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The objective of this study is to determine the impact of GHG assurance on firms’ carbon emissions performance (CEP) regarding curbing carbon emissions and the effect on such by the GHG assurance provider’s affiliation and reputation. It also explores whether the affiliation and reputation of GHG assurance providers imply the relationship between GHG assurance and the firm’s CEP. Further, this study examines the moderating effect of the country’s development level on the relationship.

Based on a sample of international firms from 56 countries spanning the period from 2012 to 2020, this study utilizes the ordinary least squares (OLS) regression. We also run the OLS regression at times t+1 and t+2 to verify the baseline results. To address the endogeneity concerns arising from self-selection bias and the causality effect, this study applies the generalized method of moment (GMM) and the Heckman test.

This study finds that GHG assurance leads to better CEP by firms. We also find that engaging with accounting assurance providers leads firms to a better CEP than non-accounting assurance providers. Our results show that Big Four auditors can help firms decrease carbon emissions. We also find that the positive effect of GHG assurance is prevalent in firms operating in developed countries.

Our study only considers the influence of the assuror’s reputation and affiliation on CEP without examining other factors that may influence the quality of assurance services provided.

Our study provides a practical implication related to the influence of a GHG assurance provider’s affiliation and reputation globally by providing evidence that accounting and Big Four assurance providers do play a significant role in a firm’s carbon emission performance. This study offers great insights into the GHG assurance impact on CEP with the interplay between the assuror’s affiliation and reputation and the country’s development.

This paper enriches the limit evidence on GHG assurance and CEP by providing novel evidence on the relationship between GHG assurance and a firm’s CEP. Moreover, this study provides insights into the implication of a country’s development level on the role of GHG assurance in CEP.

Avoided emissions refer to greenhouse gas emission reductions that are a result of using a product or are emission removals due to a decision or an action. Although there is no uniform standard for calculating avoided emissions, market actors have started referring to avoided emissions as “Scope 4” emissions. By default, making a claim about Scope 4 emissions gives an appearance that this Scope of emissions is a natural extension of the existing and accepted Scope-based emissions accounting framework. The purpose of this study is to explore the implications of this assumed legitimacy.

Via a desktop review and interviews, we analyse extant Scope 4 company reporting, associated accounting methodologies and the practical implications of Scope 4 claims.

Upon examination of Scope 4 emissions and their relationship with Scopes 1, 2 and 3 emissions, we highlight a dynamic and interdependent relationship between quantification, commensuration and standardization in emissions accounting. We find that extant Scope 4 assessments do not fit the established framework for Scope-based emissions accounting. In line with literature on the territorializing nature of accounting, we call for caution about Scope 4 claims that are a distraction from the critical work of reducing absolute emissions.

We examine the implications of assumed alignment and borrowed legitimacy of Scope 4 with Scope-based accounting because Scope 4 is not an actual Scope, but a claim to a Scope. This is as an act of accounting territorialization.

This study examines the carbon emissions of Australia’s agriculture, forestry and fishing sectors from a consumption perspective to develop effective policy frameworks. The objective is to identify key supply chains, industries and products contributing to these emissions and provide recommendations for sustainable development.

A multiregional input-output lifecycle assessment was conducted using the Australian Industrial Ecology Virtual Laboratory (IELab) platform to disaggregate sectors and enable benchmarking against other economic sectors.

In 2018, the “agriculture, forestry, and fishing” sector was responsible for 12.15% of Australia’s carbon footprint. Major contributors included the “electricity, gas, water, and waste” category (26.1%) and the sector’s activities (24.3%). The “transport, postal, and warehousing” sector also contributed 18.4%. Within the industry, the agriculture subsector had the highest impact (71.3%), followed by forestry and logging (15%) and fishing, hunting and trapping (7.6%). Aquaculture and supporting services contributed 6.1%.

The principal constraint encountered by the present study pertained to the availability of up-to-date data. The latest accessible data for quantifying the carbon footprint within Australia’s agriculture, forestry and fishing sector, utilizing the Input-Output analysis methodology through the Australian Industrial Ecology Virtual Laboratory (IELab) platform, about 2018.

