Environmental Objectives Research Articles

First, ‘things’ first: prioritizing environmental goods tariff reductions at the WTO

Abstract Negotiations to liberalize trade in environmental goods are a key indicator for the World Trade Organization’s (WTO) capacity to pursue climate and environmental objectives. Experience with Environmental Goods Agreement negotiations within the WTO demonstrates the necessity to establish obligations and/or procedures that link environment and trade law as the WTO pursues a sustainability agenda.

Carbon Emissions and Sustainable Supply Chains: A Stackelberg Game Analysis of Multinational Firm Relationships

Against the backdrop of global climate change and sustainable development, carbon emissions within transnational closed-loop supply chains have become a critical area of research. This paper utilizes a Stackelberg game model to analyze the relationship between a single export manufacturer and an import retailer. The study investigates the optimal solutions of the supply chain model—wholesale price, retail price, sales volume, and profit—across three consumer preference scenarios: no obvious preference, pure green preference, and pure new preference. Furthermore, this paper examines the impact of carbon emissions per unit of product on supply chain decision-making under two scenarios: with and without carbon trading. Carbon trading, which significantly increases unit costs, exerts a profound influence on the strategic decisions of both manufacturers and retailers. In addition, this paper incorporates carbon tariffs and taxes into its analysis, providing a theoretical foundation for governments and policymakers to promote sustainable production and consumption practices. The validity of the model is confirmed through numerical simulations, which reveal that under pure green and pure new preference scenarios, original equipment manufacturers (OEMs) are more inclined to invest in emissions reduction to minimize tariff costs. In contrast, under no obvious preference scenarios, OEMs are more likely to adjust product portfolios to evade carbon tariffs. This research advances the understanding of low-carbon production strategies in transnational supply chains, offering both theoretical insights and practical guidance for balancing economic and environmental objectives.

Luminescent Tactile Sensor System for Robots: Enhancing Human-Computer Interaction in Complex Dark Environments.

In order to achieve interaction and collaboration with humans, robots need to have the ability for tactile perception of simulating human. Traditional methods use electrically connected sensors with complex arrays, leading to intricate wiring, high manufacturing costs, and demanding current environments. A flexible sensor with simple structure, easy preparation process, and low cost based on triboluminescence effect is proposed in this paper, which avoids the complex array and wiring of traditional sensors. The study discusses the relationship between luminescent intensity and factors such as luminescent particle content, luminescent layer thickness, encapsulation layer thickness, and friction layer thickness. It also analyzes the mechanism of luminescence. A micro charge-coupled device is configured for the luminescent unit to collect optical information and is integrated with the robot's manipulator for testing. A simple sensing system is constructed to demonstrate environmental perception, acquiring, and feeding back shape and size information of contact objects in the dark. The system successfully identifies and judges target objects in complex dark environments, offering insights for applications such as unmanned assembly lines. It overcomes the challenge of intricate electrical connections, paving new avenues for intelligent object recognition research in human-computer interaction.

The importance of education and motivation in the training of HVAC&R professionals in Europe: Lessons from the Portuguese case

The Heating, Ventilation, Air Conditioning, and Refrigeration (HVAC&R) industry is pivotal to Europe’s goals for energy efficiency, sustainability, and technological advancement. As demand for skilled HVAC&R professionals rises, the effectiveness of educational programs in this field has become a focal point. This article explores the Portuguese case to analyze how pedagogical strategies and student motivation contribute to the quality of HVAC&R training across Europe. The study highlights innovative teaching methodologies such as active and competency-based learning, as well as the use of laboratory training and digital simulations to provide hands-on experience. Additionally, it emphasizes Bloom’s Taxonomy as a framework for curriculum development, ensuring that students advance from foundational knowledge to complex problem-solving abilities. Motivation is also identified as a critical factor for student engagement and long-term career commitment. The article concludes that a balanced integration of theoretical knowledge, practical skills, and motivational support is essential for producing highly qualified HVAC&R professionals. This approach not only meets current industry needs but also aligns with Europe’s broader environmental and technological objectives, offering valuable insights for educators, policymakers, and industry stakeholders.

