End-of-life stage natural (Re)carbonation of lower embodied carbon concrete: Case studies of Canadian cities
Bibliographic record
Abstract
Carbon dioxide (CO₂) uptake through the natural (re)carbonation of concrete during its use stage is increasingly included in life cycle carbon accounting as a means to partially offset process emissions of cement manufacturing. To date, research on (re)carbonation of the end-of-life stage of concrete has received markedly less attention in comparison to the use stage (service life). This study evaluates Canadian case studies and the sensitivity of concrete mix design variables, environmental conditions, and stockpiling configuration. Concrete mixes of ordinary Portland cement (OPC), Portland limestone cement (PLC) and supplementary cementitious materials (SCMs) were exposed to eight exposure conditions (four urban and four rural) at both the use stage and end-of-life stage. The key variables assessed include concrete mix designs (two cement types and two SCM types (fly ash and slag)), geographically relevant environmental parameters (relative humidity, temperature, and CO₂ concentration), stockpiling geometry (heaps and spread) and corresponding end-of-life exposure duration (1 and 4 months). Model estimates for CO₂ uptake-to-emission ratios (%) were developed to highlight the influence, sensitivity and impact of cement composition and environmental factors on potential for (re)carbonation yielding offsets by CO₂ uptake throughout the concrete lifecycle. Key outcomes of these geographically specific case studies scenarios are presented in this paper as upper and lower bound of the range of model input variables. (i) one year of end-of-life stage exposure can yield CO₂ uptake comparable to 50-year service life (use stage), with end-of-life carbonation rates up to six times higher due to the increased exposed surface area. (ii) PLC achieves 14% higher use-stage CO₂ uptake and 9% higher end-of-life CO₂ uptake than OPC (iii) CO₂ uptake for 100%OPC mixes increased by 9% (with 20% fly ash) and 11% (with 35% slag) during the use stage. In contrast, for PLC mixes, SCM influence was minimal in the use stage and negligible at end-of-life stage. (iv) Changes in environmental exposure, namely, relative humidity and CO₂ concentration, impacted the CO₂ uptake-to-emission ratio (%) by up to 35% and 27%, respectively during the use stage. In comparison, the end-of-life CO₂ uptake was highly sensitive to stockpiling geometry and stockpiling durations than environmental conditions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".