Long-Term Monitoring of Cloud Water Chemistry at Whiteface Mountain: The Emergence of a New Chemical Regime
Bibliographic record
Abstract
Abstract. Atmospheric aqueous chemistry can have profound effects on our environment. The importance of chemistry within the atmospheric aqueous phase was first realized in the 1970s as there was growing concern over the negative impacts on ecosystem health from acid deposition. Research at mountaintop observatories including Whiteface Mountain (WFM) showed that gas phase sulfur dioxide emissions react in cloud droplets to form sulfuric acid, which also impacted aerosol mass loadings. Cloud chemistry research has experienced a major resurgence in scientific interest due to the potential for aqueous chemical processes to fill the gap between modeled and observed organic aerosol mass. The current study updates the long-term trends in cloud water composition at WFM for the past 28 years (1994–2021). Substantial decreases in sulfate (SO42-) and nitrate (NO3-) concentrations have not been matched by an equivalent decrease in ammonium (NH4+) concentrations, leading to significantly higher cloud droplet pH. Meanwhile, Total Organic Carbon (TOC) concentrations may be increasing (both in relative and absolute terms). In the past, samples were excluded from trend analysis if they did not meet an approximate ion balance, which resulted in approximately half of samples being excluded in recent years. We show that, when including the entire available dataset, decreasing trends in SO42-, NO3- and NH4+ become more modest, TOC concentrations increase at a faster rate, and increasing trends in Ca2+ and Mg2+ emerge. A growing trend in cation / anion ratios is also observed, implying that a significant fraction of anions are not being measured with the current suite of measurements, and these missing anions are growing in importance. Organic acids are identified as the most likely candidates for the missing anions, since the measured ion imbalance correlates strongly with measured TOC concentrations. The TOC trend becomes statistically insignificant when evaluating cloud water loadings (or air equivalent mass loadings), possibly due to the complex role that LWC may play in TOC concentrations. We highlight the emergence of a new chemical regime characterized by low acidity and relatively high conductivity, and increasing TOC and base cation concentrations. With the increasing impact from Ca2+ and Mg2+ on the bulk cloud water pH, which are largely thought to reside within coarse mode aerosol that only represent a small fraction of cloud droplets, an "inferred cloud droplet pH" is introduced, to better represent the pH of the vast majority of cloud droplets as they reside in the atmosphere. While measured pH has increased during the history of the monitoring site, the cloud droplet pH has remained relatively flat since 2009. We also show that there is a missing source of acidity in the system that correlates with TOC. The chemical system at WFM has shifted away from a system dominated by SO42- to a system controlled by base cation, nitrogen containing species and TOC. Further research is required to understand the effects on air quality, climate, and ecosystem health.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".