Carbon Footprint, Financial Structure, and Firm Valuation: An Empirical Investigation

This study aims to investigate the complex link between carbon emissions, firm value, and financial choice in regard to the GCC, a dynamic emerging economy. It also seeks to answer the question on whether the financial structure of a firm moderates the correlation between carbon emissions and firm value. We focus on analyzing data from non-financial firms registered on the GCC stock markets between 2010 and 2020. By applying the GLS technique, we assess the impact of carbon emissions on firm value and examine the manner in which a firm’s financial structure either enhances or hinders this relationship. The results demonstrate that there is a strong and adverse connection between carbon emissions and corporate value, as increased emissions translate into lower corporate value. The study then moves on to emphasize the critical role that capital financing plays in mitigating the detrimental effects of carbon emissions. This is accomplished by balancing both debt and equity in terms of their proper proportions (optimal capital structure). However, excessive borrowing could have adverse consequences in terms of carbon emissions on company value. Moreover, the GMM estimator is also applied to carry out a robustness check and the results are consistent with the main findings. This study highlights the significance of financial strategy in advancing sustainability and protecting business value. These findings are supported by both stakeholder and signaling theory, proving that companies can use their capital financing to signal their dedication to sustainability. These results could be used by GCC policymakers to create rules and regulations that encourage environmentally friendly corporate activities and efforts to lower emissions. The research expands the existing literature by examining the difficulties and opportunities faced by GCC firms when combining financial strategy with environmental objectives. It may be necessary to perform additional research in regard to various circumstances and for an extended period, because this study is restricted to non-financial sectors.

A Study on Global Climate Mitigation and National Resource Management Based on the Green GDP Accounting Model

This article investigates the potential of Green GDP (GGDP) to replace conventional GDP as a global economic metric. By accounting for environmental degradation and natural resource depletion—factors typically excluded from traditional GDP calculations—GGDP offers a more comprehensive measure of long-term economic performance. Utilizing a linear regression model, this study examines the relationship between economic activity and climate change, with a focus on carbon emissions and water consumption. The findings reveal an inverse correlation between GGDP and rising global temperatures, suggesting GGDP’s potential to mitigate climate change by integrating the environmental costs of economic growth. A case study of China further illustrates how adopting GGDP could lead to improvements in air quality, more efficient resource management, and alignment with the country’s environmental objectives, including its commitments under the Paris Agreement. Although the transition from GDP to GGDP may face resistance, particularly in nations heavily reliant on fossil fuel consumption and resource exploitation are significant. This study underscores the necessity of incorporating environmental considerations into economic evaluations to foster a sustainable future, where economic growth can be achieved in harmony with ecological preservation. GGDP thus provides a more holistic and sustainable framework for assessing global economic performance.

Orchestrating Digital Resilience: A Clinical IS Study of an Everything-as-a-Service Technology Strategy

ABSTRACT Organisations must build digital resilience to effectively safeguard their business operations against environmental, economic, or socio-political disruptions. One approach involves adaptation – using Information Technology (IT) to design business operations that can withstand and recover from such disruptions. A second approach involves mitigation – using IT to advance environmental, social, or economic objectives that reduce the root causes and likelihood of future disruptions. However, both approaches to building digital resilience are challenging to implement. Our clinical Information Systems (IS) research article examines and reflects on how Beta Bank, an Australian fintech firm, developed an Everything-as-a-Service (EaaS) technology strategy and achieved digital resilience throughout its business operations. We explain how Beta Bank strategically leveraged EaaS to adapt to the significant disruptions caused by the Australian wildfire disaster and the global COVID pandemic of 2019–2021. We then unpack how Beta Bank further leveraged EaaS to enhance its digital resilience via a mitigation approach. Our work delineates a typology of four EaaS pathways for pursuing digital resilience, discusses the scholarly implications of EaaS as a future IS research area, and provides actionable managerial guidance through an EaaS roadmap, a strategic planning tool for those aiming to implement and benefit from this technology strategy.

