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Sustainability of a bio-waste treatment plant: Impact evolution resulting from technological improvements
The aim of this work is to evaluate how the environmental impacts of the Romagna Compost composting plant (central Italy) have changed as a consequence of its expansion and adaptation. This led to a considerable evolution of the plant, from a traditional composting process to an integrated anaerobic...
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Published in: | Journal of cleaner production 2018-01, Vol.171, p.1006-1019 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The aim of this work is to evaluate how the environmental impacts of the Romagna Compost composting plant (central Italy) have changed as a consequence of its expansion and adaptation. This led to a considerable evolution of the plant, from a traditional composting process to an integrated anaerobic-aerobic system. For this purpose, the Life Cycle Assessment (LCA) methodology was chosen. Inventory analysis was completed using mostly primary data supplied by the company. Plant performances were evaluated for each year of operation and by grouping data to analyze the main stages (storage and pretreatment of the organic waste, anaerobic fermentation, composting, etc.). The modelling was performed using SimaPro software and the ReCiPe analysis method. Seven scenarios were created to simulate the seven-year process. The aim of the study was to assess whether and how the introduction of anaerobic fermenters to produce energy from biowastes has led to a real improvement of the process sustainability with an overall decrease in environmental impacts. After analyzing in detail the performances of the plant, biowaste transportation and the avoided landfill disposal were also assessed. The main problems connected with transportation, and environmental benefits resulting from the avoided disposal of waste, were identified and in order to evaluate the robustness of the model, a sensitivity analysis using the Monte Carlo method was performed. |
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ISSN: | 0959-6526 1879-1786 |
DOI: | 10.1016/j.jclepro.2017.10.082 |