Corporate Carbon Footprint Research Articles

Transport-Related Emissions and Transition Strategies for Sustainability—A Case Study of the Fast Fashion Industry

The fast fashion industry significantly impacts the environment at every stage of a product’s life cycle. The transport of products to wholesalers and stores, as one of the stages of the product life cycle, is often overlooked during the analysis of their carbon footprint. Therefore, research is needed on the impact of fast fashion on the environment through its logistics and transport, especially in relation to air emissions. This article attempts to determine how extensively fast fashion companies disclose the impact of their transport operations on their overall corporate carbon footprint, determine the proportion of total emissions attributed to transport, and evaluate the effectiveness of companies’ efforts to mitigate their transport-related environmental impact. This research used a case study method on selected brands (H&M Group, Inditex, Shein), using secondary data available in non-financial reports for 2023. As a result of the analysis of their non-financial reports on transport emissions, several key findings have been presented. Companies predominantly rely on external frameworks and standards, particularly the Global Reporting Initiative. However, the level of detail of the data presented varies. The priority for the surveyed companies is to reduce emissions from significant sources, such as production processes. The data disclosed in the reports (scope 1, 2, 3) must be clearly formulated and can be used to calculate the level of their CO2 emission reduction or increase. Companies should improve their environmental reporting by including indicators of their transport-related emissions. This approach provides a comprehensive view of their environmental impact, highlighting absolute values and efficiency metrics.

CEO hubris and corporate carbon footprint: The role of gender diversity

AbstractThis paper investigates the effect of an overconfident CEO on firm greenhouse gas emissions. Using panel data of 160,115 firm‐year observations from 41 countries for 2000–2021, we find a negative relationship between CEO overconfidence and greenhouse gas emissions. Additionally, drawing on the theories of gender socialisation and diversity, we find that great representation of females on the board further compels overconfident CEOs to reduce firm carbon emissions. Our findings are robust to varying estimation techniques and identification strategies. These findings offer important insights to green investors, corporate boards, managers and policymakers on the role of overconfident CEOs and female leadership in the carbon abatement efforts of public companies.

A real-time estimation method of carbon emission for cement corporations based on load identification

Abstract Accurate carbon emission estimation is the basis for assessing the carbon emissions of various regions and industries and formulating reasonable and feasible emission reduction programs. This paper presents a generalized real-time corporate carbon footprint measurement method. The total carbon emissions are categorized into direct emissions and indirect emissions. For the former, a load identification method based on CNN-BLSTM is proposed to monitor the state of the devices, and the carbon emissions are directly calculated in combination with the carbon emission intensity of the devices; for the latter, accurate estimation of carbon emissions is achieved through the application of marginal carbon emission factor. By utilizing this analytical model, the estimated carbon emissions are more accurate than those of other methods, which can better grasp the carbon emissions of enterprises and promote energy saving and emission reduction.

Corporate Carbon Footprint: Evaluating Environmental Risks and Incentives in the Era of Climate Finance

To fight climate change and reduce their increasing pollution levels, developing nations must have access to worldwide public climate funds. In the view of developing nations, meeting their commitments to reduce emissions under the Paris Agreement depends on receiving funding for climate-related initiatives. According to earlier studies, financing developing nations may help them meet their climate targets. The most recent data on climate money and NDCs are used in this research to examine the subject from a practical standpoint. Two research approaches were used in this study to investigate the impact of climate funding on the objectives of recipient nations. Data indicated that it was excellent regardless of the size of the effect. Developing nations’ attempts to reduce emissions were more affected than those of the least developed nations, especially those with economies centred on tiny islands. This paper outlines how to solve the issue, but it is just the beginning. By informing their handling of climate money, investors can gain poorer nations’ confidence, according to this research.

Corporate carbon accounting: balance sheets and flow statements

Current corporate disclosures regarding carbon emissions lack generally accepted accounting rules. The transactional carbon accounting system described here takes the rules of historical cost accounting for operating assets as a template for generating carbon emissions (CE) statements comprising a balance sheet and a flow statement. The asset side of the CE balance sheet reports the carbon emissions embodied in operating assets. The liability side conveys the firm’s cumulative direct emissions into the atmosphere as well as the cumulative emissions embodied in goods acquired from suppliers less those sold to customers. Flow statements report the company’s annual corporate carbon footprint calculated as the cradle-to-gate carbon footprint of goods sold during the current period. Taken together, balance sheets and flow statements generate key performance indicators of a company’s past, current, and future performance in the domain of carbon emissions.