Introduction to the Special Issue on Extended Intelligence for Cultural Engagement

New curatorial practices have emerged in the last decade to increase the engagement of citizens in cultural heritage, ranging from visitors’ experiential feedback to exhibitions and cultural artifacts, to digitally mediated forms of interaction, such as social media and games. Within this context, citizen curation is proposed as a methodology for eliciting, producing, collecting, interpreting, and archiving people's responses to cultural objects in interactive and immersive environments. This special issue provides a comprehensive exploration of the challenges and opportunities posed by artificial intelligence and interactive technologies for citizen curation by presenting a diverse set of case studies that range from museums to heritage sites.

Navigating labor-market transitions: an eco-social policy toolbox for public employment services

Current societies are heavily reliant on employment as a cornerstone of prosperity, both in terms of individuals’ access to income and social security and to finance welfare states through tax revenues. At the same time, work is often linked to environmentally harmful activities and not necessarily oriented toward meeting human needs. Against this background, work emerges as a key lever for a social-ecological transformation, and public employment services (PES) as key actors in labor-market policy – an area that has largely ignored environmental objectives until now. This article contributes to the small but growing field of research on eco-social labor-market policies by developing a novel set of 15 measures for eco-social labor. These indicators are grouped into six key thematic clusters of action for PES: (1) information and consultancy; (2) eco-social retraining and qualification; (3) sustainable mobility; (4) working time distribution; (5) livelihood provisioning; and (6) ecological eligibility criteria for unemployment benefits. The proposed policy measures are PES-oriented and offer concrete options toward transformation. While the policy toolbox has been developed in the context of Austria, it can also be used as a framework for other countries.

Enhancing camouflaged object detection through contrastive learning and data augmentation techniques

Camouflaged object detection (COD) aims to locate and segment objects that blend into their surroundings, presenting significant challenges due to the high similarity between the objects and their background. This work introduces a novel approach, Contrastive Learning with Augmented Data (CLAD), which enhances COD performance by leveraging contrastive learning and data augmentation. Our method formulates a simplified task by placing camouflaged objects in new environments, creating positive and negative samples for contrast learning. This process strengthens the model’s ability to differentiate camouflaged objects from complex backgrounds. Furthermore, we introduce a concatenated feature enhancement module to integrate and enrich multi-scale features, improving the overall expressive power of the model. Extensive experiments on four benchmark datasets demonstrate that CLAD outperforms state-of-the-art COD methods, and its effectiveness extends to salient object detection tasks, achieving competitive results across multiple metrics.

Estimates of optimal supplies of animal-sourced foods differ by food system goal and socioeconomic context

Reduced consumption of animal-sourced food (ASF) has been recommended for environmental and human health objectives; however, ASF can be important for food security and diet affordability. We explored country-level relationships among various metrics of food supply, socioeconomic context, food security, diet affordability, and agricultural greenhouse gas emissions (GHGe) to characterize how optimal inclusion ranges for ASF vary with socioeconomic factors and food system goals. Data from 2015 to 2022 for 153 countries were sourced to generate Bayesian Networks representing relationships among the studied food system metrics. Networks were used in simulations to characterize optimal ASF inclusion to achieve environmental, food security, or diet affordability goals based on individual country data. Results are most appropriately interpreted in aggregate rather than as representations of specific countries due in large part to data limitations. Across countries simulated, median total ASF inclusion in the food supply to support food security, GHGe, or affordability objectives was 18.2% ± 12.1%, 11.9% ± 6.8%, and 17.6% ± 8.5%, respectively. Joint optimization for these goals resulted in median ASF inclusion of 15.1% ± 7.2%, with notable regional differences. Although ASF increases were supported in most developing regions, decreases were supported in developed countries. The reported SD in optimal ASF inclusion were considerable, and represented between-country variation. Empirical relationships of food categories to goals consistently favored dairy and egg products over meats. These results support previous literature highlighting the environmental intensity of ASF, but also indicate that moderate ASF supplies contribute to multiple food system goals simultaneously.

