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

Abstract

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.

Isotopic Composition of Gaseous Elemental Mercury in the Marine Boundary Layer of East China Sea

“…However, given the large number of trajectory endpoints utilized in PSCF and PBCF modeling, the uncertainty of the locations of identified source region is substantially reduced. Besides, the "trailing effect," selection of concentration threshold, transformation, and deposition of atmospheric Hg during transport can affect the PSCF and PBCF receptor model (Cheng et al, 2015), which were not evaluated in the present study. Therefore, the identified source regions of elevated and low atmospheric GEM should be regarded as potential source contributors only.…”

Observations of aerosol optical properties at a coastal site in Hong Kong, South China

“…(3) is that it shows the average value of the property x observed at the receiving site when air masses have come from over grid cell i, j . The method is analogous to that presented by Stohl et al (1996) and the concentration-weighted trajectory (CWT) methods reviewed by Cheng et al (2015). The major difference is that in the present approach, the footprints were used instead of single trajectories for each time step.…”

A synthesis of research needs for improving the understanding of atmospheric mercury cycling

“…With an increasing geographical coverage of speciated Hg data, receptor-based source apportionment analysis has been utilized for quantifying contributions to the observed ambient Hg concentrations (Cheng et al, 2015a). Results generated from these analyses should be carefully compared to the results of source-based approaches, which may have the potential to improve natural emission inventories that can then be used in improving CTMs performance.…”

“…Observations of speciated atmospheric Hg have been used in identifying Hg source-receptor relationships (Cheng et al, 2015a, and references therein), understanding Hg cycling, gas-particle partitioning and oxidation mechanisms (Amo et al, 2012;Cheng et al, 2014;Gabay et al, 2017;Obrist et al, 2011;Shah et al, 2016;Timonen et al, 2013;Ye et al, 2016), evaluating Hg transport models Gustin et al, 2015;Kos et al, 2013;Weiss-Penzias et al, 2015) and quantifying Hg deposition budgets (Amo et al, 2012;Cheng et al, 2015b;Zhang et al, 2016b). Limited long-term data have also been applied in assessing Hg trends in the atmosphere and the effects of emission control policies (Brown et al, 2015;Castro and Sherwell, 2015;Cole et al, 2013Cole et al, , 2014Martin et al, 2017;Steffen et al, 2005).…”

“…A global observational flux database of the atmosphere-surface exchange of GEM was developed and the implication of the flux data to global Hg budgets was discussed in Zhu et al (2016). Receptor-based source apportionment studies using speciated Hg were summarized in Cheng et al (2015a), and studies related to speciated Hg in China were reviewed in Fu et al (2015).…”