1.1. Background
Lifecycle assessment (LCA) has been proved the principal method used for evaluating different solid waste management systems (SWMS), presenting an important input to decision making processes (Allesch and Brunner, 2014). One of the commonly mentioned strengths of LCA is is the fact of being a holistic approach, including many different types of environmental impacts in the assessment. Indeed, according to the ISO standards and the ILCD Handbook (2011) recommendations, all relevant impact categories should be included in the performance of LCA (ISO, 2006; European Commission, 2010). It is essential to consider global and local impacts simultaneously for a total environmental management to genuinely balance impacts reduction rather than just shifting problems (Kobayashi et al., 2015). Even so, recent reviews have also shown that most SWMS LCAs focus on a small number of environmental impact categories (Laurent et al., 2014). While this might facilitate the interpretation of the results, it also creates a risk of excluding relevant aspects from the assessment and increases the risk of missing relevant trade-offs. On the other hand, the inclusion of a larger number of impact categories in the study increases risks of conflicting results, i.e. one alternative can be preferable in relation to some aspects, while another is preferable in relation to others.
With the aim of achieving more comprehensive environmental management, this problem has been approached by several authors for example through hybridisation of LCA and qualitive risk assessment (QRA) (Kobayashi et al., 2015) or through integration of risk-related geographical information system (GIS) data (Gasol et al., 2011).
While results from an LCA can facilitate understanding of the benefits and drawbacks of each alternative, determining the best alternative might be difficult. In addition, the best alternative might look different from different perspectives, i.e. depending on which environmental impacts are regarded as most relevant. Thus, further combinations of LCA with methods for decision-aiding are commonly sought.
In decision-aiding, Multi-criteria Decision Analysis (MCDA) is a relevant approach. It provides the possibility of combining the analysis of diversified indicators/impact categories in a common framework. This helps organizing available information and identifying pros and cons in the decision process, namely through outputs aggregation (Matteson, 2014; Valle and Clímaco, 2015, Recchia et al., 2011). MCDA has previously been used in several studies for decision aiding taking into account alternatives for solid waste management (SWM) (Garfi et al., 2009; Karagiannidis and Perkoulidis et al., 2009; Yap and Nixon, 2015; Ângelo et al., 2017).
Such studies are commonly applied when current management of solid waste is challenged through new legislation, meaning that several alternatives must be considered. The Brazilian National Solid Waste Policy from 2010 aimed at eradicating dumps until 2014 (Brasil, 2010). However, in 2014, more than 45% of all MSW was still disposed of in open dumpsites (IPEA, 2014). A transfer from illegal dumps to sanitary landfills is the process which is focused in the national plan, but the plan opens the possibilities for technological leapfrogging and introduction of more advanced waste-to-energy and material recovery technologies. The environmental changes due to such strategies could be investigated through the use of the consequential lifecycle assessment (CLCA) methodology. CLCA being change-oriented, it quantifies the effects associated with changes in the life cycle of a system brought about by decisions regarding introduction of these strategies (Weidema 2000; Curran et al. 2005). In this way, the consequential approach seeks to take the environmental assessment a step further, to analyse how environmental burdens may vary in response to changes with market implications, where processes are linked via market mechanisms beyond the foreground system (Vazquez-Rowe et al., 2013). Such linkages can occur when waste is used for energy or material recovery. Recovery implies that waste-based resources are released on the market, with the effect of substituting other product-systems, which, in CLCA, is modelled through system expansion and identification of affected technologies (Finnveden et al., 2009). Several studies have also been performed in recent years, using a consequential framework for Life Cycle Inventory (LCI) modelling of waste management systems (Boesch et al., 2014; Sevigné-Itoiz et al., 2015; Tonini and Astrup; 2012; Cimpan et al., 2014; Hamelin, 2013).
In the last decade, several fruitful studies appeared in the scientific literature combining classical LCA studies with MCDA techniques in order to evaluate consequences of alternative choices (Clímaco and Valle, 2016, Rechia et al., 2011, Yap and Nixon, 2015 and Ângelo et al., 2017). So, it seems reasonable to apply a consequential LCA approach together with MCDA techniques. However as far as we know, this is one of the first integrations between MCDA and CLCA in SWM.