Assessment of Environmental Impacts of Thermal Caisson Geothermal Systems
Bibliographic record
Abstract
This paper investigates the total environmental impacts of a thermal caisson (TC) system by implementing a life cycle assessment methodology. The total environmental impacts consider the comprehensive effect on the environment across two life cycle stages: manufacturing and operation. A comparison between the TC results and two different HVAC systems, including air-conditioning/furnace and conventional ground-source heat pump (GSHP) systems, was made by adopting the ReCiPe 2016 methodology. This study reveals that the operation phase is the predominant contributor to environmental impacts across systems, mainly due to its extended duration. Specifically, the operational impacts of GSHPs are substantial, accounting for approximately 87% of total environmental impacts. A TC GSHP system demonstrates a notable environmental advantage, achieving a 79% reduction in total environmental impact when compared to traditional AC/furnace systems. This represents a 21% improvement over conventional GSHP systems. Despite this substantial reduction in total environmental impact, the TC GSHP system shows an almost 5% increase in the resource availability damage category relative to the conventional GSHP, which is attributed to its higher material consumption. These results highlight the TC GSHP system’s superior efficiency in reducing environmental impacts and its potential as a more sustainable alternative in residential heating and cooling applications.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".