Microalgae Biofuel for a Heavy-Duty Transport Sector within Planetary Boundaries

In this contribution, we study the extent to which 68 scenarios for microalgae biofuels could help the heavy-duty transport sector operate within planetary boundaries. The proposed scenarios are built considering a range of alternative configurations based on three types of fuel production processes (i.e., transesterification, hydrodeoxygenation, and hydrothermal liquefaction), different carbon sources (such as natural gas power plants and direct air capture), byproduct treatments, and two electricity mixes. Our results reveal that microalgae biofuels could significantly reduce the environmental and human health impacts of the business-as-usual (fossil-based) heavy-duty transport sector. Moreover, relative to standard biofuels that show large land-use requirements, we find that microalgae biofuels also decrease the damage on biosphere integrity substantially. Notably, pathways resorting to hydrodeoxygenation of microalgae oil and direct air capture and carbon storage could reduce the current impact induced globally on climate change by the heavy transport by 77%, while attaining six-fold reductions in biosphere integrity impacts, both relative to conventional biofuels.


Definition of scenarios and planetary boundaries
The scenarios considered in the analysis and the corresponding labels are provided in Table S1. In Table S2, the abbreviations adopted for the PBs are described, and Table  S3 provides the control variables values, along with the proposed boundaries. Table S1. Correspondence between labels and scenarios reported in this study.

Label Scenario BAU
Business-as-usual (global demand for road freight covert by diesel) M2020 Current global electricity grid mix. 1 M2040 2040 sustainable development (SD) grid mix. 2 NGP Carbon dioxide provided to algae harvesting is captured from the natural gas power plant. 3

DAC
Carbon dioxide provided to algae harvesting is captured from direct air capture plant. 4

CCS
Carbon dioxide after cogeneration is captured and stored in a geological reservoir. 5,6 CCU Carbon dioxide after cogeneration is captured and send to algae harvesting. 7 NoCCU Remaining Lipid Extracted Algae (LEA) is not used as a source of energy, therefore the use of CO 2 is not considered and this is considered strictly as an emission C Cogeneration of energy occurs through the direct combustion of LEA to supply heat via a steam boiler. Considering an electric efficiency of 21.7% and a heat recovery efficiency of 65% and a biomass moisture of 20% 7 B Cogeneration of energy is carried out through anaerobic digestion to produce biogas and its subsequent use in a gas turbine. Considering an electric efficiency of 33% and a heat recovery efficiency of 64%. 7

ACR
Combustion gases from the cogeneration process are released into the S2 atmosphere without carbon dioxide capture HDO Biofuel from hydrodeoxygenation BD20 Biofuel from transesterification in a blend with fossil fuels 20% vol HTL Biofuel from hydrothermal liquefaction †HTL-Soybean is not considered because for biofuel production by HTL a moisture content of 20% is considered. 8 . Soybean oil is considered a feedstock and currently the soybean residue has an important economic value (i.e., 56% allocation). Therefore, the use of whole grains as feedstock is not considered. 9 Figure S1 shows in a more detailed representation than Figure 3 of the manuscript, showing the interactions between the different processes in the scenarios under analysis.

Data sources
The required data used in the LCA calculations is provided in this section. Most values were taken from the GREET database, 7 which contains harmonized data from 1400 facilities with different annual capacities, as shown in Table S4.  Table S5 to Table S21 provide the different life cycle inventories considered for microalgae biofuel production, along with all the dependent sub-processes that were adapted from the original references. The final LCIs were obtained by combining data from the process model in GREET with information from the literature and Ecoinvent v3.7. 1 The latter activities, missing in Ecoinvent and requiring a tailored intermediate inventory analysis based on the literature, are labeled with a "*" detailed in LCI Tables. Furthermore, as seen in tables S5 and S21, several of the inputs to the foreground system were modeled utilizing additional information from the literature and Ecoinvent.
The "Electricity" activity differs depending on the scenario. Table S22 and Table S23 provide a thorough breakdown of the various electricity scenario options. We assume that the electricity consumed in the background system is modeled with the default activities in Ecoinvent v3.7. Hence, we only change the electricity of the foreground system while keeping the energy generation activities in the background system unaltered. Table S5-S7 provide information about microalgae production with a moisture of 20%. The process considers the use of open pools, where water and fertilizers are recirculated after the filtration and drying process so that the replacement water introduced corresponds to the water lost by evaporation and blowdown to avoid excess mineral and salt build-up, and to regulate the pH of the culture medium. 12 The harvesting and drying process is carried out in two stages using flocculation followed by mechanical filtration using centrifuges 7 .
The yield of microalgae is influenced by their geographical location and, as a result, the potential of microalgae to reduce their impacts on seven Earth-system processes can vary across different scenarios. The yield of microalgae varies widely across the world, ranging from 4.43 g/m 2 /day (1.13 m 3 oil/ha/yr) to 38.80 g/m 2 /day (27 m 3 /ha/yr), with the geographical location and season affecting growth due to variations in radiation and temperature. 13 However, for the purposes of this study, harmonized values corresponding to 26.37 g/m 2 /day (3.6 m 3 /ha/yr) were used, based on studies conducted in the United States region. 10

S5
The process of CO 2 capture from direct air capture (Table S15) or natural gas power plant (Table S15) provides concentrations higher than 97%. This concentration is adopted since GREET describes a pure CO 2 flow for microalgae growing. Furthermore, in the case of CO 2 from the natural gas power plant to remove compounds such as nitrogen oxides, sulfur oxides and heavy metals that can adversely affect the growth of microalgae.  Table S15 and Table S16, respectively. The LCI data for microalgae biomass production are retrieved from the GREET2022 datasheet in section 1.3 of the "Algae" category. 14 More information and details on cultivation can also be found in the document "2017 Algae Harmonization Study". 10 Table S6. LCI of the foreground system microalgae production based on open ponds with CO 2 recovery after LEA combustion for energy cogeneration.

