Sulfite Stabilization and Reduction of the Aqueous Mercuric Ion: Kinetic Determination of Sequential Formation Constants
Bibliographic record
Abstract
The aqueous sulfite ion reacts with Hg 2+ (aq) to form 1:1 and 2:1 coordination complexes. The Hg(SO 3 ) 2 2- complex is redox stable. However, dissociation of a sulfite ligand forms redox-unstable HgSO 3 . Under conditions where Hg(SO 3 ) 2 2- predominates, the rate of reduction of the mercuric ion to Hg 0 by coordinated sulfite depends inversely on the concentration of uncoordinated sulfite, while it is unaffected by the amount of sulfite liberated by dissociation. Analysis of the kinetics yields the sequential sulfite binding constants K 1 = 2.1 × 10 13 and K 2 = 1.0 × 10 10 at μ = 0.10 M. These values lead to the prediction that HgSO 3 is more abundant in clouds than is Hg(SO 3 ) 2 2- under virtually all atmospheric conditions. The product of the redox reaction appears to be a strongly bound Hg 0 ·SO 2 complex, which is at least 3 orders of magnitude more soluble than uncomplexed Hg 0 (aq) . This finding may have important implications for the partitioning of atmospheric mercury from the gas phase into atmospheric water droplets prior to its wet deposition.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".