Optimization of pig manure-based digestate biorefinery framework using p-graph

• Main Author: Paulo, Jacob Louies Rohi
• Format: text
• Language: English
• Published: Animo Repository 2024
• Subjects: Renewable energy sources; Biomass energy; Chemical Engineering; Engineering
• Online Access: https://animorepository.dlsu.edu.ph/etdb_chemeng/36; https://animorepository.dlsu.edu.ph/context/etdb_chemeng/article/1034/viewcontent/Optimization_of_pig_manure_based_digestate_biorefinery_framework_copy.pdf
• Institution: De La Salle University

Hog farming is the second largest industry in the Philippines, next to rice cultivation. Waste generation is one of the main challenges of the industry with manure as its main byproduct. Philippines generates hundred million tons of pig manure being the 8th largest pork producer in the world. A manure management framework is necessary to address the problems in line with waste generation. Waste valorization of manure through anaerobic digestion and different digestate treatments to produce electricity, heat, biomethane, biofertilizer, microalgae, and compost were explored. Process graph (P-graph) was employed to determine the potential optimal pathways of processing pig manure by minimizing the production cost and greenhouse gas (GHG) emissions. Environmental impacts of the processes were expressed as global warming potential (GWP) or CO2-equivalent emissions. P-graph is a bipartite graph consisting of nodes (raw material, operating unit, and product) connected using arcs (input and output streams) capable of generating different process configurations. Six feasible solutions (S0-S5) were generated, three of which were profit-generating (S0-S2). The raw material costs were almost equivalent for every solution. S0 was the solution with the most amount of potential profit to be generated along with having the least investment cost. S1 and S2 were the net zero CO2-e processes, however, their investment costs were among the highest. Potential solutions were determined using P-graph that meets a certain criterion with its corresponding trade-off. Selection of the feasible solution would require a contextual approach. The study has shown that the application of P-graph in solving process network synthesis (PNS) problems can aid greatly in decision making process of choosing the perfectly viable solution under different contexts: environmental, social, or economic.