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. 2018 May 15;52(10):5851-5858.
doi: 10.1021/acs.est.7b05730. Epub 2018 Apr 27.

Phytoremediation Reduces Dust Emissions from Metal(loid)-Contaminated Mine Tailings

Phytoremediation Reduces Dust Emissions from Metal(loid)-Contaminated Mine Tailings

Juliana Gil-Loaiza et al. Environ Sci Technol. .

Abstract

Environmental and health risk concerns relating to airborne particles from mining operations have focused primarily on smelting activities. However, there are only three active copper smelters and less than a dozen smelters for other metals compared to an estimated 500000 abandoned and unreclaimed hard rock mine tailings in the US that have the potential to generate dust. The problem can also extend to modern tailings impoundments, which may take decades to build and remain barren for the duration before subsequent reclamation. We examined the impact of vegetation cover and irrigation on dust emissions and metal(loid) transport from mine tailings during a phytoremediation field trial at the Iron King Mine and Humboldt Smelter Superfund (IKMHSS) site. Measurements of horizontal dust flux following phytoremediation reveals that vegetated plots with 16% and 32% canopy cover enabled an average dust deposition of 371.7 and 606.1 g m-2 y-1, respectively, in comparison to the control treatment which emitted dust at an average rate of 2323 g m-2 y-1. Horizontal dust flux and dust emissions from the vegetated field plots are comparable to emission rates in undisturbed grasslands. Further, phytoremediation was effective at reducing the concentration of fine particulates, including PM1, PM2.5, and PM4, which represent the airborne particulates with the greatest health risks and the greatest potential for long-distance transport. This study demonstrates that phytoremediation can substantially decrease dust emissions as well as the transport of windblown contaminants from mine tailings.

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Figures

Figure 1.
Figure 1.
Illustration of various mining activities, particle sizes generated, the temporal scale at which particles could be generated or transported and the two dust monitoring approaches (DustTrak and passive sampling) used in this study.
Figure 2.
Figure 2.
Effect of treatment on the annual average of the differential horizontal dust flux. Negative numbers indicate there was a net deposition of dust into the study area while positive numbers indicate that there was a net emission of dust from the study area. Windrose insert describes predominant wind direction from May 2011 to May 2012 (WS= wind speed).
Figure 3.
Figure 3.
Effect of treatment on annual average of the differential horizontal dust flux at 0.06, 0.18, 0.25, and 0.5 and 1.0 m above the mine tailings surface. Negative numbers indicate there was a net deposition (Dep) of dust into the study area while positive numbers indicate that there was a net emission (Em) of dust from the study area.
Figure 4.
Figure 4.
Effect of treatment on the annual average of the horizontal elemental flux associated with dust particles. Negative numbers indicate there was a net deposition of dust into the study area while positive numbers indicate that there was a net emission of dust from the study area. Metals analyzed were arsenic (As), lead (Pb), copper (Cu) and cadmium (Cd).
Figure 5.
Figure 5.
Effect of treatment on dust flux for different particle sizes. DustTrak data were analyzed by averaging data from 15 min intervals of a four hour measurement time. Values presented are the average ± standard deviation (n=16); negative numbers indicate there was a net deposition of particle matter into the study area while positive numbers indicate that there was a net emission of particle matter. Windrose inserts show predominant wind direction (WS= wind speed). Rates of dust emission and/or deposition were estimated for each of the study plots by DustTrak Flux out – Flux in. Wind roses measuring day average wind direction (vectors) and speed (m s−1) for May 24th, 2011 and June 6th, 2011. Differences show the variability of weather conditions in different seasons.

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