The findings of this study provide policymakers with detailed insights into the carbon footprints of key sectors, highlighting the contributions from each subsector. This information can be directly used to develop effective emission-reduction policies, with a focus on reducing emissions in utility services, transport and warehousing.

The study, by raising public awareness of the significant role of industrial agricultural methods in Australia’s carbon footprint and emphasizing the importance of renewable energy and sustainable fuels for electricity generation and road transport, underscores the urgent need for action to mitigate climate change.

This study stands out by not only identifying the most impactful industries but also by providing specific strategies to reduce their emissions. It offers a comprehensive breakdown of specific agricultural activities and outlines mitigation strategies for utility services, agricultural operations and transport, thereby adding a unique perspective to the existing knowledge.

This study aims to examine the influence of corporate carbon emissions on the financial performance of select Indian companies. It further studies the moderating role of science-based target initiatives (SBTi) in this relationship.

The study is based on 57 Indian SBTi companies and 74 Bombay Stock Exchange-listed non-SBTi companies for the period of four years from 2019–2020 to 2022–2023. The panel data regression models are used to study this association. Furthermore, two-stage least square and generalized method of moments models are used to test the robustness of the results.

There is a negative relationship between corporate carbon emissions and financial performance. The findings support the “win-win” hypothesis and confirm that reducing carbon emissions can improve the financial performance of Indian firms. Furthermore, the SBTi moderate the carbon emission and firm performance nexus.

The findings of the study would provide insights to the policymakers, regulators and managers to mainstream climate change in their core business activities driving sustainability and profitable outcomes.

This study is a noble attempt to study the moderating role of science-based targets in the carbon emissions and firm performance nexus in an emerging market setting. Earlier studies have been conducted in a cross-country context.

The nexus of transport and tourism is critical to the 2021 Glasgow Declaration which sets out the net zero by 2050 goal for global tourism in the context of the Paris Agreement. Numerous small and medium-sized urban destinations (SMUDs) populated under one million are constrained by a limited capacity to manage visitor flows and increasing greenhouse gas (GHG) emissions. This paper aims to develop an analytical approach for urban practitioners, based on a case study in Taiwan, to identify the low-emission pathway and strategies for tourism passenger transport.

A GHG emissions assessment and scenario analysis were enabled by historical activity data from official sources and projected scenario data from the International Energy Agency. The scenarios were established based on the avoid-shift-improve framework for low-carbon transport.

To drive tourism passenger transport to a low-emission pathway compatible with the Paris Agreement goal, three low-carbon transport strategies, i.e. “Avoid,” “Shift” and “Improve,” shall be applied all together, with a focus on “improving” the efficiency of heavy-duty vehicles and rail transport. Meanwhile, alternative tourism and integrated transport policy packages could enhance demand-side management of visitors’ mobility, enabling the “avoid” and “shift” strategies.

Unlike most studies that have focused on large cities or small tourist areas, this paper addressed our knowledge gap regarding the low-emission pathway for tourism transport in numerous SMUDs compatible with a 1.5°C world. The proposed analytical approach can help policymakers assess effective strategies toward the targeted pathway.

Globally, the landscape of corporate carbon disclosures (CCD) is continually evolving as societal, environmental and regulatory expectations change over time. The goal of this study is to examine the challenges faced by Indian firms’ corporate carbon reporting (CCR). The literature recognized the hurdles to reaching net zero emissions and decarbonization, which are equally applicable to carbon disclosure (CD).

The scope 3 emission disclosure barriers (S3EDBs) identified from the literature were ranked, and their relationships were discovered using the “Grey-based decision-making trial and evaluation laboratory” (Grey- DEMATEL) technique.

The key findings are the S3EDBs, the most prominent barriers, their interrelationships and important insights for managers of organizations in prioritizing the action area for scope 3 CD. Eight S3EDBs were categorized in terms of cause and effect, threshold value is calculated as 0.78. “Quality, and reliability of data,” “Government policies and statutory requirement on emission disclosure” and “Traceability and managing supply chain partners” are the most prominent S3EDBs.

The results will help industry people in countries with emerging economies that have significant scope 3 carbon footprints. The managers can plan to deal with top S3EDBs as a step towards decarbonization and ultimately fighting climate change (CC).

