Arsenic mobilization in an oxidizing alkaline groundwater: Experimental studies, comparison and optimization of geochemical modeling parameters

被引:3
|
作者
Hafeznezami, Saeedreza [1 ]
Lam, Jacquelyn R. [1 ]
Xiang, Yang [2 ]
Reynolds, Matthew D. [3 ]
Davis, James A. [4 ]
Lin, Tiffany [1 ]
Jay, Jennifer A. [1 ]
机构
[1] Univ Calif Los Angeles, Dept Civil & Environm Engn, 5732 Boelter Hall,Box 951593, Los Angeles, CA 90095 USA
[2] Xiamen Univ, State Key Lab Marine Environm Sci, 422 Siming S Rd, Xiamen 361006, Fujian, Peoples R China
[3] Drumlin Environm LLC, 97 India St, Portland, ME 04101 USA
[4] Lawrence Berkeley Natl Lab, Div Earth Sci, 1 Cyclotron Rd, Berkeley, CA 94720 USA
基金
美国国家科学基金会;
关键词
Arsenic; Mobilization; Groundwater contamination; Remediation; Geochemical modeling; Surface complexation modeling; Acidification; Adsorption; Natural attenuation; PHREEQC; FITEQL; SURFACE COMPLEXATION; ORGANIC-MATTER; ALLUVIAL AQUIFERS; WEST-BENGAL; NEW-ENGLAND; ADSORPTION; IRON; WATER; FERRIHYDRITE; BANGLADESH;
D O I
10.1016/j.apgeochem.2016.07.011
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Arsenic (As) mobilization and contamination of groundwater affects millions of people worldwide. Progress in developing effective in-situ remediation schemes requires the incorporation of data from laboratory experiments and field samples into calibrated geochemical models. In an oxidizing aquifer where leaching of high pH industrial waste from unlined surface impoundments led to mobilization of naturally occurring As up to 2 mg L-1, sequential extractions of solid phase As as well as, batch sediment microcosm experiments were conducted to understand As partitioning and solid-phase sorptive and buffering capacity. These data were combined with field data to create a series of geochemical models of the system with modeling programs PHREEQC and FITEQL. Different surface complexation modeling approaches, including component additivity (CA), generalized composite (GC), and a hybrid method were developed, compared and fitted to data from batch acidification experiments to simulate potential remediation scenarios. Several parameters strongly influence the concentration of dissolved As including pH, presence of competing ions (particularly phosphate) and the number of available sorption sites on the aquifer solids. Lowering the pH of groundwater to 7 was found to have a variable, but limited impact (<63%) on decreasing the concentration of dissolved As. The models indicate that in addition to lowering pH, decreasing the concentration of dissolved phosphate and/or increasing the number of available sorption sites could significantly decrease the As solubility to levels below 10 mu g L-1. The hybrid and GC modeling results fit the experimental data well (NRMSE<10%) with reasonable effort and can be implemented in further studies for validation. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:97 / 112
页数:16
相关论文
共 50 条
  • [42] Geogenic manganese and iron in groundwater of Southeast Asia and Bangladesh - Machine learning spatial prediction modeling and comparison with arsenic
    Podgorski, Joel
    Araya, Dahyann
    Berg, Michael
    SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 833
  • [43] Treatment of Arsenic Contaminated Groundwater Using Calcium Impregnated Granular Activated Carbon in a Batch Reactor: Optimization of Process Parameters
    Mondal, Prasenjit
    Mohanty, Bikash
    Balomajumder, Chandrajit
    CLEAN-SOIL AIR WATER, 2010, 38 (02) : 129 - 139
  • [44] Experimental studies and modeling of a 250-kW alkaline water electrolyzer for hydrogen production
    Ren, Zhibo
    Wang, Jinyi
    Yu, Zhiyong
    Zhang, Chang
    Gao, Shiwang
    Wang, Pengjie
    JOURNAL OF POWER SOURCES, 2022, 544
  • [45] Removal of arsenic by metal organic framework/chitosan/carbon nanocomposites: Modeling, optimization, and adsorption studies
    Akha, Nastaran Zare
    Salehi, Samira
    Anbia, Mansoor
    INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES, 2022, 208 : 794 - 808
  • [46] Modeling and optimization of lime-based stabilization in high alkaline arsenic-bearing sludges with a central composite design
    Lei, Jie
    Peng, Bing
    Min, Xiaobo
    Liang, Yanjie
    You, Yang
    Chai, Liyuan
    JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH PART A-TOXIC/HAZARDOUS SUBSTANCES & ENVIRONMENTAL ENGINEERING, 2017, 52 (05): : 449 - 458
  • [47] Kinetic modeling and optimization of parameters for biomass pyrolysis: A comparison of different lignocellulosic biomass
    Mahmood, Hamayoun
    Ramzan, Naveed
    Shakeel, Ahmad
    Moniruzzaman, Muhammad
    Iqbal, Tanveer
    Kazmi, Mohsin Ali
    Sulaiman, Muhammad
    ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS, 2019, 41 (14) : 1690 - 1700
  • [48] Optimizing arsenic removal from groundwater using continuous flow electrocoagulation with iron and aluminum electrodes: An experimental and modeling approach
    Tenodi, Kristiana Zrnic
    Tenodi, Slaven
    Nikic, Jasmina
    Mohora, Emilijan
    Agbaba, Jasmina
    Roncevic, Srdan
    JOURNAL OF WATER PROCESS ENGINEERING, 2024, 66
  • [49] Optimization of experimental design parameters for high-throughput chromatin immunoprecipitation studies
    Ponzielli, Romina
    Boutros, Paul C.
    Katz, Sigal
    Stojanova, Angelina
    Hanley, Adam P.
    Khosravi, Fereshteh
    Bros, Christina
    Jurisica, Igor
    Penn, Linda Z.
    NUCLEIC ACIDS RESEARCH, 2008, 36 (21)
  • [50] Solar-driven flash vaporization membrane distillation for arsenic removal from groundwater: Experimental investigation and analysis of performance parameters
    Manna, Ajay K.
    Pal, Parimal
    CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION, 2016, 99 : 51 - 57