Assessment of Corporate Carbon Footprint and Energy Analysis of Transformer Industry

Transformers are primarily key components in power transmission and distribution systems. In the electrical industry, transformers are becoming increasingly important to increase energy efficiency and reduce environmental impact. In the process from the production to the use of transformers, various strategies and technologies are adopted to reduce the carbon footprint. To achieve decarbonization targets and a future with sustainable energy, ongoing efforts to reduce the carbon footprint of transformers need to continue. Therefore, this study aims to calculate the carbon footprint (CF) of Beta Energy in the Adana Province of Türkiye. A comprehensive inventory is being created to determine and monitor the greenhouse gas emissions of Beta Energy, a transformer manufacturer. This inventory includes direct and indirect greenhouse gas emissions from all of the company’s activities. The findings show that in 2023, the total CF of Beta Energy is equal to 1,799,482.72 tons of CO2-eq and considering the total of 6044 transformers sold in 2023, results in 297 tons of CO2-eq/transformer per product. The results show that the transformer manufacturing industry has a high carbon footprint because it is an energy-intensive process. The areas where the most carbon emissions occur in transformer production are revealed by CF hot spot analysis in this study. To minimize both current and future greenhouse gas emissions during transformer production, the measures to be taken during the R&D, production, transportation, and service stages are revealed. This study aims to establish a foundation for Beta Energy’s efforts to reduce greenhouse gas emissions by managing them effectively.

Corporate carbon footprint and market valuation of restructuring announcements

AbstractThe call for greener and more sustainable corporate practices triggered a surge in corporate restructuring. In this study, we investigate the impact of carbon emissions on the market reaction to announcements of corporate restructuring activities. Using a sample of US firms, we find that investors discount the value of corporate restructuring announcements when firms have higher levels of carbon emissions. Our results indicate that emissions are negatively associated with cumulative abnormal returns (CAR), cumulative total returns (CTR), and buy and hold abnormal returns (BHAR) around announcements. This effect is more pronounced for firms with a lower risk of bankruptcy, those financially constrained, and those with lower growth opportunities. We also find that high emissions at announcements are negatively associated with post-restructuring financial and market performance. Overall, our results highlight the growing implications of firm-level carbon emissions for corporate market valuations, especially amongst firms undertaking restructuring.

Reduction of carbon footprint by using recyclable bottles—A case study on Austrian wine

A decarbonized society can only become reality if all potential greenhouse gas is leveraged. In order to achieve this, it is necessary to scrutinize all processes, to assess whether a high level of energy and material efficiency has been achieved and whether renewable energy sources are used to the maximum extent. In this investigation, we were investigating the corporate carbon footprint of a winery in Austria. All data, energy and material inputs were taken within the framework of a scenario analysis for one hectare of vineyard with a yield of a 5-year average of 5380 L. The energy and material input in a winery in Austria under the system limit considered in these calculations results in a GHG emission of about 1.04 kg per L of bottled wine (or 0.78 kg per 0.75-L bottle). On the other hand one kg of grapes would therefore cause 0.24 kg of CO2e.The GHG emissions for the production of a wine bottle in Austria causes 0.328 kg CO2 equivalent emissions. The GHG emissions for washing (0.011 kg CO2 equivalent emissions per bottle), on the other hand, amount to only 3.4% measured against a new bottle in Austria. The bag-in-box system can only be used once. This system leads to 59% higher GHG emissions per L compared to reusable bottles on the basis of 12 filling cycles (system sustainability – lightweight bottles). At a refill rate of 50% in a winery, GHG emissions are reduced to 4367 kg per ha (−32% compared to normal and new glass in the winery). The calculations show that refilling the wine bottle has the highest savings potential. Measures to achieve this multiple use should be implemented as soon as possible in the wine industry.

