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The increasing volume of electronic waste (e-waste) creates significant environmental and economic challenges which demands practical management strategies. Life Cycle Assessment (LCA) has been known as a principal tool for evaluating the environmental impact of e-waste recycling and disposal methods. However, its application is hampered by inconsistencies in methodology, data limitations, and variations in system boundaries. This study provides a review of current LCA tools used in e-waste analysis and identifies gaps and opportunities for improvement. It categorizes studies into three groups: studies that applied LCA to product and process optimization, impact evaluation, and policy development. Findings reveal that LCA has been helpful in assessing the sustainability of different recycling strategies. However, significant variations exist in methodological approaches and data accuracy. Challenges such as the lack of standardized LCA protocols, the limited availability of regionspecific impact data, and inconsistencies in assessment methodologies are still barriers to its widespread adoption. Finally, the study discusses emerging trends in LCA aimed at addressing current gaps, including the incorporation of machine learning and artificial intelligence for predictive modeling, dynamic impact assessment frameworks, and the role of real-time data collection via IoT-based sensors.
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Electronic Waste, an Environmental Problem Exported to Developing Countries: The GOOD, the BAD and the UGLY
Electronic waste (e-waste) is a rapidly developing environmental problem particularly for the most developed countries. There are technological solutions for processing it, but these are costly, and the cheaper option for most developed countries has been to export most of the waste to less developed countries. There are various laws and policies for regulating the processing of e-waste at different governance scales such as the international Basel Convention, the regional Bamoko Convention, and various national laws. However, many of the regulations are not fully implemented and there is substantial financial pressure to maintain the jobs created for processing e-waste. Mexico, Brazil, Ghana Nigeria, India, and China have been selected for a more detailed study of the transboundary movements of e-waste. This includes a systematic review of existing literature, the application of the Driver, Pressure, State, Impact, Response (DPSIR) framework for analysing complex problems associated with social ecological systems, and the application of the Life Cycle Assessment (LCA) for evaluating the environmental impact of electronic devices from their manufacture through to their final disposal. Japan, Italy, Switzerland, and Norway have been selected for the LCA to show how e-waste is diverted to developing countries, as there is not sufficient data available for the assessment from the selected developing countries. GOOD, BAD and UGLY outcomes have been identified from this study: the GOOD is the creation of jobs and the use of e-waste as a source of raw materials; the BAD is the exacerbation of the already poor environmental conditions in developing countries; the UGLY is the negative impact on the health of workers processing e-waste due to a wide range of toxic components in this waste. There are a number of management options that are available to reduce the impact of the BAD and the UGLY, such as adopting the concept of a circular economy, urban mining, reducing loopholes and improving existing policies and regulations, as well as reducing the disparity in income between the top and bottom of the management hierarchy for e-waste disposal. The overarching message is a request for developed countries to help developing countries in the fight against e-waste, rather than exporting their environmental problems to these poorer regions.
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- Award ID(s):
- 1840868
- PAR ID:
- 10280247
- Date Published:
- Journal Name:
- Sustainability
- Volume:
- 13
- Issue:
- 9
- ISSN:
- 2071-1050
- Page Range / eLocation ID:
- 5302
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/su13095302
