Mercury(编程语言)
环境化学
环境科学
沉积(地质)
化学
地质学
计算机科学
沉积物
古生物学
程序设计语言
作者
Xun Wang,Zhengduo Bao,Che‐Jen Lin,Wei Yuan,Xinbin Feng
标识
DOI:10.1021/acs.est.5b06351
摘要
There is a large uncertainty in the estimate of global dry deposition of atmospheric mercury (Hg). Hg deposition through litterfall represents an important input to terrestrial forest ecosystems via cumulative uptake of atmospheric Hg (most Hg(0)) to foliage. In this study, we estimate the quantity of global Hg deposition through litterfall using statistical modeling (Monte Carlo simulation) of published data sets of litterfall biomass production, tree density, and Hg concentration in litter samples. On the basis of the model results, the global annual Hg deposition through litterfall is estimated to be 1180 ± 710 Mg yr(-1), more than two times greater than the estimate by GEOS-Chem. Spatial distribution of Hg deposition through litterfall suggests that deposition flux decreases spatially from tropical to temperate and boreal regions. Approximately 70% of global Hg(0) dry deposition occurs in the tropical and subtropical regions. A major source of uncertainty in this study is the heterogeneous geospatial distribution of available data. More observational data in regions (Southeast Asia, Africa, and South America) where few data sets exist will greatly improve the accuracy of the current estimate. Given that the quantity of global Hg deposition via litterfall is typically 2-6 times higher than Hg(0) evasion from forest floor, global forest ecosystems represent a strong Hg(0) sink.
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