Global Biogeochemical Implications of Mercury Discharges from Rivers and Sediment Burial

Abstract

Rivers are an important source of mercury (Hg) to marine ecosystems. Based on an analysis of compiled observations, we estimate global present-day Hg discharges from rivers to ocean margins are 27 ± 13 Mmol a(-1) (5500 ± 2700 Mg a(-1)), of which 28% reaches the open ocean and the rest is deposited to ocean margin sediments. Globally, the source of Hg to the open ocean from rivers amounts to 30% of atmospheric inputs. This is larger than previously estimated due to accounting for elevated concentrations in Asian rivers and variability in offshore transport across different types of estuaries. Riverine inputs of Hg to the North Atlantic have decreased several-fold since the 1970s while inputs to the North Pacific have increased. These trends have large effects on Hg concentrations at ocean margins but are too small in the open ocean to explain observed declines of seawater concentrations in the North Atlantic or increases in the North Pacific. Burial of Hg in ocean margin sediments represents a major sink in the global Hg biogeochemical cycle that has not been previously considered. We find that including this sink in a fully coupled global biogeochemical box model helps to balance the large anthropogenic release of Hg from commercial products recently added to global inventories. It also implies that legacy anthropogenic Hg can be removed from active environmental cycling on a faster time scale (centuries instead of millennia). Natural environmental Hg levels are lower than previously estimated, implying a relatively larger impact from human activity.

Benefits of mercury controls for the United States

“…Our GEOS-Chem simulations take into account the effect of anthropogenic emissions changes on concentrations of mercury in surface reservoirs only, and consequently underestimate the total deposition benefits attributable to policy. To roughly estimate the extent of this underestimation, we use a seven-box, biogeochemical model developed by Amos et al (28,29), which captures the deep ocean and soil reservoirs, but not the spatial distribution of impacts (SI Appendix, Chemical transport modeling). We find that globally, deposition reductions under policy are ∼30% larger when taking into account enrichment of these subsurface pools.…”

Observed decrease in atmospheric mercury explained by global decline in anthropogenic emissions

“…The concentrations of major oxidants for atmospheric Hg 0 , including OH, O 3 , and Br, have remained relatively steady or slightly decreased since the mid-1990s and are thus not an important driver for the observed decline (5). Decreasing riverine discharges, which was previously speculated to drive the decline in North Atlantic Ocean Hg concentration and subsequent reemission flux (6), are also insufficient for forcing the global atmospheric trend (31,33).…”

Constraints from observations and modeling on atmosphere–surface exchange of mercury in eastern North America

“…Terrestrial emissions in some other models are mapped according to biogenic CO emission and/or historical Hg deposition and scaled by global Hg budgets Chen et al, 2015;Jung et al, 2009). Simulated global Hg 0 fluxes from terrestrial surfaces range from -1300 to 3500 Mg yr -1 Chen et al, 2015;Lei et al, 2013;Corbitt et al, 2011;SmithDowney et al, 2010;Kikuchi et al, 2013;Amos et al, 2013Amos et al, , 2014De Simone et al, 2014). Net Hg 0 fluxes from the contiguous United States may also be positive or negative based on flux scaling methods (-183 to 269 Mg yr -1 , 50% uncertainty range; Agnan et al, 2016) and a newly developed bidirectional exchange model (118-141 Mg yr -1 , Wang et al, 2014).…”

“…Most surface ocean waters have been observed to be supersaturated in DGM, generating a positive net flux of Hg 0 to the atmosphere (Sprovieri et al, 2010;Soerensen et al, 2014;Kuss et al, 2011;Ci et al, 2011a). Global Hg 0 fluxes from oceanic surfaces have been estimated in the range of 800-5500 Mg yr -1 by different numerical models Soerensen et al, 2010;Zhang et al, 2014;De Simone et al, 2014;Lei et al, 2013;Chen et al, 2015;Amos et al, 2013Amos et al, , 2014Sunderland and Mason, 2007) and using flux scaling methods (Mason and Sheu, 2002).…”