Use of Monte Carlo Analysis in Life Cycle Assessment: Case Study – Fruits Processing Plant in Ghana

Introduction Life-cycle studies range from highly detailed and quantitative assessments that characterize, and sometimes assess the environmental impacts of energy use, raw material use, wastes and emissions over all life stages, to assessments that qualitatively identify and prioritize the types of impacts that might occur over a life cycle. ii. Objectives The study is to improve the understanding of the environmental impact of fruit processing in a global context and to suggest improvements at the most important environmental hotspots. It is also to effectively reflect the environmental burdens arising from fruit processing industries, and to make precise alternatives often encountered in environmental decisions iii. Methodology The methodology is proposed to systematically analyze the uncertainties involved in the entire procedure of Life Cycle Assessment (LCA) for pineapple fruit processing at the fruit processing plant. The methodology also explores the degree of uncertainty of various impact categories. The Monte Carlo simulation is used to analyze the uncertainties associated with Life Cycle Inventory (LCI), Life Cycle Impact Assessment (LCIA), and the normalization and weighting processes. The uncertainty of the environmental performance for individual impact categories is also calculated and compared. iv iv. Results and Discussion The study investigated the impact of access to electricity from 100% diesel-electric generating set, 100% national grid, and hybrid (94% of national grid electricity and 6% of diesel-electric generating set) on the environment by fruit processing plant. Their respective impacts were compared using Monte Carlo simulations. The impact on the environment in the use of only electricity from the national grid source or from diesel-electric generating set as well as a combination (hybrid) of the two, to establish optimum model that would minimize environmental burden were also investigated. The use of Poly-Ethylene Terephthalate (PET) containers in packing different weights of sliced pineapple and then packaging (different quantities of PET containers with sliced pineapple) in cardboard packaging boxes as part of the processes at the fruit processing plant and its consequential impact on the environment is also examined to ascertain environmental load of these processes. Outcome of the Monte Carlo simulation runs in systematic comparison of the different models of electricity sources suggests that the use of 100% of diesel-electric generating set to provide electricity in production of sliced pineapple at the fruit processing plant has highest impact on human health and ecosystem quality damage categories. There is a significant difference in impact on human health by the use of diesel-electric generating set. Sourcing of electricity solely from the national grid has the highest impact on resources in the damage category. The use of electricity from hybrid source generates the least total environmental load. v v. Conclusion The processing plant must source 85.6% of its electricity from national grid and, sliced pineapple must be packed at 300 g net weight in PET containers and then 5 of that packaged in a cardboard packaging box as the optimized conditions to minimize climate change at 1.08537E-07 DALY. It would achieve minimum ozone layer impact value of 8.78226E-11 DALY at the optimized conditions of 295 g net weight of sliced pineapple in PET containers and then, 5 of that packaged in a cardboard packaging box. The electricity from the national grid source should be 87.3%. The minimum impact on ecotoxicity under optimal conditions was determined as 0.097831954 PDF*m2yr. The minimum ecotoxicity could be achieved under the optimal conditions of packaging sliced pineapple in 203 g net weight units and then pack 8 of such PET containers in a cardboard box, and 85.2% electricity is sourced from national gird.

Source: KNUST