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Carbon emissions commonly serve as an indicator for environmental friendliness, and so more and more carbon emission calculators (CECs) are offered that allow an estimation of the environmental footprint of freight transport operations. Unfortunately, their exact measurement is challenging due to the availability or poor quality of necessary input data and a multitude of possible calculation methods that may result in highly inaccurate to very misleading figures.

A structured online search was conducted to identify suitable online carbon emission calculators (OCECs) for further assessment in the form of a benchmark case that includes different modes of transport from road and rail to air and sea between China and Europe. Further comparison resulted in a ranking of OCECs along the categories of transparency (routing system, data sources and calculation method), completeness (input options) and accuracy (data output).

Different predefined inputs and calculation methods employed by the OCECs assessed inevitably result in a wide spread of more or less reliable carbon footprint measurement results.

All potential users of CECs, including policymakers, actors from the transport industry and other stakeholders, are well advised to question greenhouse gas (GHG) emission statements that are not backed by transparent procedures and internationally recognized calculation standards.

This study, including a benchmark case and a ranking, offers a guideline for potential users of CEC to avoid major pitfalls coming along with the present carbon footprint measurement of freight transport operations.

Given the interest in sustainable development, this study aims to assess the relationship between CO₂ and urbanization as well as the role of world uncertainty in this association in a South African context.

This study focuses on yearly data from 1968 to 2020. To do this, the authors use the autoregressive distributed lag (ARDL) approach.

The authors find that urbanization’s effect on CO₂ emissions is only significant when it is augmented with world uncertainty. Moreover, this effect is negative (referring to a reduction in CO₂ emissions). Meanwhile, the authors find that GDP has a positive (that is, increasing) and significant effect on CO₂ emissions. Overall, policymakers should focus on decoupling economic growth from traditional fossil fuels that produce greenhouse gas emissions.

The existing body of research contains numerous studies examining the relationship between urbanization and CO₂ emissions. However, the dearth of research on the impact of global uncertainty on this connection is weak. Hence, this study aims to fill this gap and make a significant contribution to the field.

This paper aims to investigate the influence of air and rail transportation on pollution in Turkey from 1970 to 2020.

Fourier Autoregressive Distributive Lags (ADL) and Fourier Fractional ADL cointegration tests (Banerjee et al., 2017; Ilkay et al., 2021) are employed to analyze the relationship be-tween the variables. Cointegration tests that take into account soft transitions under structural changes are implemented. Structural change issues are crucial for this topic since the changes in countries’ environmental policies and transportation habits are shaped by the decisions taken in relation to environmental regulations. Finally, for robustness purposes, we tested the estimated equation with a completely different methodology. Thus, a Machine Learning (ML) analysis is conducted, through a Ridge Regression (RR).

The findings obtained by applying Fourier Autoregressive Distributive Lags (FADL) and Fourier Fractional ADL cointegration tests, which can control for structural changes, reveal the existence of a long-term relationship between the variables. In addition, FMOLS estimates emphasize that economic growth and air transport can lead to increased pollution in the long run, while rail transport reduces it. Moreover, the statistically significant trigonometric terms indicate the existence of a smooth structural change among the variables. Robustness checks are performed through a Machine Learning (ML) analysis, which roughly confirms the previous results.

To our knowledge, existing research in Turkey focuses mainly on road transport, while the impact of rail and air transport on pollution has not yet been investigated. As such, this study will be a significant addition to the academic literature.

This study aims to investigate the impact of financial performance on carbon emission disclosure.

The study uses ordinary least squares (OLS) multiple regression analysis on a sample of 177 Financial Times Stock Exchange 350 index (FTSE-350) non-financial firms to test the impact of market (Tobin’s Q) and accounting (return on equity) financial performance indicators on carbon emission disclosure.

The results show that the financial performance market indicator has a significant positive impact on carbon emission disclosure. The accounting indicator illustrates similar results except for Scope 3, where the results are insignificant. This study may help firms understand how financial performance affects carbon emission disclosure, particularly by showing that high-performing firms are motivated to maintain strong environmental practices and enhance carbon emission awareness.