Process:
Microalgae production w CO 2 from LEA combustion

Ecoinvent entry Description Amount
Inputs: 0.459 †For CO 2 reuse from LEA combustion, 1.23 kg CO 2 /kg algae biomass is supplied, 0.336 kWh of electricity is delivered from the cogeneration plant, and 0.015kWh are required for capture and transport of CO 2 from LEA combustion with a moisture of 20%. The LCI data for microalgae biomass production are retrieved from the GREET2022 datasheet in section 1.3 of the "Algae" category. 14 More information and details on cultivation can also be found in the document "2017 Algae Harmonization Study". 10 The electric and heat recovery efficiencies are 21.7% and 65%, respectively. 7,15 *CO 2 from NG and DAC are the possible activities that supply CO2 to the process and are detailed in Table S14 and Table S15, respectively. Table S7. LCI of the foreground system microalgae production based on open ponds with CO 2 recovery after LEA combustion for energy cogeneration.

Process:
Microalgae production w CO 2 from biogas combustion For CO 2 reuse from biogas combustion, 0.69 kg of CO 2 are supplied for each kg of algae introduced to the microalgae production process, 0.592 kWh of electricity are delivered from the cogeneration plant, and 0.008 kWh are required for capture and transport of CO 2 from biogas combustion. The electric and heat recovery efficiencies are 33.1% and 64%, respectively for combined heat and power through a gas turbine. 7,15,16 .

Ecoinvent entry Description Amount
*CO 2 from NG and DAC are the possible activities that supply CO 2 to the process and are detailed on table Table S15 and Table S16, respectively. Table S8. LCI of the microalgae oil production based on wet extraction without cogeneration.

Process:
Microalgae oil extraction

Ecoinvent entry Description Amount
Inputs: The data for microalgae extraction are retrieved from the GREET2022 datasheet in section 2.3 from oil extraction column, of the "Algae" category. 14 Table S9. LCI of the microalgae oil production based on wet extraction.

Process:
Microalgae oil extraction

Ecoinvent entry Description Amount
Inputs: 1 †The heat demand is considered 0 for the scenarios with cogeneration of energy by direct combustion of LEA or cogeneration from biogas. In the first case, 23.12 MW/kg oil, and in the second case, 17.75 MW/ kg oil of thermal energy are generated 7 . Table S10. LCI of the energy cogeneration from lipid extracted algae combustion.

Process:
Energy cogeneration from LEA combustion

Ecoinvent entry Description Amount
Inputs:  Table S11. LCI of the energy cogeneration from biogas combustion.

Process:
Energy cogeneration from biogas

Ecoinvent entry Description Amount
Inputs:

S10
LCI data for HDO production are retrieved from the GREET2022 datasheet in section 2.2 of the "Algae" category where "Renewable Diesel I" column is selected. 14 †The economic allocation considered was 89% for HDO, 6% for fuel gas, and 5% for heavy oil. LCI data for biodiesel production are retrieved from the GREET2022 datasheet in section 2.2 of the "Algae" category where "Biodiesel" column is selected. 14 †Economic allocation of 95.7% for biofuel and 4.3% for glycerin were considered. LCI data for HTL production are retrieved from the GREET2022 datasheet in section 2.2 of the "Algae" category where "Hydrothermal liquefaction" column is selected. 14 More information and details on cultivation can also be found in the document "2017 Algae Harmonization Study". 10 *LCI of catalyst are detailed in Table S21. †Economic allocation of 67.3% for HTL and 32.7% for gasoline were considered.  Table S20. LCI data for CO 2 captured form a natural gas power plant was modeled in Ecoinvent based on the data provided by Ioannou et al. 17 The electricity shown is equal to the required demand minus the electricity for compression because compression at 30 bar is not required. 17,18 An economical allocation factor of 81% for electricity and 19% for CO 2 was considered. 3,19  1.17E-04 LCI data for CO 2 capture and compression plant was modeled in Ecoinvent based on the data provided by Bello et al. 5 †For electricity inputs GLO electricity is going to be changed to electricity M2040.   For combustion, the fuel consumption of 0.023 kg/t km was considered. 7,21 This value is within the range reported with fuel consumption at full load capacity for short-haul trucks between 0.018 and 0.024 kg diesel/t km. 22 In this case, our study, for the sake on simplicity will consider the same fuel consumption per t km, although this value has certain variations according to the type of fuel used. 1.02E-07 LCI of diesel combustion was modeled in Ecoinvent based on the data provided by GREET® 2021 .Net software, emissions correspond to the combustion of a heavy-duty truck denominated "HD Truck: short haul" powered by low sulfur diesel. 23 1.02E-07 LCI of BD20 combustion was modeled in Ecoinvent based on the data provided by GREET® 2021 .Net software, emissions correspond to the combustion of a heavy-duty truck denominated "HD Truck: short haul" powered by biodiesel 20% vol. 23 S18 3. Additional data 3.1.

Overall level of transgression
The results shown in Figure 3 from the main manuscript are analyzed in greater detail for the different scenarios studied (Table S27 to Table  S31). The planetary boundaries main contributions activities are detailed from Figure S1 to Figure S9, the resulting datasets generated during the current work are publicly available online at Cabrera-Jimenez R. et al. 24

Contributions to planetary boundaries
Figures S2 -S9 in this section we provide the breakdowns of every PB for the scenarios included in the main study with respect to the selected functional unit (FU), i.e., the freight road transport (t km).