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Measuring the recycling potential of industrial waste for long-term sustainability

AbstractIndustrial waste is the byproduct of many industrial processes. Estimating the recycling potential of industrial waste can help solve the anthropogenic circularity conundrum. Here we employed the Environmental Kuznets Curve (EKC) to verify GDP as a route to "amplified resource efficiency". The results provide substantial evidence for an inverted U and N relationship between the hypothesized GDPPC and industrial waste generation. During 2011–2025, the recycling potential in China showed a downward trend. China is projected to experience a dramatic increase in the production of industrial hazardous waste until the successful implementation of industrial hazardous waste prevention measures reverses the current trends. The turning point of the EKC between industrial waste generation and economic development is around US$8000, while the comprehensive utilization is 102.22 million tons. The EKC inflection points established by the study are correlated with the waste category’s turning point. The revised EKC claims that technological change may accelerate the turning points; thus, the graph shifts downward and right. The study recommends investing in new technology development to help the industry produce virgin and recycled industrial waste for a circular economy. Recycling potential evaluation also assists us to achieve our Sustainable Development Goals (SDGs).
- Tsinghua University China (People's Republic of)
- State Key Joint Laboratory of Environment Simulation and Pollution Control China (People's Republic of)
H, AZ20-999, Social Sciences, History of scholarship and learning. The humanities
H, AZ20-999, Social Sciences, History of scholarship and learning. The humanities
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).3 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
