The grey water footprint of milk due to nitrate leaching from dairy farms in Canterbury, New Zealand
Bibliographic record
Abstract
The Canterbury Region of New Zealand has undergone rapid and significant land use intensification over the last three decades resulting in a substantial increase of nitrate-nitrogen leached to the environment. In this article, we determined the nitrate grey water footprint of milk, which is the amount of water needed to dilute nitrogen leached past the root zone to meet different receiving water nitrate standards per milk production unit. Our analysis revealed the nitrate grey water footprint for Canterbury ranged from 433 to 11,110 litres of water per litre of milk, depending on the water standards applied. This footprint is higher than many estimates for global milk production, and reveals that footprints are very dependent on inputs included in the analyses and on the water quality standards applied to the receiving water. The extensive dairy farming in Canterbury is leading to significant pollution of the region’s groundwater, much of which is used for drinking water. Dairy farming at this intensity is unsustainable and if not reduced could pose a significant risk to human health and the market perception of the sustainability of the New Zealand dairy industry and its products.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".