This paper enhances stakeholders’ understanding of how firms’ environmental policies align with their financial objectives, thereby expanding knowledge in carbon accounting.

The purpose of this paper is to asses the welfare and macroeconomic implications of three distinct degrowth strategies designed to reduce carbon emissions: penalizing fossil fuel demand, substituting aggregate consumption with leisure and disincentivizing total factor productivity (TFP) growth.

Using an environmental dynamic general equilibrium (eDGE) model that incorporates both green renewable technologies and fossil fuels in the production process, this study sets an emissions reduction target aligned with the goals of the Paris Agreement by 2050.

The results reveal that the conventional degrowth strategy, wherein a reduction in the consumption of goods and services is compensated with an increase in leisure, may entail significant economic consequences, leading to a notable decline in welfare. In particular, a degrowth scenario resulting from a decline in TFP yields the most pronounced reduction in welfare. Conversely, inducing a reduction in fossil fuel demand by fiscally inflating the price of the imported commodity, despite potential social backlash, exhibits noticeably less detrimental welfare effects compared to other degrowth policies. Furthermore, under this degrowth strategy, the findings suggest that a globally coordinated strategy could result in long-term welfare gain.

To the best of the authors’ knowledge, this is the first contribution that uses an eDGE model to evaluate the welfare implications of an additional degrowth strategy amidst the ongoing inertial reduction of carbon emissions.

This paper aims to assess the economic impacts of the European Union’s Carbon Border Adjustment Mechanism (CBAM) on Vietnam.

We constructed a general equilibrium model to assess the economic impacts of the CBAM on the macroeconomic indicators of Vietnam. We also constructed a generic partial equilibrium model to provide a zoomed-in view of the impact on each group of CBAM-targeted commodities, which is not possible in the general equilibrium model. Both the general equilibrium and the partial equilibrium models were calibrated with publicly available data and a high number of value sets of hyperparameters to estimate the variations of the estimated impacts.

The results suggest that the current form of the EU’s CBAM is unlikely to produce substantial effects on the overall economy of Vietnam, mainly because the commodities affected by it represent a small portion of Vietnam’s exports. However, at the sectoral level, the CBAM can reduce production outputs and export values of steel, aluminium, and cement.

The CBAM by itself may not lead to significant decreases in greenhouse gas emissions, but it could provide a rationale for implementing carbon pricing strategies, which might result in more significant economic effects and help in reducing greenhouse gas emissions. This highlights the necessity of supplementary policies to tackle global climate change.

We constructed economic models to evaluate the impacts of the European Union’s Carbon Border Adjustment Mechanism on Vietnam, both at the macroeconomic level and zooming in on directly impacted groups of commodities.

This pathway discusses the need for further research into how focal companies measure and manage indirect Scope 3 emissions in their value chains.

This pathway relies on the authors' qualitative research on European companies' decarbonisation strategies. We analysed self-reported and tertiary data from 33 manufacturing European companies considered leaders in climate action. Additionally, interviews were conducted with four experts who work to elaborate decarbonisation strategies in large companies that are part of global value chains.

The limited visibility of focal firms over their value chains and data collection capacity raises questions on the reliability of indirect emissions inventories and companies’ ability to manage indirect emissions.

Investigation of the emerging empirical phenomena of indirect emissions may lead to valuable insights for the measurement and management of sustainability issues.

Our piece explores the process of constructing indirect emissions inventories, assists in ensuring accurate interpretation of the data and provokes discussion on focal companies’ role in managing Scope 3 emissions.

Many stakeholders refer to companies' Scope 3 inventories. This piece exposes inconsistencies in these inventories and what companies' responsibilities are in managing emissions.

Research on managing sustainability issues in supply and value chains is increasing, and indirect emissions are central in this space. This impact pathway seeks to stimulate research in underdeveloped areas by discussing the limitations of this data and highlighting practical limitations present in its management.

