Source–receptor relationships for atmospheric mercury in urban Detroit, Michigan

Lynam, Mary M.; Keeler, Gerald J.

doi:10.1016/j.atmosenv.2006.01.026

Cited by 72 publications

(65 citation statements)

References 25 publications

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“…This component generally consisted of high component loadings on Hg and other air pollutant markers, such as NO x , SO 2 , O 3 , PM 2.5 , black carbon, CO, and/or trace metals. A component consisting of GEM, NO x , and CO was attributed to vehicular emissions in Detroit (Lynam and Keeler, 2006). Graney et al (2004) was able to narrow down the PBM source in south Florida to waste incineration because of the presence of PBM, V and Ni in one of the components.…”

Section: Source Apportionmentmentioning

confidence: 97%

“…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).…”

Section: Source Apportionmentmentioning

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). Most of the studies identified a factor/component that was representative of combustion sources (e.g., coal combustion, vehicular, industrial, biomass burning, and waste incineration emissions) regardless of whether the studies were conducted in urban, rural, or coastal locations.…”

Section: Source Apportionmentmentioning

confidence: 99%

“…There are several statistics that have been determined to assess whether the data set is suitable for PCA, such as the Kaiser-MeyerOlkin measure of sampling adequacy (> 0.6 criterion) and Bartlett's test of sphericity (p < 0.05 criterion). The number of components to retain is determined by other statistics such as Kaiser's criterion (eigenvalues > 1), scree plot, analysis of variance, and/or parallel analysis, as well as by achieving some minimal value of percent variance of the data set explained by all the components (e.g., 70-80 %) and how easily the components can be interpreted (Blanchard et al, 2002;Lynam and Keeler, 2006;Temme et al, 2007;Cheng et al, 2009). The number of components in a suitable solution to Eq.…”

Section: Principal Components Analysis (Pca) Descriptionmentioning

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: Source Apportionmentmentioning

confidence: 97%

Section: Source Apportionmentmentioning

confidence: 99%

Section: Source Apportionmentmentioning

confidence: 99%

Section: Principal Components Analysis (Pca) Descriptionmentioning

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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“…These observations were typically attributed to major sources of Hg surrounding the urban sites, such as coal-fired power plants and industrial facilities. However, not all urban sites were located near combustion and industrial sources; therefore in these cases, the sources were attributed to regional and long-range transport of Hg emissions and local vehicular emissions and surface emissions (Lynam and Keeler, 2006;Cheng et al, 2009;Xu and Akhtar, 2010).…”

Section: Introductionmentioning

confidence: 99%

Concentration-weighted trajectory approach to identifying potential sources of speciated atmospheric mercury at an urban coastal site in Nova Scotia, Canada

Cheng¹,

et al. 2013

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Regional and local sources contributing to gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particle-bound mercury (PBM) at an urban coastal site in Dartmouth, Nova Scotia, Canada were investigated using the Concentration-Weighted Trajectory model (CWT) and Conditional Probability Function. From 2010–2011, GEM, GOM, and PBM concentrations were 1.67 ± 1.01 ng m⁻³, 2.07 ± 3.35 pg m⁻³, and 2.32 ± 3.09 pg m⁻³, respectively. Seasonal variability was observed, with statistically higher GEM and PBM concentrations in winter and spring and higher GOM in spring. In the CWT, concentrations are the weighting factors for the trajectory residence time in modeled grid cells, which results in the identification of source areas based on the CWT values in the grid cells. Potential source areas were identified in regions with known industrial Hg sources particularly in the fall season, but also in regions without these sources (e.g. Atlantic Ocean, northern Ontario and Quebec). CWTs for GOM and PBM that were associated with ≥ 5 kg industrial Hg emissions from 2010–2011 were statistically larger than those with zero Hg emissions, despite a lack of strong correlations. A large proportion of elevated CWTs (85–97%) was in regions with zero industrial Hg sources indicating the potential role of non-point sources, natural emissions, and residential-scale combustion. Analysis of wind data suggests that a commercial harbor and vehicular traffic were potential local sources. Evaluating modeled source areas against Hg emissions inventories was not an ideal method for assessing the CWT model accuracy because of insufficient data on Hg emissions at more precise locations

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Comparisons of mercury sources and atmospheric mercury processes between a coastal and inland site

Cheng¹,

Zhang

Blanchard

et al. 2013

JGR Atmospheres

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[1] Comparisons of mercury sources and atmospheric mercury processes were conducted between a coastal and inland site in northeastern North America. Identifying sources of atmospheric Hg is essential for understanding what is potentially contributing to Hg bioaccumulation at these two sites. A data set consisting of gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), particle-bound mercury, ozone, trace gases, particulate ions, and meteorological data were analyzed using principal components analysis (PCA), absolute principal component scores (APCS), and back trajectories. The PCA factors representing gaseous Hg condensation on particles during winter and combustion and industrial sources were found at both sites. However, the PCA factor for combustion/industrial sources was not found in 2010 at either site, likely because of SO 2 emissions reductions from coal utilities from 2008 to 2010. Using APCS and back trajectories, the combustion/industrial factor at the coastal site was narrowed down to shipping ports along the Atlantic coast. Hg sources affecting coastal sites are different from those affecting inland sites because of the influence of marine airflows. GEM evasion from the ocean was evident from a PCA factor containing GEM, relative humidity, wind speed, and precipitation along with significantly higher contributions of this source (APCS) from oceanic trajectories compared to land/coastal trajectories. Analysis of the effects of ozone and water vapor mixing ratio on %GOM/total gaseous mercury suggest that Hg-Br photochemistry occurred at lower ozone concentrations (<40 ppb) at the coastal site and the absence of free troposphere transport of GOM.Citation: Cheng, I., L. Zhang, P. Blanchard, J. Dalziel, R. Tordon, J. Huang, and T. M. Holsen (2013), Comparisons of mercury sources and atmospheric mercury processes between a coastal and inland site,

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Source–receptor relationships for atmospheric mercury in urban Detroit, Michigan

Cited by 72 publications

References 25 publications

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

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

Concentration-weighted trajectory approach to identifying potential sources of speciated atmospheric mercury at an urban coastal site in Nova Scotia, Canada

Comparisons of mercury sources and atmospheric mercury processes between a coastal and inland site

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