## 4 Applications and Societal Importance  
Fecal ash derived from the treatment of human wastes has a minimal environmental impact, and it could be an effective solution for the management of solid wastes. Simultaneously, studies reveal that fecal ash can also serve varied applications in treatment plants and as a consumer-grade product. Primarily, fecal ash can be used as an excellent adsorbent material owing to its tendency to trap moisture and other types of soil nutrients. Although the adsorption capacity is not on par with other carbonaceous materials such as activated carbon--fecal ash compensates for this lack in performance by being a \"green\" adsorbent. [PERSON] et al., 2020 [48], conducted a study to recover phosphorous from human urine using solid waste ash. The study deemed fecal ash as an effective solution to adsorb phosphorous from wastewater streams.  
Fecal ash can also be used for soil remediation--used ash contains moisture and soil nutrients embedded in it. This can be added to plantation fields as a fertilizer and will serve as a viable method of closing nutrient loops in an ecosystem. Hence, it can be a cost-effective and eco-friendly alternative to chemical fertilizers. Other benefits may include a considerable reduction in solid waste disposal cost, which can significantly lower the operational cost of a sewage plant. Produced ash can be valorized and serve tertiary applications instead of ending up in landfills.  
Despite all the potential applications of fecal ash, this ubiquitous resource continues to be flushed out every day. Aside from societal perception, this oversight practice can be primarily accredited to the lack of reliable data that can be used to quantify and assess this resource as a commercial-grade product. Hence, there is an acute necessity to set up a uniform database of information that producers and traders can refer to. Lastly, there is a shortage in literature for comprehensive multi-variable optimization studies that can accurately assess the produced ash by taking numerous process parameters and variables  
Figure 3: Levenberg–Marquardt back-propagation neural network (LMBNN) for urea adsorption. (**a**) Neural network overview; (**b**) training performance; (**c**) variation in gradient, training gain (mu) and validation fail for epoch range 0 to 5; (**d**) error histograms with 20 bins; (**e**) response of output element; (**f**) results of curve fitting with variation in target; (**g**) autocorrelation of error with variation of lag.  
into consideration. Such a study will also help predict and classify the ash produced according to their most suitable application.  
The lack of proper sanitation facilities is a prevalent issue in several countries to date. Although most nations are actively ensuring appropriate sanitation facilities, the solid waste collected from these establishments is not adequately managed. This study plays its part by offering a viable eco-friendly solution to the question of solid waste management  
Simultaneously, proper treatment of such biowastes mitigates the spread of diseases and allows an increased number of sanitation facilities. This also uplifts the living standards of the general population and puts a stop to the practice of open defecation. Hence, the study lays a foundation to rehabilitate and remediate different sectors of our society.