2030 Palm Oil Plantation Carbon Footprint Estimation using O-LCA and Forecasting

碳足迹 棕榈油 足迹 估计 环境科学 棕榈 农业工程 工程类 温室气体 农林复合经营 地理 生态学 物理 考古 系统工程 量子力学 生物
作者
Farizal Farizal,Trisha Amanda,M. Dachyar,Zainura Zainon Noor
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:463: 142646-142646
标识
DOI:10.1016/j.jclepro.2024.142646
摘要

Since palm oil products have a crucial role in society development, palm oil business in Indonesia has grown significantly over the past few decades. However, this industry is frequently linked to environmental issues, particularly its potential emission of greenhouse gases (GHGs). This study attempts to estimate the carbon footprint of a palm oil company's operation for the year of 2030. In doing so, a novel methodology that consists of organisational lifecycle assessment (O-LCA), simple linear regression (SLR), and double exponential smoothing (DES) methods is proposed. O-LCA is used to identify the sources of emission and estimate the amount of the emission generated, while SLR and DES are used to forecast the sources. As the result, the carbon footprint in 2030 is estimated to be 62,758,433 kg Carbon Dioxide equivalent (CO2eq) where on average a ton of crude palm oil (CPO) produces 1.08 ton CO2eq. The study also discloses that the three largest emission sources are palm oil mill effluent (POME), fertilizer, and transportation. The forecasting methods used are quite accurate with mean absolute percentage error (MAPE) of less than 10%. The results of this study can shed a light to help Indonesia achieving its target to reduce GHG emission by 2030.

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