Calculating the Environmental Benefit of Reuse Platforms

AbstractReuse platforms are contributing to the circular economy by hosting or mediating unwanted products or materials until new users are found. This saves products from premature disposal on one hand, and avoids new products purchase on the other. Translating this resource efficiency and waste minimisation into GHG emission avoidance can support the relevance of reuse platforms in fostering a circular economy and promoting climate protection through resource preservation and potential GHG emission reductions. The authors present the analysis of existing reuse methodologies and point out incomplete considerations in terms of LCA modules and Corporate Carbon Footprint of reuse platforms [11]. This paper fills the gap in literature by formulating a holistic methodology for calculating benefits of reuse in terms of GHG emissions for the whole reuse sector and provides an application guide for 4 different types of reuse platforms. This new approach is then illustrated by applying it to a reuse enterprise Zündstoffe Materialvermittlung Dresden (ZUMADD) case study, for which data was gathered for 2 years under Dresden Future City Project (2019–2022). The results show that the project could save 13,301 kg of CO2e emissions through mediating 6,213 kg of material for reuse.

Carbon insetting as a measure to raise supply chain energy efficiency potentials: Opportunities and challenges

There is great potential for companies to reduce greenhouse gas emissions (GHGE) by implementing and financing decarbonisation measures in their own value chain. A company's active contribution to reducing GHGE at a stakeholder in its value chain is considered as carbon insetting e.g. financing of energy efficiency measures along the supply chain as one possibility. The implementation of insetting measures by industrial companies is currently only rudimentarily established. Moreover, there are no precise rules on how insetting should be accounted for. However, the resulting GHGE reductions can affect the corporate carbon footprints of several companies. This leads to the question on how insetting could be transparently reported, while still setting incentives for emission reductions along the supply chain. A comparison of literature based carbon insetting concepts are distinguished from each other in regard to local references and accounting approaches. Based on these a case study of the implementation of supply chain energy efficiency measures in the automotive industry to illustrate accounting issues is developed. The case study exemplifies, that a company that finances an energy efficiency measure at a supplier can only report 10% of the reduced GHGE in its carbon footprint. In light of this background, the pillar model for GHGE accounting is adapted to incorporate carbon insetting. In addition to the carbon footprint (pillar A), two other pillars are introduced. In pillar B, the GHGE reductions outside the scopes of the reporting company can be accounted for. Greenhouse gases removed from the atmosphere can be accounted for in pillar C. The novelty of this study is applying the concept of insetting to an industrial case study and the use of the pillar model to enable transparent accounting of insetting measures. It can thereby serve as a basis for industrial reporting of carbon insetting. By addressing methodological challenges the study provides a basis for further discussion on the concept of carbon insetting.

Moderation of Clean Energy Innovation in the Relationship between the Carbon Footprint and Profits in CO₂e-Intensive Firms: A Quantitative Longitudinal Study

This paper sought to analyze the moderating effect of clean energy innovation on the relationship between corporate carbon footprint and corporate profits in fossil fuel intensive industrial sectors in which it is “hard to abate” CO₂e emissions. We used a longitudinal design consisting of a panel study with a structural equation modeling (SEM) method, based on partial least squares. For the analysis of longitudinal moderation, this paper employed a Bayesian multiple-indicator latent growth curve model (B-LGC model). A global sample was used, consisting of 7827 firm-year observations between 2015 and 2021 for 167 international firms. The results showed that the corporate carbon footprint had a very significant impact on corporate profits and that innovations in clean energy—measured as renewable energy consumption—positively moderate the relationship between Scope 3 value chain greenhouse gas emissions (according to the Greenhouse Gas (GHG) Protocol) and the gross profit margin obtained. In addition to the academic contributions made by the moderating effect of clean energy innovation, these findings imply that a more detailed understanding of total value chain emissions (Scope 3 CO₂e) among executives and managers at high CO₂e-emitting companies offers an effective mechanism for obtaining higher profits and creating competitive advantages, while at the same time achieving a net zero emissions strategy. More importantly, public policymakers will be able to use these results to revise CO₂e-related policies, paying closer attention to the Scope 3 CO₂e emissions produced by these companies to design regulatory and control mechanisms that stimulate clean energy innovation.

