Temporal Variability of Atmospheric Total Gaseous Mercury in Windsor, ON, Canada

Xu, Xiaohong; Akhtar, Umme S.; Clark, Kyle; Wang, Xiaobin

doi:10.3390/atmos5030536

Cited by 11 publications

(17 citation statements)

References 36 publications

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“…All papers reported differences between the subsets and between the full data set and the subsets to some extent (Gao, 2007;Parsons et al, 2013, Xu et al, 2014. In the 2007-2011 Windsor, Ontario, TGM study (Xu et al, 2014), seasonal PCA revealed that the transport component seems to be very influential to TGM concentrations due to high winds. The impact of GEM oxidation was more easily extracted from the springtime data because there are less confounding factors, e.g., re-emission of GEM.…”

Section: Pca Results From Data Subsetsmentioning

confidence: 99%

“…The Canadian sites are located in Point Petre and Egbert, Ontario (Blanchard et al, 2002); CAMNet stations (Temme et al, 2007), Toronto (Cheng et al, 2009), northwestern Ontario (Cheng et al, 2012); Kejimkujik National Park (Cheng et al, 2013a); Flin Flon, Manitoba (Eckley et al, 2013); Fort McMurray, Alberta (Parsons et al, 2013); and Windsor, Ontario (Xu et al, 2014). The US sites included south Florida (Graney et al, 2004); Detroit, Michigan (Lynam and Keeler, 2006;Liu et al, 2007); Mount Bachelor, Oregon (Swartzendruber et al, 2006); Athens, Ohio (Gao, 2007); Rochester, New York (Huang et al, 2010); and Grand Bay, Mississippi (Ren et al, 2014).…”

Section: Source Apportionmentmentioning

confidence: 99%

“…The percent variance that can be explained by anthropogenic combustion sources varied from 10 to 57 % among the studies reviewed. It explained most of the variance (> 35 %) at some urban locations, such as in Seoul, Toronto, Windsor, and south Florida because of the proximity to Hg point sources and/or traffic (Kim and Kim, 2001;Graney et al, 2004;Cheng et al, 2009;Xu et al, 2014). At rural locations further away from Hg point sources and traffic, 15-29 % of the variance was explained by the transport of anthropogenic combustion emissions (Blanchard et al, 2002;Cheng et al, 2012Cheng et al, , 2013a.…”

Section: Source Apportionmentmentioning

confidence: 99%

“…This component included strong positive component loadings on GOM, O 3 , temperature and wind speed, and negative loadings on relative humidity (Lynam and Keeler, 2006). Other studies also extracted a component representative of GEM oxidation with similar pollutant or meteorological parameter loadings; however, the component did not explain the most variance with percentages ranging from 11 to 27 % (Li et al, 2008;Huang et al, 2010;Cheng et al, 2012Cheng et al, , 2013aRen et al, 2014;Xu et al, 2014). GEM oxidation was also inferred from a PCA component containing GOM, BrO and O 3 (Ren et al, 2014).…”

Section: Source Apportionmentmentioning

confidence: 99%

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Overview of receptor-based source apportionment studies for speciated atmospheric mercury

Cheng

Zhang

2015

Atmos. Chem. Phys.

