Environmental life cycle analysis of manufacturing options for humanitarian supplies: drinking water containers
Bibliographic record
Abstract
Abstract Purpose The purpose of this life cycle assessment (LCA) study was to determine the life cycle impacts for production and distribution of a humanitarian supply item under various supply chain paradigms in order to illustrate the potential environmental benefits of organizing production and supply operations for these items in novel ways. To do this a case study is used on a family-size water storage and dispensing bucket, such as the 14L-capacity polyethylene (PE) bucket commonly produced by Oxfam International. Methods The LCA is cradle-to-gate including production and transportation of PE plastic feedstock, fabrication of the water bucket, and transportation of the bucket to a common distribution site representative of a humanitarian aid location. Three different humanitarian aid locations are used to illustrate the range of potential impacts for each processing and supply system: Nepal, South Sudan, and Peru. Six processing and supply scenarios were investigated: 1) centralized Oxfam traditional system, 2) centralized commercial Chinese supply and distribution, 3) quasi-centralized Field Ready supply and distribution, 4) distributed supply and distribution system with 3-D printing, 5) distributed supply and distribution system with 3-D printing and local waste feedstock, and 6) distributed supply and distribution system with extrusion molding and local waste feedstock. Results and discussion The results found the major contribution to total GHG emissions are electricity usage for manufacturing and shipping feedstock and final product. Among Systems 1–3, System-1 and System 2 are environmentally poor as the electricity emissions in Pakistan and China are high. System 3 was an improvement as the products are manufactured locally. Decentralized supply and distribution system with 3-D printing (System 4) is less compatible with regions of high grid emissions. In System 5, the same equipment has been used, but with local waste feedstock, which shows an improvement of 67.7% for Nepal and 65.5% for Peru because of the reduced shipping emissions, even if the manufacturing emission is the highest among all of the systems. System 6 is feasible for all three locations. Conclusions It is concluded that manufacturing should be prioritized on grids where the electricity emission is lower using local waste feedstock as it is the most efficient approach; however, a further study should be done on operating the FPF/FGF 3-D printer or extrusion molding systems powered with distributed photovoltaic systems in order to complement this process and produce the most environmentally responsible production.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".