Current understanding of the driving mechanisms for spatiotemporalvariations of atmospheric speciated mercury: a review
Bibliographic record
Abstract
Abstract. Atmospheric mercury (Hg) is a global pollutant and thought to be the main source of mercury in oceanic and remote terrestrial systems, where it becomes methylated and bioavailable; hence, atmospheric mercury pollution has global consequences for both human and ecosystem health. Understanding of spatial and temporal variations of atmospheric speciated mercury can advance our knowledge of mercury cycling in various environments. This review summarized spatiotemporal variations of total gaseous mercury or gaseous elemental mercury (TGM/GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM) in various environments including oceans, continents, high elevation, the free troposphere, and low to high latitudes. In the marine boundary layer (MBL), the oxidation of GEM was generally thought to drive the diurnal and seasonal variations of TGM/GEM and GOM in most oceanic regions, leading to lower GEM and higher GOM from noon to afternoon and higher GEM during winter and higher GOM during spring–summer. At continental sites, the driving mechanisms of TGM/GEM diurnal patterns included surface and local emissions, boundary layer dynamics, GEM oxidation, and for high-elevation sites mountain–valley winds, while oxidation of GEM and entrainment of free tropospheric air appeared to control the diurnal patterns of GOM. No pronounced diurnal variation was found for Tekran measured PBM at MBL and continental sites. Seasonal variations in TGM/GEM at continental sites were attributed to increased winter combustion and summertime surface emissions, and monsoons in Asia, while those in GOM were controlled by GEM oxidation, free tropospheric transport, anthropogenic emissions, and wet deposition. Increased PBM at continental sites during winter was primarily due to local/regional coal and wood combustion emissions. Long-term TGM measurements from the MBL and continental sites indicated an overall declining trend. Limited measurements suggested TGM/GEM increasing from the Southern Hemisphere (SH) to the Northern Hemisphere (NH) due largely to the vast majority of mercury emissions in the NH, and the latitudinal gradient was insignificant in summer probably as a result of stronger meridional mixing. Aircraft measurements showed no significant vertical variation in GEM over the field campaign regions; however, depletion of GEM was observed in stratospherically influenced air masses. In examining the remaining questions and issues, recommendations for future research needs were provided, and among them is the most imminent need for GOM speciation measurements and fundamental understanding of multiphase redox kinetics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".