2 resultados para wet deposition

em Digital Commons - Michigan Tech


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Since it is very toxic and accumulates in organisms, particularly in fish, mercury is a very important pollutant and one of the most studies. And this concern over the toxicity and human health risks of mercury has prompted efforts to regulate anthropogenic emissions. As mercury pollution problem is getting increasingly serious, we are curious about how serious this problem will be in the future. What is more, how the climate change in the future will affect the mercury concentration in the atmosphere. So we investigate the impact of climate change on mercury concentration in the atmosphere. We focus on the comparison between the mercury data for year 2000 and for year 2050. The GEOS-Chem model shows that the mercury concentrations for all tracers (1 to 3), elemental mercury (Hg(0)), divalent mercury (Hg(II)) and primary particulate mercury (Hg(P)) have differences between 2000 and 2050 in most regions over the world. From the model results, we can see the climate change from 2000 to 2050 would decrease Hg(0) surface concentration in most of the world. The driving factors of Hg(0) surface concentration changes are natural emissions(ocean and vegetation) and the transformation reactions between Hg(0) and Hg(II). The climate change from 2000 to 2050 would increase Hg(II) surface concentration in most of mid-latitude continental parts of the world while decreasing Hg(II) surface concentration in most of high-latitude part of the world. The driving factors of Hg(II) surface concentration changes is deposition amount change (majorly wet deposition) from 2000 to 2050 and the transformation reactions between Hg(0) and Hg(II). Climate change would increase Hg(P) concentration in most of mid-latitude area of the world and meanwhile decrease Hg(P) concentration in most of high-latitude regions of the world. For the Hg(P) concentration changes, the major driving factor is the deposition amount change (mainly wet deposition) from 2000 to 2050.

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A mass‐balance model for Lake Superior was applied to polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), and mercury to determine the major routes of entry and the major mechanisms of loss from this ecosystem as well as the time required for each contaminant class to approach steady state. A two‐box model (water column, surface sediments) incorporating seasonally adjusted environmental parameters was used. Both numerical (forward Euler) and analytical solutions were employed and compared. For validation, the model was compared with current and historical concentrations and fluxes in the lake and sediments. Results for PCBs were similar to prior work showing that air‐water exchange is the most rapid input and loss process. The model indicates that mercury behaves similarly to a moderately‐chlorinated PCB, with air‐water exchange being a relatively rapid input and loss process. Modeled accumulation fluxes of PBDEs in sediments agreed with measured values reported in the literature. Wet deposition rates were about three times greater than dry particulate deposition rates for PBDEs. Gas deposition was an important process for tri‐ and tetra‐BDEs (BDEs 28 and 47), but not for higher‐brominated BDEs. Sediment burial was the dominant loss mechanism for most of the PBDE congeners while volatilization was still significant for tri‐ and tetra‐BDEs. Because volatilization is a relatively rapid loss process for both mercury and the most abundant PCBs (tri‐ through penta‐), the model predicts that similar times (from 2 ‐ 10 yr) are required for the compounds to approach steady state in the lake. The model predicts that if inputs of Hg(II) to the lake decrease in the future then concentrations of mercury in the lake will decrease at a rate similar to the historical decline in PCB concentrations following the ban on production and most uses in the U.S. In contrast, PBDEs are likely to respond more slowly if atmospheric concentrations are reduced in the future because loss by volatilization is a much slower process for PBDEs, leading to lesser overall loss rates for PBDEs in comparison to PCBs and mercury. Uncertainties in the chemical degradation rates and partitioning constants of PBDEs are the largest source of uncertainty in the modeled times to steady‐state for this class of chemicals. The modeled organic PBT loading rates are sensitive to uncertainties in scavenging efficiencies by rain and snow, dry deposition velocity, watershed runoff concentrations, and uncertainties in air‐water exchange such as the effect of atmospheric stability.