Transforming the science of transformation toward sustainability: the case of ammonia and reactive nitrogen
Bibliographic record
Abstract
Chemistry has played a central role over the past century in the large-scale anthropogenic transformation of matter into diverse materials that have improved the quality of life for many people on our planet. The lens of chemistry is fundamentally necessary to understand the resulting flux of chemical substances in Earth system processes, the unintended consequences of those transformations, impacts on food supply security, water and energy concerns, ways to mediate and adapt to climate change, loss of biodiversity, and how best to build and maintain resilient ecosystems. Reactive nitrogen compounds (Nr) such as ammonia from the industrial fixation of atmospheric nitrogen exemplify both the central importance of chemistry in providing food and meeting basic human needs for a global population of 7.9 billion people and the sustainability challenges arising from the intended and unintended consequences of large-scale human production and release of Nr. The chemistry profession can use the Planetary Boundaries framework as a systems thinking tool to understand and address challenges facing the entire Earth system resulting from the altered biogeochemical flows of nitrogen. This analysis has compelling priority due to the roles Nr currently plays in global food production and ammonia’s potential role as an energy carrier for large-scale human activities in a future low carbon economy. As this example illustrates, navigating the complex benefits and challenges large-scale human activity imposes on Earth system processes requires the convergence of chemistry research, industrial practice, and education. Since the chemical reactions and processes that transform matter are foundational to sustainability challenges, this perspective maps multiple levels at which chemistry can contribute toward the emergence of sustainability of the Earth system. We conclude with recommendations for steps the profession of chemistry can take to make education relevant and engaging and to connect chemistry research and practice to cross-disciplinary sustainability challenges.
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 | 0.001 |
| 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".