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An Anaerobic Biosensor Assay for the Detection of Mercury and Cadmium
Published on: December 17, 2018
Particulate organic matter governs the vulnerability of soil mercury in Himalayan valleys
Huhu Kang1, Miaoxin Ji2, Junming Guo3
1School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China; State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China.
Abstract:
Understanding mercury (Hg) sequestration in soils requires moving beyond bulk soil measurements to resolve the functionally distinct organic matter pools that govern Hg stability. Here we quantify Hg partitioning across particulate (POM) and mineral-associated (MAOM) organic matter in five Himalayan valleys, critical transboundary corridors for atmospheric Hg transport. MAOM contained markedly elevated Hg concentrations (1.0-268.1 ng g⁻¹, mean ± SD = 49.2 ± 51.3 ng g⁻¹), with values 1.8- to 2.9-fold higher than those of particulate organic matter (POM). When subdivided, coarse POM (cPOM) spanned 2.3-244.7 ng g⁻¹ (56.4 ± 47.8 ng g⁻¹), while fine POM (fPOM) ranged from 5.0 to 409.9 ng g⁻¹ (89.8 ± 54.3 ng g⁻¹). Combined POM fractions accounted for 67.9% of the total soil Hg pool, highlighting a fundamental duality: MAOM functions as a stable, Hg-concentrated sink, whereas POM represents the dominant yet potentially labile Hg reservoir. Drivers shift systematically: coarse POM is controlled by eight key significant factors (carbon, nitrogen, microbes, metal oxides), whereas MAOM is governed primarily by two core factors among the measured variables, microbial biomass and soil moisture. This shift delineates two distinct sequestration pathways, litterfall-driven incorporation in POM versus microbially mediated stabilization in MAOM, with largely different implications for Hg stability under environmental change. Soil fractionation thus provides a transferable framework for integrating functionally distinct Hg pools into global models and assessing risks in mountain ecosystems.
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