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Abstract. Receptor-based source apportionment studies of speciated atmospheric mercury are not only concerned with source contributions but also with the influence of transport, transformation, and deposition processes on speciated atmospheric mercury concentrations at receptor locations. Previous studies applied multivariate receptor models including principal components analysis and positive matrix factorization, and back trajectory receptor models including potential source contribution function, gridded frequency distributions, and concentration-back trajectory models. Combustion sources (e.g., coal combustion, biomass burning, and vehicular, industrial and waste incineration emissions), crustal/soil dust, and chemical and physical processes, such as gaseous elemental mercury (GEM) oxidation reactions, boundary layer mixing, and GEM flux from surfaces were inferred from the multivariate studies, which were predominantly conducted at receptor sites in Canada and the US. Back trajectory receptor models revealed potential impacts of large industrial areas such as the Ohio River valley in the US and throughout China, metal smelters, mercury evasion from the ocean and the Great Lakes, and free troposphere transport on receptor measurements. Input data and model parameters specific to atmospheric mercury receptor models are summarized and model strengths and weaknesses are also discussed. Multivariate models are suitable for receptor locations with intensive air monitoring because they require long-term collocated and simultaneous measurements of speciated atmospheric Hg and ancillary pollutants. The multivariate models provide more insight about the types of Hg emission sources and Hg processes that could affect speciated atmospheric Hg at a receptor location, whereas back trajectory receptor models are mainly ideal for identifying potential regional Hg source locations impacting elevated Hg concentrations. Interpretation of the multivariate model output to sources can be subjective and challenging when speciated atmospheric Hg is not correlated with ancillary pollutants and when source emissions profiles and knowledge of Hg chemistry are incomplete. The majority of back trajectory receptor models have not accounted for Hg transformation and deposition processes and could not distinguish between upwind and downwind sources effectively. Ensemble trajectories should be generated to take into account the trajectory uncertainties where possible. One area of improvement that applies to all the receptor models reviewed in this study is the greater focus on evaluating the accuracy of the models at identifying potential speciated atmospheric mercury sources, source locations, and chemical and physical processes in the atmosphere. In addition to receptor model improvements, the data quality of speciated atmospheric Hg plays an equally important part in producing accurate receptor model results.

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Section: Pca Results From Data Subsetsmentioning

confidence: 99%

Section: Source Apportionmentmentioning

confidence: 99%

Section: Source Apportionmentmentioning

confidence: 99%

Section: Source Apportionmentmentioning

confidence: 99%

See 2 more Smart Citations

Overview of receptor-based source apportionment studies for speciated atmospheric mercury

Cheng

Zhang

2015

Atmos. Chem. Phys.

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“…Wintertime annual maximums were probably attributed to more coal combustion to produce energy for space heating, less oxidation of GEM (Stamenkovic et al, 2007), and periods of cold and stagnant air probably leading to buildup of pollution and more Hg evasion prompted by wet conditions (Peterson et al, 2009). Temporal variations in GEM concentrations could be attributed to the combined influence of environmental variables, anthropogenic sources, photochemistry, and regional transport (Xu et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Impacts of large-scale circulation on urban ambient concentrations of gaseous elemental mercury in New York, USA

Mao

Hall

et al. 2017

Atmos. Chem. Phys.

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Abstract. The impact of large-scale circulation on urban gaseous elemental mercury (GEM) was investigated through analysis of 2008-2015 measurement data from an urban site in New York City (NYC), New York, USA. Distinct annual cycles were observed in 2009-2010 with mixing ratios in warm seasons (i.e., spring-summer) 10-20 ppqv ( ∼ 10-25 %) higher than in cool seasons (i.e., fall-winter). This annual cycle was disrupted in 2011 by an anomalously strong influence of the US East Coast trough in that warm season and was reproduced in 2014 associated with a particularly strong Bermuda High. The US East Coast trough axis index (TAI) and intensity index (TII) were used to characterize the effect of the US East Coast trough on NYC GEM, especially in winter and summer. The intensity and position of the Bermuda High appeared to have a significant impact on GEM in warm seasons. Regional influence on NYC GEM was supported by the GEM-carbon monoxide (CO) correlation with r of 0.17-0.69 (p ∼ 0) in most seasons. Simulated regional and local anthropogenic contributions to wintertime NYC anthropogenically induced GEM concentrations were averaged at ∼ 75 % and 25 %, with interannual variation ranging over 67 %-83 % and 17 %-33 %, respectively. Results from this study suggest the possibility that the increasingly strong Bermuda High over the past decades could dominate over anthropogenic mercury emission control in affecting ambient concentrations of mercury via regional buildup and possibly enhancing natural and legacy emissions.

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Soil-air exchange of mercury from agricultural fields in Zhejiang, East China: Seasonal variations, influence factors, and models of fluxes

Shi

Gong

et al. 2020

Chemosphere

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Temporal Variability of Atmospheric Total Gaseous Mercury in Windsor, ON, Canada

Cited by 11 publications

References 36 publications

Overview of receptor-based source apportionment studies for speciated atmospheric mercury

Overview of receptor-based source apportionment studies for speciated atmospheric mercury

Impacts of large-scale circulation on urban ambient concentrations of gaseous elemental mercury in New York, USA

Soil-air exchange of mercury from agricultural fields in Zhejiang, East China: Seasonal variations, influence factors, and models of fluxes

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