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Circularity in Practice: Review of Main Current Approaches and Strategic Propositions for an Efficient Circular Economy of Materials. SUSTAINABILITY 2022. [DOI: 10.3390/su14020962] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
This paper aims to summarize, propose, and discuss existing or emerging strategies to shift towards a circular economy of materials. To clarify the landscape of existing circular practices, a new spectrum is proposed, from product-based strategies, where entire products go through several life cycles without being reprocessed, to material-based approaches, extracting, recycling, and reprocessing materials from the waste flow. As refillable packaging does not lose any functionality or value, when re-used through many life cycles, product-based strategies are globally extremely efficient and must be promoted. It appears however that their implementation is only possible at the scale of individual products such as packaging containers, relying on the cooperation of involved companies and consumers. It appears more and more urgent to focus as well on a more systematic and flexible material-oriented scheme. The example of circular glass recycling is a success in many countries, and technologies become nowadays available to extend such practices to many other materials, such as rigid plastics. An ideal would be to aim at an economy of materials that would imitate the continuous material cycle of the biosphere. Technological and business strategies are presented and discussed, aiming at a relevant impact on circularity.
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Abstract
An innovative route for plastics recycling is proposed, based on a combination of a logarithmic sorting process and colour plus high-resolution near-infrared (NIR) sensors. Although counterintuitive, it is shown that such a technology could sort clean flakes from rigid packaging waste into a very large number of different plastic grades with modest sorter capacity, provided that the chosen sensor is able to differentiate correctly between any two grades of plastics in the waste. Tests with high-resolution NIR on single pixels of transparent flakes from different types and brands of packaging show that this is indeed the case for a selection of 20 different packaging items bought from shops. Moreover, the results seem to indicate, in line with previous research, that high-resolution NIR data can be linked to important physical plastic properties like the melt flow viscosity and tensile strength. The attraction of deep sorting of waste plastics with relatively cheap sensors and modest sorter capacity is that the present industrial practice of tuning plastic grades to specific applications could coexist with commercial high-grade recycling at high levels of circularity and low carbon footprint. Therefore, advanced recycling technology is likely to be a societal alternative to phasing out plastics for rigid applications.
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Ukil A, Bernasconi J. Neural Network-Based Active Learning in Multivariate Calibration. ACTA ACUST UNITED AC 2012. [DOI: 10.1109/tsmcc.2012.2220963] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Gosselin R, Rodrigue D, Duchesne C. On-line prediction of crystallinity spatial distribution across polymer films using NIR spectral imaging and chemometrics methods. CAN J CHEM ENG 2008. [DOI: 10.1002/cjce.20098] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Ryan Gosselin
- Department of Chemical Engineering, Université Laval, Quebec City, Canada G1K 7P4
| | - Denis Rodrigue
- Department of Chemical Engineering, Université Laval, Quebec City, Canada G1K 7P4
| | - Carl Duchesne
- Department of Chemical Engineering, Université Laval, Quebec City, Canada G1K 7P4
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