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Articles by Nik Meriam Nik Sulaiman
Total Records ( 2 ) for Nik Meriam Nik Sulaiman
  Vijaya Subramaniam , Ma An Ngan , Choo Yuen May and Nik Meriam Nik Sulaiman
  Malaysia is currently the world leader in the production and export of palm oil. This study has a gate to gate system boundary. The inventory data collection starts at the oil palm fresh fruit bunch hoppers when the fresh fruit bunch is received at the mill up till the production of the crude palm oil in the storage tanks at the mill. The plantation phase and land use for the production of oil palm fresh fruit bunch is not included in this system boundary. This gate to gate case study of 12 mills identifies the potential impacts associated with the production of palm oil using the life cycle assessment approach and evaluates opportunities to overcome the potential impacts. Most of the impact categories show savings rather than impact. Within the system boundary there are only two main parameters that are causing the potential impacts to the environment; they are the Palm Oil Mill Effluent (POME) followed by the boiler ash. The impact categories that the POME contributes to are under the Respiratory Organics and Climate Change. Both these impact categories are related to air emissions. The main air emission from the POME ponds during the anaerobic digestion is the biogas which consists of methane, carbon dioxide and traces of hydrogen sulfide. An alternate scenario was conducted to see how the impact will be if the biogas was harvested and used as energy and the results shows that when the biogas is harvested, the impact from the POME is removed. The other significant impact is the boiler ash. This is the ash that is produced when the biomass is burnt in the boiler. This potential impact contributes to the ecotoxicity impact category. This is mainly because of the disposal of this ash which in most cases was used for land application in the roads leading to the mil or in the plantations. If the parameters causing these two potential impacts are curbed, then this will be a further plus point for the Malaysian oil palm industry which is already avoiding fossil fuel based energy and chemical use for processing.
  Saeid Baroutian , Mohamed Kheireddine Aroua , Abdul Aziz Abdul Raman and Nik Meriam Nik Sulaiman
  In this study, a new approach based on Artificial Neural Networks (ANNs) has been designed to estimate the density of pure palm oil-based methyl ester biodiesel. The experimental density data measured at various temperatures from 14 to 90°C at 1°C intervals were used to train the networks. The present research, applied a three layer back propagation neural network with seven neurons in the hidden layer. The results from the network are in good agreement with the measured data and the average absolute percent deviation is 0.29%. The results of ANNs have also been compared with the results of empirical and theoretical estimations.
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