The Effects of the Covid-19 Period on Carbon Footprint in Sakarya University Esentepe Campus

Climate change, one of the biggest threat of global life, is continuously triggered by greenhouse gases released into the atmosphere due to human activities. Carbon dioxide (CO2), one of the most important greenhouse gases, has revealed the concept of carbon footprint, and efforts to take mitigation measures by calculating it have become widespread. With sustainable campus studies, universities, where science and innovations are created, lead other institutions by creating the necessary database for measuring and managing greenhouse gas (GHG) emissions and calculating the corporate carbon footprint. This study calculated and compared the carbon footprints of Sakarya University Esentepe Campus for 2019 and 2020 when distance education was carried out during the Covid-19 pandemic. Greenhouse gas emissions resulting from activities on campus were calculated and converted to a CO2 equivalent. GHG emission factors and the Tier-1 method of the Intergovernmental Panel on Climate Change (IPCC) were used in the calculations. As a result, the carbon footprint was 13273.38 tCO2e in 2019 and 6338.72 tCO2e in 2020. It was determined that the largest share of carbon emissions was due to the use of electrical energy. The results obtained for both years were compared, and a 47.7% reduction in total emissions was evaluated. In the light of current studies on carbon emission reduction, suggestions and measures need to be taken are summarized in this research.

Real-Time Corporate Carbon Footprint Estimation Methodology Based on Appliance Identification

Achieving carbon neutrality is widely recognized as the key measure to mitigate climate change. As the basis for achieving carbon neutrality, corporate carbon footprint (CCF) estimation is mainly based on the disclosed information of corporates to roughly estimate the direct carbon emission, but the estimation may not be comprehensive, timely, and accurate. In this article, the CCF estimation problem is formulated and a novel estimation methodology is proposed for the first time to estimate the direct and indirect carbon emissions of factories in real time. An appliance identification method based on the multihead self-attention mechanism and gated recurrent unit is proposed to identify the device states, and then, calculate the corresponding direct carbon emission. The indirect carbon emission is derived from the electricity consumption of the factory and the marginal carbon emission factor of the connected bus. A dataset containing load and device state data from six different industries is released and used to verify the effectiveness of the proposed method. Experiments show that the proposed appliance identification method is significantly superior to the benchmarks in the literature, and the proposed method can achieve a comprehensive and accurate estimation of the minute-level CCF.

In search of climate distress risk

Using the Merton distance to default model we investigate whether a firm's climate risk affects its default (distress) risk. S&P 500 non-financial firms during 2010–2019 are analysed and we employ both corporate carbon footprints and climate risk disclosures in annual filings to measure climate risk. Our results show that climate risk has a negative impact on firms' distance to default. This impact is limited to the disclosure of transition risk in annual filings. In contrast, disclosures of physical or non-specific risk do not affect firm-level default risk, while the impact of corporate carbon footprints is inconsistent but insignificant in most models. We also find that the negative effect of climate transition risk on firms' distance to default is stronger for firms headquartered in states with carbon pricing (California and states covered by the Regional Greenhouse Gas Initiative) and temporarily strengthens because of the Paris Agreement in 2015. However, this ‘Paris’ effect is short-lived and fades away in subsequent years.

Climate transition risk in U.S. loan portfolios: Are all banks the same?

We examine banks' exposure to climate transition risk using a bottom-up, loan-level methodology incorporating climate stress test based on the Merton probability of default model and transition pathways from the Intergovernmental Panel on Climate Change (IPCC). Specifically, we match machine learning predictions of corporate carbon footprints to syndicated loans initiated in 2010–2018 and aggregate these to loan portfolios of the twenty largest banks in the United States. Banks vary in their climate transition risk not only due to their exposure to the energy sectors but also due to borrowers' carbon emission profiles from other sectors. Banks generally lend a minimal amount to coal (0.4%) but hold a considerable exposure in oil and gas (8.6%) and electricity firms (4.6%) and thus have a large exposure to the energy sectors (13.5%). We observe that climate transition risk profile was stable over time, save for a temporary (in some cases) and permanent (in others), reduction in their fossil-fuel exposure after the Paris Agreement. From the stress testing, the median loss is 0.5% of US syndicated loans, representing a decrease in CET1 capital of 4.1% when extrapolated to the whole balance sheet. The loss is twice as large in the 1.5°C scenarios (1.4%–2.1% of loan value, 12%–16% of CET1 capital) compared to the 2°C target (0.6%–1.1% of loan value, 5%–9% of CET1 capital) with significant tail-end risk (7.7% of loan value, 62% of CET1 capital). Banks' vulnerabilities are also driven by the ex-ante financial risk of their borrowers more generally, highlighting that climate risk is not independent from conventional risks.

How colleges should lead on climate.

How colleges should lead on climate.

