Unexpected Electrophiles in the Atmosphere - Anhydride Nucleophile Reactions and Uptake to Biomass Burning Emissions
Bibliographic record
Abstract
Biomass burning is a significant contributor to atmospheric pollution, its emissions have been found to have adverse impacts on climate and human health. Largely, these impacts are dictated by how the composition of the emissions changes once emitted into the atmosphere. Recently, anhydrides have been identified as a significant fraction of biomass burning emissions, however, little is known about their atmospheric evolution, or their interactions within the burn plume. Without this understanding, it is challenging to predict the impact of anhydrides on biomass burning emissions, and by extension, their influence on climate and health. In this study, we investigate anhydrides as potentially unrecognized electrophiles in the atmosphere. Firstly, by exploring their reactivity towards important biomass burning emitted nucleophiles, and secondly, by measuring their uptake on the emissions themselves. Our results show that phthalic and maleic anhydride can react with a wide range of nucleophiles, including hydroxy and amino-containing compounds, such as levoglucosan or aniline. Additionally, using a coated-wall flow tube setup, we demonstrate that anhydrides reactively uptake to biomass burning films and influence their composition. The anhydride nucleophile reaction was found to be irreversible, proceeding without sunlight or free radicals and indicating it may occur during the day or night time. Furthermore, the reaction products were found to be water-stable and contain functional groups which enhance their mass and likely contribute to the formation of secondary organic aerosol, with knock-on climate effects. Overall, our study sheds light on the fundamental chemistry of anhydrides and their potential impacts in the atmosphere.
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 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 | 0.000 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".