Regional Characterization of Freshwater Use in LCA: Modeling Direct Impacts on Human Health
Why this work is in the frame
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Bibliographic record
Abstract
Life cycle assessment (LCA) is a methodology that quantifies potential environmental impacts for comparative purposes in a decision-making context. While potential environmental impacts from pollutant emissions into water are characterized in LCA, impacts from water unavailability are not yet fully quantified. Water use can make the resource unavailable to other users by displacement or quality degradation. A reduction in water availability to human users can potentially affect human health. If financial resources are available, there can be adaptations that may, in turn, shift the environmental burdens to other life cycle stages and impact categories. This paper proposes a model to evaluate these potential impacts in an LCA context. It considers the water that is withdrawn and released, its quality and scarcity in order to evaluate the loss of functionality associated with water uses. Regionalized results are presented for impacts on human health for two modeling approaches regarding affected users, including or not domestic uses, and expressed in disability-adjusted life years (DALY). A consumption and quality based scarcity indicator is also proposed as a midpoint. An illustrative example is presented for the production of corrugated board with different effluents, demonstrating the importance of considering quality, process effluents and the difference between the modeling approaches.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it