Life Cycle Carbon Emissions Savings of Replacing Concrete with Recycled Polycarbonate and Sand Composite
Bibliographic record
Abstract
Recent work demonstrated that 50:50 sand-recycled polycarbonate (rPC) composites have an average compressive strength of 71 MPa, which dramatically exceeds the average offered by commercial concrete (23.3–30.2 MPa). Due to the promising technical viability of replacing carbon-intensive concrete with recycled sand plastic composites, this study analyzes the cradle-to-gate environmental impacts with a life cycle assessment (LCA). Sand-to-plastic composites (50:50) in different sample sizes were fabricated and the electricity consumption monitored. Cumulative energy demand and IPCC global warming potential 100a were evaluated to quantify energy consumption and greenhouse gas emission associated with sand–plastic brick and two types of concrete, spanning the life cycle from raw material extraction to use phase. The results showed that at small sizes using Ontario grid electricity, the composites were more carbon-intensive than concrete, but as samples increased to standard brick–scale rPC composite bricks, they demonstrated significantly lower environmental impact, emitting 96% less CO2/cm3 than sand–virgin PC (vPC) composite, 45% less than ordinary concrete, and 54% less than frost-resistant concrete. Energy sourcing has a significant influence on emissions. Sand–rPC composite achieves a 67–98% lower carbon footprint compared to sand–vPC composite and a 3–98% reduction compared to both types of concrete. Recycling global polycarbonate production for use in sand–rPC composites, though small compared to the total market, could annually displace approximately 26 Mt of concrete, saving 4.5–5.4 Mt of CO2 emissions. The results showed that the twin problems of carbon emissions from concrete and poor plastic recycling could be partially solved with sand–rPC building material composites to replace concrete.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".