BiomiMETRIC Assistance Tool: A Quantitative Performance Tool for Biomimetic Design.

This article presents BiomiMETRIC, a quantitative performance tool for biomimetic design. This tool is developed as a complement to the standard ISO 18458 Biomimetics-terminology, concepts, and methodology to quantitatively evaluate the biomimetics performance of a design, a project, or a product. BiomiMETRIC is aimed to assist designers, architects, and engineers to facilitate the use of the biomimetic approach beyond the existing frameworks, and to provide an answer to the following question: How can a quantitative evaluation of biomimetic performance be carried out? The biomimetic quantitative performance tool provides a method of quantitative analysis by combining the biomimetic approach with the impact assessment methods used in life-cycle analysis. Biomimetic design is divided into eight steps. The seventh step deals with performance assessment, verifying that the concept developed is consistent with the 10 sustainable ecosystem principles proposed by the Biomimicry Institute. In the application of the biomimetic quantitative performance tool, stone wool and cork are compared as insulation materials used in biomimetic architecture projects to illustrate the relevance and added value of the tool. Although it is bio-based, cork has a lower biomimetic performance according to the indicators used by the biomimetic quantitative performance tool presented in this article.

Service area size assessment for evaluating the spatial scale of solid waste recovery chains: A territorial perspective.

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.

A spatial analysis of hierarchical waste transport structures under growing demand.

The design of waste management systems rarely accounts for the spatio-temporal evolution of the demand. However, recent studies suggest that this evolution affects the planning of waste management activities like the choice and location of treatment facilities. As a result, the transport structure could also be affected by these changes. The objective of this paper is to study the influence of the spatio-temporal evolution of the demand on the strategic planning of a waste transport structure. More particularly this study aims at evaluating the effect of varying spatial parameters on the economic performance of hierarchical structures (with one transfer station). To this end, three consecutive generations of three different spatial distributions were tested for hierarchical and non-hierarchical transport structures based on costs minimization. Results showed that a hierarchical structure is economically viable for large and clustered spatial distributions. The distance parameter was decisive but the loading ratio of trucks and the formation of clusters of sources also impacted the attractiveness of the transfer station. Thus the territories' morphology should influence strategies as regards to the installation of transfer stations. The use of spatial-explicit tools such as the transport model presented in this work that take into account the territory's evolution are needed to help waste managers in the strategic planning of waste transport structures.

Dynamic waste management (DWM): towards an evolutionary decision-making approach.

To guarantee sustainable and dynamic waste management, the dynamic waste management approach (DWM) suggests an evolutionary new approach that maintains a constant flow towards the most favourable waste treatment processes (facilities) within a system. To that end, DWM is based on the law of conservation of energy, which allows the balancing of a network, while considering the constraints of incoming (h1 ) and outgoing (h2 ) loads, as well as the distribution network (ΔH) characteristics. The developed approach lies on the identification of the prioritization index (PI) for waste generators (analogy to h1 ), a global allocation index for each of the treatment processes (analogy to h2 ) and the linear index load loss (ΔH) associated with waste transport. To demonstrate the scope of DWM, we outline this approach, and then present an example of its application. The case study shows that the variable monthly waste from the three considered sources is dynamically distributed in priority to the more favourable processes. Moreover, the reserve (stock) helps temporarily store waste in order to ease the global load of the network and favour a constant feeding of the treatment processes. The DWM approach serves as a decision-making tool by evaluating new waste treatment processes, as well as their location and new means of transport for waste.