# A Neural Network Model for Decision-Making with Application in Sewage Sludge Management
## 1 Introduction  
Climate change is a global crisis that has forced a more sustainable development of resources planning, analyses, and policymaking regarding the valorization of the limited resources on earth. The sustainability of industrial activities has now become crucial for many firms [1]. To this concern, increased awareness concerning greenhouse gas (GHG) emissions evaluation, mainly carbon dioxide (CO\({}_{2}\)), methane (CH\({}_{4}\)), and nitrous oxide (N\({}_{2}\)O), was observed in recent years. In this context, the wastewater (WW) sector plays a crucial role in identifying needs, barriers, and new strategies to face the future's expected challenges [2]. According to [PERSON] et al., the emissions due to the WWT are the sixth largest contributors to methane (CH\({}_{4}\)) emissions and the third largest sources of nitrous oxide (N\({}_{2}\)O) emissions, respectively [3]. Meanwhile, the management of the SS generated from WWT is one of the most controversial issues of modern cities. If, on the one hand, the new advanced WWT available on the market and the forced implementation of the European Directive 91/271/EC ensure a higher quality of the effluent treated, then, on the other hand, the amount of the SS produced in the process is significantly increasing. Recent studies showed that, in the last fifteen years, the EU-12 annual production of the SS increased by almost 50%, from 9.8 million tons in 2005 to over 13 million tons in 2020. The lack of continuity among official reports and the relevant lack of data for the new Member States further complicate the study of this topic [4]. The \"Green Impact\" was introduced to indicate all activities aiming at measuring and minimizing the negative effects on the environment [5]; traditionally, SS has been disposed of in landfills without prior treatment. The consequent impact on the environment of this waste and the uncontrolled generation of pollution dangerous to human health led theauthorities to adopt a sustainable growth policy. To address these problems, the European Union has set the target to reduce the final waste disposal by 35% in 2016 (compared to 2000) in all Member States (EU Directive 99/31). Therefore, in recent years, the interest and request for new and more efficient SS management methods have exponentially increased. According to [PERSON] et al., the traditional water value chain should be rethought, rethinking how to use resources to create a sustainable economy, which is \"free\" of waste and emissions [6]. In other words, the authors consider as not sustainable a linear approach on the WWT, where the SS is considered waste. The authors, on the contrary, promote a \"circular approach\" (Figure 1), where the SSs produced are resources for agriculture, pharmaceutical and personal care products, renewable energy production, and co-firing as construction materials. In this scenario, promoting sustainability as operational strategy is considered a winwin strategy [7]. Therefore, the choice regarding the SS treatments, made in the context of a wastewater treatment plant (WWTP), has a significant impact. On the one hand, this choice must be consistent with the objective of environmental sustainability and rethinking of the wastewater value chain in a circular perspective, and, on the other hand, it must be economically sustainable. It is estimated, indeed, that the costs associated with the processing and the management of SS constitute 50% of the annual operating costs of a WWTP [8]. Making a choice that is consistent with these two aspects, however, is highly complex. According to [PERSON] et al., indeed, SS decision problems can be defined as \"wicked\" problems, i.e., problems involving multidisciplinary aspects, such as economic, social, technical, and regulatory aspects, and a large number of stakeholders with often conflicting interests, interacting with each other in a fragmented network that is not clearly defined.