RESEARCH ARTICLE · Journal of the Atmospheric Sciences · 2019

Atmospheric Chemistry of Gaseous Oxidized Mercury at a Coastal Site in Atlantic Canada

Irene Cheng, Leiming Zhang, Huiting Mao, Zhuyun Ye, Robert Keenan

Read original paper ↗

See where this research leads.

A citation map has not been saved for this paper yet.

Open in your workspace →Open your workspace to prepare the citation network.

The paper record is available below. Preparing a network uses the existing account and source-allowance controls.

Papers that cite this work

No saved citation network is available; this does not mean the paper has no citations.

The evidence behind the map

Publication record

Research article.

Abstract

Abstract A chemistry box model containing a comprehensive suite of mercury (Hg) oxidation mechanisms involving O3, OH, H2O2, Br, BrO, NO2, HO2, and other oxidants was used to simulate the formation of gaseous oxidized mercury (GOM) and understand the chemical processes driving the observed trends in GOM at Kejimkujik, Nova Scotia, Canada. Simulations were conducted using chemical schemes with and without oxidation by O3 and OH. The major oxidants of Hg are O3 and OH (79%), H2O2 (10%), Br with second-stage HgBr oxidation by NO2 (7%), and BrO (3%) in simulations where all GEM oxidation reactions were considered simultaneously. In an alternative chemical scheme without gas-phase oxidation by O3 and OH, the dominant GOM species were HgBrNO2 (58%) and HgBrO (23.5%). Using this chemical scheme, the model reproduced the observed GOM at sub-ppqv Br2 mixing ratios. In the scheme with O3 and OH, the variability in GOM between seasons and between continental and marine air masses was mainly due to the variability in gaseous elemental Hg, O3, OH, and aerosol liquid water content (LWC). LWC governs the partitioning of GOM to the aerosol aqueous phase in the model. In the scheme without O3 and OH, the variability in GOM by season and airmass origin strongly depends on Br and BrO, suggesting that rigorous validation of modeled Br and BrO data are essential for improving the model predictions of GOM in coastal environments.

Coverage and freshness

Citation coverage has not been established for this paper.

Counts describe saved source records; repository versions may appear separately. A completed source query is not a complete or live citation census. A citation does not prove endorsement or research quality. Counts depend on publication age and index coverage. Colors identify research areas; positions are for readability.

Source: Saved OpenAlex scholarly metadata. Visits to this public page do not acquire new provider data.

Report a correction