Environmental impact assessment of chicken meat production via an integrated methodology based on LCA, simulation and genetic algorithms - López-Andrés, Jhony Josué; Aguilar-Lasserre, Alberto Alfonso; Morales-Mendoza, Luis Fernando; Azzaro-Pantel, Catherine; Pérez-Gallardo, Jorge Raúl; Rico-Contreras, José Octavio (Journal of cleaner production, 2018)
This study performed a Life Cycle Assessment (LCA) to evaluate the environmental impact of chicken meat production from a Mexican case study, with a “cradle-to-slaughterhouse gate” approach. To overcome the LCA's limitations and provide a more holistic picture of the system, simulation and artificial intelligence techniques were integrated. First, raw material/energy requirements were obtained from the case study and simulated using Process simulation (PS) and Monte Carlo (MC) simulation to estimate the emissions and quantify their uncertainty. Then, IMPACT 2002 + was used to calculate the overall impact using Ecoinvent and LCA Food databases. The results highlight that chicken farms are the main factors responsible for the environmental impacts assessed, where feed production (use of chemicals and energy requirements) and on-farm emissions (organic waste decomposition) are the main contributors. Concerning the slaughterhouse, the energy production (electricity and steam) and the cooling-related activities present a significant impact. Afterwards, three impact allocation procedures (mass method, neural networks, and stepwise regression) were tested, showing similar results. Finally, a multiobjective optimization model based on a Genetic Algorithm was applied looking to minimize the environmental impacts and maximize the economic benefits. The selected alternative achieved a reduction of 15.14% per functional unit at the environmental indicators. The results encourage the use of support techniques for LCA to perform a reliable assessment and an environmental/economic optimization of the system. [Display omitted] •An integrated methodology based on LCA is applied on a Mexican chicken meat system.•Variability and uncertainty are propagated into LCA results by simulation.•Importance (%) of each core product is determined by three allocation techniques.•An improvement of the system performance is possible using genetic algorithms.•The proposed techniques helps LCA to provide a more holistic picture of the system.