Life cycle assessment module

The LCA module simulates the biofuel GES (Table 5-6) and includes the estimation of the biodiesel GHG emissions from LUC and soybean cultivation. The GES is linked to the BM module to estimate the fulfilment of the GES threshold.

The LCA model is based on earlier work, by “dynamising” an attributional LCA of soybean- base biodiesel production for export in Argentina (Panichelli et al. 2009). The methodology, however, was adapted based on the European methodology for LCA GHG emissions

SIMULATION MODEL

estimations in biofuel pathways (EC 2009). Table 5-7 gives the specifications of the LCA module.

Table 5-6. Outputs and simulated variables of the LCA module.

Outputs Units Symbol Equation

GHG emission saving by supply region % erbio,sr _{Eq. 4-52}

Simulated variables

GHG emission balance of the biofuel gCO2eq/MJ

bp sr bio

e _{, Eq. 4-49}

LUC GHG emissions from biodiesel supply gCO2eq/MJ elsr Eq. 4-50 GHG emissions from soybean cultivation by method gCO2eq/MJ eecm Eq. 4-51

Table 5-7. Specifications of the LCA module.

Modeling assumptions Description

System definition Well-to-Wheel

Allocation method Energy/Economic

Functional unit gCO2eq/MJ

Reference land-use Based on simulated land-use changes from LCS Reference fossil fuel EU fossil diesel reference

Unit processes

Soybean production

Oil extraction (soybean crushing)

Oil transesterification (biodiesel production) Biodiesel transport and distribution

Biodiesel use

LCIA method IPCC 2001 GWP 100a (climate change)

LCI data ecoinvent® 2.01 database

GHG emission gases

carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O)

CO2 equivalence

CO2 :1 N2O :296 CH4 :23 LUC emissions amortisation 20 years

The AR soybean-based biodiesel GHG emission balance was modeled through an LCA and was compared with the reference fossil diesel value given in the EU-RED. The system is modeled based on a well-to-wheel approach, which means that the model accounts for GHG emissions from the feedstock production to the biofuel use. The function unit was specified as gCO2eq per energy unit, as required in the EU-RED. The system was divided into five unit processes, including the main production stages of the biodiesel supply chain. Energy allocation is the default setting of the LCA allocation approach. Nonetheless, an alternative allocation case was simulated based on economic value to evaluate the variability of results with regard to this key methodological parameter. Economic allocation was based on the simulated producer prices of each soybean product in the biodiesel supply chain, with the exception of glycerine, where a constant price was used.

The life cycle inventory (LCI) and the life cycle impact assessment (LCIA) were performed in Excel spreadsheets using the ecoinvent ® 2.01 database and then integrated as constants into the dynamic simulation model. GHG emission gases and their respective CO2 equivalence are also specified according to the EU-RED methodology. Emissions from each unit process include emissions from the production process itself; from the collection of raw materials;

or cultivation. CO2 uptake in the cultivation of soybean was excluded and emissions from fuel use are assumed to be zero.

In the dynamic simulation model, the LCA module does not present any specific stock and flow structure (Figure 9-9 -Figure 9-11). The module is mainly a set of auxiliary variables. The interconnections between them determine the GHG emission balance for each unitary process of the biodiesel supply chain. While no policy variables are included in the LCA module, the module accounts for some critical methodological option in LCA of biofuel pathways such as economic and energy allocation, land-use change accounting and functional unit choice.

The simulation of the GHG emission saving is as follows (Figure 5-11). Firstly, LUC GHG emissions from cropland expansion are estimated based on simulated land-use changes in the LCS module. LUC GHG emissions from cropland expansion are estimates based on the supply of cropland from unmanaged land-uses and pastureland, given by the LCS module (following the B4 feedback loop). Instead of giving a credit for soybean cultivation in degraded land38, the model simulates GHG emission savings from cultivation in degraded land. Emissions from cropland expansion are then allocated to soybean for biodiesel based on the share of soybean on cropland expansion and the share of soybean for biodiesel on soybean land supply, which are endogenous variables given by the LCS module.

Set methodological LCA choice § Allocation method

§ LUC emissions amortization time

Set external factor scenario § Energy content of soybean products § Industrial, distribution and use emissions § LUC, inputs and fossil reference emision factors

GHG emissions from cropland dLUC End t=T? yes get average soybean yield t=t+1

t=t0 Set initial conditions

Cropland supply GHG emissions from soybean

cultivation by production method (no dLUC)

Average GHG emissions from soybean

cultivation no GES Soybean land supply Allocate cropland dLUC GHG emissions to soybean Allocate cropland dLUC GHG emissions to soybean Biodiesel production/export Soybean production

Figure 5-11. Simulation procedure of the LCA module.

GHG emissions from soybean cultivation are estimated based on the three main soybean production systems in Argentina (font, sont, foct). Diesel consumption in agricultural processes was converted into inputs of agricultural field work processes according to ecoinvent® (Nemecek et al. 2007) in order to consider agricultural machinery production and

38 _{The EU-RED assigns a}

bonus of 29 gCO2eq/MJ biofuel or bioliquid if biomass is obtained from restored degraded land under

SIMULATION MODEL

use as well as exhaust emissions from the tractor. Pesticide and fertiliser use is the average of soybean cultivation in Argentina under the different production systems. Nitrogen fertiliser is only applied to first occupation soybean as monoammonium phosphate (MAP), whilst second occupation uses the residual fertilisation of the previously implanted crop. P fertiliser is applied as MAP and triple super phosphate (TSP) fertilisers. N2O emissions are calculated as a direct emission from the N input and an indirect emission from the N content in nitrate leaching, as implemented in ecoinvent®. N input accounts for the N biological fixation (BNF) and for N fertiliser (Jungbluth et al. 2007). Transport distances are adjusted for each soybean production region, based on the distance to the Rosario, where most of the crushing facilities are located.

Industrial emissions from soybean oil crushing and transesterification are based on emissions from average international technology. Solvent extraction technology (with methanol) and soybean oil transesterification (with hexane) is based on international standard technology, as described in Jungbluth et al. (2007) for biodiesel production. However, yields, allocation factors, natural gas and electricity consumption, electricity mix and transport distances are specific to the Argentinean context. No data was available for the soybean intermediate storage and drying phase. Consequently, this stage was not considered in the system boundaries, and it was assumed to take place only at the vegetable oil extraction plant. No difference was assumed between biodiesel and fossil diesel in useful work done in the estimation of biodiesel use emissions.

Finally, total emissions from biodiesel production are estimated as the sum of emissions of each unitary process to simulate the biodiesel GHG emission balance. The GES is then estimated based on the reference fossil diesel emission factor. The GES of the biodiesel is linked to the BM module to estimate the biodiesel export potential under the GES threshold imposed in the EU-RED.