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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.

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 paper aims to analyze the influences of context and methodological differences in how universities confront, report and manage carbon neutrality in selected Andean universities, contrasted with a university in the USA.

A sequential, mixed-methods design, using quantitative and qualitative approaches was applied. The data analysis is based on a systematic literature review with bibliometric analysis to identify how carbon neutrality in universities is understood and applied. Informed by the quantitative analysis, the qualitative phase compared the assessment methodologies, opportunities and obstacles in three Andean universities – EAFIT in Colombia, EPN in Ecuador and the UC in Chile – contrasted with MIT (USA) for comparative purposes beyond the region.

The bibliometric analysis points to the evolution of carbon management and carbon neutrality in universities and indicates how universities have applied methodologies and defined opportunities and obstacles. In this comparative experience, the contextual issues are brought to the fore. The conclusions highlight the importance of context in carbon neutrality assessment and argue against crude comparative metrics. While carbon assessment protocols provide data on which actions may be taken, the phase of carbon management development and the specifics of context – based on local institutional, geographical, climatic, cultural, socioeconomic and national policy conditions – are far more relevant for identifying actions.

This study only considered four universities, and the findings are not generalizable. The argument highlights the point that contextual factors generate important differences that may complicate simple comparisons based on the university's type or size. It also highlights the differences in the carbon calculation methodologies used by the institutions.

Results build on the recent publications that document the Latin American context. The article contributes to knowledge about Andean university commitments and actions relating to climate change and carbon neutrality. This knowledge can contribute to how universities in the region seek to apply different methodologies, set targets and the timing of actions and consider their contextual opportunities and obstacles.

Comparing university carbon footprints and carbon neutrality plans is an emerging topic, presenting methodological and institutional difficulties. This paper reveals some of these difficulties by comparing parameters, actions and implementation processes against contextual factors. While there is a drive for international and national comparisons and systematization of data on university carbon performance, significant methodological gaps still need to be resolved to account for these contextual factors.

While urban farming is advocated as a contributor to urban sustainability and resilience, the “informal” household-practiced urban agriculture activities are taking place within urban spaces in most Emirati neighbourhoods but unfortunately without investigating their potential as participatory processes that could efficiently help attain urban sustainability and resilience on the neighbourhood level. So, this research is a humble attempt to bridge the gap of the lack of official recognition of informal residents-led processes and their products in a way that help understand them and their impacts and to explore the possibility of developing them further into wider community shared urban agriculture activities.

The research adopted the case study method and selected a representative neighbourhood to investigate informal residents-led urban agriculture practices. The utilized qualitative–quantitative investigation tools included map analysis, field observation and in-depth interviews with the residents of the selected neighbourhood.

The results of the research have revealed that the residents managed to successfully pursue informal urban farming processes that have led to significant environmental, social and economic sustainability and resilience outcomes. While these informal urban farming activities are performed individually by each household, the interviewed residents have shown enthusiasm to take part in larger-scale collective community urban farming activities, especially in the deserted public and semi-public spaces in their neighbourhood.

The research outcomes significantly contribute to the growing worldwide discourse about urban agriculture/farming, especially in a country like the UAE where such activities are almost overlooked. Based on its findings, the research concludes by proposing a set of recommended actions to legitimatize these informal urban agriculture processes in the urban development regulations and to build on them to encourage the local communities towards more collective urban farming activities.

Infill materials play a pivotal role in determining buildings’ life cycle costing (LCC) and environmental impacts. International standards prescribe LCC and life cycle assessments (LCA) to assess materials’ economic and environmental sustainability. The existing methods of LCC and LCA are tedious and time-consuming, reducing their practical application. This study sought to integrate LCC and LCA with building information modeling (BIM) to develop a swift and efficient approach for evaluating the life cycle performance of infill materials.

