Comparative life cycle assessment of conventional and novel microalgae production systems and environmental impact mitigation in urban-industrial symbiosis
Bibliographic record
Abstract
The versatility of microalgae biomass as candidates for various products and bioremediation needs motivates interests towards design and implementation of novel microalgae bioreactors. Conventional open-reactors are reliant on large quantities of sunlight and space while yields are constrained by outdoor environment conditions. Conversely, closed-reactor systems like bubble columns reduces these constrains on microalgae growth while occupying far less space at the expense of high energy demands, notably from lighting systems. A novel patented closed reactor design has recently been proposed that improves the bubble column concept with an efficient and effective lighting system. The present study uses Life Cycle Assessment approach to compare the environmental performance of conventional reactors and the proposed internally luminated novel closed reactor design, expressing impacts per kg biostimulant for the Scenedesmus almeriensis harvest from such units. All performance data was collected from a pilot facility in Almeria, Spain. Urban-industrial symbiosis scenarios are also portrayed in the study using wastewater and incinerator flue gas. Results show that under synthetic nutrient and carbon inputs in Spanish pilot operations, the cumulative energy demand for the novel photobioreactors is similar to conventional vertically-stacked horizon bioreactors but are substantially more demanding than conventional open reactors. However, when leveraging renewable energy sources and the photosynthesis process to consume wastestreams in urban-industrial symbiosis scenarios, the novel photobioreactor was able to achieve up to 80 % improvements in several impact categories e.g. eutrophication and climate change. Impact mitigation credits per kg dwt biomass across all energy scenarios in symbiosis amount to ≈1.8 kg CO2eq and ≈0.09 kg PO4 eq. This highlights that such closed and internally illuminated photobioreactors can be competitive with conventional reactors, and have potential to harness photosynthesis to reduce environmental burdens in an urban-industrial symbiosis setting. Possible economies of scale and the associated potential gains in efficiencies are further discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".