Financial inclusion and knowledge diffusion for green growth in Sub-Saharan African countries

This article examines the associated and interactive effects of financial inclusion measured through financial inclusion index and knowledge diffusion, measured through research and development (R&D), internet usage, and education, on green growth measured by CO2 emissions intensity due to production, in Sub-Saharan Africa. Based on a sample of 36 countries and data spanning the period from 2004 to 2018, the analysis employs POLS, Newey & West, and Driscoll & Kraay estimation methods. The findings reveal that financial inclusion, R&D, and internet usage exacerbate CO2 emissions intensity from production, thereby hindering green growth. Conversely, education plays a positive role by reducing production-related CO2 emissions and promoting sustainable practices. Education improves green growth, yet knowledge production through R&D deteriorates green growth when interacting with financial inclusion. Similarly, internet usage, when it interacts with financial inclusion, harms green growth. These results indicate that financial inclusion, R&D, and internet usage negatively impact green growth by increasing CO2 intensity related to production. The study recommends better alignment to green financial inclusion, sustainable R&D, and digital policies with environmental sustainability objectives while advocating for the promotion of environmental education to support green growth. To maximize sustainable development benefits, Sub-Saharan African countries need to adjust their development strategies by incorporating greener practices into financial inclusion, R&D, and digital technologies.

Rethinking the Paradigm of Economic Development: A Critical Examination of its Intersection with Sustainable Development Goal 4 – Quality Education

Abstract Quality education is an effective instrument for promoting economic development. It equips individuals with the skills and knowledge necessary to secure improved employment, achieve higher earnings and contribute to the economy. This study critically analyses the relationship between economic development and Sustainable Development Goal 4 (SDG 4) – Quality Education within the context of education for sustainable development. It aims to explore the dearth of traditional economic development paradigms in promoting holistic human well-being and propose alternative approaches that prioritise high-quality education to achieve sustainable development. This study draws on the sustainable development concept articulated and expanded by various scholars in the literature that was reviewed. It further explores the principles of education for sustainable development (ESD) as outlined by UNESCO and analyses various economic frameworks such as the Green Economy, Well-being Economics and Doughnut Economics. As a conceptual study, the researcher reviewed existing literature on economic development, sustainable development and education. The study synthesises findings from various studies to critically analyse the interplay between economic growth and quality education. Furthermore, the findings emphasise the potential of ESD in promoting sustainable development. The analysis reveals that traditional economic development paradigms, which focus heavily on GDP growth, often neglect social equity and environmental sustainability, thereby resulting in a failure to advance holistic human well-being. In contrast, integrating quality education as a core component of development strategies may significantly contribute to the progress towards sustainable development. Education empowers individuals, by equipping the with knowledge and skills, encourages critical thinking and promotes environmental stewardship. As a result, education helps to align economic operations with broader social and environmental objectives. This study emphasises the need for policymakers to embrace holistic and inclusive approaches for economic development that give priority to quality education. Reforms in educational systems are necessary to prioritise critical thinking and sustainability. Additionally, investments should be made in teacher training and interdisciplinary learning. The findings support the need to transition from growth-centric development models that prioritise economic growth to models that consider and balance economic, social and environmental objectives, ensuring a future that is both sustainable and equitable.