The BIM model for a case study was prepared using Autodesk Revit®, and the study included four infill materials (lightweight aggregate concrete block (LECA), autoclaved cellular concrete (AAC), concrete masonry and bricks). LCC was conducted using Revit® and Autodesk Insight 360® to estimate costs incurred across different project phases. LCA was conducted using “One Click LCA®,” a BIM-based platform featuring a comprehensive material inventory. Carbon emissions, acidification, and eutrophication were chosen as environmental impact factors for LCA.

LECA was the preferred choice due to its lower cost and environmental impact. Its lifetime cost of $440,618 was 5.4% lower than bricks’, with 2.8% lower CO₂ emissions than AAC’s, which were second-place options, respectively. LECA had 6.4 and 27% lower costs than concrete blocks, and AAC’s carbon emissions were 32 and 58% lower than concrete blocks and bricks, respectively.

BIM has been employed for life cycle analysis in existing literature, but its efficacy in evaluating the lifetime costs and environmental impacts of infill materials remains unexplored. The current study presents a BIM-based approach for conducting LCC and LCA of infill materials, facilitating informed decision-making during the planning phase and promoting sustainable construction practices.

This study aims to assess carbon emissions in urban aged residential buildings in Qingdao, Shandong Province, constructed prior to 2000, and to evaluate retrofitting and rebuilding strategies for potential carbon reduction.

Field investigations and literature reviews were conducted to identify key factors influencing carbon emissions, such as shape coefficient, window-to-wall ratio and envelope structure. A combination of generalization and mathematical statistical methods was used to classify buildings based on construction year, form, structural type and energy-saving goals. Cluster analysis was employed to extract six typical building models.

Results demonstrate that building form complexity positively correlates with carbon emissions per unit area, while longer lifespans reduce emission intensity. Retrofitting exhibits shorter carbon payback periods (1.62–3.92 years) than rebuilding (18.7–49.94 years), indicating superior environmental performance. Pre-1986 buildings are advised for demolition/rebuilding due to limited retrofit benefits. For 1986–1995 buildings, retrofitting is recommended if structurally viable. Post-1996 buildings favor retrofitting over new construction for its shorter payback and lower emissions, enhancing long-term carbon reduction.

This study contributes to the understanding of carbon emissions in urban aged residential buildings by considering various factors and providing specific recommendations for retrofitting and rebuilding strategies tailored to different construction periods. Additionally, it highlights the importance of building form complexity and remaining lifespan in determining carbon emissions, offering insights for sustainable urban development and carbon reduction initiatives.

In 2022 generative AI took the Internet world by storm. Free access to tools that can generate text and images that pass for human creations triggered fiery debates about the potential uses and misuses of generative AI in education. There has risen a need to check the popular utopian and dystopian narratives about AI against the diversity of hopes, concerns and future imaginaries that educators themselves associate with generative AI. The purpose of this study is to investigate the perspectives of Finnish teacher educators on the use of AI in education.

This article reports findings from a hands-on workshop in teacher training, where participants learned about how generative AI works, collaboratively explored generative AI and then reflected on its potential and challenges.

The results reveal nuanced, calm and thoughtful imaginaries rooted in deep understanding of educational policy, evaluation and the sociocultural context of education. The results cover teachers’ views on the impact of AI on learners’ agency, metacognition, self-regulation and more.

This article offers a unique exploration into the perceptions and imaginaries of educators regarding generative AI in specific (instead of “monolithic AI”), moving beyond dystopian views and instead focusing on the potential of AI to align with existing pedagogical practices. The educators contrasted the common techno-deterministic narratives and perceived AI as an avenue to support formative assessment practices and development of metacognition, self-regulation, responsibility and well-being. The novel insights also include the need for AI education that critically incorporates social and ethical viewpoints and fosters visions for a future with culturally, socially and environmentally sustainable AI.