Since the withdrawal of IFRIC 3 in 2005, there has been a regulatory freeze in accounting for emission rights that contrasts with the international momentum of climate-related financial disclosures. This paper explores how different narratives and institutional dynamics explain the failure to produce guidance on accounting for emission rights.

This paper mobilises the notion of field-configuring events to examine a sequence of six events between 2003 and 2016, including four public consultations and two dialogues between standard setters. The paper presents a qualitative analysis of documents produced in this space that investigates how different practices and narratives configured the field's positions, agenda, and meaning systems.

Accounting for emission rights was gradually decoupled from climate change and carbon markets, relegated to the research pipeline, and forgotten. The obstacles that the IASB and EFRAG found in presenting themselves as central in the recurring events, the excess of representations, and the increasingly technical and abstract debates eroded the 2003 momentum for regulation, making the different initiatives to revitalise the project vulnerable and open to scrutiny. Lukes (2021) refers to nondecision-making to express that some issues are suffocated before they are expressed.

The regulation of accounting for emission rights, an area that has received scant attention in the literature, provides some insights into the different narrative mechanisms that, materialising in specific times and spaces, draw regulatory attention to particular accounting issues, which are problematised and, eventually, forgotten. This study also illustrates that identifying interests is problematic as actors shift from alternative positions over a long period. The case examined also raises some doubts about the previous effectiveness of international standard setters in dealing with matters of connectivity between the environment and finance, as is the case for accounting for emissions rights.

To achieve sustainable development in shipping, accurately identifying the impact of artificial intelligence on shipping carbon emissions and predicting these emissions is of utmost importance.

A multivariable discrete grey prediction model (WFTDGM) based on weakening buffering operator is established. Furthermore, the optimal nonlinear parameters are determined by Grey Wolf optimization algorithm to improve the prediction performance, enhancing the model’s predictive performance. Subsequently, global data on artificial intelligence and shipping carbon emissions are employed to validate the effectiveness of our new model and chosen algorithm.

To demonstrate the applicability and robustness of the new model in predicting marine shipping carbon emissions, the new model is used to forecast global marine shipping carbon emissions. Additionally, a comparative analysis is conducted with five other models. The empirical findings indicate that the WFTDGM (1, N) model outperforms other comparative models in overall efficacy, with MAPE for both the training and test sets being less than 4%, specifically at 0.299% and 3.489% respectively. Furthermore, the out-of-sample forecasting results suggest an upward trajectory in global shipping carbon emissions over the subsequent four years. Currently, the application of artificial intelligence in mitigating shipping-related carbon emissions has not achieved the desired inhibitory impact.

This research not only deepens understanding of the mechanisms through which artificial intelligence influences shipping carbon emissions but also provides a scientific basis for developing effective emission reduction strategies in the shipping industry, thereby contributing significantly to green shipping and global carbon reduction efforts.

The multi-variable discrete grey prediction model developed in this paper effectively mitigates abnormal fluctuations in time series, serving as a valuable reference for promoting global green and low-carbon transitions and sustainable economic development. Furthermore, based on the findings of this paper, a grey prediction model with even higher predictive performance can be constructed by integrating it with other algorithms.

This study investigated the visibility of carbon emissions allowances accounting in the financial reports of 32 clean development mechanism (CDM) projects in the UAE to uncover the obstacles to setting consistent standards for carbon emission accounting. As carbon emissions are monetized as credits, consistent accounting standards can aid decision-makers in the development of carbon emission mitigation strategies.

This study used a grounded theoretical framework for exploring the terms used in the policy documents of international accounting bodies regarding accounting standards and guidelines for carbon emission credits. Raw qualitative data were gathered, and an inductive approach was used by analyzing documents from various sources using the qualitative data text analysis software QDA Miner 6.

The findings showed that the financial statement reports of the corporations did not include disclosure of the carbon credit account. This omission was due to the lack of global standardization of carbon credit accounts and emission allowance recognition. This may hinder the production of a comprehensive report containing accurate and valuable financial information relevant to all stakeholders.

The study is among the first to use a grounded theoretical framework to investigate whether corporations are applying common standards and guidelines for carbon emissions accounting.