Dynamic effects of energy transition on environmental sustainability: Fresh findings from the BRICS+1

The study aims to fill a critical gap in understanding the multifaceted impact of various economic and environmental factors on sustainability within the BRICS+1 nations. Rapid industrialization and urbanization in these BRICS countries have led to significant environmental challenges, necessitating a comprehensive examination of the effectiveness of energy transitions, green patents, urbanization, environmental policies, and economic growth on environmental sustainability. This research specifically examines the impact of the energy transition (ET), green patents (GPT), and environmental policy on environmental sustainability represented by the Load Capacity Factor (LCF) and using the CS-ARDL, PMG-ARDL, and Dumitrescu Hurlin (DH) panel causality techniques. The panel datasets gathered from BRICS +1 nations from 1993 to 2020 indicated a significant statistically direct causal effect from energy transition to environmental sustainability. The outcome also shows that еnеrgy transition adopted by thе BRICS nations arе inadеquatе in addressing environmental sustainability objectives in the long run. Urbanization and the implementation of environmental policies have a negative effect on the LCF. Simultaneously, green patents substantially and favourably influence, ultimately revealing the lack of concern for environmental matters in global technological innovation. Empirical findings indicate that selected BRICS+1 countries should implement various policy measures to enhance environmental sustainability.

Integrating YOLOv7 with FixMatch for Enhancing Vehicle Detection Performance in Mixed Traffic Environments

A major challenge in the development of object detection technology is the significant reliance on large labeled datasets, which requires substantial time and memory for manual annotation—especially in complex, mixed traffic environments with varied vehicle types, congestion levels, and unpredictable motion patterns. This study addresses this issue by integrating the semi-supervised learning technique, FixMatch, into the YOLOv7 object detection model, utilizing 4000 transportation-related datasets. The FixMatch technique enables the model to detect unlabeled objects effectively through strong and weak augmentation methods. In this study, the detected objects in the mixed traffic environment include public transportation, pedicabs, cars, motorcycles, and trucks. This study achieved an impressive 97.5% detection accuracy by leveraging unlabeled data, demonstrating the model's efficiency and effectiveness in identifying vehicles under diverse traffic conditions. Consequently, integrating the FixMatch method into YOLOv7 provides a practical and efficient solution for object detection in situations where collecting labeled data is challenging, such as in dynamic and highly variable traffic environments.

Climate action and social equity: Mitigation strategies and carbon credits

Carbon taxes are a critical tool in global efforts to reduce greenhouse gas emissions, but they often have regressive effects, disproportionately burdening low-income households. This study examines the economic impact of carbon taxes on different income groups, with a focus on the regressive nature of these policies. Low-income households, which typically spend a higher percentage of their income on energy and carbon-intensive goods, are more adversely affected by carbon taxes. This analysis explores potential mitigation strategies, such as rebates, targeted subsidies, and income-based tax adjustments, to offset these regressive effects. Additionally, the study investigates the role of carbon credits in income distribution, analyzing how the allocation and trading of credits can influence social equity. The research also considers the broader implications of carbon taxes and credits on income distribution, highlighting the need for policies that balance environmental objectives with social equity. By examining the intersection of carbon pricing mechanisms and income inequality, this study provides insights into how policymakers can design carbon taxes and credits that minimize regressive impacts while promoting fair and equitable climate action. The findings underscore the importance of integrating social equity considerations into carbon pricing strategies to ensure that climate policies contribute to sustainable and inclusive economic growth.

Voluntary sustainability standards, employee ownership, and the sustainable development goals: can VSS leverage EO to accelerate progress towards the SDGs?

