Multicomponent reactive transport modeling of acid neutralization reactions in mine tailings

2004 ◽  
Vol 40 (11) ◽  
Author(s):  
Jasna Jurjovec ◽  
David W. Blowes ◽  
Carol J. Ptacek ◽  
K. Ulrich Mayer
Keyword(s):  
Mine Tailings ◽  
Reactive Transport ◽  
Transport Modeling ◽  
Reactive Transport Modeling ◽  
Acid Neutralization ◽  
Multicomponent Reactive Transport

Multicomponent reactive transport modeling of uranium bioremediation field experiments

2009 ◽  
Vol 73 (20) ◽  
pp. 6029-6051 ◽  
Author(s):  
Yilin Fang ◽  
Steven B. Yabusaki ◽  
Stan J. Morrison ◽  
James P. Amonette ◽  
Philip E. Long
Keyword(s):  
Reactive Transport ◽  
Field Experiments ◽  
Transport Modeling ◽  
Reactive Transport Modeling ◽  
Multicomponent Reactive Transport

Reactive Transport Modeling of Natural Carbon Sequestration in Ultramafic Mine Tailings

2012 ◽  
Vol 11 (2) ◽  
pp. vzj2011.0053 ◽  
Author(s):  
S.A. Bea ◽  
S.A. Wilson ◽  
K.U. Mayer ◽  
G.M. Dipple ◽  
I.M. Power ◽  
...  
Keyword(s):  
Carbon Sequestration ◽  
Mine Tailings ◽  
Reactive Transport ◽  
Transport Modeling ◽  
Reactive Transport Modeling ◽  
Natural Carbon

scholarly journals Probability of Non-Exceedance of Arsenic Concentration in Groundwater Estimated Using Stochastic Multicomponent Reactive Transport Modeling

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3086
Author(s):  
Nico Dalla Libera ◽  
Daniele Pedretti ◽  
Giulia Casiraghi ◽  
Ábel Markó ◽  
Leonardo Piccinini ◽  
...  
Keyword(s):  
Reactive Transport ◽  
Volume Fraction ◽  
Transport Model ◽  
Initial Conditions ◽  
Critical Concentration ◽  
Arsenic Concentration ◽  
Transport Modeling ◽  
Reactive Transport Modeling ◽  
Iron Hydroxides ◽  
Multicomponent Reactive Transport

Stochastic multicomponent reactive transport modeling is a powerful approach to quantify the probability of non-exceedance (PNE) of arsenic (As) critical concentration thresholds in groundwater. The approach is applied to a well-characterized shallow alluvial aquifer near Venice, Italy. Here, As mobility depends primarily on rainfall-controlled redox-dependent precipitation-dissolution of iron hydroxides. A Monte-Carlo analysis based on a calibrated three-dimensional flow and transport model targeted the geochemical initial conditions as the main source of uncertainty of As concentrations in the studied aquifer. It was found that, during 115 simulated days, the fraction of the entire aquifer volume with As > 10 μgL−1 decreased on average from ~43% to ~39% and the average As concentration from ~32 μgL−1 to ~27 μgL−1. Meanwhile, PNE increased from 55% to 60% when 10 μgL−1 was set as target threshold, and from 71% to 78% for 50 μgL−1. The time dependence of As attenuation can be ascribed to the increase of oxidizing conditions during rainfall-dependent aquifer recharge, which causes As sorption on precipitating iron hydroxides. When computing the same statistics for the shallowest 6 m, As attenuation was even more evident. The volume fraction of aquifer with As > 10μgL−1 dropped from 40% to 28% and the average As concentration from 31 μgL−1 to 20 μgL−1, whereas PNE increased from 58% to 70% for As < 10 μgL−1 and from 71% to 86% for As < 50 μgL−1. Thus, the wells screen depth in the aquifer can be a critical aspect when estimating As risk, owing to the depth-dependent relative change in redox conditions during rainfall events.

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