4.7 Article

An investigation of the environmental sustainability of palm biomass supply chains via dynamic simulation modeling: A case of Malaysia

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 237, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.117740

Keywords

Biomass supply chain (BSC); Environmental aspect; Dynamic model; Palm oil; Sustainability; Malaysia

Funding

  1. RMIT

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With the ever-increasing need for clean and accessible energy sources, biomass has long been considered as a potential prospect. Malaysia is one of the leading suppliers and has the largest palm oil plantation in the world. Therefore, biomass from the palm oil industry appears to be a very promising alternative source of raw materials, including for renewable energy, in Malaysia. However, ensuring the environmental sustainability of the biomass supply chain (BSC) is one of the major challenges faced by the biomass industry. Therefore, this paper aims to assess the effect of changing the efficiency of transportation technology (TT) and production technology (PT) on the environmental sustainability of the palm oil BSC. We developed a dynamic simulation model to explore the greenhouse gas (GHG) emissions for 50 years (2000-2050) for three palm biomass suppliers (Johor, Perak and Pahang) in Malaysia. Results show that supplier in Perak produced the highest rate of GHG emissions in the whole system. Also, suppliers in Johor and Perak had the highest GHG emissions with 180-240 million tonnes (mt) CO2 equivalent (CO(2)e) and 375-400 mt CO(2)e, respectively, from transportation of empty fruit bunches (EFB) product. In terms of production, the supplier in Perak had the highest (and constant value) of GHG emissions (up to 160 mt CO(2)e). The analysis shows that the supplier in Pahang generated the lowest level of GHG emissions. Our findings suggest that improvement of the transportation and production efficiency of BSC should be the priority to work towards the sustainable development of the palm biomass industry. (C) 2019 Elsevier Ltd. All rights reserved.

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