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Methylation index as means of quantification of the compliance of sedimentary mercury to be methylated
Methylmercury (MeHg) is the most bioavailable and toxic mercury species in the marine environment. MeHg concentration levels, methylation rates leading to MeHg formation, and methylation index (MI) are all used to assess the compliance of mercury to be methylated in the marine sedimentary environmen...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4498312/ https://www.ncbi.nlm.nih.gov/pubmed/26160740 http://dx.doi.org/10.1007/s10661-015-4716-y |
Sumario: | Methylmercury (MeHg) is the most bioavailable and toxic mercury species in the marine environment. MeHg concentration levels, methylation rates leading to MeHg formation, and methylation index (MI) are all used to assess the compliance of mercury to be methylated in the marine sedimentary environment. This paper reports on the works conducted on the MI upgrade. This paper proposes a new formula for calculating MI. Apart from labile mercury(II) and organic matter, it includes redox potential and abundance of sulfur-reducing bacteria (SRB), both essential factors for MeHg generation. The obtained MI is validated against actual sedimentary MeHg concentrations proving the potential usefulness of MI as a factor characterizing status of sedimentary environment regarding possible occurrence of MeHg. Moreover, values of the methylation index in particular regions show that MI values correspond well to environmental conditions in those areas. The values calculated correlate well with MeHg concentrations; however, the correlation coefficients vary between different regions. This has been attributed to the lack of empirical coefficients. Thus, MI could be used as a characteristic of the sedimentary environment indicating the potential presence of MeHg. It could also be used in methylation rate modeling, provided that empirical constants are applied to improve model performance. |
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