ABSTRACT Employee ownership (EO), broadly defined, refers to business models that distribute power and/or profit more widely than conventional firms. EO aims to foster a more equitable distribution of income and wealth. The Sustainable Development Goals (SDGs) are a set of 17 social, economic, and environmental objectives. In 2015, all 193 United Nations member countries agreed to work towards achieving the SDGs by 2030. This article explores the connection between EO and the SDGs It addresses two questions: 1) Could the benefits of EO support the SDGs, and if so, which specific targets? 2) Is EO promoted by voluntary sustainability standards (VSS), also known as ‘sustainability certifications’ or ‘eco-labels’ (e.g. Fairtrade)? This study suggests that EO has the potential to support the implementation of five SDGs. More specifically, the benefits of EO may catalyse progress towards nine targets, none of which is currently on track for achievement by 2030. This study also finds that only 26% of VSS organisations encourage companies to engage in or support EO. Removing the two VSS that focus specifically on fair trade, this figure falls to 18%. Overall, this article suggests that employee ownership may be an underutilised tool for accelerating progress towards the UN SDGs.

영상처리 기법 기반 겹친 넙치 객체 탐지를 위한 자동 라벨링 방법

Detecting objects in underwater environments is challenging due to factors such as object overlap, noise, and lighting variations. In particular, labeling underwater organisms like Paralichthys olivaceus requires significant time and effort when done manually. To address these challenges, this paper proposes a method to automate the labeling of Paralichthys olivaceus using image processing techniques and to increase the size of the dataset for training. The proposed method applies morphological operations and contour detection to remove noise and accurately extract object boundaries. Additionally, the YOLOv8 model is used to analyze performance variations based on dataset size and training methods. The results demonstrate that expanding the dataset through automated image preprocessing improves object detection performance, even in cases of object overlap, and proves to be more time-efficient compared to manual labeling.

A low earth orbit satellite descent strategy

The object of the article is the method of descending a satellite from low Earth orbit (LEO) at the end of its service lifetime for its disposal. The main problem is to ensure a safe and cost-effective disposal of the satellite while minimizing risks to the environment and other objects in orbit. Based on the method, calculations were made for lowering the orbit and directing the satellite to a remote area of the Earth’s ocean. The calculations included braking pulses, fuel consumption, descent time to the burial orbit, and the time for natural descent before reaching the Earth's surface. The descent process is divided into three stages: active descent using low-thrust engines (LTE), passive descent due to natural braking in the out-of-atmosphere part, and fall through the dense atmosphere. Dependency graphs were provided to illustrate orbit altitude, satellite speed, reentry angle changes, and flight range over time. The findings revealed that combining active orbital maneuvers with passive orbital decay optimizes the deorbiting procedure by minimizing fuel requirements and operational complexity. The proposed strategy ensures the satellite-controlled re-entry and safe disposal, significantly reducing the risks of collisions and environmental impact. The results solved the problem by defining a staged satellite descent process. Duration were computed for active descent with braking impulses for uniform altitude reduction and passive descent due to atmospheric drag. The trajectory and duration of fall in atmosphere. The process ensures controlled re-entry and safe disposal. This method is suitable for satellite operators and space agencies handling LEO missions

Interaction-aware control for robotic vegetation override in off-road environments

Robotic systems tasked with completing off-road economic, military, or humanitarian missions often encounter environmental objects when traversing unstructured terrains. Certain objects (e.g. safety cones) must be avoided to ensure operational integrity, but others (e.g. small vegetation) can be interacted with (e.g. overridden/pushed) safely. Pure object-avoidance assumptions in conventional robotic system navigation policies may lead to inefficient (slow) or overly-cautious (immobilized) traversal behaviors in off-road terrains. To address this gap in system performance, we draw inspiration from existing hybrid dynamic system control literature. We have designed a nonlinear trajectory optimization controller that utilizes vegetation-interaction models as a jump map in the dynamics constraint. In contrast to purely vision-based navigation policies which classify the traversability of obstacles, the allowable subset of objects with which the vehicle can safely interact is now characterized by a data-driven collision model and the existence of a dynamically-feasible trajectory which satisfies the contact constraints. The controller’s capabilities are demonstrated on a full-sized autonomous utility task vehicle where objects including posts and trees of up to 25.4 [mm] and 81.8 [mm] diameter are overridden.