TY - JOUR
T1 - 2030 oil palm plantation carbon footprint estimation using O-LCA and forecasting
AU - F, Farizal
AU - Amanda, Trisha
AU - Dachyar, Muhammad
AU - Noor, Zainura Zainon
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/7/15
Y1 - 2024/7/15
N2 - 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 organizational 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 62,758,433.56 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.
AB - 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 organizational 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 62,758,433.56 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.
KW - Carbon footprint
KW - Forecasting
KW - Greenhouse gases
KW - O-LCA
KW - Palm oil
UR - http://www.scopus.com/inward/record.url?scp=85195060527&partnerID=8YFLogxK
U2 - 10.1016/j.jclepro.2024.142646
DO - 10.1016/j.jclepro.2024.142646
M3 - Article
AN - SCOPUS:85195060527
SN - 0959-6526
VL - 463
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 142646
ER -