The Ecocentric and Anthropocentric Attitudes toward the Sustainable Development (EAATSD) scale measures environmental concern in relation to sustainable development. This article will discuss how this scale was tested with three groups of Dutch higher education students. Findings demonstrate that anthropocentric and ecocentric values are independent of the students’ chosen course of study, suggesting that students attracted by the ‘sustainable development’ course title do not necessarily associate ‘sustainability’ with ecocentric aims. This article discusses why ecocentric values are beneficial to the objective of a sustainable society and proposes ways forward in which these values can be enhanced in learners. https://doi.org/10.3390/educsci7030069 https://www.linkedin.com/in/helenkopnina/
MULTIFILE
The hospitality industry contributes significantly to global climate change through its high resource consumption and emissions due to travel. As public pressure for hotels to develop sustainability initiatives to mitigate their footprint grows, a lack of understanding of green behavior and consumption of hotel guests hinders the adoption of effective programs. Most tourism research thus far has focused on the ecotourism segment, rather than the general population of travelers, and while research in consumer behavior shows that locus of control (LOC) and guilt can influence guests’ environmental behavior, those factors have not been tested with consideration of the subjective norm to measure their interaction and effect on recycling behavior. This study first examines the importance of internal and external LOC on factors for selecting hotel accommodation and the extent of agreement about hotel practices and, second, examines the differences in recycling behavior among guests with internal versus external LOC under levels of positive versus negative subjective norms and feelings of low versus high guilt.
MULTIFILE
This chapter addresses environmental education as an important subject of anthropological inquiry and demonstrates how ethnographic research can contribute to our understanding of environmental learning both in formal and informal settings. Anthropology of environmental education is rich in ethnographies of indigenous knowledge of plants and animals, as well as emotional and religious engagement with nature passed on through generations. Aside from these ethnographies of informal environmental education, anthropological studies can offer a critical reflection on the formal practice of education, especially as it is linked to development in non-Western countries. Ethnographic and critical studies of environmental education will be discussed as one of the most challenging directions of environmental anthropology of the future. This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in "Environmental Anthropology: Future Directions" on 7/18/13 available online: https://doi.org/10.4324/9780203403341 LinkedIn: https://www.linkedin.com/in/helenkopnina/
MULTIFILE
The production of denim makes a significant contribution to the environmental impact of the textile industry. The use of mechanically recycled fibers is proven to lower this environmental impact. MUD jeans produce denim using a mixture of virgin and mechanically recycled fibers and has the goal to produce denim with 100% post-consumer textile by 2020. However, denim fabric with 100% mechanically recycled fibers has insufficient mechanical properties. The goal of this project is to investigate the possibilities to increase the content of recycled post-consumer textile fibers in denim products using innovative recycling process technologies.
The increasing amount of electronic waste (e-waste) urgently requires the use of innovative solutions within the circular economy models in this industry. Sorting of e-waste in a proper manner are essential for the recovery of valuable materials and minimizing environmental problems. The conventional e-waste sorting models are time-consuming processes, which involve laborious manual classification of complex and diverse electronic components. Moreover, the sector is lacking in skilled labor, thus making automation in sorting procedures is an urgent necessity. The project “AdapSort: Adaptive AI for Sorting E-Waste” aims to develop an adaptable AI-based system for optimal and efficient e-waste sorting. The project combines deep learning object detection algorithms with open-world vision-language models to enable adaptive AI models that incorporate operator feedback as part of a continuous learning process. The project initiates with problem analysis, including use case definition, requirement specification, and collection of labeled image data. AI models will be trained and deployed on edge devices for real-time sorting and scalability. Then, the feasibility of developing adaptive AI models that capture the state-of-the-art open-world vision-language models will be investigated. The human-in-the-loop learning is an important feature of this phase, wherein the user is enabled to provide ongoing feedback about how to refine the model further. An interface will be constructed to enable human intervention to facilitate real-time improvement of classification accuracy and sorting of different items. Finally, the project will deliver a proof of concept for the AI-based sorter, validated through selected use cases in collaboration with industrial partners. By integrating AI with human feedback, this project aims to facilitate e-waste management and serve as a foundation for larger projects.
Currently, many novel innovative materials and manufacturing methods are developed in order to help businesses for improving their performance, developing new products, and also implement more sustainability into their current processes. For this purpose, additive manufacturing (AM) technology has been very successful in the fabrication of complex shape products, that cannot be manufactured by conventional approaches, and also using novel high-performance materials with more sustainable aspects. The application of bioplastics and biopolymers is growing fast in the 3D printing industry. Since they are good alternatives to petrochemical products that have negative impacts on environments, therefore, many research studies have been exploring and developing new biopolymers and 3D printing techniques for the fabrication of fully biobased products. In particular, 3D printing of smart biopolymers has attracted much attention due to the specific functionalities of the fabricated products. They have a unique ability to recover their original shape from a significant plastic deformation when a particular stimulus, like temperature, is applied. Therefore, the application of smart biopolymers in the 3D printing process gives an additional dimension (time) to this technology, called four-dimensional (4D) printing, and it highlights the promise for further development of 4D printing in the design and fabrication of smart structures and products. This performance in combination with specific complex designs, such as sandwich structures, allows the production of for example impact-resistant, stress-absorber panels, lightweight products for sporting goods, automotive, or many other applications. In this study, an experimental approach will be applied to fabricate a suitable biopolymer with a shape memory behavior and also investigate the impact of design and operational parameters on the functionality of 4D printed sandwich structures, especially, stress absorption rate and shape recovery behavior.
Lectoraat, onderdeel van HAS green academy
Lectoraat, onderdeel van NHL Stenden Hogeschool
