# A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
## 2 Literature Review  
A systematic literature network analysis (SLNA) was adopted to identify the papers to be investigated. All the search terms and their combinations were searched for in the title, abstract, and keywords on Scopus, the largest scientific peer-reviewed literature database. References [9; 10] introduce the keywords used in the literature review. They are split into three subsets:  
* Subset 1: keywords related to SS treatment and its principal sub-processes (e.g., SS, SS management, WWT, WW, etc.). * Subset 2: keywords related to sustainability (e.g., circular economy, green, environment, greenhouse gas, etc.). * Subset 3: keywords related to decision support systems (DSSs) in SS management (e.g., decision theory, decision making, decision support techniques, etc.). The keywords of Subset 1 and Subset 2 were combined with Subset 3 in the title, abstract, or keywords. No public year limitation was used, and all articles published in English were selected from peer-reviewed journals indexed by Scopus; 24 papers were identified. Nine manuscripts were collected, refining the research to consider only papers published from 2014. The authors' keywords analysis of the collected papers allowed us to detect through the co-occurrence network map (Figure 2) the scientific literature pattern covered by available scientific studies. The keywords co-occurrence network map evaluation showed that three clusters in published scientific studies could be identified. The first one is related to SS treatments; the second one is focused on sustainability in WWT, as well as in SS treatments; and the third one investigates the application of DSS to SSs management. In the first cluster, [PERSON] [11] introduced a new drying technology to reduce the pollutants due to heavy metals in SS, allowing for the adoption of the same SS on the agricultural lands as organic fertilizer rather than incineration or landfilling. An innovative centralized SS management of the co-composting process with the purpose to reduce the current economic and technological disadvantages of the individual treatment was presented by [PERSON] [12]; the authors proved the efficiency of the management solution in terms of economically attractive physical-chemical characterization of SS treated, as well as odor emissions. The second cluster identified by the co-occurrence network map is related to sustainability in WWT that SS treatment. An optimization problem solved by using a multi-objective mixed-integer linear program that includes three possible options, namely co-incineration, co-processing, and mono-incineration, was developed for the treatment of the digested SS produced in the Canton of Zurich. The model combining material flow analysis, process models, life cycle assessment (LCA), and mathematical optimization techniques allowed for the improvement of the environmental impact of the selected treatment. The sensitivity analysis results showed a reduction of environmental impact categories considered in the range of 2-6%, with a reduction of the energy consumption of 42% [9]. Life Cycle Assessment (LCA) is a widely used method for evaluating different treatment alternatives, but it is focused on an environmental assessment, without considering other aspects (e.g., economic, technological, etc.). To this concern, [PERSON] et al. developed an LCA to compare the environmental performance of different alternatives for the disposal of the WWT and the SS in a WWTP in Southern Italy. They considered different scenarios with a progressively circular pattern, starting from the as-is scenario of the WWTP considered, and observed, as expected, that the greater the circularity of the strategy adopted, the lower the impact in different categories, such as the Global Warming Potential, Freshwater Eutrophication Potential, and Human Toxicity Potential [13]. In Reference [14], the LCA methodology was applied to identify the most environmentally sustainable way to dispose of SS between fluidized bed incineration and a cement kiln employing SS as a secondary fuel.