The long-term impact of urbanization on nitrogen patterns and dynamics in Shanghai, China
Bibliographic record
Abstract
Urbanization is an important process that alters the regional and global nitrogen biogeochemistry. In this study, we test how long-term urbanization (1952-2004) affects the nitrogen flows, emissions and drivers in the Greater Shanghai Area (GSA) based on the coupled human and natural systems (CHANS) approach. Results show that: (1) total nitrogen input to the GSA increased from 57.7 to 587.9 Gg N yr(-1) during the period 1952-2004, mainly attributing to fossil fuel combustion (43%), Haber-Bosch nitrogen fixation (31%), and food/feed import (26%); (2) per capita nitrogen input increased from 13.5 to 45.7 kg N yr(-1), while per gross domestic product (GDP) nitrogen input reduced from 22.2 to 0.9 g N per Chinese Yuan, decoupling of nitrogen with GDP; (3) emissions of reactive nitrogen to the environment transformed from agriculture dominated to industry and human living dominated, especially for air pollution. This study provides decision-makers a novel view of nitrogen management.
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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".