507306 research-article2013
WMR311210.1177/0734242X13507306Waste Management & ResearchRojo et al.
Original Article
Dynamic waste management (DWM): Towards an evolutionary decision-making approach
Waste Management & Research 31(12) 1285–1292 © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0734242X13507306 wmr.sagepub.com
Gabriel Rojo1, Mathias Glaus1, Robert Hausler1, Valérie Laforest2 and Jacques Bourgeois2
Abstract 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 (∆H) 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 (∆H) 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. Keywords Waste management, decision-making tool, model simulation, systemic approach, integrated management, law of conservation of energy
Introduction Waste management should not aim solely to reduce the volume of waste heading to incineration or landfills (Barton et al., 2008), but must also optimize social acceptability, economic gain and environmental compatibility, while promoting a sustainable and fair society (Ghinea et al., 2012; Morrissey and Browne, 2004; Pires et al., 2011). Moreover, one of the main issues associated with sustainable waste management lies in the ability of decision-making tools to combine the notions of systemic approach and of minimization of the impacts in a global and dynamic fashion (Ishii et al., 2010; Woolridge et al., 2005). In this context, the DWM approach lies in the balancing of the global network (multiple treatment processes and interrelated networks) rather than on a unilateral process ranking, which can lead to erroneous, and even inadequate, decision-making because of its linearity (Kirkeby et al., 2006; Schmidt et al., 2007). The DWM approach thus aims to consider the variations in the generated waste volumes and in the demands from the different treatment processes in order to meet deciders’ expectations (Eskandari et al., 2012; Gautam and Kumar, 2005). However, the treatment processes must be considered with respect to their impacts not only on the environment, as in the life-cycle analysis (Liamsanguan
and Gheewala, 2008; Winkler and Bilitewski, 2007), but also on the social and economic aspects. Moreover, DWM considers transport as a main component of the network, knowing that the load is directly influenced by the impacts associated with transport (Bovea et al., 2007; Eisted et al., 2009; Salhofer et al., 2007), such as the means of transport chosen, the distance traveled and the road type. To meet these challenges, this article presents the dynamic waste management (DWM) approach, which combines the notions of network distribution and conservation of energy, based on an analogy with hydraulic networks. To demonstrate the potential of DWM, the bases of the approach will be explained, and will then be followed by a case study.
1Station
Expérimentale des Procédés Pilotes en Environnement (STEPPE), Ecole de Technologie Supérieure, Montréal, Canada 2Institut Henri Fayol, Département PIESO, Ecole Nationale Supérieure de Mines de Saint-Etienne, Saint-Etienne, France Corresponding author: Mathias Glaus, Ecole de Technologie Superieure, 1100 Notre-Dame West, Montreal, QC Quebec H3C 1K3, Canada. Email: [email protected]
Downloaded from wmr.sagepub.com at NORTH DAKOTA STATE UNIV LIB on June 3, 2015
1286
Waste Management & Research 31(12)
Methodology: DWM Basic concepts In addition to the evolution of waste treatment processes and means of transport, the quantities of available waste (generated or in reserve) vary constantly. This type of network is similar to a water distribution network (Figure 1), where varying volumes of water enter the system (QIN), and are redistributed or stored (reserve R with capacity CR) according to demand (QOUT,i). Thus, the reserve serves as a buffer, allowing water accumulation when QIN>∑QOUT and meeting demand when QIN
WMR311210.1177/0734242X13507306Waste Management & ResearchRojo et al.
Original Article
Dynamic waste management (DWM): Towards an evolutionary decision-making approach
Waste Management & Research 31(12) 1285–1292 © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0734242X13507306 wmr.sagepub.com
Gabriel Rojo1, Mathias Glaus1, Robert Hausler1, Valérie Laforest2 and Jacques Bourgeois2
Abstract 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 (∆H) 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 (∆H) 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. Keywords Waste management, decision-making tool, model simulation, systemic approach, integrated management, law of conservation of energy
Introduction Waste management should not aim solely to reduce the volume of waste heading to incineration or landfills (Barton et al., 2008), but must also optimize social acceptability, economic gain and environmental compatibility, while promoting a sustainable and fair society (Ghinea et al., 2012; Morrissey and Browne, 2004; Pires et al., 2011). Moreover, one of the main issues associated with sustainable waste management lies in the ability of decision-making tools to combine the notions of systemic approach and of minimization of the impacts in a global and dynamic fashion (Ishii et al., 2010; Woolridge et al., 2005). In this context, the DWM approach lies in the balancing of the global network (multiple treatment processes and interrelated networks) rather than on a unilateral process ranking, which can lead to erroneous, and even inadequate, decision-making because of its linearity (Kirkeby et al., 2006; Schmidt et al., 2007). The DWM approach thus aims to consider the variations in the generated waste volumes and in the demands from the different treatment processes in order to meet deciders’ expectations (Eskandari et al., 2012; Gautam and Kumar, 2005). However, the treatment processes must be considered with respect to their impacts not only on the environment, as in the life-cycle analysis (Liamsanguan
and Gheewala, 2008; Winkler and Bilitewski, 2007), but also on the social and economic aspects. Moreover, DWM considers transport as a main component of the network, knowing that the load is directly influenced by the impacts associated with transport (Bovea et al., 2007; Eisted et al., 2009; Salhofer et al., 2007), such as the means of transport chosen, the distance traveled and the road type. To meet these challenges, this article presents the dynamic waste management (DWM) approach, which combines the notions of network distribution and conservation of energy, based on an analogy with hydraulic networks. To demonstrate the potential of DWM, the bases of the approach will be explained, and will then be followed by a case study.
1Station
Expérimentale des Procédés Pilotes en Environnement (STEPPE), Ecole de Technologie Supérieure, Montréal, Canada 2Institut Henri Fayol, Département PIESO, Ecole Nationale Supérieure de Mines de Saint-Etienne, Saint-Etienne, France Corresponding author: Mathias Glaus, Ecole de Technologie Superieure, 1100 Notre-Dame West, Montreal, QC Quebec H3C 1K3, Canada. Email: [email protected]
Downloaded from wmr.sagepub.com at NORTH DAKOTA STATE UNIV LIB on June 3, 2015
1286
Waste Management & Research 31(12)
Methodology: DWM Basic concepts In addition to the evolution of waste treatment processes and means of transport, the quantities of available waste (generated or in reserve) vary constantly. This type of network is similar to a water distribution network (Figure 1), where varying volumes of water enter the system (QIN), and are redistributed or stored (reserve R with capacity CR) according to demand (QOUT,i). Thus, the reserve serves as a buffer, allowing water accumulation when QIN>∑QOUT and meeting demand when QIN
