Kinetic Modeling of Co-Pyrogasification in Municipal Solid Waste (MSW) Management: Towards Sustainable Resource Recovery and Energy Generation

Anabel Fernandez, Daniela Zalazar-García, Carla Lorenzo-Doncel, Diego Mauricio Yepes Maya, Electo Eduardo Silva Lora, Rosa Rodriguez and Germán Mazza ()
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Anabel Fernandez: Instituto de Ingeniería Química, Facultad de Ingeniería, Universidad Nacional de San Juan, Grupo Vinculado al PROBIEN (CONICET-UNCo), Av. Libertador San Martín (Oeste) 1109, San Juan J5400ARL, Argentina
Daniela Zalazar-García: Instituto de Ingeniería Química, Facultad de Ingeniería, Universidad Nacional de San Juan, Grupo Vinculado al PROBIEN (CONICET-UNCo), Av. Libertador San Martín (Oeste) 1109, San Juan J5400ARL, Argentina
Carla Lorenzo-Doncel: Departamento de Ingeniería Química, Facultad de Ingeniería, Universidad Nacional de San Juan, Av. Libertador San Martín (Oeste) 1109, San Juan J5400ARL, Argentina
Diego Mauricio Yepes Maya: Núcleo de Excelência em Geração Termelétrica e Distribuída (NEST), Instituto de Engenharia Mecânica, Universidade Federal de Itajubá, Av. BPS 1303, Itajubá 37500-903, MG, Brazil
Electo Eduardo Silva Lora: Instituto de Engenharia Mecânica, Universidade Federal de Itajubá, Av. BPS 1303, Itajubá 37500-903, MG, Brazil
Rosa Rodriguez: Instituto de Ingeniería Química, Facultad de Ingeniería, Universidad Nacional de San Juan, Grupo Vinculado al PROBIEN (CONICET-UNCo), Av. Libertador San Martín (Oeste) 1109, San Juan J5400ARL, Argentina
Germán Mazza: Instituto de Investigación y Desarrollo en Ingeniería de Procesos, Biotecnología y Energías Alternativas, PROBIEN (CONICET-Universidad Nacional del Comahue), Calle Buenos Aires 1400, Neuquén Q8300IBX, Argentina

Sustainability, 2024, vol. 16, issue 10, 1-19

Abstract: This study addresses the co-pyrogasification of municipal solid waste (MSW) from the Environmental Technology Park, San Juan, Argentina. This process involves heating waste at high temperatures in a low-oxygen or oxygen-free atmosphere as a sustainable strategy for waste management and energy generation. The principal objective is to focus on understanding the MSW co-pyrogasification kinetics to enhance performance in reactor design. A representative sample of MSW collected over a month was analyzed, focusing on the variation in mass proportions of plastic, organic matter, and paper. The empirical methodology included the deconvolution of macro-TGA curves and deep learning algorithms to predict and validate macro-TG data during co-pyrogasification. The findings reveal that MSW is a solid matrix more easily treated on thermochemical platforms, with kinetic and thermodynamic parameters favoring its processing. This approach suggests that MSW co-pyrogasification may represent a feasible alternative for resource recovery and bioenergy production, supporting the policies for the transition to a cleaner future and a circular economy.

Keywords: waste management; ANN model; synergistic effects; deconvolution method (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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