment of Petroleum Products | Upstream Energy | Downstream | 2740 | Mfg. Precious & Non Ferrous Metals | Metals | Manufacture | | 5157 | Wholesale Power and Gas | Upstream Energy | Downstream | 1320 | Non Ferrous Ores Mining | Metals | Manufacture | | 5156 | Wholesale: Fuels, Metals, Paper & Other Intermediate Products | Upstream Energy | Downstream | 1450 | Other Mining & Quarrying | Metals | Manufacture | | 4526 | Oil & Gas Contractors | Upstream Energy | Midstream | 3410 | Mfg. Motor Vehicles | Auto | Manufacture | | 6030 | Oil&Gas: Midstream, Transportation, Gathering and Processing | Upstream Energy | Midstream | 7019 | Housing Associations | UK CRE | Property Investment | | 1120 | Oil&Gas: Service Activities incidental to Oil/Gas Extraction | Upstream Energy | Midstream | 7027 | Property Investment: Commercial | UK CRE | Property Investment | | 1010 | Mining of Coal & Lignite; Manufacture of Solid Fuel | Upstream Energy | Upstream | 7057 | Property Investment: Commercial - Aged Care/Retirement Living | UK CRE | Property Investment | | 1110 | Oil&Gas: Extraction of Crude, Nat Gas, Bituminous Shale & Sand | Upstream Energy | Upstream | 7058 | Property Investment: Commercial - Diversified | UK CRE | Property Investment | | 4020 | Gas Manufacture & Distribution | Power | Distribution | 7055 | Property Investment: Commercial - Healthcare | UK CRE | Property Investment | | 4021 | Gas Manufacture and Distribution - Private | Power | Distribution | 7056 | Property Investment: Commercial - Hospitality / Leisure | UK CRE | Property Investment | | 4022 | Gas Manufacture and Distribution - Public | Power | Distribution | 7054 | Property Investment: Commercial - Industrial | UK CRE | Property Investment | | 4034 | Gas Supply | Power | Distribution | 7051 | Property Investment: Commercial - Multifamily/ Residential | UK CRE | Property Investment | | 4035 | Gas Utility - Integrated | Power | Distribution | 7052 | Property Investment: Commercial - Offices | UK CRE | Property Investment | | 4038 | Power Distribution & Transmission - Investor Owned (i.e. Electric Utilities - Regulated) | Power | Distribution | 7059 | Property Investment: Commercial - Other | UK CRE | Property Investment | | 4039 | Power Distribution & Transmission - Publicly Owned (i.e. Electric Utilities - Regulated) | Power | Distribution | 7053 | Property Investment: Commercial - Retail | UK CRE | Property Investment | | 4010 | Electricity Production & Distribution | Power | Generation | 7028 | Property Investment: Residential | UK CRE | Property Investment | | 4036 | Integrated Utilities - Private | Power | Generation | 7066 | Property Investment: SPE - Aged Care/Retirement Living | UK CRE | Property Investment | | 4037 | Integrated Utilities - Public | Power | Generation | 7067 | Property Investment: SPE - Diversified | UK CRE | Property Investment | | 4011 | Non-renewable Electricity Production and Distribution - Private | Power | Generation | 7064 | Property Investment: SPE - Healthcare | UK CRE | Property Investment | | 4012 | Non-renewable Electricity Production and Distribution - Public | Power | Generation | 7065 | Property Investment: SPE - Hospitality / Leisure | UK CRE | Property Investment | | 4013 | Non-renewable Electricity Production and Distribution - Public (Cooperative) | Power | Generation | 7063 | Property Investment: SPE - Industrial | UK CRE | Property Investment | | 2330 | Nuclear Fuel Processing | Power | Generation | 7060 | Property Investment: SPE - Multifamily/Residential | UK CRE | Property Investment | | 4040 | Power Generation - Alternative Energy | Power | Generation | 7061 | Property Investment: SPE - Offices | UK CRE | Property Investment | | 4041 | Power Generation - Merchant Generators | Power | Generation | 7068 | Property Investment: SPE - Other | UK CRE | Property Investment | | 4042 | Power Generation - Nuclear Energy | Power | Generation | 7062 | Property Investment: SPE - Retail | UK CRE | Property Investment | | 4043 | Power Generation - Other | Power | Generation | 7012 | Property Trading Companies | UK CRE | Property Investment | | 4044 | Power Generation - Project Finance | Power | Generation | 7075 | Real Estate Operating Company (REOC) - Aged Care/Retirement Living | UK CRE | Property Investment | | 4045 | Power Generation - Renewable Energy | Power | Generation | 7076 | Real Estate Operating Company (REOC) - Diversified | UK CRE | Property Investment | | 4046 | Power Generation - Retail | Power | Generation | 7073 | Real Estate Operating Company (REOC) - Healthcare | UK CRE | Property Investment | | 4014 | Renewable Electricity Production and Distribution - Private | Power | Generation | 7074 | Real Estate Operating Company (REOC) - Hospitality / Leisure | UK CRE | Property Investment | | 4015 | Renewable Electricity Production and Distribution - Public | Power | Generation | 7072 | Real Estate Operating Company (REOC) - Industrial | UK CRE | Property Investment | | 4016 | Renewable Electricity Production and Distribution - Public (Cooperative) | Power | Generation | 7069 | Real Estate Operating Company (REOC) - Multifamily/ Residential | UK CRE | Property Investment | | 2650 | Mfg. Cement, Lime & Plaster | Cement | Manufacture | 7070 | Real Estate Operating Company (REOC) - Offices | UK CRE | Property Investment | | 2660 | Mfg. Concrete, Cement & Plaster Products | Cement | Manufacture | 7077 | Real Estate Operating Company (REOC) - Other | UK CRE | Property Investment | | 2730 | Iron & Steel Processing (inc. Rolling & Drawing) | Metals | Manufacture | 7071 | Real Estate Operating Company (REOC) - Retail | UK CRE | Property Investment | | 1310 | Iron Ores Mining | Metals | Manufacture | 6210 | Scheduled Air Transport | Aviation | Air Transport | | 2710 | Mfg. Basic Iron, Steel & Ferroalloys | Metals | Manufacture | 128 | Securitisation - Aircraft | Aviation | Asset Backed | | 2310 | Mfg. Coke Oven Products | Metals | Manufacture | 127 | Dairy Farming | UK Agriculture | Food and Products | | | | | | 126 | Hill & Upland Cattle & Sheep Farming | UK Agriculture | Food and Products | | | | | | 126 | Lowland Cattle & Sheep | UK Agriculture | Food and Products | --- # Appendix 2: Our approach to reporting financial emissions Figure 38 shows how we are measuring progress made against our Upstream Energy metric from 2020-24. ### Figure 38: Tracking the progress made in our Upstream Energy sector | | 2020 | 2021 | 2022 | 2023 | 2024 | Definition | |---|---|---|---|---|---|---| | Reported ($\text{R}_T$) | 75.2 | 58.1 | 51.7 | 42.5 | 41.1 | $\text{R}_T$ = Per methodology as at year T | | Previous year recalibrated ($\text{RC}_T$) | 75.2 | 58.4 | 51.6 | 42.0 | | $\text{RC}_T$ = Per methodology at year T | | Base year rebaseline ($\text{RB}_T$) | 75.2 | 75.6 | 75.4 | 74.1 | | $\text{RB}_T = \text{RB}_{T-1} * \text{RC}_T / \text{RC}_{T-1}$ | | Cumulative progress ($\text{CP}_T$) | -23% | -32% | -44% | -45% | | $\text{CP}_T = \text{RT}_T / \text{RB}_{T-1}$ | | Annual progress ($\text{AP}_T$) | -23% | -9% | -12% | -1% | | $\text{AP}_T = \text{CP}_T - \text{CP}_{T-1}$ | **Definitions** * **Reported**: The metric as reported for the current year * **Previous year recalibrated**: The recalibrated metric for the prior year (T-1), calculated using the same methodology and data in the current year * **Base year rebaseline**: The theoretical baseline metric as at the current year * **Cumulative progress**: Cumulative progress made towards the target in the current year * **Annual progress**: Progress made towards the target in the current year ### Figure 39: Our approach to reporting financed emissions data | Scenario | Our Approach | |---|---| | **Error identified in our internal finance data or methodology** | **Restatement** | Financed emissions metrics for all years impacted by the error will be recalculated including the baseline year. If the impact to portfolio progress over the reporting period is less than 5 percentage points (pp) we will reflect the updated progress in the current reporting period and update the baseline. If the impact is greater than 5pp we will restate prior progress. | | **Change our methodology and/or data sources to calculate financed emissions (including additional GHGs, for example)** | **Re-baseline** | The updated methodology will be applied from the start of the current reporting period. The last reported financed emissions spot metric will be recalculated using the new methodology/data source to provide the new baseline. This will ensure consistency of data and methodology when calculating our performance. The recalculated baseline and the progress achieved to date will be used to disclose the theoretical baseline for the year the targets were originally set. | | **Updates to external counterparty data driven by timing lags when data is reported (counterparty valuations or emissions estimates, for example)** | **Capture in-year** | The cumulative progress will be the progress for the current reporting period (using the new methodology) and the progress up until the last reporting period (using the old methodology). The impact of updated external data will be included in the current period financed emissions data and the progress metric for the current reporting period. Data lags are inherent to the process and Barclays will endeavour to use the latest available data. Historically reported metrics will not be updated for data lags. | --- **[End of Document]** **Barclays PLC 2025** Registered office: 1 Churchill Place, London E14 5HP Registered in England. Registered No: 48839