Abstract. Atmospheric deposition of Hg(II) represents a major input of mercury to surface environments. The phase of Hg(II) (gas or particle) has important implications for deposition. We use long-term observations of reactive gaseous mercury (RGM, the gaseous component of Hg(II)), particle-bound mercury (PBM, the particulate component of Hg(II)), fine particulate matter (PM 2.5 ), and temperature (T ) at five sites in North America to derive an empirical gas-particle partitioning relationship log 10 (K −1 ) = (10±1)-(2500±300)/T where K = (PBM/PM 2.5 )/RGM with PBM and RGM in common mixing ratio units, PM 2.5 in µg m −3 , and T in K. This relationship is within the range of previous work but is based on far more extensive data from multiple sites. We implement this empirical relationship in the GEOS-Chem global 3-D Hg model to partition Hg(II) between the gas and particle phases. The resulting gas-phase fraction of Hg(II) ranges from over 90 % in warm air with little aerosol to less than 10 % in cold air with high aerosol. Hg deposition to high latitudes increases because of more efficient scavenging of particulate Hg(II) by precipitating snow. Model comparison to Hg observations at the North American surface sites suggests that subsidence from the free troposphere (warm air, low aerosol) is a major factor driving the seasonality of RGM, while elevated PBM is mostly associated with high aerosol loads. Simulation of RGM and PBM at these sites is improved by including fast in-plume reduction of Hg(II) emitted from coal combustion and by assuming that anthropogenic particulate Hg(p) behaves as semivolatile Hg(II) rather than as a refractory particulate component. We improve the simulation of Hg wet deposition fluxes in the US relative to a previous version of GEOS-Chem; this largely reflects independent improvement of the washout algorithm. The observed wintertime minimum in wet deposition fluxes is attributed to inefficient snow scavenging of gas-phase Hg(II).
Atmospheric deposition represents a major input of mercury to surface environments. The phase of mercury (gas or particle) has important implications for its removal from the atmosphere. We use long-term observations of reactive gaseous mercury (RGM), particle-bound mercury (PBM), fine particulate matter (PM<sub>2.5</sub>), and temperature at five sites in North America to derive an empirical gas-particle partitioning relationship log<sub>10</sub>(<i>K</i><sup>-1</sup>) = (10 ± 1) − (2500 ± 300)/<i>T</i> where <i>K</i> = (PBM/PM<sub>2.5</sub>)/RGM with PBM and RGM in common mixing ratio units, PM<sub>2.5</sub> in μg m<sup>−3</sup>, and <i>T</i> in Kelvin. This relationship is in the range of previous work but is based on far more extensive data from multiple sites. We implement this empirical relationship in the GEOS-Chem global 3-D Hg model to partition divalent mercury (Hg(II)). The resulting gas-phase fraction of Hg(II) ranges from over 90% in warm air with little aerosol to less than 10% in cold air with high aerosol. Hg deposition to high latitudes increases because of more efficient scavenging of particulate Hg(II) by snow. Model comparison to Hg observations at surface sites suggests that subsidence from the free troposphere (warm air, low aerosol) is a major factor driving the seasonality of RGM, while elevated PBM is mostly associated with high aerosol loads. This and other model updates, including the correction of an outstanding algorithm error, to wet deposition improve the simulation of Hg wet deposition fluxes in the US relative to the previous version of the model. The observed wintertime minimum in wet deposition fluxes is attributed to inefficient snow scavenging of gas-phase Hg(II)
This air synthesis review presents the current state of knowledge on the sources, fates, and effects for polycyclic aromatic compounds (PACs) and related chemicals released to air in the oil sands region (OSR) in Alberta, Canada. Through the implementation of the Joint Canada–Alberta Oil Sands Monitoring Program in 2012 a vast amount of new information on PACs has been acquired through directed monitoring and research projects and reported to the scientific community and public. This new knowledge addresses questions related to cumulative effects and informs the sustainable management of the oil sands resource while helping to identify gaps in understanding and priorities for future work. As a result of this air synthesis review on PACs, the following topics have been identified as new science priorities: (i) improving emissions reporting to better account for fugitive mining emissions of PACs that includes a broader range of PACs beyond the conventional polycyclic aromatic hydrocarbons (PAHs) including, inter alia, alkylated-PAHs (alk-PAHs), dibenzothiophene (DBT), alk-DBTs, nitro-PAHs, oxy-PAHs including quinones and thia- and aza-arenes; (ii) improving information on the ambient concentrations, long-range transport, and atmospheric deposition of these broader classes of PACs and their release (with co-contaminants) from different types of mining activities; (iii) further optimizing electricity-free and cost-effective approaches for assessing PAC deposition (e.g., snow sampling, lichens, passive ambient sampling) spatially across the OSR and downwind regions; (iv) designing projects that integrate monitoring efforts with source attribution models and ecosystem health studies to improve understanding of sources, receptors, and effects; (v) further optimizing natural deposition archives (e.g., sediment, peat, tree rings) and advanced forensic techniques (e.g., isotope analysis, marker compounds) to provide better understanding of sources of PACs in the OSR over space and time; (vi) conducting process research to improve model capabilities for simulating atmospheric chemistry of PACs and assessing exposure to wildlife and humans; and (vii) developing tools and integrated strategies for assessing cumulative risk to wildlife and humans by accounting for the toxicity of the mixture of chemicals in air rather than on a single compound basis.
Abstract. The offline Eulerian AURAMS (A Unified Regional Air quality Modelling System) chemical transport model was adapted to simulate airborne concentrations of seven PAHs (polycyclic aromatic hydrocarbons): phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene, chrysene + triphenylene, and benzo[a]pyrene. The model was then run for the year 2002 with hourly output on a grid covering southern Canada and the continental USA with 42 km horizontal grid spacing. Model predictions were compared to ~5000 24 h-average PAH measurements from 45 sites, most of which were located in urban or industrial areas. Eight of the measurement sites also provided data on particle/gas partitioning which had been modelled using two alternative schemes. This is the first known regional modelling study for PAHs over a North American domain and the first modelling study at any scale to compare alternative particle/gas partitioning schemes against paired field measurements. The goal of the study was to provide output concentration maps of use to assessing human inhalation exposure to PAHs in ambient air. Annual average modelled total (gas + particle) concentrations were statistically indistinguishable from measured values for fluoranthene, pyrene and benz[a]anthracene whereas the model underestimated concentrations of phenanthrene, anthracene and chrysene + triphenylene. Significance for benzo[a]pyrene performance was close to the statistical threshold and depended on the particle/gas partitioning scheme employed. On a day-to-day basis, the model simulated total PAH concentrations to the correct order of magnitude the majority of the time. The model showed seasonal differences in prediction quality for volatile species which suggests that a missing emission source such as air–surface exchange should be included in future versions. Model performance differed substantially between measurement locations and the limited available evidence suggests that the model's spatial resolution was too coarse to capture the distribution of concentrations in densely populated areas. A more detailed analysis of the factors influencing modelled particle/gas partitioning is warranted based on the findings in this study.
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