1. Introduction

The increasing dependence on fossil fuels has intensified concerns over climate change, greenhouse gas emissions, and depletion of natural resources, creating an urgent need for cleaner and more sustainable energy sources. Among the available renewable alternatives, biofuels have emerged as a promising option for reducing reliance on petroleum-based transportation fuels. However, first-generation biofuels derived from edible crops have raised concerns regarding food security, land competition, and environmental sustainability. Consequently, attention has shifted toward third-generation biofuels produced from microalgae, which offer high lipid productivity, rapid growth rates, and the ability to grow on non-arable land without competing with food crops.

Microalgae-based biodiesel has attracted considerable interest because certain species, particularly Chlorella vulgaris, can accumulate substantial quantities of lipids suitable for biodiesel production. Unlike conventional vegetable oils, microalgae possess significantly higher biodiesel yield per unit area and can utilize carbon dioxide during cultivation, contributing to carbon mitigation. Despite these advantages, the overall sustainability of algal biodiesel depends greatly on cultivation, harvesting, lipid extraction, and downstream conversion processes, many of which require considerable energy and material inputs. Therefore, comprehensive environmental evaluation is necessary before large-scale commercialization can be recommended.

2. Objective of the Study

The primary objective of this research was to evaluate the environmental performance of microalgae-derived biodiesel by comparing three different harvesting and lipid recovery pathways while maintaining identical downstream biodiesel production processes. Rather than assessing completely independent biodiesel production systems, the study focused specifically on upstream operations because harvesting and lipid extraction are among the largest contributors to environmental burdens and energy consumption.

The investigation assessed greenhouse gas emissions, cumulative energy demand, water footprint, resource utilization, and multiple environmental impact categories using Life Cycle Assessment (LCA). In addition, uncertainty associated with the inventory data was quantified using Monte Carlo Simulation to improve the reliability of the conclusions.

3. Methodology

A comparative cradle-to-gate Life Cycle Assessment was performed according to ISO 14040 and ISO 14044 standards. The system boundary included microalgae cultivation, harvesting, lipid extraction, and biodiesel production through transesterification, while excluding transportation, fuel combustion, infrastructure construction, and end-of-life stages. The functional unit selected for comparison was the production of 1 kg of biodiesel, allowing consistent comparison among all production pathways.

Three biodiesel production pathways were investigated:

• BD1: Conventional hexane extraction (Business-as-Usual)

• BD2: Dynamic Cross-Flow (DCF) microfiltration with direct esterification

• BD3: Flocculation/sedimentation combined with DCF followed by direct esterification

Only the harvesting and lipid recovery stages differed among the pathways, while cultivation and transesterification remained identical, enabling direct comparison of environmental impacts attributable solely to upstream processing differences.

4. Microalgae Cultivation and Biodiesel Production

The study considered the cultivation of Chlorella vulgaris in open raceway ponds under a 21-day cultivation cycle. Nutrients such as urea, diammonium phosphate, and carbon dioxide were supplied to promote biomass growth, while electricity was required for mixing and maintaining suitable growth conditions. Biomass productivity and lipid content were based on published literature and incorporated into the life cycle inventory.

After cultivation, harvesting methods differed according to each scenario. BD1 employed settling tanks, dissolved air flotation, centrifugation, and hexane extraction. BD2 used Dynamic Cross-Flow microfiltration and centrifugation before direct esterification, whereas BD3 combined flocculation, sedimentation, and DCF prior to direct esterification. These different harvesting strategies significantly influenced electricity consumption, material usage, and environmental performance.

5. Life Cycle Impact Assessment

Environmental impacts were quantified using multiple assessment methods to capture different sustainability dimensions.

The IPCC 2021 methodology was applied to evaluate climate change impacts through Global Warming Potential (GWP) and Global Temperature Potential (GTP) over different time horizons.

The ReCiPe 2016 method was used to assess midpoint and endpoint environmental categories including:

• Global warming

• Ozone depletion

• Human toxicity

• Ecosystem damage

• Acidification

• Eutrophication

• Resource depletion

• Water consumption

In addition, Cumulative Energy Demand (CED) analysis quantified direct and indirect energy requirements, while water footprint assessment evaluated freshwater consumption and water scarcity impacts. Using several assessment methods enabled a more comprehensive evaluation of biodiesel sustainability than relying on a single impact assessment framework.

6. Energy Balance and Scenario Analysis

The sustainability of biodiesel production was further evaluated through energy balance indicators including Net Energy Value (NEV), Net Renewable Energy Value (NRnEV), Net Energy Ratio (NER), and Renewability (Rn). These indicators compared energy inputs with useful energy outputs from biodiesel and its co-products.

Scenario analysis was also performed to evaluate avoided products and alternative impact assessment methods. Glycerine produced during biodiesel production was treated as an avoided product using the substitution approach, thereby accounting for environmental credits associated with replacing conventionally produced glycerine. Additional scenarios employed the IMPACT World+ methodology to verify whether conclusions obtained using IPCC and ReCiPe remained consistent under different environmental assessment models.

7. Uncertainty Analysis

Because Life Cycle Assessment relies on inventory data obtained from literature and databases, uncertainty analysis was incorporated to improve confidence in the results. The study employed a Monte Carlo Simulation with 10,000 iterations, combined with a pedigree matrix to assign uncertainty scores based on data reliability, completeness, temporal correlation, geographical relevance, and technological representativeness.

A lognormal probability distribution was adopted for the simulations because environmental inventory data generally exhibit multiplicative variability. The uncertainty analysis quantified variability in impact categories and strengthened the robustness of the comparative assessment among the three biodiesel pathways.

8. Results and Environmental Performance

The environmental assessment demonstrated substantial differences among the three biodiesel production pathways.

BD2 exhibited the highest environmental burden because of its intensive electricity consumption and fertilizer requirements during cultivation and harvesting. It recorded the highest Global Warming Potential, cumulative energy demand, and several midpoint environmental impacts. Electricity use and fertilizer application together accounted for the majority of greenhouse gas emissions and other environmental impacts.

The conventional BD1 pathway showed intermediate environmental performance. Although widely adopted as the business-as-usual scenario, its reliance on hexane extraction and energy-intensive harvesting resulted in greater impacts than the optimized BD3 pathway.

Among all alternatives, BD3 consistently achieved the best environmental performance. The combination of flocculation/sedimentation with Dynamic Cross-Flow significantly reduced electricity consumption during biomass concentration. Consequently, BD3 exhibited the lowest greenhouse gas emissions, reduced cumulative energy demand, lower water consumption, and improved resource efficiency across most environmental categories. The analysis demonstrated that optimizing harvesting and lipid recovery technologies can substantially improve the sustainability of microalgae-based biodiesel production.

9. Conclusions

The study demonstrates that harvesting and lipid recovery technologies are critical determinants of the environmental sustainability of microalgae-derived biodiesel. While conventional production methods remain energy intensive, alternative harvesting approaches can significantly reduce greenhouse gas emissions, energy demand, and resource consumption. Comparative Life Cycle Assessment showed that the BD3 pathway consistently outperformed both the conventional BD1 process and the Dynamic Cross-Flow-based BD2 process across multiple environmental indicators.

By integrating Life Cycle Assessment, cumulative energy demand analysis, water footprint assessment, scenario analysis, and Monte Carlo uncertainty analysis, the research provides a comprehensive framework for evaluating sustainable biodiesel production. The findings indicate that improving upstream processing technologies represents an effective strategy for enhancing the environmental performance of algal biodiesel and supporting its future commercialization as a renewable transportation fuel.