| Title | The Cycle rate as the means for real-time monitoring of wastes in circular economy |
|---|---|
| ID_Doc | 4373 |
| Authors | Tsiliyannis, CA |
| Title | The Cycle rate as the means for real-time monitoring of wastes in circular economy |
| Year | 2019 |
| Published | |
| Abstract | The EC circular economy waste directive sets ambitious recycling and reuse targets towards waste reduction and banning of landfills. Monitoring of wastes can lead to efficient policies and implementation of proactive measures for waste reduction. Up-to-date methods for waste monitoring in cyclic economy (CE) may not provide reliable and useful figures. Product stock-in-use and flows in CE, including waste flows, are uncertain due to varying demand and imports/exports, random, early losses of stock-in use, delayed and distributed product returns or end-of-life exit and varying utilization of returns by remanufacturers. Adopting a systems perspective and using a dynamic/stochastic model of stock and flows in CE, this work quantifies waste monitoring and reduction under realistic conditions. It reveals how consumption and stock depletion consist the driving forces of waste generation, compensated by cyclic actions, reuse/remanufacturing and recycle. The conventional recycling rate and other key parameters, including the reuse rate, the mean lifetime, the remanufacturing rate, the number of reuse cycles, are shown inapt to accurately monitor end-wastes. None can consistently distinguish the environmentally superior system or state, featuring lower end-wastes. Higher recycling rates and/or higher reuse rates may not ensure lower wastes. Asymmetric policies (differing recycle and reuse rates) can be advantageous: higher reuse is preferable under rising stock and higher recycle under stock depletion. Sharp real-time monitoring of end-wastes is provided by the cycle rate, a dimensionless rate accounting for consumption and stock variations in CE. Its supreme efficacy is demonstrated in a robust Case study (US cellular phones) via Markov-Chain-Monte-Carlo simulation. (C) 2019 Elsevier Ltd. All rights reserved. |
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