Measured greenhouse gas budgets challenge emission savings from palm-oil biodiesel

Special thanks to our field assistants in Indonesia (Basri, Bayu and Darwis) and to Frank Tiedemann, Edgar Tunsch, Dietmar Fellert and Malte Puhan for technical assistance. We thank PTPN VI and the owner of the plantation at Pompa Air for allowing us to conduct our research at their plantation. We would also like to thank the Spanish national project GEISpain (CGL2014-52838-C2-1-R) and the DAAD (scholarship from the programme ‘Research Stays for University Academics and Scientist 2018, ref. no. 91687130)' for partly financing A. Meijide during the preparation of this paper.The potential of palm-oil biofuels to reduce greenhouse gas (GHG) emissions compared with fossil fuels is increasingly questioned. So far, no measurement-based GHG budgets were available, and plantation age was ignored in Life Cycle Analyses (LCA). Here, we conduct LCA based on measured CO2, CH4 and N2O fluxes in young and mature Indonesian oil palm plantations. CO2 dominates the on-site GHG budgets. The young plantation is a carbon source (1012 ± 51 gC m−2 yr−1), the mature plantation a sink (−754 ± 38 gC m−2 yr−1). LCA considering the measured fluxes shows higher GHG emissions for palm-oil biodiesel than traditional LCA assuming carbon neutrality. Plantation rotation-cycle extension and earlier-yielding varieties potentially decrease GHG emissions. Due to the high emissions associated with forest conversion to oil palm, our results indicate that only biodiesel from second rotation-cycle plantations or plantations established on degraded land has the potential for pronounced GHG emission savings.This study was financed by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)— Project-ID 192626868—in the framework of the collaborative German-Indonesian research project CRC990 (subprojects A03, A04 and A05).Spanish national project GEISpain (CGL2014-52838-C2-1-R) and the DAAD (scholarship from the programme ‘Research Stays for University Academics and Scientist 2018, ref. no. 91687130

Analysing the water and greenhouse gas effects of soya bean-based biodiesel in five different regions

Bioenergy may have significant lower greenhouse gas (GHG) emission intensities compared to fossil alternatives, but concerns are raised that bioenergy would contribute to additional water scarcity. Therefore, the GHG intensity, water intensity and water-related risks are analysed simultaneously for conventional diesel and soya bean-based biodiesel from Argentina, Brazil, Unites States (U.S.), Thailand and Iran on a life cycle basis. The water-related risks are estimated with a water scarcity—consumption matrix, which was recently developed. Results show that a significant share (9%-38%) of the GHG emissions in all biodiesel cases is caused by soil N2O emissions. In addition, the ranges in water consumption intensity for soya bean-based biodiesel are considerably larger than for fossil fuels. However, whether this leads to high water-related risks depends on the local water scarcity. Soya bean-based biodiesel from Argentina has low water-related risks to all nodes of the supply chain due to low local water stress combined with a low direct water consumption intensity (20 L/GJfuel). In addition, high GHG emission reduction (71%) and a low-specific eutrophication potential (0.04 kg PO4 3−/GJfuel) are achieved. The indirect water consumption intensity is estimated at 120–420 L/GJ for soya bean-based biodiesel, which is significant if the soya beans are rainfed, like in Argentina and Brazil. If irrigation is required, indirect water consumption is dwarfed by irrigation water. Overall, it is concluded that soya bean-based biodiesel can have significant lower GHG emission intensity than fossil diesel, without causing additional water stress in the supply chain if they are produced in water abundant areas and good agricultural practices are used. The used method shows disaggregated water-related risks for the different nodes of the supply chain to acknowledge the regional nature of water scarcity and enables decision makers to identify “hot spots” and take targeted actions