Harmonizing corporate carbon footprints

Global greenhouse gas emissions need to reach net-zero around mid-century to limit global warming to 1.5 °C. This decarbonization challenge has, inter alia, increased the political and societal pressure on companies to disclose their carbon footprints. As a response, numerous companies announced roadmaps to become carbon neutral or even negative. The first step on the journey towards carbon neutrality, however, is to quantify corporate emissions accurately. Current carbon accounting and reporting practices remain unsystematic and not comparable, particularly for emissions along the value chain (so-called scope 3). Here we present a framework to harmonize scope 3 emissions by accounting for reporting inconsistency, boundary incompleteness, and activity exclusion. In a case study of the tech sector, we find that corporate reports omit half of the total emissions. The framework we present may help companies, investors, and policy makers to identify and close the gaps in corporate carbon footprints.

Current trends and key limitations of climate-related disclosure by Russian companies

Climate-related disclosure and reporting have become major topics of the discussion among the key players influencing business decisions in the past few years. The United Kingdom and other countries’ plans regarding mandatory climate-related disclosure for the major listed companies, investors’ enquires about CDP questionnaires to be filled and European Union actively promoting its carbon neutral plans influence Russian business community decisions. In order to comply with the latest trends and future demands it is critical to assess corporate carbon footprint correctly, especially for the most carbon intensive companies specialising in mining and steel production, which can be seriously affected by the forecasted EU Carbon Border Tax towards carbon intensive imported products. Although, currently there are some limitations which may misrepresent some of the Russian companies’ greenhouse gas emissions calculation results, and further decarbonisation initiatives. One of the key reasons is a lack of national methodological guidelines and emissions factors provided by the Russian ministries and research centres, which have to guide Russian companies in the field of regional-based emissions assessment. This article examines the current trends of climate-related disclosure based on the CDP scores of Russian companies and discusses the potential ways of improving the national methodological support in order to provide quality and credible data connected with the climate risk management and disclosure. The most important drawbacks were identified, such as the lack of methodological guidelines and emission factors for calculating direct greenhouse gas emissions (Scope 1), regional emissions factors for calculating indirect energy emissions (Scope 2) for the Russian Federation, as well as the lack of both methodological guidelines and emissions factors database for calculating other indirect emissions (Scope 3). Finally, the expected consequences of such methodological disadvantages were described, and the recommended steps to improve the effectiveness of this climate-related disclosure practice were proposed.

The making of the corporate carbon footprint: the politics behind emission scoping

ABSTRACT The key measurement standard used by the private sector to measure the carbon emission impact of an organization is the corporate carbon footprint. Known as the GHG Protocol, this standard was created in 2001 through a multi-stakeholder collaboration and is now used by thousands of companies globally. This article discusses the origins of the Protocol to better illuminate the politics surrounding the counting and measuring of carbon emissions as environmental intangibles that serve as a critical first step towards corporate climate action. Using archival research and interviews with key stakeholders, I underscore the actors involved and their motivations, which combined led to the development of certain internal accounting technologies, namely the practice of scoping. Scoping was proposed as a way to categorize emissions according to levels of legal ownership and control and avoid ‘double-counting’. Using Chiapello and Engels’ suggesting that integrating scoping was an effort to forge a compatibility between economic growth and climate protection and protect the financial interests of businesses by narrowly enclosing climate mitigation responsibility. To conclude, I discuss the lasting implications to measuring carbon with the corporate carbon footprint for meaningful climate action.

Predicting corporate carbon footprints for climate finance risk analyses: A machine learning approach

Abstract Corporations have come under pressure from investors and other stakeholders to disclose and reduce their greenhouse gas emissions (GHG). Corporate GHG footprints, proxying for transition risk, are dominated by carbon emissions from energy use. Thus the growing attention on the carbon emissions of corporations from, principally, their energy use, motivates firms to invest in energy efficiency and renewable energy. However, only a subset of corporations disclose their GHG/carbon footprints. This paper uses machine learning to improve the prediction of corporate carbon emissions for risk analyses by investors. We introduce a two-step framework that applies a Meta-Elastic Net learner to combine predictions from multiple base-learners as the best emission prediction approach. It results in an accuracy gain based on mean absolute error of up to 30% as compared with the existing models. We also find that prediction accuracy can be further improved by incorporating additional predictors (energy production/consumption data) and additional firm disclosures in particular sectors and regions. This provides an indication of where policymakers should concentrate their efforts for greater level of disclosure.