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Service area size assessment for evaluating the spatial scale of solid waste recovery chains: A territorial
Audrey Tanguy1, Jonathan Villot2, Mathias Glaus3
1Station Expérimentale des Procédés Pilotes en Environnement (STEPPE), Ecole de Technologie Supérieure, 1100 Notre-Dame West, Montreal, QC, Quebec H3C 1K3, Canada; UdL, UMR CNRS 5600 EVS, Ecole des Mines de Saint-Etienne, I. Fayol, 158 cours Fauriel, Saint-Etienne F42023, France.
Abstract:
Waste recovery is an integrated part of municipal solid waste management systems but its strategic planning is still challenging. In particular, the service area size of facilities is a sensitive issue since its calculation depends on various factors related to treatment technologies (output products) and territorial features (sources waste production and location). This work presents a systemic approach for the estimation of a chain's service area size, based on a balance between costs and recovery profits. The model assigns a recovery performance value to each source, which can be positive, neutral or negative. If it is positive, the source should be included in the facility's service area. Applied to the case of Montreal for food waste recovery by anaerobic digestion, the approach showed that at most 23 out of the 30 districts should be included in the service area, depending on the indicator, which represents around 127,000 t of waste recovered/year. Due to the systemic approach, these districts were not necessarily the closest to the facility. Moreover, for the Montreal case, changing the facility's location did not have a great influence on the optimal service area size, showing that the distance to the facility was not a decisive factor at this scale. However, replacing anaerobic digestion by a composting plant reduced the break-even transport distances and, thus, the number of sources worth collecting (around 68,500 t/year). In this way, the methodology, applied to different management strategies, gave a sense of the spatial dynamics involved in the recovery chain's design. The map of optimal supply obtained could be used to further analyse the feasibility of multi-site and/or multi-technology systems for the territory considered.
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