This study is one of the first to rank these barriers to CD so that industry practitioners can prioritize their actions. The core contribution of this research is to detect the most significant S3EDBs and their interdependencies.

The purpose of this study is to examine the application of sustainable building design and operation within a university setting to determine its economic efficacy and potential for further university investment.

This study incorporated a life cycle cost analysis (LCCA), simple payback period and discounted payback period calculations to determine the return on investment, including a sensitivity analysis when comparing the energy use and financial benefits of the sustainable design of a multi-use facility at Toronto Metropolitan University with buildings of similar size and use-type.

It was found that there is a positive business argument for Canadian Universities to consider the use of sustainable design to reduce energy use and greenhouse gas (GHG) emissions. A reasonable payback period and net present value within an institutional context were determined using a life-cycle cost assessment approach.

This study was limited to the measure of only a single location. Certain assumptions regarding energy pricing and interest rates and the related sensitivities were anchored on a single year of time, and the results of this study may be subject to change should those prices or rates become significantly different over time. Considerations for future research include a longitudinal approach combined with a more detailed analysis of the effect of use-type on the variables discussed.

For university administrators, the results of this study may encourage institutions such as universities to approach new building projects through the lens of energy efficiency and environmental sustainability.

GHG emissions are a well-proven contributor to global climate change, and buildings remain a significant source of GHG emissions in Canada due to their winter heating and summer cooling loads. As a result, sustainable building design on university campuses can mitigate this impact by optimizing and reducing energy consumption.

Research related to the economic evaluation of sustainable building design on university campuses is generally limited, and this study represents the first of its kind in regard to an LCCA of a sustainably designed building on a Canadian University campus.

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.

Due to their limited capacity for adaptation and dependence on natural resources for economic growth, developing countries (DCs) tend to be more prone to climate change. It is argued that climate finance (CF) is a significant financial innovation to mitigate the negative effects of climate variation. However, the heterogeneous impacts of CF on environmental sustainability (ES) and social welfare (SW) have been masked. Thus, this study aims to investigate the heterogeneous effects of CF on ES and SW in 80 CF receipt DCs from 2002 to 2018. This study also aims to investigate the effects of CF on ES and SW based on population size, income heterogeneity and the type of CF.

The method of moments quantile regression (MMQR) with fixed effects is utilized. Alternatively, the fully modified least square (FMOLS) and dynamic least square (DOLS) estimators are used for the robustness test.

The findings revealed that DCs with the lowest and middle quantiles of EF, carbon dioxide (CO₂) emissions and human development exhibit large beneficial impacts of CF on ES and SW. In contrast, the positive effects of CF on ES breakdown for countries with the largest distributions of EF and CO₂ emissions. Besides, the impacts of CF on ES and SW depend on income heterogeneity, population size and the type of CF.

This study calls for a framework to integrate CF into all economic development decisions to strengthen climate-resilient SW and ES in DCs.

To the best of the authors’ knowledge, this is the first study to investigate the effects of CF on ES and SW in a wide range of DCs. Thus, it complements existing related literature focusing on the effects of CF on ES and SW.

Modular capacity units enable rapid reconfiguration, providing tactical flexibility to efficiently meet customer demand during disruptions and ensuring sustainability. Moreover, the Physical Internet (PI) enhances the potential of modular capacity in addressing efficiency, sustainability, and resilience challenges. To evaluate the sustainability and resilience advantages of the PI-enabled reconfigurable modular system (PI-M system), this paper studies a PI-enabled sustainable and resilient production-routing problem with modular capacity.

We develop a multi-objective optimization model to assess the sustainability and resilience benefits of combining PI and modular capacity in a chemical industry case study. A hybrid solution approach, combining the augmented e-constraint method, construction heuristic, and hybrid adaptive large neighborhood search, is developed.

The experimental results reveal that the proposed solution approach is capable of obtaining better solutions than the Gurobi and the existing heuristic in a shorter running time. Moreover, compared with the traditional system, the PI only and traditional with modular capacity systems, PI-M system has significant advantages in both sustainability and resilience.

To the best of our knowledge, this study is the first to integrate the PI and modular capacity and investigate sustainability and resilience in the production-routing problem.