Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/89970
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Title: A system dynamics model for evaluating food waste management in Hong Kong, China
Authors: Lee, CKM 
Ng, KKH 
Kwong, CK 
Tay, ST 
Issue Date: May-2019
Source: Journal of material cycles and waste management, 1 May 2019, v. 21, no. 3, p. 433-456
Abstract: Of landfilled municipal solid waste in Hong Kong, 33.2% is attributed to food waste. The government has set a waste reduction target to reduce by 40% the current food waste disposal at landfills by 2022 and has launched various policies and strategies to achieve this target. The Hong Kong Government is eager to control the utilisation level of food waste through various policies and the food waste conversion by a newly adopted Organic Waste Treatment Facility. In this study, the current landfill situation and the effectiveness of food waste policies are investigated using a system dynamics approach to study the dynamics and interrelationships in food waste management. The model is used to forecast the effectiveness of the food waste management in different scenarios. Among these scenarios, adopting Organic Waste Treatment Facility and implementing a quantity–volume-based charging scheme are examined. Although improvements are expected to be made after implementing these policies when compared to the current trends, the model output indicates that without any other new policy or action plan, it is difficult to achieve the objectives set by the government. Suggestions are made so as to improve the effectiveness of food waste management in the future.
Keywords: Food waste management
Simulation
STELLA
System dynamics modelling
Publisher: Springer
Journal: Journal of material cycles and waste management 
ISSN: 1438-4957
EISSN: 1611-8227
DOI: 10.1007/s10163-018-0804-8
Rights: © Springer Japan KK, part of Springer Nature 2018
This is a post-peer-review, pre-copyedit version of an article published in Journal of Material Cycles and Waste Management. The final authenticated version is available online at: https://doi.org/10.1007/s10163-018-0804-8.
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