This study is carried out to demonstrate the computational practicalities of environmental construction economics necessary to offer early-stage cost advice. A case study of a private sector client’s development proposal is used. This is for the acquisition of a vacant freehold land of 1.2 acres brownfield site to develop a Grade A office complex with plans to achieve the BREEAM Excellent rating green building certification.

A three-stage methodology was deployed: Order of cost estimating, before life cycle costing and then development appraisal. The Order of Cost Estimate is generated using the BCIS online database, following the procedural guideline of the New Rules Measurement (NRM). The life cycle costing was carried out from an environmental perspective to explore two design options – Design A and Design B, in terms of which would offer the best value for money whilst reducing carbon emissions.

Based on the outcome of the life cycle costing computations, Design B was chosen as the advised development due to minimal differences in net present values and annual equivalents. Further evaluation of Design B, using the residual method of developmental appraisal was carried out, with all necessary assumptions made. From the extensive computations carried out, the project is considered unviable, as it reports a loss. Alternative use of the site or an alternative site is thus recommended to check if a greater return on investment is tenable.

The study narratively interweaves the application of three computational techniques that are core to offering early-stage cost advice.

The purpose of this paper that will address in this paper are: how to implement and test a reliable Block-chain-based energy system for the EU energy payments and logistic? What are the main results, impacts and implications of a Block-chain-based energy system for the EU energy payments and logistic?

The main aim of this study is to propose a Block-chain-based method to offer a secure, reliable and transparent method for energy logistic and payments for European Energy Transactions. To accomplish that aim, the research method of the study follows the design science research approach of smart contracts in the EU Energy logistic and payments. This research approach mainly consists of five sequential steps which are (1) problem and motivation identification, (2) solution objectives definition, (3) design and development and (4) demonstration and evaluation.

Results of data model demonstrate that the Block-chain-based energy system here can be used for any EU energy payments and logistics. Based on the data results of the model that mentioned above enhance the security and the integrity of the energy payments and logistic by using cryptographic techniques and consensus mechanisms to prevent and detect any tampering or falsification of the data on the Block-chain.

This paper represents a genuine piece of research that contributes to the field by providing new insights and understanding. The findings presented are the result of rigorous analysis and have not been previously published or submitted elsewhere for consideration.

Corporate social responsibility (CSR) has gained tremendous importance after several corporate scandals, financial crises and the rise of the hyper-competitive world. Firms must address multiple stakeholders’ interests to increase firm value. This study aims to investigate the effect of CSR on firm value. This study also examines the mediating role of enterprise risk management (ERM) and the moderating influence of corporate governance (CG) in this CSR-firm value relationship.

The sample of the study comprises 119 Pakistan Stock Exchange (PSX) listed firms and the study covers the period from 2010 to 2021. The corporate social responsibility performance has been quantified across five dimensions. These aspects are product, environment, employee relations, diversity and community. Four proxies i.e. strategy, operation, reporting and compliance, have been used to measure ERM. The governance quality of the sample companies was evaluated using the governance index, which included 29 governance provisions. The authors used the dynamic panel data technique (system-GMM) is used to achieve the objectives of the study. Furthermore, a firm’s engagement in CSR activities can also be measured through a multinational financial approach to check the robustness of the result.

Based on the regression analysis, the authors discovered that CSR was positively connected with firm value, validating the stakeholder view of CSR. Furthermore, following Baron and Kenny’s (1986) mediation technique, the findings confirm that ERM mediates this association. These results are robust by using the bootstrapping tests by Preacher and Hayes (2004). Furthermore, the result shows that corporate governance (CG) is positively connected with firm performance, and this relationship is strengthened in the presence of an effective governance system in the organization.

This study provides useful insights to regulators, investors and policymakers to consider CSR as a value-enhancing factor and encourage the development of enterprise risk management and compliance with CG mechanisms to improve firm value.

The presented analysis strengthens the existing CSR–firm value relationship by analyzing the mediating and moderating roles of ERM and CG, which have not yet been tested, particularly in the context of Pakistan.